Global Tuna Demand and Fisheries Dynamics:
Economics of the Tuna Longline and
Tuna Purse-Seine Fisheries
in the Eastern Pacific Ocean
Chin-Hwa Jenny Sun
Professor
Institute of Applied Economics
National Taiwan Ocean University
[email protected]
and
Visiting Research Scholar (2009-2010)
Inter-American Tropical Tuna Commission
Abstract
This study includes the report and presentations given at the International Workshop on
Global Tuna Demand, Fisheries Dynamics and Management in the Eastern Pacific Ocean. The
Workshop, which took place in La Jolla, California, USA, on May 13-14, 2010, was hosted by the
Inter-American Tropical Tuna Commission (IATTC). It was funded by the Pacific Islands Fisheries
Science Center (PIFSC) as part of the Project Global Tuna Demand and Fisheries Dynamics:
Economics of the Tuna Longline and Tuna Purse-Seine Fisheries in the Eastern Pacific Ocean
The Workshop, which was coordinated by Chin-Hwa Jenny Sun, Mark N. Maunder, Minling
Pan, and Dale Squires, was organized by the Project, with the collaboration and financial and in-kind
support of: (i) the PIFSC and Southwest Fisheries Science Center (SWFSC), National Marine
Fisheries Service (NMFS), National Oceanic and Atmospheric Administration (NOAA), Department
of Commerce, United States of American; (ii) the IATTC; and (iii) other international and national
fisheries institutions involved in tuna fishing and fisheries research and management (including those
of the tuna fishing industry).
The objectives of the study were to identify the global tuna market structure and to estimate
the corresponding price flexibilities of sashimi and cannery-grade tuna products in the major global
markets. In addition, an evaluation of the economics of the tuna longline and tuna purse-seine
fisheries on bigeye tuna and yellowfin tuna in the eastern Pacific Ocean (EPO) is also provided to
discuss how to increase the economic value of tuna fishery while maintaining the spawning biomass
at a target level for the long-run sustainable plan.
Global Tuna Demand and Fisheries Dynamics in the EPO
The outcome of the project would facilitate market-based conservation and management
measures for the tuna longline and tuna purse-seine fisheries in area of concern to the IATTC (from
the west coast of the Americas to 150°W between 50°N and 50°S). Three tasks, which build on
current work, have been accomplished:
(i) Evaluated the economics of the tuna longline and tuna purse-seine in the EPO;
(ii) Estimated an inverse demand model of tuna raw material for canning in Thailand and for the
sashimi market in Tokyo, Japan;
(iii) Hosted an International Workshop on Global Tuna Demand, Fisheries Dynamics and
Fisheries Management in the Eastern Pacific Ocean.
Dr. Guillermo A. Compeán, Director of the IATTC, was invited to deliver the keynote
address, “Tuna Fleet Dynamics and Capacity Overview in EPO" for the Workshop and two
background discussion papers were prepared to circulate to all invited participants before the
Workshop. In addition, the invited experts of the major tuna purse-seine and longline fisheries in the
USA, Ecuador, France, Spain, Japan, the Republic of Korea, and Taiwan delivered a total of twenty
presentations, including seven country fleet dynamics reports and thirteen case studies. Summaries of
the presentations and the discussions carried out during the Workshop are also included in the report.
The views expressed in this workshop are those of the authors, and do not necessarily reflect
the views of IATTC. They were not participating as representatives of organizations, countries, or
neither sectors, nor they express the views of the hosting organizations.
The workshop convener would be very grateful for your comments on the executive
summary of the workshop, as these will form the basis of coupling of human and natural elements in
this complex system in order to fully understand the observed dynamics of resilience. Please feel free
to put it directly into the text and track changes while edit and reply to [email protected].
ii
Global Tuna Demand and Fisheries Dynamics in the EPO
Contents
Abstract
i
Acknowledgements
ii
LIST OF REPORT
Introduction
1
Task I.
5
Economics and Conservation: Increasing the Economic Value of the Eastern
Pacific Ocean Tropical Tuna
(Workshop Background Discussion Paper No. 1)
Task II. Inverse Demand Analysis of Tuna for the Canning Market in Thailand and
for the Sashimi Market in Tokyo, Japan
Task III. Executive Summary of International Workshop on Global Tuna Demand,
Fisheries Dynamics and Fisheries Management in the Eastern Pacific Ocean
1. Opening
28
51
51
2. Introduction of participants
51
3. Overview of the Workshop and its implementation
51
4. Summary and Discussion
52
4.1 Comments and Reply on the Discussion Paper No. 1
58
4.2 Policy Implications of the Estimation of Global Tuna Demand
62
5. Panel Discussion and Concluding Remarks
64
6. Adjournment
68
APPENDIX I
– Letter of Invitation
A-1
APPENDIX II – Programme
A-3
APPENDIX III – List of participants
A-8
APPENDIX IV – Background Discussion of Paper No. 2: Bioeconomic Modeling and
Management of the Western and Central Pacific Ocean Tuna Stocks
Harry Campbell, John Kennedy, and Chris Reid
A-11
APPENDIX V – Abstracts and Biographical Sketches of the Speakers
A-65
APPENDIX VI – “How to increase the economic value of tuna fishery while
A-84
maintaining the spawning biomass at a target level,” feature article,
Organization for the Promotion of Responsible Tuna Fisheries
Newsletter (http://oprt.or.jp/eng/wp-content/uploads/2011/03/OPRT29.pdf),
August, 2010.
APPENDIX VII – Meeting Agenda of Modelling Global Demand for Tuna,
A-86
CLIOTOP-IMBER Working Group 5, supported by the ANR-Project
MACROES and NOAA-NMFS, April 14-15, 2011, Nantes, France.
iii
Global Tuna Demand and Fisheries Dynamics in the EPO
LIST OF PRESENTATIONS
These presentations are available at workshop website http://www.fisheriesstockassessment.com/
TikiWiki/tiki-index.php?page=Global+Tuna+Demand+and+Fisheries+Dynamics. If there are
multiple authors, the speaker is indicated by "*".
P1. Tuna Fleet Dynamics and Capacity Overview in EPO
Guillermo A. Compeán
P2. Recent Development on Rights-based Management of Tuna Fishery: Summary
Report of the IATTC and World Bank Workshop in May 2008
Dale Squires
P3. World Trends of Tuna Industry - Recent Developments in Tuna Industry: Stocks,
Fishery, Management, Processing, Trade and Markets
(FAO Fisheries Technical Paper 543)
Peter M. Miyake*, Patrice Guillotreau, Chin-Hwa Sun, and Gaku Ishimura
P-1
P-7
P-17
P4. Japanese Distant Water Longline Fleet
Peter M. Miyake
P-27
P5. Tuna Longline Fleet Dynamics in U.S
Minling Pan
P-28
P6. Tuna Longline Fishery Dynamics in Taiwan
Chin-Hwa Jenny Sun
P-33
P7. Tuna Longline Fishery Dynamics in Korea
Yongil Jeon
P-36
P8. Tuna Purse-Seine Fishery Dynamics in France
Patrice Guillotreau*, Ramón Jiménez Toribio*, and Juan José García del Hoyo
P-40
P9. Tuna Purse-Seine Fishery Dynamics in Spain
Patrice Guillotreau*, Ramón Jiménez Toribio*, and Juan José García del Hoyo
P-44
P10. Global Tuna Cannery and Market Overview
Michael McGowan and Kevin McClain
P-50
P11. Tuna Cannery and Market Overview in Ecuador
Iván Prieto
P-54
iv
Global Tuna Demand and Fisheries Dynamics in the EPO
P12. Status of Bigeye Tuna in the Eastern Pacific Ocean in 2008 and Outlook for the
Future
Alexandre Aires-da-Silva* and Mark N. Maunder
P-60
P13. Status of Yellowfin and Skipjack Tuna in the Eastern Pacific Ocean in 2008 and
Outlook for the Future
Mark N. Maunder* and Alexandre Aires-da-Silva
P-67
P14. Economics and Conservation: Increasing the Economic Value of the Eastern
Pacific Ocean Tropical Tuna Fishery
Chin-Hwa (Jenny) Sun*, Mark N. Maunder, Alexandre Aires-da-Silva, and
William H. Bayliff
P-75
P-85
Commentator: Christopher D. Stone
P15. Fishing Capacity and Productivity Growth in the EPO Tuna Purse Seine Fishery
Eric Janofsky*, James Kirkley, Dale Squires, Chin-Hwa Jenny Sun,
and Yongil Jeon
P-88
P16. Global Integration of European Tuna Markets
Ramón Jiménez-Toribio, Patrice Guillotreau*, and R. Mongruel
P-99
P17. A Demand Analysis of the Spanish Canned Tuna Market
Juan José García del Hoyo, Ramón Jiménez-Toribio*, and Patrice Guillotreau
P-104
P18. Price Linkage of Global Tuna Cannery Market
Yongil Jeon* and Dale Squires
P-113
P19. Tuna Price in Response to Changes of Market Structure and Ecosystem Conditions:
Price Linkage between Hawaii and Japanese Tuna Sashimi Markets
Minling Pan*, Chin-Hwa Jenny Sun, and Dale Squires
P-120
P20. Inverse Demand Analysis of the Tuna Sashimi Market in Tokyo, Japan: An
Application of the Rotterdam Inverse Demand System
Chin-Hwa Jenny Sun* and Fu-Sung Chiang
P-128
v
Global Tuna Demand and Fisheries Dynamics in the EPO
Acknowledgements
The organization of the Workshop, the outcome of which is presented in this report, would
not have been possible without the PIFSC’s Project on the Global Tuna Inverse Demand Estimation
and the Economics of the Tuna Longline and Tuna Purse-Seine Fisheries in the Eastern Pacific
Ocean.
The Workshop was organized by the Project, with financial and in-kind support of: (i) the
IATTC; (ii) PIFSC, and the SWFSC and (iii) the other international and national fisheries institutions
involved in tuna fishing and fisheries research and management (including those of the tuna fishing
industry).
The IATTC contributed to the preparatory technical work for the Workshop, including the
keynote address and the stock assessments of bigeye, yellowfin and skipjack tuna in the EPO that
were documented in the list of presentations given at the Workshop. The invited speakers and
independent panels were composed of experts affiliated with the tuna agencies and programs and
some other institutions involved in tuna fishing and fisheries research and management to foster the
collaboration with these institutions at the time of holding the Workshop are listed below.














Dr. Guillermo A. Compeán, Director, IATTC.
Dr. Alexandre Aires-da-Silva, Senior Scientist, IATTC.
Dr. Theodore Groves, Professor and Director, Center for Environmental Economics,
Department of Economics, University of California, San Diego.
Dr. Patrice Guillotreau, Researcher in Fisheries Economics, Institut de Recherche pour le
Développement (IRD) and University of Nantes, France.
Dr. Yongil Jeon, Associate Professor, School of Economics SungKyunKwan University,
Republic of Korea.
Dr. Ramón Jiménez-Toribio, Universidad de Huelva, España.
Dr. Mark N. Maunder, Head of the Stock Assessment Program, IATTC.
Dr. Makoto Peter Miyake, Associate Researcher, National Research Institute of Far Seas
Fisheries, Japan.
Dr. Minling Pan, PIFSC, NMFS
Ivan Arturo Prieto, Economics Advisor, Cámara Nacional de Pesquería, Ecuador
Kevin McClain, Bumble Bee Foods, LLC.
Dr. Dale Squires, SWFSC, NMFS.
Dr. Christopher D. Stone, J. Thomas McCarthy Trustee Chair in Law, Gould School of Law,
University of Southern California.
Chin-Hwa Jenny Sun, Professor, National Taiwan Ocean University; Visiting Research
Scholar (2009-2010), IATTC.
The Project Investigator is grateful to the institutions and persons listed above, the authors of
the papers included as part of these Proceedings, and all the participants in the Workshop for their
collaboration and support of the Workshop. Thanks to the institutes to finance the participation of
their experts at the Workshop. Without their collaboration and support, it would not have been
possible to produce the report. A special thanks is extended to the staff of the SWFSC in providing
in-kind support, especially the meeting venue and the video conference equipment for presentations
vi
Global Tuna Demand and Fisheries Dynamics in the EPO
delivered remotely from France and Spain. Furthermore, a financial support was provided by the
International Seafood Sustainability Foundation (ISSF) in the form of funds for a welcome dinner,
coffee breaks, and lunches for the expanded number of invited participants.
The designations employed and the presentation of material in this information product do
not imply the expression of any opinion whatsoever on the part of the IATTC concerning the legal or
developmental status of any country, territory, city, or area or of its authorities, or concerning the
delimitation of its frontiers or boundaries. The mention of specific companies or products of
manufacturers, whether or not these have been patented, does not imply that these have been
endorsed or recommended by IATTC in preference to others of a similar nature that are not
mentioned.
Group photo of all participants at Workshop in La Jolla, CA May 13-14, 2010
vii
Global Tuna Demand and the Fisheries Dynamics in the EPO
Introduction
This report includes the project report and presentation given at the International Workshop
on Global Tuna Demand, Fisheries Dynamics and Fisheries Management in the Eastern Pacific
Ocean. The Workshop was hosted by the Inter-American Tropical Tuna Commission (IATTC) at the
Southwest Fisheries Science Center (SWFSC) Conference Room, located at 3333 North Torrey
Pines Court, La Jolla, California, United States of America, from 13 to 14 May 2010 as an activity
funded by the Pacific Islands Fisheries Science Center (PIFSC), the National Marine Fishery Service
(NMFS), National Oceanic and Atmospheric Administration (NOAA), Department of Commerce,
United States of American on the Project “Global Tuna Inverse Demand Estimation and the
Economics of the Tuna Longline and Tuna Purse-Seine Fisheries in the Eastern Pacific Ocean”.
Tunas support some of the most important fisheries in the world. Because of the high demand
and value of tunas, knowledge of the global demand and price responses is required to better
understand and predict the impact of international tuna conservation and management measures on
the economics of the global tuna fishery. The project focuses on both economic and biological
system research in order to manage the use of highly-migratory tuna resources through ecosystembased management. In order to understand and predict the impact of an international tuna
conservation and management measure on the economics of a global tuna fishery, the project aims to
analyze the global tuna demand and the inverse demand models are specified to estimate the
corresponding price flexibilities for the major global tuna cannery markets in Thailand and the major
tuna sashimi market in Japan.
IATTC staff has cooperating with personnel from the U.S. NMFS in the organization of the
Workshop to focus on both economic and biological system research to enhance the conservation
and management of highly-migratory tuna resources through incentive-based management. The
Workshop was coordinated by Chin-Hwa Jenny Sun, Mark N. Maunder, Minling Pan, and Dale
Squires and was organized by the Project in collaboration and with financial and in-kind support of:
(i) the IATTC; (ii) the PIFSC and the SWFSC; and (iii) the other international and national fisheries
institutions involved in tuna fishing and fisheries research and management (including those of the
tuna fishing industry) to ensure the participated papers are of high quality and relevant to the theme.
The IATTC, an international scientific organization established in 1949, is responsible for the
conservation and management of tunas and other species taken by tuna-fishing vessels in the EPO. It
is composed of 20 members1 and 2 Cooperating Non Parties2. The agreement area for the IATTC is
the EPO, generally taken to be from the coastline of the Americas to 150°W longitude between 50°N
and 50°S, and is so defined in the new “Antigua Convention,” which entered into force in August
2010.
The goal of the Workshop is to identify the most promising areas of inquiry and action and
address priorities for further research by bringing together world tuna experts from diverse fields of
economics, international affairs, biology, policy, and the global tuna industry. The project is
1
Belize, Ecuador , Japan, Peru, Canada, El Salvador, Korea, Chinese Taipei, China, European Union, Mexico, United
States, Colombia, France, Nicaragua, Vanuatu, Costa Rica, Guatemala, Panama, and Venezuela.
2
Cook Islands and Kiribati.
1
Global Tuna Demand and the Fisheries Dynamics in the EPO
improved by scientific advice from Workshop participants to explore how to evaluate the benefits of
a possible rights-based management measure for bigeye tuna that will ensure the recovery of the
biomass in order to support the IATTC’s mission in developing a long run sustainable plan.
The outcomes of the project would communicate to NOAA/NMFS, PIFSC, the SWFSC, and
the interested public to facilitate the market-based management. The result of the Workshop is
essential not just to the US, but also in the international arena to serve as regional and national
outreach efforts to bring together key industry players and policy makers from the coastal state
members of Colombia, Costa Rica, Ecuador, El Salvador, Guatemala, Mexico, Nicaragua, Panama,
Peru, and the United States. In addition, this Workshop has also invited the NGOs, such as the
International Seafood Sustainability Foundation (ISSF) and the World Wildlife Fund (WWF) to
focus on ensuring that tuna populations are protected from overfishing, to facilitate work with local
communities to develop well-managed policy, and create new economic incentives for a sustainable
future to benefit the global ecosystems and the people who depend on them.
The Workshop serves as a follow-up in addressing the right-based conservation and
management measure of the tuna longline and tuna purse-seine fisheries in EPO “Workshop on
Rights-based Management and Buybacks in International Tuna Fisheries”, which was sponsored by
the NOAA/NMFS and World Bank, in La Jolla, CA during May 5-9, 2008. The IATTC has the
experience to address the challenge of creating an international rights-based regime for the purseseine fishery operating in the EPO and to disseminate the findings of the Workshop to the general
public, and stakeholders (for example see http://www.iattc.org/PDFFiles2/Rights-basedmanagement-report.pdf). Wide dissemination will improve public understanding and public
involvement in stewardship of tuna resources.
While biological and economic elements are essential parts of management, it is also helpful
to have social science research involved in the international scientific organization like IATTC.
Recognizing the importance of impacts from human activities/uses upon marine living resources, this
Workshop had invited a keynote address, “Tuna Fleet Dynamics and Capacity Overview in EPO,”
delivered by Dr. Guillermo A. Compeán, Director of the IATTC. In addition, 12 invited experts and
2 external discussants from the field of EPO tuna stock assessment, the global market situation,
demand modeling, and industry development of the major tuna purse-seine and longline fisheries in
the USA, Ecuador, France, Spain, Japan, the Republic of Korea, and Taiwan delivered a total of
seven country fleet dynamics reports and thirteen case studies presentations. The report documents
presentations made and the discussions carried out during the Workshop; their recommendations are
also included in the report. In addition, the IATTC’s international involvement and expertise brought
in by this conference has encouraged and benefited research and fisheries management and
collaborations in the Pacific Ocean, where the pelagic fisheries are the main fisheries and fisheries
resources are shared by many countries.
This project has also invited bigeye and yellowfin tuna stock assessment scientists of the
IATTC, Dr. Mark N. Maunder and Dr. Alexandre Aires-da-Silva, to utilize the IATTC Stock
Synthesis stock assessment model to simulate the effect of various vessel reduction programs on the
spawning biomass of bigeye and yellowfin stocks in the EPO. Based upon the IATTC's stock
assessments, Task I simulates the effects of various fishing management policies on the spawning
biomass of bigeye and yellowfin stocks in the EPO, which served as one of the background
discussion paper to evaluate the effects of right-based management in the EPO. An extensive
simulation analysis of the economics of the tuna longline and tuna purse-seine fisheries would be
provided during the Workshop to identify possible management strategies to facilitate negotiations
among IATTC member countries. The Workshop had facilitated the engagement in new
2
Global Tuna Demand and the Fisheries Dynamics in the EPO
technological and scientific exchange with our domestic and international partners to protect, restore,
and manage marine resources within and beyond the Exclusive Economic Zones (EEZs) of the
nations involved.
The present Workshop aims at providing a comprehensive state-of-the-art analysis and
discussion of the global demand for tuna. The bio-economic dimensions of the tuna industry will be
covered by various specialists within a two-day session. The communications and discussion, along
with additional commissioned papers, were published on the Workshop’s website after the
conference. A recommendation will be provided to design a rights-based management decision rule
that will ensure the recovery of the tuna biomass that incorporates the market response information,
to support and/or compensations to reach the best mix of tuna purse-seine and longline gears and to
utilize the highly-migratory tuna resources in a biologically sustainable and economically viable way.
The focus of the Workshop is on discussions, allowing ample time for each presentation,
followed by extensive discussions. Due to the attention the Workshop received and the IATTC’s
international involvement and expertise brought in by our Workshop coordinators, the number of
participants3 for our Workshop has expanded from 15 to 40. In serving the extended participants, a
Workshop website 4 , is constructed by the Project Investigator to facilitate and administrate the
Workshop and to accomplish the Workshop objectives to disseminate the findings of the Workshop
to improve public understanding and public involvement in stewardship of tuna resources in the EPO.
Two background discussion papers were prepared to circulate to all invited participants before the
Workshop, and four sub-sessions are envisaged, with a total 20 presentations as examples of related
topics. Presentations and discussions of the focus questions during the Workshop are also captured in
the Executive Summary of the Workshop. A full set of information about the invitation letter, an
outline of the Workshop program, the participant list, the second discussion paper, and presentation
abstracts are indicated as Appendix I, II, III and IV.
In summary, three tasks, which build on current work of the project, have been
accomplished. The report is constructed to include these as follows:
Task I.
Economics and Conservation Are not Necessary Incompatible: Increasing the Economic
Value of the Eastern Pacific Ocean Tropical Tuna Fishery
Task II.
Inverse Demand Analysis of the Tuna Raw Material for Canning in Thailand and the
Sashimi Market in Tokyo, Japan;
Task III. Report of International Workshop on Global Tuna Demand, Fisheries Dynamics and
Fisheries Management in the Eastern Pacific Ocean;
First, a background discussion paper for the Workshop has also been finished and presented
by Dr. Sun and IATTC scientists to evaluate the economics of longline and purse seine fishing in
order to increase the economic value of the eastern Pacific Ocean tropical tuna fishery. It has been
shown that the constrained management measures to reduce both longline and purse-seine fishing
effort proportionally would not maximize the total values of the catches in the EPO. Second, a
written technical report on the inverse demand analysis for the tuna raw material for the canning
market in Thailand and for the tuna sashimi market in Tokyo will form the basis of a journal article.
3
4
A special thanks to the International Seafood Sustainability Foundation (ISSF) to brought in
funding to add the possibility to host a welcome dinner, coffee breaks, and lunches for about 40
participants.
http://www.fisheriesstockassessment.com/TikiWiki/tiki-index.php?page=Global+Tuna+Demand+and+Fisheries+Dynamics
3
Global Tuna Demand and the Fisheries Dynamics in the EPO
Last, a user-friendly report is prepared for distribution to the U.S. Department of State, NMFS Office
of International Affairs, the Inter-American Tropical Tuna Commission, the International
Commission for the Conservation of Atlantic Tunas, the Western and Central Pacific Fisheries
Management Commission, the Indian Ocean Tuna Commission, the International Sustainable
Seafood Foundation (the global tuna industry’s new NGO for sustainable tuna fisheries), and other
interested parties.
To ensure the result of the Workshop will be essential in promoting regional and national
outreach efforts to bring together key industry players and policy makers from Ecuador, Mexico,
France, Spain, Japan, Korea, Taiwan and the United States, the outcomes of the project has been
communicated to international fishery economics community, and the interested public. For example,
Dr. Sun had presented a summary of the findings of the Workshop in the 2010 biannual conference
of International Institute of Fishery Economics and Trade (IIFET) in Montpellier, July 13-16, 2010,
such as indicated in http://www.colloque.ird.fr/iifet-2010/.
The Organization for the Promotion of Responsible Tuna Fisheries (OPRT) had published a
feature article and distributed to all over the world including FAO, United Nations about “How to
increase the economic value of tuna fishery while maintaining the spawning biomass at a target level,”
based on the findings of the Task I in our workshop. The front page news of OPRT Newsletter
(http://oprt.or.jp/eng/wp-content/uploads/2011/03/OPRT29.pdf) in August, 2010 is included in
Appendix VII. In addition, the findings of the “Inverse Demand Analysis of Tuna for the Canning
Market in Thailand and for the Sashimi Market in Tokyo, Japan” had also been invited to present in
the International Workshop on Modeling Global Demand for Tuna, CLIOTOP-IMBER Working
Group 5, supported by the ANR-Project MACROES and NOAA-NMFS, in April 14-15, 2011,
Nantes, France.
Thanks to IATTC for hosting the Workshop and thanks to all the participants for this had
been a fruitful Workshop that gave us so many different views on this important subject. There are
many more scientific issues have been identified would be need to explore in the future, for example,
a spatial distribution stock assessment model would be needed to take into account the probability
that the bigeye tuna not caught by a purse-seiner, would get caught by a longliner. Therefore, as the
effect of climate change might also change the distribution of the bigeye and yellowfin tuna, that
might create tension among different countries. The focus of future research would be how to
evaluate the joint production issue and how to allocate the fishing rights in a political economy
context, in order to help clarify what to do about management.
4
Task I: Economics and Conservation
Global Tuna Demand and Fisheries Dynamics in the EPO
Task I
Economics and Conservation:
Increasing the Economic Value of the Eastern
Pacific Ocean Tropical Tuna Fishery
Chin-Hwa Sun1, Mark N. Maunder2, Alexandre Aires-da-Silva3, and William H. Bayliff3
Abstract
Yellowfin and bigeye tuna in the eastern Pacific Ocean (EPO) are not managed
optimally with respect to their economic value. Both species are caught at sizes too small
to take full advantage of their individual growth and the higher prices obtained for large
fish in the sashimi market. Large bigeye and yellowfin caught in the longline fishery are
utilized as sashimi, while almost all of the smaller bigeye, yellowfin, and skipjack caught
in the purse-seine fisheries are canned. The economic and biological trade-offs that might
be considered are evaluated to see if the purse-seine and longline fisheries could be
managed in such a way that the economic value would be increased while the spawning
biomasses of the two tuna species were maintained at target levels.
It is assumed that if the catches of small bigeye and yellowfin were reduced
anywhere in the EPO, the gains to the biomass of those species due to growth would
exceed the losses to it due to natural mortality and that this would increase the
availability of large bigeye and yellowfin to the longline fishery operating anywhere in
the EPO. This would, in turn, increase the total value of catches of those species. In this
case, it is further assumed that the purse-seine and longline fisheries could be managed in
such a way that the spawning biomasses of the two species were maintained at a target
levels.
Three analyses are conducted to evaluate the economic and biological tradeoffs of
different levels of purse-seine and longline fishing effort. The first evaluates the different
combinations of effort that could produce the target biomass level. The second evaluates
combinations of effort that optimize equilibrium (long-term) catch and economic value.
The third evaluates the dynamic (short-term) effect of different combinations of effort.
The analyses are based on the stock assessment models for yellowfin and bigeye tuna in
2009 and recent average catch levels for a third species, skipjack tuna, which is rarely
1
Professor, Institute of Applied Economics, National Taiwan Ocean University, [email protected]; Visiting
Scientist, Inter-American Tropical Tuna Commission, 2009-2010.
2
Head of the Stock Assessment Program, Inter-American Tropical Tuna Commission.
3
Scientist, Inter-American Tropical Tuna Commission.
5
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
caught by longlin gear. The total economic value of the catch is determined from the
landings value for purse-seine- and longline-caught tuna of each species.
In conclusion, several possible methods of implementing management that may
address the social and equity issues are also discussed. By taking into account the
conflicts of interest among different countries and fishing gears that utilize the tuna
resources, it is imperative that socio-economic and ecological considerations are
incorporated to establish a cooperative scheme to create incentives to purse-seine
fishermen to reduce their catches of juvenile bigeye and yellowfin tuna under a tradable
rights-based management scheme. The economics and conservation are not necessary
incompatible and details of such a management system would have to be worked out to
address the complexities of the fishery and the society that depends on it, but the potential
benefits and the possibility of implementing such a system should not be ignored.
Keywords: tradable rights-based management, eastern Pacific Ocean, yellowfin tuna,
bigeye tuna, skipjack tuna, tuna purse-seine fishery, tuna longline fishery
INTRODUCTION
The fishery for tropical tunas in the eastern Pacific Ocean (EPO) is directed
principally at three species, yellowfin tuna, Thunnus albacares, bigeye tuna, T. obesus,
and skipjack tuna, Katsuwonus pelamis. Yellowfin and bigeye are not managed optimally
with respect to either catch in weight of fish or economic value of the catch. Both
yellowfin and bigeye tuna are caught at sizes too small to take full advantage of the
growth of the individual fish or of the higher prices obtained for large fish in the sashimi
market.
Most of the catches are taken by two types of gear, purse-seine and longline.
Smaller bigeye, yellowfin, and skipjack destined for the canned tuna market are caught in
the purse-seine fisheries, while large bigeye and yellowfin destined for the sashimi
market are caught in the longline fishery. Optimizing catches and revenue, therefore,
requires an understanding of both economic and biological processes to evaluate the
tradeoffs among different management actions. Likewise, the definition of overfishing
with respect to either catch in weight of fish or economic value is more complicated than
the simplistic reference points commonly used for fisheries management.
A stock of fish is overfished if its abundance is reduced by fishing to the extent that
it cannot produce the maximum catches (or the maximum economic value of the catches)
on a sustained basis.
Production of maximum catches (maximum sustainable physical yield; MSPY) will
be considered first. Whether overfishing (or underfishing) occurs depends on the size of
fish caught and the amount of effort that is deployed. There are two types of overfishing,
―growth overfishing‖ and ―recruitment overfishing.‖ The biomass of a cohort of fish (a
6
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
group of fish hatched at about the same time) increases when the fish are relatively young
because the gains in weight to it due to growth exceed the losses in weight to it due to
natural mortality. Eventually, as the fish grow older, the gains due to growth and the
losses due to natural mortality are equal, at which point the fish are said to have reached
the ―critical size.‖ After that the gains due to growth are exceeded by the losses due to
natural mortality, and the biomass decreases. If substantial amounts of smaller, younger
fish are caught, growth overfishing occurs because greater catches could be realized if the
biomass were permitted to increase. Growth overfishing could occur because the fishing
gear selects fish that are too small or because the fishing mortality is so high using a gear
that selects a wide range of sizes that fish are caught at a small size. Recruitment
overfishing occurs when the abundance of mature fish is reduced so much by fishing that
the recruitment of young fish is reduced.
We continue with the goal of MSPY in weight of the catch of fish. If more than one
type of gear is employed in a fishery, different sizes of fish are probably caught by each,
and the total weight of fish caught can be maximized by maximizing the use of the type
of gear that catches fish that are close of the critical size and minimizing the use of the
type of gear that catches younger, smaller fish. At the same time, the managers of the
fishery must ensure that the fishing mortality does not get too high to avoid growth or
recruitment overfishing.
We turn now to the goal of maximum sustainable economic yield (MSEY) in value
of the catch of fish. In this case, the ―critical value,‖ rather than the critical size, is of
interest, and the goal is to maximize the use of the type of gear that catches the most
valuable fish and to minimize the use of the type of gear that catches the least valuable
fish. The value of a fish is not necessarily proportional to its weight, so a management
scheme that maximizes the weight of the catch would not necessarily maximize its value.
Purse-seiners make three types of sets, sets on tunas associated with dolphins, sets
on tunas associated with floating objects, and sets on tunas in unassociated schools. In
general, sets on tunas associated with dolphins catch large yellowfin, and sets on floating
objects and on unassociated schools catch skipjack and small bigeye and yellowfin.
Longliners catch large yellowfin and large bigeye. The purse-seine fishery on tunas
associated with floating objects expanded rapidly starting in the early 1990’s, and this has
had a substantial impact on the catches of skipjack and bigeye tuna.
The assessment of tropical tunas in the EPO is carried out by the staff of the InterAmerican Tropical Tuna Commission (IATTC). It has been shown that growth
overfishing occurs for both bigeye and yellowfin tuna, but it is uncertain whether
recruitment overfishing of either species is occurring. In particular, the expansion of the
purses-seine fishery on floating objects in the early 1990’s has caused growth overfishing
of bigeye tuna due to high exploitation rates and the small size of fish selected by the
fishery.
The IATTC has the mandate to manage stocks at levels that will support MSPYs.
Under the allocation of effort in 2008, MSPY for bigeye occurs at a spawning biomass
level that is 19% of the unexploited level. The current IATTC resolution, recommends
reducing both the longline and purse-seine fishing effort proportionally by 20.5% during
7
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
2009-2011. Given the different sizes and landed values of tuna caught by the two fishing
gears, it is unlikely that this approach would provide optimal catches in either weight or
economic value. It appears that the fishery could be better managed by curtailing purseseine fishing on tunas. However, the two fishing methods are conducted by vessels from
different nations and catch different species compositions, so social and equity issues
would need to be addressed.
Three analyses are conducted to evaluate the economic and biological tradeoffs of
different levels of purse-seine and longline fishing effort. The current stock assessments
for bigeye (Aires-da-Silva and Maunder, 2010) and yellowfin (Maunder and Aires-daSilva, 2010) tuna and the recent average catch levels for skipjack tuna are used to
evaluate the effect of various effort reduction programs of purse-seine and longline effort
on the equilibrium catch, spawning biomass, and economic value of tropical tunas in
EPO. The first evaluates combinations of effort that optimize equilibrium (long term)
catch and economic value. The second analysis evaluates the different combinations of
effort that could produce the target biomass level. The third evaluates the dynamic (short
term) effect of different combinations of effort. The economic value is determined from
the landings value for purse-seine and longline-caught tuna of each species.
METHODS
Biological model
The analyses are based on the IATTC’s stock assessments for bigeye (Aires-daSilva and Maunder, 2010) and yellowfin tuna (Maunder and Aires-da-Silva, 2010). The
assessments for these species are carried out using Stock Synthesis II (Methot, 2005),
which is age-structured and takes into account the different sizes of tuna caught by the
different fishing methods and set types.
No reliable assessment is available for skipjack tuna. Therefore, changes in
equilibrium catches for skipjack were assumed to be proportional to changes in purseseine equilibrium catches for yellowfin tuna. (The average annual skipjack catch for
2001-2007 was multiplied by the ratio of the equilibrium yellowfin purse-seine catch to
the equilibrium yellowfin purse-seine catch under the effort allocation in 2008.)
It is assumed that if the catches of small bigeye and yellowfin were reduced, the
gains to the biomass of those species due to growth would exceed the losses to it due to
natural mortality This would increase the availability of large bigeye and yellowfin to the
longline fishery, which, in turn, would increase the total catches of those species,
provided there was sufficient fishing effort by longliners. It is further assumed that bigeye
and yellowfin are well mixed within the EPO, in which case reductions in the catches of
small tunas anywhere in the EPO would be beneficial to longliners operating anywhere in
the EPO. It is further assumed that the purse-seine and longline fisheries could be
8
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
managed in such a way that the spawning biomasses of the two species were maintained
at optimum levels.
In all scenarios, the characteristics of the different purse-seine set types are
maintained separately, but the effort changes are the same for each set type. The effort for
longline and purse-seine are changed independently.
Economic value
The economic value was simply calculated by summing the ex-vessel prices
multiplied by the total landings for each of the three species and each gear. In the
dynamic calculations, the value is summed over all projected years. Note that the total exvessel economic value is lower than the possible value-added final product value for
various type of consumption after processing and the economic multiplier effect about
how the society that depends on it is also ignored in this study.
It is also notable that the ex-vessel prices of the frozen bigeye and yellowfin tuna
caught by longline for the Japanese sashimi market are about 4 to 6 times higher than
those caught by purse-seiners for canning. The maximum economic landings value
depends on the quality and the size of the fish caught, such as shows in Table 1 (Sun
et.al., 2010).
The 2007 prices are used in calculating the steady-state equilibrium landings
values since the stock assessment model is based on data ends in 2007, and the 2008
prices are used to calculate the cumulated dynamic projection from 2008-2018.
Equilibrium value
The stock assessment model for bigeye and yellowfin tuna is used to estimate the
spawning biomass ratio (SBR; the ratio of the current spawning biomass, S, to the
spawning biomass of the unexploited stock, S0), catch, and economic value of the
fisheries for different levels of longline and purse-seine fishing effort in a steady state. A
large number of effort combinations are used to allow investigation of the tradeoff.
Target spawning biomass of bigeye tuna
By maintaining the bigeye tuna spawning biomass at 19% of the unexploited
level in a steady state, the stock assessment for bigeye and yellowfin tuna model is used
to estimate the SBR, catch, and economic value of the fisheries under different levels of
longline and purse-seine fishing effort. Aires-da-Silva and Maunder (2009) estimated the
SBR corresponding to the MSPY of bigeye to be about 0.19, so one of the goals of
management should be to avoid letting the SBR decrease to less than 0.19. In particular,
we evaluate the catch and economic value of the fisheries under the following scenarios:
(A) effort allocation in 2008; (B) equal proportional reduction in effort for longline and
purse-seine effort that would support MSPY for bigeye tuna (SBR = 0.19), (C) fixed
longline effort and a reduction in purse-seine effort so that SBR = 0.19; and (D) fixed
purse-seine effort and a reduction in longline effort so that SBR = 0.19.
Dynamic projections of bigeye tuna
9
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
The model is used to estimate the SBR, catch, and economic value of the fisheries
over the period of 2008 to 2018 for different levels of longline and purse-seine fishing
under the effort levels defined above.
RESULTS
Equilibrium value
The SBR, catch, and revenue are all sensitive to the purse-seine and longline
effort. Bigeye and yellowfin SBRs appear to be linear functions of purse-seine and
longline effort and, as expected, increase as both purse-seine and longline effort are
reduced (Figures 1 and 2).
SBRBET = 0.9078 - 0.5940*PS_Effort - 0.2666*LL_Effort; Adj-R2 = 0.8908
SBRYFT = 0.9314 - 0.5283*PS_Effort - 0.0764*LL_Effort; Adj-R2 = 0.9045
(3)
(4)
The relationships between effort and catch or economic value appear to be
nonlinear (Figures 3 and 4). The equilibrium bigeye and yellowfin catches increase, with
increased longline catch. The catch increases as the purse-seine effort is reduced. The
purse-seine effort is about optimal for yellowfin, so either an increase or a decrease in
effort, particularly the latter, reduces the catch.
The total economic value increases as purse-seine effort is reduced and longline
effort is increased, since the values of both yellowfin and bigeye value also increase
(Figures 5, 6, and 7). The contour plots can be used to evaluate a range of effort
allocation schemes. For example, if the longline effort is fixed at the level of 2008, the
economic yield would be increased by reducing the purse-seine effort.
Since changes in skipjack catch are assumed to be proportional to changes in
yellowfin catch, skipjack catch decreases with a decrease in purse-seine effort. Since
skipjack is not caught by the longline fishery, the skipjack catches change with changes
in purse-seine effort only.
Target spawning biomass for bigeye tuna
There are an infinite number of possible purses-seine and longline effort
combinations that can produce a bigeye SBR of 0.19. The relationship is essentially
linear and the tradeoff is 1% change of purse-seine effort corresponds to a 3.68% change
in longline effort.
LL_EffortBET = 3.77 - 3.68*PS_EffortBET;
Adj-R2 = 0.9975
(5a)
The tradeoff can also be evaluated in terms of catch in weight with respect to
standardized purse-seine effort. For example, a 1% reduction in purse-seine effort would
reduce the purse-seine catch by 301 tons and allows a 1,170-ton increase in the longline
catch.
PS_CatchBET = 32.10 + 30.06*PS_EffortBET;
10
Adj-R2 = 0.9654
(5b)
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
LL_CatchBET = 121.21 -117.04*PS_EffortBET;
Adj-R2 = 0.9771
(5c)
where PS_CatchBET and LL_RevenueBET are defined as bigeye tuna catches landed by the
purse-seine and by longline fishery, in thousand metric tons, respectively.
In terms of catch in weight, the tradeoff, while maintaining the SBR at 0.19, is a
1-ton reduction in purse-seine catch would allow a 3.85-ton increase in longline catch.
The slope of the relationship is similar for other levels of SBR.
LL_CatchBET = 243.63 - 3.85*PS_CatchBET;
Adj-R2 = 0.9894
(6)
Equilibrium economic value can be substantially increased by fishing more using
longline and less with purse-seines, while maintaining the SBR at 0.19. One ton of
bigeye tuna not caught in the purse-seine fishery would contribute a $36,878 gain in
revenue for longline fishery and the total bigeye tuna landings value would increase to
$35,340 after providing $1,540 compensation to the loss of purse-seine's bigeye tuna
landings value.
LL_RevenueBET = 2,332.97 - 36.88*PS_CatchBET; Adj-R2 = 0.9894
(7)
Total_RevenueBET = 2,333.71 - 35.34* PS_CatchBET; Adj-R2 = 0.9894
(8)
Total_RevenueBET = 1,211.03 - 1074.45*PS_EffortBET; Adj-R2 = 0.9772
(9)
where LL_RevenueBET and Total_RevenueBET are defined as revenue generated by the
retained catches by longline and by both longline and purse-seine fishery, in millions of
dollars, respectively.
As indicated in equation (9), a 1% reduction in purse-seine fishing effort would
increase the total revenue by $10.74 million after compensating for the loss of catches by
the purse seiners. In summary, a 1% reduction in purse-seine effort on tunas associated
with floating objects (roughly 84 sets), would sustain an increase in longline effort
sufficient to increase the longline catch by 1,170 tons. This implies a reduction of 300.6
tons in the catch of juvenile bigeye, which would increase the total value of the catch by
$10.74 million.
As indicated in Table 2, at the 2008 levels of fishing effort, the steady-state total
revenue, indicated as case A, would be lower than under the 20.5% proportional
reduction of both purse-seine and longline fishing effort, since the SBR would increase
from 0.12 to 0.19 and produce greater catches of bigeye, with greater values, by
longliners.
The SBR = 0.19 line can be used to evaluate a range of effort allocation schemes
to obtain the biomass target. For example, if the longline effort is fixed at its 2008 level,
the purse-seine effort would have to be reduced to 73.7% of its 2008 level (Case C) in
which case the economic value would be increased by $93 million, as compared to an
equal proportional reduction, such as indicated by Case B, shown in Table 2.
By comparing Case C to Case B, the extra revenue generated by the longline fleet
would be $58 million in bigeye tuna catch and $57 million in yellowfin tuna catch. For
11
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
the purse-seiners, there would be $3 million, $11 million, and $8 million decreases in the
catches of bigeye, yellowfin, and skipjack, respectively. The increase in revenue to the
longline fishery—$115 million—would far exceed the decrease in revenue to the purseseine fishery—$22 million.
In contrast, if the purse-seine effort is maintained at its 2008 level, and the goal is
to maintain the SBR at 0.19 (Case D), the longline effort would have to be reduced to
13.3% of its 2008 level, and the total revenue would be decreased by $311 million or
25%, relative to Case B.
Suppose that the longline effort is kept at the 2008 levels and the purse-seine is
shut down (Case X). By comparing this with Case B, the gain for the longline fishery
would be $685 million and $676 million for increased catches of bigeye and yellowfin,
respectively, and the loss for purse-seine fishery would be $810. The net gain would be
$551 million, relative to Case B.
Dynamic projections of landings and value of bigeye tuna
Under current effort levels the bigeye population is predicted to continue
declining (Figure 8). However, if the effort is reduced to levels that support a SBR of
0.19, the bigeye population is predicted to first increase due to recruitment that is greater
than the average recruitment of recent years, and then decline. The economic value of the
catch would increase, and then decline, except for Case D, for which there would be a
precipitous decrease from 2008 to 2009, followed by a gradual decline after that (Figure
9).
Reduction in purse-seine effort to maintain the SBR of bigeye SBR at 0.19 would
causes a reduction in the skipjack catch and its corresponding value (Figure 10). Based
on the average landings of 138,204 mt of skipjack caught in purse-seine sets on tunas
associated with floating objects during 2000-2007 (Anonymous, 2008), the estimated loss
of skipjack value of landings are $40.4 million and $51.8 million, respectively, for 20.5%
and 26.7% reductions in purse-seine effort on tunas associated with floating objects for
Cases B and C, respectively.
In Case B, for which there are 20.5% reductions for both longline effort and
purse-seine effort on tunas associated with floating objects, the cumulative loss due to
reduced catches of skipjack would reach $200 million in three years, and the increase in
economic value due to the increase in the biomass of bigeye tuna and in the catch of that
species by longliners would not be enough to offset the loss due to the decreased catches
of skipjack until 10 years later (Figure 10: Panel (a)).
In Case C, for which we maintain the longline effort at the 2008 level while
reducing the purse-seine effort on tunas associated with floating objects sufficiently to
maintain the SBR at 0.19, then we would produce higher total revenue for all years
compared to equal proportional reductions in both purse-seine and longline effort (Figure
10, Panel (d))—even greater than for Case A in just 3 years later (Figure 10, Panel (b).
12
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
By comparing Case C to Case A (Figure 10, Panel (b)), the total revenue is
estimated to be reduced in the short term, but in only 3 years it would be compatible to
the level in Case A and would take only one more year to compensate for the initial loss
in revenue during the first two years. After deducting the losses to purse seiners of
catches of skipjack associated with floating objects, the cumulative extra gain in revenue
to longline-fishing countries, who benefits from the recovery of the bigeye biomass,
could be cumulated to more than $800 million in 10 years.
As shown in Table 3, the cumulative value of the dynamic projections of the
catches of bigeye and skipjack tuna by longliners and by purse seiners directing their
effort toward tunas associated with floating objects under Case C would be $698 million
greater than that for Case B during 2009-2018.
SUMMARY AND DISCUSSION
Tuna in the EPO are not managed optimally with respect to their economic value.
Catch and economic value are highly sensitive to the allocation of effort between the
purse-seine and longline fisheries. For the same bigeye tuna biomass target levels, higher
economic value can be obtained by increasing the longline effort and reducing the purseseine effort. The current management action, which reduces the longline and purse-seine
fishing effort proportionally so as to maintain the SBR of bigeye at = 0.19 results in a
cumulative loss in value. An alternative action, that would reduce only the purse-seine
fishing effort sufficiently to maintain the SBR of bigeye at 0.19 would result in a
substantial gain in value relative to that realized at the effort levels of 2008. These results
suggest that the economic value could be an important consideration in the management
of tropical tuna in the EPO.
The results show that substantially greater total revenue for the tuna fishery in
EPO can be obtained by modifying the amount of effort conducted by each fishing
method. The current IATTC management measures, which require 20.5% equal
proportional reductions in effort for both the purse-seine and longline fisheries is not
economically optimal. While achieving the same bigeye tuna biomass level, equilibrium
economic value can be substantially increased by increasing the longline effort and
decreasing the purse–seine effort. Under the effort scenario that optimizes equilibrium
economic value while holding longline effort constant (which reduces the influences of
the unknown costs of fishing on the calculations) and reducing the purse-seine effort on
tunas associated with floating objects, the total revenue is estimated to be reduced in the
short term, but the total revenue would be greater than it would be with the 20.5%
proportional reduction scheme and it would take only 3 years for the total revenue to
return to the 2008 level. In the steady-state equilibrium situation, the total annual revenue
for the entire tuna fleet in the EPO would be $93 million greater after compensating for
the initial loss in revenue for purse-seiners.
The economic value is given purely in terms of landed value, and does not take
into consideration the costs of fishing. The costs of fishing could influence the calculation
of economic value. However, the influence of the cost of fishing can be reduced by
13
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
maintaining the longline fishery at its 2008 level while reducing the purse-seine fishing
effort. In this scenario, the additional cost to the longline fishery will be only the cost of
handling more fish, while the reduction in the cost of the purse-seine fishery would be
substantial. Allocation of effort among the fleets is complicated due to differences in the
countries whose vessels participate in the fisheries. In generally the large longline vessels
are from Asia, while the purse-seine vessels are owned by companies in Latin America
and Europe. In addition, there are large numbers of artisanal longline vessels based in
Latin America. An equitable method is needed to allocate effort among the different
fleets and nations. The methods for doing this are discussed below.
1). Property rights. A property rights system could be introduced that provides a quota
to each fleet or nation based on some equitable scheme (e.g. historical catch or
adjacency to the resource) and leave the allocation of effort to the market. If our
calculations are correct, the longline fleet should lease or purchase the quota from the
purse-seine fleet because they could get more value out of the quota. To avoid
overexploitation due to differences in the age structure of the catch among fleets a
quota equivalency would need to be determined between longline and purse-seine
fleets. Since there is a linear relationship between SBR and effort and this relationship
appears to be similar for different target levels of SBR, an equivalency of 1 purseseine quota equals 3.86 longline quotas would be appropriate. Setting quota in terms
of effort would require strict controls on the effort standards. Setting quota in terms of
amounts of fish caught would require accurate estimates of sustainable yields on an
annual basis due to the variable nature of tuna populations.
2). Compensation. A compensation system could be used to pay the purse-seine fleet to
reduce its fishing effort. The payment would have to be negotiated between the two
fleets, but the calculations here can give a guide to what value would be obtained by
reducing the purse-seine catch. While holding bigeye SBR at 0.19, the marginal effect
of increasing in the steady-state equilibrium landings value for each ton of purse-seine
bigeye tuna not caught is $36,878 and would reach $35,340 after providing $1,540
compensation to the loss of purse-seine's bigeye tuna landings value. So the longline
fishery could compensate the purse-seine fishery for their decreases in revenue and
still be better off than they are at present.
By considering all three major tuna species, the economic value would be increased
by $93 million if the managers were to allow the longline fleet to maintain its effort at
the 2008 without increasing its expenditures (Table 2). The purse-seine fleet would
decrease its expenditures while maintaining its income (sales of fish caught plus
payments from longline interests), so its benefit would be even greater.
If the purse-seine vessels were paid an amount equal the value of their catch not to
fish, while the longline effort is fixed at its 2008 level, the purse-seine effort would
need to be reduced to 73.7% of its 2008 level to obtain the bigeye tuna SBR of 0.19.
In contrast, the present IATTC recommendation is that there be 20.5% reductions in
both the purse-seine and longline efforts. The additional cost for proposal for
reduction of only the purse-seine effort would be $8 million, but the increase in
revenue to the longline fleet would be $102 million, so the net economic increase
14
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
would be $93 million. In addition, the costs to the purse-seine fleet of maintaining the
vessels in port would be far less than the costs of fishing, so the benefit to them would
be even greater.
3). Bycatch compensation. It is possible that purse-seine vessels could reducue their
catches of bigeye in sets on tunas associated with floating objects, although
preliminary studies (Lennert-Cody et al., 2008) suggest that this may be difficult. A
possible compensation scheme could be used to pay purse-seine vessels to avoid
bigeye tuna. This would allow the purse-seine vessels to still capture skipjack and
yellowfin tuna, but perhaps at a lower levels since avoiding bigeye may reduce their
efficiency. It may also involve extra costs due to additional man power or equipment
that might be needed to avoid bigeye. Related to this is the establishment of a research
fund to determine methods to avoid bigeye tuna. Given the value gained by avoiding
bigeye tuna a substantial amount of money should be invested in research. However,
the possibility of not being able to find an appropriate solution needs to be considered.
4). Vessel buybacks. A vessel buyback system (Squires et al., 2010), for which the
longline fishery purchases purse-seine vessels and sinks them or converts them to
other uses, could be implemented. Strict control would be needed to ensure that no
new vessels entered the fishery. Currently, the IATTC has a limit on the fish-carrying
capacity of purse seiners that are permitted to fish in the EPO. The fish-carrying
capacity (which is approximately proportional to fishing capacity) of the purse-seine
fleet in the EPO was 209 thousand m3 in its 2009. Based on data given by Allen et al.
(2008), the prices paid for a 1200-m3 used vessel ranged between $5 million and $8.5
million, so the estimated cost of reducing the capacity to 73.7% of its 2008 level under
Case C that would support the bigeye tuna SBR of 0.19 is $229 million to $366
million. The cost of buying back all the purse-seine vessels would be $871 million to
1,393 million.
The vessel buyback proposal would be a one-time cost and would occur either in a
single year or over several years, but if carried out over several years it would take
longer for the benefits to be realized compared to paying the purse-seine vessels not to
fish. Care would be needed to determine the effective fishing capacities of the vessels
purchased, since the least efficient vessels could be the first to be offered for sale
during a buyback. The buyback would work based strictly on vessel costs if the purseseine fishery was not making a profit, otherwise the business value of the vessel (the
fact that it has fishing access to the EPO) would also have to be integrated into the
price.
If we could manage to have the compensation system pay the purse-seine fleet to
reduce its fishing effort, we could increase the annual revenue to the longline fishery
by $93 million after compensating for the losses in revenue to the purse-seine fishery,
by allocating the effort in accordance with Case C, rather than continuing with Case
B. It would take only 3 to 4 years to accumulate enough funds to buy back the 26.3%
excess purse-seine capacity and it would be even sooner if we are planned to buyback
only about 30% of the purse-seiners who set on floating objects.
15
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Discussion
Some of these proposals would cause substantial loss of jobs related to the purseseine fisheries. To negate the effect of the loss of jobs and make the proposals more
attractive to purse-seine fishing nations, the agreements could consider more than just
revenue. For example, the longline nations could implement joint venture longline
vessels or establish processing or transportation plants in nations that had their purseseine fisheries reduced or eliminated.
The dynamic effect of the compensation scheme would have to be taken into
consideration. It would take several years before the stock size was rebuilt and the
longline catches increased. Therefore, in the first couple years the strategy would cause a
loss in value to the longline fleet, but this loss would be gained back after 2-3 years.
Therefore, any agreement would have to be made for a substantial number of years to
make it profitable to the longline fleet.
Spawning biomass would also increase under scenarios that reduce the purseseine effort and keep the longline effort at levels in 2008. This would provide additional
protection against stock collapse. In addition, the calculations made above are based on
the assumption that recruitment is independent of stock size, provided that the SBR is
equal to or greater than 0.19. If recruitment increased as the stock size increased, the
increase in value of the fishery would be expected to be greater. Catches of yellowfin in
the longline fishery might be increased if some longline vessels changed their fishing
practices to target yellowfin.
Few bigeye tuna are caught in the purse-seine sets on tuna associated with
dolphins. Although about 98% of bigeye caught by purse seiners are fished by floating
objects, the steady-state equilibrium results presented in this study are based on treatment
of all purse-seine effort equally. This is partly due to the difficulties in restricting purseseine vessels on different set types since vessels that fish on dolphin associated tuna can
also set on floating objects and unassociated schools. Encouraging fishermen to make
sets on tunas associated with dolphins might increase the purse-seine catches of
yellowfin, since most of the yellowfin caught in such sets are close to the critical size.
However, the economic value of a purse seine caught yellowfin is lower than a longline
caught yellowfin.
The calculations in this paper are based on several assumptions about the
population dynamics of bigeye, yellowfin, and skipjack, and their economic value. There
are situations in which the estimated increase in value could be overestimated, and this
needs to be taken into consideration when contemplating the suggested actions. For
example, the calculations do not take into account the elasticity of the market; increased
catches of bigeye for the sashimi market might reduce the price. It is not certain that all
bigeye that are vulnerable to the purse-seine fishery would be vulnerable to the longline
fishery if they were not caught. For example, the large increase in purse-seine catches of
bigeye tuna as the floating object fishery expanded did not appear to reduce the longline
catch rates as might be expected indicating the possibility that bigeye vulnerable to the
purse-seine fishery may not be vulnerable to the longline fishery.
16
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Managing the fisheries for tropical tunas in the EPO is complicated. Management
objectives differ among resource users, and there are a multitude of factors that need to
be considered. We have shown that the economic value of the resource is highly
dependent on the allocation of effort between the longline and purse-seine fisheries.
Economic and social considerations have not been formally integrated into management
of the fisheries for tropical tunas in the EPO. This is likely to change in 2010, when the
new IATTC convention enters into force, as it states that ―Considering the importance of
fishing for highly migratory fish stocks as a source of food, employment and economic
benefits for the populations of the Parties … conservation and management measures
must address those needs and take into account the economic and social impacts of those
measures.‖
The details of such a management system would have to be worked out to address
the complexities of the fishery and the society that depends on it, but the potential
benefits and the possibility of implementing such a system should not be ignored.
References
Aires-da-Silva, A., and M.N. Maunder. (2010). Status of bigeye tuna in the eastern
Pacific Ocean and outlook for the future. Inter-Amer. Trop. Tuna Comm., Stock
Asses.. Rep. 10: 116-228.
Allen, Robin, James Joseph, and Dale Squires. (2008), Report of Workshop on Rightsbased Management and Buybacks in International Tuna Fisheries, University of
California at San Diego, La Jolla, California May 5-9, 2008.
Allen, Robin, James Joseph, and Dale Squires. (2010), Rights-Based Management and
Buybacks in International Tuna Fisheries. IATTC Special Report 19: in
preparation. http://www.iattc.org/PDFFiles2/Allen-Joseph-and-Squires.pdf
Anonymous. (2008). Tunas and billfishes in the eastern Pacific Ocean in 2007. InterAmer. Trop. Tuna Comm., Fish. Status Rep., 6: 140 pp.
Bertignac, M., H.F. Campbell, J. Hampton, and A.J. Hand. (2000). Maximizing resource
rent in the western and central Pacific Ocean tuna fisheries. Marine Resource
Economics, 15 (3): 151-177.
Campbell, H.F. and R.B. Nicholl. (1995). Allocating yellowfin tuna between the
multispecies purse seine and longline fleets. Marine Resource Economics, 10 (1):
35-58.
Christensen, V. (2010). MEY = MSY. Fish and Fisheries, 11 (1): 105-110.
Green, R.E., and G.C. Broadhead. (1965). Costs and earnings of tropical tuna vessels
based in California. Fishery Industrial Research, 3 (1): 29-58.
Lennert-Cody, C.E., J.J. Roberts, and R.J. Stephenson. (2008). Effects of gear
characteristics on the presence of bigeye tuna (Thunnus obesus) in the catches of
the purse-seine fishery of the eastern Pacific Ocean. ICES Jour. Mar. Sci., 65 (6):
970-978.
17
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Maunder, M.N., and A. Aires-da-Silva. (2010). Status of yellowfin tuna in the eastern
Pacific Ocean and outlook for the future. Inter-Amer. Trop. Tuna Comm., Stock
Asses.. Rep. 10:3-109.
Maunder, M. N. (2010). Updated indicators of stock status for skipjack tuna in the eastern
Pacific Ocean. Inter-Amer. Trop. Tuna Comm., Stock Asses. Rep. 10: 110-115.
Methot, R. D. (2005). Technical description of the Stock Synthesis II assessment
program. NOAA Fisheries. 54 pp.
Squires, D., J. Joseph, and T. Groves. (2010). Buybacks in transnational fisheries In
Allen, R., J. Joseph, and D. Squires (editors), Conservation and Management of
Transnational Tuna Fisheries, Wiley-Blackwell: 181-194.
Table 1 Frozen bigeye, yellowfin and skipjack prices in 2007 and 2008
Market Ex-vessel prices1 in Mexico
Auction prices2 in Tsukiji,
Year
and Ecuador ($/mt)
Tokyo, Japan ($/mt)
Species
2007
2008
2007
2008
Yellowfin
$1,710
$1,945
$7,858
$9,579
Bigeye
$1,568
$1,783
$9,576
$12,271
Skipjack
$1,425
$1,621
1
Personal communication from the tuna processors in Mexico and Ecuador for
landings caught by tuna purse seine fishery.
2
Personal communication from the auction market in Tsukiji, Tokyo, Japan for
landings caught by tuna longline fishery.
18
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Table 2 Static comparison of the retained bigeye and yellowfin tuna catches landed by
longline and purse-seine landings and value under different scenarios while
holding the SBR as 0.19
Retained Catches
Revenue (million $)
Fishery
LL
PS
LL Changes
PS Changes Total
Changes
Scenario
(1,000 mt)
to Case B
to Case B
to Case B
Bigeye Tuna
Case A
22
59
211
93
304
Case B
27
56
263
89
352
Case C
34
55
321
58
86
-3
407
55
Case D
4
62
41
-170
97
8
138
-214
Case X
99
0
685
0
-89
948
596
948
Yellowfin Tuna
Case A
20
252
155
432
587
Case B
22
245
173
418
591
Case C
29
238
230
57 407
-11
637
46
Case D
3
262
23
-132 448
30
471
-120
Case X
109
0
849
676
0
-418
849
258
Skipjack Tuna
Case A
220
313
313
Case B
213
303
303
Case C
207
- 295
-8
295
-8
Case D
228
- 325
22
325
22
Case X
0
0
-303
0
-303
All Tuna
Case A
42
531
366
838
1,204
Case B
49
514
436
810
1,246
Case C
63
500
551
115 788
-22 1,339
93
Case D
7
552
64
-302 870
60
934
-312
Case X
208
0
1,797
1361
0
-810 1,797
551
*The standardized purse-seine and longline effort is indicated in the parenthesis under
each scenarios as Case A (PS=1, LL=1), Case B (PS=0.795, LL=0.795), Case C
(PS=0.737, LL=1), Case D (PS=1, LL=0.133) and Case X (PS=0, LL=1).
Table 3 Cumulated landings value of the dynamic projections of the retained bigeye and
skipjack tuna landed by longliners and floating objects purse-seiners under
different scenarios during 2009-2018
Floating Objects Purse-Seine
Longline
Total Compared
Cumulated
landings
Total Compared
value
Bigeye Skipjack (3)
Bigeye compared
to
(Million $) (1)
(2) =(1)+(2) to Case B
(4) to Case B (3)+(4) Case B
Case A
1,278 1,969 3,247
3,421
3,247
Case B
1,215 1,566 2,781
3,545
2,781
Case C
1,170 1,451 2,621
-160 4,403
858 3,479
698
Case D
1,321 1,969 3,290
509
812
-2,733
557
-2,224
19
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
0.12
0.19
D
A
B
C
Spawning biomass ratio
1.0
0.8
Longline effort
1.5
0.6
1.0
0.4
0.5
0.2
0.0
0.5
1.0
1.5
Purse seine effort
Figure 1 Surface and contour plot of equilibrium bigeye tuna spawning biomass ratio
(SBR) under different purse-seine (PS_F) and longline effort (LL_F) levels relative to
effort levels in 2008
20
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Spawning biomass ratio
1.0
0.8
Longline effort
1.5
0.6
1.0
0.4
0.5
0.2
0.5
1.0
1.5
Purse seine effort
Figure 2 Surface and contour plot of equilibrium yellowfin tuna spawning biomass ratio
(SBR) under different purse-seine (PS_F) and longline effort (LL_F) levels relative to
effort levels in 2008
21
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Equilibrium BET yield (thousands of tons)
140
2
120
Longline effort
1.51.5
SBR=0.12
SBR=0.19
11.0
C
100
80
A
60
B
40
0.50.5
20
D
0
0
0
0.5
0.5
1.0
1
1.5
1.5
2
Purse seine effort
Figure 3 Contour plot of bigeye tuna steady-state catch (1,000 mt) under different purseseine and longline effort levels relative to effort levels in 2008
22
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Equalibrium YFT yield (thousands of tons)
2
250
Longline effort
1.5
1.5
SBR=0.12
SBR=0.19
C
1
1.0
200
A
150
B
100
0.5
0.5
50
D
0
0
0
0.5
0.5
1
1.5
1.0
1.5
2
Purse seine effort
Figure 4 Contour plot of yellowfin tuna steady-state catch under different purse-seine and
longline effort levels relative to effort levels in 2008
23
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
BET landed value (billions)
1.5
Longline effort
1.5
1.0
1.0
0.5
0.5
0.0
0.5
1.0
1.5
Purse seine effort
Figure 5 Equilibrium revenue ($ million) for bigeye tuna under different purse-seine and
longline effort relative to effort level in 2008
24
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
YFT landed value (billions)
1.5
Longline effort
1.5
1.0
1.0
0.5
0.5
0.0
0.5
1.0
1.5
Purse seine effort
Figure 6 Equilibrium revenue for yellowfin tuna under different purse-seine and longline
effort levels relative to effort levels in 2008
25
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Change in value (billions)
1.5
1.0
Longline effort
1.5
0.5
1.0
0.0
-0.5
0.5
-1.0
-1.5
0.5
1.0
1.5
Purse seine effort
Figure 7 The change in total landings values of the EPO tuna fishery after adjustment for
compensating the purse-seine fishery for lost catch under different purse-seine and
longline effort levels relative to effort levels in 2008
0.500
Case A (PS=1, LL=1)
Case B (PS=0.795, LL=0.795)
Case C (PS=0.737, LL=1)
Case D (PS=1, LL=0.133)
Case E (F_current 90%)
Case F (F_current 70%)
Spawning Biomass Ratio (SBR)
0.450
0.400
0.350
0.300
0.250
0.200
0.150
0.100
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
Figure 8 Trajectory plot of bigeye tuna spawning biomass ratio under different floating
objects purse-seine (PS) and longline effort (LL) levels relative to effort levels in 2008
26
Landings Value (Millions $)
Task I. Tradeoffs between LL and PS Fishing
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
600
500
400
Case A (PS=1, LL=1)
Case B (PS=0.795, LL=0.795)
Case C (PS=0.737, LL=1)
Case D (PS=1, LL=0.133)
300
200
100
2008
2010
2012
2014
2016
2018
Figure 9 Trajectory plot of total landings value of bigeye under Case A, B, C and D with
different floating objects purse-seine (PS) and longline effort (LL) levels relative to effort
levels in 2008 while holding the bigeye tuna SBR as 0.19
1,000
Millions $
Millions $
100
LL: Bigeye
0
PS: Bigeye
2008
2013
2018
-100
PS: Skipjack
Cumulated
800
LL: Bigeye
600
PS: Bigeye
400
PS: Skipjack
200
Cumulated
0
-200 2008
-200
(a) Gains and Losses under Case B vs
Case A
(b) Gains and Losses under Case C vs
Case A
Millions $
Millions $
0
2008
2013
2018
LL: Bigeye
-3,000
600
400
LL: Bigeye
PS: Bigeye
PS: Skipjack
Cumulated
200
PS: Bigeye
-2,000
2018
800
1,000
-1,000
2013
0
Cumulated
-200 2008
(c) Gains and Losses under
Case D vs Case A
2013
2018
(d) Gains and Losses under Case C vs
Case B
Figure 10 Trajectory plot of the gains and/or losses of floating objects purse-seine (PS)
and longline (LL) for each tuna species and the cumulated total landings value under
Case A, B, C and D while holding the bigeye tuna SBR as 0.19
27
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
Task II
Inverse Demand Analysis of Tuna for the Canning
Market in Thailand and for the Sashimi Market in
Tokyo, Japan
Chin-Hwa Sun1 and Fu-Sung Chiang2
Abstract
The objective of this research is to estimate the global market responses of tuna raw
material for canning in Thailand and tuna for the sashimi market in Tokyo, Japan, since income
to fishermen and, in turn, and the dynamics of the tuna fleet might be influenced by both the
availability of resources and price levels. This study uses General Synthetic Inverse Demand
Systems (GSIDS) to estimate the price flexibility of frozen skipjack and yellowfin tuna, two
major target species of the tuna purse-seine fishery, to their major imports in Thailand and the
price flexibility of fresh and frozen bluefin, bigeye and yellowfin tuna, three major target species
of the tuna longline fishery, for the sashimi market in Tokyo, Japan. These analyses are used to
determine to what extent changes in the price of one species might impact prices of others in
each market. The estimation results indicate that the price of each tuna responds negatively in
relation to its own quantity in either of the major global markets.
For the tuna imported in Thailand, the scale flexibility of skipjack and yellowfin tuna in
Bangkok are estimated as -0.99 and -1.02, respectively and is significantly different than zero,
i.e., a 1% increase in skipjack imports would reduce both the skipjack and yellowfin tuna import
prices by 1%. The constantly increasing exploitation rate of skipjack worldwide would push the
expansion of the canning industry in Thailand, but the total revenue for the fishing industry
would be offset by the proportionately reduction in price.
For the sashimi market in Tokyo, the scale flexibilities of fresh and frozen bluefin tuna, 0.726 and -0.932, respectively, are both less than unity in absolute value, which indicates these
goods are considered as luxury, i.e., if the supply of all sashimi-grade tuna species increased by
1% and they would have less than 1% decrease in prices. Since the bluefin tuna prices are less
responsive to the changes of the supply of all tuna species, it means that the Japanese consumers
are still willing to pay premium prices for high-quality fresh and frozen bluefin tuna than that for
the other tuna species. There is no incentive for suppliers of bluefin tuna to cooperate to reduce
their supply from either wild caught or cage-cultured bluefin tuna because this would result in
reduction in their total revenue.
For the sashimi-grade bigeye and yellowfin tuna, their scale flexibilities are identified to be
greater than unity and are referred as necessities which would be less preferable than bluefin tuna
1
Professor, Institute of Applied Economics, National Taiwan Ocean University, [email protected]; Visiting
Scientist, Inter-American Tropical Tuna Commission, 2009-2010.
2
Professor, Institute of Applied Economics, National Taiwan Ocean University, [email protected]
28
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
and its price would decline more than proportionately as consumption of all goods in the bundle
increases. We would predict a negative impact on total revenue induced by the result of an
intense race for fish, or derby, which would imply a more than proportionately decrease in
prices. Hence, if fishermen could act collectively to adjust their operation cost through a quotatrading mechanism monitored by the tuna RFMOs, fishermen could get the capability to help
conservation by avoid overcapacity and the derby effect. It would be beneficial for the fishing
industry to realize that a better marketing distribution scheme for yellowfin and bigeye tuna
would increase their total landings values, even if a fishing quota for these tunas are strained due
to conservation measures.
Keywords: General Synthetic Inverse Demand Systems, Price Flexibility, Scale Flexibility, Tuna
Cannery Market, Tuna Sashimi market
INTRODUCTION
There are many different types of tuna markets, differentiated by products–fresh and
frozen sashimi grade tuna, frozen tuna for canning and canned tuna - and by locales—Japan,
Thailand, United States, and European Union, etc. Supply varies across these markets, but
overall it is limited, and regulations on fishing are necessary to maintain the stocks at their
optimum levels. Demand varies as well–e.g. demand in Japan for sashimi, demand in the
Thailand for tuna for canning, and demand in the United State and European Union for canned
tuna, and also in the costs of fishing cause changes of the composition of the fishing fleets–e.g.
from high-cost nations to low-cost nations, which makes management of fishing effort more
difficult.
It is important for fishery managers to understand market responses, since income to
fishermen and, in turn, and the dynamics of the fleet might be influenced by both the availability
of resources and price levels. The ex-vessel price for each species is subject to the dynamic
behavior of the demand and supply in the market. Critically, changes in landings can impact exvessel prices, revenues, and license fees received by coastal states, which is especially important
in developing countries. If the price flexibility is greater than unity in absolute value, decreases
in landings can increase the price to compensate the reduction in landings, and revenues would
be increased. Identifying the strength of this relationship would also provide convincing
evidence that management through temporary or permanent reduction in catches not only lowers
costs, but also raises revenues and hence profits and resource rent.
If the price flexibility is less than unity in absolute value, there is no incentive for
fisherman to cooperate to reduce their catches because this would result in reduction in their
revenue. A quota-trading mechanism would provide to fishermen the capability to adjust their
operation cost to avoid overcapacity and the derby effect in an optimal economic scale to help
conservation through reduced catches.
Estimated demand price flexibilities are needed to simulate different scenarios of changes
in fishing capacity (a proxy for fishing effort) upon total revenues, and the impacts that climate
change, resource abundance, and policies have on markets. The U.S. Department of State, for
29
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
example, has repeatedly expressed interest in the revenue impacts of alternative capacity
policies, which in turn affect supply. Actual estimates will help to develop the strategic plan and
mission goals in this regard. The price flexibilities will be particularly helpful in recognizing the
linkage between our global economy and tuna management in order to protect, restore, and
manage the use of coastal and high-seas tuna resources through ecosystem management
approaches and to enhance society’s ability to plan and respond. Such estimates will also be
helpful in current efforts to reduce purse-seine and longline fishing capacity, as necessary, and in
determining the best mix of purse seine, longline, and other gears through their revenue effects.
Building the economic evaluation on top of the stock assessment model to evaluate the best mix
of gears and to estimate bio-economic resource rents under alternative policy scenarios also
relies upon price flexibility.
Previous estimates of price flexibility and inverse demand for tunas have largely been ad
hoc and directed at single species. Without a systems approach, consumption substitution
possibilities among different species, inventories, impacts of global quota management control,
supply effects from different species, and effects from socio-economic variables are excluded.
Such exclusion can lead to biased estimates. For example, a recent report containing a
bioeconomic model to the Government of Australia used a price flexibility for all tunas
aggregated together (Bertignac, Campbell, Hampton, and Hand, 2000). Critically, changes in
landings can impact ex-vessel revenues and license fees received by coastal states, most of which
are developing countries in EPO.
As long as market responses can be estimated, the impact of quota control on prices in
both local and global markets could be predicted. For example, a decision rule, which was
designed to build on a CPUE-based rational expectation of next period’s total allowable catch
(TAC) by taking into account the inverse demand flexibility to moderating effect on the southern
bluefin tuna market’s self-adjustment following the TAC reductions in cooperating with the
stock assessment multiple cohort operating model provided by Commission of Conservation for
Southern Bluefin Tuna (CCSBT) in 2004, was selected and recognized by the Scientific
Committee as one of the final four candidate decision-rules to ensure the recovery of the biomass
in the long run and also to prevent a dramatic reduction of the common wealth of the industry in
the short run (Sun, 2004, 2005; Sun and Lin, 2007).
The identification of the price flexibility will facilitate the market-based conservation and
management measure of the tuna longline and tuna purse-seine fisheries in EPO to support the
IATTC’s mission in developing a long run sustainable plan and to evaluate the benefits of rightbased management of the tuna purse-seine and longline fishery landing in IATTC region.
Managing uses of bigeye and yellowfin tuna stock would require applying scientifically sound
observations, assessments, and research findings to ensure the sustainable use of resources and to
balance competing uses of coastal and marine ecosystems in EPO.
Several recent studies have shown the globalization of tuna fisheries and markets.
Sashimi-grade or cannery-grade tuna markets are strongly integrated at the world-wide level,
making any regional change of catches important for the entire industry. The concentration of
processors and traders is high, and information is rapidly transmitted from one location to
another (Pan and Sun, 2009; Jiménez, Guillotreau, Mongruel, 2009; Miyake, Guillotreau, Sun
and Ishimuram, 2010).
30
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
The implications of the price flexibility are important in terms of fishery management
because market incentives are largely taken into account by the local regulation bodies, such as
the recent rent-sharing rule between US vessels and Small Pacific islands adopted within the
South Pacific Tuna Treaty in Squires et al. (2006). First, the local fishermen’s income can
fluctuate substantially because of higher catches in other world fisheries, and the developing
economies that are highly dependent on tuna fisheries could be strongly affected. Secondly, the
investment cycle, hence the dynamics of the fleet, might be influenced with lagged effects both
by the availability of resources and price levels. The implications are also important for local
buyers of raw tropical tuna, who are very concerned by the linkage and volatility of prices
throughout time.
The methodology proposed here follows two steps: (1) a general synthetic inverse
demand systems (GSIDS) to estimate the price flexibility of the frozen skipjack and yellowfin
tuna in the global major imports in Thailand. (2) the GSIDS mentioned in the first step is also
used to identify the price flexibility of fresh and frozen bluefin, bigeye and yellowfin tuna
sashimi market in Tokyo, Japan. The estimates of own- and cross- price flexibility and scale
flexibility can be used to examine the impact of global quota management control.
The structure of the report is organized that the market structure of both tuna canning and
sashimi market are reviewed next. Section 3 reviews both the inverse demand. Section 4 presents
and estimates of the price flexibilities of each species in relation to their own landings and scale
flexibilities with respect to the total landings. Section 5 concludes the reports and discusses the
implication.
MARKET STRUCTURE OF THE TUNA FOR CANNING MARKET IN THAILAND
According to statistics compiled by the Food and Aquaculture organization of the United
Nations, the global catch of skipjack and yellowfin tuna were 2.42 million mt and 1.14 million
mt, respectively, in 2008. About 1.93 million mt of skipjack and 545 thousand mt of yellowfin
tuna caught by the purse-seine gear were delivered to cannery. About 73% of purse-seine catches
of skipjack were made in the western central Pacific Ocean (WCPO). More than 83% percent of
the global imports of frozen skipjack are delivered to the top five countries, Thailand, Mauritius,
Cote D'Ivoire, Japan, and Spain. Furthermore, Thailand accounted for more than 66% of the
global imports of frozen skipjack in 2007, and its annual imports have more doubled from 320
thousand mt in 2001 to 669 thousand mt in 2009. More than 95% of Thailand’s imports of
skipjack are supplied by countries that caught the fish in the WCPO. Thailand imports more tuna
than any other country in the world.
Taiwan, supplied 28% and 20% of the skipjack imports to Thailand in 2001 and 2009,
respectively, other major supplies have been the United states (12% in 2001; 17% in 2009),
Micronesia (17% in 2001; 3% in 2009) and Japan (9% in 2001; 3% in 2009) in Bangkok are
supplied by Taiwan as the major supplier and only 1% of the imports, which is about 2,600 mt,
are supplied by the US purse-seiners (Customs, Thailand). However, in 2009, the US share of
the total imports has increased dramatically to 19%, which is about 124 thousand mt, and is
almost equivalent to the share that the Taiwanese had, 20%, and counted as the top two countries
of origins.
31
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
On a monthly basis, the imports of yellowfin tuna is less than 10 thousand mt, but the
imports of skipjack have been more than double which had reached 64 thousand mt in February
2010. In 2009, the imports of skipjack is more than 5 times higher than the imports of yellowfin
tuna, and the average imports prices of frozen yellowfin tuna is about US$300 to US$500 higher
than the average imports prices of frozen skipjack per mt.The imports of skipjack to Thailand far
exceed those of yellowfin (figure 2). The import of both skipjack and yellowfin increased during
the period of 2001- 2009. On a monthly basis, the imports of yellowfin tended to be the greatest
during the northern hemisphere winter. The prices paid for yellowfin exceeded those for skipjack,
although the difference was small during late 2008 and early 2009.
There is a dramatic change in market share in the last decade, since the Thailand
supplanted the USA as the world’s largest producer of canned tuna in 1994. The top three canned
tuna importing countries in both quantity and value are USA, France, and UK, which purchase
over 50 percent of world imports. About 70 percent of the United States’ canned tuna imports
come from Thailand.
Based on a market analysis of unprocessed and canned tuna, Thailand is both the largest
exporter of canned tuna and the largest importer of frozen raw tuna in the world. Since Thailand
has been the largest importing country of frozen tuna raw materials, the ex-vessel price of the
skipjack is determined by the processing factories in Thailand. Although Thailand is the largest
producer of canned tuna, its domestic consumption is still quite low, and nearly all of its canned
tuna is exported.
Conservation and management of global tuna fisheries can be greatly aided by
knowledge of the responsiveness of ex-vessel prices and revenues of tunas to changes in
landings. At least two key objectives can be drawn from such a projection: to reduce the
fluctuations in fishing effort over time, and if reliable expectations can be obtained for future
prices, financial instruments could be designed to cover the risk of price variability.
Through the use of the Granger Causality test, Sun and Hsieh (2000) shown that frozen
skipjack tuna caught by the tuna purse-seine fishery of Taiwan and exported to Thailand
statistically determined the ex-vessel market prices in Thailand during January 1993 to
December 1996. A transfer function model is specified, and the resulting estimates of the price
flexibilities reach –0.55 when landings are high during April and May and the price is less
flexible while landings are low during October to December. Jeon et al. (2008) utilized
cointegration analysis to show that prices of tuna for canning interconnected global markets
(Jeon et al., 2008). However, due to the limitations of their dataset without the corresponding
landings, the price flexibility and the yellowfin tuna price linkage with the skipjack are not
available.
In order to use the GSIDS to identify the price flexibility of both the skipjack and
yellowfin tuna in Thailand, this study compiles the monthly imports data set in Thailand. As
shown in Fig. 2, the skipjack and yellowfin prices co-move closely and the import prices of
skipjack tuna seems to be more volatile than those of yellowfin tuna. The monthly imports of
yellowfin tuna is limited to be less than 15 thousand mt while those of skipjack have expanded to
be almost three times from 23 thousand mt in January 2001 to 64 thousand mt in January 2010.
On average, the frozen import prices of yellowfin tuna is about US$300 to US$500 higher than
those of skipjack, and specifically, the imports of skipjack is more than 6 times of the imports of
yellowfin tuna.
32
Task II: Inverse Demand Analysis
VANUATU
2%
SOLOMON
ISLANDS
2%
Global Tuna Demand and Fisheries Dynamics in the EPO
INDONESIA
2%
SPAIN
1%
UNITED STATES
1%
OTHERS
6%
MALDIVES
2%
SEYCHELLES
3%
TAIWAN
28%
KOREA,R
3%
JAPAN
9%
KIRIBATI
3%
PNG
9%
(a) in 2001 (320,455 mt)
MARSHALL
ISLAND
2%
MALDIVES
2%
PAPUA NEW
GUINEA
2%
SPAIN
2%
MARSHALL
ISLAND
12%
OTHERS
6%
SOLOMON
ISLANDS
1%
TAIWAN
20%
PHILIPPINES
2%
JAPAN
3%
UNITED STATES
19%
MICRONESIA
3%
INDONESIA
5%
MICRONESIA
17%
CHINA
5%
VANUATU
11%
KOREA,R
17%
(b) in 2009 (668,515 mt)
Fig. 1 Imports of Frozen Skipjack in Thailand by Countries of Origin in 2001 and 2009
33
3,000
Global Tuna Demand and Fisheries Dynamics in the EPO
YFT Imports in Bangkok, Thailand (MT)
SKJ Imports in Bangkok, Thailand
YFT Import Prices (C&F) in Bangkok, Thailand ($/MT)
SKJ Import Prices (C&F) in Bangkok, Thailand
2,500
80
70
60
2,000
50
1,500
Imports (Thousand mt)
Imports Prices (US$/mt)
Task II: Inverse Demand Analysis
40
30
1,000
20
500
10
0
2001/1
0
2003/1
2005/1
2007/01
2009/01
Fig. 2 Imports and Import Prices of Frozen Skipjack and Yellowfin for
Canning in Bangkok, Thailand
SITUATION OF THE SASHIMI MARKET IN TOKYO, JAPAN
The value-added tuna sashimi demand in Japan constitutes the largest fresh, chilled, and
frozen tuna sashimi market in the world. Since 1987, more than half of the tuna sashimi
consumption in Japan has come from imports, as shown in Fig. 3. The annual total consumption
of fresh and frozen bigeye, yellowfin, bluefin and southern bluefin tuna in Japan exceeded
500,000 mt during most years at the 1989-2002 period. After that, the total consumption began to
shrink, reaching 350,000 mt in 2008 a 40% reduction relative to the peak years of 1993-1995.
34
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
Thousands mt
While the domestic sashimi grade tuna harvests in Japan have decreased since 1985, the
total imports to Japan increased from 1985 to 2002. In particular, the imports of yellowfin tuna
to Japan had already begun to exceed domestic supply in 1996. In 2002, total imports had grown
to be more than twice the level of Japanese domestic supply (Import Statistics in Japan, 2008).
Information on the efficiency of the pricing of yellowfin, bigeye, and the three species of bluefin
tuna, in the Japanese tuna sashimi market is of the most interest to all the tuna fishing countries
in the world.
700
Domestic Landings
Imports
600
500
400
300
200
100
0
1985
1990
1995
2000
2005
Fig. 3 Fresh and Frozen Bigeye, Yellowfin and Bluefin Tuna Supply in Japan
The market for wild captured tuna in Japan has experienced the price reduction trend
since the economic recession of the 1990s. Since then, the supermarket channels in Japan have
tended to attract customers by offering special discount for farmed bluefin tuna because it is
cheaper and the supply is stable. Imports of frozen southern bluefin tuna (SBT) in Japan have
increased dramatically from 1997-98; due to successful cage culture in Australia in the 1990s.
The southern bluefin price is very sensitive to the amount of imports. Import prices fluctuate
widely, with summer prices exceeding (sometimes tripling) winter prices, since the most of the
imports of frozen SBT in Japan taken place during August-November.
During 2002 to 2003, there was a 40% reduction in the SBT imports; however, the price
of SBT also experienced a 24% reduction, a strong indication from this is that there are plenty of
substitutes for the Japanese consumer to choose from, i.e., even though there was a shortage of
imported SBT in 2003, the price did not increase due to the availability of other sashimi grade
tuna species. However, in 2004, the quantity of imports increased 34% and import prices
decreased 30%, which means a downward trend on the import price from 2002-2007 can also be
also observed since the dramatically increasing in imports of frozen SBT (Sun, 2005). The
annual total consumption of fresh and frozen bigeye, yellowfin, Atlantic bluefin, Pacific bluefin,
35
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
and southern bluefin tuna reached a record high of 580 thousand MT in 1993 and then shrank to
349 thousand MT in 2008. A set of inverse demand system is required to estimate the price
flexibilities for each sashimi grade tuna species simultaneously.
Because of the scarcity of fresh bluefin tuna in Japan, substituting different tuna species
and alternating between fresh and frozen tuna is common (Yamamoto, 1994; Owen and
Troedson, 1994; Bose and McIlgorm, 1996). Bose and McIlgorm (1996) utilized cointegration
analysis to show that substitution of yellowfin and bigeye tuna for bluefin tuna clearly exists in
Japan. However, the price response to fluctuations in landings is not addressed, due to the limits
of the data.
Sun and Wang (1999) thoroughly investigated the monthly fresh tuna auction market
structure and the relationship between the major fresh tuna auction markets in Ping-Tung
County, Taiwan and the major fresh tuna auction markets in Tokyo, Japan. A multivariate
ARMA with seasonal adjustment factor models shows that a significant fresh tuna auction price
link between Taiwan and Japan.
Sun and Hsu (1998) and Sun and Chiang (1999) examined the price linkages of the
frozen yellowfin and bigeye tuna markets across three countries - Japan, Taiwan, and South
Korea, using the monthly auction fresh tuna price in 51 major fishing ports in Japan and various
import prices. Results show that the price series of yellowfin or bigeye tuna from Japan, Taiwan,
and South Korea all exhibit similar linear long run price change trends, and an error-correction
model to analyze the linkages among species and countries and to identify the efficiency of the
market.
Sun and Wu (2008), using the multivariate Markov-switching error-correction model,
shows that the import prices of frozen bigeye and yellowfin tuna in Japan have no significant
impact in causing the decreasing trend of the auction price of the frozen bigeye and yellowfin
tuna caught by the Japanese fleet during the 1990-2006 period. They found the auction price of
both frozen bigeye and frozen yellowfin tuna experience a structural change of the marketing
channels in Japan, such as the increase in the import of cage-cultured bluefin tuna and the
expansion of the supermarket channel in providing cheap sashimi-grade tuna since the 1990's.
Chiang et al. (2001) examined the impacts of inventories on tuna auction prices in Japan,
using the Rotterdam inverse demand system, and claimed that frozen tunas are more likely to be
close substitutes. Fresh and frozen tunas of the same species are also likely to be substitutes, and
inventory had significant impacts on auction prices. The consumers’ preference for sashimi
products seems to have changed in 1997 and 1998, in response to the result of the Asian financial
crisis. During this period of time, Japanese consumers shifted their demand toward cheaper
products, such as frozen yellowfin and bigeye, instead of expensive fresh/chilled sashimi-grade
tuna.
However, the dataset, that was used by Sun and Chiang (1999), Sun and Hsu (1998) and
Chiang et al. (2001), is compiled from the negotiated ex-vessel wholesale prices landed by
Japanese vessels in their major landing ports. Since most of the premier sashimi-grade tuna are
shipped daily from all over the world to Tokyo directly for auction, it would be more precise to
use the auction price in Tsukiji, the center metropolitan wholesale fish markets in Tokyo, to
capture the price flexibility to represent the tuna price response of Japanese consumers directly.
36
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
In addition, those high-quality sashimi-grade tuna that are auctioned in Tsukiji would
experience very high in storage fee, since there is no enough cold storage facility to hold the
inventory in Tokyo and the auction would usually continue until all the newly arrived tuna were
sold. Since the monthly auction price in Tsukiji would adjust more frequently to the landings
from all over the world, it would also justify the selected model specification of inverse demand
analysis.
INVERSE DEMAND SYSTEM MODEL
In a study of the price formation of fish, Barten and Bettendorf (1989) first developed a
Rotterdam inverse demand system (RIDS), using the direct utility function and Wold-Hotelling
identity. Barten (1992) compared the RIDS and almost ideal inverse demand system (AIDS),
along with two mixed models - one with Rotterdam-type price effects and AIDS-type income
effects and the other with AIDS-type price effects and Rotterdam-type income effects. A
synthetic direct model that combines the features of the latter four models and allows non-nested
hypothesis testing among models has also been proposed by Barten (1992). Brown et al. (1995)
specified a family of the general synthetic inverse demand systems (GSIDS), which includes two
flexible specifications: the RIDS and the almost ideal inverse demand system (AIIDS) that have
been proposed (Barten and Bettendorf, 1989) and the inverse demand system proposed by
Laitinen and Theil (1979), with a fourth variant. The GSIDS can be written as
wit d ln it = (hi -d1 wit) dlog Q + j (hij -d2 wit (δij -wjt)) d ln qjt
(1)
where subscript t represents time; it is the normalized price (it = pit/mt) of good i; with pit and
mt being the price and total expenditure, respectively; qit is the quantity of good i; wit = qitit is
the budget share of qit; d ln it = log(it/it-1); d ln qit = log(qit/qit-1); where δij = 1 if i = j, else δij =
0; and dlog Q = jwjt d ln qjt is the Divisia volume index. The scale flexibility is calculated as:
fi =hi / wi - d1
(2)
The compensated cross-price flexibility is calculated as
fij* = hij/w(i) - d2(δij - wj)
(3)
For simplicity, subscript t will be deleted in the following discussion. The above inverse-demand
system satisfies  hi  1  d1 and  hij  0 (adding-up) 3 ,  hij  0 (homogeneity), and
i
i
j

