Coastal fish resources: the foundation for tourist fishing and related commerce (NFR project no. 173274/S40)
A probability-based survey using self-sampling
to estimate catch and effort in Norway’s coastal
tourist fishery
By
Jon Helge Vølstad, Knut Korsbrekke, Kjell Nedreaas, Merete Nilsen,
Gro Nesheim Nilsson, Michael Pennington, Samuel Subbey
and Rupert Wienerroither
Institute of Marine Research
P.O. Box 1870 Nordnes
5817 Bergen, Norway
A project supported by The Norwegian Research Council
(Project number 173274/S40)
2
Table of contents:
Abstract .................................................................................................................................. 5
1
2
Introduction .............................................................................................................................................. 7
1.1
Background .................................................................................................................. 7
1.2
Political considerations .............................................................................................. 10
1.3
Management and social issues ................................................................................... 11
Material and methods ........................................................................................................................ 13
2.1
Defining the target and study population of fishing tourists ..................................... 13
2.2
Developing the survey design and sampling plan ..................................................... 14
2.3
The Pilot Study .......................................................................................................... 14
2.4
The 2009 National Survey of Catch and Effort ......................................................... 17
2.5
Quality Control and Quality Assurance (QA/QC) .................................................... 19
2.6
Survey design and analytical methods ....................................................................... 20
3
Results ...................................................................................................................................................... 23
4
Discussion ............................................................................................................................................... 27
4.1
General comments and comparison to prior studies .................................................. 27
4.2
Sources of bias ........................................................................................................... 29
4.3
Improving accuracy ................................................................................................... 30
Acknowledgements .............................................................................................................. 33
References ............................................................................................................................ 34
Tables ................................................................................................................................... 37
3
Figures .................................................................................................................................. 44
Appendices ........................................................................................................................... 57
List of appendices
Appendix 1. Daily catch diaries forms ..................................................................................... 57
Appendix 2. Form for registering boating activity (e.g. group 1). ........................................... 60
Appendix 3. Questionnaire used by the Norwegian Coast Guard to classify fishing tourists
and recreational anglers. ........................................................................................................... 61
4
Abstract
Recreational fishing as tourism has become an increasingly important part of the Norwegian
travel industry and may account for a significant portion of the fishing mortality of local fish
stocks. In this study, we evaluated the use of a probability-based sampling survey to estimate
yearly catch and effort taken by boat anglers associated with 445 registered tourist fishing
businesses that we were able to identify. From a stratified random sample of businesses,
fishing tourists were recruited every 6th week (with a random start) and asked to record their
catch and effort in catch diaries. This report documents methods and results of a survey
conducted in 2009. Estimated species composition and catch-per-unit of effort for
commercially important species by region were judged to be credible. Atlantic cod (Gadus
morpha) dominated the catches in northern Norway, while saithe and mackerel were the most
common species caught in western and southern Norway. We estimated that the total catch of
all species taken by tourist fishers in the business sector during 2009 was 3.3×103 metric tons
(RSE=17%), and that 1.6 ×103 metric tons (RSE =22%) of cod were caught overall. Most of
the cod (1.58 ×103 metric tons, RSE= 22%), was caught north of 62°N. We conclude that selfreporting can provide reliable data on catch per unit effort (CPUE). The estimation of total
effort proved more challenging and requires independent data collection that complements the
catch diary data. Survey methods that are applicable to cover the informal sector of tourist
fishing are discussed. Choice of survey methods are limited because no complete registry of
businesses catering to fishing tourists exists. Conducting a cost-effective survey of the entire
tourist fishery is also made difficult by Norway‟s intricate coastline that extends over 25,000
km, which does not include the shores of islands, the diverse assortment of fishing activities,
and the lack of a comprehensive sampling frame. No license is required for tourists fishing in
Norway‟s coastal waters. The lack of a tracking tool means that foreign fishing tourists cannot
be contacted to conduct a random telephone interview survey.
5
6
1
Introduction
1.1 Background
Norwegian coastal waters contain plentiful and valuable resources that contribute to the well
being and economy of the people living along the coast. Recreational fishing is a popular
leisure activity, and some studies have suggested that about half of the adult population goes
fishing at least once during a year. Recreational fishing has been defined as the utilization of
fish resources for personal consumption and/or recreation (Hickley and Tompkins, 1998).
Marine recreational fishing in Norway is subject to few regulations. In particular, marine
recreational fishing does not require a fishing license and consists of; fishing with rod and
reel, hand-line, machine driven handline, long-line, gill net, pots, and other gears (EEA,
2004). No bag-limits (Pollock et al., 1994) are in effect, and legal size limits were only
introduced in the recreational fishery in 2010 and only for selected species1. Foreign tourists
may only bring home 15 kilo of filet and may only use handheld tackle when fishing in the
sea, while Norwegians and legal residents are allowed to use pots, nets, long-lines or similar
gears and may even sell their catch2.
Marine recreational fishing is a rapidly growing part of the nature-based tourism industry in
Norway and may account for a significant portion of the fishing mortality for some local fish
stocks. Not taking into account the contribution of recreational fishing and angling to the total
fish harvest could have severe consequences for economically and ecologically important fish
stocks (Cooke and Cowx, 2004; 2006). Marine tourist fishing has become an increasingly
important part of the Norwegian travel industry and is a significant component of the local
economy (Borch, 2009), In particular, the number and quality of fishing camps along the
coast were greatly improved and now provide a full range of services including
accommodation, boats, guided tours and fish processing facilities (Borch, 2004). To secure
the sustainability of this business, it is necessary to quantify the effect this fishery has on
coastal stocks. Of particular concern in recent years is the decline of the coastal cod (Gadus
1
http://www.fiskeridir.no/english
2
http://www.fiskeridir.no/fritidsfiske
7
morhua) stock (ICES, 2009; 2010). Without reliable estimates of total catches, including
catches taken by recreational fishers and fishing tourists, it is impossible to assess or manage
any fishery (see, e.g., Pollock et al., 1994; Reid and Montgomery, 2005).
Total reported catches of coastal cod in the commercial fishery from 2004-2008 has ranged
from 22 434 metric tons to 25 777 metric tons. In 2010, the Ministry of Fisheries and Coastal
Affairs allocated a quota of 7000 metric tons of coastal cod to the recreational fisheries
(Figure 1). At present there are no precise and unbiased statistics on the recreational fishing
effort along the coast of Norway in general or on how much and which species were caught.
Hence, it is not possible to assess accurately if the catches of coastal cod by recreational and
fishing tourists are adequately accounted for by the dedicated quota.
In this study, we estimated the catches of cod and other important species taken by fishing
tourists that rent accommodation through the tourist fishing businesses along the coast of
Norway (Figure 1). A tourist fishing business was defined as an enterprise renting out rooms,
boats for recreational fishing at sea, or a cabin rented by fishing tourists through a registered
business. The business sector of tourist fishing depends on the coastal fisheries resources just
as commercial fishers do. There are several definitions of fishing tourism in the general
literature (Ditton et al., 2002). Borch (2004) define a fishing tourist as anybody that is
“traveling from home to stay overnight to take part in fishing for recreational purposes”.
Fishing tourists as defined here include non-residents as well as Norwegians and legal
residents. We decided not to include Norwegians and legal residents who stay in their second
home in the fishing tourist group, but rather to include them in the recreational fishers‟ group.
The tourist fishing business mainly attracts foreign anglers, but also a number of fishers that
are legal residents who primarily use hand held tackle. Recreational fishing conducted by all
fishing tourists is referred to as the tourist fishery throughout the report. The term angling is
applied to recreational fishing involving the use of a hook only (on either rod or hand-held
line) (Pawson et al., 2008).
We grouped fishing tourists and recreational fishers into sectors based on how they could be
accessed for catch sampling, interviews, or to recruit them for participation in catch diary
programs. For the business sector of the tourist fishery, a list of businesses was constructed
and used as a sampling frame to gain access to fishers and then collect data through face to
face interviews, or ask them to report their daily catch and fishing effort in diaries. For this
sector, access- intercept surveys (Pollock et al., 1994; Pollock et al., 1997) may be employed
8
to estimate catch and effort. It is more difficult to gain access to fishers in the informal tourist
fishery, or the entire group of recreational fishers. These fishers are distributed along the
entire coastline, and their fishing trips are not limited to defined ports, boat ramps, or marinas
like in some countries. More than 80% of the population in Norway lives within 10 km of the
coast, and a large portion own homes or second homes that have docking for private boats.
Hence, recreational fishers generally embark and return to their private property, and cannot
easily be intercepted for interviews and catch sampling. A large portion of the recreational
fishers, and fishing tourists that are legal residents may, in principle, be contacted by phone,
while foreign fishing tourists will not, of course, be listed in the Norwegian phone directory.
