Marine Stewardship Council Science Series
Stock management units and limit reference
points in salmon fisheries: best practice
review and recommendations to the MSC
Nicole Portley1,2 and Harold J. Geiger2
1
Sustainable Fisheries Partnership, 4348 Waialae Avenue, Number 692, Honolulu, Hawaii 96816, USA
St. Hubert Research Group, 222 Seward Street, Suite 205, Juneau, Alaska, USA
2
Abstract
To reach a conclusion that a salmon fishery is sustainable, an MSC certification body would need to
understand the delineation of stocks supporting the fishery and to understand when stocks are overfished.
Due to the nature of salmon, which spawn where the fish are visible and countable, management
approaches for marine fisheries are generally not appropriate for salmon. Further, different management
agencies have followed various theories, practices, and traditions in setting and achieving management
targets for salmon. After reviewing current practices, we recommend that salmon populations be evaluated
for sustainability at the stock, rather than sub-stock, level, unless the stock is in a detectably perilous state.
Specifically, we recommend that the MSC retain the stock management unit (SMU) as the basic unit of
scoring as long as management measures also adequately protect sub-stocks. Furthermore, we
recommend a series of locally appropriate and simple proxy reference points, analogous to the 0.5 Bmsy
target, to define overfishing.
Citation: Portley N and Geiger HJ (2014) Stock management units and limit reference points in salmon
fisheries: Best practice review and recommentdations to the MSC. Marine Stewardship Council Science
Series 2: 89 – 115.
(Note that sections of this paper were published in the paper “Portley, N and Geiger, HJ (2014) Limit reference points
for Pacific salmon fisheries, North American Journal of Fisheries Management 34(2):401410” and are reproduced here
with the kind permission of that journal.)
Date submitted: May 2013 | Date published: May 2014
Disclaimer: The Marine Stewardship Council Science Series has been commissioned by Marine
Stewardship Council (MSC) as part of its goal to extend scientific research and understanding of marine
ecosystems and fisheries. The views expressed in this publication do not necessarily reflect the views of
the MSC. The MSC certification program changes over time; every attempt is made to ensure all details
within this paper are accurate at the time of publication. An internal review process has been established to
ensure as far as possible the accuracy, content, completeness, legality and reliability of the information
presented. For full detail of the review process visit: http://www.msc.org/science-series
Copyright: © The Author 2014. Published by Marine Stewardship Council Science Series. This is an Open
Access article distributed under the terms of the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction
in any medium, provided the original author and source are properly cited.
*Correspondence: Nicole Portley
Email: [email protected]
89
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Introduction
The Marine Stewardship Council (MSC) has accumulated fourteen years (2000-2013) of experience in the
assessment and certification of Pacific salmon fisheries. Over that time period, the MSC standard and its
protocols have evolved to better reflect best practices in fisheries management. Assessment trees (i.e.
frameworks) applied to salmon fisheries have correspondingly become more detailed. Since the 2008
issuance of the default Fisheries Assessment Methodology, certification bodies have made controlled
changes to the default assessment tree to account for some of the specificities of salmon fishery
management. However, as described by Portley & Sousa (2013) who took a statistical approach, scoring in
MSC salmon fishery assessments of stock status and hatchery-relevant performance indicators exhibited
wide variation among eight assessments. In an effort to be more precise, the MSC is striving to improve the
default assessment tree specifically adapted to salmon fisheries.
Salmon are anadromous and semelparous and are captured when mature fish return en masse to their
natal streams to spawn. This important ecological, economic and social event is usually referred to as the
“salmon run”. Escapement goals are one of the main management tools used for salmon fisheries and are
defined as the number of fish allowed to avoid capture by the fishery and go on to spawn. Generally the
number is set to allow the fishery to achieve maximum sustainable yield (Carroll, 2005). Management of the
fishery in a particular area can be complicated by the fact that the timing of salmon runs can be specific to
tributaries and genotype (Stewart et al., 2002; Stewart et al., 2006).
The various regional salmon management authorities across the Pacific Rim have adopted different
methods for the delineation of stocks and determination of management objectives. As a result, the
different regional languages, terminology, approaches, and objectives have all led to confusion among
mangers and researchers, and even dissent among stakeholders. However, a critical appraisal of each
region’s approach shows that there are many features in common that can be used to build a logical path
forward for the MSC.
We offer a review of best practices as well as recommendations to the MSC regarding two issues that have
provoked considerable debate among stakeholders involved in the development of the default assessment
tree for salmon:
•
•
Definition of the salmon assessment tree equivalent of “stock”, i.e., the basic unit of scoring for
Principle 1 performance indicators in the default Fisheries Assessment Methodology
A description of a method for determining the Limit Reference Point (LRP) against which stock
status is measured in scoring issue (a.) of performance indicator 1.1.1
www.msc.org/science-series/volume-02
90
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Stock Management Units
In the draft MSC default assessment tree and accompanying guidance for salmon, released for stakeholder
commentary in 2012, the Stock Management Unit (SMU) was identified as the basic unit of scoring for
Principle 1 performance indicators, and the following definition of the term was provided:
A group of one or more populations for which fishery management goals have been established by
the management agency and for which fisheries are regulated to achieve these goals. SMU is a
broad management concept, such that not every population with a defined goal need be an
individual SMU, but can be part of a collection of such populations within an SMU (MSC, 2012).
In order to address whether or not the SMU is the appropriate basic unit of scoring for the MSC salmon
default assessment tree, we first explore the term stock and its broad usage in fisheries management,
before proceeding to review of the various stock units adopted for management of salmon around the
Pacific Rim. We also examine the units that have been established for the conservation of sub-stocks or
endangered species management – rather than fisheries management.
Stock Units and General Fisheries Management
The current MSC Fisheries Assessment Methodology (2010) describes stocks as “biologically-distinct
population units” and stock assessment as “an integrated analysis of information to estimate the status and
trends of a population against benchmarks such as reference points”. The two definitions strike a balance
between biological and management focused approaches to the stock concept. Both approaches are
described in scientific literature and fisheries policy. On the biological end of the spectrum, Ricker (1972)
described a salmonid stock as “the fish spawning in a particular lake or stream (or portion of it) at a
particular season, which…to a substantial degree do not interbreed with any group spawning in a different
place”. Busack & Marshall’s (1995) general definition of a fish stock is similar to Ricker’s: “a group of
interbreeding individuals that is genetically distinct and substantially reproductively isolated from other such
groups". Booke (1981), meanwhile, avoided the subjectivity of a definition that includes the word
“substantial” through application of the Hardy-Weinberg equilibrium (“a population of fish that maintains and
sustains Castle-Hardy-Weinberg equilibrium”). Hilborn & Walters (1992) included the concept of life history
diversity in their definition, which maintains that stocks are self-reproducing groups of fish that share life
history characteristics.
William Ricker did not use the term stock consistently, and a later Ricker (1975) definition is weighted
toward management considerations: “the part of a fish population which is under consideration from the
point of view of actual or potential utilization”. A similar definition from the same era describes stocks as
groups of populations that are separately fished (Larkin, 1972). Milton and Shaklee (1987) follow Larkin in
referring to stocks as any group of fish species available for exploitation in a given area.
When one takes the above biological and management focused definitions cumulatively into account, the
spectrum of possible meanings of stock is quite large: it could include one or multiple species, one or
multiple genetically distinct groupings of fish, and be targeted by one or several fisheries. Geiger & Gharrett
(1998) sought to limit confusion surrounding the term stock by applying the word deme to fish groups
delineated for conservation purposes, while reserving the term stock strictly for fisheries management
purposes. This usage of the word deme in fisheries biology has not been widely adopted since then, but
other similar concepts with respect to salmon (for instance, Evolutionary Significant Units in the continental
United States and Conservation Units in British Columbia) are used in this context.
In summary, ambiguity remains between the biological and management usages of stock. Definitions that
seek to strike a balance between the two camps have gained the most traction in recent times: for example,
www.msc.org/science-series/volume-02
91
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Begg & Waldman (1999) asserted that “the stock concept really has to do with the interaction between a
fish species and its management”. These authors and others also describe a distinction between fisheries
management and endangered species management with respect to stock identification and management
units (Crandall et al., 2000). With respect to stock delineation in salmon fisheries, this paper follows Begg &
Waldman and Crandall in addressing these two concepts separately.