hij  h ji (Antonelli symmetry). Note that the adding-up condition
i
hi   i wi f i  1 is
based on the reference quantity vector or the reference quantity vector has a scale factor k = 1
(Anderson).
3
Note that
or

i
q
i
i i
 1;
therefore,
 (q d
i
i
i
  i dqi )  0 ,
wi d ln qi   i wi d ln  i .
37
or
 ( q (d
i
i i
i
/  i )  xi i (dqi / qi ))  0 ,
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
Barten and Bettendorf worked with a transformation of the H. Using the vectors h = [hi]
and w = [wi] they derived the counterpart of the Allais coefficients for the inverse demand
system. By selecting r and s as the standard pair of goods, the Allais coefficient for the inverse
demand system can be defined as
aij = hij/wiwj - hrs/wrws + (hi/wi – hr/wr) + (hj/wj – hs/ws)
(4)
In the definition of a = [aij], the subscripts r and s refer to a standard pair of goods r and s.
The above equation indicates that ars = 0. Thus aij > 0 indicates that i and j have the same type
interaction as r and s. Base on the Allais coefficient the measure of the intensity of interaction
can be defined as
αij = aij/(aiiajj)1/2
(5)
which for a negative definite matrix A = [aij], aij varies between –1 (perfect substitution) and +1
(perfect complementarity).
We can also obtain the other models and their flexibilities by restricting dl and d2
appropriately; i.e.,
dl = 0, d2 = 0 for the Rotterdam Inverse Demand System (RIDS) model;
dl = 1, d2 = 0 for the Laitinen-Theil model, known as Inverse Census Bureau of Statistics
(ICBS) Model
dl = 1, d2 = 1 for the Almost Idea Inverse Demand System model (AIIDS);
dl = 0, d2 = 1 for the RAIIDS model with RIDS scale effects and AIIDS quantity effects,
known as Inverse National Bureau of Research (INBR);
The restrictions above underlie the testing procedure to compare models.
RESULTS
A. Inverse Demand Analysis of the Major Tuna Cannery Market in Bangkok
The price response for frozen skipjack and yellowfin tuna, which are caught by the tuna
purse seine fishery, is analyzed based on the imports in the major tuna cannery market in
Bangkok, Thailand, during January 2001 to February 2010 (Table 1).
38
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
Table 1. Monthly Sample Statistics of the Tuna Cannery Market in Bangkok
Mean
Standard Error
Minimum
Quantity Sold (metric tons; mt)
Frozen Skipjack
43,994
13,033
19,273
Frozen Yellowfin Tuna
7,736
3,363
2,532
Average Auction Price ($/mt)
Frozen Skipjack
994
305
472
Frozen Yellowfin Tuna
1,388
316
755
Revenue Share
Frozen Skipjack
79.74%
7.41%
53.24%
Frozen Yellowfin Tuna
20.26%
7.41%
8.59%
Maximum
78,594
21,216
1,910
2,205
91.41%
46.76%
The GSIDS is utilized to identify the price response of skipjack and yellowfin tuna to
their landings in Thailand in a monthly basis. To account the natural logarithm of imports and
imports prices of both skipjack and yellowfin tuna are all non-stationary, the first difference were
taken in transforming the data as required to specify the differential inverse demand system.
The system-wide analog to the Wu-Hausman test was performed and the null hypothesis
of landings, which could be treated as exogenous in the IDS, is not rejected with CHISQ(2) of
4.2384955 and p-value of 0.12. Likewise, in testing for exogenenity in prices, the null hypothesis
of prices, which could be treated as exogenous in the DS, is rejected with CHISQ(2) of 4.980121
and p-value of 0.0829. Therefore, the specification of an inverse demand system is valid and a
set of 7 synthetic models and restricted versions IDS were estimated. Table 2 shows the
logarithmic likelihood values for each of the models. Based on the likelihood ratio test, only
Laitinen-Theil (CBS) and the synthetic IDS with free d1 and zero d2 models are not significantly
different than the synthetic model. The estimate of d1 for synthetic model with free d1 and zero d2
is equals 0.966106.
The corresponding inverse demand parameter estimates are shown in Table 3 and the
scale flexibility, own-quantity flexibility and uncompensated flexibility are estimated and shown
in Table 4. The imports price scale flexibility of skipjack and yellowfin tuna are -0.99 and -1.02,
respectively. These two numbers imply that both prices will reduce around 1% if the total
imports increase 1%. The uncompensated own-quantity flexibility of skipjack is estimated as 1.00 and is significantly different from zero, i.e., a 1% increase in skipjack imports would reduce
the import price by 1.00%. However, a 1% increase in yellowfin tuna imports would reduce the
import price of skipjack by 0.18 % only.
The constantly increasing exploitation rate of skipjack worldwide would push the
expansion of the canning industry in Thailand, but the total revenue for the fishing industry
would be offset by the proportionately reduction in price.
39
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
Table 2. Maximum likelihood test statistics
System
Synthetic
d1
1.26129*
(.448690)
RIDS
0
Laitinen-Theil (CBS)
1
AIIDS
1
RAIIDS (NBR)
0
free d1, zero d2
0.966106*
(.114144)
free d2, zero d1
0
d2
0.305322
(.429019)
0
0
1
1
0
Log Likelihood
Value (LLV)a
291.431
256.292
290.973
264.471
223.772
291.019
-0.86639*
285.197
(.115748)
a2*(LLV_LLV for the synthetic); degrees of freedom in parentheses.
b
Numbers in parentheses are standard errors of parameter estimates.
*
Statistically different from zero at 5% level.
Log Likelihood
Ratio Test
70.278* (2)
0.916 (2)
53.92*(2)
135.318*(2)
0.824 (1)
12.468*(1)
Table 3. Synthetic inverse demand parameter estimates for free d1 and zero d2
Antonelli Effect
Scale Effect
Frozen Skipjack
Frozen Yellowfin
Frozen Skipjack
-0.0229
-0.0028
0.0028
(0.0919)
(0.0044)
(0.0044)
Frozen Yellowfin
-0.0110
-0.0028
(0.0236)
(0.0044)
Numbers in parentheses are standard errors of parameter estimates.
*
Statistically different from zero at 1% level.
Table 4. Scale flexibility and uncompensated own-quantity and interaction flexibility
Scale
Uncompensated Flexibility
Flexibility
Frozen Skipjack
Frozen Yellowfin
Frozen Skipjack
-0.9948*
-0.999312*
4.53E-03
(0.0091)
(0.0088)
(0.0060)
Frozen Yellowfin
-1.0206*
-0.0027161
-0.017875
(0.0360)
(0.0973)
(0.0288)
Numbers in parentheses are standard errors of parameter estimates.
* Statistically different from zero at 1% level.
The uncompensated cross flexibility between skipjack and yellowfin tuna shows that
when imports of skipjack increase 1%, the imports prices of yellowfin tends to be reduced but
not significantly and the import price of skipjack is also not significantly influenced by the
imports of yellowfin tuna.
40
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
The price flexibility would then be utilized to simulate the derived demand of vessel day
scheme market for tuna purse seine vessels in the Western and Central Pacific by multiplying the
price flexibility with the marginal productivity of vessel day. The price of fish is directly
associated with fishers’ income, and income to fishers (and in turn, the dynamics of the fleet)
might be influenced by both the availability of resources and price levels. This research advances
our understanding of the dynamics of global tuna fisheries by providing a vital bridge between
human and natural elements in support of an ecosystem approach to management.
B. Inverse Demand Analysis of the Tuna Sashimi Market in Tokyo, Japan
Table 5 shows the bluefin, bigeye, and yellowfin tuna accounted for 57.7%, 38.9% and
3.4% of the revenue from all tuna sold at Tsukiji wholesale fish markets, respectively, during
January 2002 through February 2009. During this period the averaged tuna auction quantity in
Tsukiji was about 5,000 tons per month, represents roughly 25% of the total consumption in
Japan. Such as shown in Fig. 4 and 5, the sales of frozen bluefin tuna account for the major
source of the sale and its price experienced a clear seasonality.
Table 5. Monthly Sample Statistics of Tuna Sashimi Market in Tokyo, Japan
Mean Std. Err. Minimum Maximum
Quantity Sold (metric tons)
Fresh Yellowfin
120
123
9
677
Frozen Yellowfin
241
91
95
527
Fresh Bigeye
286
74
137
609
Frozen Bigeye
2,671
414
1,815
3,699
Fresh Bluefin
400
125
212
778
Frozen Bluefin
1,346
387
599
2,553
Average Auction Price (Yens/kilogram)
Fresh Yellowfin
868
207
459
1,496
Frozen Yellowfin
652
111
466
874
Fresh Bigeye
1,553
202
869
1,961
Frozen Bigeye
873
76
760
1,052
Fresh Bluefin
3,203
587
1,829
4,300
Frozen Bluefin
2,224
382
1,457
3,285
Revenue Share
Fresh Yellowfin
1.27%
0.99%
0.14%
4.09%
Frozen Yellowfin
2.16%
0.67%
0.95%
3.83%
Fresh Bigeye
6.21%
1.39%
3.23% 11.26%
Frozen Bigeye
32.67%
2.08%
27.21% 38.03%
Fresh Bluefin
17.33%
3.06%
10.54% 29.87%
Frozen Bluefin
40.37%
3.43%
31.73% 49.02%
41
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
Bluefin Frozen
Bluefin Fresh
BET Frozen
BET Fresh
YFT Frozen
YFT Fresh
8
Thousand mt
7
6
5
4
3
2
1
0
1-Jan-02
1-Jan-04
1-Jan-06
1-Jan-08
Fig. 4 Tuna Sales at Tsukiji central market
5,000
Price (Yen/Kg)
4,500
Bluefin Frozen
Bluefin Fresh
BET Frozen
BET Fresh
YFT Frozen
YFT Fresh
4,000
3,500
3,000
2,500
2,000
1,500
1,000
500
0
1-Jan-02
1-Jan-04
1-Jan-06
1-Jan-08
Fig. 5 Tuna wholesale price at Tsukiji Central market in Tokyo, Japan
42
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
Table 6. Maximum likelihood test statistics of Inverse Demand Tuna Sashimi
Market in Tokyo, Japan
Log Likelihood Log Likelihood
System
d1
d2
Value (LLV)a
Ratio Test
Synthetic
0.593***
0.459***
1418.880
(0.1623)
(0.0329)
RIDS
0.000
0.000
114.880***(2)
1361.440
Laitinen-Theil (CBS)
1.000
0.000
91.600***(2)
1373.080
AIIDS
1.000
1.000
164.900***(2)
1336.430
RAIIDS (NBR)
0.000
1.000
145.080***(2)
1346.340
free d1, zero d2
1.124***
0.000
91.320***(1)
1373.220
(0.2124)
free d2, zero d1
0.000
0.459***
-2.400 (1)
1420.080
(0.0329)
a 2*(LLV-LLV for the synthetic); degrees of freedom in parentheses.
b Numbers in parentheses are standard errors of parameter estimates.
***Statistically different from zero at 1% level
The GSIDS is utilized to identify the price response of six types of tuna to their quantity
in Tokyo in a monthly basis. To account the natural logarithm of the auction prices of all types of
tuna are all non-stationary, the first difference were taken in transforming the data as required to
specify the differential inverse demand system.
The specification of an inverse demand system for a set of 7 synthetic models and
restricted versions IDS were estimated. Table 6 shows the logarithmic likelihood values for each
of the models. Based on the likelihood ratio test, the synthetic IDS seems to fit our data the best,
since its log likelihood value is significantly higher than all the other IDS; however, the
estimated elasticities of the synthetic model won't promise a consistent estimates if different
product is omitted from the system while estimating. The same problem happens to AIIDS and
RAIIDS, and the synthetic model with free d2 and zero d1.
There are different assumptions on demand parameters – the Rotterdam assumes fixed
demand parameters (i.e., marginal propensity to consume (MPC) and Slutsky coefficients are
fixed parameters) and the AIDS assumes variable demand parameters (MPC is a function of
budget share and Slutsky is a function of budget shares and scale coefficients. Therefore, even if
the likelihood function value for the synthetic model is significantly higher than the Rotterdam
and Laitinen-Theil CBS, the resulting demand parameters (MPC and Slutsky) may suggest the
AIDS and NBR are not the best models to use – the high likelihood values only suggest
goodness of fit, but not theoretically sound.
Only if the d2 is set as 0, the regression result won't be affected by choosing which
commodities to omit during estimation. Hence, the Laitinen-Theil (CBS) is preferable to have
the estimates of flexibilities make sense. The log likelihood value of the Laitinen-Theil inverse
demand is not significantly different than the synthetic model with free d1 and zero d2 and its
demand parameter estimates are shown in Table 7 and its scale flexibility, estimates of its ownquantity flexibility and uncompensated flexibility are shown in Table 8.
43
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
The results of the Laitinen-Theil CBS Inverse Demand model, is shown in Table 8. All of
the own-quantity price flexibilities of each species are all significantly less than zero and are all
less than their corresponding scale flexibility, the consideration of the impact of the total supply
of all of the six sashimi tuna on the price of each species would be necessary.
For the sashimi market in Tokyo, both fresh and frozen bluefin tuna show less than unity
in absolute value for their scale flexibilities, which indicates these goods are considered as
luxury, i.e., if the supply of all sashimi-grade tuna species increased by 1% and they would have
less than 1% decrease in prices. Since the bluefin tuna prices are less responsive to the changes
of the supply of all tuna species, it means that the Japanese consumers are still willing to pay
premium prices for high-quality fresh and frozen bluefin tuna than that for the other tuna species.
There is no incentive for suppliers of bluefin tuna to cooperate to reduce their supply from either
wild caught or cage-cultured bluefin tuna because this would result in reduction in their total
revenue.
Fluctuation in the auction prices of fresh and frozen bluefin tuna would confirm the price
responses to the availability of landings of that species. Consumers prefer high fat content, and
cage-cultured bluefin tunas are often thought to have a higher fat content. Wild bluefin is quite
variable in fat content, whereas farmed bluefin is fattened in a more predictable way.
For the sashimi-grade bigeye and yellowfin tuna, their scale flexibilities are identified to
be greater than unity and are referred as necessities which would be less preferable than bluefin
tuna and its price would decline more than proportionately as consumption of all goods in the
bundle increases. We would predict a negative impact on total revenue induced by the result of
an intense race for fish, or derby, which would imply a more than proportionately decrease in
prices.
Hence, if fishermen could act collectively to adjust their operation cost through a quotatrading mechanism monitored by the tuna RFMOs, fishermen could get the capability to help
conservation by avoid overcapacity and the derby effect. It would be beneficial for the fishing
industry to realize that a better marketing distribution scheme for yellowfin and bigeye tuna
would increase their total landings values, even if a fishing quota for these tunas are strained due
to conservation measures. The estimated scale flexibility could help to support the economic
benefit of global quota management control and the impact of changes in fishing capacity upon
the value of the total landings.
Based on the Allais coefficients that measure the intensity of interaction, the positive
Allais coefficient indicates that i and j have the same type interaction as fresh bigeye and frozen
bluefin tuna. Results indicate that bigeye and yellowfin tunas are more likely to be close
substitutes of each other; fresh and frozen tunas of the same species are also likely to be
substitute, as the same type interaction as fresh bigeye and frozen bluefin tunas.
44
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
Table 7. Laitinen-Theil inverse demand parameter estimates
Scale
Antonelli Effect
Fresh
Frozen
Fresh
Frozen
Fresh
Effect
Yellowfin
Yellowfin
Bigeye
Bigeye
Bluefin
Fresh Yellowfin
-0.004
-0.005***
-0.001
-0.001
0.005***
0.000
(0.003)
(0.001)
(0.000)
(0.001)
(0.001)
(0.001)
Frozen Yellowfin
-0.006*
-0.004***
0.001
-0.003
0.003*
(0.004)
(0.032)
(0.001)
(0.002)
(0.001)
Fresh Bigeye
0.000
-0.020***
0.002
-0.001
(0.007)
(0.002)
(0.004)
(0.002)
Frozen Bigeye
-0.065***
-0.154***
0.040***
(0.015)
(0.009)
(0.005)
Fresh Bluefin
0.048***
-0.059***
(0.006)
(0.006)
Frozen Bluefin
0.027
(0.017)
Numbers in parentheses are standard errors of parameter estimates.
*,**, and *** represent the estimate is statistically different from zero at 10%, 5% and 1% level, respectively.
45
Frozen
Bluefin
0.001
(0.001)
0.005***
(0.002)
0.020***
(0.003)
0.111***
(0.006)
0.017***
(0.005)
-0.154***
(0.007)
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
Table 8 Laitinen-Theil inverse demand scale, own-quantity flexibilities, and Allais interaction intensity coefficients
Allais interaction intensity a46 = 0
Flexibility
Scale
Fresh Yellowfin
Frozen Yellowfin
Fresh Bigeye
Frozen Bigeye
Fresh Bluefin
Frozen Bluefin
-1.364***
(0.278)
-1.285***
(0.171)
-1.005***
(0.106)
-1.200***
(0.046)
-0.726***
(0.087)
-0.932***
(0.042)
Ownquantity
-0.397***
(0.041)
-0.195***
(0.037)
-0.319***
(0.036)
-0.475***
(0.027)
-0.333***
(0.034)
-0.381***
(0.018)
Fresh
Yellowfin
Frozen
Yellowfin
-1.000
-0.177*
(0.095)
-1.000
46
Fresh
Bigeye
-0.137*
(0.072)
-0.074
(0.096)
-1.000
Frozen
Bigeye
-0.009
(0.057)
-0.323***
(0.065)
-0.216***
(0.064)
-1.000
Fresh
Bluefin
-0.093
(0.067)
-0.011
(0.081)
-0.163***
(0.069)
0.025
(0.064)
-1.000
Frozen
Bluefin
-0.107***
(0.038)
-0.099***
(0.037)
0.041
(0.043)
0.000
(0.000)
-0.073
(0.063)
-1.000
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
CONCLUSION AND DISCUSSION
The purpose of this study is to examine the price flexibility of the skipjack and yellowfin
tuna in Bangkok's frozen tuna markets and the sashimi grade tuna in Tokyo, Japan. The price of
fish is directly associated with fishers’ income, and income to fishers (and in turn, the dynamics
of the fleet) would be influenced by both the availability of resources and price levels. This
research advances our understanding of the dynamics of global tuna fisheries by providing a vital
bridge between human and natural elements in support of a welfare evaluation approach to
management.
First, by using the GSIDS, the long-run own price flexibility of skipjack and yellowfin
tuna in Bangkok are -0.99 and -1.02, respectively. The uncompensated own-quantity price
flexibility of skipjack is estimated about unity and is significantly different from zero, i.e., a 1%
increase in skipjack imports would reduce the import price by 1%. Since it is the major global
skipjack market for tuna purse seine vessels, the skipjack price flexibility could be utilized to
simulate the derived demand of vessel day in western and eastern Pacific Ocean for tuna purseseine vessels by multiplying the price flexibility with the marginal productivity of vessel day.
Second, the GSIDS is also utilized to identify the price response of six types of tuna to
their quantity in Tokyo on a monthly basis. The results of the Laitinen-Theil Inverse Demand
model indicate that both fresh and frozen bluefin tuna show less than unity in absolute value for
their scale flexibilities, which means that the Japanese consumers are willing to pay premium
prices for high-quality fresh and frozen bluefin tuna; furthermore, their prices are less responsive
to the changes of their quantities than they are for the other tuna species when the supply
changes. A 1% reduction of quantities caused by quota control would imply a more than 1%
increase in prices, which would have a positive impact on total revenue. For sashimi-grade
bigeye and yellowfin tuna, their price flexibilities are identified to be greater than unity and
would predict a positive impact on total revenue if there is a 1% increase of quantities supplied
and they would have less than 1% decrease in prices.
Due to Japan's weak economy, consumers might switch toward cheaper fish; however,
the relation between price and landings might be affected only slightly, since the yen has been
much more stable than other currencies. In fact, this crisis perhaps even helped Japanese
consumers in terms of this market. Regardless of trends in the Japanese market, demand will
gradually trend upwardes, Chinese and European buyers' demand is increasing.
The success of quota control also is influenced by the possibility that fewer fish could
ensure higher profit. If a fisherman could take his boat out when the price is right, the net present
value of the fishery resources in the long run would be maximized. There is a clear and present
need to utilize the revenue-cost survey of longline fisheries to analyze their economic response to
the market and to evaluate the factors that influence their entry/exit behavior in the long run.
The growth of the global tuna industry is nonetheless limited by the future state of natural
stocks of skipjack, yellowfin, bigeye, bluefin or albacore exploited by the longliners, purseseiners and pole-and-liners fishing in the three major oceans. Many tuna stocks around the world
are fully if not over-exploited. In particular, the sustainable use of the natural resources is
47
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
jeopardised by the presence of considerably IUU fishing and the lack of long-term management
and property-right regimes proposed by the RFMOs.
Because the price of crude oil skyrocketed from 2004 to present, peaking at $147 a
barrel, the tuna longline and the purse-seine industry total costs increased about 20%, which
challenged the profitability of the both tuna industry. The price of oil increased by 113.7% from
2003 to 2006; however, the frozen skipjack and yellowfin tuna prices in Bangkok rose only by
16.4% and 13.4%, respectively, which is lower than what the world oil price had experienced.
With bearing in mind that high oil prices results in high fishing costs also for the coastal purseseine industry.
This project studies the global economics of the tunas with a view to determining the
effects that how's the market might response to quota control and natural factors have on their
demand. By collecting global tuna market demand information, the market situation is captured
by identifying the price flexibility in major international tuna markets. The findings of the
research would help to design an appropriate conservation measures so that to optimize the
economic revenue while the stocks of fish can be maintained at levels. Anticipating the future
decline or rise of the quota caused by the biomass change could help fishery managers adjust
their decisions given the expected harvest in the long run and offer a framework for a derivative
commodity market for tuna products. Auction price in Tokyo is very different from the ex-vessel
negotiated landing price. The problem of price distortions is not yet included in analysis to look
at price volatility/flexibility from the consumers' perspective.
One of the most pressing issues is whether such exogenous shocks may re-localize
markets, or conversely, whether those shocks may be instantaneously transmitted to the global
tuna market, affecting the strategies of fishing companies. Other external inputs such as energy
costs may also have serious impacts on fishing strategies and long-distance international trade
flows. Furthermore, this study could be further expanded to include a framework evaluating the
effects of ENSO (El Niño/Southern Oscillation) cycles on biomass and landings. Anticipating
fluctuations in biomass abundance caused by the ENSO cycles could help investors and fishery
managers make sound decisions about expected tuna harvests despite an uncertain environment.
The findings of this research will promote advancements in understanding the ecosystem
dynamics of global tuna fisheries by providing a set of knowledge and management tools that
bridge of connecting the dynamics of fishery markets with the changes in the ecosystem and
management.
REFERENCE
Barten AP, Bettendorf LJ. 1989. Price formation of fish: An application of an inverse demand
system. European Economic Review 33:1509-1525.
Bertignac, Michel Harry F. Campbell, John Hampton, and Anthony J. Hand. 2000. Maximizing
Resource Rent from the Western and Central Pacific Tuna Fisheries, Marine Resource
Economics. 15(3): 151-177.
Bose, S., and A. Mcilgorm. 1996. Substitutablity Among Species in the Japanese Tuna Market:
A Cointegration Analysis. Marine Resource Economics. 11:143-155.
Brown, Mark G., Jonq–Ying Lee, and James L. Seale Jr. 1995. A Family of Inverse Demand
Systems and Choice of Functional Form. Empirical Economics. 20(3): 519–30.
48
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
Clements, M.P. and H.M. Krolzig, (2002), ―Can Oil Shocks Explain Asymmetries in the US
Business Cycle,‖ Empirical Economics, 27(2), 185–204.
Clements, M.P. and H.M. Krolzig. 2003. Business Cycle Asymmetries: Characterizing and
Testing Based on Markov-Switching Autoregression, Journal of Business and Economic
Statistics, 21(1), 196–211.
Chiang, Fu-Sung, Jonq-Ying Lee and Mark G. Brown. 2001. The Impact of Inventory on Tuna
Prices: An Application of Scaling in the Rotterdam Inverse Demand System, Journal of
Agricultural and Applied Economics, 33(3): 403-411.
Dickey, D.A. and W.A. Fuller. 1979. Distribution of the Estimate for Autoregressive Time Series
with a Unit Root, Journal of the American Statistics Association, 24:427-431.
Dickey, D.A. and W.A. Fuller. 1981. ―Likelihood Ratio Statistics for Autoregressive Time Series
with a Unit Root, Econometrica, 49:1057-1072.
GLOBEFISH. 2008. Tuna Commodity Update, Food and Agriculture Organization of the United
Nations.
Hamilton, J.D. 1989. A New Approach to the Economic Analysis of Nonstationary Time Series
and the Business Cycle, Econometrica, 57(2), 357–384.
Hansen, B.E. 1992. The Likelihood Ratio Test under Nonstandard Conditions: Testing the
Markov Switching Model of GNP, Journal of Applied Econometrics, 7(0), S61–S82.
Hansen, B.E. 1996. Erratum: The Likelihood Ratio Test under Nonstandard Conditions: Testing
the Markov Switching Model of GNP, Journal of Applied Econometrics, 11(2), 195–198.
Japan Tariff Association. 2010. Japan Exports and Import Statistics. Edited by Customs and
Tariff Bureau, Ministry of Finance, Japan.
Jeon, Y., C. Reid, and D. Squires. 2008. Is There a Global Market for Tuna? Policy Implications
for Tropical Tuna Fisheries, Ocean Development and International Law, 39(1), pp. 3250.
Jiménez, Toribio R., P. Guillotreau, R. Mongruel, 2009, Global Integration of European Tuna
Markets, Progress in Oceanography.
Laitinen, K, H. Theil. 1979. The Antonelli Matrix and the Reciprocal Slutsky Matrix. Economic
Letters, 3:153-157
McGowan, Michael. 2008. Market and Cannery Overview, Western and Central Pacific
Fisheries Commission, WCPFC5, December 8-12.
Owen, A.D., and D.A. Troedson. 1994. The Japanese Tuna Industry and Market, The Economics
of Papua New Guinea’s Tuna Fisheries. Australian Centre for International Agricultural
Research (ACIAR) Monograph No. 28:231-238.
Miyake, Peter M., Patrice Guillotreau, Chin-Hwa Sun, Gaku Ishimura. 2010. Recent
Developments in Tuna Industry: Stocks, Fishery, Management, Processing, Trade and
Markets, FAO Fisheries and Aquaculture Technical Paper. No. 543. Rome, FAO. 125p.
Majkowski, Jacek. 2007. Global fishery resources of tuna and tuna-like species, FAO Fisheries
Technical Paper 483, Food and Agriculture Organization of the United Nations.
Pan, Minling and Chin-Hwa Sun, 2009, Structural Breaks and Price Linkage between Hawaii
and Japanese Tuna Sashimi Markets, PICES Annual Meeting, Oct. 23- Nov. 1, Jeju, Korea.
Sun, Chin-Hwa and W-H Hsu. 1998. Analysis of the Price Cointegration across Different
Countries for the Frozen Tuna Sashimi Market in Japan, Selected Paper of the Ninth
International Conference of the International Institute of Fisheries Economics and Trade,
Tromso, Norway.
49
Task II: Inverse Demand Analysis
Global Tuna Demand and Fisheries Dynamics in the EPO
Sun, Chin-Hwa and Wei-Tsung Wang. 1999. Forecasting Analysis of the Fresh Tuna Prices in
Taiwan and the Import Prices in Japan: An Application of Vector ARMA Model, Journal
of Agricultural Economics, 66: 49-84.
Sun, Chin-Hwa. 1999. Analysis of the Market Structure and Price Cointegration of the Tuan
Raw Material Markets for Tuna Canneries in the World, Agriculture and Economics, 22:
51-72.
Sun, Chin-Hwa. 2004. Selection of The Decision Rules of Management Procedures for Southern
Bluefin Tuna, Third Management Procedure Workshop, Commission for Conservation of
Southern Bluefin Tuna (CCSBT), 19-24 April 2004, CCSBT-MP/0404/07, Busan,
Republic of Korea.
Sun, Chin-Hwa, 2005. An evaluation of the TAI candidate management procedure rules for
southern bluefin tuna based on the updated reference set and robustness trails, the fourth
meeting of the Management Procedure Workshop, Canberra, Australia, 16-21 May 2005,
CCSBT-MP/0505/08, pp.1-29.
Sun, Chin-Hwa, Lin, C. 2007. Evaluation of the TAI_decision rules of the management procedure
of total allowable catch of southern bluefin tuna, Taiwan Economic Forecast and Policy,
37(3):55-82.
Sun, Chin-Hwa and Ming-Chia Hsieh. 2000. Analysis of the Price Response of Taiwan Tuna
Purse Seine Fishery in the Frozen Tuna Raw Material Market in Thailand, Journal of
Fisheries Society of Taiwan, 27(1): 45-58.
Sun, Chin-Hwa. 1999. Analysis of the Market Structure and Price Cointegration of the Tuan Raw
Material Markets for Tuna Canneries in the World, Agriculture and Economics, 22: 51-72.
Yamamoto, T. 1994. Japan’s Tuna Market Today, INFOFISH International (March/April):18-22.
50
TASK III: REPORT OF THE WORKSHOP
Global Tuna Demand and Fisheries Dynamics in the EPO
Task III
Executive Summary of International Workshop on
Global Tuna Demand, Fisheries Dynamics and
Fisheries Management in the Eastern Pacific Ocean
1. Opening
Dr. Guillermo A. Compeán, Director of the Inter-American Tropical Tuna Commission
(IATTC), the organization hosting the Workshop, welcomed the participants.
He stated that the IATTC and the Project are grateful to the Pacific Islands Fisheries Science
Center (PIFSC) and Southwest Fisheries Science Center (SWFSC), both of which strongly supported
the organization of the Workshop and provided significant in-kind contributions (see Programme of
the Workshop in Appendix I). He expressed particular thanks to:
• the IATTC as the host of the Workshop and its Director and other staff members for
making the arrangements for the Workshop; and
• the PIFSC, which financed the Project that organized the Workshop.
He also offered his condolences to the family and friends of Dr. James Joseph, Director of the
IATTC from 1969 to 1999, who died suddenly on December 16, 2009. Dr. Joseph was an inspiration
to a series of right-based management workshops hosted by the IATTC. Dr. Compeán asked the
participants to observe 3 minutes of silence in mourning the passing of Dr. Joseph, which was a
tremendous loss, not only to his family and to his myriad of friends and colleagues, but also to
fisheries science and conservation.
As Convener of the Workshop and a visiting scholar in IATTC, Dr Chin-Hwa Jenny Sun,
described logistic arrangements for the meeting and thanked the participants for:
• securing funds for their travel to La Jolla; and
• the substantial technical work preparatory to the Workshop, which was completed in a
timely manner.
Dr Sun indicated that four sub-sessions were envisaged, with 20 presentations of country
reports and case studies on related topics, and she was looking forward to the participation of all the
attendees at the Workshop, which would allow these subjects to be fully discussed. The letter of
invitation, an outline of the program, the list of participants,, the second background discussion
paper, and abstracts of presentations are indicated in the REPORT OF WORKSHOP as Appendices
I, II, III, IV, and V, respectively. In addition, the Workshop website, which was constructed to
include a full set of information, was made available to all invited participants before the Workshop.
51
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
2. Introduction of participants
The Chairman asked the participants at the Workshop to introduce themselves, indicating
their institutional affiliations. These are listed in Appendix III.
3. Overview of the Workshop and its implementation
This Workshop brings together scientists from the major fishing nations, Regional Fishery
Management Organizations (RFMOs), non-governmental organizations (NGOs), and other involved
parties to review current tuna purse-seine and longline fleet dynamics, global tuna markets, and
management strategies in the eastern Pacific Ocean (EPO). A special keynote address, ―Tuna Fleet
Dynamics and Capacity Overview in EPO,‖ was delivered by Dr. Guillermo A. Compeán, Director
of the IATTC, and two background paper were presented to show the simulated effects of various
effort reduction programs on the spawning biomasses of bigeye and yellowfin tuna in the EPO.
The 12 invited experts and 2 external discussants from the field of EPO tuna stock
assessment, the global market situation, demand modeling, and industry development of the major
tuna purse-seine and longline fisheries in the USA, Ecuador, France, Spain, Japan, the Republic of
Korea, and Taiwan delivered a total of 7 country fleet dynamics reports and 13 case study
presentations.
Four sub-sessions were envisaged, with a total of 20 presentations, are included in the LIST
OF PRESENTATIONS as case studies of related topics. The sessions were chaired by the following
invited participants:
Subsession I. Tuna Fleet Dynamics and Capacity Overview (Chair: Peter Miyake)
Subsession II. Stock Assessment and Fishery Management in the EPO (Chair: Mark N. Maunder)
Subsession III. Tuna Fishing Capacity and Fishery Dynamics (Chair: Dale Squires)
Subsession IV. Estimation of Global Tuna Demand (Chair: Jenny Sun)
(a) Case Study of Canned Tuna Trade and Markets
(b) Case Study of Tuna Sashimi Trade and Markets
In addition, the upcoming FAO Technical Paper 543 regarding the recent developments in the
tuna industry stocks, fisheries, management, processing, trade, and markets, was introduced. It could
be found on the FAO website in pdf or zip format at the following
link: http://www.fao.org/docrep/013/i1705e/i1705e00.htm.
The aim of the Workshop was to ensure that the tuna populations are protected from
overfishing, to facilitate work with local communities to develop good management policies, and to
create economic incentives for sustaining the global ecosystems for the benefit of the people who
depend on them.
The fact that there are multiple species, nations, markets, and product types is intimidating.
This Workshop attempts to encourage researchers to cooperate and to make progress in determining
how to evaluate the impacts of alternative fishing management policies in order to maximize the
joint production welfare. The research focus might be different in different countries, but this is a
process, and processes provide stimulus for further exploration.
52
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
4. Summary and Discussion
The comments regarding Discussion Paper No. 1, the replies to those comments, and the discussion
regarding policy implications of the estimation of the global tuna demand during the Workshop are
summarized as follows:
4.1 Comments and Reply on the Discussion Paper No. 1
Commentator: Christopher D. Stone, University of Southern California Law School
This is an excellent, provocative paper. Even if there is, typical of empirical efforts in their
mid-stages, room for methodological criticisms, the paper lays down a challenge to tuna harvest
governance that cannot be ignored.
While it is not stated explicitly, I assume that the inspiration for the authors’ analysis is the
IATTC’s proposal to reduce tuna catch in the EPO 20.5% across the board, i.e., not differentiating
sectors. Examined as a matter of diplomacy, a pro rata cutback must have the appeal of a path of
least resistance, inasmuch as the different gears are associated with different nations (members of
IATTC). But viewed in its economics aspects, an across-the-board measure is unlikely to be
efficient (in the absence, at least, of a mechanism enabling redistribution of entitlements). Indeed,
the pro rata outcome would be the efficient solution only in the improbable limiting case in which
every fisher’s catch value per unit effort was exactly equal.
But marginal value of production per unit of effort is not equal. At the heart of the authors’
argument is that tuna fishing in the EPO is divided, as defined by gear, into two sectors: purse-seine
operations on the one hand and longline effort on the other. The purse seiners that set on floating
objects (a sub-set of the purse seiners) harvest a high percentage of bigeye tuna (BET) at a juvenile
stage (and also immature yellowfin). The longline fleets, by contrast, catch a high percentage of
mature BET. Each mature BET sells for more than a juvenile, not only in terms of price-per-fish, but
even in price per pound (the meat of the larger fish being more desirable.)
This observation leads to the question: What allocation of effort provides value-maximizing
revenues? The authors follow the IATTC in assuming that the ―safe‖ target equilibrium requires
maintenance of a 19% spawning biomass ratio (SBR), that is, the ratio of the current spawning
biomass, S, to the spawning biomass of the unexploited stock, So. But the even-handed (50-50)
cutback by gear is not the only allocation that would meet the SBR = 0.19 constraint. There are
presumably infinite solutions within that line, of which the authors model four cases, denominated A,
B, C and D in Figure 9.
In Case A (I’ll call it ―business as usual‖), the efforts of both the PS and LL vessels continue
unabated. Note that the present course is upward heading originally, reflecting the continued
excessive effort, and then declines.
Case B is the IATTC proposal. Both LL and PS vessels reduce their effort by 20.5% (to 0.79.5% of
the 1980 effort). The revenue is superior to Case A.
53
Landings Value (Millions $)
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
600
500
400
Case A (PS=1, LL=1)
Case B (PS=0.795, LL=0.795)
Case C (PS=0.737, LL=1)
Case D (PS=1, LL=0.133)
300
200
100
2008
2010
2012
2014
2016
2018
Figure 9 Trajectory plot of total landings value of bigeye under Case A, B, C and D
with different floating objects purse-seine (PS) and longline effort (LL) levels
relative to effort levels in 2008 while holding the bigeye tuna SBR as 0.19
In Case C (see graph in the right), by contrast, the
longline effort is capped at the 2008 level (―1‖),
but the purse -seiner effort is restrict to a level of
0.737. The stock equilibrium remains stable. The
purse-seiners come out worse than under Cases A
and B, facing decreases in catch of $3 million, $11
million, and $8 million in bigeye, yellowfin, and
skipjack, respectively. But the longline fleet,
exploiting the more mature fish, adds $58 million
in landings of bigeye tuna and $57 million in
yellowfin. Hence, the increase in revenue to the
longline fishery—$115 million—far exceeds the
decrease in revenue to the purse-seine fishery—
$22 million.
net benefits
Case C > Case B
BET
$58
Case
B
$3
YFT
SKJ
$93
SBRBET = 19%
LL = 1.000 (2008)
PS = .737 (2008)
Net = $93 million
[Values disregard
price elasticity to
supply]
$57
$11
$8
Case D, just for comparison, reverses the assumptions of Case C. The purse-seiners continue their
effort at the 2008 level, while the longliners provide the reduction (to 0.133) that the target
equilibrium requires. This turns out to be the worst case of all. Clearly, of the four cases, Case C
dominates.
This raises an important policy issue: can we conclude that if purse seiners were to reduce
their catches, long-liners would be able to, and would, increase theirs, more economically shifting to
the mature cohorts, without any increased pressure on the stock?
One useful way to put their finding is that:
―a 1% reduction in purse-seine effort on tunas associated with floating objects (roughly 84
sets), would sustain an increase in longline effort sufficient to increase the longline catch by
1,170 tons. This implies a reduction of 300.6 tons in the catch of juvenile bigeye, which
would increase the total value of the catch by $10.74 million.‖
No one supposes the purse seiners, being distinct fishers, would graciously step aside. But
the prospect of side payments presents itself:
54
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
―One ton of bigeye tuna not caught in the purse-seine fishery would contribute a $36,878 gain
in revenue for longline fishery and the total bigeye tuna landings value would increase to
$35,340 after providing $1,540 compensation to the loss of purse-seine's big-eye tuna
landings value.‖
Indeed, once we set out on this track, why stop at a modest percentage decline? The authors’
most striking claim is a sort of Case E, that (were it politically possible) the gains to the long liners
from a total shut-down of the set-on-floating objects tuna fishery would more than offset the losses to
the purse seiners of the foregone BET and yellowfin and skipjack tuna.
Critique
Assessing a paper of this sort is difficult, particularly for a lawyer untrained in the
technicalities both of substance and technique. My overall impression is that, in my own
terminology, the authors have put the burden of proof on the critics.
There are several assumptions that deserve further conversation. I recite them in no particular
order.
(1) The target biomass. The authors accept SBRBET = .19. I wonder if allowance for (a) a
precautionary approach and (b) an ecosystem approach (accounting for the lost value of nontarget elements of nature) ought not dictate a more stringent constraint that the conventional
MSEY or MSBY measures.
(2) Fishery dynamics. It is not necessary for the authors to demonstrate that a particular fish forgone
by the purse seiners will reappear, mature, on a LL hook. It is enough to show that the foregone
fish, added to the biomass, will permit (subject to the SBR constraint) and enable additional catch
of mature fish. But that appears to assume, as the authors say, that the EPO stocks are well
enough mixed that a fish left in the biomass by withdrawal of purse-seine effort will reappear in
the biomass exploited by longliners. A (juvenile) fish on the deck may be worth two (mature) in
the sea.
(3) Management. The authors further assume that the purse-seine and longline fisheries could be
managed in such a way that the spawning biomasses of the two species are maintained at
optimum levels. I think the simplifying assumption is well warranted; however, at some point of
developing the paper’s rich ideas, it may be appropriate to introduce management effectiveness
as a variable. For example, if ideal policy entails a restriction on purse-seined BET caught on
object sets, but not otherwise, how practical is the distinction as a matter of monitoring and
enforcement?
(4) Costs. The authors model alternative revenue streams. It would be more satisfactory to review
estimates of net revenues, if the authors can come up with them. The rise of purse-seining may
reflect lower costs—perhaps in part, as was suggested (Squires), because BET capture brings
along an associated catch as a joint product. In addition, I suspect that producing ―costs‖ will be
complicated by subsidies: can we get our hands on ―real‖ costs, cropping away the ubiquitous
government supports? Would special corrections be required if it turned out that the nations
fostering one gear type were more heavily subsidizing than the nations behind the other gear?
(5) Product prices. There are at least two price issues. The authors price mature bigeye at $36,878 a
ton, the juvenile at $1540. First, I am not certain where the prices are drawn from. One
participant (Miyake) noted that if the prices were drawn from Tsukiji auctions, the mature BET
55
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
prices would be considerably higher than average (because of the premium quality of tuna
auctioned in that market. Second, the model does not account for elasticity of price to supply;
one would expect a material increase in BETs to reduce the price and thereby the estimates of
revenues.
(6) Discount. The authors base their paper on the higher value of BET that are mature. This argues,
as they say, for deferring catch of any cohort for an additional period—perhaps 3-5 years. One
participant (Squires) notes any suspension in the conversion of fish to cash invites some
corrections for discount: deferring catch foregoes the investment value of the funds that catch
would produce for the period of suspension. One might want to know how the growth rate of the
economy, i, compares with the economic growth rate of the fish.
(7) Exploiting the potential cooperative surplus. Assuming the validity of the price figures, and the
posited fishery dynamic, each ton of BET foregone in the PS fishery increases the revenue from
the stock. Viewed as a single entity, by $35,340: $36,878 in revenue from the mature fish minus
the $1,540 opportunity cost of the ―lost‖ juvenile (minus also the ―saved‖ expenses of the PS
fleet’s efforts). This difference, the authors point out, provides an opportunity for efficient
outcome side-payments. They suggest that the LLs can pay the PSs $1,540 to forego the
juveniles, and still come out $35,340 ahead. I think this is a dramatic and excellent way to
illustrate the potential. Even if the cooperative surplus, rightly tinkered with, is half that figure ,
there is still robust room for a Pareto-efficient outcome through PS-LL negotiations. I would
only add that there is no reason to believe that in PS-LL negotiations the LLs would wind up
siphoning off (does one say ―bullying their way to‖?) all of the co-operative surplus. The division
of the surplus is a complicated issue, and, indeed, the basis of John Nash’s Nobel-winning work
demonstrating that that the division is not totally indeterminate between the two extremes. In real
life, however, the parties lack the utility data the Nash solution requires; actual negotiations
would have to surmount transactions costs, or fashioning a mutually (or n-party) acceptable
solution, particularly if there are uncertainties as to which LLs were benefiting from which PSs’
(non)effort.
(8) Implementation option. If we regard LL reduction of catch to be an externality of PS activity, the
theoretical first line of thought is to impose a Pigovian-level of tax on the PS activity, that is, one
that maximizes the value of PS-LL activity by suppressing PS activity to the efficient level when
the LLs have taken efficient response measures. Lacking the data to calculate the tax, the
establishment of tradable shares seems to be indicated. This is not the time to explore whether
the ―coinage‖ traded should be share of catch, share of effort, or share of capacity. There also
looms the nagging issues of allocating the rights, whatever the coinage: by historical catch? With
adjustments for locale of catch? Each of these candidate variables has its own relative advantages
and drawbacks that warrant further attention. But in the last analysis, a system of tradable rights
is well worth pointing toward. Whatever the initial allocation—even 20.5% across the board
cutbacks—market forces would shift production to the most efficient equilibrium of fishers/gears.
Moreover, a system that permitted rights holders to ―bank‖—to defer cashing in rights until a
later period, would be valuable as a flexibility mechanism. The potential for cooperative surplus
could also be exploited through vessel buy backs. Squires has estimated, I recall, that 1/3 of the
purse seiners could be repurchased for USD $470 million, which would appear to be within the
capitalized value of the surplus the authors estimate. Buy-back experience has been mixed, but
that should not obstruct further attention to the option, perhaps in combination with tradable
rights (which would be more manageable with smaller fleets).
56
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
I look forward to the next version of this excellent paper. Unlike the many descriptive papers
we get, this one has powerful policy implications. If any of the assumptions or methodologies are
material, we owe it to Sun et al. to identify them.
Reply:
The author agrees with virtually everything that the commentator has said, but especially with his
statement that, unless the reasons are political, purse-seine fishing, rather than longline fishing,
should be restricted. When it was first suggested that longline fishing should be curtailed in the EPO
(IATTC Resolution C-99-04), I thought that that made no biological sense.
The fishery on fish associated with floating objects is directed at skipjack, but there are
substantial bycatches of juvenile bigeye and yellowfin, particularly the former.
Option 0, status quo. Things could get even worse for bigeye tuna.
Option 1, best case scenario (from the point of view of minimal impact on the purse-seine
fishery): Ideally, a way could be found to eliminate, or at least substantially reduce, the bycatches of
juvenile bigeye and yellowfin without reducing the catches of skipjack. I used to think that that
might not be so hard if there were as much effort put into that as was put into reduction of bycatches
of dolphins, but I'm not so sure now. I understand that the International Seafood Sustainability
Foundation is thinking hard about this, which is a good sign.
Option 2, second-best case scenario: The second best thing might be to further restrict sets
on floating objects, or even eliminate them, but this would greatly reduce the catches of
skipjack, which is already underfished. Skipjack would still be caught in unassociated schools, but
even if all the boats that had previously fished on floating objects were to fish entirely on
unassociated schools, it is unlikely that they would be able to catch as many skipjack as they had
previously. (Also, they would probably burn more fuel than they would if they were directing their
effort toward fish associated with floating objects.)
Option 3, third-best case scenario: The third-best thing might be to eliminate all purse-seine
fishing except that on fish associated with dolphins. That would reduce the catches of skipjack and
small bigeye to insignificant levels. Yellowfin would be caught, but these would be mostly large
fish, albeit not as large as those caught by the longline fishery.
Option 4, worst-case scenario: The worst thing would be to eliminate all purse-seine fishing,
which would reduce the surface catches of all species to insignificant levels. The longliners would
catch more bigeye and yellowfin, but the catch of yellowfin by longliners alone would probably be
far less than the catch of yellowfin by longliners and purse seiners combined under any of the
other options. Yellowfin are caught closer to the surface by longline gear than are bigeye. Maybe
some longliners would configure their gear for bigeye and some for yellowfin, taking into
consideration the fact that bigeye fetch more per kilogram, but yellowin are more abundant.
From an economic standpoint, bigeye are so esteemed by sushi eaters that the maximum
economic rent, or whatever it is called, could probably be realized by Option 4, with large side
payments to the purse-seine fishing countries, which would establish new industries to employ the
fishermen, cannery workers, etc. Alternately, purse-seine fishermen could learn a new set of skills
and become longline fishermen. An artisanal longline fishery has been growing in the eastern
Pacific Ocean, and its development might be accelerated if the purse-seine fishery were
57
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
curtailed. No matter what, however, if Dr. Sun's scheme were implemented worldwide, inexpensive
canned tuna would virtually disappear, which would be a shame.
There are some assumptions to be considered:
Bigeye and yellowfin are not highly migratory, so to catch the fish that are not caught by
purse seiners, longliners would have to increase their effort in the eastern Pacific Ocean, which
would require that they spend a lot on fuel. If the catches of bigeye and yellowfin increased, the
prices for them would probably decrease, which would affect the computations (but almost
certainly not invalidate them).
The evidence that there is a spawner-recruit relationship for tunas is not strong, and it may
not even exist at SBR levels of around 0.20 (although, obviously, it would have to exist at very low
levels). Maybe this should be discussed more in the Sun et al. manuscript, which I intend to look at
again as soon as I can. Incidentally, 50 percent of female bigeye are mature at about 135 cm, and
most of the bigeye caught by longliners are bigger than that, so it is hard to image that even a very
intense longline fishery would decrease the recruitment of juvenile bigeye.
It would take the wisdom of Solomon to allocate the side payments among the participants
and potential participants in the purse-seine fishery. The owners of distant-water longline vessels are
currently barely breaking even, which is presumably why Japan and Taiwan have been scrapping
longliners. At the same time, however, there are reports of longliners flying flags of convenience
and operating illegally or semi-illegally and their catches being bought illegally or semi-illegally in
Japan. Presumably, those vessels can operate successfully because their labor costs are lower. If
Japan and Taiwan pay purse seiners not to fish, then they would object to the owners of vessels
flying flags of convenience benefitting, but not contributing to the side payments. However, most of
the longline-caught tuna is consumed in Japan, so Japan would just have to clamp down on the
importation of tuna caught by vessels flying flags of convenience.
What if the longline interests were committed to huge side payments to the purse-seine
interests, and then found that they weren't catching enough fish to pay the side payments? A sidepayment plan would have to be implemented gradually, which would be very time-consuming, since
the benefits to the longline fishery would not be realized until several years after curtailment of the
purse-seine fishery was implemented.
In addition to the difficulty in estimating the operating cost of various fishing gears, the
capital cost in canning facilities and the sunk costs of the fishing vessels must also be taken into
account in the evaluation. There will be many unanticipated changes in the future; fishermen will
also be needed in the discussions in order to determine fishermen’s behavior and the development of
the tuna fishery. We will need more global and extended opportunities to create these meetings to
bring these issues to the academic community.
4.2 Policy Implications of the Estimation of the Global Tuna Demand
Because of the global nature of markets, the global tuna price response could be identified
through several reference markets for cannery-grade or sashimi-grade tuna. Two groups of cases
were presented at the Workshop:
58
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
(a). Case Study of Canned Tuna Trade and Markets:
Two presentation were provided by Kevin McClain, the invited speaker from tuna canning
industry, who reviewed the global tuna cannery and market situation. Also, Iván Prieto discussed the
Ecuadorian tuna industry. In addition, "The Price linkage of Global Cannery Tuna Market" was
presented by Yongil Jeon, "The Global Integration of European Tuna Markets" was presented by
Patrice Guillotreau of France, and "A Demand Analysis of the Spanish Canned Tuna Market" was
presented by Ramón Jiménez-Toribio of Spain. Drs. Guillotreau and Jiménez-Toribio summarized
the policy implications of the results of the two papers on the global integration of European tuna
markets, and on the demand for canned fish in Spain as follows.
The risk of a dominant position by the global canning oligopsony1 or by the retailing sector in
some European countries (as shown by the evidence of market power on the French market for
canned fish) is the potentially low price paid for raw tuna and the relatively high price paid by the
(south) European end consumers. In such a case, producers might be tempted, for a while, to increase
their fishing effort in order to compensate for the fairly low level of prices through higher quantities.
However, if the price is significantly low for too long a period, they could conversely be discouraged
from fishing. During past couple of decades, US fleets stopped fishing because they considered that
the price paid by canneries was unfair (Le Roy and Guillotreau, 2002). More recently in the late
1990s, tuna prices plummeted because of high catches of skipjack in the western Pacific, thus pulling
the global tuna market downward. Several distant-water fishing nations (DWFNs) (the Philippines,
Ecuador, Taiwan, France, Spain ...) stopped fishing for several weeks in 1999, forming a sort of
cartel (World Tuna Producers Organisation - WTPO), and prices started to recover after the sharp
decline in catches.
Manufacturers´ demand is considered price elastic (Bertignac et al., 2000; Chiang et al.,
2001). Because of this relatively high elasticity of demand from the processing industry (reported as
-1.55 raw tuna supplied to the canning market by purse-seine and pole-and-line fleets of the western
and Central Pacific Ocean; Bertignac et al., 2000), any decline in catches due to over-exploitation
would result in decreasing revenue for the producers. Other evidences of market power or product
differentiation down the chain (for processing, but also from the retailing industry) are given by the
relatively inelastic demand for canned fish in Spain (see below) or in the UK (Jaffry and Brown
2008), meaning that the price transmission is likely to be imperfect between producers and
consumers, resulting in a lower consumer surplus (consumers paying too-high prices for too-low
quantity).
This does not represent good news for the fishing industry, nor for tuna conservationists.
Fishery economic theory forecasts that there should be a safer level of biomass and economic rent
with monopoly and property rights, instead of competitive open access. But in the real world, the
fishing industry typically consists of highly-competitive harvesting sectors facing oligopsonistic 1
processing sectors, the latter capturing whole or part of the fishery surplus by depressing the prices
paid to fishermen (Weninger, 1999). If prices remain too low, scarcity signals due to
mismanagement are not passed on by the middlemen to the consumer, and fishermen are likely to
fish more for the same amount of income and, in turn, increase pressure on the stocks. To some
extent, this depressing effect on prices has been compensated for by the tremendous increase of
1
An oligopson is a market structure where a few buyers face many competitive sellers.
59
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
effort (vessel size, use of fish-aggregating devices (FADs) and supply vessels, technical progress
onboard ...) and thus harvested quantity.
―The effects of changes in harvest levels on tuna prices are difficult to predict‖ (Bertignac et
al., 2000, p. 175), presumably because of inventories that allow a certain power on prices for
processors who can buy primary fish and store it when the market price is low, and then wait while
there are peaks in market prices due to a bad harvest (Chiang et al., 2001). If the derived demand of
the canning industry is so elastic, any decrease in harvest due to overexploitation or a quota policy
would also reduce the revenue of fishing companies. The rent sharing between resource owners (for
instance, African, Caribbean and Pacific Group of States (ACP) or Pacific Islands countries whose
benefits come mainly from access licences to their Exclusive Economic Zones (EEZs), fishing
companies and canneries clearly shows the advantage that the downstream industries have over the
market (Mongruel, 2002). Some states that do not enjoy good bargaining positions against the fishing
companies can be tempted to let the DWFNs use more intensively the resources located in their
EEZs in order to maintain a good level of revenues.
Whatever the market power at the canning or retailing level, the most outstanding result of
the European market study lies in the remarkable linkage between the two major tuna species
(skipjack and yellowfin) in the Asian-European market. Even more unexpected was the leadership of
the yellowfin market over the larger skipjack market. Indeed, in the two markets where both species
were present (Thailand and Spain), the yellowfin tuna price leads the other market by two. In terms
of implications for fisheries, this means that any change in yellowfin tuna supply in the world market
would affect prices in the skipjack tuna markets, and the subsequent responses of fishermen in order
to adapt may occur in any area. Yellowfin tuna is less abundant and more difficult to catch than
skipjack and, as a result, purse-seiners prefer to target it because of its higher prices. Likewise
canneries prefer to buy it because of a higher yield in the filleting process associated with its loins
and possibly also because of better pricing due to market imperfections in some final consumption
places. Although yellowfin tuna has a smaller market and a lower stock level, the race to obtain it is
more time-consuming and unpredictable (more in free-swimming schools and fewer associated with
FADs). This has resulted in its influence on the skipjack tuna market. In order to confirm this result,
it would be interesting to have access to an American series of yellowfin tuna prices (either in
American Samoa or in Ecuador) because the market leader could reasonably be found somewhere in
the Pacific.
Regarding more specifically the demand for canned tuna in Spain, the most important result
obtained is that its own-price flexibility has a negative sign as expected, and reaches a fairly high
value (-2.58). This means that a 1% increase in the demanded quantity of canned tuna by Spanish
households could produce a 2.58% decrease in its normalised price. Therefore, the elasticity of
demand would be approximately -0.39 [Lee and Kennedy (2008)]. That means that in the Spanish
market a 1% increase in the price of canned tuna would result in a less than proportional decrease
and, consequently, there is an inelastic demand for canned fish in Spain. As demand for frozen tuna
is derived to a large extent from the canned tuna demand, this behavior could also indicate an
inelastic demand for fishermen and ultimately some bioeconomic instability in the design of
management policies [Anderson (1973)] because of the possibility of multiple equilibria 2. Such an
equivalence of elasticities along the chain is not straightforward (it would contradict previous
2
Considering the Gordon-Schaefer model, an inelastic demand would result in an anomalous sustainable revenue
function, which would follow the pattern of the ―back of a camel‖ rather than the usual inverted U shape.
60
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
analyses in the Pacific, as cited above) because of possible input substitution and imperfect price
transmission linked with market structures (in particular due to the degree of vertical integration in
the Spanish canning industry), and the quality of price transmission should certainly be scrutinized in
future research as a major issue for the industry.
It is worth noting also that the scale flexibility of canned tuna has a positive value (4.072). It
would indicate that a change in the aggregate consumed quantity of canned fish could result in a
more than proportional increase in the normalised price of canned tuna. The scale flexibility is not
usually positive. When it is related to the expenditure elasticity, it can indicate that this expenditure
elasticity has a value greater than one. This means that a change in consumers’ income (hence in the
expenditure devoted to canned fish by consumers) would produce a more than proportional increase
in the demand for canned tuna [Park and Thurman (1999)].
Furthermore, there is a clear substitution effect between canned tuna and other canned fish
because a 1% increase in the demand for other canned fish would result in a 2.94% decrease in the
price of canned tuna. Symmetrically, a 1% increase in the demand for canned tuna would result in a
2.29% decrease in the price of other canned fish. However, it is interesting to note that we do not
know for sure which products are classified as ―other canned fish‖ in the statistics of the Food
Consumption Panel from the Spanish Ministry of Agriculture, Fisheries and Food. In this category,
several species—sardine, tuna, mackerel, horse mackerel and anchovy—could be aggregated. This
group accounts for 40% of canned fish consumption. However, if we eliminate the aforementioned
species from Spanish production figures according to the Industrial Products Survey or apparent
consumption, the remaining species–salmon, hake, bullet tuna, etc.–account for only 13% in 1993
and 8% in 2008. Consequently, in the Food Consumption Panel, the category ―other canned fish‖
may possibly include canned tuna with vegetables or even canned albacore, because there is some
uncertainty about the content of the following goods: ―atún blanco‖, ―bonito del norte‖, ―bonito del
sur‖, ―atún‖, ―atún listado‖, ―atún claro‖, ―atún de almadraba‖, etc. This hypothesis is supported by
the fact that apparent consumption of canned tuna in the Spanish market is 247,000 mt, on average,
between 2002 and 2008, whereas according to the Food Consumption Panel the total consumption
amounts to only 107,000 mt. There is no doubt in such circumstances that other tuna products make
the bulk of this undefined category.
Also, we should consider how the results obtained on the canned tuna market affect the
market for frozen tuna. The main Spanish canning firms are often vertically and horizontally
integrated. Almost half of the Spanish tuna fleet harvesting tropical tunas belongs to a few large
canning firms–Calvo, Jealsa-Rianxeira, Garavilla-Isabel, and Albacora-Sálica—which cumulate
40.5% of sales and own canning plants in Spain and South America (Ecuador, Guatemala, El
Salvador, Venezuela before 2004, and Brazil). Since 2002, tremendous quantities of precooked tuna
loins have been exported, and their usage for the production of canned tuna in Spanish plants has
resulted in a reduction in costs and a 133% increase in canned production since 1993. Therefore,
Spanish imports have increased by 547% since 2002. Additionally, the creation of plants in these
countries has extended the access of the Spanish fleet to new fishing grounds. As a result, there has
been a significant ―export‖ of boats (re-flagged vessels) to the aforementioned countries and to the
Seychelles Islands. In fact, 85% of exports of canned tuna or tuna loins from El Salvador, 100% from
Guatemala, and 45% from Ecuador go to the Spanish market. These three countries represent 65% of
Spanish total imports of preserved and prepared (i.e. canned tuna + tuna loins). Spain has large
canning business groups, which have a very significant international expansion policy. The fleet,
which is controlled by these business groups, represents half of the Spanish fleet and a third of the
61
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
European Union fleet. Due to the corporate strategy on imports of precooked tuna loins, there has
been a ―price war‖ that has kept prices of canned tuna very low on the Spanish market.
Finally, it is difficult to replicate the analysis of the canned tuna market to the Spanish market
for frozen tuna because supposedly more than half of the tropical tuna production of the Spanish tuna
fleet–around 183,000 mt. in 2007–is controlled by these large business groups. Besides the inelastic
own-price demand of canned tuna that has been found, the income effect can be defined as dominant,
and due to the fact that the total expenditure in canned fish has experienced a 31% increase since
2004, this has encouraged the stability and even the growth of prices in the market (+26% in the
same time span). This can be seen as an incentive for the expansion of catches. In other words,
whatever the level of profitability in the fishing sector, the margins of the vertically-integrated and
growing canning sector would be large enough to support a deficit or a low profitability in the
fishing segment. Any management policy trying to find incentives at the fishing level should then
pay attention to the degree of vertical integration of the Spanish canning industry.
References
Anderson, L.G. 1973. ―Optimum Economic Yield of a Fishery given a variable price of output‖,
Journal of Fisheries Research Board of Canada, 30, 509-519.
Bertignac, M., Campbell, H.F., Hampton, J., Hand, A.J., 2000. Maximising resource rent from the
Western and Central Pacific tuna fisheries. Marine Resource Economics 15, 151–177
Chiang, F.-S., Jonq-Ying, L., Brown, M.G., 2001. The impact of inventory on tuna prices: an
application of scaling in the Rotterdam inverse demand system. Journal of Agricultural and
Applied Economics 33, 403–411.
Jaffry, S., Brown, J., 2008. A demand analysis of the UK canned tuna market. Marine Resource
Economics 23, 215–227.
Lee, Y. and L. Kennedy. 2008. ―An Examination of Inverse Demand Models: An Application to the
U.S. Crayfish Industry‖, Agricultural and Resource Economics Review, 37/2, 243-256.
Le Roy, F., Guillotreau, P., 2002. Contester la domination des leaders de marché en changeant les
règles du jeu: le cas de l’industrie thonière française. Management International 6, 29–41.
Mongruel, R., 2002. The European regulation framework of tropical tuna supply chains: its impact
on the tuna rent distribution between economic actors. Proceedings of the 14th EAFE
Conference, Faro, 25–27 March 2002, http://www.fe.ualg.pt/conf/eafe2002/papers.htm
Park, H. and W.N. Thurman,. 1999. ―On Interpreting Inverse Demand Systems: A Primal
Comparison of Scale Flexibilities and Income Elasticities‖, American Journal of. Agricultural
Economics, 81, 950-958.
Weninger, Q., 1999. Equilibrium prices in a vertically coordinated fishery. Journal of Environmental
Economics and Management 37, 290–305.
(b). Case Study of Tuna Sashimi Trade and Market:
There are two papers dedicated to modeling of demand for sashimi-grade tuna."Tuna Price in
Response to Changes of Market Structure and Ecosystem Conditions - Price Linkage between
Hawaii and Japanese Tuna Sashimi Markets" was presented by Minling Pan and "The Inverse
Demand Analysis of the Tuna Sashimi Market in Tokyo, Japan" was presented by Chin-Hwa (Jenny)
Sun. This situation presents different challenges and unanswered questions, which have important
62
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
policy implications for the management of fish stocks by Regional Fisheries Management
Organizations (RFMOs).
The first paper examines the pricing efficiency of bigeye and yellowfin tuna in the Hawaii
fresh/chilled tuna markets between 2000 and 2008 and identifies how the Hawaiian local market is
effectively pricing its products to follow the sashimi prices in Japan. Fresh bigeye tuna, that are
landed in Hawaii are exported quickly–the premium quality to Japan and the mid-quality to the
United States –much of it to cities like New York City.
The ex-vessel prices for fresh bigeye in Hawaii are lower than the import prices in Japan, but
the import prices in Japan are much more volatile. Fishers would, for many reasons, seem to feel
more comfortable just selling their catches at the Hawaii auction market. If the fat content of the fish
is high, there is big margin to induce the fishers take the risk of selling to Japan. There are brokers at
the auction who arrange the sales to Japan. Transportation cost is not high and the broker splits the
risk between himself and the fisher. The price volatility is partly a result of this situation, since it is a
gambling process, with lots of variability. In conclusion, the Hawaii market price for bigeye would
be driven up if the high-quality fish are sold to Japan. The auction prices in the Tsukiji market in
Tokyo follows the consumers' retail prices closely, compared to the frozen import market.
The second paper utilizes the inverse demand model to estimate the price flexibility of major
species of sashimi tuna. The value-added tuna sashimi demand in Japan constitutes the largest fresh,
chilled, and frozen tuna sashimi market in the world. Since 1998, more than 50% of the tuna sashimi
consumption in Japan has relied on imports. The annual total consumption of fresh and frozen bigeye,
yellowfin, bluefin, and southern bluefin tuna in Japan was above 500,000 mt since then, but the total
consumption began to shrink to 350,000 mt in 2008, and both the imports and the domestic landings
in Japan have experienced a 30% reduction.
Fluctuation in the auction prices of fresh and frozen bluefin tuna would confirm the price
responses to the availability of landings of that species. Consumers prefer high fat content, and cagecultured bluefin tunas are often thought to have a higher fat content. Wild bluefin is quite variable in
fat content, whereas farmed bluefin is fattened in a more predictable way. The auction price in Tokyo
is very different from the ex-vessel negotiated landing price. The problem of price distortions is not
yet included in analysis to look at price volatility/flexibility from the consumers' perspective.
Both the estimated fresh and frozen bluefin tuna show less than unity in absolute value for
their scale flexibilities, which means that the Japanese consumers are willing to pay premium prices
for high-quality fresh and frozen bluefin tuna; their prices are less responsive to the changes of their
quantities than they are for the other tuna species when the supply increases. However, a 1%
reduction of quantities caused by quota control would imply a less than 1% increase in prices and
would have a negative impact on total revenue.
For the sashimi market in Tokyo, both fresh and frozen bluefin tuna show less than unity in
absolute value for their scale flexibilities, which indicates these goods are considered as luxury, i.e.,
if the supply of all sashimi-grade tuna species increased by 1% and they would have less than 1%
decrease in prices. Since the bluefin tuna prices are less responsive to the changes of the supply of all
tuna species, it means that the Japanese consumers are still willing to pay premium prices for highquality fresh and frozen bluefin tuna than that for the other tuna species. There is no incentive for
suppliers of bluefin tuna to cooperate to reduce their supply from either wild-caught or cage-cultured
bluefin tuna because this would result in reduction in their total revenue.
63
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
For the sashimi-grade bigeye and yellowfin tuna, their scale flexibilities are identified to be
greater than unity and are referred as necessities that would be less preferable than bluefin tuna and
its price would decline more than proportionately as consumption of all goods in the bundle
increases. We would predict a negative impact on total revenue induced by the result of an intense
race for fish, or derby, which would imply a more than proportionately decrease in prices. Hence, if
fishermen could act collectively to adjust their operation cost through a quota-trading mechanism
monitored by the tuna RFMOs, fishermen could get the capability to help conservation by avoid
overcapacity and the derby effect. The estimated price flexibility could help to support the economic
benefit of global quota management control and the impact of changes in fishing capacity upon the
value of the total landings. It would be beneficial for the fishing industry to realize that a better
marketing distribution scheme for yellowfin and bigeye tuna would increase their total landings
values, even if a fishing quota for yellowfin and bigeye tunas are strained due to conservation
measures.
The value of tuna landings in the EPO reached $1.1 billion in 2008 and about 65% is
contributed by the tuna purse-seine fishery. The IATTC is charged with the management of this
fishery. In addition to the effect of fishing activity on biomass, the skyrocketing fuel cost variations
have a significant impact on the tuna price of the major international markets and the fishermen’s
revenue in the short and long run. As long as price flexibility in the major global market responses
can be estimated, we can predict the impact of quota control on prices both in local and global
markets. The identification of the price flexibility and linkages will facilitate the market-based
conservation and management measure of the tuna longline and tuna purse-seine fisheries in the EPO
to support both the IATTC’s mission in developing a long-run sustainable plan and to evaluate the
benefits of rights-based management of the tuna purse-seine and longline fishery landing in the
IATTC region. Manage the bigeye, yellowfin and skipjack tuna stock by applying scientificallysound observations, assessments, and research findings to ensure the sustainable use of resources and
to balance competing uses of coastal and marine ecosystems in the EPO.
5. Panel Discussion and Concluding Remark
The Panel Discussion was led by Dr. Rebecca Lent. Two fundamental questions were raised:
1. What do you want to see come from of this Workshop?
2. What do you want to do in this subject area?
If the disparity in prices paid for purse seine- and longline-caught fish is so great, why haven’t
the fishermen moved to curtailment of purse-seine fishing in response to side payments from
longline fishermen. Shouldn’t this just happen on its own?