Earlier studies of marine tourist fisheries in Norway (Hallenstvedt, 2001; Hallenstvedt and
Wulff, 2001; Cap Gemini Ernst &Young, 2003; Jacobsen, 2005) have indicated that the total
catch by fishing tourists ranges from 6000 metric tons to 15000 metric tons. Hallenstvedt and
Wulff (2001) estimated that the total catch of all species taken by recreational fishers staying
at tourist fishing businesses caught 4413 metric tons of fish. Estimates in Hallenstvedt and
Wulff (2001) were mainly obtained by combining daily catch rates observed in regional sports
fishing competitions with estimates of total effort for different segments of the tourist fishery,
based on searches on the internet, interviews of selected businesses, questionnaires and
professional judgment. Maske (2005) reviewed prior studies and concluded that the estimated
catches by fishing tourists account for only 2-5 % of the total coastal cod catches. However,
she concluded that the accuracy of available estimates was not sufficient to exclude the
possibility that fishing tourists might have had a negative impact on the recruitment of coastal
cod in some areas along the Norwegian coast. None of the earlier studies have included
collecting data on the catch by species taken by fishing tourists as was done in our study.
Hallenstvedt and Wulff (2004) estimated that the total catch taken by Norwegian recreational
fishers (excluding foreign fishing tourists) in 2003 was approximately 10 000 metric tons
(round weight) in each of the regions in eastern Norway, western Norway and mid-Norway
(Møre and Romsdal, south Trøndelag, north Trøndelag); and 18 000 metric tons in northern
Norway (Nordland, Troms, Finnmark); altogether 48 000 metric tons. These estimates were
based on various methods including telephone interviews where recall bias (e.g., Connelly
and Brown, 1995; Tarrant et al., 1993; National Research Council, 2006) is an issue.
Although this fishery may be considered rather stable, a proper statistical assessment is
necessary to get an accurate estimate of the total catch. Quantifying this component of the
Norwegian recreational fishery was not part of the current project.
9
Studying and quantifying Norway‟s recreational fisheries in general is made difficult by
Norway‟s intricate coastline that extends over 25 000 km not including islands, the diverse
assortment of fishing activities, and the lack of a comprehensive sampling frame (Cochran,
1977). The total marine recreational fishery in Norway can be grouped into several segments
based on how fishers can be contacted to obtain data on their catch and fishing effort (Figure
1). For this study we developed methods to estimate total catch by species taken by fishing
tourists associated with tourist fishing businesses. The informal tourist fishing sector was
excluded for cost reasons.
1.2 Political considerations
In the protocol from the 33rd session of the Norwegian-Russian Fishery Commission
(October 2004), Norway and Russia agreed to exchange information annually on the
recreational and tourist fishery in their respective economic zones. It is important that Norway
fulfills this commitment and designs and establishes routines for providing such information.
The present project developed appropriate statistical methods and reporting procedures for
meeting this requirement.
The Norwegian government (“Stortinget”) desires to make tourist fishing a significant
component of the tourist industry in Norway3. To achieve this goal, the Government will
ensure that tourists can fish along the Norwegian coast and regulate the fishery so that it is
sustainable. In addition, several new laws and regulations have recently been introduced (for
example the Marine Resources Act) to ensure the sustainable utilization of coastal resources
and to prevent unnecessary conflicts among stakeholders. Good regional knowledge about
species composition, size and seasonal variation is crucial to manage resources in a
sustainable way, to obtain a sound balance between resources and harvest, and to formulate
laws and regulations that fit the actual conditions along the coast.
It has been argued that the economic impact worth generated by a fish caught by a tourist is
ten times higher than when caught by a commercial fisher (Cap Gemini Ernst &Young,
2003). Motivated by this observation, the Ministry of Fisheries and Coastal Affairs has
3
„Stortingsmelding no. 19‟ (Report number 19 from the Storting), March 2005.
10
suggested recently that it may be advantageous to assign part of the Norwegian commercial
quota to tourist fishing companies. Clearly this proposal should not be put into operation until
a proper sampling program of the catch by the fishing tourists is in place. In 2010, the
Ministry of Fisheries and Coastal Affairs allocated a quota of 7000 metric tons of coastal cod
to the marine recreational fisheries (Figure 1.) To assess if the total catch in the marine
recreational fishery is within this quota it would be necessary to quantify the catches taken by
fishing tourists as well as recreational fishers.
1.3 Management and social issues
The Norwegian coastal waters are a series of varied ecosystems. Therefore, it is crucial that
regulations are based on data appropriate for each distinct ecosystem. The project collected
data throughout the year, and therefore we now have some regional and seasonal insights that
may contribute to plans that will appropriately manage local resources and provide
information on oceanic stocks that seasonally inhabit some coastal regions. We worked,
together with local fishers, tourists and tourist fishing companies, to characterize the various
coastal societies and industries, which should provide managers with relevant information on
the status and use of marine coastal resources.
Tourist fishing is currently a high profile and contentious issue in Norway that has been
extensively debated on radio and television, in newspapers and within political circles. The
debate centers on the optimum use of coastal fish resources, which sets local inhabitants and
professional fishermen against the fishing tourists and related businesses. In particular, the
commercial fishing industry feels that the increasing tourist fishing business trade will result
in local declines in abundance and ultimately in more restrictive regulations.
Precise and reliable statistical data are a necessary starting point for reducing such conflicts
among stakeholders in the coastal zone (a sub-program in “Havet og kysten” is “Management
and conflict solving” no. IV). The Norwegian Research Council (NRC) sees a need for more
and better information on the coastal system to mitigate conflicts among stakeholders. The
present project in conjunction with a complementary study of socio-economic effects4 of the
4
http://www.norut.no/tromso_en//Norut/Nyheter/Nyhetsarkiv/Sjoefisketurisme-i-tall
11
tourist fishery conducted by the Northern Research Institute (NORUT) provides data that are
critical for resolving such conflicts. The NRC further states in its description of the „Havet og
kysten‟ program that in addition to having a sustainable management regime, it is important to
distribute the resource among coastal stakeholders in a way that is equitable, cost efficient and
optimizes the benefits derived from the resource.
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2
Material and methods
2.1 Defining the target and study population of fishing tourists
The target population for this study was all recreational fishers that rent lodging and boats
from a tourist fishing businesses (see Figure 1.) The major objective was to estimate the
number and weight of the landed catch by species for boat anglers in the business segment of
the tourist fishery. Fishing from shore was considered to contribute marginally to total catches
of this segment and was not included in the study. In practice, not all elements (business
units) in the target population of all businesses may be accessible for sampling. Our sampling
frame was based on a list of businesses that could be sampled with known probability. The
frame should ideally include the entire population of tourist fishing businesses, but these
cannot easily be identified from the national business registry. Hence, not all fishing tourists
in the business segment were accessible for sampling. We developed a well defined study
population (Cochran, 1977; Jessen, 1978; ICES, 2009) that comprises as much of the target
population as we could locate. A list of tourist fishing businesses was developed by the
Institute of Marine Research (IMR) in collaboration with the Northern Research Institute
(NORUT), the Norwegian Hospitality Association („NHO Reiseliv‟), the travel operator Din
Tur5 and through an internet search (Table 1). NHO first provided the list of tourist fishing
businesses in their registry. This list of businesses was adjusted after all firms had been
contacted to verify that they catered to fishing tourists. Also, the number of rental boats was
recorded for nearly all businesses. The study population was the fishing tourists that rent
accommodation in the 445 registered businesses in our data base (Figure 1). A data base with
only confidential information was developed in collaboration with the Norwegian Marine
Data Centre (NMD) at the IMR. The data base includes information about tourist fishing
businesses identified in the search, including capacity (number of beds), number of rental
boats, and length of season. The data base also includes catch reports and the number of boat
rental days for each firm.
5
http://www.dintur.no/home.aspx
13
2.2 Developing the survey design and sampling plan
It would be unreasonably expensive to contact and interview every fishing tourist (that is,
conduct a complete census) or even to visit every tourist business where the fishery takes
place on representative days selected throughout the year. Therefore we developed a sampling
scheme to quantify and assess the tourist fishery (Cochran, 1977; Pollock et al., 1994). The
choice of survey methods was limited because no complete registry of businesses catering to
fishing tourists exists. Our survey design incorporated important aspects of survey planning
identified by Särndal et al. (1992) and guidelines for designing recreational fishery surveys
given by WKSMRF (ICES, 2009).
The National Research Council of the U.S.A. provides a thorough review of the NMFS
recreational fishery survey with recommendations for survey designs, and concluded that
recreational surveys in the US may be the most complex national surveys currently
conducted. (National Research Council, 2006).
Because of Norway‟s long and intricate coastline and the large number of tourist fishing
businesses, we determined that the most feasible sampling plan for estimating catch and effort
in Norway‟s coastal tourist fishery would involve representative sampling of businesses and
time periods, combined with self-sampling by fishing tourists. The sampling plan is a form of
access-point survey (Pollock et al., 1994; Vølstad et al., 2006), and involved a scheme for
selecting tourist fishing businesses and dates when daily catches by tourists would be
recorded in catch diaries. Representative sampling from a frame of businesses/days was done
by selecting a stratified random sample of tourist fishing businesses as the primary sampling
units (PSU). Within selected PSUs and time periods, all fishing tourists were asked to record
data on their daily catch and fishing effort in catch-diaries. This type of sampling of fishery
catches is known as cluster sampling (e.g., Cochran, 1977; Levy and Lemeshow, 1991;
Lehtonen and Pahkinen, 2004), where it is usual that the variability in catches within a PSU is
less than variability between all catches. The sampling design involved multi-stage sampling
such that there was a hierarchy of sampling decisions.