Stock Units Used in Salmon Fishery Management
Below are descriptions of the stock units used in the management of salmon fisheries within each of the
major regional management systems. This is not intended as an exhaustive listing, but, rather, a review
sufficient for the determination of best practices. Attention is generally paid to the species and fisheries in
each region that contribute significantly to harvest at the Pacific Rim-wide scale.
Alaska
Many escapement goals specific to Alaskan salmon stocks have been in use since the 1970s, but the
implementation of the Salmon Escapement Goal Policy in 1992 marks an important point in terms of
codification of the term stock for use in management of Alaskan salmon. According to that policy, stock may
refer to a group of salmon spawning within (1) a single creek or stream; (2) a portion of a river drainage; (3)
an entire river drainage, or (4) several creeks, streams, and rivers occurring in a single management unit
(included in the Alaska Administrative Code as 5 AAC 39.223).
The Salmon Escapement Policy laid the groundwork for an escapement goal review effort that has resulted
in the current catalogue of 324 species- and geography-specific salmon stocks that are managed in order
to achieve escapement goals in Alaska (Munro and Volk, 2012). Stock units vary from very narrow
classifications specific to a single river or portion of a drainage (e.g. Chinook salmon stocks in Southeast
Alaska) to very broad classifications that encompass wide geographies and numerous basins (e.g. Prince
William Sound pink and chum salmon stocks) (Fried, 1994). Overall, delineation of stocks in Alaska reflects
the availability of resources for active monitoring and the prioritization of some stock units over others in
terms of splitting out some finer-scale units for individualized management while lumping others into
coarser units.
Generally, in Alaska, a grouping of salmon is referred to as a stock if there is a single management
escapement goal. However, grey areas are found in some instances where fisheries target groups of fish
for which there is no escapement goal. Examples include Unakwik sockeye salmon in Prince William Sound
and several stocks of Chinook salmon in the Kuskokwim region—area management annual reports for
these fisheries can refer to these groups of fish as “stocks” despite their exclusion from existing
escapement goal coverage (Volk et al., 2009; Brazil et al., 2011; Botz et al., 2012). Generally, in these
instances, management intends to someday complete the necessary research and review process required
for establishment of escapement goals for these groups of fish.
British Columbia
Canada’s Policy for Conservation of Wild Pacific Salmon (DFO, 2005), known as the Wild Salmon Policy
(WSP), is the policy framework for the conservation and sustainable use of wild Pacific salmon in Canada.
The WSP provides a standardized process for organizing Pacific salmon into Conservation Units (CUs)
defined as “a group of wild salmon sufficiently isolated from other groups that, if extirpated, is very unlikely
to recolonize naturally within an acceptable timeframe”. There are currently more than 9,600 spawning
systems of Pacific salmon in Canada grouped into 457 CUs (Holtby & Ciruna, 2007). The methods for
identifying CUs builds on Waples et al.’s (2001) characterization of diversity in Pacific salmon in the
www.msc.org/science-series/volume-02
92
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
American Pacific Northwest and the concepts of reproductive isolation, adaptive variation and ecological
exchangeability that underlie commonly used units for the conservation of species diversity.
Historically, the term stock has been applied to salmon management by Department of Fisheries and
Oceans Canada (DFO) with a narrower, biological focus, and British Columbia has generated many
corresponding escapement goals. However the units that are actively used in fishery management tend to
be much broader. For example, harvest control rules for the Skeena sockeye salmon fishery are set on the
basis of catch of Skeena sockeye salmon at the Tyee test fishery in the lower river, while there are many inriver goals for different portions of the basin above the test fishery (DFO, 2012).
As is the case elsewhere throughout the Pacific Rim, salmon spawning in British Columbia are exploited in
fisheries that potentially harvest multiple Conservation Units. For example, there are 24 Fraser sockeye
CUs that generally correspond to nursery rearing lakes, and in some cases variations in run timing within a
lake (British Columbia is a major contributor to global sockeye salmon harvest). Chum salmon, meanwhile,
are organized into large CUs that include several spawning systems with nested operational management
escapement goals.
The Fraser sockeye fishery focuses upon broad stock units that can contain multiple CUs. Since 2007,
escapement goals are derived from 19 Fraser sockeye stocks with adequate escapement and catch data to
assess the modelled performance of alternative harvest control rules. Meanwhile, in-season management
is carried out using control rules applied to in-season estimates of four stock-aggregates termed “run-timing
groups” because their spawning migrations overlap temporally, although each stock spawns in a distinct
portion of the Fraser basin (Pestal et al., 2011; PSC, 2012). A certification body assessing the Fraser
sockeye salmon fishery must decide between the four run-timing groups and 19 “modelled stocks” with
respect to determination of stock management units for use in assessment of Principle 1 performance
indicators. Similarly, commercial fisheries that target Barkley Sound sockeye salmon off the west coast of
Vancouver Island focus on two CUs (Great Central and Sproat Lake), and the control rule applied to the
Barkley stock is based on in-season run size estimates for the stock-aggregate of those CUs.
Japan
Japan is a major contributor to global harvest of chum salmon. Since 1888, Japanese salmon fishery
management has been focused upon achieving objectives for hatchery sourced rather than wild fish. While
research conducted over the last decade indicates that wild chum salmon still exist in approximately 100
rivers of Hokkaido, there are as yet no wild escapement goals in place according to publicly available
information. Ongoing development of a Hokkaido Wild Salmon Policy indicates that reference points for wild
stocks may be put into place in the future (Nagata, 2010). For harvest reporting purposes, there are four
management units delineated according to the island where the fishery occurs (Hokkaido or Honshu) and
the coast where the fishery occurs (Pacific Ocean or Sea of Japan) (Sasaki et al., 2012).
Pacific Northwest, USA
The Washington-Oregon Chinook salmon troll fishery is a major contributor to global harvest of Chinook
salmon. Chinook stocks are grouped into coastal aggregates that include indicator streams with
escapement goals that are reviewed and approved by the Pacific Salmon Commission’s Chinook Technical
Committee (CTC). Three such groupings are found in Oregon—the North Oregon, Mid-Oregon, and South
Oregon Coastal Aggregates—and these three aggregates include five nested indicator stocks delineated by
basin. Additionally, six indicator stocks within the Columbia River basin are delineated and factored into
CTC fishery management and planning. Similar stock groupings exist in Washington. Failure to achieve
www.msc.org/science-series/volume-02
93
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
goals for stock aggregates results in catch limitations in subsequent fishing seasons through the 2009
Pacific Salmon Treaty (CTC, 2012).
Russia
Russian legislation governing the determination of quotas in fisheries describes “single or multi-species
stocks” delineated by the analysis of “data generated through annual fisheries stock status monitoring, with
the exceptions of species, sub-species, and populations listed as endangered at the national or Oblast
levels” (Russian Federal Law 166-F3). This broad definition of stock is reflected in the wide variation in
scale among salmon management units in the different regions of the Russian Far East where Pacific
salmon fisheries are conducted. Examples of the most narrow classifications include Sakhalin’s 217 official
salmon spawning rivers, each of which has its own escapement goals for pink and chum salmon
(Springmeyer et al., 2007). The Ozernaya sockeye salmon stock in southwestern Kamchatka is also
managed to achieve a drainage-specific escapement goal (MRAG Americas, 2012).
Meanwhile, East Kamchatka pink salmon are managed with the aim of achieving a single escapement goal
of 20–30 million fish despite the presence of over 100 major spawning rivers within that geography
(Shevlyakov, 2006; TINRO, 2012). Data regarding in-river goals specific to certain index streams within
East Kamchatka are not reported publicly. As in Alaska, stock delineation reflects granularity of available
monitoring data. While many Sakhalin rivers are accessible by vehicle and there is a counting weir and
sonar in place to monitor escapement of Ozernaya sockeye salmon, East Kamchatka is largely
inaccessible to vehicular traffic and pink salmon escapement is mostly monitored by overflight (Shevlyakov
& Maslov, 2011).
Sub-Stock Units for Endangered Species Conservation or Research
Purposes
In addition to the stock units used for fishery management, in each region we found examples of what we
are calling sub-stock (population) units delineated for conservation or research purposes.