Industry response:
o Inertia in fishing habits; purse seiners know how to catch tunas by purse seining, and
are reluctant to give up fishing or switch to longlining
o Purse seining requires large boats, so there is a large amount of fixed physical capital
that fishermen don’t want to give up.
64
Task III: Report of the Workshop

Global Tuna Demand and Fisheries Dynamics in the EPO
In contrast, the fixed physical capital required for coastal longlining vessels is
relatively much less.
o The longline fleet already has a significant overcapacity.

But why is the market not solving the problem? What types of laws would have to be
implemented to bring about a change.

Purse seiners are naturally subsidized from the negative externality that they impose on the
longline fleet. Proper incentives are not in place for them to change on their own.

A reduction in the overall catch quotas and the distribution of rights through an individual
transferrable quota (ITQ) system would allow more juvenile tunas to reach the sizes
vulnerable to capture by longlining, which would permit longline vessels to purchase the
fishing rights from purse-seine vessels. Thereby, the bycatch issue would be slowly phased
out.

An alternative perspective: The focus on revenue is perhaps skewing the results.
o Variable costs are actually significantly higher in longlining than in purse seining.
o Purse seining may actually be more profitable, which may be why purse seining isn’t
going away.
o Yes. But longliners would need less effort if there were more fish because the purse
seiners were no longer catching the juveniles.
o You have to reduce the take of juveniles before you can see an effect on the longline
fishery.

From a moral societal perspective, do we really want to be trading canned tuna (caught by
purse seiners), which is consumed by a large portion of the population, for sashimi-grade
tuna, which is consumed by a smaller, wealthier portion of the population?

Purse seining does not discriminate between what is caught, whereas longlining, for the most
part, does. Long lining has a smaller impact on the ecosystem than does purse seining.

Getting the prices right (i.e. accounting for the true costs) make a large difference in creating
the incentive to change behavior.

The idea that we should actually reduce the purse seining fleet to zero is inconceivable. You
will have more credibility if you stay within realistic terms.

NGOs have tried to establish a variety of different incentive-based compensation schemes
(e.g. buying back used purse seiner vessels). Nothing has worked.

Trying to establish a compensation scheme so that the purse-seine industry is not so adversely
affected. That is the reason for the quota system; purse seiners will be paid back in the future
through the quotas. However, there are arguments to claim that there is no need for a
compensation scheme, for the following reasons.
o In the EPO, 90% of the tuna is caught by 10% of the fleet. If you really want to have
an impact on the fishery, then you regulate those boats.
65
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
o There is no need for compensation; you just tell them what to do. That is the only
way you are going to get change.

We must remember that IATTC is an international organization and it does not set quotas.
The levels that are set are to be thought of more as ―limits.‖ They are mutually-agreed-upon
limits. There is no penalty for going over the limit.
The following Concluding Remarks were furnished by Dr. Rebecca Lent:
Overarching ideas/themes
Objective: The objective of the Workshop was to build a think tank to have a better understanding of
the global tuna fishery, including: status of stocks, capacity issues, and markets. All of this, with the
goal of informing policy makers to hopefully do the right thing, and to understand the relative
impacts of their alternative policies. In some cases, this would include potential change in gear
types.
Per Dr. Minling Pan, it is interesting to look at the chain of Market Response –> Fishermen’s
Response -> Catch availability. So what did we see?
Stocks:
The status of tuna stocks varies, but overall it is not all doom and gloom (infamous 90% decline
story). In some cases, estimates are available that show that shifts to different gear types could result
in significant modifications in the level of maximum sustainable yield. Areas that need improvement
include data collection on interactions between target and other species (small individuals of target
species, non-target species, and protected species).
Capacity:
There are too many boats, and capacity is moving around the planet. Overall, purse-seine capacity
appears to be still growing, while large-scale pelagic longlining has slowed and small-scale
longlining is growing, possibly in response to market signals (declining profits). There is a lack of
data, and there are problems in measuring capacity, but maybe it’s less important to measure
capacity than to cap and reduce it. Statistical coverage of those small-scale longliners is increasing,
so that’s also a source of growth that may have already been there.
There was some discussion of the possibility of rights-based management as a way to reduce
capacity through market mechanisms. This raises the question as to whether this would be possible
across countries for shared stocks.
Markets:
There is considerable evidence of market integration, but this integration is not always perfect.
Thailand is important, but not the only player. Market chains have fewer intermediaries. Some large
retailers may be making large profits, and therefore denying lower prices to consumers. Tariffs are
affecting locations of canning facilities. The sashimi market is very much quality driven. Canned
tuna demand is both taste and income-driven. Fishermen are more informed, and can actually take
the risk of selling their fish on the Japanese auction market, or they can sell to buyers who might turn
around and take on that risk.
66
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
Issues:






Having a global markets might mean that a local reduction in landings does not result in an
increase in price, which makes management more challenging. This raises the question of a
possible backward-bending supply curve of fish.
How can it be ensured that private sector decisions are good for overall societal welfare?
Importance of getting the prices right.
If it is true that RFMOs can improve market integration, how might that happen?
Big issue: this case of the alleged benefits of going from purse seiners to longliners. There’s
a huge externality where purse seiners impose an externality with take of small tunas and
reduce availability to longliners. If loss to purse seiners is less than the gain to the longliners,
then they can find a payoff.
So, as Professor Groves says, we’re left with a political economy question
My perspective: RFMO management. My sense is that economists should be more integrated
into the science machinery of these RFMOs. There is openness to this in RFMOs, although not
always for the right reasons. Economists should make their work understandable to non-economists,
including biologists, stock assessment scientists, and policy makers. Get to the nitty-gritty, and use
the results to demonstrate the outlook under different scenarios. This can help with the political
economy, I believe, as it promotes transparency and full knowledge of the alternatives and their
impacts. Have options ready, as Dr. Miyake says.
For example, stock assessment scientists project growth (or decline) in stocks depending on
each quota scenario. We will need economists to add the present value or other straightforward
presentation of impacts.
The challenge: July 2011, ―Meeting of Regional Fisheries Management Organizations (Kobe 3)"
process will be held in La Jolla.
A template "STRATEGY MATRIX" for presenting scenarios and management solutions is
supposed to be used in Kobe 2–once we have a completed matrix (e.g. with quotas) get the
―monetary‖ version, e.g. present value of stream of net revenues. This would be a great goal as part
of a Kobe 3 focus on incorporating socioeconomics into multilateral science and stewardship.
Strategy Matrix for Setting Management Measures
Management
Target 1
FMSY
Time
Probability of Meeting Target
Data Rich/
Frame 2
50%
60%
75%
90%
Data Poor
In 1 years
In 3 years
In 5 years
BMSY
In 5 years
In 10 years
In 15 years
1
FMSY=fishing effort corresponding to maximum sustainable yield. BMSY=biomass corresponding to
maximum sustainable yield.
2
In cases where a rebuilding time frame has already been agreed, the Standing Committee on
Research and Statistics should base its advice on that time frame.
67
Task III: Report of the Workshop
Global Tuna Demand and Fisheries Dynamics in the EPO
Policymakers have sufficient information to do the right thing. We all understand the issues,
now. Purse-seiners are catching juvenile fish, which is a problem. The fact that we are approaching
this scientifically is a good sign, but we need to get economists involved. The exciting part is to show
impacts of different scenarios and propose different options. It is crucial that we estimate the present
values of a future payment or series of future payments, discounted to reflect the time value of
money and other factors such as investment risk! This is where economists are needed.
6. ADJOURNMENT
On behalf of the IATTC and its Project that hosted the Workshop, Dr. Compeán thanked all the
participants for their valuable technical input to the Workshop. He expressed particular thanks to:
• Dr Chin-Hwa (Jenny) Sun, Convener of the Workshop, for very effectively organizing it;
• the authors of the papers;
• the Chairpersons;
Dr. Compeán mentioned that the IATTC and its Project are grateful to all the organizations
that provided strong support and substantial contributions to the Workshop. In this respect, he
mentioned specifically (1) the IATTC, the host of the Workshop, and (2) the PIFSC and SWFSC, the
principal donor to the Workshop.
Dr. Sun, the Convener of the workshop, thanked the IATTC for hosting the workshop and
thanked to all of the participants, for this has been a fruitful Workshop that gave us so many different
views on this important subject.
This Workshop had gathered many international experts in modeling global tunas. A
good way to take full advantage of this is to establish a follow-up forum in the near future, and we
have a wonderful follow-up news that one of our invited speakers, Patrice Guillotreau of the
University of Nantes, has announced that his organization will host a follow-up workshop "Modeling
global demand for tuna" at the University of Nantes in France on April 14-15, 2011. With the
financial support of the MACROES, (French) National Agency for Research project and
NOAA/NMFS, and in co-operation with the CLimate Impacts on Oceanic TOp Predators-Integrated
Marine Biogeochemistry and Ecosystem Research (CLIOTOP-IMBER) programs, scholars gathered
at the current Workshop are also invited to participate in a follow-up Workshop to enhance our
empirical knowledge of tuna markets around the world in connection with management policy
issues, and to discuss the most relevant econometric methods and specifications to model adequately
tuna markets on a global scale. The agenda of the follow-up workshop is also included in Appendix
VII.
Finally, evaluation of the economic impacts of the management target will require the
incorporation of socioeconomics into multilateral science and stewardship to capture the dynamics
of tuna fisheries. The convener hopes that all participants will have a safe trip home and that they
will be able to see each other soon at the Kobe III meeting, which will be held in La Jolla on July
11-15, 2011.
68
APPENDIX I – Invitation Letter
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
COMISION INTERAMERICANA DEL ATUN TROPICAL
INTER-AMERICAN TROPICAL TUNA COMMISSION
8604 La Jolla Shores Drive, La Jolla CA 92037-1508, USA – www.iattc.org
Tel: (858) 546-7100 – Fax: (858) 546-7133 – Director: Guillermo Compeán
A-1
APPENDIX I – Invitation Letter
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
COMISION INTERAMERICANA DEL ATUN TROPICAL
INTER-AMERICAN TROPICAL TUNA COMMISSION
8604 La Jolla Shores Drive, La Jolla CA 92037-1508, USA – www.iattc.org
Tel: (858) 546-7100 – Fax: (858) 546-7133 – Director: Guillermo Compeán
Workshop on Global Tuna Demand, Fisheries Dynamics and Fisheries
Management in the Eastern Pacific Ocean
May 13-14 2010 – 13 -14 de mayo 2010
Southwest Fisheries Science Center, Large Conference Room,
3333 North Torrey Pines Court
La Jolla, USA
Registration / Registro
Last name/Apellido:
First name/Nombre:
Organization -Company / Organización -Compañía:
Job title / Cargo:
Department / Departamento:
Address / Domicilio:
City/Ciudad:
State/Estado:
Phone number / Número telefónico:
Zip /Código Postal:
Country/País:
Fax number / Número de fax:
E-mail / Correo electrónico:
_____________________________________________
Signature / Firma
Please fill out and email
to Jenny Sun [email protected] or fax (858)546-7133 by APRIL 23, 2010
Date
Meeting Schedule / Programa de Reuniones
May Workshop on Global Tuna Demand, Fisheries Dynamics and Fisheries Management in the
13-14 Eastern Pacific Ocean
All foreign nationals are required to send, in addition to the registration form, a copy of their passport
in order to process the required clearance to enter a federal building.
A-2
APPENDIX III – Programme
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
APPENDIX II
Programme
WORKSHOP ON GLOBAL TUNA DEMAND,
FISHERIES DYNAMICS AND
FISHERIES MANAGEMENT
IN THE EASTERN PACIFIC OCEAN
May 13-14, 2010
Large Conference Room, Torrey Pines Court
Southwest Fisheries Science Center
La Jolla, CA 92037
Coordinators:
Chin-Hwa “Jenny" Sun, Mark N. Maunder, Minling Pan, and Dale Squires
Agenda1
Welcome/Introduction
Arrangements and Introduction of Participants
Session I. Tuna Fleet Dynamics and Capacity Overview
Keynote Speech: Tuna Fleet Dynamics and Capacity Overview in EPO
(a) Recent Developments in Tuna Industry
(b) Tuna Cannery Capacity and Market Overview
Session II. Stock Assessment and Fishery Management in EPO
Session III. Tuna Fishing Capacity and Fleet Dynamics
(a) Tuna Purse-Seine Fleet Dynamics in France, and Spain and US
(b) Tuna Longline Fleet Dynamics in Japan, Korea, and US
A-3
APPENDIX III – Programme
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Session IV. Estimation of Global Tuna Demand
(a) Case Study of Tuna Can Trade and Markets
(b) Case Study of Tuna Sashimi Trade and Market
Session V. Meeting Report and Considerations for Further Work
Note:
A. The workshop website, http://www.fisheriesstockassessment.com/TikiWiki/tikiindex.php?page=Global+Tuna+Demand+and+Fisheries+Dynamics, is constructed to include
background discussion papers, presentation abstracts, and focus questions.
B. Due to the limited space of the meeting venue, please e-mail the registration form and confirm with
Jenny Sun ([email protected]) to see the availability of the seating. All foreign nationals are required to email to Jenny, in addition to the registration form, a copy of their passport in order to process the
required clearance two weeks before entering a federal building. All IATTC stuff is waived from this
requirement.
C. The meeting venue is at the Southwest Fisheries Science Center, located at 3333 North Torrey Pines
Court, La Jolla, CA 92037. We will provide transportation for participants daily at 7:50 am from the
Best Western Inn by the Sea to the meeting location. The Welcome Dinner, sponsored by International
Seafood Sustainability Foundation, is arranged at Piatti Ristorante (2182 Avenida De La Playa, La
Jolla, CA 9203 7) at 8pm on May 13. Dress code is usual casual attire around La Jolla.
D. Two background discussion papers are posted on the workshop website to facilitate discussions and
generally contribute to the success of the workshop. Participants are encouraged to read the background
discussion papers in preparation for the feedback discussion and considerations for further work.
1
Statements made by participants at the workshop only reflect their personal opinions. They are not
attending as representatives of organizations, countries, or sectors, nor they express the views of the
hosting organizations.
A-4
APPENDIX III – Programme
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Program
Thursday May 13, 2010
On-site Registration Opens at 7:45 am (pick-up workshop materials)
07:50 Continental breakfast provided
08:20 Welcome/Opening (Guillermo A. Compeán and Coordinators)
Session I. Tuna Fleet Dynamics and Capacity Overview (Chair: Peter Miyake)
08:30 Recent Development on Rights-based Management of Tuna Fishery: Summary Report of
the IATTC and World Bank Workshop in May 2008 (30 mins)
(Dale Squires)
09:00 Keynote Speech: Tuna Fleet Dynamics and Capacity Overview in EPO (50 mins)
(Guillermo A. Compeán)
09:50 World Trends of Tuna Industry - Recent Developments in Tuna Industry: Stocks,
Fishery, Management, Processing, Trade and Markets (FAO Fisheries Technical Paper,
Rome)
(Peter M. Miyake*, Patrice Guillotreau, Chin-Hwa Sun, and Gaku Ishimura) (60 mins)
10:50 Coffee break (15 mins)
11:05 Global Tuna Cannery and Market Overview (35 mins)
(Kevin McClain)
11:40 Tuna Cannery and Market Overview in Ecuador (40 mins)
(Iván Prieto)
12:20
Lunch break (70 mins)
Session II. Stock Assessment and Fishery Management in EPO
(Chairs: Mark N. Maunder)
13:30 Status of Bigeye Tuna in the Eastern Pacific Ocean in 2008 and Outlook for the Future
(Alexandre Aires-da-Silva* and Mark N. Maunder) (20 mins)
13:50 Status of Yellowfin and Skipjack Tuna in the Eastern Pacific Ocean in 2008 and Outlook
for the Future (20 mins)
A-5
APPENDIX III – Programme
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
(Mark N. Maunder*, and Alexandre Aires-da-Silva)
14:10 Increasing the Economic Value of the Eastern Pacific Ocean Tropical Tuna Fishery:
Tradeoffs Between Longline and Purse Seine Fishing (40 mins)
(Chin-Hwa Jenny Sun*; The author is heartily thankful to Mark N. Maunder, Alexandre
Aires-da-Silva, and William H. Baylif f for help in compiling the IATTC tuna stock
assessment result for this study.)
14:50 Questions and Answers - Discussant: Chris Stone (30 mins)
15:20 Coffee Break (15 mins)
Session III. Tuna Fishing Capacity and Fishery Dynamics (Chairs: Dale Squires)
15:35 Fishing Capacity and Productivity Growth in the EPO Tuna Purse Seine Fishery (65
mins)
(Eric Janofsky*, James Kirkley, Dale Squires, Chin-Hwa Jenny Sun, and Yongil Jeon)
16:40
Tuna Longline Fishery Dynamics in Japan, Korea, US and Taiwan (60 mins)
(Peter M. Miyake*, Yongil Jeon*, Minling Pan* and Chin-Hwa Jenny Sun*)
17:40 Feedback Discussion (1): Bioeconomic Modeling of the EPO Tuna Stocks (20 mins)
18:00 Break for the day
20:00 Welcome Dinner (Piatti Ristorante, 2182 Avenida De La Playa, La Jolla, CA 92037)
- Sponsored by International Seafood Sustainability Foundation (ISSF)
Friday May 14, 2010
08:00 Continental breakfast provided
Session IV. Estimation of Global Tuna Demand
(a). Case Study of Tuna Can Trade and Markets (Chair: Patrice Guillotreau)
08:30 Global Integration of European Tuna Markets (50 mins)
(Ramón Jiménez-Toribio, Patrice Guillotreau* and R. Mongruel)
09:10 Tuna Purse-Seine Fishery Dynamics in France (20 mins)
(Patrice Guillotreau*, Ramón Jiménez Toribio* and Juan José García del Hoyo)
09:30 A Demand Analysis of the Spanish Canned Tuna Market (50 mins)
(Juan José García del Hoyo, Ramón Jiménez-Toribio*, Patrice Guillotreau)
10:10 Tuna Purse-Seine Fishery Dynamics in Spain (20 mins)
A-6
APPENDIX III – Programme
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
(Patrice Guillotreau*, Ramón Jiménez Toribio* and Juan José García del Hoyo)
10:30 Coffee break (15 mins)
10:45 Price Linkage of Global Cannery Tuna Market (45 mins)
(Yongil Jeon and Dale Squires)
Session IV (b). Case Study of Tuna Sashimi Trade and Market (Chair: Jenny Sun)
11:30 Tuna Price in Response to Changes of Market Structure and Ecosystem Conditions Price Linkage between Hawaii and Japanese Tuna Sashimi Markets (45 mins)
(Minling Pan*, Chin-Hwa Jenny Sun and Dale Squires)
12:15 Lunch break (60 mins)
13:15 Inverse Demand Analysis of the Tuna Sashimi Market in Tokyo, Japan: An Application
of the Rotterdam Inverse Demand System (45 mins)
(Chin-Hwa Jenny Sun* and Fu-Sung Chiang)
13:50 Bioeconomic Modeling and Management of the Western and Central Pacific Ocean Tuna
Stocks (30 mins) (Harry Campbell, John Kennedy, and Chris Reid)
Discussant: Theodore Groves*
Session V. Meeting Report and Considerations for Further Work (Chair: Minling Pan)
14:20 Feedback Discussion (2): Analysis of the Global Demand of Tuna Fisheries (70 mins)
(Panelists: Theodore Groves, James Kirkley, Minling Pan, Mark N. Maunder, Chin-Hwa
Jenny Sun, Rebecca Lent, Dale Squires, Makoto Peter Miyake, Patrice Guillotreau,
Ramón Jiménez-Toribio , Yongil Jeon, Chris Stone, and Iván Prieto)
15:30 Break for the meeting. Safe travels!
A-7
APPENDIX III – List of Participants
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
APPENDIX III
List of Participants
Invited Speakers (Alphabetically Order):
1. Alexandre Aires-da-Silva, Ph.D.
Senior Scientist
Inter-American Tropical Tuna
Commission (IATTC)
[email protected]
2. Guillermo A. Compeán, Ph.D.
Director
IATTC
[email protected]
Associate Researcher
National Research Institute of Far Seas
Fisheries
3-3-4, Shimorenjaku, Mitaka-shi
Tokyo, 181-0013, Japan
Phone: +81 (0)422 46 3917
[email protected]
8. Minling Pan, Ph.D.
Pacific Islands Fisheries Science Center
National Marine Fisheries Service
2570 Dole Street
Honolulu, Hawaii 96822-2396, USA
[email protected]
9. Ivan Arturo Prieto
Economics Advisor
Cámara Nacional de Pesquería
9 de Octubre 424 y Chile
Edificio Gran Pasaje piso 8
Of. 802-803, Casilla 1269
Guayaquil, Ecuador
Phone: +593 (4) 228 2286
Fax: +593 (4) 2399424
Mobil: 5939 406 1121
[email protected]
3. Patrice Guillotreau, Ph.D.
Researcher in Fisheries Economics
Institut de Recherche pour le
Développement (IRD)
and University of Nantes, France
[email protected]
4. Yongil Jeon, Ph.D.
Associate Professor
School of Economics SungKyunKwan
University (SKKU), South Korea
Phone: 760-0487
[email protected]
5. Ramón Jiménez-Toribio, Ph.D.
Departamento de Métodos Cuantitativos
para la Economía y la Empresa
Estadística e Investigación Operativa
MEMPES-AEA
Universidad de Huelva
España
Tlf.: +34 959 217 871
[email protected]
6. Mark N. Maunder, Ph.D.
Head of the Stock Assessment Program
IATTC
[email protected]
7. Makoto Peter Miyake, Ph.D.
A-8
10. Kevin McClain
Bumble Bee Foods, LLC
9655 Granite Ridge Dr.
Suite 100
San Diego, CA 92123
[email protected]
11. Dale Squires, Ph.D.
Southwest Fisheries Science Center
National Marine Fisheries Service
[email protected]
12. Chin-Hwa Jenny Sun, Ph.D.
Professor (1994-present)
Inst. of Applied Economics
National Taiwan Ocean University
[email protected]
Visiting Research Scholar (2009/2010)
IATTC
APPENDIX III – List of Participants
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Invited Participants:
13. Reno L. Harnish III
Director
Center for Environnemental and
National Security
Scripps Institution of Oceanography
2250 Historic Decatur rd. #84
University of California, San Diego
(858)534-2542
[email protected]
Former American Ambassador and
Principal Deputy Assistant Secretary of
State in the Bureau of Oceans and
International Environmental and
Scientific Affairs
14-5. US Department of State
Office of Marine Conservation
2201 C Street, NW - Room 2758
Washington, DC 20520
18. James E. Kirkley, Ph.D.
Professor of Marine Science
Chair, Department of Coastal and Ocean
Policy
Virginia Institute of Marine Science
Phone (804) 684-7160
[email protected]
19. Rebecca Lent, Ph.D.
Director
Office of International Affairs
National Marine Fisheries Service
1315 East-West Highway
Silver Spring, MD 20910
[email protected]
20. Raymond Clarke
Pacific Island Regional Office
1601 Kapiolani Boulevard, Room 1110
Honolulu, HI 96814-4700
Phone: +1 (808) 944-2205
Fax: +1 (808) 973-2941
[email protected]
William Gibbons-Fly
Director
[email protected]
David Hogan
[email protected]
21-25. Southwest Fisheries Science Center
National Marine Fisheries Service
8604 La Jolla Shores Drive
La Jolla CA 92037-1508, USA
16. Theodore Groves, Ph.D.
Professor and Director
Center for Environmental Economics
Department of Economics
University of California, San Diego
La Jolla, CA 92093-0508
Phone: +1 (858) 534-2818
[email protected]
Sam Herrick, Ph.D.
[email protected]
Joe Terry, Ph.D.
[email protected]
Stephen Stohs, Ph.D.
[email protected]
17. Chris Stone, Ph.D.
J. Thomas McCarthy Trustee Chair in
Law, Gould School of Law
University of Southern California
699 Exposition Blvd.
Los Angeles, CA 90089
Office (213) 740-2550
[email protected]
James Hilger, Ph.D.
[email protected]
Eric Janofsky
[email protected]
A-9
APPENDIX III – List of Participants
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
1250 24th St., NW
Washington, DC 20037
Tel 202-495-4711
Fax: 202 223-6971
[email protected]
26-28.
Southwest Regional Headquarters
National Marine Fisheries Service
501 W. Ocean Blvd. Suite 4200
Long Beach, Ca 90502-4213
33-34. International Seafood Sustainability
Foundation (ISSF)
Mark Helvey
Phone: +1 (562) 980-4040
[email protected]
Susan Jackson
President
[email protected]
Craig Heberer
[email protected]
Victor Restrepo
Chair, Scientific Advisory Committee
P.O. Box 11110
McLean, VA 22102
+34689563756
[email protected]
Heidi Hermsmeyer
[email protected]
29. John Zuanich
Sr. Manager
Seafood Procurement
Star Kist Company
Ecuador
Phone: (1-310) 519-2218
USA cell (1-310) 710-4522
Ecuador cell: (593) 98080720
[email protected]
35-41.
Inter-American Tropical Tuna
Commission (IATTC)
8604 La Jolla Shores Drive
La Jolla CA 92037-1508, USA
Brian S. Hallman
[email protected]
30. Paul Krampe
Executive Director
American Tunaboat Association
1 Tuna Lane Suite 1
San Diego California 92024
TEL: 610-233-6407
FAX: 619-839-3643
[email protected]
Richard B. Deriso, Ph.D.
[email protected]
Martín A. Hall, Ph.D.
[email protected]
Michael Gene Hinton, Ph.D.
[email protected]
31-32. World Wildlife Fund - US
William W. Fox, Jr., Ph.D.
Vice President & Managing Director,
Fisheries
Phone/Fax: +1 619 222 2489
Mobile: +1 571 205 8845
[email protected]
Kurt M. Schaefer
[email protected]
Vishwanie Maharaj, PhD
Senior Program Economist, Fisheries
Ricardo Belmontes
[email protected]
William H. Bayliff, Ph.D.
[email protected]
A-10
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
APPENDIX IV
Background Discussion Paper 2
Bioeconomic Modeling and Management of the Western and Central
Pacific Ocean Tuna Stocks
Background Discussion Paper
Prepared by
Harry Campbell1, John Kennedy2 and Chris Reid
(Preliminary: please do not cite or quote without permission from one of the
authors. The views expressed in the paper are those of the authors and do not necessarily
represent the views of any organization with which they are affiliated.)
1: Introduction
This survey paper reviews some recent research, involving the authors, on the
biology, economics and management of the Western and Central Pacific Ocean (WCPO)
tuna fisheries. The Western and Central Pacific perspective may be useful as a
comparison with the management experience in the Eastern Pacific Ocean.
Concerns about the level of fishing effort, and about the balance of effort among
gear types - principally between purse seine and longline effort - led to the development
of a detailed bioeconomic model (WCPOBTM v1) involving four tuna species and
sixteen fleets operating in the WCPO. The model was used to work out the level and
combination of fishing effort that maximized the annual rent generated by the tuna
fisheries in the region.
The results of the model suggested that a significant reduction in purse seine
effort would lead to an increase in annual rent. This conclusion was further examined by
means of a revised model (WCPOBTM v2) which retained much of the structure of
WCPOBTM v1 but incorporated some revised parameter values. The results of
WCPOBTM v2 suggested that while a moderate decline in purse seine effort might
contribute to raising the level of fishery rent, much of the increase could be attributed to
price increases for the catch rather than changes in catch per unit effort (CPUE). The
model also suggested that a reduction in effort would lead to significantly different
relative outcomes for the various fleets and countries involved, indicating that agreement
on such a measure might be difficult to achieve.
1
2
University of Queensland, Australia
La Trobe University, Australia
A-11
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Subsequent research based on a simpler version of the WCPOBTM models, but
incorporating some of their features and parameter values, was undertaken to predict the
outcome of negotiations among tuna fishing nations on the level and structure of fishing
effort. The results of this work highlighted the difficulty of achieving the rent mazimizing
outcome identified by the earlier models. Since some fishing nations are involved in the
purse seine fishery only it would be difficult to reach agreement on a reduction in the
relative amount of purse seining effort. This conclusion suggests some directions for
further research.
2: Background
The tuna fishery in the Western and Central Pacific Ocean (see Figure 1) is
diverse, ranging from small-scale artisanal operations in the coastal waters of Pacific
states, to large-scale, industrial purse-seine, pole-and-line and longline operations in both
the exclusive economic zones of Pacific states and on the high seas. The main species
targetted by these fisheries are skipjack tuna (Katsuwonus pelamis), yellowfin tuna
(Thunnus albacares), bigeye tuna (T. obesus) and albacore tuna (T. alalunga).
Annual total catches of the four main tuna species (skipjack, yellowfin, bigeye
and albacore) in the Western and Central Pacific Convenstion Area (WCP–CA), as
reported in Figure 2, increased steadily during the 1980s as the purse seine fleet expanded
and remained relatively stable during most of the 1990s until the sharp increase in catch
during 1998. Over the recent years, there has been an increasing trend in total tuna catch,
primarily due to increases in purse-seine fishery catches (see Figure 2). The total WCP–
CA tuna catch for 2007 was around 2.4 million mt, clearly the highest annual catch
recorded, and more than 120,000 mt higher the previous record in 2006. During 2007, the
purse seine fishery accounted for an estimated 1.74 million mt (73% of the total catch,
and a record for this fishery), with pole-and-line taking an estimated 214,935 mt (9%),
the longline fishery an estimated 232,388 mt (10%), and the remainder (8%) taken by
troll gear and a variety of artisanal gears, mostly in eastern Indonesia and the Philippines.
The WCP–CA tuna catch for 2007 represented 84% of the total Pacific Ocean catch of
around 2.8 million mt, and 55% of the global tuna in 2007 estimated at just under 4.4
million mt (Williams and Terawasi, 2008).
A-12
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Figure 1: The Western and Central Fisheries Commission boundary, and national
EEZs
Figure 2: Catch (mt) of albacore, bigeye, skipjack and yellowfin in the WCP–CA, by
longline, pole-and line, purse seine and other gear types (Williams and Terawasi,
2008)
The 2007 WCP–CA catch of skipjack (1,726,702 mt – 72% of the total catch) was
the highest ever, continuing the trend of consecutive record catches since 2002 (see
Figure 3). The WCP–CA yellowfin catch for 2007 (431,814 mt – 18%) was lower than in
2006 (442,288 mt), but higher than the average catch level for the period since 2000
(~424,000 mt). The WCP–CA bigeye catch for 2007 (143,059 mt – 6%) was the second
highest on record (after the catch in 2004–156,768 mt), mainly due to a relatively high
estimated bigeye catch from the purse seine fishery. The 2007 WCP–CA albacore catch
(95,240 mt – 4%) was the lowest for over ten years, primarily due to the continuing trend
of low catches in the North Pacific in recent years (Williams and Terawasi, 2008).
A-13
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Figure 3: Catch (mt) of albacore, bigeye, skipjack and yellowfin in the WCP–CA
(Williams and Terawasi, 2008)
The Western and Central Pacific Fisheries Commission (The Commission) was
established under The Convention on the Conservation and Management of Highly
Migratory Fish Stocks in the Western and Central Pacific Ocean (the Convention) to
conserve and manage migratory fishery resources in the western and central Pacific
Ocean. The Convention was negotiated at a series of Multilateral High-Level
Conferences (MHLCs), which included participants from Pacific Island Countries (PICs)
and distant water fishing nations. At the Seventh meeting of the MHLC in September
2000 the delegates adopted the text of the Convention. On 19 June 2004, the convention
entered into force and the Commission met for the first time in December 2004 in
Pohnpei, Federated States of Micronesia.
Article 5 of the Convention lays out the principles and measures for conservation
and management of fish stocks. Part b of Article 5 sums up the scope of measures to be
implemented so as to:
"ensure that such measures are based on the best scientific evidence
available and are designed to maintain or restore stocks at levels capable
of producing maximum sustainable yield, as qualified by relevant
environmental and economic factors, including the special requirements
of developing States in the Convention Area, particularly small island
developing States, and taking into account fishing patterns, the
interdependence of stocks and any generally recommended international
minimum standards, whether subregional, regional or global;"
The Commission seeks advice from a Scientific Committee (SC) on stock assessment,
and from a Technical and Compliance Committee (TCC) for evaluating options for
effective implementation of possible management measures. One current area of concern
arises from the SC noting that overfishing of bigeye and yellowfin tuna is now likely
occurring, though not of skipjack or South Pacific albacore.
One index used for assessing the sustainability of current catches is maximumsustainable-yield fishing mortality relative to current fishing mortality. The index is less
A-14
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
than one for bigeye and yellowfin (about 0.8), but much greater for albacore (about 19).
The Commission is consequently considering the following measures for reducing fishing
effort targeted at juvenile and adult bigeye and yellowfin:
(a) Catch and/or effort limits
(b) Capacity limits for large-scale tuna fishing vessels
(c) Measures to address impacts of large-scale tuna fishing vessels, so as to ensure
compatibility between measures applied outside areas of national jurisdiction and
measures being applied by coastal states to manage fishing by such vessels within
their zones
(d) Time and area closures
(e) Mitigation measures to address the mortality of non-target species such as
seabirds, turtles and sharks.
A measure that is clearly being considered by the Commission and is referred to
several times in Article 5 ‗Conservation and Management Measures‘, is the imposition of
a total allowable catch (or total allowable amount of effort) spanning the Convention
Area. For example, in paragraph 41, it is said that:
A priority issue for the Commission, given the expectation that a
Convention Area TAC with national and high seas allocations of catch is
likely to be the most effective long-term option for the conservation and
management of the large, multispecies, multi-gear, multiple landing point
fisheries of the WCPO, is the development of mechanisms for the
allocation of TAC (or TAE), in accordance with Art. 10(3), and adopting
any such decisions by consensus (Art. 10(4)). The Commission could
usefully consider the most suitable approach to initiate this process.
3: Bioeconomic Modeling
A study funded by the Australian Center for International Agricultural Reearch
(ACIAR) on the economics of Papua New Guinea's tuna fisheries raised questions about
the level and structure of tuna fishing effort in PNG's EEZ (Campbell and Owen (1994)).
It was established that purse seiners, fishing primarily for skipjack tuna, had some ability
and incentive to target juvenile yellowfin tuna (Campell and Nicholl (1994)). A simple
spreadsheet model, incorporating plausible parameters, suggested that the marginal
benefit of juvenile yellowfin to the purse seine fishery was less than the marginal cost, in
terms of lower CPUE, to the longline fishery (Campbell (1994)). A spatial analysis of the
relationship between the level of purse seine tuna catches and longline CPUE lagged one
period suggested that the purse seine fishery was, in fact, impinging on the profitability of
the longline fishery (Campbell and Nicholl (1995)). However it was concluded that a
detailed bioeconomic model of the region's tuna fisheries would need to be constructed to
put this hypothesis to the test. Such a model would also address questions about the level
as well as the composition of fishing effort in the region. ACIAR Project
ASEM/2001/036 funded joint research by the University of Queensland, the South
A-15
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Pacific Community's Oceanic Fisheries Program and the Forum Fisheries Agency to
build and operate such a model. Two versions of the model were constructed: the
Western and Central Pacific Ocean Bioeconomic Tuna Model Version 1 (WCPOBTM
v1) is described in Sections 4 and 5 of this paper, WCPOBTM v2 is described in Section
6, Section 7 compares the result of the two models, and Section 8 analyses management
options using WCPOBTM v2.
The above models are prescriptive in nature - they aim at determining the level
and structure of effort which will maximize rent from the fisheries, rather than at
predicting the outcome which will occur as a result of negotiations among the resource
exploiting nations. Hannesson and Kennedy (2008, 2009) develop a bioeconomic model,
simpler than WCPOBTM, of the WCPO tropical tuna fisheries which is predictive in
nature. It considers the range of management outcomes which might be predicted to
result from negotiations between the fishing nations. This work is reviewed in Section 9
of the paper.
As noted above, a bioeconomic model of the longline, pole and line and purse
seine tuna fisheries in the Western and Central Pacific Ocean (WCPO) was developed in
the mid to late 1990s by the Secretariat of the Pacific Community (SPC) and the
University of Queensland (Bertignac et al, 1998, 2000). This multi-species, multi-fleet
bioeconomic model (known hereafter as the WCPOBTM v1) was subsequently used to:
estimate rents generated by the tuna fisheries occurring in the waters of Pacific Islands
Nations for various levels and combinations of purse-seine, pole-and-line, frozen tuna
longline, and fresh tuna longline fishing effort (Bertignac et al. 2000); examine the
potential for Forum Fisheries Agency (FFA) members to increase access fee revenue
from the purse seine fishery (FFA 1999a); and examine the impact of increases in the
catch of bigeye and yellowfin tunas in the purse seine fishery on total revenues generated
by all tuna fisheries within the FFA ―region‖ (FFA 1999b).
The results of the Bertignac et al. (2000) study, as discussed in more detail in
Section 5, indicated that rents could be increased substantially in the fishery above the
then prevailing levels by significantly decreasing the size of all fleets with the possible
exception of the tuna longline fleet. This study also suggested that the countries of the
region could benefit significantly by changing the level and structure of access fees
levied as a percentage of total catch revenue. The Pacific Islands Forum Fisheries Agency
also conducted an analysis using WCPOBTM v1 which indicated rents generated in the
purse seine fishery would be maximized when effort levels were reduced by around 5060 per cent of their 1996 levels, that increases in catch per unit effort and rents would be
substantial (FFA, 1999a), and that an increase in the CPUE of bigeye tuna by purse seine
vessels was likely to a lead to a decrease in revenues in the longline fishery greater than
the increase in revenues in the purse seine fishery, while for yellowfin the decrease in
revenues in the longline fishery would be less than or of similar magnitude to the
resulting increase in revenues in the purse seine fishery (FFA, 1999b).
A major outcome of these analyses was the prediction that the level of rent
generated in the WCPO tuna fishery could be increased significantly through a reduction
A-16
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
in the level of fishing effort in the purse seine fishery. The primary driver of the
estimated increase in rents available under a reduction in purse seine effort is the increase
in rents in the purse seine fishery rather than in the longline and pole and longline
fisheries. For example, WCPOBTM v1 predicted that if purse seine effort levels were cut
by 20 per cent the total catch would fall by 10 per cent with CPUE increasing by 12 per
cent. In effect the model predicts that a 20 per cent reduction in effort levels in the ―FFA
region‖, which leads to a 20 per cent reduction in the cost of the production of that effort,
would result, assuming constant prices, in a fall of 10 per cent in revenue and an increase
in rents in the purse fishery of around two thirds (from US$78 million to US$130
million). Where prices are assumed to be dependent on supplies from the FFA region, to
the extent that a 1 per cent reduction in supplies from the FFA region is assumed to lead
to a 0.55 per cent increase in prices received, revenues are estimated to fall by only 6 per
cent and rents to more than double to (US$166 million).
These results were used to argue that by reducing purse seine effort the Parties to
the Palau Arrangement 3 could increase the level of rent generated by the purse seine
fishery in their EEZs and hence have the potential to increase the level of fees they are
able to charge for access to their waters (see, for example, Geen 2000). However,
questions as to the validity of the results of the WCPOBTM v1, particularly with regard
to the assumed relationship between total catch and catch per unit effort were raised.
Long term trends in the fishery have seen significant increases in purse seine catch levels
accompanied by a steady if not increasing CPUE for many fleets, at least with regard to
skipjack. Figures 4 and 5 show total purse seine catch in the Western and Central Pacific
Convention Area (WCP-CA) and CPUE for the purse seine fleets of the major distant
water fishing nations (DWFNs) fleet for skipjack and yellowfin respectively.
Figure 4: Skipjack tuna CPUE for Japanese, Korean, Chinese-Taipei and US purse
3
The Palau Arrangement as it currently stands places limits on the total number of purse seine vessels
allowed to be licensed within the national waters of Parties to the Nauru Agreement Concerning
Cooperation in the Management of Fisheries of Common Interest (the Nauru Agreement). The Twelfth
Meeting of the Parties to the Nauru Agreement in Palau in May, 1993 set the current level of 205 vessels.
The Parties to the Nauru Agreement (PNA) are proposing to amend the Palau Arrangement and introduce a
Vessel Day Scheme (VDS) in which effort within the national waters of the Parties will be limited by the
imposition of limits on the number of vessel days that can be expended in their national waters.
A-17
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
seiners fishing in the WCP–CA and total purse seine skipjack tuna catch in WCPCA
Source for Figures 4 and 5: Williams and Reid (2005)
Figure 5: Yellowfin tuna CPUE for Japanese, Korean, Chinese-Taipei and US purse
seiners fishing in the WCP–CA and total purse seine yellowfin tuna catch in WCPCA
In a subsequent study aimed at examining management strategies to maximise the
economic benefits obtained by Pacific Island Nations from the exploitation of their tuna
resources WCPOBTM v1 was developed further: a reexamination of the issue of the
appropriate treatment of the relationship between total catch and catch per unit effort was
undertaken and several other components of the model were revised. This led to a revised
version of the model (WCPOBTM v2) being developed. In Sections 4 and 5
specifications and parameters for WCPOBTM v1 are provided followed by a description
of the results of the policy analysis undertaken by Bertignac et al 2000. Following this, in
Section 6 the changes to the model made under WCPOBTM v2 are detailed with the
results of the policy analysis undertaken by Reid (2006) presented and compared in
Section 7. Section 8 of the paper reviews the management policy analysis undertaken on
the basis of WCPOBTM v2. In Section 9 the analysis of the negotiations between
resource-exploiting nations undertaken by Hannesson and Kennedy (2008, 2009) is
reviewed.
4: The Western and Central Pacific Ocean Bioeconomic Tuna Model Version 1
4.1: Population Dynamics Model
The tuna population dynamics model is a spatially-disaggregated, multigear,
multispecies simulation model. The model is age structured, to account for growth and
gear selectivity, and includes tuna movement based on a diffusion-advection equation in
which the advective term is proportional to the gradient of a habitat index. The model
predicts the spatial distribution of spawning, the age-structured population and the catch
for various fishing fleets as a function of specified levels and distributions of fishing
effort. Details of the structure of the population dynamics model are provided in
Bertignac, Lehodey, and Hampton (1998), which deals with one species (skipjack) and
two fleets (purse-seine and pole-and-line). A summary description of the expanded
A-18
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
version of the Bertignac, Lehodey, and Hampton model used in the Bertignac et al.,
(2000) study is provided below.
4.2: Species and Fleets Treated by the Model
Four tropical tuna species are included in the model—yellowfin (Thunnus
albacares), bigeye (T. obesus), albacore (T. alalunga) and skipjack (Katsuwonus
pelamis). Five different gear types, each with separate catchability and age-based
selectivity coefficients, are included. They are: eastern Pacific purse seine, western
Pacific purse seine, frozen tuna longline, fresh tuna longline, and pole-and-line. As noted
earlier, the eastern Pacific purse seine fleet is included in the biological model, since its
effort affects the sizes of migratory stocks in the western Pacific, but is not included in
the economic model since the focus is on the FFA region.
The five gear categories have been further stratified on the basis of nationality, as
described in the Harvesting Model section, reflecting the differences in productivity and
cost structure among the diverse range of vessels operating in the fishery. A total of 16
different fleets are represented in the model. This differentiation of the fleets in terms of
cost structure and prices is made to improve the accuracy of the profitability estimates. It
will also enable more flexibility in examining the effects of different policy decisions,
such as the licensing arrangements for particular fleets. However, it was believed that the
accuracy of all fleet-specific economic parameters is not sufficient to warrant the
reporting of profit levels for each of the 16 fleets. Instead, profit for five general fleet
categories was reported—the purse-seine fleet, the frozen sashimi longline fleet, the
frozen albacore longline fleet, the fresh tuna longline fleet, and the pole-and-line fleet.
The three categories of longline fleets serve different markets, and the frozen albacore
fleet targets a different species than the frozen sashimi and fresh tuna longline fleets.
Monthly catch and fishing effort data for each fleet were obtained at 5° square
resolution for the period 1988–94. Each fleet‘s total catch and effort in each 5° square
over the period were computed for each month, and then scaled by the ratio of the 1996
catch or effort in that month to the total catch or effort in that month over the period
1988–94 to obtain annual distributions of catch and effort that summed to the observed
1996 levels. These reference distributions of catch and effort over the year and over the
fishery are used to parameterize the model (see Section 4.7 Parameterizing the Model),
and the distribution of effort is also used in the simulations to examine the bioeconomic
effects of different levels of effort.
Table 1 Average Catch of Major Tuna Species by Gear Type in the SPC Statistical Area,
1988–94
A-19
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Source: South Pacific Commission Yearbooks 1988–94.
4.3: Spawning, Recruitment, and Movement
In most models of fish-population dynamics, spatial variation in the stocks is
ignored. However, tropical tunas are highly migratory, and their densities vary strongly
over space and time. It was, therefore, considered necessary to build a spatially
disaggregated model which incorporates the movement and spatial distribution of the fish
at all stages of their life history, as well as the spatial distribution of fleet-specific fishing
effort. To do this, the entire Pacific Ocean between 45°N and 45°S at a spatial resolution
of 5° of latitude by 5° of longitude and over monthly time intervals was considered.
Skipjack and Yellowfin
Spawning of skipjack and yellowfin was assumed to occur in a 5° square—month
stratum if the mean sea surface temperature (SST) was more than 25°C (skipjack) and
26°C (yellowfin). Monthly average temperature data from the World Ocean Atlas (WOA)
climatology were used for determining spawning areas (Levitus and Boyer 1994). For the
first three months after spawning, larvae were assumed to be distributed passively by
monthly average ocean currents (obtained from the general circulation model OPA
developed by the Laboratoire d‘Oceanographie Dynamique Management of the Pacific
Tuna Fisheries 157 et de Climatologie, Paris). After this time, juvenile skipjack and
yellowfin movement is based on a habitat index. The habitat index consists of two
components — sea surface temperature and food availability. Food availability is based
on the redistribution of average monthly primary production (chlorophyll) by average
monthly ocean currents. It has been determined in a separate study (Bertignac, Lehodey
and Hampton 1998), and was, thus, exogenous to the bioeconomic model. Movement is
parameterized such that directed movement (or advection) tends to occur in the direction
of positive habitat gradients. Conversely, greater undirected movement (or diffusion)
occurs in areas of low habitat index. Such diffusive movement may be thought of as
mimicking searching behavior. For full details of the parameterization of movement in
relation to habitat index, see Bertignac, Lehodey, and Hampton (1998).
Bigeye and Albacore
For bigeye and albacore, which are primarily sub-surface tunas exploited by
longliners, there is less understanding of their environment and how it influences their
distribution. Therefore a simpler hypotheses consistent with the current understanding of
the life histories of these species was adopted.
A-20
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
For bigeye, it was assumed that the distribution of spawning is limited to areas
where the SST is >23°C. As with skipjack and yellowfin, larvae are moved passively in
ocean currents for the first three months. After this, they are assumed to move in a simple
diffusive manner, which is the simplest hypothesis of a gradually dispersing population.
For albacore, it was assumed that recruitment occurs in the region south of 30°S,
consistent with the results of other analyses (Fournier, Hampton, and Sibert 1998).
Diffusive movement then occurs, with movement bounded in the north by the equator.
4.4: Mortality and Age Structure
Individual cohorts (quarterly in the case of skipjack, yellowfin, and bigeye;
annual in the case of albacore) are tracked in the model, allowing the age structure of the
populations at any point in time to be determined. The initial size of the cohorts is
determined by the level of recruitment, after which time cohort attrition occurs due to
natural and fishing mortality. The natural mortality rate is assumed to be constant in
space and time.
The fishing mortality rate of a particular age class in a stratum is the sum across
fleets of the product of fishing effort, the corresponding catchability coefficient, and the
selectivity coefficient. The catch in the stratum is simply the product of the fishing
mortality rate, the local population size, and the average weight for each age class (as
determined by growth and length-weight relationships), summed over age classes.
4.5: Summary of Parameters of the Biological Model
The biological parameters in the population dynamics model are described in
Bertignac, Lehodey, and Hampton (1998). The parameter values, together with their
sources, are reported in Table 2 to permit comparison with those used in the Bertignac,
Lehodey, and Hampton (1998) model.
Table 2: Main Biological Parameters (and References) used in the Simulation Model
(for references see Bertignac et al. (1998, 2000))
A-21
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
4.6: Harvesting Model
In a single species, single cohort, single gear type and spatially aggregated
context, the harvesting model would take the following form:
H = AEX
A-22
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
where: H is the monthly harvest in tons, E is the level of fishing effort in vessel months,
and X is the level of stock in tons. A is known as the catchability coefficient and describes
the proportion of the stock that is taken by a single unit of fishing effort.
By adding some extra detail to the model, it is possible to represent the four
different species (and a number of cohorts within each species), four different gear types,
and to account for some of the spatial heterogeneity inherent in the fishery. As discussed
earlier, this level of disaggregation is important because it facilitates the modeling of
interactions among gear types. The proportion of each cohort of each species represented
in vessel catches varies across fleets. Catch by one fleet impacts stocks and affects other
fleets‘ catch rates, total catch, and profit levels. To measure the impact of each fleet on
other fleets, and to optimize the mix of fleets, it is necessary to use a disaggregated
model. Including these factors in the harvest function gives the following functional
form:
Ha,s,r,m,g, f = As,g, f Sa,s,gEr,m,g,f Xa,s,r,m
where: a is age class, s is species, g is the gear type, f is fleet nationality, m is the month,
and r is the region (5o latitude by 5o degree longitude grid). S is the selectivity coefficient,
which modifies the catchability coefficient, A, to allow for the fact that catchability of
juveniles of each species is different from that of adults. The selectivity coefficients are
presented in Figure 6.
Fishing effort is varied for the four fleet categories, which were identified earlier
as operating in the FFA region. These fleet categories are: (i) Purse seine fleets: US,
Japanese, Korean, Taiwanese, ―other‖ western Pacific, and eastern Pacific fleets; (ii)
Pole-and-line fleets: Japanese north (of 20°N), Japanese south (of 20°N), and domestic
(i.e., FFA member countries) pole-and-line fleets; (iii) Frozen tuna longline fleets:
Japanese, Korean, and Taiwanese fleets; and (iv) Fresh tuna longline fleets: Japanese,
Chinese, Taiwanese, and ―other‖ western Pacific fleets.
The spatial distribution of effort of each fleet in each month is held constant at its
1988–94 average in the sense that the proportion of total fleet effort allocated to each
region is maintained, although the total level of effort may be varied. The annual harvest
of each species by each fleet is obtained from the harvesting model by aggregating across
regions, months, and age classes.
4.7: Parameterizing the Model
The model was not subjected to a comprehensive parameterization by fitting it to
observed data at the best spatial and temporal resolution possible. As a first step, an
approximate tuning procedure was applied by adjusting the recruitment (or spawning) so
that stock biomass estimates equal those obtained independently from tagging studies
(skipjack and yellowfin) or other stock assessments (bigeye and albacore), and then
adjusting catchability coefficients to levels such that estimated catches of each species by
each fleet for the 1988–94 period approximate the reported catches. The recruitment and
A-23
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
catchability coefficients obtained in this way and used in the bioeconomic simulations are
reported in Table 3.
4.8: Prices and Costs
Current tuna prices for all fleets are as reported in Hand and Forau (1997b), and
costs are as reported in Hand and Forau (1997a). All values are in 1995 US dollars. The
price received by each fleet for each species is a weighted average of the prices received
for the various size classes of the species in the various markets served by the fleet. The
cost of fishing effort includes the long-run opportunity cost of capital, but excludes
access fees.
Purse-seine Fleets
Prices for all purse-seine fleets are US$1,000 per mt for bigeye, and US$1,063 per
mt for yellowfin. Prices for skipjack for all purse-seine fleets, except Japan, are US$923
per mt. Average prices received for skipjack by the Japanese fleet are higher because
higher-value markets are supplied. A weighted average of the prices received on these
higher value markets of US$1,161 per mt is used (see Hand and Forau 1997b).
Figure 6: Selectivity Coefficients by Age Class, Species, and Gears Used in the
Simulation
Note: The albacore coefficients are estimated from a stock assessment analysis (Fournier,
Hampton, and Siebert 1998). For the three other species, selectivity coefficients are
extrapolated from length-frequency distributions of catches by gears (SPC data) (see text
for details).
A-24
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Table 3: Catchability Coefficients for Each Fleet Included in the Simulation Model
Pole-and-Line Fleets
Japanese pole-and-line vessels supply skipjack and yellowfin to higher-value
markets than their domestic counterparts (Hand and Forau 1997b), and, therefore,
different prices are used for Japanese pole-and-line and domestic vessels‘ pole-and-line
catch. The prices for the Japanese fleet are US$2,246 per mt, and US$4,196 per mt for
skipjack and yellowfin, respectively, while the prices for the domestic fleets are US$982
per mt and US$898 per mt for skipjack and yellowfin, respectively.
Frozen Tuna Longline Fleets
Prices received for the catch of Japanese longline vessels are based on prices
received at 42 Japanese ports, as reported in Hand and Forau (1997b). These prices are
US$2,440 per mt for albacore, US$10,520 per mt for bigeye, and US$5,610 per mt for
yellowfin. Due to the 4–5% tariff and preference for Japanese caught tuna in the main
sashimi markets of Japan, it is assumed that Korean and Taiwanese vessels receive 5%
less for frozen longline catch than Japanese vessels. Taiwanese vessels also target
albacore for the canned market, receiving US$2,280 per mt.
A-25
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
At this point, it should be noted that while the net of tariff prices of frozen and
fresh longline-caught tuna supplied to the Japanese market by the Korean, Taiwanese,
Chinese and other fleets are the appropriate prices to use when calculating the private
profits of these fleets, using these prices to calculate total fishery rent leads to a slight
underestimate. The net of tariff prices is used to implement a non-negative profit
requirement for each fleet. It should be borne in mind while interpreting the results of the
simulations that the estimates slightly underestimate fishery rent.
Prices for bycatch are US$2,830 per mt for blue marlin, US$4,560 per mt for
black marlin, US$5,880 per mt for striped marlin, US$6,050 per mt for swordfish, and
US$1,850 per mt for sailfish (prices obtained from AFMA - see Bertignac et al. (1998)).
It is assumed that the CPUE of these bycatch species is constant—no population
dynamics models for these species are developed. However, bycatch does contribute a
significant amount of revenue which is attributed to fleets, for any effort level, on the
basis of historical CPUE for these species. Japanese longliners have a much higher
CPUE, and, therefore, value per unit effort, of bycatch species (US$44.43 per 100 hooks)
than Korean vessels (US$17.10 per 100 hooks).
Fresh Tuna Longline Fleets
Prices received by Japanese fresh tuna longline vessels are based on prices
received at Yaizu, as reported in Hand and Forau (1997b). These prices are US$2,980 per
mt for albacore, US$9,460 per mt for bigeye, and US$7,830 per mt for yellowfin. It is
assumed that Taiwanese, Chinese, and domestic FFA vessels receive 5% less than
Japanese vessels.
Bycatch prices are the same as those used for longline freezer catch, and bycatch
value per unit effort is calculated on the basis of these prices and historical CPUE. The
following bycatch values of CPUE are assigned to the fresh longline fleets: US$54.01 per
100 hooks for the Japanese fleet; US$20.17 per 100 hooks for the Chinese fleet;
US$18.62 per 100 hooks for the Taiwanese fleet; and US$25.39 per 100 hooks for the
domestic fleets.
Price Elasticities of Demand
The WCPO currently supplies between 30% and 40% of the world‘s pole-andline, purse-seine, and longline catches of tuna. Since some of the bioeconomic
simulations will involve significant departures from current catch levels of species
supplied to markets for canning (mainly by purse-seine and pole-and-line vessels) and for
fresh and frozen tuna consumption (mainly by longline vessels), demand elasticities are
used to allow market prices to vary according to quantities supplied. The elasticities take
into account the price elasticity in the final demand market, the various markups on the
price of raw tuna, the share of the WCPO in world catch, and the elasticity of supply
from competing regions.
A-26
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Demand elasticities are calculated for the catches of each of two types of fleets:
those using purse-seine and pole-and-line gear, whose catch is destined for the canning
market; and those involved in fresh and frozen longline operations, whose catch is mainly
destined for the Japanese sashimi market. The following simple model can be used to
estimate the elasticity of demand for raw tuna from either of these fleets. Let world
demand be Q = Qf + Qo, where Qf is sourced from the WCPO region and Qo from other
sources, and let the retail price be P = Pr + Pp, where Pr is the price of raw tuna, and Pp
is the cost of processing and distribution. Assuming that the latter mark-up remains
constant, the elasticity of demand for tuna products in the retail market can be expressed
as:
e = -(dQf/dPr + dQo/dPr) (Pr+ Pp)/(Qf + Q o)
Using this expression, the elasticity of demand for raw tuna from the WCPO region
can be expressed as:
er = -(dQf/dPr)(Pr/Qf) = er(Sr/Sf) + [eso (1/Sf )-1]
where Sr is the share of the price of raw tuna in the price of tuna at the retail level, Sf is
the share of the region‘s output in the world market, and eso is the elasticity of the tuna
supply from the rest of the world.
Using parameter values obtained from Campbell (1998), the elasticity of demand
for raw tuna supplied to the canning markets by purse-seine and pole-and-line fleets
operating in the WCPO is estimated to be 1.55, and that for fresh and frozen tuna
supplied by the longline fleets is 2.53. Since albacore caught by the Taiwanese longline
fleet is used for canning, these catches were grouped with the purse-seine and pole-andline catches in calculating the price response.
A linear demand function was used to calculate the price responses in each of the
two main markets:
where pe,g,j is the current price for species e supplied by gear category g in market j,
pe,g,j96 is the price in 1996, Cj and Cj96 are the total catches supplied from the WCPO
region to market j by all gear types, and j is the elasticity coefficient, consisting of the
inverse of the demand elasticity for raw tuna. Since the elasticity coefficients are based
on point rather than arc elasticities of demand, the calculated price responses will only
approximate the effects of changes in quantities supplied and will decline in accuracy the
further simulated catches depart from current levels.
Costs
A-27
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
The basic unit of purse-seine and pole-and-line effort in the bioeconomic model is
days fished; whereas for the longline fleets, it is hooks fished per day. Information on
annual costs, number of days fished per year, and number of hooks fished per day is used
to calculate the unit cost of effort of each fleet (Hand and Forau 1997a).
Purse-seine Fleets
Estimated total costs of fishing per day are US$19,417 for US purse seine;
US$15,500 for Taiwanese purse seine; US$21,033 for Korean purse seine; US$23,607
for Japanese purse seine; and US$14,671 for domestic purse seine vessels.
Pole-and-Line fleets
Due mainly to large variations in vessel size, there is a substantial difference in
the cost of pole-and-line fishing between Japanese vessels operating the western and
central Pacific and domestic vessels of FFA countries. The estimated total costs of fishing
per day for Japanese vessels (North and South) and domestic pole-and-line vessels are
US$9,134, US$14,500, and US$2,391, respectively.
Frozen Tuna Longline Fleets
Among the frozen tuna longline fleets included in the model—Japan, Korea, and
Taiwan—data are available for the Japanese cost of fishing only. Data in Hand and Forau
(1997a) are for the 100–200 and 200 GRT size classes. With a cost per day of US$8,533
for 100–200 GRT vessels and US$12,433 for 200-500 GRT vessels, and an average
number of hooks per day of 2,811 and 2,949, respectively, the cost per hook for each size
class was estimated at US$3.04 and US$4.22, respectively. A weighted average was then
taken on the basis of 31% of hooks being set by the 100– 200 GRT size class over the
1988–94 period and 68% being set by the 200–500 GRT class, giving a final cost per day
of US$3.85 per hook for the Japanese fleet. The use of this cost figure for the Korean and
Taiwanese fleets would lead to negative profits over the entire range of the fishery. In the
absence of other information, costs of fishing were assumed which resulted in a breakeven performance at the 1996 levels of effort and catch for these fleets. These break-even
costs are US$3.35 per hook for the Korean fleet and US$1.05 per hook for the Taiwanese
fleet.
Fresh Tuna Longline Fleets
Again, the only reliable cost data for this fleet category are for Japanese vessels.
Hence, these data were used as a proxy for all of the fresh longline fleets except China,
for which breakeven costs in 1996 are assumed.
It was necessary to convert cost per day for various vessel size classes to a
weighted average cost per hook. The costs of fishing were US$4,853 per day for the 10–
30 GRT size class, US$9,499 per day for the 50–100 GRT size class, and US$12 433 per
day for the 200–500 GRT size class. The numbers of hooks per day for each fleet were
A-28
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
1,966, 2,312 and 2,640, respectively, over the 1988–94 period. This resulted in costs per
hook of US$2.47, US$4.11 and US$4.71, respectively. Given that 94% of hooks were set
by the 10–30 GRT class fleet, 5% by the 50–100 GRT class fleet, and 1% by the 200–500
GRT class fleet, the final weighted average cost of fishing was estimated at US$2.57 per
hook. For Chinese vessels, the cost was set to US$2.80 per hook.
5: Management Policy Analysis using WCPOBTM v1
Bioeconomic simulations were conducted on the basis of percentage changes in
the 1996 level of fishing effort within the FFA region. According to the FFA vessel
register, 1996 vessel numbers equated to 182 purse seiners, 58 pole-and-liners, 642
freezer longliners, and 450 fresh longliners (Gillett 1997). These figures include only
vessels that are licensed by at least one FFA member country. The effort levels of fleets
operating in areas of the WCPO outside the FFA region were held constant at 1996
levels.
Three types of bioeconomic simulations were undertaken: varying the 1996 effort
levels within the FFA region for the four fleet categories by the same relative amounts;
varying the effort levels of the individual fleet categories in sequence by set relative
amounts; and using an optimization algorithm in which effort for each fleet category was
varied simultaneously in order to maximize the value of an objective function (either the
value of fishery rent generated within the FFA region or the returns to FFA member
countries).
The simulations were employed to generate predicted values, for all fleets in the
regional fishery, of total revenues, total costs (exclusive of access fees and including a
normal rate of return on capital), access fees, fishery rent (total revenues less total costs),
and total private profit (net of access fees) of the combined fleets. Access fees are set at
4% of the gross value of the catch of each fleet, although Swan (1997) has estimated
actual access fee revenues at the time to be around 3.5% of gross value. FFA regional
returns are measured as the sum of access fee revenues and the profits of local fleets such
as the Solomon Islands purse seine fleet.
Consider first the effect on total revenue, costs, and fishery profitability of
changes in effort levels relative to 1996 levels in the FFA region. In this case, equivalent
proportional changes are made in the effort levels of all fleets represented in the model.
The results of the model indicated that annual fishery rent generated in the FFA region
was around $US108 million per annum at the 1996 effort levels. Fishery rent is fully
dissipated at a level of effort 20-30% higher than the 1996 level. Private profit falls to
zero at an effort level 10-20% higher than the 1996 level. Both fishery rent and private
profit are maximized at approximately 50% of the 1996 effort level, with the private
optimal effort level being marginally lower than the rent maximizing level because of the
4% royalty. The results suggest that higher access fees could be sustained at lower levels
of effort.
A-29
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Next the model is used to examine the effects of changing the effort of one fleet
(to 80%, 90%, 110%, and 120% of the 1996 level) on the profitability of that fleet and of
the other fleets, holding the effort of the other fleets constant at the 1996 level. Consistent
with the finding reported above that the overall level of effort is significantly above the
optimal level, the profitability of each fleet, except the frozen tuna longline fleet, rises
(falls) as its effort level falls (rises). The effects of the effort level of a given fleet on the
profitability of other fleets can be interpreted as estimates of the ―marginal bioeconomic
interaction‖ between the fleets. The following observations can be made regarding the
extent of bioeconomic interaction among the fleets predicted by the model:
a) increases in purse seine effort have negative impacts on fresh tuna longline
profitability, but relatively little effect on pole-and-line and frozen tuna longline
profitability. Purse seiners catch juvenile yellowfin and bigeye in fishing areas favored
by the fresh tuna longline fleets, but are less active in areas preferred by the frozen
tuna longline fleets. Since pole-and-line fleets catch mainly skipjack, which is in
plentiful supply, the purse seine skipjack catches have little impact on the profitability
of the pole-and-line fleet;
b) increases in pole-and-line effort have relatively little impact on the profitability of the
other fleets, because pole-and liners catch mainly skipjack tuna, which is in plentiful
supply;
c) increases in frozen tuna longline effort have a strong negative impact on fresh longline
profitability because of their impact on the levels of migratory stocks, but little impact
on the profitability of the other fleets, which depend on different species or age
classes; and
d) increases in fresh tuna longline effort have relatively little impact on the profitability
of the other fleets. While the fresh tuna longline fleet targets the same species as the
frozen longline fleet, it operates in different areas and on a smaller scale.
Since the results of the model suggest that some strong bioeconomic interactions
exist among the four fleet categories being considered it may be possible to increase
fishery rent, or some other measure of economic performance, by varying the mix of
effort levels. To consider this, the simulation model was interfaced with a Simplex
optimization algorithm to attempt to locate an optimum level and mix of gears given the
objective of maximizing fishery rent in the long-run, or maximizing the returns to the
FFA region under the current fee structure. Several constraints were placed on each
optimization to prevent it entering an unreasonable domain. These were that effort
multipliers (defined as one plus the proportionate change in effort relative to the 1996
level) must remain positive; the global profitability of each fleet over the entire
geographical range of its activities (i.e., including operations outside the FFA area) must
remain positive; and the population biomass of each of the four species must not fall
below 40% of their virgin levels (determined by the equilibrium population in the
absence of effort). The latter constraint was applied in order to impose a reasonable
conservation guideline (or limit reference point) on the stocks. Each combination of
A-30
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
effort values was applied for 15 years from the initial state (1996) in order to attain an
approximate equilibrium. Conditions at equilibrium (i.e., in year 15) were then used to
compute the variables for the optimization.
In conducting the optimizations, the frozen tuna longline fleet was separated into
two components impacting different fish stocks and markets: the frozen sashimi longline
fleet, consisting mainly of Japanese and Korean longliners, targets bigeye and yellowfin
tuna for the sashimi market; and the frozen albacore longline fleet, consisting mainly of
Taiwanese longliners, targets albacore for the canned tuna market. There are, therefore,
five fleets for which optimal levels of effort have to be determined — purse seine, poleand-line, frozen sashimi tuna longline, frozen albacore longline and fresh tuna longline.
The optimizing model was used to determine the level and composition of fishing
effort which maximized total FFA region fishery rent and the level and composition of
effort which maximized returns to the countries of the FFA region. The latter return is
calculated as 4% of the gross revenues of the distant water fishing nation (DWFN) fleets
plus the profits of the domestic fleets. It must be emphasized that the maximization of
FFA returns is constrained by the maintenance of the current fee structure, which, as
argued in Bertignac et al. (2000), is suboptimal from the regional viewpoint. The
optimizations were first carried out holding constant the prices received by the various
fleets for their catches, and then allowing prices to vary as a function of quantities of the
various species of tuna supplied to the canning and sashimi markets.
Holding fish prices constant, annual fishery rent generated in the region was
maximized at an estimated $US311 million, more than twice the value for 1996. The
maximum was obtained by reducing fishing effort for all fleets except the fresh and
frozen tuna longline fleets, which were increased significantly. The pole-and-line and
frozen albacore longline fleets were virtually eliminated from the rent maximizing
solution. The maximization of FFA region returns is achieved by increasing the effort of
groups of fleets in which some of the regional domestic fleets participate. In particular,
this is the case for the fresh tuna longline fleet, which increases by a factor of 5 (while
that of the DWFN frozen tuna longline fleet is curtailed), and that of the pole-and-line
fleet, which more than doubles. This results in the relative shares of access fees and
domestic fleet profits in total FFA region receipts going from 67% and 33%, respectively,
in a 1996 type situation to 57% and 43% at the optimum. The predicted receipts of
$US81.6 million for the FFA countries can be compared with the predicted level under
the 1996 effort levels of $US69.6 million, implying a 17% increase.
Product prices were allowed to vary as a function of the quantities of the various
species of tuna supplied to the two different markets, canning and sashimi, by means of
demand functions which provided a simple, linear link between prices by species and
gear categories and total catches supplied to each of the two markets. For more detail, see
Section 4.8 above.
The main effect of the variable as compared with fixed prices in the regional rent
maximization is that fresh and frozen longline effort is curtailed, with the former falling
A-31
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
substantially. In the case of the FFA region return, constrained by the current fee level
and structure, the price effects act in the expected directions, making longlining relatively
less attractive from a regional perspective. However, the increase in the price of canning
tuna causes a marked shift in the balance of effort in this fishery towards purse seining, as
compared with the fixed prices case.
The catches of each species for 1996 and those associated with the optimal
solutions discussed above can be compared. While there is some redistribution of catches
among fleets, resulting in lower purse seine catches and higher fresh tuna longline
catches, total catch levels under the optimized effort levels are considerably lower than
those that existed in 1996. While catch levels in 1996 are believed to be sustainable
(although there is some uncertainty regarding bigeye), the lower catches under the
optimized effort levels would afford the stocks an even greater degree of protection from
overfishing. It should be stressed, however, that the lower catches associated with the
optimized effort levels result because the model predicts increased rent at lower effort,
not because the stocks were perceived at that time to be in need of rebuilding for
purposes of conservation.
6: The Western and Central Pacific Ocean Bioeconomic Tuna Model Version 2
6.1: Overview of the WCPOBTM v2
As for WCPOBTM v1, WCPOBTM v2 consists of four separate models. They are
a population dynamics model, a catch or harvest model, a revenue model and a cost of
fishing model.
The population dynamics model simulates the size of the four main tuna stocks
caught in the Western and Central Pacific Ocean (WCPO) and Eastern Pacific Ocean
(EPO) (Figure 7) when given levels of fishing effort by the various fleets are applied to
the respective stocks.
The harvest model simulates the catch associated with a given stock size based on
fleet-specific levels of effort, catchability and selectivity of the fishing gear used by the
major fleets operating throughout the area covered by the model.
The revenue model simulates the revenues earned by the fishing fleets for a given
level of catch and the cost model determines the cost of applying the effort required to
take the catch. Cost and revenue are defined only for those fleets that are active within
the ―FFA region‖. The ―FFA region‖ is an area defined in the model to approximate the
area encompassing the EEZs of Pacific Island FFA members at a 5° square resolution,
and, therefore, contains some areas of high seas (Figure 7). There are 15 fleets that
operate within the FFA region in the model. These are:

The purse seine fleets from Japan, Korea, Taiwan, the USA, and Pacific Island
Countries (PICs). Vessels from all other nations (for example, the Philippines and
the EU) are treated as an additional single fleet;
A-32
APPENDIX IV– Discussion Paper



Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
The pole and line fleet from PICs and the Japanese pole and line fleet that
operates in ―southern‖ WCPO waters ;
The frozen longline fleets from Japan, Korea and Taiwan; and,
The fresh longline fleets from Japan, China, Taiwan and PICs.
The population dynamics and the harvest model include all of the above fleets
throughout their range (that is, inside and outside of the ―FFA region‖) plus five
additional fleets, which fish outside of the ―FFA region‖ and are defined as:





The Eastern Pacific Ocean (EPO) purse seine fleet:
The Japanese pole and line fleet operating exclusively in ―northern‖ WCPO
waters;
The Indonesian domestic fishery.
The Philippines domestic fishery.
The troll fishery.
Thus the population dynamics and harvest models model the stocks and their
interaction with the major fishing fleets throughout the Pacific Ocean while the economic
component models the interaction between economic returns and fishing activity within
the FFA region.
FFA region
Figure 7: The western and central Pacific Ocean (WCPO), the eastern Pacific Ocean
(EPO), the WCPFC Convention Area (WCP–CA in dashed lines) and “ FFA
region” as defined for the WCPOBTM.
A-33
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
6.2: Structural changes to the WCPOBTM model
This section details the structural changes to the population dynamics, the harvest
model and the revenue model incorporated into WCPOBTM v2 as compared with
WCPOBTM v1. The structure of the cost model is as for the WCPOBTM v1. Much of
the structure of WCPOBTM v1 remains, and is not repeated below.
Population dynamics model
The instantaneous monthly rates of natural mortality and weights by age class and
species are shown in Figures 8 and 9. These are taken from results generated by
MULTIFAN-CL for stock assessments presented to the 15th Meeting of the Standing
Committee on Tuna and Billfish (SCTB15). Under MULTIFAN-CL natural mortality
and weight at age are estimated from the age at recruitment, which is 0 for skipjack, 1
quarter for yellowfin, 2 quarters for bigeye and one year for albacore. In WCPOBTM v2
which models the whole population and not only the recruited stock, values for the period
from spawning to recruitment are thus also required. Values of mortality rates, M, for the
pre-recruited classes were the MULTIFAN-CL estimates, and for weight at age, the
values were the same as those in the WCPOBTM v1 model using growth parameters For
values of M for the pre-recruited classes the first values given in MULTIFAN-CL were
used, and for weight at age, the values obtained from the previous model using growth
parameters were used.
Harvest model
Selectivity coefficients
In the original model selectivity coefficients were set as follows: the albacore
coefficients were estimated from a stock assessment analysis (Fournier et al. 1998), and
for skipjack, yellowfin and bigeye, selectivity coefficients were extrapolated from lengthfrequency distributions of catches by gears. In revising the model, and given the
availability of selectivity coefficients from MULTIFAN-CL, it was decided to
parameterise the selectivity coefficients using estimates generated by MULTIFAN-CL.
A-34
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
These estimates are generated by fleet (even if two fleets use the same gear), however, in
WCPOBTM v2 they are defined by main gears (Purse Seine, Pole and Line, Longline).
Therefore, to use the MULTIFAN-CL estimates, selectivity estimates for fleets using the
same gear were combined using catches by fleets as weights and are shown in Figure 10.
Figure 10: Selectivity coefficients by age class, species, gear and fleet
Stock and effort exponents
It will be recalled from Section 3.6 above that the coefficients on effort and stock
in the harvest production function in WCPOBTM v1 were each set at unity in the
simulations. In this section a brief overview of work conducted by the SPC-OFP in
testing for non-unitary values for the stock and effort exponents in the WCPO purse seine
fishery is provided. For all other fleets it continues to be assumed that the stock and effort
exponents are equal to 1.
Effort exponent
SPC-OFP used MULTIFAN-CL to test for non-unitary values for the effort
exponent for the purse seine fishery in the WCPO by specifying the fishing mortality
function, F, as:
ln F   ln S   ln  A   ln e
(6)
where S and A are the selectivity and catchability coefficients respectively and e is the
relative level of effort scaled against average effort over the entire time period for the
A-35
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
fishery, and testing for the null hypothesis that α is equal to 1. The test was carried out for
skipjack caught on logs, Fish Aggregating Devices (FADs) and school sets in regions 5
and 6 of the MULTIFAN-CL skipjack model; and for yellowfin caught on log, FAD and
school sets in regions 2 and 3 of the MULTIFAN-CL yellowfin model (see Figures 11and
12) for MULTIFAN-CL regions for skipjack and yellowfin at the time the analysis was
undertaken).
Figure 11: Distribution of total skipjack catch, 1972-1999, and the six-region spatial
stratification used in MULTIFAN-CL
.
Figure 12: Distribution of yellowfin tuna catch, 1992−2001, and the five-region
spatial stratification used in MULTIFAN-CL
A-36
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
The results of the analysis are shown in Table 4 with the estimated effort
exponential (α) for skipjack and yellowfin catches by region and set type. There are
various methods for testing the statistical significance of α estimated using the composite
Bayesian/likelihood models employed in the analysis. SPC-OFP applied a simple
frequentist approach. Using a likelihood ratio (LR) test (with 6 degrees of freedom for the
6 additional parameters), SPC-OFP obtained p's (the probability of wrongly rejecting the
null hypothesis that α = 1) of 0.05 for skipjack and < 0.001 for yellowfin. This probably
overstates the significance for high-dimensional models such as these. So the skipjack
effort exponent, which appears only marginally significant using the LR test, might not
be significant under other types of test such as AIC or BIC. The other indicator of this is
that the coefficients were very close to 1 for all 6 purse seine fishery types for this model.
For both reasons the purse seine effort exponent for skipjack in WCPOBTM v2 is set at
1.
The yellowfin effort exponential, however, is likely to be highly significant
whatever test is applied. The analysis suggests that for yellowfin school sets α > 1,
implying that increases in effort levels impact positively on the catchability of yellowfin
for purse seine school sets. For FAD and log sets the results varied between regions and
sets. Given that under the model α was set as a single value across all areas and set types
and that there appear to be different characteristics among the set types with some
indicating that as effort grew catchability was positively impacted, some that it was
negatively impacted and some that there was no impact, the purse seine effort exponential
for yellowfin in WCPOBTM v2 was also set at 1.
Table 4: Purse seine effort coefficient (α) estimates by species by region by set type
Skipjack
Region
Log
5
Fad
Sch
0.978
Region
6
Log
1.034
Fad
Sch
1.054
1.061
0.991
1.012
Yellowfin
Region
log
2
fad
sch
0.828
Region
3
log
1.164
fad
sch
1.000
1.317
0.964
1.134
Stock exponent
SPC-OFP also used MULTIFAN-CL to test for non-unitary values for the stock
exponent for the purse seine fishery in the WCPO by specifying a function for the rate of
fishing mortality, F  H / X , as:
ln  F   ln  S   ln  A  ln  e   (   1)ln X
A-37
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
where X is the biomass of the stock scaled relative to the average biomass, A, S and e
are as before. The null hypothesis is that (   1) is equal to 0. The test was again carried
out for skipjack caught on log, FAD and school sets in regions 5 and 6 of the
MULTIFAN-CL skipjack model and for yellowfin caught on log, FAD and school sets in
regions 2 and 3 of the MULTIFAN-CL yellowfin model.
Once again SPC-OFP applied a simple frequentist approach using a likelihood
ratio test (with 6 degrees of freedom for the 6 additional parameters), and obtained p's for
skipjack and yellowfin of < 0.001. Further, all the estimates for (   1) were negative as
shown in Table 5.
Table 5: Purse seine stock coefficient (β-1) estimates by species by region by set type
Skipjack
Region
Log
5
Fad
Sch
Region
Log
6
Fad
Sch
-0.331
-0.187
-0.213
-0.305
-0.370
-0.383
Yellowfin
Region
log
2
fad
sch
Region
log
3
fad
sch
-0.719
-0.758
-0.712
-0.198
-0.683
-0.128
The stock exponents generated by the MUTLTIFAN-CL analysis were
incorporated in WCPOBTM v2 by specifying the harvest function as:

1
s ,g
H a , s ,r ,m, g , f  As , g , f Sa , s , g Er ,m, g , f X Tropic
X a , s ,r ,m
s ,m
where X Tropic is the relative inter-tropic (defined as the area between 20ºS and 20ºN and
110ºE and 150ºW) stock biomass for each species during each month and (   1) is
specified by gear type and species. This specification was used in order to ensure to a
reasonable degree that a similar spatial aggregation was used as that which is used in the
MULTIFAN-CL analysis. Relative stock was calculated as the stock in the given month
divided by the average stock which was assumed to be that estimated at equilibrium
under current effort levels (that is, where X Tropic  1 ).
As previously outlined the stock exponent coefficients analysis was carried out
for the WCPO purse seine fishery only. For this fishery (   1) was set at -0.3 for
skipjack and -0.7 for yellowfin based on the results of the MULTIFAN-CL analysis as
outlined above. No estimates were obtained for bigeye catches in the purse seine fishery
nor for the other fisheries in the model including the EPO purse seine fishery. As no
analysis was conducted for these fleets and they operate, at least partially, outside of the
inter-tropic region the assumption used in WCPOBTM v1, that is that (   1) = 0, was
A-38
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
maintained. Future work may be worthwhile to test the null hypothesis that (   1) is
equal to 0 for these fleets.
As described in this and the previous section SPC-OFP tested for non-unitary
values for the stock and effort exponents separately. Consideration was later given to
testing for non-unitary values for the stock and effort exponents simultaneously but it was
considered that little would be gained by doing so. As detailed above in the case of
skipjack, the effort exponent was not found to be significant and this will not change by
estimating the effort and stock exponents simultaneously. In the case of yellowfin it is
likely that the same result would be obtained if the effort and stock exponents were
included simultaneously: the effort exponents would vary by region and set type and once
again it would be necessary to set the effort exponent to the default value of 1 for the
purse seine fishery in the bioeconomic model. However, in future research this issue may
be worth revisiting.
Recruitment and Catchability
As in WCPOBTM v1, spawning in a 5 by 5 degree cell is ―tuned‖ to get a stock
size in the range of what was estimated through independent stock assessment analysis.
Tagging studies were used in tuning WCPOBTM v1. Estimates obtained by
MULTIFAN-CL are used for tuning WCPOBTM v2. The comparison between
WCPOBTM v2 and MULTIFAN-CL populations after tuning (i.e. population sizes at age
by species, observed catches and F at age are reasonably similar) is shown in Figure 13.
Figure 13: Population at age estimated in MULTIFAN-CL and obtained in
WCPOBTM v2 for the four tuna species
Catchability coefficients
A-39
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Catchability coefficients were estimated for both inside and outside the ―FFA
region‖ by tuning predicted catch to observed catch within and outside the ―FFA region‖
under observed effort levels. The observed catch shown in Table 6 is the average catch
over the period 1997-2000 (SPC database). In Table 7 the derived catchability
coefficients are shown by fleet and species.
Recruitment
During this process, it appeared that recruitment in the fishing areas of the
Philippines and Indonesia was not sufficient to support the large catches of those fleets,
consisting of very small fishes in the case of Indonesia. Two causes are likely to be
responsible for this. First, the assumed movement of larvae and juveniles from spawning
to recruitment may not allow fish to be recruited to the fishing area of those fleets.
Second, in MULTIFAN-CL, the spatial resolution is coarser than in WCPOBTM v2 and
thus the model fishing areas of the two fleets could be larger, meaning that the two fleets
could have access to a larger population. To correct for this likely bias, fishing effort was
spread somewhat more widely, and local recruitment was increased.
Table 6: Average annual catch by fleet used for tuning model (1997-2000)
A-40
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Revenue and cost models
Revenue and cost parameters for fleets that operate within the FFA region are
presented in Tables 8 and 9 and are based on data provided in Reid et al. 2003 and reflect
estimates of the cost structure and prices received over the period 1997-2001.
Table 7: Catchability coefficient by fleet and species
A-41
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Table 8: Cost and price parameters
Fleets
Cost
(US$)
parameters
Purse seiners US
21,949 per day
Purse seiners Japan
28,191 per day
Purse seiners Korea
21,124 per day
Purse seiners Taiwan
15,747 per day
Purse seiners Others (non
17,047 per day
PI)
Purse seiners Others_(PI) 10,339 per day
Pole_and_line_Japan_So 14,500 per day
uth
Pole_and_line_Others
2,931 per day
Longline_frozen_Japan 3.04 per hook
Longline_frozen_Korea 2.33 per hook
Longline_frozen_Taiwan 1.02 per hook
Longline_fresh_Japan
1.87 per hook
Longline_fresh_China
1.28 per hook
Longline_fresh_Taiwan 1.53 per hook
Longline_fresh_Others 1.51 per hook
Prices (US$/Mt ex-vessel)
Skipjack Yellowfi
n
803
1125
1034
1479
730
1061
730
1061
Bigeye
1125
1479
1061
1061
Albacor
e
-
730
1061
1061
-
730
1714
1061
4268
1061
-
-
776
-
993
4268
3830
3830
4242
5239
5390
4110
7513
6779
6779
10636
5132
4659
5570
2712
2532
2532
2712
2532
2532
2532
Table 9: Price elasticity of demand parameters
Fleets
Price elasticity
Skipjac Yellowfi
k
n
1.90
1.90
1.90
1.90
1.90
1.90
1.90
1.90
Purse seiners US
Purse seiners Japan
Purse seiners Korea
Purse seiners Taiwan
Purse seiners Others (non
1.90
PI)
Purse seiners Others_(PI) 1.90
Pole_and_line_Japan_So
1.90
uth
Pole_and_line_Others
1.90
Longline_frozen_Japan Longline_frozen_Korea Longline_frozen_Taiwan Longline_fresh_Japan
Longline_fresh_China
Longline_fresh_Taiwan Longline_fresh_Others -
Bigeye
1.90
1.90
1.90
1.90
Albacor
e
-
1.90
1.90
-
1.90
1.90
1.90
1.90
1.90
9.97
9.97
9.97
9.97
9.97
9.97
9.97
1.90
9.97
9.97
9.97
9.97
9.97
9.97
9.97
A-42
6.46
6.46
6.46
6.46
6.46
6.46
6.46
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
7: Comparison of the Results Generated by WCPOBTM v1 and WCPOBTM v2
In this section a comparison of results generated by the previous and current
versions of the WCPOBTM is presented. The model runs conducted examine:


The effect of changes to purse seine effort on CPUE and economic rents in the
purse seine fishery, and
The effect of an increase in purse seine catchability of bigeye and yellowfin on
longline catches and fishery revenue.
These analyses conducted using the WCPOBTM v1 were presented to the 3rd meeting of
the Skipjack Species Working Group in April 1999 (FFA 1999a and 1999b).
However, before presenting these analyses a comparison of the base case
scenarios under both models for the purse seine fishery is presented to highlight some of
the differences between the models resulting from their underlying data.
Base case results for the purse seine fishery under WCPOBTM v1 and v2
Under WCPOBTM v1 aggregate catch and effort levels are 1996 levels and their
spatial distribution are the average levels over the period 1988-94.
Under WCPOBTM v2 monthly catch and fishing effort data for each fleet were
obtained at 5° square resolution for the period 1997–2000 with base case aggregate catch
and effort levels set at average observed levels over the same period.
In WCPOBTM v2 prices and costs are specified ex-vessel, that is, at the point at
which the fish is unloaded from the vessel, while in WCPOBTM v1 prices and costs were
estimated on a delivered basis, that is, at the point the fish is delivered to its respective
market. To allow for a direct comparison of the results the estimates of revenues and cost
obtained from WCPOBTM v1 were adjusted so that they also reflect ex-vessel values.
As can be seen in Table 10 the estimated level of rent in each model under their
base case scenario are similar despite the fact that CPUE is 20 per cent higher under
WCPOBTM v2. This is driven by the fact that the costs per unit effort parameters in
WCPOBTM v2 are on average 20 per cent higher than in WCPOBTM v1.
Gillett et al. (2000) and Lewis (2004) provide estimates of purse seine access fees
of US$48 million in 1996 and US$58 million in 2003. If we assume that access fees from
the purse seine fishery average US$54 million over the period 1997-2001 it can be seen
that access fees captured over 70 per cent of the rent created in the fishery during that
period. It is important to note that the ―FFA region‖ as defined in the model also covers
high seas areas and thus the estimates overstate the rent that would be generated in the
national waters of FFA member countries. It is also worth noting that these figures are
based on averages over the period 1997-2001, a period which saw large fluctuation in
A-43
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
prices, for example the highest Bangkok price for skipjack (4-7.5lbs, c.i.f.) 4 over the
period was around US$1250/Mt in August 1997 and the lowest price was US$360/Mt in
November 2000. Consequently over the period 1997-2001 rents earned in the fishery are
likely to have fluctuated widely with periods when access fees were substantially greater
than the rents and periods when they were substantially lower.
Table 10: Base case catch, effort, CPUE, revenue, economic costs and rents at
equilibrium in the“FFA region” under WCPOBTM v1 and WCPOBTM v2
Catch
Skipjack
Yellowfin
Bigeye
Effort
CPUE
Skipjack
Yellowfin
Bigeye
Revenue (ex-vessel)
Economic Costs
Rent
Units
‘000 Mt
‘000 Mt
‘000 Mt
‘000 Mt
Days
Mt/day
Mt/day
Mt/day
Mt/day
$US
million
$US
million
$US
million
WCPOBTM v1
715
537
176
1.9
34,165
20.9
15.7
5.2
0.06
WCPOBTM v2
797
647
712
569
638
78
75
590
187
20
31,786
25.1
18.6
5.9
0.64
The effect of changes to purse seine effort levels on CPUE and economic rents in the
purse seine fishery
To examine the effect of changes to purse seine effort levels on CPUE and
economic rents in the purse seine fishery WCPOBTM v2 was run with effort set within
the FFA region at levels ranging from 10 to 130 per cent of base levels following the
FFA (1999a) analysis using WCPOBTM v1.
The effect of changes to purse seine effort levels on CPUE in the purse seine fishery
In the WCPOBTM v1 runs there was a significant impact of changes in purse
seine effort levels on CPUE. For example, a 10 per cent cut in effort within the ―FFA
region‖ resulted in an increase in skipjack and yellowfin CPUE at equilibrium5 within the
4
c.i.f. price is the price at destination including cost, insurance and freight
All results from both versions of the WCPOBTM relate to the fishery at equilibrium, that is, where catch
remains constant over time. Equilibrium results are generated by running the model under a given effort
level for a period of 15 years. The actual time that it will take for a particular stock to reach equilibrium
varies between species due to their differing biological characteristics. In WCPOBTM v2 the skipjack catch
approaches equilibrium (that is, catch is within 1 per cent of its final equilibrium level) 2 years after the
commencement of a given level of fishing effort. In contrast, yellowfin and bigeye catches respectively
approach equilibrium 6 and 9 years after the commencement of a given level of fishing effort
5
A-44
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
―FFA region‖ of around 5 and 7 per cent respectively. Similarly a 30 per cent reduction
of effort within the ―FFA region‖ resulted in an increase in skipjack and yellowfin CPUE
at equilibrium of 17 and 24 per cent respectively. By comparison, under WCPOBTM v2
a 10 per cent effort reduction from base levels results in a 2 per cent increase in CPUE at
equilibrium for both species and a 30 per cent reduction in effort results in a 7 per cent
increase in CPUE at equilibrium for both species. These are significantly different results.
(see Figure 14).
A question arising from these results is whether the far smaller increases in
skipjack and yellowfin CPUE at equilibrium as effort is reduced which were obtained
from WCPOBTM v2 arise as a result of the change to the value of the stock exponent
(from its previously assumed value of 1) or as a result of the changes to the biological
structure of the model. To examine this question WCPOBTM v2 was recalibrated and
rerun under the assumption that in effect β-1 in the harvest equation is equal to 0. From
the results of this analysis, as illustrated in Figure 14, it appears that the change to the
biological structure of the model plays a more significant role than the change to the
value of the stock exponent.
As previously noted the results of the two models are very different and paint a
different picture of the fishery. WCPOBTM v1 estimated that if effort is cut back catch
levels will decline by substantially less than the effort reduction leading to substantial
increases in CPUE. For example, an effort reduction of 30 per cent results in a decline in
the skipjack catch of 18 per cent and in the yellowfin catch of only 13 per cent. In
contrast the WCPOBTM v2 results show that if effort is cut back catch levels will decline
by only a little less than the effort reduction, leading to only a moderate increase in
CPUE. For example, an effort cut of 30 per cent results in a decline in the catch of both
species of 25 per cent.
For bigeye in WCPOBTM v1 purse seine catch levels were extremely small and
changes in effort levels had a similar effect on bigeye catch rates as under WCPOBTM
v2. Under WCPOBTM v2 the CPUE/effort curve is steeper than for both skipjack and
yellowfin, with a 10 per cent cut in effort resulting in an increase in CPUE of around 3
per cent. For effort reductions of 30 per cent from base levels WCPOBTM v2‘s results
indicate an increase in bigeye CPUE of 13 per cent.
A-45
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Figure 14: Skipjack and yellowfin CPUE in “FFA region”against effort level for
WCPOBTM v1 and v2
Note: a. Base effort is defined as the average annual number of days spent fishing and
searching over the period 1997 to 2000.
The effect of changes to purse seine effort levels on economic rents
Using WCPOBTM v1, FFA (1999a) estimated the effect of changes in effort
levels on potential economic rents at equilibrium in the purse seine fishery within the
―FFA region‖. As previously outlined, at equilibrium under the base case scenario purse
seine fishery revenue was estimated to be US$647 million per annum while the economic
costs of fishing were estimated to be US$569 million and fishery rents to be US$78
million. Under an effort reduction of 10 per cent, assuming constant prices, it was
estimated that costs would decline by US$57 million (10 per cent) in direct proportion to
the reduction in effort while revenues would decline by only US$32 million (5 per cent)
as a result of the CPUE increases outlined above. Thus it was estimated that at
equilibrium rents in the fishery would increase by US$24 million (31 per cent). Further
the model estimated that equilibrium rents would be maximized when effort was set at
around 16,000 effort days and rents would be in the order of US$157 million. A further
analysis was carried out in which prices were assumed to vary with supply levels from
the WCPO, such that prices received for purse seine tuna product rose (declined) by
0.645 percent for each 1 percent decline (rise) in the supply of canning tuna from the
WCPO. Under this assumption and an effort reduction of 10 per cent it was estimated at
equilibrium that revenues would decline by only US$14 million (2 per cent) as a result of
the CPUE and price increases. Thus, it was estimated that rents in the fishery would
increase by US$43 million (55 per cent). Further the model estimated that rents at
equilibrium would be maximized when effort was at around 14,000 effort days and rents
would be in the order of US$250 million (Figure 15).
A-46
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Using WCPOBTM v2 to estimate the effect of changes in effort levels on
potential economic rents in the purse seine fishery within the ―FFA region‖ once again
provides very different results. As previously outlined under the base case scenario purse
seine fishery revenue in the ―FFA region‖ was estimated at US$712 million while the
economic costs of fishing were estimated to be US$638 million and fishery rents US$75
million, a similar result to the estimate obtain under WCPOBTM v1. Under an effort
reduction of 10 per cent assuming constant prices it was estimated that costs would
decline by US$64 million (10 per cent) in direct proportion to the reduction in effort
while revenues would decline by US$57 million (8 per cent). Thus it was estimated that
rents in the fishery would increase by US$6 million (8 per cent). Further, the model
estimated that rents would be maximized when effort is around 23,000 effort days. When
prices were assumed to vary with supply levels from the WCPO, such that prices
received for purse seine tuna product rose (declined) by 0.526 percent for each 1 percent
decline (rise) in the supply of canning tuna from the WCPO as estimated by Reid et al.
(2003), under an effort reduction of 10 per cent it was estimated that revenues would
decline by US$34 million (5 per cent) with the price increase being the primary influence
in offsetting catch declines. Thus it was estimated that rents in the fishery would increase
by US$30 million (40 per cent). Further the model estimated that rents would be
maximized when effort was at around 17,000 effort days and rents would be in the order
of US$160 million (Figure 16).
First comparing the models under the assumption that prices are constant
regardless of supplies from the WCPO it can be seen that the two versions of the model
have different implications from a policy perspective. Under WCPOBTM v1 the results
indicate that if FFA members acted to reduce effort levels in the purse seine fishery
CPUE would increase substantially resulting in large increases in economic rents earned
in the purse seine fishery in the ―FFA region‖ of the order of US$80 million. This in turn
would provide FFA members with the potential to increase their access fees significantly.
Under WCPOBTM v2, however, while the model predicts that there would be an
increase in economic rents if effort were cut back resulting in CPUE increases, the extent
of the CPUE increase is far smaller and consequently the benefit from the effort reduction
is muted. However, if the effect of reduced supplies on prices from the effort reduction is
in the order of magnitude estimated then there may be significant gains in terms of
increasing rents in the fishery by reducing effort levels.
It is important to acknowledge in comparing the results of the two versions of
WCPOBTM that, as noted by Bertignac et al. (2000), results generated by models such as
the WCPOBTM are best used to indicate directions for change rather than specifically
what those changes should be in absolute terms. In this regard the outcomes of the two
models provide similar outcomes: that is, reductions in purse seine effort are likely to
lead to an increase in the level of rent in the purse seine fishery. However, the analysis
presented in this paper indicates that such increases in rent, if they are to occur, are
unlikely to be of the magnitude estimated under WCPOBTM v1 and are likely to be
driven primarily by price increases that arise as a result of the reduction in supplies rather
than by an increase in CPUE.
A-47
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Figure 15: Revenues, economic costs and resource rent in “FFA region” under
constant prices
Figure 16: Revenues, economic costs and resource rent in “FFA region” under
variable prices
A-48
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
The effect of an increase in purse seine catchability of bigeye and yellowfin on longline
catches and fishery revenue.
Purse seine vessels land as part of their catch yellowfin tuna and to a lesser degree
bigeye tuna. These species are also important components of the catch taken by both the
fresh and frozen longline fleets. The capture of juvenile yellowfin and bigeye tunas by
the purse seine fleet is likely to impact upon catch rates of these species by the longline
fleets. Tuna caught by the longline fleets are adults, and are therefore usually
significantly larger and heavier. They also attract a higher unit price, with prices per
kilogram being 5-10 times that received for the purse seine product. Hence an increase in
the catch of these species by the purse seine fleet may adversely affect total revenues
raised from the fishery and, in turn, access fee revenue collected by FFA member
countries and the profitability of tuna longlining by the domestic fleets of FFA members.
In FFA (1999b) an analysis of the effect of an increase in purse seine catchability
of bigeye and yellowfin on longline catches and fishery revenue was undertaken using
WCPOTBM v1. The purpose of the analysis was to examine the interaction between the
fisheries, particularly given concerns at the time of increases in bigeye and yellowfin
catches by the purse seine fleet operating in the WCPO, resulting from increases in the
depth of nets used in fishing operations and the increasing number of sets made on FADs.
The analysis was conducted by running the model under a range of scenarios in relation
to the catchability of the respective species. Catchability relates to the probability that a
given fish will be caught when a unit of effort is applied to the fish stock. The scenarios
examined included a 50 and 100 percent increase in the catchability of yellowfin and
bigeye by each of the six purse seine fleet groupings incorporated into the model (that is,
the US, Japanese, Korean, Taiwanese, Pacific Island and other purse seine fleets). Under
each scenario the effort levels of all fleets in the fishery were kept constant. As such,
costs remain constant under each scenario and changes to the revenue earned by each
fleet result in an equal change to the ‗resource rent‘ earned by the respective fleets.
In Figures 17 and 18 the outcomes of the FFA (1999b) analysis conducted using
WCPOBTM v1 and the rerunning of the analysis using WCPOTBM v2 are shown for
yellowfin and bigeye respectively. As can be seen, for both species, catch and revenue
increase at a significantly greater rate as catchability increases under WCPOBTM v2.
However, the general conclusions of the analyses are the same: an increase in the
catchability of yellowfin by purse seiners leads to an increase in the gross value of the
fishery while an increase in the catchability of bigeye by purse seiners leads to a decline
in the gross value of the fishery. In other words the analysis indicates that at current effort
levels the value of additional yellowfin catches in the purse seine fishery is greater than
the resulting reduction in the value of yellowfin catches in the pole and line and longline
fisheries, whereas, the value of additional bigeye catches in the purse seine fishery is less
than the resulting reduction in the value of bigeye catches in the longline fisheries.
A-49
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Figure 17: WCPOBTM v1 and WCPOBTM v2 yellowfin catch (top) and change in
revenue (bottom) by fishery under 100, 150 and 200 per cent of base catchability
Figure 18: WCPOBTM v1 and WCPOBTM v2 bigeye catch (top) and change in
revenue (bottom) by fishery under 100, 150 and 200 per cent of base catchability
A-50
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
8: Management Policy Analyses using WCPOBTM v2
Effect of effort reduction across all fisheries on catch and economic rents
At the SC1 meeting held in August 2005 Hampton et al. (2005) presented a paper
Estimates of sustainable catch and effort levels for target species and the impacts on
stocks of potential management measures in response to a request from the Western and
Central Pacific Fishery Commission (WCPFC) to its Science Committee (WCPFC-SC)
relating to concerns about the status of the bigeye and yellowfin stocks in the WCPO. In
this paper numerous analyses were undertaken using MULTIFAN-CL with regard to the
effect of various management options on the biomass and total catch level of yellowfin
and bigeye and whether fishing mortality (F) would be above FMSY and stock biomass (B)
would be above BMSY. WCPOBTM v2 was used to analyse some economic implications
of one of these management options, that is, an across the board cut in fishing effort with
the cut in effort set at 30 per cent. This analysis is conducted under the assumption that
prices remain constant across all levels of supply from the WCPO for all species and
market destinations.
In Figures 19 and 20 the estimated effect of an across the board 30 per cent
reduction in effort on catch and revenues by fishery and species is provided. In Figure 21
the estimated effect of an across the board 30 per cent reduction in effort on rents by
fishery is provided.
As can be seen from these Figures WCPOBTM v2 predicts that catch, and hence
the value of the catch, will decline for all species for all fleets. The largest decline in both
volume and value terms will be for the skipjack fishery with volumes predicted to decline
from average 1997-2000 levels by around 210,400Mt (25 per cent) and the value of the
catch to decline by around US$200 million. The majority of this decline will occur within
the purse seine fishery within the ―FFA region‖ with catches predicted to fall by around
145,600Mt and the value of the catch to decline by US$117million. The next largest fall
in terms of volumes is yellowfin with catches predicted to decline from average 19972000 levels by 68,100Mt (26 per cent) while bigeye catches are predicted to decline from
average 1997-2000 levels by 23,000Mt (20 per cent). The declines in the value of the
yellowfin and bigeye catch are predicted to be of similar magnitude at US$119 million
and US$134 million respectively. As was the case for skipjack the largest proportion of
the decline in the value of the yellowfin catch will be borne by purse seine vessels
operating within the ―FFA region‖ which will incur about 50 per cent of the total decline.
For bigeye the decline in the value of the catch will be borne predominantly by the frozen
longline fishery outside of the FFA region. The albacore fishery sees the smallest
absolute and relative declines in catch and catch values with catch declining from average
1997-2000 levels by 7,600Mt or 18 per cent and catch values by US$20 million.
With regard to fishery rent, as can be seen from Figure 21, an across the board
reduction in effort levels leads to an increase in rents in all fisheries as CPUE rises.
However, the gains are not consistent across fisheries as the CPUE increases in response
to reductions in effort vary across fisheries. The model predicts that the biggest increases
A-51
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
in rents will be earned in the frozen longline fishery with an increase of some US$71
million, of which US$45 million will be earned outside of the ―FFA region‖. This
increase in rents represents around 11 per cent of the estimated ex-vessel value of the
fishery after the effort reduction. The fresh longline fishery is predicted to see a US$14
million increase in rents, which also represents around 11 per cent of the estimated exvessel value of the fishery after the effort reduction. In comparison the purse seine fishery
is predicted to see a US$22 million increase in rents which represents an increase of only
around 3 per cent of the estimated ex-vessel value of the fishery after the effort reduction.
Within the FFA region the predicted increase in rents in the purse seine fishery is some
US$13 million or 2 per cent of the estimated ex-vessel value of the fishery after the effort
reduction.
Discussion
The results of the analysis indicate that if an across the board effort reduction
were implemented in the WCPO the total level of rent generated the WCPO tuna fishery
as a whole is likely to increase but that the net benefits gained are likely to be
disproportionately shared by particular fisheries and jurisdictions. The purse seine fishery
within the waters of FFA members is likely to see the least proportionate gains, while the
high seas frozen longline fishery is likely to see the largest net benefits from such an
action. Actual outcomes are likely to be more detrimental to FFA member countries with
a significant purse seine fishery in their waters than the analysis indicates as the model
does not take into consideration the benefits gained from processing activities or
employment associated with the purse seine fishery, but not associated with the high seas
longline fishery. Campbell (2006) outlines a framework within which the value of tuna
processing activities to the host nations can be estimated. Given high levels of
underutilisation of (non-tuna) resources, particularly labour, in Pacific Island countries
the resources utilised in these activities may have low opportunity costs associated with
them. For example, Campbell (2008) estimates the opportunity cost of tuna cannery
workers in Papua New Guinea in the range 40-60% of the market wage. Further, the
results of the modeling in terms of total bigeye catch reductions associated with the 30
per cent across the board effort reduction are substantially greater than the outcomes
indicated by the Hampton et al. (2005) analysis. If it is the case that WCPOBTM v2
overestimates the relative reduction in catch of bigeye it is likely that the beneficiaries of
this will be the longline fisheries and that the estimated revenue reduction in this fishery
will be overstated and, hence, the rent increases understated.
These results in turn lead to the question of whether it is reasonable to expect one
party or one group of parties to agree to measures that may have significant adverse
economic consequences while other parties gain significant economic benefits without
any form of compensation for the loss borne for the benefit of the other.
The report of the Norway-FAO Expert Consultation on the Management of
Shared Fish Stocks (FAO 2002) noted that the Consultation emphasized among other
things ―that the sharing of the benefits from the fisheries should not be restricted to
allocations of TACs, or the equivalent, to national fleets, and that consideration should
A-52
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
also be given to the use of what the Consultation referred to as ―negotiation facilitators‖,
or ―side payments‖, such as quota trades, or mutual access arrangements. These would
help "to broaden the scope for bargaining over allocations, assist in achieving
compromises when there are differences in the management goals of cooperating
States/entities, and enhance the flexibility and resilience of the cooperative arrangements
over time.‖
The adoption of management measures by the WCPFC is likely to have
substantially different economic outcomes for different fleets and Commission members.
To overcome the difficulties inherent in obtaining agreement on implementing
management measures members of the WCPFC will need to give serious consideration to
the possibility of the use of ―negotiation facilitators‖ or ―side-payments‖ in order to
ensure that the costs and benefits of any such management measures are borne equitably
between members.
Figure 19: Change in catch by fishery by species under a 30 per cent effort reduction
Figure 20: Change in revenue by fishery by species under a 30 per cent effort reduction
A-53
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Figure 21: Change in fishery rent under a 30 per cent effort reduction
9: Existence of a Grand Rent Maximizing Coalition
The main purpose of the WCPOBTM v1 and v2 models was to determine the
level and mix of fishing effort which would maximize the rent from the WCPO tuna
fisheries. Two papers by Kennedy and Hanneson (2008, 2009) examine the question of
whether the behaviour of the tuna fleets is likely to result in rent maximization. While the
WCPOBTM models are essentially prescriptive, the Kennedy and Hannesson papers are
aimed at predicting the outcome which will actually occur. Since obtaining solutions for a
game theoretic model is more complex than the maximization problem considered by the
WCPOBTM models, a simpler model of the WCPO tuna fisheries was constructed. When
possible, data from the WCPOBTM model were used in this simpler and highly
aggregated model, but some of the model changes lead to requirements for different
parameter estimates. The way in which some parameters were tuned to obtain good fits
between modeled and actual catches is described below.
The model considers three stocks that are likely to be, to a greater or lesser
degree, mixed in the fishing areas and hence jointly caught by the fishing fleets: bigeye,
yellowfin and skipjack. All three are found mainly in the tropical areas between 10
degrees north and south of the equator. Albacore tuna, also fished in the WCPO, is
mainly found further away from the equator and therefore less likely to be included in the
joint catches of the other three species and is omitted from the model. A three-species
form of the bioeconomic model is also adopted by Kompas and Che (2006) to calculate
optimal effort for the exploitation of these three stocks.
Two types of fishing fleet are considered, purse seining and longlining. These are
the currently dominant types of gear. Pole and line effort, which has similar selectivity to,
and has largely been replaced by, purse seining is included with the effort of the purse
seine fleets. The model contains 14 fishing fleets: six purse seine fleets; five longline
A-54
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
fleets; and three contrived fleets to account for local fleets such as domestic Indonesian
and Philippine fleets. These contrived fleets are aggregated and included as a residual
fleet with a constant fishing mortality. Each of the contrived fleets is assumed to target a
single species (bigeye, yellowfin or skipjack) to account for catches over and above those
modeled for the 11 other fleets.
The model employed is a yield-per-recruit model. Each age interval is one quarter
year. Growth, natural mortality, availability, and gear selectivity parameters were taken
from the WCPOBTM model (Reid et al., 2006).
For modeling purposes, a steady state age-structured stock system is simulated as
follows. Stock in each age category is reduced over each quarterly fishing season by
natural mortality, which is exogenously determined, and fishing mortality, which is
determined by the harvesting efforts of the 14 fleets. Stock in the first age category is
replenished in each quarter at a constant rate of recruitment. This is a convenient
abstraction from biological models that treat recruitment as a function of adult stock
biomass. As numbers decline in older age categories, the effect on biomass is to some
degree offset by the increasing weight of individual fish.
For each stock species s, the population xi , s in each quarterly age category i from
1 to I s is:
x1, s  xr , s
xi , s  xi 1, s e
 fi ,s  mi ,s
i  2,..., I s  1; s  1, 2,3
xI , s  ( xI 1, s  xI , s )e
 fi ,s  mi ,s
where xr , s is recruitment numbers into the first age category, mi , s is the quarterly
14
instantaneous rate of natural mortality, and fi , s   qs ,k vi , s ,k Ek is fishing mortality with
k 1
qs ,k and vi ,s ,k the availability and selectivity coefficients respectively for fleet k, and Ek
is quarterly fishing effort for fleet k.
Catch for species s accumulates from each age category over the season as a
function of the standing biomass, which in turn depends on natural and fishing mortality,
and individual growth, as follows:
Is
cs   fi , s xi , s wi ,s  e
i 1
Is
1 (  f m )t
i ,s
i ,s
0
  fi , s xi , s wi , s (1  e
 fi ,s  mi ,s
i 1
dt
) /( fi ,s  mi ,s )
s  1, 2,3
where wi , s is the average unit catch weight of fish in the i-th age category.
A-55
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
The model is not dynamic in that the decision variables Ek remain the same for all
quarterly time periods. However, this enables the impact of changes in Ek on steady state
stocks, catches and rents to be determined.
The effort vector Ek , to be used as a reference solution, is meant to reflect the
recent status of the fleets and is estimated by solving the following problem:
3
min
14
  c
E1 ,..., EK s 1 k 1
s ,k
( E1 ,..., EK )  cs ,k 
2