2.3 The Pilot Study
The feasibility of recruiting fishing tourists to report data on their daily catch and effort was
tested on a small scale in collaboration with some tourist fishing businesses in Øygarden,
14
which is outside Bergen, during the summer of 2007. Daily catch diary forms were developed
(Appendix 1) and tested. We determined that it would be most practical to distribute catch
diaries to each rental unit when tourists arrived. The tourists in each rental unit were then
asked to record in diaries their daily effort (number of boats rented and number of fishers) and
the number and total round weight of fish kept. A larger pilot study was conducted in 2008 to
test the adequacy of the design of the catch diaries and of the sampling protocols for a wider
range of businesses and to gain information for developing a national survey of the business
segment of the tourist fishery. A total of 85 tourist fishing businesses were selected from
clusters within geographic areas along the coast in order to keep the travel and time expense
low. Norwegian Hospitality Association (NHO Reiseliv) provided lists with an overview of
businesses that could be interested in the tourist fishing project, together with a list of
members that rent out fishing boats. Din Tur provided complete contact information for their
members.
A total of 85 tourist businesses were contacted by mail and phone, of which 67 (Figure 2),
from a total of 11 counties, agreed to join the project (which is a respectable response rate).
The businesses were asked to recruit fishing tourists to report on their daily catch and effort
during the main fishing season. Recreational fishers arriving within a given week were given
a catch diary and an information brochure. Catch diaries were collected at the end of their
stay, and the catch diaries were returned to IMR by mail. During the pilot study, the
recreational fishers were asked to report the number and total weight of all species caught
during their stay. In addition, 51 out of 67 businesses were visited to assess the quality of the
catch reports and collect information about the tourist fishing businesses. A total of 816 catch
diaries were received from 39 businesses. Typically, each group of fishing tourists rent
accommodation for about one week, and thus a catch diary represents 5-7 days of fishing.
During the pilot study, all businesses in the study frame were contacted in order to categorize
them as a tourist fishing business or as a provider of information about tourist fishing. A
tourist fishing business was defined as a business renting out beds and boats for recreational
fishing at sea. The data base contains contact information for 445 tourist fishing businesses,
which had an estimated 2393 boats available for rental (Table 1).
15
A web-based reporting system was developed during 2007-2008 and tested in the pilot study.
A consulting company was contracted to assist the IMR in developing a reporting system
implemented in the Norwegian Official Web Portal Altinn6. Altinn is widely used in Norway
to report business statistics and also by the public to provide tax information to the Internal
Revenue Service. We asked selected business owners to use the Altinn system during the pilot
study to report aggregate data on catch and effort from catch diaries provided by tourist
fishers. The feedback from business owners suggested that data registration forms developed
in Altinn should be modified before such a system could be used for reliable and easy
reporting. Such modification includes forms that allow daily catch and effort data as reported
by the fishing tourists to be entered and not aggregate data. The forms in Altinn should be
modified to match the catch diaries, because it was too demanding for the volunteer business
owners to aggregate data. Also, our inspection of more than 800 diaries from the pilot studies
suggested that the diaries provided by fishing tourists should be proofed by fishery biologists
as part of the Quality Assurance/Quality Control (QA/QC). In some cases, for example, it was
apparent that fishing touristss had provided the average weight of fish caught rather than the
total round weight as requested. Such errors would not have been discovered and corrected if
only aggregated data were recorded. To enable a national survey in 2009 with sufficient
sample sizes to estimate the total catch of cod and other key species, it was determined to
simplify data reporting by providing pre-paid envelopes to collaborating businesses in which
to send their diaries to the IMR. The reporting system developed for Altinn, nevertheless, has
promise, and if modified it may be used in the future for reporting catch and effort data from
tourist and recreational fisheries.
During the pilot study we also solicited help from the Norwegian Coast Guard to collect data
on recreational fisheries as part of their routine inspection of leisure boats at sea. The Inner
Norwegian Coast Guard (Den Indre Kystvakt) records for each boat inspected; the number of
anglers, time and position of the boat, citizenship of the anglers, and their choice of
accommodation (see Figure 1 for the segments). These data should over time provide a basis
for mapping the relative fishing effort by recreational and fishing tourists and the fraction of
all foreign tourists that are in the informal sector versus the business sector. The number of
fishers that live at home (or in their own 2nd home) versus the number that rent
6
https://www.altinn.no/en/
16
accommodations would provide an indication of the effort in the tourist fishery versus the
Norwegian recreational fishery. In addition, the fraction of fishing tourists that rent rooms at
collaborating businesses would be valuable information.
The Norwegian Coast Guard vessel KV Garsøy7 (34 m length overall) tested the use of a
questionnaire (Appendix 3) in Øygarden, Hordaland County. During one day, 20 boats were
inspected by Norwegian Coast Guard staff using a smaller boat launched from KV Garsøy.
Two scientists from the IMR participated in the operation as observers. All but one of the
boats inspected were rented by German anglers that stayed at tourist fishing businesses in the
area. A routine that worked well for the crew on KV Garsøy was to use a plastic laminated
form (Appendix 3) to register data from interviews in the field and to enter these data into
Excel spreadsheets when returning to the main vessel. The data could then be emailed to IMR.
These results were encouraging, and demonstrated that the Norwegian Coast Guard could
play an important role in the mapping of recreational fisheries as part of their routine
operations.
2.4 The 2009 National Survey of Catch and Effort
A national survey to estimate catch and effort in the business segment of the marine tourist
fishery in Norwegian coastal waters was conducted in 2009. Catch and effort data were
provided by fishing tourists from a representative sample of tourist businesses and time
periods over the year. Based on lessons learned from the pilot study, we determined that it
would be a burden for collaborating businesses to voluntarily administer a self-sampling
program where catch diaries are filled in by all fishing tourists during the entire season. We
therefore modified the sampling plan to include representative sampling of weeks throughout
the year when each business should administer fishing tourists‟ catch diaries. For a stratified
random sample of businesses, fishing tourists were recruited every 6th week (with a random
start) to record their catch and effort in catch diaries. Recreational fishers renting boat(s) and a
cabin/apartment entered information about their daily catches and fishing effort during their
stay. The businesses were also asked to enter information about boat rental days (Appendix 2)
to provide independent information on effort.
7
http://www.mil.no/sjo/kv/start/fartoyene/article.jhtml?articleID=156024
17
Our goal was to recruit 107 businesses for the 2009 national survey. We maintained 30
businesses from the pilot study (spread out by size, and geographically) and selected 77 new
businesses by stratified random sampling. All businesses in our sampling frame were sorted
by county and further divided into two categories; group 1 (≤ 3 boats) and group 2 (> 3 boats).
The businesses in each county and group were arranged randomly on a list and contacted by
phone sequentially until we had recruited the desired number of businesses in each category.
The target sample size of businesses in each stratum was approximately proportional to
stratum size. A total of 182 tourist fishing businesses were called, and altogether 97
responded and agreed to join the project (Figure 3). At the end of the 2009 season, six of these
businesses had to withdraw from the project due to special circumstances.
For each collaborating business, daily catch diaries filled in by fishing tourists were requested
for every 6th calendar week (with a random start) throughout the year. A few businesses chose
to collect data throughout the whole fishing season (i.e., a census). For the main project, most
of the new recruited businesses were requested to solicit daily catch reporting by tourists and
only record the number of fish caught by species. This was done to ease the task and to
encourage more fishing tourists to report their catches. At 44 businesses the fishing tourists
were asked to report the total catch of each species by weight and number, while at 53
businesses the fishing tourists reported only the number of fish caught. The diaries also
included records of fishing effort, number of boats rented and number of fishing tourists. The
business reported how many boats they had available and how many boats were rented out.
Based on careful examination, data from 51 businesses (605 catch diaries) were deemed
sufficiently reliable to be included in the analysis.
Data on the weight of catches by species were not provided by some collaborating businesses
during the 2009 season. Length measurements from the catches of saithe, cod and halibut
were provided by a limited number of these businesses (7). Data were collected to estimate
the average weight using length-weight relationships. One person working at the tourist
fishing business was responsible for measuring fish during the reporting week and was paid
1000 NKR per week as compensation. The estimated weight in combination with the number
of fish caught was used to estimate the weight of total catches of saithe, cod and halibut taken
by fishing tourists at these businesses. Measurements of a minimum of 25 fish of each species
were marked on waterproof measurement sheets that were then sent back to IMR.