Alaska
Alaska has a three-tiered system for classifying what are called stocks of concern (ADF&G, 2001). The
lowest level of concern, defined as a yield concern, results from “a chronic inability, despite the use of
specific management measures, to maintain specific yields, or harvestable surpluses, above a stock’s
escapement needs; a yield concern is less severe than a management concern". A management concern
arises from a “chronic inability, despite the use of specific management measures, to maintain
escapements for a salmon stock within the bounds of the [the management targets], or other specified
management objectives for the fishery; a management concern is not as severe as a conservation
concern”. The most severe classification, a conservation concern, is defined as “a concern arising from a
chronic inability, despite the use of specific management measures, to maintain escapements for a stock
above a sustained escapement threshold (Alaska’s limit reference point)”. As we describe later in this
report, Alaska has never established a sustained escapement threshold for any stock nor have they
described how one would be established. No stock in Alaska can be classified as a conservation concern
without first establishing these levels. Under the Alaskan system a concern designation is only applied at
the stock level. However, managers have the flexibility to redefine stocks so that data collection, reporting,
and analysis takes place at a finer level if needed. We noted that Alaskan managers have actually done
this; for example, the scale of stock definition has recently been changed for pink salmon in Prince William
Sound.
www.msc.org/science-series/volume-02
94
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
SCS (2007) and others have expressed concerned that some mixed-stock fisheries in Alaska are placing
too much pressure on particular sub-stocks. Alaska has responded with stock identification research to
better describe sub-stock structure. Example fisheries include the Copper River sockeye salmon fishery
and Westward Alaska chum and sockeye salmon fisheries, which have all been the focus of genetic studies
over the last several years. Stock identification results can be incorporated into area escapement goal
reviews, where umbrella stock goals can be adjusted in order to better encompass nested sub-stocks, or
new, smaller-scale goals can be delineated (Ackerman et al., 2011; Munro et al., 2012).
British Columbia
Canada’s Committee on the Status of Endangered Wildlife in Canada (COSEWIC) is an advisory body to
assess the risk of extinction or extirpation under the Species at Risk Act (SARA). This act parallels the US
Endangered Species Act in that guidelines for recognition of Designatable Units (DUs) make primary
reference to the concept of the ESU (COSEWIC, 2011). Four Pacific salmon DUs have received COSEWIC
designations dating back to 2002 (Cultus sockeye salmon, Sakinaw sockeye salmon, Okanagan Chinook
salmon, and Interior Fraser coho salmon), although none have been listed under SARA. Listing a
population as Endangered or Threatened under SARA involves required, formal recovery action planning,
while COSEWIC listing alone may or may not result in formal recovery efforts. Information regarding
recovery planning for Cultus sockeye salmon is provided as an example: the COSEWIC listing of the
population in 2002 triggered formation of a recovery planning team, and subsequent listing under SARA
was expected (COSEWIC endangered status is followed within nine months by consideration for SARA
listing). Ultimately, Cultus sockeye salmon was not listed under SARA, given projected high socio-economic
costs. As a consequence of not listing, the recovery planning team did not develop a formal recovery action
plan, although some recovery measures were implemented.
The recent Cohen Commission proceedings and final report regarding declines in Fraser River sockeye
salmon included criticism of the failure to list Cultus Lake sockeye under SARA and indicated a mixed
record of recovery implementation. As specifically pertains to harvest management, following a significant
reduction in the Cultus sockeye exploitation rate in 2005, exploitation rates were allowed to drift upward
again, and have exceeded the target exploitation rate four times in the most recent seven year period for
which data are available (2004–2010) (Cohen, 2012).
Canada’s Policy for Conservation of Wild Pacific Salmon (DFO, 2005) (Wild Salmon Policy or WSP),
described above, represents another opportunity to integrate conservation objectives with fisheries
management. The policy indicates conservation of biodiversity to be a DFO objective and defines a level of
biodiversity at the CU level that DFO intends to conserve. The policy’s definition of CU focuses upon the
time required for recolonization of habitat should it be vacated by extirpation of a population, thereby
amounting to a variant of Crandall’s concept of ecological exchangeability (Crandall et al. 2000). If
recolonization is unlikely to occur within an “acceptable time frame” (upwards of 10 generations), the
population is declared a separate CU. Applying a method that incorporated all three of Waples’ axes
(ecology, life history, and biochemical genetics), 457 CUs were delineated in British Columbia for five
species of Pacific salmon (Waples et al., 2001; Holtby & Ciruna, 2007). The large number of CUs compared
with the quantity of ESUs in the Pacific Northwest demonstrates that occurrence of natural recolonization in
short time frames requires a very high degree of similarity, a higher degree than implied by the definition of
the ESU.
www.msc.org/science-series/volume-02
95
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
The Wild Salmon Policy contains six strategies:
1. Standardized Conservation Unit (CU) status monitoring and benchmarking,
2. Habitat assessment,
3. Maintaining and restoring ecosystem integrity,
4. Strategic planning and integration of planning results into fisheries management,
5. Annual program delivery, and
6. Performance review.
Most implementation to date has focused upon Strategy 1, with status benchmarks having been developed
for Fraser River sockeye salmon and under development for Skeena River sockeye salmon. It is not yet
clear how CU status versus benchmarks will be integrated into fisheries management planning as part of
Strategy 4.
Japan
The Japanese Ministry of the Environment maintains a Red List of endangered species that can include
sub-species. Listed salmonids include Sakhalin taimen and masu salmon of western Japan and the Kanto
Region (Ministry of the Environment, 2013). We did not find other evidence of the delineation of salmon
sub-stock or population units for conservation or research purposes.
Pacific Northwest, USA
The concept of the Evolutionarily Significant Unit was first introduced in 1986 in terms of its broad
application to ecology and conservation biology, and was then incorporated into a National Marine
Fisheries Service policy focused upon organizational planning with respect to the Endangered Species Act
(Ryder, 1986; Waples, 1991). The Endangered Species Act of 1973, in accordance with a 1978
amendment, includes distinct population segments (DPS) in its definition of species. Populations or groups
of populations are considered distinct if they represent an Evolutionarily Significant Unit (ESU), i.e., if the
unit represents significant adaptive variation (Ryder, 1986). The linkage between the Endangered Species
Act and the concept of the ESU encouraged efforts to apply the DPS and ESU definitions consistently, and
anadromous salmonids came to stand out as a particularly troublesome species group due to their rich and
important life history diversity.
Waples (1991) developed a two-pronged test for salmon ESUs, declaring their status dependent upon: 1.
the degree of reproductive isolation of a population unit, and 2. a population unit’s importance in the
evolutionary legacy of the species. The definition was then applied in several coast-wide reviews of the
status of seven species in the Pacific Northwest, the five Pacific salmon species and steelhead and
cutthroat trout (Weitkamp et al., 1995; Busby et al., 1996; Hard et al., 1996; Gustafson et al., 1997;
Johnson et al., 1997, 1999; Myers et al., 1998). These reviews yielded a schematic for the delineation of
ESUs for salmon throughout the region; there are currently 58 of these units for the seven species, and
several of these ESUs are currently listed as endangered or threatened under the Endangered Species Act
(Waples et al., 2001).
Waples’ (1991) technical memorandum did not end debate over what constitutes an ESU. Rather it fueled it
through the tension between reproductive isolation and adaptive variation that is implicit within his
definition. Gene flow does not occur under conditions of reproductive isolation, while adaptive variation (a
characteristic of a population’s importance in terms of evolutionary legacy) can arise under gene flow and
might depend upon it for continued variability (Crandall et al., 2000). Several authors have therefore worked
to refine the ESU definition further. Moritz (1994) posited that focus upon historical population structure and
prioritization of reproductive isolation (as particularly indicated by reciprocal monophyly through genetic
analyses of mitochondrial DNA) over adaptive variation was most sensible.
www.msc.org/science-series/volume-02
96
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
While recognizing the simplicity of the Moritz (1994) definition, Crandall et al. (2000) argued that adaptive
variation cannot be dismissed, and that focus upon mitochondrial DNA analysis excluded plant species
from consideration. He proposed emphasis upon variation in phenotypes through the concept of ecological
exchangeability, which was coupled with genetic exchangeability as the foundation of population
distinctiveness and a null hypothesis for whether or not a unit should be considered an ESU. According to
Crandall, “the central idea of ecological exchangeability is that individuals can be moved between
populations and can occupy the same ecological niche or selective regime”. Ecological exchangeability can
be explored with genetic analysis, while another option involves gathering of ecological evidence (life
history traits, morphology) and overlaying it upon the underlying genealogy of the population, with
subsequent application of statistical methods. Genetic exchangeability, meanwhile, focuses upon gene flow
between populations, as indicated by a variety of molecular techniques (i.e., not only mitochondrial DNA
analysis). In a nod to Moritz, Crandall also made a distinction between historical and recent adaptive
distinctiveness. When grouped with ecological and genetic exchangeability, the historic or recent adaptive
distinctiveness of a population makes for sixteen possible scenarios, for which conservation management
recommendations are provided.