where c s ,k is the share of the total catch of species s taken by fleet k, as produced by the
model, and c s ,k is the average annual catch share 2001-2005. In this model there are 14
fishing fleets: six purse seine fleets; five longline fleets; and three contrived fleets. Each
of the contrived fleets targets a single species (bigeye, yellowfin or skipjack) to account
for catches over and above those modelled for the 11 other fleets. The latter three fleets
are termed ‗Other fleets‘ or ‗Others‘ in result tables.
Taking the age-specific weight wi , s , natural mortality mi , s , availability qs ,k and
selectivity si , s ,k used in the WCPOBTM model, a reference solution is defined by finding
the fleet effort levels Ek that best reproduce the average catch shares taken over the
reference period 2001-2005, according to the above minimization problem. In this
exercise it is assumed that the recruitment to all three stocks is the same. Thereafter the
initial recruitment to each stock xr , s was set so that the catch produced by the model
equalled the average catch 2001- 2005. For further details, see Hannesson and Kennedy
(2009).
This highly aggregated model is not directly comparable to the much more
detailed WCPOBTM model so cost parameters from that model cannot be used. As a
base reference case the cost per unit of effort is set so as to produce rents equal to 10
percent of revenue for all fleets in the reference solution, the cost per unit of effort being
constant. The WCPOBTM model produces rents from nil to over 30 percent of revenues,
varying across fleets. These levels will be compared with the rents of the fleets obtained
for a non-cooperative Nash equilibrium solution for seven country groupings of the
fleets, to gauge whether or not these cost assumptions are realistic.
As to prices, there are two alternative assumptions. First, fish prices are assumed
to be fixed and insensitive to catch volumes and identical to the ones used in the
reference solution discussed below. These prices are based on average prices 2001-2004
(Reid, 2006). For the longline fleets the price of fresh tuna is used. Fresh longline tuna is
the most highly priced tuna product and also the most profitable one. Using this price for
all longline caught tuna will exaggerate the advantage of the longline fleets, partly
A-56
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
because not all longline caught tuna can be sold fresh, and partly because increased
catches of longline tuna are likely to lead to lower prices. Second, the effect on the results
of the price changes that would result from changed supplies from the West Central
Pacific, using price flexibilities reported in Reid et al. (2002), will be investigated.
Rent Maximization
The aggregate rent is the maximum, undiscounted, sustainable rent, as the model
is a static yield-per-recruit model that compares different long term equilibrium solutions,
but including the dynamics between age groups. With fixed prices, the aggregate rent in
the fishery more than doubles, compared with the reference solution. The purse seine
fleets are virtually eliminated while the fishing mortality for the longline fleets almost
doubles for yellowfin and remains virtually unchanged for bigeye. Because the virtual
disappearance of the purse seine fleets leaves more fish to be taken by the longline fleets
the longline catches of yellowfin more than double, and catches of bigeye increase by
almost 40 percent. The rent grows almost fivefold for the longline fleets. As a percent of
revenue, rent is between 20 and 30 percent of revenue both for the purse seine and the
longline fleets.
Taking price sensitivity into account gives radically different results, with the
effort of the purse seine fleet reduced by much less than in the previous case. The catches
of yellowfin and skipjack by the purse seine fleets are roughly halved while the catches
of the longline fleet increase only moderately. These results are similar to those obtained
by Bertignac et al. (2000) and Kompas and Che (2006), who took price sensitivity to
catch volumes into account.
As a possibly more realistic alternative to rent maximization behaviour, the
behaviour of the likely players and their coalitions needs to be considered. Since the
decisions on harvesting effort are made by fleets, players are likely to be fleet-based. The
following possibilities for coalitions of fleet players could be considered: (1) single
member fleet coalitions; (2) a coalition of the fleet players by fleet type - purse seiner or
long liner; (3) coalitions of purse seine fleets by country, and coalitions of long line fleets
by country; and (4) coalitions of all fleets by country. The type (1) coalition setup results
in the rent maximization discussed in this section if all single member fleet coalitions act
cooperatively.
Whilst opportunities exist for deals to be done between the same fleet types of
different countries, it is perhaps more plausible that coalitions of fleets will be country
based in view of the advantages of possible government support. Consequently the type
(4) coalition setup is adopted. Thus seven country players are defined as coalitions of the
fleet players of the country (or a group of countries, PICs, ―Others‖). Four country
players have both a purse seine fleet and a longline fleet (Japan, Korea, Taiwan, and
―Others‖) while the remaining three country players have only a purse seine fleet (US,
China and PICs). We now consider two possible types of strategic coalitions of country
players.
A-57
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Nash equilibrium 1: One country player against all other country players
Solutions like the rent-maximizing solution described above are none too likely to
be attained. They imply that the most efficient fleets should do the fishing and the others
disappear, with the latter being compensated by a share in the greater profit. Such grand
coalitions are sometimes not viable even in principle, as there may be incentives for some
members of the coalition to break out and form their own sub-coalition, either with
themselves as a single member or with more, but not all, members. See Kennedy (2003)
for consideration of solution concepts, with and without side-payments, and allocations to
indicate the security of coalitions.
The rents accruing to the h-th player breaking out and those who remain in the
coalition are given by the following Nash equilibrium, consistent with the solution to the
following problem:

 arg max   E

E
*
Eh*  arg max  h Eh E g
Eh
E g*
g
*
h
Eg
where  h is the rent generated by defecting country h setting effort level at Eh , E g is the
set of effort levels Eg g  h , and    is the resulting rent generated for the coalition of
remaining players. For more detail see Hannesson and Kennedy (2009).
.
Suppose each country would have to be offered an outcome at least as good as it
could obtain if it decided to break out of the coalition and maximize its own rent. Table
11 shows the rent that would result if one country acts independently and the rest act as a
coalition, as well as the maximum rent (the grand coalition), which is $569.7 million in
the fixed price case and $642.7 with price flexibilities as discussed above. What is
noteworthy is that the rent obtained by a single member who breaks out of the grand
coalition, summed across all possible single members, is more than twice that of the
maximum rent. It would thus not be possible to offer all members of the grand coalition a
share in the total rent which exceeds what each could obtain if he decides to leave the
coalition and the rest remain in the coalition. This makes it doubtful whether the grand
coalition would be stable. While the remaining coalition could buy off one member who
defects (third column in Table 11), it would not be possible to deter all members
simultaneously from leaving the coalition by offering each what he would get if he went
alone.
A-58
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Table 11: Rent obtained by one Defecting Country Player, Rent for Coalition of
Remaining Country Players, and Coalition Rent for Dissuading Defection. Million
US$. Numbers in parentheses refer to volume-dependent prices.
NE Single
country
(Defector)
rent
Japan
Korea
Taiwan
PICs
China
US
Others
Total
NE Total
rent for
coalition of
remaining
countries
Maximum payment
coalition could make
to dissuade
defection, given the
maximum
cooperative joint rent
is 569.7 (642.7)
NE rent for
each
country
competing
against all
other
countries
197.3
238.3
331.4
20.8
(252.8)
(280.0)
(362.7)
(44.3)
230.0
221.1
348.6
26.7
(265.3)
(283.8)
(358.9)
(43.5)
259.4
222.5
347.2
25.7
(276.8)
(273.8)
(368.9)
(52.5)
128.7
294.1
275.6
24.8
(159.4)
(408.9)
(233.8)
(34.3)
180.2
313.5
256.3
12.9
(164.5)
(425.2)
(217.5)
(22.1)
126.2
155.9
413.9
22.3
(162.2)
(323.7)
(319.0)
(33.4)
223.5
272.0
297.8
21.3
(193.5)
(315.9)
(326.8)
(32.9)
1345.2
154.5
(1474.5)
(263.0)
A-59
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
In some cases the expansion of effort implied by one country going alone is quite
large, especially if prices are not dependent on volume (see Table 12): both China and the
US would expand their effort tenfold, but for others more moderate values are obtained;
Japan would double its effort in longlining and increase it by 50 percent in purse seining.
To the extent the effort expansions reported in Table 12 are unrealistic the gains from
breaking out of the coalition would be limited, which in turn would increase the
likelihood that the grand coalition would be stable. It turns out, however, that this is not
an important constraint. Even if each country were to fish with the same effort as in the
reference solution and the rest were to maximize their joint rents, the sum of single
country rents would exceed the maximum rent; it would be 578.5 compared with the
maximum rent of 569.7 in the fixed price case, and 838.8 against 642.7 with volumedependent prices. The incentive to free ride is thus much stronger when prices are
volume-dependent: a coalition of all but one would take into account the beneficial effect
of restraining catches to get higher prices, which would much benefit the free rider.
Another aspect of this is that a single country could free ride on the cooperative efforts of
the rest, if the latter would let them do so.
Table 12. Effort of one Country Player who breaks out of the Grand Coalition
divided by Effort in the Reference Solution (fixed prices)
Purse seine
US
10.2
Japan Korea Taiwan
1.5
4.7
1.8
Longline
PICs
Others
3.9
0
Japan
2.0
Korea Taiwan China Others
2.7
3.9
10.5
4.4
There are other conditions under which the grand coalition would be stable. This
occurs if all countries realize that if one of them breaks out, all the others would do
likewise. What then is important to look at is the temporary gain one country might
obtain from breaking out of the coalition less the present value of the discounted loss
resulting from everyone else going for the Nash equilibrium solution. The outcome of
this depends on the discount rate and would require an intertemporal model to analyse
fully (see Hannesson, 1997).
Nash equilibrium 2: Each country player against all other country players
Given that a grand coalition is unlikely, it makes sense to look at a solution where
everyone is competing against everyone else. This type of outcome can be expected to
prevail in a virtually unregulated situation.
A-60
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
For the Nash equilibrium, the following set of solutions to all one-member
coalition problems holds:
Eh*  arg max  h {Eh | E g* }
Eh
where E  the set of Eg*  g  h.
h
*
g
The algorithm used for finding Nash Equilibrium 2 is reported in Hannesson and
Kennedy (2009).
The last column of Table 11 shows the rents prevailing in this Nash equilibrium,
for the case of volume-independent prices. These are only 27 and 40 percent,
respectively, of the maximum rent with fixed prices and volume-dependent prices, so if
the players reckon that this situation would prevail in the absence of cooperation, and if
side payments are possible, the grand coalition could indeed be stable. A country that
breaks out of the coalition would make only a temporary gain.
Table 13 compares this Nash equilibrium with the reference solution for the fixed
price case. Effort expands for six fleets and contracts for five, resulting in an increase in
fishing mortality by 7-30 percent, and total rent falls about 35 percent. This result can be
interpreted in two ways. One is that the present situation is considerably better than the
solution that would emerge in unrestricted competition by all against all. In that case
there is reason to expect that the situation will get worse, unless cooperation among the
fishing nations with respect to limiting fishing effort is improved or maintained. Note that
since there is only a limited number of competitors, all rent would not disappear in the
Nash equilibrium.
Alternatively, the assumed cost per unit of effort may be too low (in the reference
solution rent was assumed to be 10 percent of revenues for all fleets). Since there appear
to be few restraints on effort by the different fishing nations and little cooperation
between them with respect to limiting it, it would be expected that the present situation
would be close to a Nash equilibrium. Hence, if the cost per unit of effort has been set at
an unrealistically low level, effort would expand as we go from the reference solution to
the Nash equilibrium. The higher effort and lower rent in the Nash equilibrium may thus
be due to setting the cost per unit of effort at an unrealistically low level.
A-61
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Table 13: Effort in the Nash Equilibrium, relative to the Reference Solution, and
Percentage Change in Rents from the Reference Solution
Purse seine
Longline
US
Japan Korea Taiwan PICs Others
WCPOBTM*
Effort
Japan Korea Taiwan China Others
+
+
+/-
4.6
0.7
2.3
0.9
1.8
0
0.6
0.7
1.2
156.6 -63.1
26.6
-51.5
2.0
-100
-68.4 -67.1
-36.6
Rent % change
*
Indicates whether the WCPOBTM model rents are greater or less than 10 percent of
revenues.
 + for fresh tuna vessels and - for frozen tuna vessels.
3.0
51.4
The effort in the Nash equilibrium is not uniformly higher than in the reference
solution for all the fleets involved, which on the second interpretation above could mean
that rent and cost per unit of effort vary significantly between them. The first row in
Table 13 shows whether the rents produced by the WCPOBTM model are greater or less
than 10 percent of revenues. This, it will be recalled, was the basis for setting the costs
per unit of effort. If these rents are representative for the fleets, a positive sign indicates
that the rent is in fact higher than has been assumed and the cost per unit of effort lower.
If the cost per unit of effort has been set too high, the effort in the Nash equilibrium will
be lower than it ought to be and in all probability lower than in the reference solution.
The result for Taiwanese purse seiners supports this; the effort is lower than in the
reference solution. Hence it is likely that the rent of this fleet is higher than 10 percent of
revenues and the cost per unit of effort lower than has been assumed. For purse seiners
from Japan, Korea and the Pacific island countries, as well as Taiwanese and Chinese
longliners, the opposite is true; the WCPOBTM model indicates lower rents than
assumed here. Hence the cost per unit of effort assumed in the game theory model is
probably too low, resulting in greater effort in the Nash equilibrium than in the reference
solution.
The simulated results for Korean longliners are also out of line: the WCPOBTM
model shows lower rent than assumed here, implying a too low cost per unit of effort, so
that effort should have been greater in the Nash equilibrium than in the reference
solution, but this is not the case. The rent of the US purse seine fleet is greater than 10
percent of revenues, but nevertheless the effort is much greater in the Nash equilibrium
than in the reference solution. The rent produced for this fleet by the WCPOBTM model
may therefore not be representative: it is probably lower and the cost of effort higher than
assumed. For Japanese purse seiners the opposite is true. For Japanese longliners there is
no clear case; the rent of fresh fish longliners is more than 30 percent of revenues while
for frozen fish longliners it is virtually zero.
Discussion
As in the case of the WCPOBTM v1 model the results suggest that a considerable
increase in rent can be obtained from changing the tuna fishery from its present
A-62
0
1.5
-21.7
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
configuration. The model suggests that purse seining should be reduced drastically. If
prices are not sensitive to catch volumes the purse seine fleets would almost be
eliminated and the benefits would be realized by the longline fleets, which deliver a more
valuable product. If prices are sensitive to catch volume, reduced catches by the purse
seine fleets would generate some benefits for them in the form of higher prices, while the
benefits for the longline fleets due to more fish being available there would be limited by
the volume sensitivity of prices for sashimi-grade products.
The results also suggest that, provided there is a mechanism to share the aggregate
rent, the fishing should be carried out by countries with the most cost-effective fleets.
This means that some fleets would disappear altogether, with the nations involved getting
a share of the total rent. There are obvious practical and political obstacles to such a
solution: how long would a country without any fishing fleet of its own be considered
entitled to a share in the rents from fishing by others hundreds of miles away from its
economic zone? Apart from that, in this particular setting this kind of solution would
probably not be stable: it is unlikely that all countries can be offered rent shares that
exceed what they could get on their own if one breaks out of the coalition and the others
stay in it. Only if they realize that a breakdown of the coalition would end in everybody
competing against everyone else and that the gains from breaking away would be
temporary could the grand coalition be viable.
The biggest obstacle to achieving the cooperative solution is perhaps the fact that
this would reduce the purse seine effort drastically, although further work along the lines
of the WCPOBTM v2 model would probably modify this conclusion. Some of the
nations engaged in purse seining are not involved in longlining, or do so only to a limited
extent, and would lose heavily from reducing their activity, unless a way could be found
to give them a share in the benefits accruing to the longline fleets. For the Pacific islands
countries this could come in the form of higher access fees for distant water longliners,
but for those distant water fishing nations with purse seiners only (US and China), some
other mechanism would have to be found.
References
Bertignac, M., P. Lehodey and J. Hampton (1998), "A Spatial Population Dynamics Simulation
Model of Tropical Tunas using a Habitat Index based on Environmental Parameters",
Fisheries Oceanography Vol. 7, pp. 326-334.
Bertignac, M., A. Hand, J. Hampton and H.F. Campbell (1998), ―A Bioeconomic Model of
Longline Pole-and-Line and Purse Seine Fisheries in the Western and Central Pacific‖,
Technical Paper No. 9, ACIAR Project No. 9405: A Bioeconomic Study of Tuna Purse
Seining in the Pacific Islands Region October, pp 20.
Bertignac, M., H.F. Campbell, J. Hampton and A.J. Hand (2000), ―Maximizing Resource Rent in
the Western and Central Pacific Ocean Tuna Fisheries‖, Marine Resource Economics, Vol.
15, No. 3, pp. 151-177.
Campbell, H.F. and R.B. Nicholl "Can Purse Seiners Target Yellowfin Tuna?‖ Land Economics,
Vol. 70, No. 3, August 1994, pp. 345-354.
Campbell, H.F. (1994), "Investing in Yellowfin Tuna: the Economics of Conservation", Marine
Policy, Vol. 18, No. 1, January 1994, pp. 19-28.
Campbell, H.F. and R.B. Nicholl (1995), ―Allocating Yellowfin Tuna Between the Multispecies
Purse Seine and Longline Fleets‖, Marine Resource Economics, Vol. 10, 1995, pp.35-58.
A-63
APPENDIX IV– Discussion Paper
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Forum Fisheries Agency (FFA) (1999a), ―The potential to increase total access fee revenues from
the western and central Pacific tuna fishery by altering the structure of the purse seine
fishery‖, Presented to the Third Meeting of the Skipjack Working Group, SKIPY3/Technical
Paper 1, Apia, April.
Forum Fisheries Agency (FFA) (1999b), ―The impact of increases in the ability of purse seiners
to catch yellowfin and bigeye tuna on total fishery catch and revenue‖, Presented to the Third
Meeting of the Skipjack Working Group, SKIPY3/Technical Paper 2, Apia, 30 April.
Hand, A.J. and P.S. Forau (1997a), "Fishing Costs for Bioeconomic Modeling of the Western
Pacific and Solomon Islands Tuna Fisheries", ACIAR Project 9405, Technical Paper No. 2,
pp. 11 + Appendices.
Hand, A.J. and P.S. Forau (1997b), "Tuna Prices for Bioeconomic Modeling of the Western
Pacific and Solomon Islands Tuna Fisheries", ACIAR Project 9405, Technical Paper No. 3,
pp. 13..
Hannesson, R. and J. Kennedy, J. (2009), "Rent Maximization versus Competition in the Western
and Central Pacific Tuna Fishery", Journal of Natural Resources Policy Research Vol. 1 (1),
pp.49-65.
Kennedy, J. (2003). Scope for Efficient Multinational Exploitation of North-East Atlantic
Mackerel. Marine Resource Economics 18(1), 55-80.
Kennedy, J. and R. Hannesson (2008), "The Stability of Rent Maximization in the Western and
Central Pacific Fishery", Proceedings of the 14th Biennial Conference of the International
Institute of Fishery Economics and Trade, Vietnam, pp. 9.
Kompas, T. and T.N. Che (2006). Economic Profit and Optimal Effort in the Western and Central
Pacific Tuna Fisheries. Pacific Economic Bulletin, Vol. 21, No. 3, November 2006, pp. 4662.
Levitus, S. and T. Boyer (1994), World Ocean Atlas 1994, Volume 4: Temperature. NOAA Atlas
NESDIS 4, 150 pp, Washington DC, US Government Printing Office.
Lewis, A. (2004), ―A Review of Current Access Arrangements in Pacific Developing Member
Countries (PDMCs)‖, ADB Project TA 6128-REG: Alternative Negotiating Arrangements to
Increase Fisheries Revenues in the Pacific, November, pp 27.
Reid, C., R. Vakurepe and H. Campbell (2003), ―Tuna Prices and Fishing Costs for Bioeconomic
Modelling of the Western and Central Pacific Tuna Fisheries‖, Technical Paper No. 1,
ACIAR Project No. ASEM/2001/036: Maximising the Economic Benefits to Pacific Island
Nations from Management of Migratory Tuna Stocks, pp 32.
Reid, C., M. Bertignac, and J.Hampton (2003) "Further development of, and analysis using, the
Western and Central Pacific Ocean Bioeconomic Tuna Model (WCPOBTM)", ACIAR
project no. ASEM/2001/036, Maximising the Economic Benefits to Pacific Island Nations
from Management of Migratory Tuna Stocks”, Technical Paper No. 2
Swan, J. (1997), Sustainable Development in the Pacific Islands: Forwarding the Fisheries File –
Law and Policy, SwanSea Oceans Environment Inc., Waverley, Nova Scotia, pp. 13.
Williams, P. and C. Reid (2005), ―Overview of the Western and Central Pacific (WCPO) Tuna
Fishery, Including Economic Conditions - 2004‖, Presented to the 1st Meeting of the
Scientific Committee of the Western and Central Pacific Fisheries Commission, WCPFCSC1 GN WP-1, Seventeenth Standing Committee on Tuna and Billfish, 8-19 August,
Noumea, New Caledonia.
Williams, P. and P.Tarawasi (2008), "Overview of the Western and Central Pacific (WCPO)
Tuna Fishery, Including Economic Conditions - 2007", Presented to the 4th Regular Session
of the Scientific Committee of the Western and Central Pacific Fisheries Commision, WCPFC
- SC1 GN WP-1, 11-22 August, ort Moresby, Papua New Guinea.
A-64
APPENDIX V– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
APPENDIX V
List of Abstract and Biographical Sketch of
Speakers
Session I. Tuna Fleet Dynamics and Capacity Overview (Chair: Peter Miyake)
P1. Keynote Speech: Tuna Fleet Dynamics and Capacity Overview in EPO
(Guillermo A. Compeán*)
The Inter American Tropical Tuna Commission (IATTC), established by international
convention in 1949, is responsible for the conservation and management of fisheries for tunas
and other species taken by tuna-fishing vessels in the eastern Pacific Ocean. Dr. Compeán is
invited to deliver the Keynote Speech to provide the most recent tuna fleet dynamics and
cannery capacity overview in EPO.
Biographical Sketch of Speaker:
Dr. Guillermo A. Compeán
Director (September 2007 - present)
Inter-American Tropical Tuna Commission
Professional Experience:
•
Director of the Mexican Tuna-Dolphin Program (Fideicomiso de Investigación
para apoyar al Programa Nacional de Aprovechamiento del Atún y de Protección
de Delfines y otros en torno a especies acuáticas protegidas, FIDEMAR) March
1996.-December 2000 and January-August 2007.
• Chief Director of the Instituto Nacional de la Pesca (Mexican Fisheries Institute),
January 2001-december 2006.
• Professor at the “Laboratorio de Ecología Pesquera” (Fisheries ecology
laboratory) at the UANL, September 1984-2000.
Distinctions:
• Member of the AIDCP/IATTC, Scientific Advisory Board), 1993-2007.
• Commissioner by México at the Inter.-American Tropical Tuna Commission
(IATTC), 1999-2007.
• Listed by UNEP/ONU as expert to the special arbitral tribunal for the protection
and preservation of the marine environment. October 2000.
• Commissioner by México at the International Commissión for the Conservation
of Atlantic Tunas (ICCAT), 2002-2007.
• Working with tuna fisheries since 1977 in the Bay of Biscay, Gulf of Mexico and
Eastern Pacific Ocean.
A-65
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
P2. World Trends of Tuna Industry - Recent Developments in Tuna Industry: Stocks,
Fishery, Management, Processing, Trade and Markets (FAO Fisheries Technical Paper,
Rome)
(Peter M. Miyake*, Patrice Guillotreau, Chinhwa Jenny Sun, and Gaku Ishimura)
This presentation intends to show historical development of tuna fisheries, to describe
current world tuna fisheries, and to explain the technological and socio-economic
developments in the entired tuna industry. All these have affected fishing operations and
contributed to the increasing fishing capacity in the world, in recent years. The review covers:
(1). Catch trends by species, gear, ocean and flag - generql continuous increase particularly of
purse seiners.
(2). The world tuna stock status, based on the results of RFMOs’ scientific reviewsk- Biomass
mostly close to MSY but F exceeding Fmsy.
(3). Tuna management measures taken by RFMOs are reviewed, including those used to
mitigate bycatch.
(4). Gear and species interactions are specifically discussed in terms of allocations of the
stocks between fisheries – particularly between longline vs purse seine fisheries – which
are closely related to the competitions between canning and sashimi markets
(5). Case study of fishery operating cost and profit are compared among various major tuna
fisheries
(6). Recent changes in tuna trade, processing industries, for sashimi, fresh tuna steak,
katsuobushi and canned tuna. – general shift of industry from developed countries to
coastal states, concentration of capitals and industries, streamlining and adding
complications in tuna flows in the international trade. Together with these changes and
eliminating intermediate buyers in market flow contributed cutting supply cost of
commodities.
(7). The tuna markets, consumption, price and profits are also covered for those tuna products
and influencing elements for market are discussed
(8). In conclusion, because of the recent rapid increase in competition among fisheries,
species, industries and even products (sashimi/fresh tuna vs. canned), the most important
and most urgent issue is how to manage and allocate tuna resources among these
competitors (e.g. using fishing capacity control measures and/or catch allocations). In
order to achieve such an objective it is imperative that socio-economic and ecological
considerations are integrated into decision-making processes alongside capacity and
allocation issues.
Biographical Sketch of Speaker:
Dr. Makoto Peter Miyake
Born in Tokyo, Japan
BS and PhD from Tokyo University, Tokyo, Japan
1957 to 1980 Japanese Fisheries Agency
Worked in many RFMOs (International North Pacific Fisheries Commission, InterAmerican Tropical Tuna Commission, and International Commission for the Conservation
of Atlantic Tunas).
A-66
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Currently
• Visiting Researcher of Research Institute of Far Seas Fisheries
• Scientific Adviser for Japan Tuna Fishermen’s Association
Experts in
• Management of tuna stocks and fisheries,
• Allocation problems,
• Management of tuna farming,
• Management of tuna fishing capacity,
• Combating IUU vessels
• Establishing tuna statistical system,
• Study on tuna trade and markets
3. Recent Development on Rights-based Management of Tuna Fishery: Summary Report of
the IATTC and World Bank Workshop in May 2008
(Dale Squires*)
The findings of the previous IATTC “Workshop on Rights-based Management and
Buybacks in International Tuna Fisheries”, sponsor by the NOAA/NMFS and World Bank, in
La Jolla, CA during May 5-9, 2008, is summarized. The challenge of creating an international
rights-based regime for the purse seine fishery operating in the eastern Pacific Ocean is
addressed and the findings of the workshop are disseminated to all member countries, the
general public, and stakeholders (http://www.iattc.org/PDFFiles2/Rights-based-managementreport.pdf). Wide dissemination will improve public understanding and public involvement in
stewardship of tuna resources.
Biographical Sketch of Speaker:
Dr. Dale Squires presently serves as the Senior Scientist and Economist for the National
Marine Fisheries Service, also carrying out his duties as an Honorary Professor at the
University of Southern Denmark and as an Adjunct Professor of Economics at the University
of California San Diego. Squires served as a visiting scientist with the WorldFish Center, as
well as on the U.S. Delegation to Renegotiate South Pacific Tuna Treaty, a member of the
FAO Technical Consultation on Global Tuna Purse Seine Capacity, and as the Pacific Fisher
Management Council Leader of the Highly Migratory Species Plan Development and
Management Teams. Squires was instrumental in the economics of capacity in the FAO
International Plan of Action on Fishing Capacity.
4. Tuna Cannery and Market Overview in Ecuador
PROPUESTA DE TOPICOS DE INVESTIGACION SOBRE LOS POSIBLES
EFECTOS DE LA MARICULTURA EN EL MERCADO DE ATUNES
TROPICALES
(Iván Prieto)
A-67
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Estudios presentados por la FAO indican que, en general, en todos los océanos del mundo
donde se realizan pesquerías de especies de túnidos, aproximadamente el 8% de las
poblaciones se encuentran agotadas, mientras que el 50% se encuentran plenamente
explotadas a expensas de caer en la sobreexplotación (FAO, 2007).
El panorama descrito es similar para los atunes tropicales, a pesar que a estas especies
se les atribuye condiciones de reproducción y crecimiento que permitirían una mejor
reacción a la explotación comercial.
En el contexto del actual estado de las especies marinas en el mundo y de los factores
económicos, ambientales y sociales entorno a la problemática expuesta, surge la maricultura
como una alternativa para complementar el manejo extractivo de la pesca.
De acuerdo a FAO, la cría de atún en granjas se inició por el año 1990, a partir del cual
países como Australia, Japón, México, y otros países del Mediterráneo como España y
Croacia han incursionado en esta técnica de producción particularmente con el atún rojo o
aleta azul, especie túnida que en la actualidad es sujeto de un gran debate en cuanto a su
estado de sobreexplotación.
Los avances tecnológicos obtenidos en el laboratorio de Achotines, Panamá (atún aleta
amarilla y barrilete negro); en Japón (atún rojo), Australia e Indonesia (atún rojo y aleta
amarilla), entre otros, apuntarían a considerar en un futuro una oferta de productos de
atunes tropicales provenientes de la maricultura, con posibles efectos en los mercados, el
estado del recurso marino, y el ambiente en general.
Por esta razón, es necesario identificar algunas tópicos de investigación sobre los
posibles efectos de la actividad. En particular, para los posibles inversionistas de la región,
es importante investigar sobre la factibilidad económica de inversiones en maricultura de
atunes tropicales, así como el posible impacto de incrementos de la oferta proveniente de la
maricultura en el comercio internacional.
Mediante un ligero análisis comparativo de costo y retorno en actividades similares de
reproducción en cautiverio, engorde y comercialización de otras especies marinas
(maricultura), se plantea la hipótesis que la viabilidad o función económica estaría
determinada entre otros factores por la tasa de supervivencia en laboratorio, tasas de
crecimiento o engorde, tasa de conversión de alimentos y por los precios que se podría
recibir por los productos.
En muchos de estos casos, las proyecciones de los precios se podrían basar
equivocadamente en una análisis estático de los precio de atún crudo comercializado en
fresco, en muchos casos considerando los altos precios de los productos de atún en los
distintos mercados, como Japón por ejemplo. Esta proyección, para ser suficientemente
conservadora a juicio del proponente, debería considerar la dinámica potencial de la
reducción de los precios como consecuencia de incrementos en las cantidades ofertadas por
la maricultura, en los mercados de estos productos. En efecto, la información inicial que
se dispone , es que en las actuales condiciones de la tecnología de producción, los altos
costos de producción, suponen un elevado precio por los productos a obtenerse para que
estos proyectos sean viables.
En este sentido cuando la tecnología de producción disponible en el mundo vuelva la
maricultura atractiva, la oferta adicional podría derivar en menores precios para los
productos de atún fresco.
A-68
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Es necesario investigar adecuadamente estos efectos, para intentar proyectar los
posibles precios a obtener por los productos de la maricultura. La teoría de análisis de
precios nos indica que unos de los factores a considerar para proyección de dinámicas
de precios es la elasticidad precio de la demanda, o más directamente su inverso, la
flexibilidad precio de la demanda. La estimación de este indicador, que mide el cambio
proporcional o porcentual de los precios como resultado de un cambio en la cantidad
ofertada de producto, resultaría entonces fundamental para estimar el precio futuro de
los productos de atún en fresco ante distintos escenarios de cambios en la oferta como
resultado de la producción de maricultura.
La metodología utilizada para estimación de los indicadores antes referidos ha
sufrido importantes avances a lo largo del tiempo. La utilización de regresiones y
análisis de series de tiempo, han mostrado ser métodos eficaces de pronósticos de precios
promedios anuales. Las técnicas antes referidas podrían ser utilizadas, en el supuesto de
que exista data adecuada sobre cantidades ofertadas y precios en un mercado de un país
específico, para intentar proyectar dinámicas posibles de precios ante distintos
escenarios de incrementos de oferta de producto como efecto de la producción de atún de
maricultura. Las dinámicas de precio estimadas podrían a su vez, utilizarse en las
funciones de costo y retorno para mejorar la calidad del análisis de factibilidad y riesgo de
las inversiones en maricultura del atún.
Biographical Sketch of Speaker:
Ivan Arturo Prieto serves as Economics Advisor for Cámara Nacional de Pesquería. He
got his Master of Agricultre, Agricultural Economics (Agricultural marketing specialization)
from Texax A&M University. He has research background in agribusiness and fisheries
economics and working experience on international marketing (import/exports), project
analysis, business development services, and other consulting activities. His areas of research
include market impact of public policy, effects of subsidies on trade and environment.
5. Global Tuna Cannery and Market Overview (Kevin McClain* and Michael McGowan)
Biographical Sketch of Speaker:
Kevin McClain
Bumble Bee Foods, LLC
Session II. Stock Assessment and Fishery Management in EPO (Chair: Mark N. Maunder)
6. Status of Bigeye Tuna in the Eastern Pacific Ocean in 2008 and Outlook for the Future
(Alexandre Aires-da-Silva* and Mark N. Maunder*)
(Stock Assessment Report 10, IATTC, 2010, http://www.iattc.org/PDFFiles2/SAR10c-BETENG.pdf)
This report presents the current stock assessment of bigeye tuna (Thunnus obesus) in the
eastern Pacific Ocean (EPO). This assessment was conducted using Stock Synthesis (Version
3)). The assessment reported here is based on the assumption that there is a single stock of
A-69
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
bigeye in the EPO, and that there is limited exchange of fish between the EPO and the
western and central Pacific Ocean (WCPO).
The stock assessment requires a substantial amount of information. Data on retained
catch, discards, catch per unit of effort (CPUE), and size compositions of the catches from
several different fisheries have been analyzed. Several assumptions regarding processes such
as growth, recruitment, movement, natural mortality, and fishing mortality, have also been
made. Catch, CPUE, and length-frequency data for the surface fisheries have been updated to
include new data for 2008. New or updated longline catch data are available for Chinese
Taipei (2005-2007), China (2007), and Japan (2003-2007).
Analyses were carried out to assess the sensitivity of results to: 1) a stock-recruitment
relationship; 2) use of a Richards growth curve fitted to age-at-length data derived from
otolith data; 3) extending the assumed western limit of the bigeye stock distribution from
150°W to 170°E.
There have been important changes in the amount of fishing mortality caused by the
fisheries that catch bigeye tuna in the EPO. On average, since 1993 the fishing mortality of
bigeye less than about 15 quarters old has increased substantially, and that of fish more than
about 15 quarters old has increased slightly. The increase in the fishing mortality of the
younger fish was caused by the expansion of the fisheries that catch tuna in association with
floating objects.
Over the range of spawning biomasses estimated by the base case assessment, the
abundance of bigeye recruits appears to be unrelated to the spawning potential of adult
females at the time of hatching.
There are several important features in the estimated time series of bigeye recruitment.
First, estimates of recruitment before 1993 are very uncertain, as the floating-object fisheries
were not catching significant amounts of small bigeye. There was a period of above-average
recruitment in 1994-1998, followed by a period of below-average recruitment in 1999-2000.
The recruitments were above average from 2001 to 2006, and were particularly high in 2005
and 2006. The 2007 recruitment was below average, but the recruitment in 2008 appears to
have been particularly high. However, this recent estimate is very uncertain and should be