18
The Norwegian Coast Guard continued to collect data on recreational anglers in 2009,
reporting information on the nationality, number of anglers, and their choice of
accommodation. This information‟s intended use was to estimate the ratio of fishing tourists
relative to recreational fishers. In conversations with the Norwegian Coast Guard, and from
observing their sampling routines at sea during a cruise in summer of 2009, it became
apparent that the Norwegian Coast Guard primarily collected data from boats with anglers
that were perceived to be foreign tourists and not from Norwegian recreational fishers. Due to
this biased selection, the data could not be used as intended. The sampling routines have been
improved to eliminate such bias, and continued data collections should provide estimates that
can be used to evaluate the relative magnitude of tourist and recreational fisheries.
2.5 Quality Control and Quality Assurance (QA/QC)
Biologists and field technicians from the IMR visited selected businesses along the coast
during the pilot study and the main study to assess and ensure the quality of self-reported data
on catch and effort provided by fishing tourists and to inform fishers about the project.
Information about the project was also provided via the web8, through television (e.g., TV2
News, “Lørdagsrevyen”), by distributing brochures in German, English, Russian, Polish,
Czech and Spanish, and by providing posters to all collaborating businesses that explained
procedures for filling in catch diaries in detail. Posters of commonly caught species were also
provided to businesses to help fishing tourists with species identification.
During the pilot study, 51 of 67 businesses were visited to assess the quality of the catch
reports and collect information about the tourist fishing businesses. A total of 70 businesses
were visited by IMR staff during the main study conducted in 2009 as part of the QA/QC; at
50 newly recruited businesses the focus was on instructing the business owners on how to run
the self-sampling program. The 15 businesses recruited to do length sampling were visited to
demonstrate methods (7 of these managed to provide length-data as requested).
A more comprehensive QA/QC study was conducted in Hordaland to assess information
concerning the species identification by fishing tourists. Eight fishing resorts were repeatedly
8
www.imr.no/turistfiske
19
visited by an expert taxonomist over the course of two and a half months during summer
2009. During these visits the ability of fishing tourists to identify species was evaluated by;
(1) identifying their own catch and; (2) asking them to identify 17 different species based on
photos. These 17 species were selected based on observations of the recreational fishery in
Hordaland County during the 2008 Pilot Study. In total 42 groups of fishers (“boats”) were
interviewed over time. Of these, 33 had caught fish on the selected days, so that it was
possible to inspect their catch and check their species identification. For 30 inspected trips, a
sub-sample of 42 angles was asked to identify the species based on photos shown to them.
All the catch diaries were entered into the data base and checked for outliers. Only forms that
were deemed reliable were included in the analysis. Businesses that had not followed the
sampling schedule were excluded.
In the spring of 2010, 24 business owners that provided data in 2009 attended a 2-day
workshop at IMR to discuss the project. Sources of bias in catch reporting and issues of nonresponse were discussed. The general consensus was that the reports in catch diaries were of
good quality.
2.6 Survey design and analytical methods
The survey involved two-stage sampling where:
1. A stratified sample of businesses (PSUs) was selected in the first stage.
2. A census or a random systematic sub-sample of reporting weeks (every 6th week with
a random start) was selected for each PSU.
We assumed that the businesses in our sample provided reliable data on catch and effort and
were representative, even though the non-response rate for the businesses contacted by phone
was about 50%. We also assumed that all active fishing tourists staying at a selected business
during the reporting weeks provided accurate catch diaries during their stay. Estimates of total
catch by species and stratum were based on standard estimators for cluster sampling (Hansen
et al., 1953; Cochran, 1977; Wolter, 1985; Vølstad et al., 2006). Total catch for each tourist
fishing business in the sample was obtained by extrapolating the average catch per reporting
week to all weeks, except for the businesses where total catch was based on a census. The
mean total catch for all businesses in the sample (PSUs) was then extrapolated to all
20
businesses in the sampling frame. The variance was computed from the primary sample, i.e.
the variation in estimated total catch by all fishing tourists for each tourist fishing business in
the sample (see Cochran, 1977, p 279; Pollock et al., 1994, p. 42; Vølstad et al., 2006,
Williams, 2000). Because the sampling fraction at the primary level was small (~10%), the
bias in the variance estimates were insignificant and tended to be slightly positive (Wolter,
1985, p. 34), and thus provided conservative variance estimates. Estimates of means and totals
along with their associated standard errors across strata were based on standard stratified
estimators (Cochran, 1977). We have also provided the relative standard error (RSE) as a
measure of precision (Jessen, 1978.) The RSE (often referred to as the proportional standard
error) expresses the standard errors as a proportion or percentage of the catch estimates,
We used a generalized linear model (GLM) with region and month as factors to estimate
mean weight per fish by species for each stratum. For catch diaries in which only the number
of fish by species was recorded, we imputed the missing weights for each species by
multiplying the reported number of fish caught by the estimated mean weight from the GLM.
21
22
3
Results
A summary of the number of tourist fishing businesses and rental boats documented in 2008
is in Table 1. This list of businesses formed our sampling frame from which a sample of
businesses was selected in 2008 and 2009. The geographical location and distribution of
businesses in our sample for 2008 and 2009 is shown in Figure 2 and Figure 3, while Figure 4
and Figure 5 display the species composition of the reported number of fish caught in 2008
and 2009 for northern, mid, western and southern regions of Norway. The results presented in
Table 1 show that about 73% of approximately 2400 boats in the sampling frame belong to
northern and mid-Norway regions. For this particular region, there was an almost equal split
in rentals between businesses with more than 3 boats and those with fewer than 3 boats. This
was slightly different in the western and southern Norwegian regions, where businesses with
more than 3 boats for rental constitute about 62% of mapped businesses.
A total of over 800 diaries with daily catch and effort data were received during the 2008 pilot
study, representing more than 5000 days of fishing by boats (Table 2). During 2009, we
received catch and effort data from more than 600 completed diaries (Table 3), representing
more than 4000 days of fishing by boat. Although the sub-sampling of weeks within each
business in the sample (PSU) for catch and effort reporting implemented in 2009 resulted in
fewer catch diaries than for 2008, the effective sample size (Kish 1965; 2003; Pennington and
Vølstad, 1994) for estimating total catch was increased because of the larger sample of
businesses (PSUs).
The estimated total catch by number and weight for the nine species named in the catch
diaries (see Table 4 and Table 6) show that cod and saithe dominated the catches reported by
fishing tourists via the diaries in the mid-northern Norway (north of 62°N) while saithe,
mackerel, and ling were the most frequently caught species south of 62°N in 2008 and 2009
(Figure 4, Figure 5). The estimated species composition by weight for 2009, for the 9 species
listed in the catch diaries (Figure 6), showed that for the most part cod were caught north of
62°N, while saithe accounted for the highest portion of the catches by weigh south of 62°N.
The histograms in Figure 7 and Figure 8 are pictorial representations of the statistics in Table
4 and Table 6. A significant feature, which is common to Figure 7-8 show the log-normal type
distribution of catches for all the species. This is perhaps indicative of unbiased reporting
across all 9 species listed in the catch diary, which also affords some degree of credibility to
the reported catch statistics. Table 7 lists infrequently caught species that were registered ad23
hoc under „other species‟ in the diaries. These were not included in catch estimates by number
and weight because the catch statistics on these species have not been standardized across
business units. A target-specific sampling strategy is required to obtain reliable statistics on
rare species. The importance of Table 7 lies in the documentation of occasional catches of
species that are likely to be caught in Norwegian Coastal waters.
A strong underpinning of the statistical analysis presented in this report was the ability of the
fishing tourists to consistently and correctly identify different fish species, and in particular
the 9 species listed in the catch diaries. The results obtained from data collected via selfsampling show that fishing tourists‟ knowledge of the most important fish species in
Norwegian coastal waters can be considered to be very good. Approximately 98 % of all
specimens in catches inspected by our expert taxonomist were identified correctly (Table 8).
Only two specimens of saithe (Pollachius virens) and pollack (Pollachius pollachius) have
been confused with each other. The less commonly caught species (Sebastes viviparus and
Trisopterus minutus) were correctly identified to a lower taxonomic level (corresponding
genus level): Single specimens of Labrus bergylta and Hyperoplus lanceolatus were either
identified incorrectly or not at all. The catch of these species were however rare, and these
catches were not included in the statistics because of the potential bias due to catch reporting
and species identification. Good species knowledge was also demonstrated when species
identification was based on photographs. Similar to Table 8, results in Table 9 indicate good
knowledge of commonly caught fish species. When misidentifications or missing answers
occurred, respondents often explained their mistakes by „I know this species when I get it, but
it looks different in the photograph‟ or „I‟ve never caught this species on the hook‟. Such
answers indicated that while their catch was of primary interest, there was also a strong
interest in correct species identification.
Analysis of the self-reported data indicates that the daily total catches per boat were highly
skewed (Figure 11), with catches from 0-20 kg (10kg mid-point) per boat-day dominating in
2009. Since fishing tourists typically stay one week fishing, a common weekly catch would be
at least 70 kg per group of anglers. This result must be considered against the background that
there was no limit on how much a fishing tourist could catch per boat-day. Hence the skewed
distribution observed in Figure 11 might be a realistic representation for the distribution of
CPUE, with little evidence of censorship.