Waples et al. (2001) described different dimensions to look for similarities or differences, or what are
sometimes called different axes, than those used by Crandall. Ecology, life history, and biochemical
genetics are three axes that are treated separately in this comprehensive examination of Pacific Northwest
salmon populations. While the three axes are considered effective in characterizing diversity, their
interchangeability was also indicated in the results (i.e., if data for one type of analysis is lacking, the other
two can be used as proxies due to the strong correlations found among the three axes).
Listing of salmon ESUs under the Endangered Species Act has resulted in federal agencies assuming
some management responsibilities that formerly belonged to states with respect to the listed ESUs, and
allocation of federal funding toward extensive recovery planning actions. With listing, five-year status
reviews are also coordinated by the National Oceanographic and Atmospheric Administration (NOAA).
Recovery plans have generally been developed to address all of the “4 H’s” (habitat, hydropower, harvest,
and hatcheries) comprehensively, but the details regarding integrated harvest planning elements of
recovery planning differ among the various ESU plans. For example, with respect to Puget Sound Chinook
salmon, the recovery plan for the ESU is considered to have been completed. Even so, a harvest
management plan was put into effect in 2011 that includes as one of its objectives achievement of
compliance with the Endangered Species Act jeopardy standard (the “salmon 4(d) rule”) (Puget Sound
Tribes and WDFW, 2010). While the Endangered Species Act prohibits take of endangered species, an
exception is made for salmon if the take does not “appreciably reduce the likelihood of survival or recovery”
according to this rule (included in the Federal Register of Rules and Regulations as 70 FR 37160).
The harvest management plan sets lower and upper management thresholds for 22 Chinook stocks
(“Management Units”) in Puget Sound, and harvest rules are described for each of three scenarios: 1. if
population status falls below the lower threshold, 2. if stock status falls between the two thresholds, and 3. if
stock status exceeds the upper threshold. When stock status falls below the lower threshold, a critical
exploitation rate ceiling is triggered. The management plan only impacts harvest control actions in
Washington and Oregon treaty and non-treaty fisheries—Southeast Alaska and British Columbia troll
fishery harvest of Puget Sound Chinook salmon is governed by the Pacific Salmon Treaty, which does not
directly link with Endangered Species Act recovery planning.
www.msc.org/science-series/volume-02
97
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Russia
The Russian Federation Red Book, under the jurisdiction of the Ministry of Natural Resources, is the main
vehicle for endangered species conservation in Russia. Underlying legislation indicates that sub-species
and populations, as well as species at large, are eligible for listing in the National Red Book. Listed
salmonid populations include Kamchatka steelhead salmon, steelhead salmon of the Shantar Islands, and
Sakhalin taimen of Sakhalin Island. According to the Fisheries Act of 2004, harvest of Red Listed-species is
generally not allowed, with room for exceptions (Russian Federal Law 166-F3). There are also Red Books
for each region (i.e., Oblast, Krai, etc.) of the Russian Federation.
In addition to the delineation of population units for the purpose of Red Book listings, there are some other
cases of research interest in sub-stock structure. Kamchatka River sockeye salmon have received
particular attention. While the fishery is managed to achieve a single escapement goal, migration and life
history-focused research has indicated the presence of five distinct sub-stock components in the basin.
These sub-stock components have varying migration timing, body size, spawning and rearing locations,
and proportions of early and late run components (Bugaev, 2010). In the absence of genetic stock
identification studies indicating the proportion of fishery harvest that the various sub-stock components
account for, fisheries management employs spatial and temporal closures in the effort to ensure that
adequate run-timing diversity is represented in total escapement (TINRO, 2012).
Trans-Pacific
Some efforts have been undertaken to delineate salmon population units at a single scale across the North
Pacific, encompassing both at risk and healthy populations. Notably:
• Pinsky et al. (2009) evaluated the conservation value of 7,159 basin-specific salmon populations
across the Pacific Rim, covering 74% of the range of six species of Pacific salmon. Data gaps were
addressed through data modelling based upon estimates of habitat capacity. Results were
compiled in an Atlas indicating extinction risk within 66 eco-regions delineated according to
dominant marine circulation patterns, ocean production domains, and watershed boundaries
(Augerot & Foley, 2005).
• An IUCN study of sockeye salmon population status across the Pacific Rim delineated 98
population units characterized by reproductive isolation (Rand, 2008).
Recommendations: Stock Management Units and Scoring
First, we take the term stock to mean a group of fish managed together, similar to the SMU concept. When
finer-scale designations are needed for conservation purposes, we will adopt the convention of calling
these sub-stocks. We use the terms sub-stocks and populations interchangeably. Among the various
management authorities for Pacific salmon, a wide variety of approaches have been adopted in the
delineation of units for management and conservation of Pacific salmon. There are, however, exemplary
practices shared by more than one authority that can be considered representative of a standard:
•
•
•
Fisheries are managed to achieve objectives at the stock scale, but sub-stock or population-scale
units are also delineated for conservation and research purposes;
When stock status problems are detectable, benchmarks for sub-stock or population units are
established and stock status against the benchmarks is monitored; and
Amidst stock-status problems, provisions linking conservation unit status with management of
stock units are enacted. Generally conservation unit benchmarks have not replaced reference
points, but reference points can be adjusted on the basis of conservation unit information, or
harvest control rules can be adapted to account for sub-stock or population status.
www.msc.org/science-series/volume-02
98
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
As salmon fisheries are fairly universally managed to achieve quantitative objectives at the stock scale, we
agree with the MSC draft salmon default assessment tree’s adoption of the Stock Management Unit (SMU)
as the basic unit of scoring for Principle 1 performance indicators. It is also important that certification
bodies verify that the harvest strategy is adequately precautionary to conserve nested sub-stock or
population diversity. The draft assessment tree addresses this need in scoring issue (d.) of performance
indicator 1.1.2 (Reference Points), which examines whether or not reference points for stocks likely
maintain the diversity and productivity of the component populations.
Were certification bodies to adopt sub-stock units as basic units of scoring, those scoring the fisheries
would immediately run into data gaps, which would hinder scoring. The question of scale would also be
difficult to address (i.e., should British Columbia with its 457 CUs be held to the same standard of
population health as the Pacific Northwest with its 58 ESUs?). If an effort were to be made to delineate
units at a single scale across the North Pacific (see Trans-Pacific section above), many units would not line
up with those of management authorities, resulting in data gaps that could only be filled in through data
modelling. Such an effort would lie outside of the scope of a fishery sustainability assessment.
While stock units are delineated at different scales, the various management authorities have committed to
managing fisheries at the stock level, which is a unifying commonality of these units. Historical and recent
data availability is best at this scale, as most management authorities’ monitoring resources are devoted to
generating data directly used in fisheries management.
It is difficult to eliminate all scorer subjectivity from the equation. Some fisheries, for instance Fraser
sockeye salmon with its run-timing aggregates and modelled stocks, integrate data from units at multiple
scales into management of the fishery, leaving the certification body with a decision regarding the scale at
which to delineate SMUs. Certification bodies will also need to assess the adequacy of data indicating
population health. We consider it sensible to expect more detailed information on population status from
those management authorities that are facing stock status problems.
Limit Reference Points
In the draft MSC default assessment tree for salmon (2012), performance indicator 1.1.1 (Stock Status)
contains two scoring issues, (a.) and (b.). Issue (a.) focuses upon stock status in relation to “recruitment
impairment”, while issue (b.) explores stock status in relation to “target reference point (e.g. a target
escapement goal)”. Only Issue (a.) contains a benchmark at the “60” scoring goalpost, highlighting the
importance of defining a point below which recruitment of a Stock Management Unit is impaired. In cases
where a limit reference point (LRP) is defined by management, it will be adopted by the certification body
for the purpose of assessment of performance indicator 1.1.1. However, limit reference points are seldom
defined in salmon fisheries, and the MSC default requirements, which state the default LRP should be ½
Bmsy, may not be applicable to salmon fisheries.