regarded with caution, due to the fact that recently-recruited bigeye are represented in only a
few length-frequency samples.
The biomass of 3+-quarter-old bigeye increased during 1975-1986, and reached its peak
level of about 630 thousand metric tons (t) in 1986, after which it decreased to a historic low
of 287 thousand t at the beginning of 2009. Spawning biomass has generally followed a trend
similar to that for the biomass of 3+-quarter-olds, but lagged by 1-2 years. There is
uncertainty in the estimated biomasses of both 3+-quarter-old bigeye and spawners.
Nevertheless, it is apparent that fishing has reduced the total biomass of bigeye in the EPO.
The biomasses of both 3+quarter-old fish and spawners are estimated to have been nearly
stable, with no trend for the last six years.
The estimates of biomass are moderately sensitive to the steepness of the stockrecruitment relationship, but the trends are similar to those of the base case. The recruitment
time series is similar to that of the base case.
A-70
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
When a Richards growth curve was used, the biomasses were lower than those obtained
by base case model, which assumes a von Bertalanffy growth function. However, the trends
in the biomasses were very similar. The recruitment estimates were also very similar between
the two models. The Richards growth curve provided a better fit to the fishery data than the
base case model.
When the assumed western limit of the bigeye stock distribution was extended from
150°W to 170°E, and the additional catch taken in the WCPO was included in the model, the
recruitments and biomasses were greater than those estimated by the base case. However, the
biomass estimates for most years became lower than the base case when the model was also
fit to the additional CPUE and size-composition data from the WCPO.
At the beginning of January 2009, the spawning biomass of bigeye tuna in the EPO was
near the historic low level. At that time the spawning biomass ratio (the ratio of the spawning
biomass at that time to that of the unfished stock; SBR) was about 0.17, which is about 11%
less than the level corresponding to the maximum sustainable yield (MSY).
Recent catches are estimated to have been 19% greater than those corresponding to the
MSY levels. If fishing mortality (F) is proportional to fishing effort, and the current patterns
of age-specific selectivity are maintained, the level of fishing effort corresponding to the
MSY is about 81% of the current (2006-2008) level of effort. The MSY of bigeye in the EPO
could be maximized if the age-specific selectivity pattern were similar to that for the longline
fishery that operates south of 15N because it catches larger individuals that are close to the
critical weight. Before the expansion of the floating-object fishery that began in 1993, the
MSY was greater than the current MSY and the fishing mortality was less than FMSY.
All four scenarios considered suggest that, at the beginning of 2009, the spawning
biomass (S) was below SMSY. MSY and the F multiplier are sensitive to how the assessment
model is parameterized, the data that are included in the assessment, and the periods assumed
to represent average fishing mortality, but under all scenarios considered, fishing mortality is
well above FMSY. The management quantities derived from the base case model were the
less pessimistic among all scenarios.
Recent spikes in recruitment are predicted to result in stabilized levels of SBR and
increased longline catches for the next few years. However, high levels of fishing mortality
are expected to subsequently reduce the SBR. Under current effort levels, the population is
unlikely to remain at levels that support MSY unless fishing mortality levels are greatly
reduced or recruitment is above average for several consecutive years.
These simulations are based on the assumption that selectivity and catchability patterns
will not change in the future. Changes in targeting practices or increasing catchability of
bigeye as abundance declines (e.g. density-dependent catchability) could result in differences
from the outcomes predicted here.
Key results
1). The results of this assessment are similar to the previous assessments;
2). There is uncertainty about recent and future recruitment and biomass levels;
3). The recent fishing mortality rates are well above those corresponding to the MSY, and
this result is consistent across various modeling scenarios;
A-71
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
4). The results from the base case model are the more optimistic among the various
modeling scenarios investigated;
5). The results are more pessimistic if a stock-recruitment relationship is assumed;
6). Assuming a more flexible Richards growth curve improved the model fit to the fishery
data. This alternative model could be considered as the base case model in future
assessments;
7). The assessment results are more pessimistic if the western limit of the bigeye stock
distribution is extended from 150°W to 170°E.
Biographical Sketch of Speaker:
Alexandre Aires-da-Silva, Dr. Alexandre Aires-da-Silva presently serves as the Senior
Scientist-Investigador Principal for the Inter-American Tropical Tuna Commission (IATTC). Alex
joined the IATTC’s Tuna-Billfish group in 2007. His main responsibility is the stock assessment
of bigeye tuna in the eastern Pacific Ocean. He is also involved in the stock assessments of
northern Pacific bluefin and albacore by the International Scientific Committee (ISC) for Tuna
and Tuna-Like Species in the North Pacific Ocean.
In addition to his tuna stock assessment work, Alex’s main research interests include:
population dynamics modeling and stock assessment of data-poor species (with emphasis on
sharks), quantitative analysis of tagging data, and investigating spatial issues in stock assessments
of highly migratory species. Alex has also a keen interest in building scientific research capacity in
developing countries through cooperative work and teaching activities.
7. Status of Yellowfin Tuna in the Eastern Pacific Ocean in 2008 and Outlook for the
Future
(Mark N. Maunder*, and Alexandre Aires-da-Silva)
(Stock Assessment Report 10, IATTC, 2010, http://www.iattc.org/PDFFiles2/SAR10a-YFTENG.pdf)
This report presents the most current stock assessment of yellowfin tuna (Thunnus
albacares) in the eastern Pacific Ocean (EPO). An integrated statistical age-structured stock
assessment model (Stock Synthesis Version 3) was used in the assessment, which is based on
the assumption that there is a single stock of yellowfin in the EPO. This model differs from
that used in previous assessments. Yellowfin are distributed across the Pacific Ocean, but the
bulk of the catch is made in the eastern and western regions. The purse-seine catches of
yellowfin are relatively low in the vicinity of the western boundary of the EPO. The
movements of tagged yellowfin are generally over hundreds, rather than thousands, of
kilometers, and exchange between the eastern and western Pacific Ocean appears to be limited.
This is consistent with the fact that longline catch-per-unit-of-effort (CPUE) trends differ
among areas. It is likely that there is a continuous stock throughout the Pacific Ocean, with
exchange of individuals at a local level, although there is some genetic evidence for local
isolation. Movement rates between the EPO and the western Pacific cannot be estimated with
currently-available tagging data.
A-72
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
The stock assessment requires substantial amounts of information, including data on
retained catches, discards, indices of abundance, and the size compositions of the catches of
the various fisheries. Assumptions have been made about processes such as growth,
recruitment, movement, natural mortality, fishing mortality, and stock structure. The
assessment for 2009 differs substantially from that of 2008 because it uses the Stock Synthesis
program, whereas the A-SCALA program was used for previous assessments. The main
differences include: use of a sex-specific model, inclusion of indices of abundance, rather than
effort, and use of functional forms for selectivity. The catch and length-frequency data for the
surface fisheries have been updated to include new data for 2008. New or updated longline
catch data are available for China (2007), Chinese Taipei (2005-2007), and Japan (2003-2007).
In general, the recruitment of yellowfin to the fisheries in the EPO is variable, with a
seasonal component. This analysis and previous analyses have indicated that the yellowfin
population has experienced two, or possibly three, different recruitment productivity regimes
(1975-1982, 1983-2002, and 2003-2006). The productivity regimes correspond to regimes in
biomass, higher-productivity regimes producing greater biomass levels. A stock-recruitment
relationship is also supported by the data from these regimes, but the evidence is weak, and is
probably an artifact of the apparent regime shifts. Larger recruitments in 2007 and 2008 have
caused the biomass to increase in recent years.
The average weights of yellowfin taken from the fishery have been fairly consistent over
time, but vary substantially among the different fisheries. In general, the floating-object,
northern unassociated, and pole-and-line fisheries capture younger, smaller yellowfin than do
the southern unassociated, dolphin-associated, and longline fisheries. The longline fisheries
and the dolphin-associated fishery in the southern region capture older, larger yellowfin than
do the northern and coastal dolphin-associated fisheries.
Significant levels of fishing mortality have been estimated for the yellowfin fishery in the
EPO. These levels are highest for middle-aged yellowfin. Despite the fact that more catch is
taken in the fishery associated with dolphins than in the other fisheries, the floating-object and
unassociated purse-seine fisheries have a greater impact on the yellowfin spawning biomass.
The estimated biomass is significantly lower than that estimated in the previous
assessment, indicating that the results are sensitive to the changes in assessment methodology.
There is also a large retrospective pattern of overestimating recent recruitment. The pattern is
due to size composition data for the floating-object fishery. These, in combination with the
wide confidence intervals for estimates of recent recruitment, indicate that estimates of recent
recruitment and recent biomass are uncertain. The results of the assessment are also
particularly sensitive to the level of natural mortality assumed for adult yellowfin.
Historically, the spawning biomass ratio (ratio of the spawning biomass to that of the unfished
population; SBR) of yellowfin in the EPO was below the level corresponding to the maximum
sustainable yield (MSY) during 1975-1983 corresponding to the lower productivity regime of ,
but above that level for most of the following years, except for the recent period (2004-2007).
The 1984 increase in the SBR is attributed to the regime change, and the recent decrease may
be a reversion to an intermediate productivity regime. The two different productivity regimes
may support two different MSY levels and associated SBR levels. The SBR at the start of
2009 is estimated to be above the level corresponding to the MSY. The effort levels are
A-73
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
estimated to be less than those that would support the MSY (based on the current distribution
of effort among the different fisheries), but recent catches are substantially below MSY.
The MSY calculations indicate that, theoretically at least, catches could be increased if
the fishing effort were directed toward longlining and purse-seine sets on yellowfin associated
with dolphins. This would also increase the SBR levels.
The MSY has been stable during the assessment period, which suggests that the overall
pattern of selectivity has not varied a great deal through time. However, the overall level of
fishing effort has varied with respect to the level corresponding to MSY.
The SBR corresponding to MSY decreased substantially from the previous assessment,
indicating that the results are sensitive to the change in methodology, specifically to method
used to model selectivity. However, the SBR relative to SBR corresponding to MSY and the
multiplier of F (fishing mortality) are similar to those of the previous assessment.
If a stock-recruitment relationship is assumed, the outlook is more pessimistic, and
current biomass is estimated to be below the level corresponding to the MSY. The status of the
stock is also sensitive to the value of adult natural mortality, the method used to model
selectivity, and the assumed length of the oldest age modeled (29 quarters).
Under recent levels of fishing mortality (2006-2008), the spawning biomass is predicted
to slightly decrease, but remain above the level corresponding to MSY. Fishing at Fmsy is
predicted to reduce the spawning biomass slightly from that under current effort and produces
slightly higher catches.
Key Results
1). The estimates of absolute biomass are lower than those in previous years.
2). The SBR corresponding to MSY is substantially less than those of previous assessments,
and the reduction is attributed to the new method to model selectivity.
3). There is uncertainty about recent and future recruitment and biomass levels, and there are
retrospective patterns of overestimating recent recruitment.
4). The recent fishing mortality rates are close to those corresponding to the MSY.
5). Increasing the average weight of the yellowfin caught could increase the MSY.
6). There have been two, and possibly three, different productivity regimes, and the levels of
MSY and the biomasses corresponding to the MSY may differ among the regimes. The
population may have recently switched from the high to an intermediate productivity
regime.
7). The results are more pessimistic if a stock-recruitment relationship is assumed.
8). The results are sensitive to the natural mortality assumed for adult yellowfin, the method
used to model selectivity, and the length assumed for the oldest fish.
8. Updated Indicators of Stock Status for Skipjack Tuna in the Eastern Pacific Ocean
(Mark N. Maunder*)
(Stock Assessment Report 10, IATTC, 2010, http://www.iattc.org/PDFFiles2/SAR10bSKJ.pdf)
A-74
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
A major management objective for tunas in the eastern Pacific Ocean (EPO) is to keep
stocks at levels capable of producing maximum sustainable yields (MSYs). Management
objectives based on MSY or related reference points (e.g. fishing mortality that produces MSY
(FMSY); spawner-per-recruit proxies) are in use for many species and stocks worldwide.
However, these objectives require that reference points and quantities to which they are
compared be available. The various reference points require different amounts and types of
information, ranging from biological information (e.g. natural mortality, growth, and stockrecruitment relationship) and fisheries characteristics (e.g. age-specific selectivity), to absolute
estimates of biomass and exploitation rates. These absolute estimates generally require a
formal stock assessment model. For many species, the information required to estimate these
quantities is not available, and alternative approaches are needed. Even more data are required
if catch quotas are to be used as the management tool.
Skipjack tuna is a notoriously difficult species to assess. Due to skipjack’s high and
variable productivity (i.e. annual recruitment is a large proportion of total biomass), it is
difficult to detect the effect of fishing on the population with standard fisheries data and stock
assessment methods. This is particularly true for the stock of the EPO, due to the lack of agefrequency data and the limited tagging data. The continuous recruitment and rapid growth of
skipjack mean that the temporal stratification needed to observe modes in length-frequency
data make the current sample sizes inadequate. Previous assessments have had difficulty in
estimating the absolute levels of biomass and exploitation rates, due to the possibility of a
dome-shaped selectivity curve (Maunder 2002; Maunder and Harley 2005), which would
mean that there is a cryptic biomass of large skipjack that cannot be estimated. The most
recent assessment of skipjack in the EPO (Maunder and Harley 2005) is considered
preliminary because it is not known whether the catch per day fished for purse-seine fisheries
is proportional to abundance. The results from that assessment are more consistent among
sensitivity analyses than the earlier assessments, which suggests that they may be more
reliable. However, in addition to the problems listed above, the levels of age-specific natural
mortality are uncertain, if not unknown, and current yield-per-recruit (YPR) calculations
indicate that the YPR would be maximized by catching the youngest skipjack in the model
(Maunder and Harley 2005). Therefore, neither the biomass- nor fishing mortality-based
reference points, nor the indicators to which they are compared, are available for skipjack in
the EPO.
One of the major problems mentioned above is the uncertainty as to whether the catch per
unit of effort (CPUE) of the purse-seine fisheries is an appropriate index of abundance for
skipjack, particularly when the fish are associated with fish-aggregating devices (FADs).
Purse-seine CPUE data are particularly problematic, because it is difficult to identify the
appropriate unit of effort. In the current assessment, effort is defined as the amount of
searching time required to find a school of fish on which to set the purse seine, and this is
approximated by number of days fished. Few skipjack are caught in the longline fisheries or
dolphin-associated purse-seine fisheries, so these fisheries cannot be used to develop reliable
indices of abundance for skipjack. Within a single trip, purse-seine sets on unassociated
schools are generally intermingled with floating-object or dolphin-associated sets,
complicating the CPUE calculations. Maunder and Hoyle (2007) developed a novel method to
generate an index of abundance, using data from the floating-object fisheries. This method
used the ratio of skipjack to bigeye in the catch and the “known” abundance of bigeye based
on stock assessment results. Unfortunately, the method was of limited usefulness, and more
A-75
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
research is needed to improve it. Currently, there is no reliable index of relative abundance for
skipjack in the EPO. Therefore, other indicators of stock status, such as the average weight of
the fish in the catch, should be investigated.
Since the stock assessments and reference points for skipjack in the EPO are so uncertain,
developing alternative methods to assess and manage the species that are robust to these
uncertainties would be beneficial. Full management strategy evaluation (MSE) for skipjack
would be the most comprehensive method to develop and test alternative assessment methods
and management strategies (Maunder 2007); however, developing MSE is time-consuming,
and has not yet been conducted for skipjack. In addition, higher priority for MSE is given to
yellowfin and bigeye tuna, as available data indicate that these species are more susceptible to
overfishing than skipjack. Therefore, Maunder and Deriso (2007) investigated some simple
indicators of stock status based on relative quantities. Rather than using reference points based
on MSY, they compared current values of indicators to the distribution of indicators observed
historically. They also developed a simple stock assessment model to generate indicators for
biomass, recruitment, and exploitation rate. We update their results to include data for 2008.
To evaluate the current values of the indicators in comparison to historical values, we use
reference levels based on the 5th and 95th percentiles, as the distributions of the indicators are
somewhat asymmetric.
Eight data- and model-based indicators are shown in Figure 1. The standardized effort,
which is a measure of exploitation rate, is calculated as the sum of the effort, in days fished,
for the floating-object (OBJ) and unassociated (NOA) fisheries. The floating-object effort is
standardized to be equivalent to the unassociated effort by multiplying by the ratio of the
average floating-object CPUE to the average unassociated CPUE. The purse-seine catch has
been increasing since 1985, and is currently above the upper reference level. Except for a large
peak in 1999, the floating-object CPUE has generally fluctuated around an average level since
1990. The unassociated CPUE has been higher than average since about 2003 and was at its
highest level in 2008. The standardized effort indicator of exploitation rate has been increasing
since about 1991, but declined in recent years. The average weight of skipjack has been
declining since 2000, and in 2008 was at the lower reference level. The biomass, recruitment,
and exploitation rate have been increasing over the past 20 years.
The main concern with the skipjack stock is the constantly increasing exploitation rate.
However, the data- and model-based indicators have yet to detect any adverse consequence of
this increase. The average weight is near its lower reference level, which can be a consequence
of overexploitation, but it can also be caused by recent recruitments being greater than past
recruitments.
Biographical Sketch of Speaker:
Dr. Mark Maunder presently serves the Head of the Stock Assessment Program for the
Inter American Tropical Tuna Commission. Mark is one of the three founding members of
the AD Model Builder Foundation, which was the driving force for the public release of AD
Model Builder. In collaboration with George Watters, Mark developed the A-SCALA stock
assessment model that was used to assess tunas in the EPO for ten years by the IATTC. He
also collaborates with Simon Hoyle on a project funded by PFRP to develop and apply
modeling methodology for protected species. This project has involved modeling of the
A-76
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
northeastern offshore spotted dolphin stock in the EPO and a Hawaiian black footed
albatross population. He has taught a course in ecological modeling at the Scripps Institution
of Oceanography and short courses on stock assessment, AD Model Builder, and ecological
modeling. His main research interests are in the development of methods for fisheries stock
assessment and ecological modeling.
9. Increasing the Economic Value of the Eastern Pacific Ocean Tropical Tuna Fishery:
Tradeoffs Between Longline and Purse Seine Fishing
(Chin-Hwa Jenny Sun*, Mark N. Maunder, Alexandre Aires-da-Silva, and
William H. Bayliff*)
Yellowfin and bigeye tuna in the EPO are not managed optimally with respect to their
economic value. Both species are caught at sizes too small to take full advantage of their
individual growth and the higher price obtained for large fish in the sashimi market. Large
bigeye and yellowfin destined for the sashimi market are caught in the longline fishery, while
smaller bigeye, yellowfin, and skipjack destined for the canned tuna market are caught in the
purse-seine fisheries. We evaluate the economic and biological trade-offs that might be
considered when managing tropical tunas in the EPO. We also discuss methods to implement
management (e.g. tradable property rights and compensation) that may address the social and
equity issues.
It is assumed that if the catches of small bigeye and yellowfin were reduced, the gains to
the biomass of those species due to growth would exceed the losses to it due to natural
mortality. This would increase the availability of large bigeye and yellowfin to the longline
fishery, which, in turn, would increase the total catches of those species, provided there was
sufficient fishing effort by longliners. It is further assumed that bigeye and yellowfin are well
mixed within the EPO, in which case reductions in the catches of small tunas anywhere in the
EPO would be beneficial to longliners operating anywhere in the EPO. It is further assumed
that the purse-seine and longline fisheries could be managed in such a way that the spawning
biomasses of the two species were maintained at optimum levels.
Three analyses are conducted to evaluate the economic and biological tradeoffs of
different levels of purse-seine and longline fishing effort. The first evaluates the different
combinations of effort that could produce the target biomass level. The second evaluates
combinations of effort that optimize equilibrium (long-term) yield and economic value. The
third evaluates the dynamic (short-term) effect of different combinations of effort. The
analyses are based on the current stock assessment models for yellowfin and bigeye tuna and
recent average catch levels for skipjack tuna. The economic value is determined from the
landings value for purse-seine- and longline-caught tuna of each species.
In order to resolve the conflicts of interest among different countries and fishing gears
that utilize the tuna resources, we propose the establishment of either a compensation scheme
to create incentives to purse-seine fishermen to reduce their catches of juvenile bigeye and
yellowfin tuna or a transferable property right system. The subtleties of such a system still
A-77
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
need to be worked out to address the complexities of the fishery, but the potential benefits are
such that the possibility of implementing such a system should not be ignored.
Biographical Sketch of Speaker:
Chin-Hwa Jenny Sun presently serves as a Professor, in the Institute of Applied
Economics and Department of Environmental Biology and Fisheries Science for the
National Taiwan Ocean University, and currently a visiting research scholar with the InterAmerican Tropical Tuna Commission. She is experienced and knowledgeable about tuna
industries, economics, and institutions, and her interests in fisheries economics cover a
number of topics, including bioeconomics, climate change, international trade,
transboundary conservation, management, and rights-based management, especially on the
economics of Taiwan’s tuna and pelagic species fisheries. She served as the Science
Delegate, representing Taiwan in the Commission Meetings of Commission for the
Conservation of Southern Bluefin Tuna from 2004 to 2008, has participated in, and
organized, many international meetings on the economics of tuna fisheries.
William H. Bayliff received his Ph.D. degree from the University of Washington in
1965. He has worked on Pacific salmon for the Washington Department of Fisheries, on
shrimp and small pelagic fishes for the Food and Agriculture Organization of the United
Nations, and on baitfishes, tunas, and billfishes for the Inter-American Tropical Tuna
Commission (IATTC). He is currently a senior scientist for the IATTC, for which he works
on a variety of projects.
Session III. Tuna Fishing Capacity and Fishery Dynamics (Chairs: Dale Squire)
10. Fishing Capacity and Productivity Growth in the EPO Tuna Purse Seine Fishery
(Eric Janofsky*, James Kirkley, Dale Squires, Chin-Hwa Jenny Sun, and Yongil Jeon)
This presentation is concerned with the estimation of (output-based) capacity and
efficiency of global tuna fleets. We present results for the three largest tuna purse-seine
fleets: western and central pacific, eastern pacific and Indian ocean. We find historical
stability throughout the Pacific with efficiency levels at a steady 75%, and capacity between
80% and 85%. We find overcapacity throughout the fisheries of interest and implicate it as a
threat to sustainable resource levels.
Biographical Sketch of Speaker:
Dr. Dale Squires presently serves as the Senior Scientist and Economist for the National
Marine Fisheries Service, also carrying out his duties as an Honorary Professor at the
University of Southern Denmark and as an Adjunct Professor of Economics at the University
of California San Diego. Squires served as a visiting scientist with the WorldFish Center, as
well as on the U.S. Delegation to Renegotiate South Pacific Tuna Treaty, a member of the
FAO Technical Consultation on Global Tuna Purse Seine Capacity, and as the Pacific Fisher
Management Council Leader of the Highly Migratory Species Plan Development and
A-78
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Management Teams. Squires was instrumental in the economics of capacity in the FAO
International Plan of Action on Fishing Capacity.
Session IV. Estimation of Global Tuna Demand
(a). Case Study of Tuna Can Trade and Markets (Chair: Patrice Guillotreau)
11. Global Integration of European Tuna Markets
(Jiménez, Toribio R., Patrice Guillotreau* and R. Mongruel)
This paper evaluates the degree of integration between the major European marketplaces
and the world market of frozen and canned tuna products through both horizontal and
vertical price relationships. Spatial linkages are investigated horizontally in order to estimate
the connection between the European market and the world-wide market on the primary
stage of the value chain. One of the key results is the high level of market integration at the
ex-vessel stage, and the price leadership of yellowfin tuna over skipjack. The same approach
is applied at the ex-cannery level. Basically, the European market for final goods appears to
be segmented between the Northern countries consuming low-priced canned skipjack
imported from Asia (mainly Thailand) and the Southern countries (Italy, Spain) processing
and importing yellowfin-based products sold at higher prices.
France appears to be an intermediate market where both products are consumed. The
European markets are found to be well integrated to the world market and can be considered
to be competitive, but there is a suspicion of market power being exercised at the
downstream stages of the value chain for canned yellowfin. Price relationships are therefore
tested vertically between the price of frozen tuna paid by the canneries and the price of
canned fish at the retail level in both Italy and France. The two species (skipjack and
yellowfin) show an opposite pattern in price transmission along the value chain: price
changes along the chain are far better transmitted for the “global” skipjack than for the more
“European” yellowfin.
The existence of market power on the market for some canned products (e.g. canned
yellowfin in brine) is perhaps due to the high level of industrial concentration at the canning
and retail level but certainly reinforced by the presence of product differentiation on the
European canned tuna markets, the height of tariff and non-tariff barriers under specific EUACP states agreements, or even the implementation of a national price policy resulting in
rear margins which are included in the end consumer price.
Such market imperfections have implications upon fisheries exploitation, because if
market power could be exercised by the intermediaries upon the tuna fishing industry, the
signal of resource scarcity might not appear at the ex-vessel level because of the high
demand pressure on production prices, hence pushing the fishermen to increase their fishing
effort so as to compensate through higher catches and landings the low level of prices. This
issue is further investigated on the French market for canned yellowfin in brine through a
structural model by introducing demand shifters in order to look at the impact of price shocks
on marginal revenue. Evidence of maret power is demonstrated, although it was not possible
to measure it accurately.
A-79
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
Biographical Sketch of Speaker:
Patrice Guillotreau is Senior lecturer in economics at the University of Nantes, France,
since 1994. His field of research deals with the economics of fisheries and seafood markets.
He has coordinated and participated in various EU-funded projects and published several
books and articles on different sea-related, economic issues (property rights, price-cost
margins, foreign trade, consumption, auctioning, competition...). He has recently been
working for two years at IRD (Institute of Research for the Development), and spent 3
months in Seychelles studying the impact of climate oscillations on the local tuna economy
under the UN Framework Convention on Climate Change.
12. A Demand Analysis of the Spanish Canned Tuna Market
(Juan José García del Hoyo, Ramón Jiménez Toribio*, Patrice Guillotreau)
In this presentation, an analysis of demand for canned tuna in Spain is carried out. The
Spanish market of canned tuna is one of the most important in the world. According to FAO,
in 2007 Spanish production of canned tuna amounted to 216,367 Metric Tonnes and Spanish
apparent consumption was equal to 219,235 Metric Tonnes. Therefore, Spanish production