24
The results were based on total catch in weight and numbers and mean weight of all (9)
species that were listed in the standard catch diaries and summarized in Table 2. Attempts
were made to quantify the estimated monthly total catch per boat-day for these 9 species using
a generalized linear model (GLM), which is a flexible generalization of ordinary least squares
regression. In this application, the linear model was related to the response variable (monthly
total catch per boat-day) via a link function, which allowed the magnitude of the variance of
each measurement to be a function of its predicted value. Based on the nature of the data and
pre-modeling analysis, the two factors included in the estimation process were region and
month. The GLM results indicated that the mean catch by species per boat per day (CPUE)
during the 2008 pilot could not be reliably estimated by region and quarter (Table 4) because
of insufficient effective sample sizes. For commonly caught species, such as cod and saithe,
reasonable estimates of CPUE by region were obtained for the main fishing season with
highest catch rates in the north (Table 4). For the 2009, mean catch per boat per day across
species (Table 6; Figure 9) are similar, with highest catch rates in the northern region (Figure
10), while the mean number of tourist anglers per boat was fairly stable over the season in
2009; with 2-3 fishers per boat on a typical fishing day (Figure 12). The GLM results indicate
that the overall total catch of the 9 species was estimated to be 3.34×103 metric tons, with
95% confidence limits 2.22×103 - 4.46×103 metric tons (Figure 9). The total catch of cod was
estimated to be 1.62×103 metric tons, with 95% confidence limits 0.99×103 - 2.30×103 metric
tons (Table 2; Table 6).
Fisher behavior (e.g., dedication to angling, fishing intensity and engaging in other tourist
activities other than fisheries) may also affect the catch per boat-day, and explain why there is
no uniform trend in the mean catch per boat-day, across all regions (Figure 10). Some other
peculiar geo-regional factors may also explain the variation in catch rates. For instance, the
midnight sun in northern Norway (which lasts from May to July in, e.g., Tromsø) may
account for higher fisher activity during this time of the year. Combining this information
with knowledge about the higher number of fishers per boat-day can help explain the upward
trend in Figure 10 for the Northern region. An explanation of the continued increasing catch
rates in the northern region after July, however, is beyond the scope of the present study.
25
26
4
Discussion
4.1 General comments and comparison to prior studies
A key goal of this study was to show that it is possible to develop a quantitative framework
for estimating the total catch by the business sector in the Norwegian the tourist fishery. The
report also demonstrates that necessary data on the fishery can be acquired directly from
businesses, which form access-points that can be representatively sampled through time. Our
study also demonstrates the feasibility of combining probability-based sampling of businesses
in which fishing tourists report on their daily catches via catch diaries. This report presented
specific results and recommendations based on a cost-effective framework. Although length
data were collected for some species, the data do not support reliable estimates of the length
distribution of catches. The length collections in 2009 were primarily conducted to estimate
weight of the catches for selected businesses. The estimated average live weight of cod caught
by tourists in the middle and northern regions of 3.0 kg is very likely and reasonable when
compared to the observed average weight of about 2.0 kg for the entire coastal cod stock in
the same region during scientific surveys in 2008-2009, and about 4.0 kg as the average
individual weight of coastal cod in the commercial catches (ICES 2010). Biological data
collections from the tourist fishery have been expanded in 2010 to provide estimates of the
size and age distribution of the catches of coastal cod to support stock assessments.
Our total catch estimate does not significantly differ from the point estimate (4.4 ×103 metric
tons) for the business sector of the fishing touristy (excluding cabins rented through foreign
portals) provided by Hallenstvedt and Wulff (2001). However, their estimate lies in the upper
range of our 95% confidence interval, and is likely biased for many reasons. Hallenstvedt and
Wulff (2001) extrapolate the average daily catches from sports fishing competitions to
estimates of total effort, which is untenable when applied to the average fishing tourist.
When comparing estimates of total catch during 2009 to those obtained in prior studies,
several factors must be taken into account, including a likely decline in the coastal cod stock
and a temporary reduction in fishing effort. The effort in the tourist fishery during 2009 was
affected by the financial crisis in Europe. Many of the collaborating businesses reported that
fewer tourists rented rooms and boats after the onset of the financial crisis. This suggests that
the total catches in 2009 may have been impacted by a reduction in boat fishing days. It
27
should also be noted that some tourists staying at the businesses catering to fishing may rent
boats for other reasons than fishing.
In contrast to prior studies, we have obtained representative data on the species composition
of catches, which allowed us to provide reliable estimates for the most important species
caught in the tourist fishery. This approach enabled us to make inferences on how tourist
fishery affects the condition of specific species. For instance, estimates for cod suggest that
the business segment of the tourist fishery overall contributes little to the total fishing
mortality of coastal cod. This inference would hold even if our list of businesses only covered
half of all fishing tourists in this sector.
The results presented in this report, however, need to be qualified with the reminder that
several factors remain unknown, which could bias our results. Our estimates of total catch for
the business sector of the tourist fishery provides a lower bound, since our sampling frame
(list of businesses) does not cover the entire population of all businesses, and since some
anglers may not have submitted catch diaries during reporting weeks, although they went
fishing. In southern Norway some large businesses declined to cooperate in the study,
potentially biasing our catch estimates based on the average catch per business in our sample.
Our many discussions with fishing tourists over the course of the study have revealed that
catch-and-release is becoming more popular among fishing tourists in Norway. Since the
introduction of the 15 kg export limit and the minimum landing size limits in the recreational
fishery for some species in 2010, the practice of catch-and-release will be more common. Our
study was based on catch diaries where only fish kept were recorded. The recording of
released fish may be important in future studies, but is challenging to incorporate in a simple
catch diary because of the multiple languages.
In general, an effective application of the prescribed framework requires that issues dealing
with coverage, across and within business units, should be addressed. Furthermore, the nature
of this sector is such that the development of a complete sampling frame and hence, good
sampling coverage is only possible with the effective involvement of stakeholders. Therefore,
methods must be devised, focusing on good marine stewardship through improved
stakeholder participation. These issues are briefly discussed below.
28
4.2 Sources of bias
One of the most important practical problems in conducting sample surveys is that lists that
can be used for selecting the sample units are generally incomplete or out of date. An
incomplete list of tourist fishing businesses can produce seriously biased estimates of the
population parameters. Updating the database of businesses is difficult and expensive.
Hallenstvedt and Wulff (2001) registered 939 businesses, but their list was not available to us
and therefore this number of businesses could not be verified.
Some information useful for assessing the coverage of businesses in our study was recently
made available by the Directorate of Fisheries. At the request of the Ministry of Fisheries and
Coastal Affairs, the regional offices of the Directorate of Fisheries conducted a search for
tourist fishing businesses during the summer of 2009. Door-to-door canvassing in the
Counties of Møre and Romsdal, Trøndelag, and Finnmark revealed 117 tourist fishing
businesses that were not on our list, suggesting that our study covered less than 80% of the
business sector (Figure 1). The under-coverage of tourist fishing businesses could be reduced
or eliminated by a more comprehensive search in all counties, but this is labor intensive and
costly and was outside the scope of this study. In future surveys, an alternative would be to
use multiple sampling frames (see, e.g., Skinner, 1991) to estimate the total number of tourist
businesses. A larger frame would include all registered businesses that provide
accommodation to tourists in coastal areas. By calling up a stratified random sample of these
businesses, we would record the proportion of the firms that caters to fishing tourists and have
boats for rent. By comparing these to our list of businesses, we could in principle estimate the
total number of tourist businesses using techniques used in mark-capture experiments.
The estimation of the catch by the informal tourist fishing sector is more difficult, but data
from the Norwegian Coast Guard may over time provide an estimate of its relative size with
respect to total fishing effort. Interviews at border crossing could also provide effort data that
could be used in conjunction with estimates of CPUE provided by our study to get
approximate catch estimates.
In general, the accuracy of the catch estimates would be improved (i.e., the bias reduced) if
independent effort estimates (boats, activity level) were available in addition to data obtained
from businesses. Catch and effort is estimated directly from the catch diaries at the accesspoints in our sample are sensitive to non-response (i.e., that some anglers do not submit catch
29
diaries). During the extension of the survey in 2010 we will attempt to collect data on nonresponse to separate these from tourist that do not fish. We also have improved the catch diary
form for 2010 by clearly spelling out „number of boats‟ and „number of fishers‟.
Estimates based on data collected from across business units provide a homogeneous picture
of the entire Norwegian tourist fishery. However, management needs a more detailed,
regional coverage in order to quantify the effect of tourist fishery on local stocks. This is
because species composition varies among regions. Furthermore, some of the questions that
often need to be addressed have regional, rather than national, implications. Thus a well
defined sampling strategy for temporal coverage of business units within regions is as
important as coverage across regions. In addition, priority must be given to develop survey
methods that are applicable for covering the informal sector of tourist fishery.