In the effort to address whether or not the default Limit Reference Point (LRP) is appropriate for salmon and
explore the significance of the LRP with respect to impairment of recruitment, we will first address the
evolution of the limit reference point concept in general fishery stock assessment. Then we will survey
existing applications of the limit reference point concept in salmon fisheries, as well as reference points that
have been proposed in literature but not put into practice. We will also explore the question of whether or
not recruitment impairment is a relevant concept for salmon fishery management. Because many salmon
fisheries are managed with target reference points, we also include information regarding escapement goal
types and the methods used to establish them around the Pacific Rim.
www.msc.org/science-series/volume-02
99
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Historical Development
Throughout the period from the late 19th Century to the present, fisheries scientists have attempted to use
mathematics to develop a language, a theory, and practice to sustain fisheries while providing the greatest
possible benefits. Quinn (2003) credits Baranov’s catch equation (derived around 1910) as a foundational
step. To understand this simple equation, we first define N0 and C as a stock size at the beginning of some
period and the catch at the end of the period, respectively, and we denote the length of the period as t.
Then Baranov’s catch equation uses two parameters, F and M, which describe fishing and natural mortality,
so as to functionally relate C to N0:
𝐶=
𝐹
𝐹+𝑀
�1 − 𝑒 −(𝐹+𝑀)𝑡 �𝑁0 .
In other words, the stock will produce catch C if the fishing mortality—which is under the control of fishery
management—is set to some level F, given that the stock started at size N0 and that natural mortality is
fixed at level M. Note that this equation does not allow for any addition or recruitment to the population
during the period. A notion of recruitment is a further step, beyond Baranov’s equation, in developing a
more complex mathematical representation of fishing and a fish population. Baranov’s catch equation can
be further developed to describe the size of the stock after fishing, and, importantly, this remaining stock
will serve as the seed for future recruitment to the stock.
Various designations of specific values of F form much of the language of fishery population dynamics.
Often these specific values are referred to as target reference points—specific targets that will, in principle,
maximize some benefit by controlling fishing mortality to some target level. The search for these rules—or
targets—is sometimes called optimal harvesting (Quinn & Deriso, 1999). Perhaps the most important
example is the pursuit of the fishing mortality that is intended to produce maximum sustainable yield, or
MSY as it is often called. In this case the benefits from the fishery are measured as yield (usually measured
in weight or biomass, but not always). A maximum is found at a fishing mortality level that trades off large
benefits now balanced against restraining fishing in the present so that the stock size will have sufficient
size to allow for adequate future reproduction to produce large benefits at a later time. The exact balance is
achieved when F is set to a specific fishing mortality denoted Fmsy. Larkin (1977) was an early and
influential critic of the MSY concept, arguing that MSY is neither feasible nor desirable as an economic
objective. Although there have been many criticisms of the concept, it is still commonly in use in fisheries
around the world.
As fisheries population dynamics theory was further developed, an extensive body of literature emerged
devoted to describing the yield of a stock based on the biomass of the stock, such as the Pella-Tomlinson
equations (e.g. Quinn & Deriso, 1999). Using these kinds of approaches, target reference points are
expressed as specific values of biomass of the stock, denoted B, with Bmsy denoting the biomass that can
support the maximum sustained yield. Others have extended these ideas of simple target reference points.
Quinn et al. (1990) and others have argued for a threshold-based management that operates under
different control rules depending on the size of the stock relative to pre-determined threshold levels.
Reflecting a greater awareness in the 1970s and 1980s that some target reference points were in some
sense “riskier” that others, fishery theorists began to consider the economic benefits of risk-averse harvest
policies that might produce benefits below the level intended to maximize sustained yield, but with lower
probabilities of failure. One important example is the F0.1 level, which is widely accepted as a conservative
fishing strategy. Notably, this reference point is simply based on a rule of thumb (Hilborn & Walters, 1992),
and, as such, is just an arbitrary fishing level that has been shown by experience to have a practical value.
In the real world, the highly consistent mathematical models of fish stocks must be replaced by statistical
estimates of model parameters, and the statistical models are often based on an incomplete understanding,
questionable assumptions, and noisy and inconsistent data. One reaction to a greater awareness of risk
was a call for additional reference points beyond just the target reference points—reference points that
www.msc.org/science-series/volume-02
100
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
would be helpful for defining overfishing or other conditions that should be avoided. In defining limit
reference points, Caddy & Mahon (1995) had this to say:
[A limit reference point, or LRP] may either correspond to some minimum condition (e.g. a
dangerously low spawning biomass) or some maximum condition (a high rate of decline in stock
size, or a high mortality rate) at which point a management response which has been negotiated
earlier with the participants in the fishery, is automatically triggered. For new fisheries, or those in
developing countries where the information required to use the mathematical fisheries models is
often not available, qualitative or semi-quantitative criteria also can be used directly as LRPs. Even
when there is adequate information for the definition of sophisticated LRPs, but there are broader
ecological concerns about the sustainability of benefits due to the possible impacts of exploitation
on the ecosystem, it may be desirable to set LRPs using a precautionary approach.
In the United States, the Magnuson-Stevens Fishery Conservation and Management Act lays out national
standards for fisheries managed under the Act. The Act requires that, “…management measures shall
prevent overfishing while achieving, on a continuing basis, the optimum yield from each fishery…”
Translating this requirement into actual policy has fallen to the National Marine Fisheries Service. In 2009,
the National Marine Fisheries Service held a meeting of the Scientific and Statistical Committees
(committee of scientific advisors charged with giving advice to the Management Councils described in the
Act), and included limit reference points and the prevention of overfishing as topics of the meeting. One of
the key findings at the workshop was that there has been a great deal of variation in how the different
councils have approached the task of preventing overfishing. Reporting on the workshop, Witherell (2010)
stated, “The different approaches reflect how each council, SSC, and each NMFS region have interpreted
the guidelines and worked towards different approaches based on availability and frequency of stock
assessments, as well as differences in data availability across the regions”. Recognizing that not all
fisheries have the benefit of an extensive analysis, Witherell (2010) stated:
In some cases, little may be known other than catch and even this may be associated with
uncertainty. In such cases, direct quantification of overfishing limits and other quantities may
appear infeasible. Nevertheless, some evaluation of the status of current levels of fishing is a
necessary first step. This first step could be a classification of stocks by scientists and locally
knowledgeable people into one of four categories of fishery impact. This is essentially a stock
assessment tailored to the data that is available and should be conducted with adequate
transparency and an appropriate level of review. This classification should be accompanied and
guided by a productivity-susceptibility analysis of the species.
In summary, no strong consensus has emerged as to exactly how to set limit reference points for marine
fisheries, and if there is a consensus, it is that reference points need to be appropriately tailored to the
specific local situation.
Guiding Principles in Salmon Fishery Management
The theory, language, and practice of fishery management of marine fisheries are often simply not shared
by managers of Pacific salmon. For example, Baranov’s catch equation is hard to apply to Pacific salmon
and it may be inappropriate to do so. Salmon management requires a substantially different approach for
many reasons: 1. Pacific salmon are semelparous, meaning that the fish die after spawning so that fish not
harvested cannot remain part of the stock in future years; 2. the harvest of Pacific salmon often takes place
in a very limited time as the fish are returning to their natal rivers to spawn, so t and M are not useful
concepts for salmon managers; 3. Pacific salmon in a single stock spawn in fresh water at approximately
the same time, so that their stock size can be accurately and precisely measured without questionable
statistical models; and 4. while the run is actually underway the run strength can be judged, so that an
www.msc.org/science-series/volume-02
101
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
active and adaptive management system can harvest all of the stock that is surplus to spawning needs,
while still protecting future production. Taken together, this means that many reference points familiar to
managers of marine fisheries simply have limited utility to salmon managers.