accounted for 13.70%, and Spanish apparent consumption represented 12.89% of canned
tuna in the world. Additionally, canned tuna is the most important canned fish product in
Spain. Using the Industrial Products Survey which is completed by the Spanish National
Statistics Institute, the overall supply of canned tuna has grown steadily over the last two
decades, whereas the price of canned tuna has also increased. Spanish imports of canned tuna
have also increased substantially due to the direct investment of Spanish canneries in some
South-American countries such as Ecuador, Guatemala, El Salvador, Brazil, Chile and
previously Venezuela.
For the demand analysis, three canned fish products have been considered: sardine, tuna
and other fish products. The data comes from the Food Consumption Panel, which is
produced by the Spanish Ministry of Agriculture, Fishing and Food. The sample covers the
period January 2004 to December 2009 inclusive. Several functional forms of demand
models have been considered: AIDS, Rotterdam, Rotterdam-CBS, inverse AIDS, inverse
Rotterdam and Laitinen-Theil. Both static and dynamic specifications have been considered.
The Laitinen-Theil demand model has been the most appropriate functional form for the
Spanish canned tuna market. For the static approach, Seemingly Unrelated Regression has
been used. For the dynamic approach, unit root and cointegration tests were performed.
According to the static and dynamic approaches for the demand model, the results explain to
a large extent the behaviour of canned tuna in the Spanish market. The scale flexibility for
canned tuna appears to indicate that an increase in the overall amount of canned fish
produces an increase in the normalised price of tuna.
Biographical Sketch of Speaker:
Ramon Jimenez-Toribio has been a lecturer in Quantitative Methods for Business and
Economics at the Faculty of Business Administration at the University of Huelva, Spain,
A-80
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
since 1997. His field of research deals with fisheries management, time series analysis and
analysis of fishing markets. He has participated in numerous projects and the publication of
several books and articles on fisheries economics and fish market issues. He was a visiting
scholar at the Department of Economics and Related Studies at the University of York
(United Kingdom) for 3 months in 1999 and at Len-Corrail at the Faculty of Economics and
Management at the University of Nantes (France) for 6 months in 2004.
13. Price Linkage of Global Cannery Tuna Market
(Yongil Jeon and Dale Squires)
Biographical Sketch of Speaker:
Yongil Jeon, Ph.D.
Associate Professor
School of Economics SungKyunKwan University (SKKU)
South Korea
Session IV (b). Case Study of Tuna Sashimi Trade and Market (Chair: Jenny Sun)
14. Tuna Price in Response to Changes of Market Structure and Ecosystem Conditions Price Linkage between Hawaii and Japanese Tuna Sashimi Markets
(Minling Pan*, Chin-Hwa Jenny Sun and Dale Squires)
The objective of this research is twofold. First, this study uses a cointegration model to
investigate possible potential long-run pricing relationships among the major landings of the
Hawaii tuna longline fishery (bigeye, yellowfin, skipjack, and albacore tuna). This analysis
determines to what extent changes in the price of one species might impact prices of others
in the Hawaii tuna auction market. Second, a Multivariate Markov-switching autoregressive
model is used to identify regime shifts and price responses in Hawaiian bigeye and yellowfin
tuna prices in relation to their own landings, explore potential price linkages with tuna
sashimi prices in Japan, and examine the possible effect of changing tuna quality (such as
the fat content) due to seasonal changes in sea surface temperature on the major fishing
grounds.
In addition, this study intends to evaluate the market effects of ENSO (El Niño/Southern
Oscillation) cycles on prices. The price of fish is directly associated with fishersincome, and
income to fishers (and in turn, the dynamics of the fleet) might be influenced by both the
availability of resources and price levels. This research advances our understanding of the
dynamics of global tuna fisheries by providing a vital bridge between human and natural
elements in support of an ecosystem approach to management.
Biographical Sketch of Speaker:
Dr. Minling Pan is the chief economist of the Economics Program for the NOAA Pacific
Island Fisheries Science Center. Also Dr. Pan serves as a committee member for Scientific
A-81
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
and Statistical Committee of the Western Pacific Regional Fishery Management Council. As
the NOAA Pacific Island Fisheries Science Center’s chief economist, Dr. Pan is responsible
for directing the economics program involved in collecting economic data and conduct
economic research in support of fisheries management in the U.S. Pacific Islands areas,
which includes Hawaii, Guam, American Samoa, and Commonwealth of the Northern
Mariana Islands.
In addition, she currently is the principal investigator of over five on-going marine
economic studies in the Joint Institute for Marine and Atmospheric Research in University of
Hawaii. She is also an affiliate faculty member of the Department of Natural Resources and
Environmental Management, University of Hawaii. She has published papers on bioeconomic analysis, regulatory impact analysis on alternative fishery management policy,
fishing capacity assessment, and fish price and market analysis. She has frequently
presented her research nationally and internationally.
15. Inverse Demand Analysis of the Tuna Sashimi Market in Tokyo: an Application of the
Rotterdam Inverse Demand System
(Chin-Hwa Jenny Sun* and Fu-Sung Chiang)
There are many markets for tunas—sashimi (from fresh or frozen fish), canned tuna (light
meat, white meat, or various specialty products), locales (Japan, the United States, the
European Union, etc.). The supply varies across these markets, but overall it is decreasing
due to intentional reductions in catches to rebuild stocks that have been overfished.
The value-added tuna sashimi demand in Japan constitutes the largest fresh, chilled, and
frozen tuna sashimi market in the world. The annual total consumption of fresh and frozen
bigeye, yellowfin, Atlantic bluefin, Pacific bluefin, and southern bluefin reached a record
high of 580 thousand MT in 1993, and then shrank to 349 thousand MT in 2008. Because of
the scarcity of fresh bluefin tuna in Japan, substituting different tuna species and fresh and
frozen tuna became common (Yamamoto, 1994; Owen and Troedson, 1994; Bose and
McIlgorm, 1996). Chiang, Lee, and Brown (2001), who examined the impacts of financial
crisis in 1997-98 and inventories on tuna wholesale prices in the major landing ports of Japan
from January 1984 to September 1999, using Barten and Bettendorf's Rotterdam inverse
demand system (RIDS), concluded that frozen tunas are likely to be used as substitutes for
fresh tunas.
Since the demand conditions varied considerably after 2000–e.g. declining demand in
Japan for sashimi, declining demand in the United States for canned tuna, but increasing
demand in the European Union for all tuna products, and cost increases have been changing
the composition of the fishing fleet–from high-cost nations to lower-cost nations, which
makes managing the fisheries more difficult. While the domestic sashimi-grade tuna harvests
in Japan have decreased since 1985, the total imports began to increase in 1985, and
continued to do so until 2002. The imports of frozen tuna were about four times the imports
of fresh tuna. Specifically, tuna imports in Japan first exceeded the domestic supply in 1996.
As a result, Japanese domestic landings account for 49.5% of the tuna used in the sashimi
market in 2008.
A-82
APPENDIX IV– Abstract
Workshop on Global Tuna Demand and Fisheries Dynamics in the EPO
A set of six RIDS equations is estimated jointly by an iterative, seemingly unrelated
regression procedure to evaluate the inverse demand price flexibilities of fresh and frozen
bluefin, bigeye, and yellowfin tuna in the major sashimi auction market, Tokyo Tsukiji
Central Wholesale Market. The monthly data, which cover the period of January 2002
through February 2009, represent more precisely the tuna price response of Japanese
consumers than the negotiated ex-vessel wholesale prices in the landing ports, which were
used by Chiang, Lee, and Brown (2001). Six types of tuna were considered: fresh and frozen
yellowfin tuna, fresh and frozen bluefin tuna, and fresh and frozen bigeye tuna.
The results show that both the fresh and frozen bluefin tuna show less than unity in
absolute value for their scale elasticities, which means that the Japanese consumers are
willing to pay premium prices for high-quality bluefin tuna and are less responsive to price
changes than they are for the other tuna species when the supply changes. Since fresh and
frozen bigeye and yellowfin tuna show greater than unity in absolute value for their scale
elasticities, it would be beneficial for the fishing industry to realize that a better marketing
distribution scheme would increase their total landings values, even if a fishing quota for
bigeye is strained due to conservation measures. The estimated price flexibility could help to
support the economic benefit of global quota management control and the impact of changes
in fishing capacity upon the value of the total landings.
Biographical Sketch of Speaker:
Chin-Hwa Jenny Sun presently serves as a Professor, in the Institute of Applied
Economics and Department of Environmental Biology and Fisheries Science for the National
Taiwan Ocean University, and currently a visiting research scholar with the Inter-American
Tropical Tuna Commission. She is experienced and knowledgeable about tuna industries,
economics, and institutions, and her interests in fisheries economics cover a number of
topics, including bioeconomics, climate change, international trade, transboundary
conservation, management, and rights-based management, especially on the economics of
Taiwan’s tuna and pelagic species fisheries. She served as the Science Delegate, representing
Taiwan in the Commission Meetings of Commission for the Conservation of Southern
Bluefin Tuna from 2004 to 2008, has participated in, and organized, many international
meetings on the economics of tuna fisheries.
A-83
APPENDIX IV– Abstract Workshop on Global
Tuna Demand and Fisheries Dynamics in the EPO
THE ORGANIZATION FOR THE PROMOTION OF RESPONSIBLE TUNA FISHERIES
OPRT
Sankaido Bldg. (9th Floor)
1-9-13 Akasaka, Minato-ku ,Tokyo, Japan
107-0052
Tel: 03-3568-6388; Fax:03-3568-6389
Website:http//www.oprt.or.jp
NEWSLETTER INTERNATIONAL
AUG. 2010, No. 29
FOR CONSERVATION AND SUSTAINABLE USE OF TUNAS
Tuna fishery management
How to increase the economic value of tuna fishery
while maintaining the spawning biomass at a target level
"O JOUFSFTUJOH BOE DPOTUSVDUJWF TUVEZ XBT SFQPS UFE CZ %S $IJO)XB +FOOZ
4VO 1SPGFTTPS *OTUJUVUF PG "QQMJFE
&DPOPNJDT /BUJPOBM 5BJXBO 0DFBO 6OJWFSTJUZ BU B 8PSLTIPQ IFME JO -B +PMMB $BMJGPSOJB 64" .BZ 5
IF XPSLTIPQ i(MPCBM 5VOB %FNBOE 'JTIFSJFT
%ZOBNJDTBOE'JTIFSJFT.BOBHFNFOUJOUIF&BTUFSO
1BDJmD0DFBOwTQPOTPSFECZ/0""1BDJmD*TMBOET
'JTIFSJFT4DJFODF$FOUFSBOE4PVUI8FTU'JTIFSJFT4DJFODF
$FOUFS XBT PSHBOJ[FE CZ %S 4VO %S .JOMJOH 1BO BOE
%S%BMF4RVJSFTUPGPDVTPOCPUIFDPOPNJDBOECJPMPHJDBM
TZTUFN SFTFBSDI UP FOIBODF UIF DPOTFS WBUJPO BOE
NBOBHFNFOUPGIJHIMZNJHSBUPSZUVOBSFTPVSDFTUISPVHI
JODFOUJWFCBTFENBOBHFNFOU5IFXPSLTIPQJEFOUJmFEUIF
NPTUQSPNJTJOHBSFBTPGJORVJSZBOEBDUJPOBOEBEESFTTFE
QSJPSJUJFTGPSGVSUIFSSFTFBSDI*UCSPVHIUUPHFUIFSXPSME
UVOBFYQFSUTGSPNEJWFSTFmFMETPGFDPOPNJDTJOUFSOBUJPOBM
BGGBJSTCJPMPHZQPMJDZBOEUIFHMPCBMUVOBJOEVTUSZ5IF
XPSLTIPQXFCTJUFIUUQXXXmTIFSJFTTUPDLBTTFTTNFOU
DPN5JLJ8JLJUJLJJOEFYQIQ QBHF(MPCBM5VOB%F
NBOEBOE'JTIFSJFT%ZOBNJDT JODMVEFT CBDLHSPVOE
EJTDVTTJPO QBQFST BOE QSFTFOUBUJPO BCTUSBDUT %S
4VOT TUVEZ DBMMFE BUUFOUJPO PG UIF UVOB GJTIJOH JOEVTUS Z
DJSDMF XIFO 013 5 JOUSPEVDFE JU EVSJOH UIF TFNJOBS
SFDFOUMZ IFME JO 5PLZP 5IF GPMMPXJOH JT UIF BCTUSBDU
:FMMPXGJO BOE CJHFZF UVOB JO UIF FBTUFSO 1BDJGJD 0DFBO
&10
BSF OPU NBOBHFE PQUJNBMMZ XJUI SFTQFDU UP UIFJS
FDPOPNJD WBMVF #PUI TQFDJFT BSF DBVHIU BU TJ[FT UPP
TNBMM UP UBLF GVMM BEWBOUBHF PG UIFJS JOEJWJEVBM HSPXUI
BOE UIF IJHIFS QSJDFT PCUBJOFE GPS MBSHF GJTI JO UIF
TBTIJNJ NBSLFU -BSHF CJHFZF BOE ZFMMPXGJO DBVHIU JO
UIFMPOHMJOFGJTIFSZBSFVUJMJ[FEBTTBTIJNJXIJMFBMNPTU
BMM PG UIF TNBMMFS CJHFZF ZFMMPXGJO BOE TLJQKBDL DBVHIU
JO UIF QVSTFTFJOF GJTIFSJFT BSF DBOOFE 5IF FDPOPNJD
BOE CJPMPHJDBM USBEFPG GT UIBU NJHIU CF DPOTJEFSFE BSF
FWBMVBUFEUPTFFJGUIFQVSTFTFJOFBOEMPOHMJOFGJTIFSJFT
DPVMECFNBOBHFEJOTVDIBXBZUIBUUIFFDPOPNJDWBMVF
XPVME CF JODSFBTFE XIJMF UIF TQBXOJOH CJPNBTTFT PG
UIF UXP UVOB TQFDJFT XFSF NBJOUBJOFE BU UBSHFU MFWFMT
*U JT BTTVNFE UIBU JG UIF DBUDIFT PG TNBMM CJHFZF BOE
ZFMMPXmOXFSFSFEVDFEBOZXIFSFJOUIF&10UIFHBJOTUP
UIFCJPNBTTPGUIPTFTQFDJFTEVFUPHSPXUIXPVMEFYDFFE
UIF MPTTFT UP JU EVF UP
OBUVSBM NPS UBMJUZ BOE
UIBUUIJTXPVMEJODSFBTF
UIFBWBJMBCJMJUZPGMBSHF
CJHFZF BOE ZFMMPXGJO
UP UIF MPOHMJOF GJTIFS Z
PQFSBUJOH BOZXIFSF JO
UIF &10 5IJT XPVME
JO UVS O JODSFBTF UIF
UPUBM WBMVF PG DBUDIFT
PG UIPTF TQFDJFT *O
UIJT DBTF JU JT GVS UIFS
BTTVNFEUIBUUIFQVSTF
T F J O F B O E M P O H M J O F
G J T I F S J F T D P V M E C F
N B O B H F E J O T V D I B
XBZ UIBU UIF TQBXOJOH
Dr. Chin-Hwa Sun
CJPNBTTFT PG UIF UXP
TQFDJFTXFSFNBJOUBJOFEBUBUBSHFUMFWFMT
5ISFF BOBMZTFT BSF DPOEVDUFE UP FWBMVBUF UIF FDPOPNJD
BOE CJPMPHJDBM USBEFPG GT PG EJG GFSFOU MFWFMT PG QVSTF
TFJOFBOEMPOHMJOFGJTIJOHFGGPSU5IFGJSTUFWBMVBUFTUIF
EJGGFSFOU DPNCJOBUJPOT PG FGGPSU UIBU DPVME QSPEVDF UIF
UBSHFUCJPNBTTMFWFM5IFTFDPOEFWBMVBUFTDPNCJOBUJPOT
PGFGGPSUUIBUPQUJNJ[FFRVJMJCSJVNMPOHUFSN
DBUDIBOE
FDPOPNJDWBMVF5IFUIJSEFWBMVBUFTUIFEZOBNJDTIPSU
UFSN
FG GFDU PG EJG GFSFOU DPNCJOBUJPOT PG FG GPS U 5IF
BOBMZTFT BSF CBTFE PO UIF TUPDL BTTFTTNFOU NPEFMT GPS
ZFMMPXGJO BOE CJHFZF UVOB JO BOE SFDFOU BWFSBHF
DBUDI MFWFMT GPS B UIJSE TQFDJFT TLJQKBDL UVOB XIJDI JT
SBSFMZDBVHIUCZMPOHMJOFHFBS5IFUPUBMFDPOPNJDWBMVF
PG UIF DBUDI JT EFUFSNJOFE GSPN UIF MBOEJOHT WBMVF GPS
QVSTFTFJOF BOE MPOHMJOFDBVHIU UVOB PG FBDI TQFDJFT
*ODPODMVTJPOTFWFSBMQPTTJCMFNFUIPETPGJNQMFNFOUJOH
NBOBHFNFOUUIBUNBZBEESFTTUIFTPDJBMBOEFRVJUZJTTVFT
BSF BMTP EJTDVTTFE #Z UBLJOH JOUP BDDPVOU UIF DPOGMJDUT
PG JOUFSFTU BNPOH EJGGFSFOU DPVOUSJFT BOE GJTIJOH HFBST
OPRT promotes responsible tuna fisheries to ensure sustainable use of tuna resources. OPRT represents all stakeholders in tuna fisheries,
including major tuna fishing operators in the world, as well as traders, distributors, and consumers in Japan.
A-84
APPENDIX IV– Abstract Workshop on Global
Tuna Demand and Fisheries Dynamics in the EPO
THE ORGANIZATION FOR THE PROMOTION OF RESPONSIBLE TUNA FISHERIES
UIBUVUJMJ[FUIFUVOBSFTPVSDFTJUJTJNQFSBUJWFUIBUTPDJP
FDPOPNJDBOEFDPMPHJDBMDPOTJEFSBUJPOTBSFJODPSQPSBUFE
UPFTUBCMJTIBDPPQFSBUJWFTDIFNFUPDSFBUFJODFOUJWFTUP
QVSTFTFJOFmTIFSNFOUPSFEVDFUIFJSDBUDIFTPGKVWFOJMF
CJHFZF BOE ZFMMPXGJO UVOB VOEFS B USBEBCMF SJHIUTCBTFE
NBOBHFNFOUTDIFNF5IFEFUBJMTPGTVDIBNBOBHFNFOU
TZTUFN XPVME IBWF UP CF XPSLFE PVU UP BEESFTT UIF
DPNQMFYJUJFTPGUIFGJTIFSZBOEUIFTPDJFUZUIBUEFQFOET
PO JU CVU UIF QPUFOUJBM CFOFGJUT BOE UIF QPTTJCJMJUZ PG
JNQMFNFOUJOH TVDI B TZTUFN TIPVME OPU CF JHOPSFE
5IF BVUIPS JT IFBS UJMZ UIBOLGVM UP .BSL / .BVOEFS
"MFYBOESF "JSFTEB4JMWB BOE 8JMMJBN ) #BZMJG G GPS
IFMQ JO DPNQJMJOH UIF *"55$ UVOB TUPDL BTTFTTNFOU
S FTVMU GPS UIJT TUVEZ 1MFBTF DPOUBDU +FOOZ 4VO
KFOOZTVO!VDTEFEV GPS GVS UIFS JOGPS NBUJPO
FAO expert calls on purseseiners to refrain from
catching juvenile tunas and
to cooperate with longliners
0
135PSHBOJ[FEJUTTFDPOETFNJOBSGPSmTDBMJO
5PLZPPO+VOF
"UUIFTFNJOBS%S.BLPUP.JZBLFBOFYQFSU
POUVOBGJTIJOHDBQBDJUZBUUIF6OJUFE/BUJPOT'PPEBOE
"HSJDVMUVSF0SHBOJ[BUJPO'"0
EFMJWFSFEBMFDUVSFVOEFS
UIFUIFNFPG4VTUBJOBCMFVTFPGUVOBSFTPVSDFTBOEUIF
XBZUPXBSETPMVUJPOPGPWFSmTIJOHDBQBDJUZJTTVF8IBU
TIPVMECFUIFQPTJUJPOPGQVSTFTFJOFSTBOEMPOHMJOFST %S.JZBLFFYQMBJOFEUIFUSFOEPGUVOBmTIFSJFTJOUIF
XPSME BOE +BQBO BT XFMM BT UIF QSPCMFN PG FYQBOEJOH
PWFS DBQBDJUZ BOE JUT NBOBHFNFOU 0VUMJOJOH UIF
JOUFSOBUJPOBM TJUVBUJPO PG UVOB GJTIFSJFT JO SFDFOU ZFBST
BOE UIF GVUVSF QSPTQFDU IF TBJE UIF PQJOJPO PG UIF
JOUFSOBUJPOBM DPNNVOJUZ JT UIBU JU JT JNQFSBUJWF UP BWPJE
DBUDIPGKVWFOJMFUVOBTCZQVSTFTFJOFmTIJOH
5IFQVCMJDWJFXPOMPOHMJOFmTIJOHPOUIFPUIFSIBOE
IBT CFFO JNQSPWJOH HMPCBMMZ JOUP POF UIBU JU JT B GJTIJOH
NFUIPE HJWJOH MFTT JNQBDU PO UVOB SFTPVSDFT BMUIPVHI
JU JT MFTT FGGJDJFOU GJTIJOH DPNQBSFE XJUI QVSTFTFJOJOH
#PUI QVSTFTFJOJOH BOE MPOHMJOJOH DBO IBWF UIFJS PXO
XBZPGDPOUJOVJOHmTIJOHBDUJWJUJFT*CFMJFWFUIFZDBODP
FYJTUXJUIPVUDPOnJDUJGQVSTFTFJOFSTSFGSBJOGSPNDBUDIPG
KVWFOJMFUVOBTIFOPUFE
%S.JZBLFGVSUIFSQPJOUFEPVUUIBUQVSTFTFJOFmTIJOH
FGGPSUIBTTFFOBSBQJEJODSFBTFUISPVHIPVUUIFXPSMEGSPN
FBSMZ T FYDFFEJOH UIF DBUDI WPMVNF CZ MPOHMJOJOH
‫*ޓ‬G IPXFWFS GJTIJOH DBQBDJUZ JT DPOUSPMMFE BU BO
BQQSPQSJBUFMFWFMJUXPVMEGBDJMJUBUFBHSFFNFOUPOSFTPVSDF
NBOBHFNFOU BNPOH WBSJPVT TUBLFIPMEFST BOE FOBCMF
TNPPUI DPNQMJBODF XJUI OFDFTTBS Z GJTIJOH SFHVMBUJPOT
*UXPVMEBMTPNBLFJUQPTTJCMFGPSmTIFSTUPSFTUSBJODPTUT
XIJMFNBJOUBJOJOHUIFJSDBUDIWPMVNFBUUIFTBNFMFWFM
*O PSEFS UP JNQMFNFOU UIF DPOUSPM PG GJTIJOH DBQBDJUZ
%S .JZBLF TUSFTTFE UIBU JU JT DSVDJBM UP GJSTU FTUBCMJTI
UIF SFTQFDUJWF GJTIJOH SJHIUT BOE UIFO SFBMJ[F HMPCBM
SFHJTUSBUJPOPGUIFDVSSFOUmTIJOHDBQBDJUZ"GUFSGVMmMMJOH
UIFTF SFRVJSFNFOUT JU XPVME CF QPTTJCMF UP DBSS Z PVU
OFDFTTBSZNFBTVSFTUPDPOUSPMmTIJOHDBQBDJUZ
*OUIFMBTUBOBMZTJTIPXFWFSUIFSFXPVMEBSJTFBOJTTVF
PGBMMPDBUJPOPGUIFSFTPVSDFTBOEDBQBDJUZ)PXUPBMMPDBUF
SFTPVSDFTBOEDBQBDJUZXPVMECFDPNFBUPVHIJTTVFBNJE
UIF DVSSFOU DPOGSPOUBUJPOT CFUXFFO QVSTFTFJOFST BOE
MPOHMJOFSTCFUXFFOTBTIJNJQSPEVDFSTBOEDBOOFEUVOB
QSPEVDFST BOE CFUXFFO EFWFMPQJOH GJTIJOH OBUJPOT BOE
BEWBODFEOBUJPOT
"TBDPODSFUFQSPQPTBMGPSDPOTJEFSJOHUIFTPMVUJPOPG
UIJTJTTVF%S.JZBLFJOUSPEVDFEUPUIFBVEJFODFUIFTUVEZ
CZ%S$IJO)XB4VOQSFTFOUFEBCPWF
RFMO Workshop
Japan proposes 20%
cutback in the number of
purse-seiners in the Western
and Central Pacific
5
IF*OUFSOBUJPOBM8PSLTIPQPO3'.0.BOBHFNFOU
PG5VOB'JTIFSJFTXBTIFMEJO#SJTCBOF"VTUSBMJB
GSPN+VOFUP+VMZUPEJTDVTTUIFJTTVFPGUVOB
GJTIFS Z NBOBHFNFOU 5IF PCKFDUJWFT PG UIF XPSLTIPQ
XFSF UP SFDPNNFOE NFBTVSFT UP FOTVSF UIF MPOHUFSN
TVTUBJOBCJMJUZ PG UIF XPSMEhT UVOB GJTIFSJFT BOE GPDVT PO
GVUVSFNBOBHFNFOUPQUJPOTBOEJOJUJBUJWF
"U UIF NFFUJOH +BQBO QSFTFOUFE B QSPQPTBM PO B
SFEVDUJPOJOUIFDBQBDJUZPGUIFQVSTFTFJOFnFFUTPGTFWFO
EJTUBOU XBUFS GJTIJOH OBUJPOT %8'/
JODMVEJOH +BQBO
DVSSFOUMZ GJTIJOH VOEFS UIF GSBNFXPSL PG UIF 8FTUFSO
BOE$FOUSBM1BDJmD'JTIFSJFT$PNNJTTJPO8$1'$
5IF
UBSHFUMFWFMPGSFEVDUJPOXBTCZWFTTFMOVNCFSJOBMM
TFWFO%8'/nFFUTCZPSJGBQQSPQSJBUFBOFRVJWBMFOU
SFEVDUJPOJOGJTIJOHDBQBDJUZJOUIFTFGMFFUTPQFSBUJOHJO
8$1'$
5IFSFEVDUJPOQSPQPTBMJTCBTFEPOUIFGBDUUIBUQVSTF
TFJOF DBUDI JO UIF 8$1'$ BSFB IBT CFFO FYQBOEJOH
ESBTUJDBMMZGPSUIFMBTUZFBSTSFQPSUFEDBUDIXBTPOMZ
A-85
ŚƚƚƉ͗ͬͬǁǁǁ͘ŵĂĐƌŽĞƐ͘ŝƌĚ͘Ĩƌͬ
DŽĚĞůůŝŶŐŐůŽďĂůĚĞŵĂŶĚĨŽƌƚƵŶĂ
/ŶƚĞƌŶĂƚŝŽŶĂů ǁŽƌŬƐŚŽƉ ĨƵŶĚĞĚ ďLJ ƚŚĞ EZͲWƌŽũĞĐƚ DZK^͕ EKͲED&^͕
ǁŝƚŚŝŶƚŚĞŝŶƚĞƌŶĂƚŝŽŶĂůƉƌŽŐƌĂŵŵĞ/DZͲ>/KdKW;ŚƚƚƉ͗ͬͬǁǁǁ͘ŝŵďĞƌ͘ŝŶĨŽͬͿ͘
hŶŝǀĞƌƐŝƚLJŽĨEĂŶƚĞƐ͕&ƌĂŶĐĞ͕ϭϰͲϭϱƉƌŝůϮϬϭϭ
dŚĞ ŵŽĚĞůůŝŶŐ ŽĨ ŐůŽďĂů ĚĞŵĂŶĚ ĨŽƌ ƚƵŶĂƐ ĨĂĐĞƐ ĚŝĨĨĞƌĞŶƚ ĐŚĂůůĞŶŐĞƐ ĂŶĚ ƵŶĂŶƐǁĞƌĞĚ
ƋƵĞƐƚŝŽŶƐ ŚĂǀŝŶŐ ŝŵƉŽƌƚĂŶƚ ƉŽůŝĐLJ ŝŵƉůŝĐĂƚŝŽŶƐ ĨŽƌ ƚŚĞ ŵĂŶĂŐĞŵĞŶƚ ŽĨ ĨŝƐŚ ƐƚŽĐŬƐ ďLJ
ZĞŐŝŽŶĂů&ŝƐŚĞƌŝĞƐDĂŶĂŐĞŵĞŶƚKƌŐĂŶŝƐĂƚŝŽŶƐ͘
dƵŶĂŵĂƌŬĞƚƐĨŽƌĐĂŶŶĞĚƉƌŽĚƵĐƚƐŚĂǀĞďĞĞŶĨŽƵŶĚǁĞůůŝŶƚĞŐƌĂƚĞĚĂƚƚŚĞǁŽƌůĚͲǁŝĚĞůĞǀĞů͕
ĨŽƌŵŝŶŐĂƐŝŶŐůĞŐůŽďĂůĂŶĚŝŶƚĞƌĚĞƉĞŶĚĞŶƚŵĂƌŬĞƚ;^ƵŶϭϵϵϵ͕^ƋƵŝƌĞƐĞƚĂů͘ϮϬϬϲ͕:ĞŽŶĞƚĂů͘
ϮϬϬϳ͕ :ŝŵĠŶĞnjͲdŽƌŝďŝŽ Ğƚ Ăů͘ ϮϬϭϬͿ͘ ,ŽƌŝnjŽŶƚĂů ƉƌŝĐĞ ůŝŶŬĂŐĞƐ ďĞƚǁĞĞŶ ƚŚĞ ŵĂũŽƌ
ŵĂƌŬĞƚƉůĂĐĞƐďƌŽƵŐŚƚĞǀŝĚĞŶĐĞŽĨĂƐƉĂƚŝĂůůLJĐŽŵƉĞƚŝƚŝǀĞŝŶĚƵƐƚƌLJ͘dŚĞŝŶƚĞƌĂĐƚŝŽŶƉůĂLJƐŶŽƚ
ŽŶůLJďĞƚǁĞĞŶĐŽƵŶƚƌŝĞƐ͕ďƵƚĂůƐŽďĞƚǁĞĞŶƚŚĞĚŝĨĨĞƌĞŶƚƐƉĞĐŝĞƐ͕ůŝŬĞƐŬŝƉũĂĐŬĂŶĚLJĞůůŽǁĨŝŶ
ƚƵŶĂ;:ŝŵĠŶĞnjͲdŽƌŝďŝŽĞƚĂů͘ϮϬϭϬͿ͘^ƵĐŚĂŚŝŐŚĚĞŐƌĞĞŽĨŵĂƌŬĞƚŝŶƚĞŐƌĂƚŝŽŶŝƐĂůƐŽƌĞƉŽƌƚĞĚ
ŽŶƚŚĞƐĂƐŚŝŵŝͲŐƌĂĚĞƚƵŶĂŵĂƌŬĞƚ͕ĚŽŵŝŶĂƚĞĚďLJƚŚĞƐƚƌŽŶŐ:ĂƉĂŶĞƐĞŵĂƌŬĞƚ;^ƵŶϭϵϵϴ͕WĂŶ
ĂŶĚ^ƵŶϮϬϬϵͿ͘ŝƐƚŝŶĐƚƐƉĞĐŝĞƐƐƵĐŚĂƐďůƵĞĨŝŶ͕ďŝŐĞLJĞŽƌĞǀĞŶLJĞůůŽǁĨŝŶƚƵŶĂƐĂůƐŽƐĞĞŵƚŽ
ďĞůŽŶŐ ƚŽ ƚŚĞ ƐĂŵĞ ŵĂƌŬĞƚ ;ŽƐĞ ĂŶĚ DĐ /ůŐŽƌŶ ϭϵϵϲͿ͘ ĞƚǁĞĞŶ ƚŚĞ ƚǁŽ ǀĂůƵĞ ĐŚĂŝŶƐ
;ƐĂƐŚŝŵŝĂŶĚĐĂŶŶŝŶŐͿ͕ƚŚĞĨŝƐŚŝŶŐŐĞĂƌƐĂƌĞĚŝƐƚŝŶĐƚ;ƌĞƐƉĞĐƚŝǀĞůLJůŽŶŐͲůŝŶĞĂŶĚƉƵƌƐĞͲƐĞŝŶĞͿ͕
ďƵƚ ƚŚĞ ƌĂǁ ŵĂƚĞƌŝĂůƐ ĐĂŶ ƐƚĞŵ ĨƌŽŵ ƚŚĞ ƐĂŵĞ ƐƚŽĐŬƐ ;Ğ͘Ő͘ ďŝŐĞLJĞ ĂŶĚ LJĞůůŽǁĨŝŶ ƚƵŶĂƐͿ͘
A-86
ŽŶƐĞƋƵĞŶƚůLJ͕ Ă ĨŝƌƐƚ ŝƐƐƵĞ ĐŽŶĐĞƌŶƐ ƚŚĞ ĚĞŐƌĞĞ ŽĨ ŝŶƚĞƌĂĐƚŝŽŶ ďĞƚǁĞĞŶ ƚŚĞ ƐĂƐŚŝŵŝ ĂŶĚ
ĐĂŶŶĞĚƚƵŶĂŵĂƌŬĞƚƐ͕ƉĂƌƚŝĐƵůĂƌůLJŝŶƚŚĞůŽŶŐͲƌƵŶ͘
ƐĞĐŽŶĚ ƐƚƌĂŶĚ ŽĨ ƌĞƐĞĂƌĐŚ ƌĞŐĂƌĚƐ ƚŚĞ ƌĞůĂƚŝŽŶƐŚŝƉ ďĞƚǁĞĞŶ ŵĂƌŬĞƚ ƉƌŝĐĞ ĂŶĚ ƋƵĂŶƚŝƚLJ͘
DĂŶƵĨĂĐƚƵƌĞƌƐDz ĚĞŵĂŶĚ ŝƐ ĐŽŶƐŝĚĞƌĞĚ ƉƌŝĐĞ ĞůĂƐƚŝĐ ;ĞƌƚŝŐŶĂĐ Ğƚ Ăů͕͘ ϮϬϬϬ͖ ŚŝĂŶŐ Ğƚ Ăů͕͘
ϮϬϬϭͿ͘dŚĞŽǁŶͲƉƌŝĐĞĞůĂƐƚŝĐŝƚLJŽĨĚĞŵĂŶĚĨŽƌĨƌŽnjĞŶƚƵŶĂďLJƚŚĞĐĂŶŶŝŶŐŝŶĚƵƐƚƌLJŚĂƐďĞĞŶ
ĞƐƚŝŵĂƚĞĚĂƚͲϭ͘ϱϱŝŶƚŚĞtĞƐƚĂŶĚĞŶƚƌĂůWĂĐŝĨŝĐKĐĞĂŶ;ĞƌƚŝŐŶĂĐĞƚĂů͕͘ϮϬϬϬͿĂŶĚĂƐŝŵŝůĂƌ
ǀĂůƵĞŚĂƐďĞĞŶĨŽƵŶĚĨŽƌĨƌŽnjĞŶLJĞůůŽǁĨŝŶƚƵŶĂŝŶƚŚĞ/ŶĚŝĂŶKĐĞĂŶ;'ĂƌĐŝĂĚĞů,ŽLJŽĞƚĂů͘
ϮϬϭϬďͿ͘KŶƚŚĞƌĞƚĂŝůĞƌͲĐŽŶƐƵŵĞƌƐŝĚĞ͕ĚĞŵĂŶĚŽĨĐĂŶŶĞĚƚƵŶĂǁĂƐƌĂƚŚĞƌĨŽƵŶĚŝŶĞůĂƐƚŝĐŽŶ
ƐĞǀĞƌĂů ƵƌŽƉĞĂŶ ŵĂƌŬĞƚƐ ůŝŬĞ &ƌĂŶĐĞ ;ͲϬ͘ϭϯ ĨŽƌ ĐĂŶŶĞĚ ƚƵŶĂ ŝŶ ďƌŝŶĞ͖ 'ƵŝůůŽƚƌĞĂƵ Ğƚ Ăů͘
ϮϬϬϴͿ͕ ^ƉĂŝŶ ;ͲϬ͘ϯϵ ĨŽƌ ƚŚĞ ǁŚŽůĞ ĚŽŵĞƐƚŝĐ ŵĂƌŬĞƚ ŽĨ ĐĂŶŶĞĚ ƚƵŶĂ͖ 'Ăƌкà ĚĞů ,ŽLJŽ Ğƚ Ăů͘
ϮϬϭϬĂͿĂŶĚƚŚĞhŶŝƚĞĚ<ŝŶŐĚŽŵ;ͲϬ͘ϱϳ͕ͲϬ͘ϭϵĂŶĚͲϬ͘ϴϬƌĞƐƉĞĐƚŝǀĞůLJĨŽƌĐĂŶŶĞĚƚƵŶĂŝŶďƌŝŶĞ͕
ŝŶ ƐĂƵĐĞ ĂŶĚ ŝŶ Žŝů͖ :ĂĨĨƌLJ ĂŶĚ ƌŽǁŶ ϮϬϬϴͿ͕ ďƵƚ ŶŽƚ ŝŶ ƚŚĞ h^ ǁŚĞƌĞ Ă ŚŝŐŚ ŽǁŶͲƉƌŝĐĞ
ĚĞŵĂŶĚĞůĂƐƚŝĐŝƚLJǁĂƐĞƐƚŝŵĂƚĞĚĚĞƐƉŝƚĞĂŚŝŐŚĚĞŐƌĞĞŽĨĚŝĨĨĞƌĞŶƚŝĂƚŝŽŶ;Ͳϭ͘ϲϳĨŽƌ^ƚĂƌŬŝƐƚ͕Ͳ
ϭ͘ϳϬ ĨŽƌ ƵŵďůĞ ĞĞ͕ ͲϮ͘ϴϬ ĨŽƌ ŚŝĐŬĞŶ ŽĨ ƚŚĞ ^ĞĂ͖ ĂůŽŽŶƉĂƚĞ ϮϬϬϮͿ͖ ďƵƚ h^ ĚĞŵĂŶĚ
ĞůĂƐƚŝĐŝƚLJŝƐůŽǁĞƌĨŽƌĚŽŵĞƐƚŝĐƉƌŽĚƵĐƚƐƚŚĂŶĨŽƌŝŵƉŽƌƚĞĚŽŶĞƐ;ĂďƵůĂĂŶĚŽƌĞLJϮϬϬϱͿ͘
^LJŵŵĞƚƌŝĐĂůůLJ͕ƚŚĞƉƌŝĐĞƌĞƐƉŽŶƐĞŽĨƉƌŝĐĞƐƚŽƚŚĞǀĂƌŝĂďŝůŝƚLJŽĨĐĂƚĐŚĞƐƐŚŽǁĞĚĂůŽǁůĞǀĞůŽĨ
ĨůĞdžŝďŝůŝƚLJ;ĐŽŵƉƌŝƐĞĚďĞƚǁĞĞŶͲϬ͘ϬϱĂŶĚͲϬ͘ϮϬͿŝŶƚŚĞĐĂƐĞŽĨdŚĂŝůĂŶĚĞƐĞŝŵƉŽƌƚƐŽĨĨƌŽnjĞŶ
ƚƵŶĂĐĂƵŐŚƚďLJdĂŝǁĂŶĞƐĞǀĞƐƐĞůƐ;^ƵŶĂŶĚ,ƐŝĞŚϮϬϬϬͿ͘,ŽǁĞǀĞƌ͕ƚŚĞĞĨĨĞĐƚƐŽĨĐŚĂŶŐĞƐŝŶ
ŚĂƌǀĞƐƚ ůĞǀĞůƐ ŽŶ ƚƵŶĂ ƉƌŝĐĞƐ ĂƌĞ ĚŝĨĨŝĐƵůƚ ƚŽ ƉƌĞĚŝĐƚ ;ĞƌƚŝŐŶĂĐ Ğƚ Ăů͕͘ ϮϬϬϬͿ͕ ƉƌĞƐƵŵĂďůLJ
ďĞĐĂƵƐĞŽĨŝŶǀĞŶƚŽƌŝĞƐǁŚŝĐŚĂůůŽǁƐĂĐĞƌƚĂŝŶƉŽǁĞƌŽŶƉƌŝĐĞƐĨŽƌƉƌŽĐĞƐƐŽƌƐǁŚŽĐĂŶďƵLJ
ƉƌŝŵĂƌLJĨŝƐŚĂŶĚƐƚŽƌĞŝƚǁŚĞŶƚŚĞŵĂƌŬĞƚƉƌŝĐĞŝƐůŽǁŝŶƉĞƌŝŽĚƐŽĨŚŝŐŚĐĂƚĐŚĞƐ;ŚŝĂŶŐĞƚ
Ăů͘ ϮϬϬϭͿ͘ ĞĐĂƵƐĞ ŽĨ ƚŚĞ ŐůŽďĂů ŶĂƚƵƌĞ ŽĨ ŵĂƌŬĞƚƐ ĂŶĚ ďĞLJŽŶĚ Ă ůŽĐĂů ŵŽĚŝĨŝĐĂƚŝŽŶ ŽĨ
ĐĂƚĐŚĞƐ͕ ŽŶĞ ĐŽƵůĚ ďĞ ŝŶƚĞƌĞƐƚĞĚ ďLJ ŬŶŽǁŝŶŐ ƚŚĞ ŐůŽďĂů ƉƌŝĐĞ ƌĞƐƉŽŶƐĞ ;Ğ͘Ő͘ ƚŚƌŽƵŐŚ ƚŚĞ
ƌĞĨĞƌĞŶĐĞ ŵĂƌŬĞƚƐ ŽĨ ĂŶŐŬŽŬ ĨŽƌ ƚŚĞ ĐĂŶŶĞƌLJͲŐƌĂĚĞ ƚƵŶĂ͕ Žƌ dŽŬLJŽ ĨŽƌ ƚŚĞ ƐĂƐŚŝŵŝͲŐƌĂĚĞ
ƚƵŶĂͿ ƚŽ ĐŚĂŶŐĞƐ ŽĨ ĂŐŐƌĞŐĂƚĞĚ ĐĂƚĐŚĞƐ Ăƚ ƚŚĞ ǁŽƌůĚǁŝĚĞ ůĞǀĞů͘ dŚĞ ůŽŶŐͲƌƵŶ ŽǁŶ ƉƌŝĐĞ
ĨůĞdžŝďŝůŝƚLJ ŽĨ ƚŚĞ ĨƌŽnjĞŶ ƐŬŝƉũĂĐŬ ĂŶĚ LJĞůůŽǁĨŝŶ ƚƵŶĂ ŝŶ ĂŶŐŬŽŬ ;ĐĂŶŶĞƌLJͲŐƌĂĚĞ ƚƵŶĂͿ ǁĞƌĞ
ĨŽƵŶĚĐůŽƐĞƚŽƵŶŝƚLJ;ͲϬ͘ϵϵĂŶĚͲϭ͘ϬϮƌĞƐƉĞĐƚŝǀĞůLJ͖^ƵŶĞƚĂů͘ϮϬϭϬͿ͕ĂŶĚĞǀĞŶŐƌĞĂƚĞƌĨŽƌĨƌĞƐŚ
ĂŶĚĨƌŽnjĞŶLJĞůůŽǁĨŝŶĂŶĚďŝŐĞLJĞƐŽůĚŝŶ:ĂƉĂŶĨŽƌƐĂƐŚŝŵŝƵƐĞƐ͖ďƵƚƚŚĞƐĐĂůĞĨůĞdžŝďŝůŝƚŝĞƐǁĞƌĞ
ĨŽƵŶĚ ƐŝŐŶŝĨŝĐĂŶƚůLJ ůŽǁĞƌ ƚŚĂŶ ƵŶŝƚLJ ĨŽƌ ĨƌĞƐŚ ĂŶĚ ĨƌŽnjĞŶ ďůƵĞĨŝŶ ƚƵŶĂ ƉƵƌĐŚĂƐĞĚ ŽŶ ƚŚĞ
:ĂƉĂŶĞƐĞ ^ĂƐŚŝŵŝͲŐƌĂĚĞ ƚƵŶĂ ŵĂƌŬĞƚ͕ ƐŚŽǁŝŶŐ ůĞƐƐ ƌĞƐƉŽŶƐŝǀĞŶĞƐƐ ŽĨ ƉƌŝĐĞƐ ƚŽ ĐŚĂŶŐĞƐ ŝŶ
ƚŚĞƐƵƉƉůŝĞĚƋƵĂŶƚŝƚLJ;^ƵŶĞƚĂů͘ϮϬϭϬͿ͘
dŚĞ ĐŽŶƐĞƋƵĞŶĐĞƐ ŽĨ ƚŚĞƐĞ ƌĞƐƵůƚƐ ;ĐŽŶǀĞƌŐĞŶĐĞ ŽĨ ŝŶƚĞƌŶĂƚŝŽŶĂů ƉƌŝĐĞƐ͕ ŽǁŶͲƉƌŝĐĞ ĂŶĚ
ĐƌŽƐƐͲƉƌŝĐĞ ĞůĂƐƚŝĐŝƚŝĞƐ͕ ƉƌŝĐĞ ƌĞƐƉŽŶƐĞ ƚŽ ĐĂƚĐŚ ĐŚĂŶŐĞƐͿ ĂƌĞ ŝŵƉŽƌƚĂŶƚ ŝŶ ƚĞƌŵƐ ŽĨ ƉŽůŝĐLJ
ŝŵƉůŝĐĂƚŝŽŶƐ͘/ĨĚĞŵĂŶĚĨŽƌĨƌŽnjĞŶƚƵŶĂŝƐĞǀŝĚĞŶĐĞĚĂƐŚŝŐŚůLJĞůĂƐƚŝĐĂŶĚƉŽŽƌůLJĨůĞdžŝďůĞŝŶ
ƉƌŝĐĞƐ͕ŝƚǁŽƵůĚŵĞĂŶƚŚĂƚƚŚĞƋƵĂŶƚŝƚLJĞĨĨĞĐƚĚŽŵŝŶĂƚĞƐƚŚĞƉƌŝĐĞĞĨĨĞĐƚ͘/ŶŽƚŚĞƌǁŽƌĚƐ͕ĂŶLJ
ĚĞĐůŝŶĞ ŝŶ ĐĂƚĐŚĞƐ ĚƵĞ ƚŽ ŽǀĞƌͲĞdžƉůŽŝƚĂƚŝŽŶ Žƌ Ă ƉŽůŝĐLJ ŵĞĂƐƵƌĞ ŽĨ ƋƵŽƚĂ ƌĞĚƵĐƚŝŽŶ ǁŽƵůĚ
ƌĞƐƵůƚ ŝŶ ĚĞĐƌĞĂƐŝŶŐ ƌĞǀĞŶƵĞ ĨŽƌ ƚŚĞ ĨŝƐŚŝŶŐ ĐŽŵƉĂŶŝĞƐ͘ ^ŽŵĞ ƐƚĂƚĞƐ ǁŚŝĐŚ ĚŽ ŶŽƚ ĞŶũŽLJ Ă
ŐŽŽĚ ďĂƌŐĂŝŶŝŶŐ ƉŽƐŝƚŝŽŶ ĂŐĂŝŶƐƚ ƚŚĞ ĨŝƐŚŝŶŐ ĐŽŵƉĂŶŝĞƐ ĐĂŶ ďĞ ƚĞŵƉƚĞĚ ƚŽ ůĞƚ ƚŚĞ ŝƐƚĂŶƚ
A-87
tĂƚĞƌ &ŝƐŚŝŶŐ EĂƚŝŽŶƐ ƵƐĞ ŵŽƌĞ ŝŶƚĞŶƐŝǀĞůLJ ƚŚĞ ƌĞƐŽƵƌĐĞƐ ůŽĐĂƚĞĚ ŝŶ ƚŚĞŝƌ  ŝŶ ŽƌĚĞƌ ƚŽ
ŵĂŝŶƚĂŝŶ Ă ŐŽŽĚ ůĞǀĞů ŽĨ ƌĞǀĞŶƵĞƐ͘ KƚŚĞƌ ĐŽŶƐĞƋƵĞŶĐĞ͗ Ă ůŽĐĂů ĚĞĐůŝŶĞ ŝŶ ĐĂƚĐŚĞƐ ŵĂLJ ŶŽƚ
ŚĂǀĞ ŵĂũŽƌ ĐŽŶƐĞƋƵĞŶĐĞƐ ŽŶƚŚĞ ŐůŽďĂů ŵĂƌŬĞƚ͕ ďƵƚ ĂŶLJ ĐŚĂŶŐĞ ŽĨ ƉƌŝĐĞƐ ŝŶ ƚŚĞ ƌĞĨĞƌĞŶĐĞ
ŵĂƌŬĞƚ ǁŝůů ŚĂǀĞ ĐŽŶƐĞƋƵĞŶĐĞƐ ĨŽƌ ƚŚĞ ŐůŽďĂů ŝŶĚƵƐƚƌLJ͕ ĂŶĚ ĐŽƵůĚ ĞǀĞŶ ďĞ ƵƐĞĚ ŝŶ ƌĞŶƚͲ
ƐŚĂƌŝŶŐĂŐƌĞĞŵĞŶƚƐďĞƚǁĞĞŶƌĞƐŽƵƌĐĞŽǁŶĞƌƐĂŶĚĨŝƐŚŝŶŐĐŽŵƉĂŶŝĞƐ;^ƋƵŝƌĞƐĞƚĂů͘ϮϬϬϲͿ͘
ůƚŚŽƵŐŚƌŽďƵƐƚĂŶĚƋƵŝƚĞĐŽŶƐŝƐƚĞŶƚ͕ƚŚĞĞƐƚŝŵĂƚĞĚƌĞƐƵůƚƐĨŽƵŶĚŝŶƚŚĞůŝƚĞƌĂƚƵƌĞŝŶĚŝĐĂƚĞ
ǀĂƌŝĂďŝůŝƚLJ ďĞƚǁĞĞŶ ƐƚƵĚŝĞƐ͕ ƉŽƐƐŝďůLJ ĞdžƉůĂŝŶĞĚ ďLJ ƚŚĞ ǁŝĚĞ ǀĂƌŝĞƚLJ ŽĨ ĞĐŽŶŽŵĞƚƌŝĐ
ŵĞƚŚŽĚŽůŽŐŝĞƐ͗ ŽƌĚŝŶĂƌLJ ůĞĂƐƚ ƐƋƵĂƌĞƐ͕ ƐŝŵƵůƚĂŶĞŽƵƐ ĞƋƵĂƚŝŽŶƐ͕ ĨŝdžĞĚ ĞĨĨĞĐƚ ŵŽĚĞůƐ͕
ĐŽŝŶƚĞŐƌĂƚŝŽŶ ĂƉƉƌŽĂĐŚ͕ sĞĐƚŽƌ ĞƌƌŽƌ ĐŽƌƌĞĐƚŝŽŶ ŵŽĚĞůƐ͕ ŝŶǀĞƌƐĞ ZŽƚƚĞƌĚĂŵ ĂůŵŽƐƚ ŝĚĞĂů
ĚĞŵĂŶĚ ƐLJƐƚĞŵƐ͕ ƐƚƌƵĐƚƵƌĂů ĚLJŶĂŵŝĐ ŵŽĚĞůƐ͕ ƚƌĂŶƐĨĞƌ ĨƵŶĐƚŝŽŶ ŵŽĚĞůƐ͕ ŶĞƚǁŽƌŬ ĂŶĂůLJƐŝƐ͕
ĞƚĐ͘dŚĞƐƉĞĐŝĨŝĐĂƚŝŽŶƐĂƌĞǀĞƌLJĚŝĨĨĞƌĞŶƚĨƌŽŵĂƐƚƵĚLJƚŽĂŶŽƚŚĞƌ͕ĂƐǁĞůůĂƐƚŚĞĨƵŶĐƚŝŽŶĂů
ĨŽƌŵƐ Žƌ ƚŚĞ ĞƐƚŝŵĂƚŝŶŐ ŵĞƚŚŽĚƐ͘ dŚŝƐ ŝŶƚĞƌŶĂƚŝŽŶĂů ǁŽƌŬƐŚŽƉ ŽŶ ŐůŽďĂů ƚƵŶĂ ĚĞŵĂŶĚ
ŵŽĚĞůůŝŶŐŚĂƐƚǁŽŽďũĞĐƚŝǀĞƐ͗ƚŽŝŵƉƌŽǀĞŽƵƌĞŵƉŝƌŝĐĂůŬŶŽǁůĞĚŐĞŽĨƚƵŶĂŵĂƌŬĞƚƐĂƌŽƵŶĚ
ƚŚĞ ǁŽƌůĚ ŝŶ ĐŽŶŶĞĐƚŝŽŶ ǁŝƚŚ ŵĂŶĂŐĞŵĞŶƚ ƉŽůŝĐLJ ŝƐƐƵĞƐ͕ ĂŶĚ ƚŽ ĚŝƐĐƵƐƐ ƚŚĞ ŵŽƐƚ ƌĞůĞǀĂŶƚ
ĞĐŽŶŽŵĞƚƌŝĐ ŵĞƚŚŽĚƐ ĂŶĚ ƐƉĞĐŝĨŝĐĂƚŝŽŶƐ ƚŽ ŵŽĚĞů ĂĚĞƋƵĂƚĞůLJ ƚƵŶĂ ŵĂƌŬĞƚƐ Ăƚ ƚŚĞ ŐůŽďĂů
ƐĐĂůĞ͘
hŶĚĞƌƚŚĞĨŝŶĂŶĐŝĂůƐƵƉƉŽƌƚŽĨƚŚĞEZͲƉƌŽũĞĐƚDĂĐƌŽĞƐĂŶĚEK͕ĂŶĚŝŶĐŽͲŽƉĞƌĂƚŝŽŶǁŝƚŚ
ƚŚĞůŝŽƚŽƉͲ/ŵďĞƌƉƌŽŐƌĂŵŵĞ͕ƐĞǀĞƌĂůŝŶƚĞƌŶĂƚŝŽŶĂůĞdžƉĞƌƚƐǁŝůůďĞŝŶǀŝƚĞĚƚŽƉĂƌƚŝĐŝƉĂƚĞƚŽ
ƚŚŝƐǁŽƌŬƐŚŽƉĂƚƚŚĞhŶŝǀĞƌƐŝƚLJŽĨEĂŶƚĞƐ;ǁĞƐƚĞƌŶ&ƌĂŶĐĞͿŽŶƉƌŝůϭϰͲϭϱ͕ϮϬϭϭ͘
/ŶǀŝƚĞĚƉĂƌƚŝĐŝƉĂŶƚƐ͗
EĂŵĞ
ZĂŵſŶ:ŝŵĠŶĞnjdŽƌŝďŝŽ
/ŶƐƚŝƚƵƚŝŽŶ
hŶŝǀĞƌƐŝƚLJŽĨ,ƵĞůǀĂ
&ĂĐƵůƚĂĚĚĞŝĞŶĐŝĂƐŵƉƌĞƐĂƌŝĂůĞƐ
WůĂnjĂĚĞůĂDĞƌĐĞĚ͕ϭϭͲϮϭϬϳϭ,ƵĞůǀĂ͕^ƉĂŝŶ
ƚŽƌŝďŝŽΛĚĞŚŝĞ͘ƵŚƵ͘ĞƐ
hŶŝǀĞƌƐŝƚLJŽĨ,ƵĞůǀĂ
&ĂĐƵůƚĂĚĚĞŝĞŶĐŝĂƐŵƉƌĞƐĂƌŝĂůĞƐ
WůĂnjĂĚĞůĂDĞƌĐĞĚ͕ϭϭͲϮϭϬϳϭ,ƵĞůǀĂ͕^ƉĂŝŶ
ŚŽLJŽΛĚĞŚŝĞ͘ƵŚƵ͘ĞƐ
EKͲEĂƚŝŽŶĂůDĂƌŝŶĞ&ŝƐŚĞƌŝĞƐ^ĞƌǀŝĐĞ
ϴϲϬϰ>Ă:ŽůůĂ^ŚŽƌĞƐƌŝǀĞ͕>Ă:ŽůůĂ͕͕h^
ĂůĞ͘^ƋƵŝƌĞƐΛŶŽĂĂ͘ŐŽǀ
hŶŝǀĞƌƐŝƚLJŽĨĂůŝĨŽƌŶŝĂ͕^ĂŶŝĞŐŽ;h^Ϳ
ĞƉƚŽĨĐŽŶŽŵŝĐƐ
ĞŶƚƌĞĨŽƌŶǀŝƌŽŶŵĞŶƚĂůĐŽŶŽŵŝĐƐ
ƚŐƌŽǀĞƐΛƵĐƐĚ͘ĞĚƵ
/dd͕ Visiting Scholar
>Ă:ŽůůĂ͕͕h^͕
ĂŶĚ/ŶƐƚŝƚƵƚĞŽĨƉƉůŝĞĚĐŽŶŽŵŝĐƐ͕EĂƚŝŽŶĂů
dĂŝǁĂŶKĐĞĂŶhŶŝǀ͕͘dĂŝǁĂŶ
:ƵĂŶ:ŽƐĠ'ĂƌĐŝĂĚĞů,ŽLJŽ
ĂůĞ^ƋƵŝƌĞƐ
dŚĞŽĚŽƌĞ'ƌŽǀĞƐ
ŚŝŶͲ,ǁĂ;:ĞŶŶLJͿ^ƵŶ
A-88
ũƐƵŶΛŶƚŽƵ͘ĞĚƵ͘ƚǁ
/ĨƌĞŵĞƌ
DͲhDZDhZ
dĞĐŚŶŽƉŽůĞĚĞƌĞƐƚͲ/ƌŽŝƐĞ͕WϳϬ
ϮϵϮϴϬWůŽƵnjĂŶĠͲ&ƌĂŶĐĞ
ZĞŵŝ͘DŽŶŐƌƵĞůΛŝĨƌĞŵĞƌ͘Ĩƌ
hŶŝǀĞƌƐŝƚLJŽĨ^ƚĂǀĂŶŐĞƌ
&ĂĐƵůƚLJŽĨ^ĐŝĞŶĐĞĂŶĚdĞĐŚŶŽůŽŐLJ
ϰϬϯϲ^ƚĂǀĂŶŐĞƌ͕EŽƌǁĂLJ
ĨƌĂŶŬ͘ĂƐĐŚĞΛƵŝƐ͘ŶŽ
hŶŝǀĞƌƐŝƚLJŽĨWŽƌƚƐŵŽƵƚŚ
WŽƌƚƐŵŽƵƚŚƵƐŝŶĞƐƐ^ĐŚŽŽů
ZŝĐŚŵŽŶĚƵŝůĚŝŶŐ͕WŽƌƚůĂŶĚ^ƚƌĞĞƚ
WŽƌƚƐŵŽƵƚŚWKϭϯ͕hŶŝƚĞĚ<ŝŶŐĚŽŵ
ƐŚĂďďĂƌ͘ũĂĨĨƌLJΛƉŽƌƚ͘ĂĐ͘ƵŬ
ĞŶŵĂƌŬ
hŶŝǀĞƌƐŝƚLJŽĨŽƉĞŶŚĂŐĞŶ
/ŶƐƚŝƚƵƚĞŽĨ&ŽŽĚĂŶĚZĞƐŽƵƌĐĞĐŽŶŽŵŝĐƐ
&ĂĐƵůƚLJŽĨ>ŝĨĞ^ĐŝĞŶĐĞƐ
ŵĂdžΛĨŽŝ͘ĚŬ
/ZWĂƌŝƐ
&ƌĂŶĐĞ
ŚƌŝƐƚŝĂŶ͘DƵůůŽŶΛŝƌĚ͘Ĩƌ
/Z^ğƚĞ
&ƌĂŶĐĞ
ĐŚƌŝƐƚŝĂŶ͘ĐŚĂďŽƵĚΛŝƌĚ͘Ĩƌ
/Z^ğƚĞ
&ƌĂŶĐĞ
:ĞĂŶŶĞ͘&ŽƌƚŝůƵƐΛŝĨƌĞŵĞƌ͘Ĩƌ
>DE͕hŶŝǀĞƌƐŝƚLJŽĨEĂŶƚĞƐ
&ƌĂŶĐĞ
&ƌĂŶĐŽŝƐͲĐŚĂƌůĞƐ͘ǁŽůĨĨΛƵŶŝǀͲŶĂŶƚĞƐ͘Ĩƌ
ZĠŵŝDŽŶŐƌƵĞů
&ƌĂŶŬƐĐŚĞ
^ŚĂďďĂƌ:ĂĨĨƌLJ
DĂdžEŝĞůƐĞŶ
ŚƌŝƐƚŝĂŶDƵůůŽŶ
ŚƌŝƐƚŝĂŶŚĂďŽƵĚ
:ĞĂŶŶĞ&ŽƌƚŝůƵƐ
&ƌĂŶĕŽŝƐͲŚĂƌůĞƐtŽůĨĨ
ZĞĨĞƌĞŶĐĞƐ
ĂďƵůĂZ͘͘ĂŶĚZ͘>ŽƌĞLJ͕ϮϬϬϱ͕h͘^͘ĂŶŶĞĚdƵŶĂ^ƵƉƉůLJĂŶĚĞŵĂŶĚ͕:ŽƵƌŶĂůŽĨ/ŶĚƵƐƚƌŝĂů&ŽŽĚ
ĂŶĚŐƌŝďƵƐŝŶĞƐƐDĂƌŬĞƚŝŶŐ͕ϭϲ;ϮͿ͕ƉƉ͘ϭϰϱͲϭϲϰ͘
ĞƌƚŝŐŶĂĐ͕ D͕͘ ĂŵƉďĞůů͕ ,͘&͕͘ ,ĂŵƉƚŽŶ͕ :͕͘ ,ĂŶĚ͕ ͘:͕͘ ϮϬϬϬ͘ DĂdžŝŵŝƐŝŶŐ ƌĞƐŽƵƌĐĞ ƌĞŶƚ ĨƌŽŵ ƚŚĞ
tĞƐƚĞƌŶĂŶĚĞŶƚƌĂůWĂĐŝĨŝĐƚƵŶĂĨŝƐŚĞƌŝĞƐ͘DĂƌŝŶĞZĞƐŽƵƌĐĞĐŽŶŽŵŝĐƐϭϱ͕ϭϱϭʹϭϳϳ͘
ŽƐĞ͕ ^͕͘ DĐ/ůŐŽƌŵ͕ ͕͘ ϭϵϵϲ͘ ^ƵďƐƚŝƚƵƚĂďŝůŝƚLJ ĂŵŽŶŐ ƐƉĞĐŝĞƐ ŝŶ ƚŚĞ :ĂƉĂŶĞƐĞ ƚƵŶĂ ŵĂƌŬĞƚ͗ Ă
ĐŽŝŶƚĞŐƌĂƚŝŽŶĂŶĂůLJƐŝƐ͘DĂƌŝŶĞZĞƐŽƵƌĐĞĐŽŶŽŵŝĐƐϭϭ͕ϭϰϯʹϭϱϱ͘
ŚŝĂŶŐ͕&͘Ͳ^͕͘:ŽŶƋͲzŝŶŐ͕>͕͘ƌŽǁŶ͕D͘'͕͘ϮϬϬϭ͘dŚĞŝŵƉĂĐƚŽĨŝŶǀĞŶƚŽƌLJŽŶƚƵŶĂƉƌŝĐĞƐ͗ĂŶĂƉƉůŝĐĂƚŝŽŶ
ŽĨƐĐĂůŝŶŐŝŶƚŚĞZŽƚƚĞƌĚĂŵŝŶǀĞƌƐĞĚĞŵĂŶĚƐLJƐƚĞŵ͘ :ŽƵƌŶĂůŽĨŐƌŝĐƵůƚƵƌĂůĂŶĚƉƉůŝĞĚĐŽŶŽŵŝĐƐ
ϯϯ͕ϰϬϯʹϰϭϭ͘
A-89
ĂůŽŽŶƉĂƚĞ͕ ͕͘ ϮϬϬϮ͘ ƐƚŝŵĂƚŝŶŐ ƚŚĞ ĚĞŐƌĞĞ ŽĨ ŵĂƌŬĞƚ ƉŽǁĞƌ ĂŶĚ ƉƌŝĐĞͲƌĞƐƉŽŶƐĞ ƐƚƌĂƚĞŐŝĞƐ ŝŶ Ă
ƉƌŽĚƵĐƚͲĚŝĨĨĞƌĞŶƚŝĂƚĞĚ ŽůŝŐŽƉŽůLJ͗ ƚŚĞ ĐĂƐĞ ŽĨ ƚŚĞ ĐĂŶŶĞĚ ƚƵŶĂ ŝŶĚƵƐƚƌLJ ŝŶ Ă ůŽĐĂů ŵĂƌŬĞƚ͕ WŚ
ŝƐƐĞƌƚĂƚŝŽŶ͕hŶŝǀĞƌƐŝƚLJŽĨdĞŶŶĞƐƐĞĞ͕<ŶŽdžǀŝůůĞ͘
'ĂƌĐŝĂĚĞů,ŽLJŽ͕:͘:͕͘:ŝŵĠŶĞnjͲdŽƌŝďŝŽ͕Z͘ĂŶĚ'ƵŝůůŽƚƌĞĂƵ͕W͕͘ϮϬϭϬĂ͘dŚĞ^ƉĂŶŝƐŚŵĂƌŬĞƚĨŽƌĐĂŶŶĞĚ
ƚƵŶĂ͕ tŽƌŬƐŚŽƉ ŽŶ 'ůŽďĂů dƵŶĂ ĞŵĂŶĚ͕ &ŝƐŚĞƌŝĞƐ LJŶĂŵŝĐƐ ĂŶĚ &ŝƐŚĞƌŝĞƐ DĂŶĂŐĞŵĞŶƚ ŝŶ ƚŚĞ
ĂƐƚĞƌŶWĂĐŝĨŝĐKĐĞĂŶ/ddͲEK͕>Ă:ŽůůĂ;^ĂŶŝĞŐŽͿ͕h^͕ϭϰDĂŝϮϬϭϬ͘
'ĂƌĐŝĂ ĚĞů ,ŽLJŽ͕ :͘:͕͘ :ŝŵĠŶĞnjͲdŽƌŝďŝŽ͕ Z͘ ĂŶĚ 'ƵŝůůŽƚƌĞĂƵ͕ W͕͘ ϮϬϭϬď͘ dƵŶĂ ƉƵƌƐĞͲƐĞŝŶĞ ĚLJŶĂŵŝĐƐ ŝŶ
&ƌĂŶĐĞ ĂŶĚ ^ƉĂŝŶ͕͕ tŽƌŬƐŚŽƉ ŽŶ 'ůŽďĂů dƵŶĂ ĞŵĂŶĚ͕ &ŝƐŚĞƌŝĞƐ LJŶĂŵŝĐƐ ĂŶĚ &ŝƐŚĞƌŝĞƐ
DĂŶĂŐĞŵĞŶƚŝŶƚŚĞĂƐƚĞƌŶWĂĐŝĨŝĐKĐĞĂŶ/ddͲEK͕>Ă:ŽůůĂ;^ĂŶŝĞŐŽͿ͕h^͕ϭϰDĂŝϮϬϭϬ
'ƵŝůůŽƚƌĞĂƵ W͕͘ DŽŶŐƌƵĞů Z͕͘ :ŝŵĠŶĞnjͲdŽƌŝďŝŽ͕ Z͕͘ ϮϬϬϴ͘ DĂƌŬĞƚ ƉŽǁĞƌ ĂŶĚ ƚŚĞ ƵƌŽƉĞĂŶ ƚƵŶĂ
ŽůŝŐŽƉƐŽŶLJ͗ŝŵƉůŝĐĂƚŝŽŶƐĨŽƌĨŝƐŚĞƌŝĞƐĂŶĚƚƌĂĚĞ͕//&dWƌŽĐĞĞĚŝŶŐƐ͕EŚĂdƌĂŶŐ͕sŝĞƚŶĂŵ͕ϮϮͲϮϱ:ƵůLJ͘
:ĂĨĨƌLJ͕ ^͕͘ ƌŽǁŶ͕ :͕͘ ϮϬϬϴ͘ ĚĞŵĂŶĚ ĂŶĂůLJƐŝƐ ŽĨ ƚŚĞ h< ĐĂŶŶĞĚ ƚƵŶĂ ŵĂƌŬĞƚ͘ DĂƌŝŶĞ ZĞƐŽƵƌĐĞ
ĐŽŶŽŵŝĐƐϮϯ͕ϮϭϱʹϮϮϳ͘
:ĞŽŶ͕z͕͘ZĞŝĚ͕͘^ƋƵŝƌĞƐ͕͕͘ϮϬϬϳ͘/ƐƚŚĞƌĞĂŐůŽďĂůŵĂƌŬĞƚĨŽƌƚƵŶĂƐ͍WŽůŝĐLJŝŵƉůŝĐĂƚŝŽŶƐĨŽƌƚƌŽƉŝĐĂů
ƚƵŶĂĨŝƐŚĞƌŝĞƐ͘KĐĞĂŶĞǀĞůŽƉŵĞŶƚĂŶĚ/ŶƚĞƌŶĂƚŝŽŶĂů>Ăǁϯϵ͕ϯϮʹϱϬ͘
:ŝŵĠŶĞnjͲdŽƌŝďŝŽ͕Z͕͘'ƵŝůůŽƚƌĞĂƵ͕W͕͘DŽŶŐƌƵĞů͕Z͕͘ϮϬϭϬ͘'ůŽďĂůŝŶƚĞŐƌĂƚŝŽŶŽĨƵƌŽƉĞĂŶƚƵŶĂŵĂƌŬĞƚƐ͘
WƌŽŐƌĞƐƐŝŶKĐĞĂŶŽŐƌĂƉŚLJϴϲ;ϭͲϮͿ͕ϭϲϲͲϭϳϱ͘
WĂŶ͕ D͕͘ ^ƵŶ͕ ͘Ͳ,͕͘ ϮϬϬϵ͘ ^ƚƌƵĐƚƵƌĂů ƌĞĂŬƐ ĂŶĚ WƌŝĐĞ >ŝŶŬĂŐĞ ďĞƚǁĞĞŶ ,ĂǁĂŝŝ ĂŶĚ :ĂƉĂŶĞƐĞ dƵŶĂ ^ĂƐŚŝŵŝ
DĂƌŬĞƚƐ͕W/^ŶŶƵĂůDĞĞƚŝŶŐ͕KĐƚ͘ϮϯͲEŽǀ͘ϭ͕:ĞũƵ͕<ŽƌĞĂ͘
^ƋƵŝƌĞƐ͕͕͘dĂĞŬǁŽŶ͕<͕͘:ĞŽŶ͕z͕͘ůĂƌŬĞ͕Z͕͘ϮϬϬϲ͘WƌŝĐĞůŝŶŬĂŐĞƐŝŶWĂĐŝĨŝĐƚƵŶĂŵĂƌŬĞƚƐ͗ŝŵƉůŝĐĂƚŝŽŶƐ
ĨŽƌ ƚŚĞ ƐŽƵƚŚ WĂĐŝĨŝĐ ƚƵŶĂ ƚƌĞĂƚLJ ĂŶĚ ƚŚĞ ǁĞƐƚĞƌŶ ĂŶĚ ĐĞŶƚƌĂů WĂĐŝĨŝĐ ƌĞŐŝŽŶ͘ ŶǀŝƌŽŶŵĞŶƚĂů ĂŶĚ
ĞǀĞůŽƉŵĞŶƚĐŽŶŽŵŝĐƐϭϭ͕ϳϰϳʹϳϲϳ͘
^ƵŶ͕͘Ͳ,͘;ϮϬϭϬͿ͕/ŶǀĞƌƐĞĚĞŵĂŶĚĂŶĂůLJƐŝƐŽĨƚŚĞƚƵŶĂĨŽƌĐĂŶŶŝŶŐŵĂƌŬĞƚŝŶdŚĂŝůĂŶĚĂŶĚƚƵŶĂĨŽƌ
ƐĂƐŚŝŵŝŵĂƌŬĞƚŝŶdŽŬLJŽ͕ŝŶ͘Ͳ,͘^ƵŶ;Ě͘Ϳ͕'ůŽďĂůƚƵŶĂŝŶǀĞƌƐĞĚĞŵĂŶĚĞƐƚŝŵĂƚŝŽŶĂŶĚƚŚĞĞĐŽŶŽŵŝĐ
ƚƌĂĚĞͲŽĨĨŽĨƚŚĞƚƵŶĂůŽŶŐůŝŶĞĂŶĚƚƵŶĂƉƵƌƐĞͲƐĞŝŶĞĨŝƐŚĞƌŝĞƐŝŶƚŚĞĂƐƚĞƌŶWĂĐŝĨŝĐKĐĞĂŶ͕EK&ŝŶĂů
ZĞƉŽƌƚ͕>Ă:ŽůůĂ͕EŽǀĞŵďĞƌϮϬϭϬ͕Ɖ͘ϮϴͲϰϵ͘
^ƵŶ͕͘Ͳ,͕͘,ƐŝĞŚ͕D͘Ͳ͕͘ϮϬϬϬ͕ŶĂůLJƐŝƐŽĨƉƌŝĐĞƌĞƐƉŽŶƐĞŽĨdĂŝǁĂŶƚƵŶĂƉƵƌƐĞͲƐĞŝŶĞĨŝƐŚĞƌLJŝŶƚŚĞ
ĨƌŽnjĞŶƚƵŶĂƌĂǁŵĂƚĞƌŝĂůŵĂƌŬĞƚŝŶdŚĂŝůĂŶĚ͕:ŽƵƌŶĂůŽĨ&ŝƐŚĞƌŝĞƐ^ŽĐŝĞƚLJŽĨdĂŝǁĂŶϮϳ;ϭͿ͕ϰϳͲϱϴ͘
^ƵŶ͕͘Ͳ,͕͘ϭϵϵϵ͘ŶĂůLJƐŝƐŽĨƚŚĞDĂƌŬĞƚ^ƚƌƵĐƚƵƌĞĂŶĚWƌŝĐĞŽŝŶƚĞŐƌĂƚŝŽŶŽĨƚŚĞdƵŶĂZĂǁDĂƚĞƌŝĂů
DĂƌŬĞƚƐĨŽƌdƵŶĂĂŶŶĞƌŝĞƐŝŶƚŚĞtŽƌůĚ͕ŐƌŝĐƵůƚƵƌĞĂŶĚĐŽŶŽŵŝĐƐϮϮ͕ϱϭͲϳϮ͘
^ƵŶ͕ ͘Ͳ,͕͘ ,ƐƵ͕ t͘Ͳd͕͘ ϭϵϵϴ͘ ŶĂůLJƐŝƐ ŽĨ ƚŚĞ WƌŝĐĞ ŽŝŶƚĞŐƌĂƚŝŽŶ ĂĐƌŽƐƐ ŝĨĨĞƌĞŶƚ ŽƵŶƚƌŝĞƐ ĨŽƌ ƚŚĞ
&ƌŽnjĞŶdƵŶĂ^ĂƐŚŝŵŝDĂƌŬĞƚŝŶ:ĂƉĂŶ͕//&dWƌŽĐĞĞĚŝŶŐƐ͕dƌŽŵƐƂ͘
A-90
ŚƚƚƉ͗ͬͬǁǁǁ͘ŵĂĐƌŽĞƐ͘ŝƌĚ͘Ĩƌͬ
ǁǁǁ͘ŝŵďĞƌ͘ŝŶĨŽͬ>/KdKW͘Śƚŵů
ŚƚƚƉ͗ͬͬŝƐƐͲĨŽƵŶĚĂƚŝŽŶ͘ŽƌŐͬ
ŚƚƚƉ͗ͬͬǁǁǁ͘ŝŵďĞƌ͘ŝŶĨŽ
'ůŽďĂůĚĞŵĂŶĚŵŽĚĞůƐĨŽƌƚƵŶĂ͕EĂŶƚĞƐ͕ϭϰͲϭϱƉƌŝůϮϬϭϭ
/ŶƚĞƌŶĂƚŝŽŶĂů ǁŽƌŬƐŚŽƉ ĨƵŶĚĞĚ ďLJ ƚŚĞ EZͲWƌŽũĞĐƚ DZK^ ĂŶĚ /^^&͕ ǁŝƚŚ
ƚŚĞƐƵƉƉŽƌƚŽĨƚŚĞ/DZͲ>/KdKWŝŶƚĞƌŶĂƚŝŽŶĂůƌĞƐĞĂƌĐŚƉƌŽŐƌĂŵŵĞ͘
'E
ĂLJϭ;dŚƵƌƐĚĂLJƉƌŝůϭϰƚŚϮϬϭϭͿ
ϵ͘ϬϬ&ƌĂŶĕŽŝƐͲŚĂƌůĞƐtŽůĨĨ͕hŶŝǀĞƌƐŝƚLJŽĨEĂŶƚĞƐ͕ŝƌĞĐƚŽƌŽĨ>DE͗tĞůĐŽŵĞĂĚĚƌĞƐƐ
ϵ͘ϭϱ WĂƚƌŝĐĞ 'ƵŝůůŽƚƌĞĂƵ͕ hŶŝǀĞƌƐŝƚLJ ŽĨ EĂŶƚĞƐ͗ tŚLJ ŵŽĚĞů ŐůŽďĂů ĚĞŵĂŶĚ ĨŽƌ ƚƵŶĂ͍
KďũĞĐƚŝǀĞƐŽĨƚŚĞǁŽƌŬƐŚŽƉǁŝƚŚŝŶƚŚĞ/ŵďĞƌͲůŝŽƚŽƉĂŶĚDĂĐƌŽĞƐƉƌŽũĞĐƚƐ͘
ϵ͘ϰϱ&ƌĂŶŬƐĐŚĞ͕hŶŝǀĞƌƐŝƚLJŽĨ^ƚĂǀĂŶŐĞƌ;EŽƌǁĂLJͿ͗͞dŚĞ&K&ŝƐŚWƌŝĐĞ/ŶĚĞdž͟
ϭϬ͘ϯϬŽĨĨĞĞďƌĞĂŬ
ϭϬ͘ϰϱDĂdžEŝĞůƐĞŶ͕hŶŝǀĞƌƐŝƚLJŽĨŽƉĞŶŚĂŐĞŶ;ĞŶŵĂƌŬͿ͗Η/ŶƚĞƌƉƌĞƚŝŶŐƉƌŝĐĞĞůĂƐƚŝĐŝƚŝĞƐĂŶĚ
ĨůĞdžŝďŝůŝƚŝĞƐŽĨĚĞŵĂŶĚĂƚŝŶƚĞƌŶĂƚŝŽŶĂůůLJŝŶƚĞŐƌĂƚĞĚƐĞĂĨŽŽĚŵĂƌŬĞƚƐΗ
ϭϭ͘ϯϬŝƐĐƵƐƐŝŽŶ;ĐŚĂŝƌĞĚďLJ&ƌĂŶŬƐĐŚĞͿ͗ǁŚĂƚŝƐƉĂƌƚŝĐƵůĂƌĂďŽƵƚŝŶƚĞŐƌĂƚĞĚŐůŽďĂůƐĞĂĨŽŽĚ
ŵĂƌŬĞƚƐ;ŐƌŽƵŶĚĨŝƐŚ͕ƚůĂŶƚŝĐƐĂůŵŽŶ͕ƐŚƌŝŵƉƐ͕ƚƵŶĂͿ͍ŽƚŚĞLJƌĞĂůůLJƉůĂLJŐůŽďĂů;ǁŽƌůĚǁŝĚĞ
ĐŽŵƉĞƚŝƚŝŽŶďĞƚǁĞĞŶƐƵƉƉůŝĞƌƐ͕ƌŽůĞŽĨŵƵůƚŝŶĂƚŝŽŶĂůĨŝƌŵƐ͕ĚĞŐƌĞĞŽĨƌĞŐŝŽŶĂůĚŝĨĨĞƌĞŶƚŝĂƚŝŽŶ
ŽƌĚĞŵĂŶĚĨŽƌŚŽŵŽŐĞŶŽƵƐŐŽŽĚƐ͙Ϳ͍&ƵƚƵƌĞĞǀŽůƵƚŝŽŶŽĨƉƌŝĐĞƐĂŶĚƚƌĂĚĞǁŝƚŚƌĞƐƉĞĐƚƚŽ
ƚŚĞĚLJŶĂŵŝĐƐŽĨĨŝƐŚĞƌŝĞƐĂŶĚĂƋƵĂĐƵůƚƵƌĞ͍͘͘͘
KƚŚĞƌ ƚŽƉŝĐƐ ƐƵŐŐĞƐƚĞĚ ďLJ ĂůĞ͗ ĐŽŝŶƚĞŐƌĂƚŝŽŶ ƚĞƐƚƐ͕ ĨƵŶĐƚŝŽŶĂů ĨŽƌŵ͕ ŝŶǀĞƌƐĞ ǀĞƌƐƵƐ ĚŝƌĞĐƚ
ĚĞŵĂŶĚ͕ ŶĞƐƚĞĚ ŚLJƉŽƚŚĞƐŝƐ ƚĞƐƚŝŶŐ ĨŽƌ ĨŝŶĂů ĨŽƌŵ͕ ƐĞƌŝĂů ĐŽƌƌĞůĂƚŝŽŶ ĐŽƌƌĞĐƚŝŽŶ͕ ĂŶLJ
A-91
ƐĞƉĂƌĂďŝůŝƚLJĂŶĚĂŐŐƌĞŐĂƚŝŽŶŝƐƐƵĞƐ;Ğ͘Ő͘ŚŽǁƚŽĨŽƌŵĐŽŶƐŝƐƚĞŶƚĂŐŐƌĞŐĂƚĞƐ͕ǁŚŝĐŚƉƌŽĚƵĐƚƐ
ƚŽ ŝŶĐůƵĚĞ ƐƵĐŚ ĂƐ ĚŝĨĨĞƌĞŶƚ ƚLJƉĞƐ ŽĨ ƚƵŶĂ ƉƌŽĚƵĐƚƐ͕ ŽƚŚĞƌ ĨŝƐŚ Žƌ ŵĞĂƚ ƐƵďƐƚŝƚƵƚĞƐͿ͕ ƉĂŶĞů
ĚĂƚĂŝƐƐƵĞƐ͕ƉƌŝĐĞŝŶĚŝĐĞƐƚŽƵƐĞ͘
ϭϮ͘ϯϬ>ƵŶĐŚďƌĞĂŬĂƚ/DEͲ/
ϭϰ͘ϬϬ^ŚĂďďĂƌ:ĂĨĨƌLJ;hŶŝǀĞƌƐŝƚLJŽĨWŽƌƚƐŵŽƵƚŚ͕h<Ϳ͗͞ĚĞŵĂŶĚĂŶĂůLJƐŝƐŽĨƚŚĞh<ĐĂŶŶĞĚ
ƚƵŶĂŵĂƌŬĞƚ͟
ϭϰ͘ϰϱ:ĞŶŶLJ^ƵŶ;EĂƚŝŽŶĂůdĂŝǁĂŶKĐĞĂŶhŶŝǀĞƌƐŝƚLJĂŶĚh^ͿΗ/ŶǀĞƌƐĞĞŵĂŶĚŶĂůLJƐŝƐŽĨ
ƚŚĞdƵŶĂĨŽƌĂŶŶŝŶŐDĂƌŬĞƚŝŶdŚĂŝůĂŶĚĂŶĚdƵŶĂĨŽƌ^ĂƐŚŝŵŝDĂƌŬĞƚŝŶdŽŬLJŽ͕:ĂƉĂŶͲŶ
ƉƉůŝĐĂƚŝŽŶŽĨƚŚĞ'ĞŶĞƌĂů^LJŶƚŚĞƚŝĐ/ŶǀĞƌƐĞĞŵĂŶĚ^LJƐƚĞŵƐΗ
ϭϱ͘ϯϬŽĨĨĞĞďƌĞĂŬ
ϭϱ͘ϰϱ ZĂŵſŶ :ŝŵĠŶĞnjͲdŽƌŝďŝŽ͕ :ƵĂŶͲ:ŽƐĠ 'ĂƌĐşĂͲĚĞůͲ,ŽLJŽ ;hŶŝǀĞƌƐŝƚLJ ŽĨ ,ƵĞůǀĂ͕ ^ƉĂŝŶͿ͗
͞^ƉĂŶŝƐŚĚĞŵĂŶĚŽĨĐĂŶŶĞĚƚƵŶĂ͟
ϭϲ͘ϯϬŝƐĐƵƐƐŝŽŶ;ĐŚĂŝƌĞĚďLJ:ĞŶŶLJ^ƵŶͿ͗>ŝŶŬĂŐĞƐďĞƚǁĞĞŶĐĂŶŶĞĚƚƵŶĂĂŶĚƐĂƐŚŝŵŝŵĂƌŬĞƚƐ
ƚŚƌŽƵŐŚŶĂƚƵƌĂůƌĞƐŽƵƌĐĞƐƚŽĐŬƐ͘>ŝŵŝƚƐŽĨƚŚĞ/^ŵŽĚĞůƐĂŶĚĂůƚĞƌŶĂƚŝǀĞƐ͘^ƵďƐƚŝƚƵƚĂďŝůŝƚLJ
ďĞƚǁĞĞŶ ƚƵŶĂ ĂŶĚ ŵĞĂƚ ƉƌŽĚƵĐƚƐ͘ /ŵƉĂĐƚ ŽĨ ďƌĂŶĚƐ ĂŶĚ ƉƌŝǀĂƚĞ ůĂďĞůƐ͘ /ŶĨůƵĞŶĐĞ ŽĨ ŐƌĞĞŶ
ŝƐƐƵĞƐ;ďLJͲĐĂƚĐŚĞƐ͕ƵƐĞŽĨ&Ɛ͙ͿĂŶĚĞĐŽͲůĂďĞůůŝŶŐŽŶƚƵŶĂĚĞŵĂŶĚ͙
ϭϳ͘ϯϬŶĚŽĨĚĂLJϭ
ϭϵ͘ϯϬ͗ĚŝŶŶĞƌĂƚƌĞƐƚĂƵƌĂŶƚ>ĂŝŐĂůůĞ͕ƉůĂĐĞ'ƌĂƐůŝŶ
ĂLJϮ;&ƌŝĚĂLJƉƌŝůϭϱƚŚϮϬϭϭͿ
ϵ͘ϬϬ :ĞĂŶŶĞ &ŽƌƚŝůƵƐ ;/Z͕ ^ğƚĞ͕ &ƌĂŶĐĞͿ͕ ŚƌŝƐƚŝĂŶ DƵůůŽŶ ;/Z͕ WĂƌŝƐ͕ &ƌĂŶĐĞͿ ĂŶĚ WĂƚƌŝĐĞ
'ƵŝůůŽƚƌĞĂƵ;hŶŝǀ͘EĂŶƚĞƐͿ͗ΗdŚĞŶĞƚǁŽƌŬƐƚƌƵĐƚƵƌĞŽĨƚŚĞŐůŽďĂůƐƵƉƉůLJĐŚĂŝŶĨŽƌƚƵŶĂΗ;ƉĂƌƚ
ϭͬϮͿ
ϵ͘ϰϱŚƌŝƐƚŝĂŶDƵůůŽŶĂŶĚ:ĞĂŶŶĞ&ŽƌƚŝůƵƐ;/ZͿ͗ΗDŽĚĞůůŝŶŐƚŚĞŐůŽďĂůƐƵƉƉůLJĐŚĂŝŶĨŽƌƚƵŶĂ͗
ĨŽƌŵƵůĂƚŝŽŶĂŶĚĨŝƌƐƚƌĞƐƵůƚƐΗ;WĂƌƚϮͬϮͿ
ϭϬ͘ϯϬŽĨĨĞĞďƌĞĂŬ
A-92
ϭϬ͘ϰϱŚƌŝƐƚŝĂŶŚĂďŽƵĚ;/Z͕^ğƚĞ͕&ƌĂŶĐĞͿ͗͞ŽŶƐĞƋƵĞŶĐĞƐŽĨƉƌŝĐĞĐŚĂŶŐĞƐŽŶƚŚĞƐƉĂƚŝĂů
ĚLJŶĂŵŝĐƐŽĨƉƵƌƐĞͲƐĞŝŶĞĨŝƐŚŝŶŐŝŶƚŚĞ/ŶĚŝĂŶKĐĞĂŶ͟
ϭϭ͘ϯϬ 'ĞŶĞƌĂůĚŝƐĐƵƐƐŝŽŶ;ĐŚĂŝƌĞĚďLJĂůĞ^ƋƵŝƌĞƐ͕ED&^ͲEKĂŶĚh^͕h^Ϳ͗
dƌĞŶĚƐŝŶƚŚĞŐůŽďĂůĚĞŵĂŶĚĨŽƌƚƵŶĂ͕ƚƌĞŶĚƐŝŶƚŚĞŵĂũŽƌƚƵŶĂĨŝƐŚĞƌŝĞƐĂƌŽƵŶĚƚŚĞǁŽƌůĚ͕
ďƌŝĚŐĞƐďĞƚǁĞĞŶƚƵŶĂĚĞŵĂŶĚĂŶĂůLJƐŝƐĂŶĚĨŝƐŚĞƌŝĞƐŵĂŶĂŐĞŵĞŶƚ
EĞdžƚ ƐƚĞƉƐ ŽĨ ƚŚĞ /ŵďĞƌͲůŝŽƚŽƉ ƉƌŽŐƌĂŵŵĞ͗ ǁŚĂƚ ƐŚŽƵůĚ ďĞ ĐŽŶƐŝĚĞƌĞĚ ĂƐ Ă ƉƌŝŽƌŝƚLJ
;ĐŽŶƐĞƋƵĞŶĐĞƐ ŽĨ ŐůŽďĂů ĐŚĂŶŐĞƐ ŽŶ ƚƵŶĂ ŵĂƌŬĞƚƐ͗ ĐůŝŵĂƚĞ ĐŚĂŶŐĞ͕ ƚƌĂĚĞ ƉŽůŝĐŝĞƐ͕
ĞŵĞƌŐĞŶĐĞŽĨŚŝŶĂĂƐĂŬĞLJƉůĂLJĞƌ͕ƚŚĞĞĐŽŶŽŵŝĐŝŵƉĂĐƚŽĨƉŝƌĂĐLJ͕ŵĂƌŝŶĞƉƌŽƚĞĐƚĞĚĂƌĞĂƐ
ŝŶ ƚŚĞ ,ŝŐŚ ƐĞĂƐ͕ ƚƵŶĂ ŵĂŶĂŐĞŵĞŶƚ ǁŝƚŚŝŶ ƚŚĞ <ŽďĞ ƉƌŽĐĞƐƐ͕ ƚŚĞ ĂůďĂĐŽƌĞ ĨŝƐŚĞƌŝĞƐ͕ ƚŚĞ
ĞŶǀŝƌŽŶŵĞŶƚĂůďĂŶŽĨ&Ɛ;ƉŽůĞͲĂŶĚͲůŝŶĞƐŽƵƌĐŝŶŐďLJWƌŝŶĐĞƐ͘͘͘Ϳ͍
ϭϮ͘ϯϬ>ƵŶĐŚĂƚ/DEͲ/
&ƌĞĞĂĨƚĞƌŶŽŽŶ
ŝŶŶĞƌĂƚƌĞƐƚĂƵƌĂŶƚ>ĞŽƵĐŚŽŶ͕ϳƌƵĞŽƐƐƵĞƚ͕EĂŶƚĞƐ͘
ĚŵŝŶŝƐƚƌĂƚŝǀĞĐŽͲŽƌĚŝŶĂƚŽƌ͗
ŶŶĞͲůĂŝƌĞŽǀĂŝŶ͕/DEͲ/
ŚĞŵŝŶĚĞůĂĞŶƐŝǀĞĚƵdĞƌƚƌĞ͕ϰϰϯϮϮEĂŶƚĞƐ
dĞů͘нϯϯ;ϬͿϮϰϬϭϰϭϳϰϴ
ŶŶĞͲůĂŝƌĞ͘ŽǀĂŝŶΛƵŶŝǀͲŶĂŶƚĞƐ͘Ĩƌ
ĐĐŽŵŽĚĂƚŝŽŶŝŶEĂŶƚĞƐ
,ŽƚĞů>ĂWĠƌŽƵƐĞ
ϯůůĠĞƵƋƵĞƐŶĞ
ϰϰϬϬϬEĂŶƚĞƐ
ϬϮϰϬϴϵϳϱϬϬ
ŚƚƚƉ͗ͬͬǁǁǁ͘ŚŽƚĞůͲůĂƉĞƌŽƵƐĞ͘Ĩƌͬ
dŽ ƌĞĂĐŚ /DEͲ/͕ ƚĂŬĞ ƚŚĞ dƌĂŵ ũƵƐƚ ŝŶ ĨƌŽŶƚ ŽĨ ƚŚĞ ,ŽƚĞů͕ >ŝŶĞ Ϯ ĚŝƌĞĐƚŝŽŶ ͞KƌǀĂƵůƚͲ
'ƌĂŶĚǀĂů͕͟ƐƚŽƉĂƚ͞&ĂĐƵůƚĠƐ͟ĂŶĚĨŽůůŽǁƚŚĞƐŝŐŶƐƚŽƚŚĞĞƉĂƌƚŵĞŶƚŽĨĐŽŶŽŵŝĐƐ;/DEͿ͘
A-93