The ancillary information presented in this report show that the survey-based estimates of
species composition and catch-per-unit of effort for the commercially important species by
region were credible. Atlantic cod dominated the catches in northern Norway, while saithe
and mackerel were the most common species caught in western and southern Norway. We
conclude that self-reporting can provide reliable data on catch-per-unit of effort. The
estimated total catch per business is based on mean total catch per week from a systematic
sample, extrapolated to the entire year. A possible source of bias is that some fishing tourists
staying at a business during the reporting week may not have filled in and submitted their
catch diary even thought they went fishing. At a conference held at the IMR with scientists
and 25 collaborating business owners during spring of 2010, the effect of non-reporters was
discussed in detail and it was concluded that it was not a major source of bias. However, in
the 2010 study we have implemented routines, in collaboration with business owners, to get
better documentation of no-response rates. The independent estimation of total effort proved
more challenging and would require independent data collection that complements the diary
data.
4.3 Improving accuracy
Complete coverage of business units (whether within or across) is dependent on an up-to-date
list of all business units. Furthermore, adequate coverage requires a sampling frame, with
strata that include only the active businesses. Unfortunately, the complete list of businesses
will change over time since firms come and go, and even the spatial coverage by the industry
30
may expand or contract. Therefore, comparison of estimates between years is unreasonable
unless data have been collected from the same active business units.
The following are key points for conducting a successful survey of the Norwegian
recreational fishery:

Collaboration is required between the Institute of Marine Research (IMR) and
governmental institutions, such as Statistics Norway (Statistisk sentralbyrå-SSB).
Since all businesses are required by law to register with Statistics Norway, it is
perhaps the governmental organization with the most up-to-date information about this
sector. Statistics Norway should be able to provide updated information on the
creation and cessation of businesses.

Ideally, an effective survey would have a large number of collaborating business
owners across and within sampling units. This report showed that obtaining data
through self-sampling programs is the most effective survey approach in terms of cost
and coverage. Since such self-sampling is voluntary, it can only be effective if
businesses can identify with the goals of the survey.

One such approach to motivate businesses would be to emphasize the relevance of
good marine stewardship. In particular, the point can be made that: “If you provide us
with appropriate data, we would vouch for your helpful collaborating effort that is
important for implementing good marine stewardship”.
In the long term, perhaps a web-based, interactive program for data collection might be a cost
effective solution for covering a wider range of tourist fishing firms. Among other
advantages, such a web application would insure the uniformity of the data collected across
regions and within and across business units.
Figure 13 presents a schematic diagram such a web-based framework. All active businesses
(Blue box on right hand side) register with Statistics Norway (SSB), which in turn, provides
an updated list to a database with limited public access. Collaborating business units provide
self-sampled data to the same database, in a standardized format prescribed by the IMR, for
example through an updated version of our Altinn program. Limited public access insures that
sensitive business information is inaccessible to third parties. Estimates and sampling surveys
are conducted on the basis of information derived from the database. Results of the estimation
process are fed back to the limited public access database, and are accessible only to
31
collaborating business units and relevant management authorities. Both IMR and
collaborating businesses provide input to an open access Good Marine Stewardship (GMS)
web page. This webpage could for instance, include a list of collaborating business units, list
of key species (with pictures and key biological information) in their geographic locations,
and where applicable, links to individual business web pages.
32
Acknowledgements
We greatly appreciate the funding for this project supported by The Norwegian Research
Council (Project number 173274/S40). A special thanks to all the Collaborating businesses for
facilitating this study, and for their hospitality during visits by IMR field staff.
We recognize the support from:
The Advisory Group:
–Anne Marie Abotnes (Fiskeridirektoratet),
–Bjørn M. Bjerke (NHO Reiseliv),
–Grete Kuhnle (Fiskeridirektoratet,)
–Ole Osvald Moss (Statistisk sentralbyrå)
NHO Reiseliv, NORUT, Din Tur are credited for help with the mapping of tourist fishing
businesses.
We greatly appreciate the support from the Coast Guard who provides independent
information on the distribution of effort among sectors of the recreational fishery by
interviewing anglers at sea.
We appreciate the help from Stephanie Borchardt, who evaluated the accuracy of catch diary
reporting in Øygarden. She had summer internships at IMR in 2007 and 2008, with support
from EU‟s Leonardo da Vinci program, to assist on the project. We thank Sondre Aanes for
statistical analysis of data from the 2008 pilot study, and Jacob Gjøsæter (IMR) for writing
contributions to the report.
And, last but not least: Thanks to all of our colleagues at IMR who assisted with infomercials,
outreach, graphic design, database development, and field data collections. The project has
been a real team effort.
33
References
Borch, T. 2004. Sustainable management of marine fishing tourism. Some lessons from
Norway. Tourism in Marine Environments, 1, 49-57.
Borch, T. 2009. Contested coastal commercialization: Marine Fishing Tourism in Norway.
Maritime Studies, 8, 33-51.
Cap Gemini, Ernst & Young. 2003. Vurdering av turistfiske som inntektskilde i Norge
hvilke inntekter gir turistfiske sammenlignet med yrkesfiske? . Trondheim.
Cochran, W.G. 1977. Sampling Techniques, 3rd ed. Wiley, New York.
Connely, N.A. & Brown, T.B. 1995. Use of angler diaries to examine biases associated with
12-month recall on mail questionnaires. Transactions of the American Fisheries
Society 124:413-442.
Cooke, S. J. & Cowx, I. G 2004. The role of recreational fishing in global fish crises.
BioScience, 54, 857-859.
Cooke, S. J. & Cowx, I. G. 2006. Contrasting recreational and commercial fishing: Searching
for common issues to promote unified conservation of fisheries resources and aquatic
environments. Biological Conservation, 128, 93-108.
Ditton, R. B., Holland, S. M. & Anderson, D. K. 2002. Recreational Fishing as Tourism.
Fisheries, 27, 17-24.
EEA 2004. EEA`s definition on Recreational Angling. 10th General Assembly of the
European Anglers Alliance. Dinant, Belgium.
Hallenstvedt, A. 2001. Fritidsfiske og turistfiske som forvaltningsproblem. Samfunnsfaglig
fiskerirådgivning
Hallenstvedt, A. & Wulff, I. 2001. Fisk som agn – Utenlandsk turistfiske i Norge. Norges
Fiskarlag og Norge. Tromsø: Norwegian High School for Fisheries , University of
Tromsø.
Hallenstvedt, A. & Wulff, I. 2004. Fritidsfiske i sjøen 2003. Tromsø: Norwegian College
for Fisheries, University of Tromsø.
Hansen, M.H., Hurwitz, W.N., & Madow, W.H. 1953. Sample Survey Methods and Theory.
Volume 1. Methods and Applications. John Wiley & Sons, New York, NY.
ICES. 2009. Report of the Workshop on Sampling Methods for Recreational Fisheries
(WKSMRF), 14-17 April 2009, Nantes, France. ICES CM 2009\ACOM:41. 231 pp.
34
ICES. 2010. Report of the Arctic Fisheries Working Group (AFWG), 22.-28. April 2010,
Lisbon, Portugal/Bergen, Norway. ICES CM 2010/ACOM:05. 664 pp.
Hickley, P. and H. Tompkins (1998). Recreational fisheries: social, economic and
management aspects. Malden, MA, Fishing News Books.
Jacobsen, J. 2005. Utenlandske bilturisters fiske i saltvann i Norge. Oslo: Institute of
Transport Economics.
Jessen, RJ. 1978. Statistical Survey Techniques. John Wiley & Sons, New York, NY.
Levy, P.S. & Lemeshow, S. 1991. Sampling of Populations. John Wiley & Sons, New York,
NY.
Kish, L. 1965. Survey Sampling. John Wiley & Sons, New York, NY.
Kish, L. 2003. Leslie Kish: selected papers/compiled and edited by Steven Heerunga and
Graham Kalton. John Wiley & Sons, Inc., Hoboken, New Jersey.
Lehtonen, R. & Pahkinen, E. 2004. Practical Methods for Design and Analysis of Complex
Surveys, 2nd ed. Wiley, New York.
Maske, N. 2005. Har turistfiske innvirkning på bestanden av kysttorsk? Essens management.
Trondheim.
Pennington, M. and J.H. Vølstad, 1994. Assessing the effect of intra-haul correlation and
variable density on estimates of population characteristics from marine surveys.
Biometrics 50:725-732.
Pawson, M. G., H. Glenn, et al. (2008). "The definition of marine recreational fishing in
Europe." Marine Policy 32(3): 339-350.
Pollock, K.H., Jones, C.M., & Brown, T.L. 1994. Angler surveys and their application to
fisheries management. American Fisheries Society Special Publication 25. Bethesda,
MD. 371pp.
Pollock, K.H., Hoenig J.M., Jones C.M, Robson D.S., & Greene C.J.. 1997. Catch
rateestimation for roving and access point surveys. North American Journal of
Fisheries Management 17: 11-19.
Reid, D.D., & Montgomery, S.S. 2005. Creel survey based estimation of recreational harvest
of penaeid prawns in four southeastern Australian estuaries and comparison with
commercial catches. 2005. Fisheries Research. 74:169-185.
35
Skinner, C.J. 1991. On the Efficiency of Raking Ratio Estimation for Multiple Frame Surveys
Journal of the American Statistical Association, 86 (415): 779-784
Särndal, C.E., B. Swensson, and J. Wretman. 1992.