Salmon management is often guided, at least conceptually, by the notion of the stock-recruit relationship
(Quinn & Deriso, 1999), which is an attempt to use mathematical models to describe the number of fish that
will be produced in the future (recruitment) based on the number of fish allowed to spawn (stock, or at other
times called the escapement). Although many stock-recruit models have been proposed, generally the
Ricker (1954) and Beverton & Holt (1957) models provide the conceptual and often the statistical models
that actually guide Pacific salmon management. The obvious difference between these two models is what
they predict at very high stocks sizes. The Beverton-Holt model predicts that salmon recruitment will reach
a plateau as stock size is increased beyond some level. This is what you might expect would happen if, for
example, all of the spawning habitat were to be used up so that later spawners were just digging up the
eggs of the previous spawners. The Beverton-Holt model also predicts that as the stock size declines below
what the carrying capacity of the habitat can support, the recruitment in the future will decline but never fail
entirely until the stock size reaches 0. Under this model the maximum sustainable yield is found at an
intermediate stock size (Smsy), well below the stock size that produces maximum recruitment. In contrast,
the Ricker models predicts that as spawning level increases past the carrying capacity the recruitment will
actually decline. This is what you might expect if very high egg density were to trigger disease outbreaks,
for example. Under Ricker’s model, the maximum sustainable yield is also found at an intermediate stock
size, well below the stock size that produces maximum recruitment. Importantly, both models predict the
same basic behaviour at low stock sizes: individual survival will increase as stock size goes down. When
animals experience lower mortality (higher survival) as density decreases, this is called compensatory
mortality, and both the Ricker and the Beverton-Holt models predict faster and faster population increases
as stock size declines (Quinn & Deriso, 1999 and many others).
If the commonly used stock-recruit functions are our conceptual guide, are there any natural reference
points that can be used as limit reference points in practical salmon fishery management? Is there an
obvious reference point that can be used to detect a stock size level that that will likely lead to an
impairment of recruitment? First it is important to realize that all of these fishery models are simply
mathematical functions, and that real fishery populations, in the real world, are not governed by, nor
constrained by, these functions. There might very well be stock sizes below which recruitment patterns are
persistently altered, where ecosystems are shifted, or where future fishery yields are jeopardized by
recruitment impairment. However, there is no stock size level where recruitment is threatened under the
Ricker or the Beverton-Holt model, nor are there any predictions about recruitment risk at specific stock
sizes for Pacific salmon populations based on accepted scientific consensus.
Although most agencies have been trying to find a consensus about limit reference points, the specific
reference points are not easily derived from the usual stock-recruit models. A survey of relevant
developments among various salmon management authorities and regions follows below.
Alaska
As we previously pointed out, the State of Alaska has defined a sustained escapement threshold (SET) as
their limit reference point for Pacific salmon, and it formally adopted the definition of a conservation concern
as the inability to maintain escapements above a sustained escapement threshold (ADF&G, 2001).
However, Alaska Department of Fish & Game (ADF&G) has never estimated nor implemented one of these
escapement thresholds for a stock under actual management. Munro & Volk (2012) reported on annual on
Alaska-wide escapement performance, and they explained that the sustained escapement threshold has
never been put into practice. They also noted that “methods to develop stock-specific sustainable
escapement thresholds…are not well developed for Pacific salmon”.
www.msc.org/science-series/volume-02
102
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Besides conservation concern, other regulatory statuses of lesser severity (yield concern and management
concern) have been applied to particular stocks in Alaska since its 2001 adoption of the policy for the
sustainable management of salmon fisheries. Stock status and quality of recovery efforts focused upon
these stocks were assessed by Marine Stewardship Council under performance indicator 1.2.2 in its 2007
assessment of the Alaska salmon fishery. Sustainable Fisheries Partnership has conducted a statistical
analysis exploring linkage between MSC scores and stock escapement performance. On average, these
Alaskan stocks of regulatory concern did not achieve their escapement goals in five of the fifteen years
leading up to certification (Sustainable Fisheries Partnership, 2013).
ADF&G reports annually to the National Marine Fisheries Service (NMFS) on the status of stocks targeted
by the Southeast Alaska troll fishery (Steve Heinl, Alaska Department of Fish and Game, pers. comm.,
March 27, 2013). This reporting occurs under the auspices of the Fishery Management Plan for the Salmon
Fisheries in the Exclusive Economic Zone off the Coast of Alaska, and is intended to illustrate consistency
between ADF&G management and the Magnuson-Stevens Act. Stock status is compared with minimum
stock size thresholds described in Appendix 6 of the Plan.
This minimum stock size threshold is defined to be equal to half of each stock’s target reference point
(escapement goal). There is no explicit relationship between minimum stock size thresholds and
sustainable escapement thresholds, but the NMFS thresholds can be considered proxies for sustainable
escapement thresholds while they are not explicitly defined by ADF&G. For those stocks that have
escapement goals expressed as ranges, minimum stock size thresholds amount to half of the escapement
goal lower bound except in the case of Chinook Technical Committee-reviewed Chinook escapement
goals, where they are equal to half of the midpoint between the escapement goal lower and upper bounds
(NPFMC & NMFS, 1990). Of all Alaskan stocks of regulatory concern assessed by MSC in 2007, these
stocks averaged two occurrences of stock sizes below the minimum stock size thresholds in the fifteen
years leading up to certification (Sustainable Fisheries Partnership, 2013).
If proxy limit reference points are to be derived from escapement goals, it is sensible to survey the types of
escapement goals currently in use in Alaska, and the methods used to establish them. Three categories of
escapement goals (a target reference point, as we have defined the term above) have been developed for
salmon management in Alaska (Munro & Volk, 2012). One target reference point is defined as the
biological escapement goal, and this is the goal intended to produce maximum sustainable yield. These
reference points are developed for systems with extensive research history. Many systems without this
extensive research history have goals that are simply intended to sustain yields, and the maximum potential
sustainable yield is simply not estimated. These targets are called sustainable escapement goals. In other
cases, goals have been set to “meet a specific management objective for salmon escapement that
considers biological and allocative factors...” (optimal escapement goals). In this latter case there may or
may not be an estimate of maximum sustainable yield (stock definitions are found in the Alaska
Administrative Code: 5 AAC 39.223).
Of the 300 escapement goals currently used in Alaskan salmon management, the majority (>60%) are
categorized as sustainable escapement goals. Most stocks with sustainable escapement goals do not have
sufficient research information to conduct a Ricker spawner-recruit analysis and a goal therefore cannot be
established upon that basis. There are 11 additional methods used to establish escapement goals in Alaska
(Table 1). Some of these methods, such as yield analysis (Hilborn & Walters, 1992) are found in standard
fisheries population dynamics references. Other methods, such as the unpublished percentile method,
appeal to common sense. In this case, escapement goals are simply set using predetermined percentiles,
th
th
such as the 25 and 75 percentiles (the range where the middle 50% of historic observations lie) of the
previous observed escapements. Yet other methods, such as the Euphotic Volume Model (Koenings &
Burkett, 1987), are based on limited data analysis, were developed in the 1980s, and the methods have
subsequently received no independent research to demonstrate that they work. Other methods have only
been published as in-house technical reports, and these do not seem to have been embraced outside of
Alaska (e.g. the risk analysis approach).
www.msc.org/science-series/volume-02
103
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Table 1: Methods used to establish escapement goals in Alaska (Munro and Volk, 2012)
No.
1
Method
Brood Interaction
Simulation Model
2
Conditional
Sustained Yield
Analysis
Empirical
Observations
3
Description
Simulates production using a spawner-recruit model, takes
into account age-structure, and estimates catches and
escapements under user-specified harvest scenarios.
Observed escapement and harvest are used to estimate
the yield that results from a particular escapement goal
range.
Method of developing goals for data-poor stocks using
average escapement over time or the value of a low
escapement for which there is evidence that the stock can
recover.
Measurement of the proportion of a lake’s volume where
enough light penetrates to support primary production is
used to estimate sockeye salmon juvenile biomass.
The relationship between lake surface area and
escapement is used to estimate adult sockeye salmon
production.
Percentiles are assigned to observed escapements in
order to assign lower and upper goal bounds.
Analysis of the relationship between escapement and
subsequent production of the next generation of adults
using the Ricker 1954 model.
Risk of management error is estimated and incorporated
into escapement goal estimation.
4
Euphotic Volume
Model
5
Lake Surface Area
6
Percentile Method
7
Ricker SpawnerRecruit Analysis
8
Risk Analysis
9
Spawning Habitat
Model
Species-specific estimates of spawning capacity in a
particular watershed are used to set goals.
10
Theoretical
Spawner-Recruit
Analysis
Information from neighbouring stocks or species-specific
generalizations is used in modeling when there is
insufficient or no stock-specific harvest and/or age data.
11
Yield Analysis
The escapement range with the greatest associated fishery
yields is identified.
12
Zooplankton
Model
Measure of a lake’s zooplankton mass is used to calculate
the number of sockeye salmon juveniles that can be
supported.
Focal goal type(s)
optimal escapement goals
(e.g. Kenai River sockeye
salmon)
sustainable escapement
goals (e.g. Kodiak pink
salmon)
sustainable escapement
goals (e.g. Norton Sound
pink salmon stocks)
sustainable escapement
goals for sockeye salmon
sustainable escapement
goals for sockeye salmon
sustainable escapement
goals for all species
biological, sustainable and
optimal escapement goals
for all species
sustainable escapement
goals for non-target stocks
of all species
sustainable and biological
escapement goals for
Chinook, coho, and
sockeye salmon
sustainable and biological
escapement goals for
Chinook, coho, and
sockeye salmon
sustainable and biological
escapement goals for
various species
sustainable escapement
goals for sockeye salmon
Among the methods for escapement goal setting in Alaska, use of the percentile method is becoming
increasingly frequent. In setting a new sustainable escapement goal in an area without a previous goal, the
percentile method has many advantages. It is simple and easy to understand and, if the fishery has been
stable, then these previous escapements have been shown by experience to sustain a fishery. However,
there are also cases where this method has been used repeatedly amidst declining escapements, resulting
in a downward trajectory for the escapement goals.
The choice of what data to include in modelling and the schedule of escapement goal re-evaluation are key
determinants in the levels of the resulting goals. In Alaska, goals are generally evaluated every three years
on a district basis, although goals are also sometimes evaluated out-of-schedule. The choice of data
included in modelling varies from stock to stock.
www.msc.org/science-series/volume-02
104
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
British Columbia
In contrast to Alaskan salmon fishery management, limit reference points are in use in some British
Columbia district salmon fisheries. These reference points are generally not derived purely from abundance
trend information, but also take into account trade-offs between lost harvest cost and extinction risk, as well
as implications of productivity and abundance differences among stocks harvested in mixed-stock fisheries
(Chaput et al., 2013). A survey of existing limit reference points follows:
1. The Fraser River sockeye fishery management system includes limit reference points for the four
run-timing groups targeted by the fishery through application of Total Allowable Mortality (TAM)
rules. The current form of the TAM rule considers projections of mortality of migrating adult sockeye
in the Fraser River due to adverse environmental conditions (high water temperature and river
discharge). The total mortality including fishing mortality is currently capped at 60% when stock
status is above the upper escapement reference point. This cap is less than exploitation at MSY.
This was a precautionary policy choice to ensure robustness against uncertainty (e.g. estimates of
productivity and capacity, changing in-season run-size estimates, implementation error) and to
protect populations that are less abundant or less productive. The TAM rule for some run-timing
stock aggregates is also constrained by recovery efforts for specific stocks of concern (e.g. Cultus
Lake sockeye). Commercial fishing is set to near zero at run sizes below cut-off points described in
annual TAM rules. The rules are generated through application of the Fraser River Sockeye
Spawning Initiative (FRSSI) model, a multi-variable simulation model that incorporates spawnerrecruit data (Larkin models for those stocks that exhibit cyclic abundance trends and Ricker 1954
models for all other stocks) for 19 stocks and predicts outcomes of various harvest strategies 48
years into the future (Pestal et al., 2011)
The performance of each harvest strategy and the values of the limit reference points have been
assessed using indicators that reflect the objectives of (1) remaining above lower escapement
benchmarks of individual stocks in a simulated mixed-stock fishery with a specified probability, and
(2) accessing catch-related benefits from the stock aggregate. FRSSI model performance is also
assessed under assumed projections of varying trends in productivity. The lower escapement
benchmarks are currently considered interim until formal Wild Salmon Policy (WSP) benchmarks
are finalized for Fraser sockeye. Once WSP benchmarks are fully implemented in the harvest
management process, the formal lower WSP escapement benchmarks will be adopted. Sgen,
defined as the stock size necessary for rebuilding to Smsy within one generation in the absence of
fishing, is considered the most appropriate choice among candidate benchmarks explored by Holt
(2009). It is difficult to express what the TAM exploitation rate cut-off amounts to for each modelled
stock in terms of Smsy (due to the inclusion of aggregations of multiple stocks in the model), but Sgen
is in the range of 0.5Smsy or less at the scale of each run-timing group (Chaput et al., 2013).
2. The management of the Barkley Sound sockeye fishery off the west coast of Vancouver Island
employs an abundance-based harvest control rule to balance the trade-off between catch and
escapement of the two primary stocks in mixed-stock fisheries (Sproat Lake and Great Central
Lake sockeye). Biological limit evaluation benchmarks were established through Wild Salmon
Policy implementation (see below), and that has informed the establishment of limit reference
points used in fishery management. Lower biological benchmarks for the Sproat and Great Central
Conservation Units were incorporated into a fishery limit reference point equivalent with Sgen, the
stock size necessary for rebuilding to maximum sustainable yield within one generation (Chaput et
al., 2013).
www.msc.org/science-series/volume-02
105
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
3. The Skeena sockeye fishery is managed to meet mixed-stock aggregate objectives of the Tyee test
fishery located in the lower basin. Currently, if escapement past the test fishery is less than 400,000
fish, no fishing is allowed (including First Nations Food, Social, and Ceremonial fisheries). If less
than 1,050,000 fish pass the test fishery, no commercial fishing is allowed (only First Nations Food,
Social, and Ceremonial and recreational fisheries are permitted). As with the Fraser TAM rule cutoffs, the Skeena reference points result from multi-stock modelling (albeit with less data than that
available for the Fraser River) and precautionary planning, and are not derived from a particular
parameter of a single stock (Cox-Rodgers et al., 2010; DFO, 2012).
4. Aggregate Abundance Based Management Chinook troll fisheries in British Columbia are managed
in accordance with the Pacific Salmon Treaty to achieve a spawning limit reference point, Slim, that
is equal to 85% of the spawning escapement that produces MSY. Missing the reference point in
two consecutive years results in reduced fishing pressure in the third year (i.e., Slim may be more
appropriately considered an escapement goal lower bound rather than a limit reference point, as
fishing is not completely curtailed in association with missed objectives) (16 U.S.C. 3631).
Other district salmon fisheries in British Columbia do not employ limit reference points. For example, pink
and chum salmon fisheries are generally managed to achieve target reference points known as
management escapement goals. These goals have been established using the yield analysis method
(Table 1). The fisheries are managed to achieve these single-point goals for broad stock units.
As part of the Wild Salmon Policy, a process for establishing new status benchmarks for salmon
Conservation Units was put into place. The decision to incorporate two benchmarks into the policy, i.e.,
target and limit evaluation benchmarks, rather than only a single target evaluation benchmark, represented
a landmark decision, despite the fact that these status benchmarks are not necessarily directly integrated
into harvest control rules (Holt & Irvine, 2013). The policy does include guidance regarding incorporation of
Conservation Unit status (measured against the new benchmarks) into the integrated harvest planning
process. Therefore, the policy could eventually result in the more widespread use of limit reference points in
management of district salmon fisheries.
As per the policy, the lower status benchmark is to be set at a high enough level so as to ensure a
substantial buffer between it and a level that would be considered to pose a risk of extinction. The group of
Department of Fisheries and Oceans Canada specialists involved in the choice of the most appropriate
lower evaluation benchmark type explored multiple threshold options described in literature before deciding
upon Sgen, the abundance of spawners that will result in rebuilding to Smsy under equilibrium conditions in
one generation in the absence of fishing. In simulations, this parameter was found to be more robust to
variability in stock productivity than other candidate abundance lower benchmarks. A second lower
benchmark expressed in terms of fishery mortality, Fmsy, was also recommended for use in Wild Salmon
Policy Conservation Unit status assessments (Holt, 2009). Currently Fmsy is not used as a benchmark to
assess biological status. Holt notes that Fmsy could be adopted in the future on a case-by-case basis
depending on the quality of assessment data. DFO's Fisheries Decision-Making Framework Incorporating
the Precautionary Approach (2009) 1 recommends that fishing mortalities remain below Fmsy.
Pacific Northwest
Amendment 16 of the West Coast Salmon Management Plan describes current limit reference points for
those Pacific Northwest salmon fisheries that are not governed by the Pacific Salmon Treaty. Fmsy is
established as the limit reference point in terms of fishing mortality, while 0.5Smsy is defined as the minimum
stock size threshold for most stocks, although some exceptions are also listed (several stocks instead use
0.75Smsy).
1
http://www.dfo-mpo.gc.ca/fm-gp/peches-fisheries/fish-ren-peche/sff-cpd/precaution-eng.htm
www.msc.org/science-series/volume-02
106
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Russia
No limit reference points are officially employed in management of Russian salmon fisheries. Most Russian
salmon is harvested in terminal fisheries (coastal traps or in-river gillnets and beach seines) managed to
achieve escapement goals expressed in terms of habitat capacity (percent of spawning grounds filled).