Model Assisted Survey
Sampling. Springer-Verlag, New York, NY.
Tarrant, M.A., Manfredo, M.J., Bailey, P.B., & Hess, R. 1993. Effects of Recall Bias and
Nonresponse Bias on Self-Report Estimates of Angling Participation. North American
Journal of Fisheries Management 13: 217-222
Vølstad, J.H, Pollock, K. H., & Richus, W. 2006. Comparing and combining effort and catch
estimates from aerial-access designs, with applications to a large-scale angler survey
in the Delaware River. North American Journal of Fisheries Management 26:727–741
Williams, R.L. 2000. A Note on Robust Variance Estimation for Cluster-Correlated Data.
Biometric 56 , 645-646
Wolter, K. M. 1985. Introduction to Variance Estimation. Springer-Verlag, New York.
36
Tables
Table 1. Total number of tourist fishing businesses and number of rental boats mapped in 2008, and used
for the 2009 National survey.
Number of businesses
Region
total
≤3 boats for rent
>3 boats for rent
no info
Number
of boats
Northern and Middle
358
182
163
13
1744
Western and southern
87
31
51
5
649
445
213
214
18
2393
Total
Table 2. Reporting rates of catch diaries for collaborating businesses during the 2008 pilot study.
Region
Northern
Middle
Western
Southern
Total
Businesses (n) Catch diaries (n)
25
11
24
7
67
Mean number of diaries
delivered per business
302
114
237
163
816
12.1
10.4
9.9
23.3
12.2
Table 3. Reporting rates of catch diaries for collaborating businesses during the 2009 National survey.
Region
Northern
Middle
Western
Southern
Total
Businesses (n) Catch diaries (n)
35
25
25
6
91
Mean number of diaries
delivered per business
206
155
178
66
605
5.9
6.2
7.1
11.0
6.6
37
Table 4. Estimated mean daily catch (kg) by species per boat (CPUE) by region and quarter for the 2008
pilot study.
Jan- Apr
CPUE
NA
4
2.05
SE
NA
NA
0.45
May-Aug
CPUE
19.62
6.1
1.3
Species
Region
Northern
Middle
Western
Cod
Southern
Northern
Middle
Western
1.22
NA
0.7
0.83
0.33
NA
NA
0.35
2.49
0.57
0.37
0.29
0.18
0.08
0.06
0.05
0.47
0.88
1.59
1.19
1.1
0.13
0.68
0.14
Haddock
Southern
Northern
Middle
Western
0
NA
0
1.31
0
NA
NA
0.36
0.08
2.88
6.42
2.39
0.02
0.47
0.51
0.25
0.04
4.45
7.84
1.16
0.02
0.55
1.99
0.19
Saithe
Southern
Northern
Middle
Western
8.48
Na
0
0.14
1.64
Na
NA
0.09
18.67
0.1
1.29
1.29
1.74
0.02
0.19
0.14
0.16
0.25
0.23
1.83
0.04
0.09
0.11
0.58
Pollack
Southern
Northern
Middle
Western
0.42
NA
0.6
0
0.19
NA
NA
0
0.54
0.26
0.07
0.02
0.08
0.08
0.03
0.01
0.17
0.6
0.03
0.08
0.06
0.14
0.02
0.05
Halibut
Southern
Northern
Middle
Western
0
NA
0
0
0
NA
NA
0
0.02
0.02
0.02
0.55
0.01
0.01
0.01
0.08
0
0.15
0.6
1.41
0
0.04
0.19
0.18
Mackerel
Southern
Northern
Middle
Western
0
NA
0
0.34
0
NA
NA
0.16
0.45
0.26
1.25
1.61
0.1
0.04
0.21
0.12
1.27
0.35
0.18
1.39
0.46
0.1
0.09
0.13
Ling
Southern
Northern
Middle
Western
0.04
NA
0
0.15
0.04
NA
NA
0.09
0.25
1.44
1.08
1.68
0.03
0.19
0.21
0.16
0.27
1.71
0.05
0.96
0.11
0.24
0.05
0.11
Tusk
Southern
Northern
Middle
Western
0.09
NA
0
0
0.09
NA
NA
0
0.07
0.36
0.02
0.02
0.03
0.07
0.01
0.01
0.02
0.26
0
0.02
0.02
0.05
0
0.02
Wolffish
Southern
0
0
0.02
0.01
0
0
38
SE
1.01
0.44
0.11
Sep- Dec
CPUE
12.45
7.53
1.3
SE
1.12
1.57
0.14
Table 5. Estimated mean daily total catch per boat by month for the 2009 National survey.
Month
N
Mean
SE
January
1
18.5
NA
February
8
7.3
1.4
2.0
12.5
March
119
12.8
1.5
0
86.0
April
257
21.0
1.6
0
240.0
May
328
23.4
1.8
0
262.0
June
381
20.8
1.3
0
214.8
July
377
25.0
1.8
0
250.0
August
199
27.2
2.9
0
254.0
September
157
12.6
1.1
0
75.0
October
63
16.9
1.9
1.5
66.5
November
0
December
0
39
Minimum
Maximum
18.5
Table 6. Estimated total catch in numbers and weight (metric tons –MT) by region, North-Middle (North)
and South-West (South), and overall for the 2009 National survey, lower and upper 95% confidence
limits.
Species
Region
All
North
South
All
Cod
North
South
All
Haddock North
South
All
Saithe
North
South
All
Pollack
North
South
All
Halibut North
South
All
Mackerel North
South
All
Ling
North
South
All
Tusk
North
South
All
Wolffish North
South
All
Number
SE(N)
Weight
(MT)
1 543 005
1 140 640
402 365
542 762
529 633
13 129
74 411
68 018
6 393
565 195
378 929
186 266
48 870
31 703
17 167
5 367
5 335
31
181 049
26 838
154 211
38 309
21 988
16 321
82 846
74 150
8 796
4 099
4 046
52
237 477
225 806
73 534
118 565
118 440
5 447
14 722
14 611
1 798
122 687
117 445
35 479
9 823
9 213
3 408
1 699
1 699
28
38 360
7 100
37 698
8 125
6 949
4 209
24 579
24 417
2 816
1 294
1 292
45
3 335.2
2 958.2
377.0
1 613.0
1 586.0
27.0
124.5
115.1
9.4
1 033.2
825.2
208.0
102.5
81.1
21.4
79.9
79.7
0.2
68.1
13.6
54.4
108.9
68.5
40.4
189.6
173.7
15.9
15.6
15.3
0.3
40
SE(MT)
572.8
567.6
77.2
348.5
348.3
11.2
24.2
24.1
2.6
246.4
241.3
49.8
26.0
25.7
4.2
29.4
29.4
0.2
14.4
3.6
13.9
28.5
26.9
9.4
51.8
51.7
4.1
4.4
4.4
0.3
Weight
RSE (%)
LCI (MT)
17 %
19 %
20 %
22 %
22 %
41 %
19 %
21 %
28 %
24 %
29 %
24 %
25 %
32 %
19 %
37 %
37 %
90 %
21 %
26 %
26 %
26 %
39 %
23 %
27 %
30 %
26 %
28 %
29 %
88 %
2 212.4
1 845.7
225.6
929.9
903.3
5.1
77.0
67.9
4.2
550.2
352.2
110.4
51.6
30.8
13.3
22.3
22.2
-0.1
39.9
6.6
27.2
53.1
15.8
22.0
87.9
72.4
7.8
7.0
6.7
-0.2
Weight
UCL
(MT)
4 457.9
4 070.6
528.3
2 296.0
2 268.7
48.9
171.9
162.2
14.6
1 516.1
1 298.2
305.6
153.5
131.4
29.6
137.5
137.3
0.5
96.2
20.6
81.7
164.7
121.2
58.7
291.2
275.0
23.9
24.1
23.8
0.8
Mean
weight
of fish
(kg)
2.2
2.6
0.9
3.0
3.0
2.1
1.7
1.7
1.5
1.8
2.2
1.1
2.1
2.6
1.2
14.9
14.9
6.1
0.4
0.5
0.4
2.8
3.1
2.5
2.3
2.3
1.8
3.8
3.8
6.0
Table 7. Additional species registered in catch diaries by region (north and south of 62°N).
Family
Species
Squalidae
Squalus acanthias Linneaus, 1758
Clupeidae
Clupea harengus Linnaeus, 1758
Gadidae
Gadidae
English
Merlangius merlangus (Linnaeus,
1758)
Micromesistius poutassou (Risso,
1827)
Norwegian
N
S
Pigghå
x
x
Sild
x
x
Whiting
Hvitting
x
x
Blue
whiting
Kolmule
x
x
Picked
dogfish
Atlantic
herring
Gadidae
Trisopterus luscus (Linnaeus, 1758)
Pouting
Skjeggtorsk
Lotidae
Molva dypterygia (Pennant, 1784)
Blue ling
Blålange
x
x
Merlucciidae
Merluccius merluccius (Linnaeus,
1758)
European
hake
Lysing
x
x
Lophiidae
Lophius piscatorius Linnaeus, 1758
Angler
Breiflabb
x
x
Belonidae
Belone belone (Linnaeus, 1761)
Garfish
Horngjel
x
x
Rockfishes
Uerfamilien
x
x
Grey
gurnard
Knurr
x
x
Sebastidae spp.
Triglidae
Eutrigla gurnardus (Linnaeus,
1758)
Cyclopteridae
Cyclopterus lumpus Linnaeus, 1758 Lumpfish
Labridae spp.
Anarhichadidae
Anarhichas spp.
Ammodytidae spp.
Rognkjeks
x
Wrasses
Leppefiskfamilien
x
x
Wolffishes
Steinbitfamilien
x
Sand lances
Silfamilien
x
Scophthalmidae
Lepidorhombus whiffiagonis
(Walbaum, 1792)
Megrim
Glassvar
x
Scophthalmidae
Psetta maxima (Linnaeus, 1758)
Turbot
Piggvar
x
Scophthalmidae
Scophthalmus rhombus (Linnaeus,
1758)
Brill
Slettvar
x
Pleuronectidae
Limanda limanda (Linnaeus, 1758)
Pleuronectidae
Pleuronectes platessa Linnaeus,
1758
Pleuronectidae spp.
Soleidae spp.
Common
dab
European
plaice
Righteye
flounders
Soles
41
Sandflyndre
x
x
Rødspette
x
x
Flyndrefamilien
x
Tungefamilien
x
Table 8. Species identification by fishers from 33 fishing trips during summer 2009.
Correctly
identified
to species
level (%)
Species
Correctly
identified
to genus
level (%)
Incorrectly
identified
Did not
identify
Cod
Gadus morhua - Torsk
100
Saithe
Pollachius virens - Sei
100
Mackerel
Scomber scombrus - Makrell
100
Ling
Molva molva - Lange
100
Tusk
Brosme brosme - Brosme
96.7
Pollack
Pollachius pollachius - Lyr
90.0
10.0
Halibut
Hippoglossus hippoglossus - Kveite
80.0
13.3
6.7
Haddock
Melanogrammus aeglefinus - Hyse
66.7
26.7
6.7
Merluccius merluccius - Lysing
66.7
16.7
16.7
Pleuronectes platessa - Rødspette
53.3
30.0
16.7
Merlangius merlangus - Hvitting
46.7
30.0
23.3
Anarhichas minor - Flekksteinbit
33.3
46.7
3.3
16.7
Anarhichas lupus - Gråsteinbit
30.0
60.0
3.3
6.7
Limanda limanda - Sandflyndre
26.7
43.3
30.0
Platichthys flesus - Skrubbe
20.0
46.7
33.3
Blue ling
Molva dypterygia - Blålange
13.3
16.7
70.0
Northern
wolffish
Anarhichas denticulatus - Blåsteinbit
European
hake
European
plaice
Whiting
Spotted
wolffish
Atlantic
wolffish
Common
dab
European
flounder
42
3.3
3.3
33.3
63.3
Table 9 a. Species identification by specimen, based on photos shown to anglers from a total of 30 fishing
trips.
Number of specimens (n)
Species
Correctly
identified
Incorrectly
identified
Saithe
Pollachius virens
288
1
Pollack
Mackerel
Tusk
Ling
Haddock
Cod
Pollachius pollachius
Scomber scombrus
Brosme brosme
Molva molva
Melanogrammus aeglefinus
Gadus morhua
68
62+
22
18
17
12
1
0
0
0
0
0
Norway redfish Sebastes viviparus
0
5
Garfish
Belone belone
2
0
Poor cod
Trisopterus minutus
0
1
Anglerfish
Ballan wrasse
Great sandeel
Lophius piscatorius
Labrus bergylta
Hyperoplus lanceolatus
1
0
0
0
1
1
Incorrectly
identified as
’Pollack’ (P.
pollachius)
P. virens
’Rotbarsch’
(Sebastes sp.)
’Stintdorsch’ (T.
esmarkii)
’Barsch’
-
Table 9 b. Species identification at a trip level (N=30), where groups of anglers from each trip identified
species based on photos.
Number of trips (group of anglers)
Species
Saithe
Pollack
Mackerel
Tusk
Ling
Haddock
Cod
Norway redfish
Garfish
Poor cod
Anglerfish
Ballan wrasse
Great sandeel
Correctly identified Incorrectly identified
Pollachius virens
Pollachius pollachius
Scomber scombrus
Brosme brosme
Molva molva
Melanogrammus aeglefinus
Gadus morhua
Sebastes viviparus
Belone belone
Trisopterus minutus
Lophius piscatorius
Labrus bergylta
Hyperoplus lanceolatus
24
16
9
3
5
5
7
0
1
0
1
0
0
43
1
1
0
0
0
0
0
3
0
1
0
1
1
Figures
Marine Recreational Fisheries
Fishing tourists
Recreational fishers
Recreational fishers traveling from
home to stay overnight
Norwegians and legal
residents staying at home or
second home
Business sector
Informal sector
Tourist fishing businesses,
or cabins rented through
a travel portal
Private rentals,
tents, motorhomes,
etc.
Businesses
mapped by
IMR/Norut
(N=445)
Other
businesses
Foreigners
(N=Unknown)
Residents
(Can be
contacted by
phone)
Figure 1. Diagram of the marine recreational fishery sectors in Norway as defined in this study.
44
Figure 2. Map of tourist fishing businesses that collaborated with the Institute of Marine Research in
2008.
45
Figure 3. Map of tourist fishing businesses that collaborated with the Institute of Marine Research in
2009.
46
Figure 4. Species composition in numbers of reported fish caught in 2008.
47
Figure 5. Species composition in numbers of reported of fish caught in 2009.
48
Figure 6. Species composition of estimated total catches by weight in 2009.
49
Norway total
4000
Tons
3000
2000
1000
0
Tusk WolffishHaddock Halibut
Ling
Pollack Mackerel Saithe
Figure 7. Estimated total catch (kg) by species nationally in 2009.
50
Cod
Total
Mid and northern regions
3000
Tons
2000
1000
0
Tusk WolffishHaddock Halibut
Ling
Pollack Mackerel Saithe
Cod
Total
Figure 8 a. Estimated total catch (kg) by species in the mid and northern regions based on the 2009
National survey.
Western and southern regions
400
Tons
300
200
100
0
Tusk WolffishHaddock Halibut
Ling
Pollack Mackerel Saithe
Cod
Total
Figure 8 b. Estimated total catch (kg) by species in western and southern regions based on the 2009
National survey.
51
Mean catch per boat and day
40
30
20
10
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Figure 9. Estimated monthly mean total catch per boat-day in 2009 (blue line), with 95% confidence limits
(red lines).
52
Mean catch per boat and day
50
40
30
20
10
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Region:
Northern
Mid
Western
Southern
Figure 10. Estimated monthly mean catch per boat and per day (CPUE) by geographic regions in 2009.
53
Distribution of total catch per boat and day
10 30 50 70 90 110 130 150 170 190 210 230 250 270
Kg
Figure 11. Distribution of reported total catches (all species) per boat-day in 2009. The x-axis denotes the
mid-point of the weight-bin.
54
Mean number of fishers per boat and day
4
3
2
1
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Figure 12. Estimated mean number of anglers per boat for a typical fishing day (blue line) along with the
95% confidence limits (red lines) in 2009.
55
SSB provides
List of active
Business Units
All Businesses
Limited Public
Access Primary
Database
Collaborating
Business Units
IMR Analysis
Open access
GMS Web
Figure 13 A schematic diagram for a web-based solution for improving the sampling frame and coverage of
tourist fishing businesses in Norway.
56
Appendices
Appendix 1. Daily catch diaries forms
2009 Daily catch diary, number and total weight of catches.
57
2009 Daily catch diary, number of fish.
58
2010 Daily catch diary, number and total weight of catches.
59
Appendix 2. Form for registering boating activity (e.g. group 1).
Antall båter i utleie:
Uke nr:
Antall båter til leie
Antall båter utleid:
Dag 1
Dag 2
Dag 3
Dag 4
Dag 5
Dag 6
Dag 7
1
7
13
19
60
25
31
37
43
49
Appendix 3. Questionnaire used by the Norwegian Coast Guard to classify fishing tourists and
recreational anglers.
Region:
Båt nummer
Dato:
1
Kystvaktfartøy:
2
3
4
Med skipper (kryss for ja)
Antall fiskere
Leverer fangstdagbok (kryss for ja)
Breddegrad (DDD° MM.M')
Lengdegrad (DDD° MM.M')
Statsborgerskap (landkode)
Citizenship
Staatsbürgerschaft
Boplass/ Accomodation/ Unterkunft
(angi antall personer per kategori)
Rorbu/ Fishing Resort/ Angelanlage
Hotell
Privat hytte/hus
Private cottage/house
Privathuette/haus
Bobil/ Camper/ Wohnmobil
Campingplass
Hjemme
Telt/Tent/ Zelt
61
Skjemanr.
5
6
7
8
Side 1
9
10