Goals for the dominant species of pink and chum salmon are derived in accordance with formulas of two
pink salmon spawners per square meter of spawning area and three chum salmon spawners per two
square meters of spawning area (Makeev, 2010). In Sakhalin Oblast, the spawning areas of 217 rivers
have been established, and escapement toward goals of 100% filled habitat capacity is monitored annually
through aerial and walking surveys (Sakhalin Oblast Regional Government, 1994). It has been noted that
some of these goals are based on out-dated habitat survey information and that some habitat capacity
estimates may be significantly lower than actual capacity (Makeev, 2011).
Information on goals used in other regions of the Far East and the models upon which they are based is not
as readily available as it is for Sakhalin. On Kamchatka, aerial surveys are used to monitor index portions of
streams for which goals have been established (in contrast with the full basin capacity goals used on
Sakhalin) (Shevlyakov, 2006). Ricker modelling has been used to set an escapement goal for Ozernaya
sockeye salmon (the largest Asian run of sockeye salmon), but it is unclear whether or not stockrecruitment modelling has been used to set management objectives elsewhere in Russia (MRAG Americas,
2012).
While the single target reference point of 100% filled habitat capacity represents the lone official target
reference point for which most Russian salmon fisheries are managed, anecdotally, 70–100% filling of
habitat capacity is considered acceptable, resulting in an informal escapement goal range.
Literature
In addition to the limit reference points described above that are currently in use in the management of
salmon fisheries, some reference points have been recommended for use in literature, but are not currently
being applied in practice.
Table 2: Limit reference points for salmon fisheries described in literature – derived partially from Chaput et al. (2013),
Table 4.2
Notation
S0.5Rmsy90
0.4Smsy
h*
0.2K
0.1Smax
Sgen2
Description
90th percentile of spawner abundance at 50% of recruitment at MSY
40% of spawner abundance at SMSY
Maximum sustainable harvest rate
15% of freshwater carrying capacity
10% of maximum spawner abundance
the stock size necessary for rebuilding to MSY within two
generations
Reference
Holt (2009)
Holt (2009)
Bradford et al. (2000)
Johnston et al. (2002)
Cox-Rodgers et al. (2010)
Korman Cox-Rodgers (2012)
Recommendations: Limit Reference Points and Scoring
In summary, limit reference points in actual use for salmon fishery management are various. It is important
to also note that some points did not evolve from clear consensus regarding risk to future fishery production
when stock size falls below the point. Usually such limit reference points evolve, as Caddy & Mahon (1995)
reported, “[as] a management response which has been negotiated earlier with the participants in the
fishery”. That is to say, limit reference points have a tradition of being derived pragmatically and without a
consistent theoretical basis. Even so, the benefits of introducing some standardization should be obvious.
In light of these facts, we recommend replacing the “60” scoring goalpost language in the default
www.msc.org/science-series/volume-02
107
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
assessment tree regarding “recruiting impairment” with a more general reference to the Stock Management
Unit falling below its minimum stock size threshold—which we define to be 0.5 times the lower
management stock size reference point (target reference point), or its equivalent.
In the cases described above, where limit reference points are already being used to manage a fishery, we
recommend that certification bodies apply the existing reference points in scoring performance indicator
1.1.1, issue (a.). Due to the need to achieve consistency when assessing stock status in salmon fisheries
against the MSC standard, it certainly makes sense to derive limit reference points for salmon from
escapement goals or their equivalent in those cases where limit reference points are not already defined.
Again, in the cases where escapement goals (or equivalent) are expressed as a range, we recommend
using the lower value as the target reference point. The current draft scoring guidance regarding 0.5Bmsy
equivalence is in alignment, at least in spirit, with limit reference points currently in use in British Columbia
and the Pacific Northwest, as well as with minimum stock size thresholds for Alaska. However, the concept
Bmsy is not usually used in Pacific salmon management. With respect to Alaskan stocks for which
escapement goals are expressed as ranges, we recommend that Certification Bodies align with guidance
regarding determination of minimum stock size thresholds in Appendix 6 of the Fishery Management Plan
for the Salmon Fisheries in the Exclusive Economic Zone off the Coast of Alaska.
As pertains to limit reference points for Russian fisheries where escapement goals are expressed in terms
of habitat capacity, it might seem that 50% of the official MSY-equivalent goal would amount to 50% filled
habitat capacity. However, if 70% of habitat capacity is taken as an unofficial lower escapement goal
bound, then the 0.5Smsy-equivalent should equal 35% filled habitat capacity. Meanwhile, there is existing,
non-Russian literature suggesting that 10–15% filled habitat capacity is an appropriate limit reference point
(Table 2). However, it should be noted that it is impossible to achieve perfect correspondence between
Russian and North American fishery parameters due to the different paradigms of fisheries management
employed in the two geographies. As a suitable, intermediate option (between 10-15% and 50%), we
recommend that certification bodies adopt 35% filled habitat capacity as the limit reference point for
fisheries managed to achieve habitat capacity goals.
Conclusion
After an extensive examination of the history of the stock concept and the history and current practice with
respect to limit reference points for salmon, we are in a position to confidently make several
recommendations. First, the Marine Stewardship Council’s stock management units are the appropriate
scale for scoring Principle 1 performance indicators. Most importantly, in spite of the criticism that the scale
of stock management units changes among fisheries and among jurisdictions, it is only at this stock
management unit scale that certifying bodies and scorers will consistently have readily available
information. Second, we conclude that usable limit reference points can appropriately be constructed from
currently published target reference points, which are available for most salmon fisheries in most
jurisdictions (Table 3). As a general approach, the simple and pragmatic idea of simply taking 0.5 times the
lower target reference point appears reasonable, and to the limited extent that there is a current practice,
this approach is consist with it. Our hope is that our analysis is helpful in support of MSC’s continuing work
to ensure fisheries sustainability and improve stakeholder understanding.
www.msc.org/science-series/volume-02
108
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Table 3: Target and limit reference points in salmon fisheries by jurisdiction
Management
Region
Existing Target Reference
Points
Existing Limit Reference
Points
1. Alaska
Three types of escapement
goals expressed in numbers of
fish:
Minimum stock size thresholds
(for stocks harvested by the
Southeast Alaska troll fishery):
50% of the escapement goal’s
lower value with the exception of
those Chinook salmon
escapement goals that have
been reviewed by the Pacific
Salmon Commission’s Chinook
Technical Committee (for these
stocks, the minimum threshold
amounts to 50% of the midpoint
between the escapement goal
upper and lower values)
•
Sgen (currently integrated into
the harvest control rules for
the Barkley Sound fishery,
foreseen in other fisheries in
the future)
•
•
•
•
•
2. British
Columbia
Biological Escapement
Goals (BEGs)
Sustainable Escapement
Goals (SEGs)
Optimal Escapement
Goals (OEGs)
Various escapement goals
expressed in numbers of fish
and specific to particular
fisheries, including:
•
•
•
•
•
Management Escapement
Goals (MEGs)
interim escapement goals
minimum escapement
goals
escapement goals
Slim (85% of the
escapement that produces
MSY – for Chinook)
•
Total Allowable Mortality rule
cutoffs (Fraser River
sockeye)
•
Tyee test fishery
escapement cutoff (Skeena
River sockeye)
Proxy Limit
Reference Points
(Suggested by the
Authors)
50% of the
escapement goal lower
bound
•
Sgen (if a
benchmarking
result is
available)
•
50% of the
escapement goal
lower bound
Various target harvest rates,
including:
•
•
•
3. Russia
4. Pacific
Northwest
harvest rate ceilings
fixed harvest rates
fixed Total Allowable
Mortality
escapement goals (generally
expressed in terms of habitat
capacity, i.e., 100% filled
habitat capacity)
Various escapement goals
expressed in numbers of fish
and specific to particular
fisheries, including:
•
•
escapement goals
upper management
thresholds
None
35% filled habitat
capacity
•
•
Minimum stock size
thresholds (generally 50% of
escapement goals, but with
some exceptions described
in Amendment 16 of the
West Coast Salmon
Management Plan)
50% of the
escapement goal
lower bound
www.msc.org/science-series/volume-02
109
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
References
Ackerman MW, Habicht C and Seeb LW (2011) Single-nucleotide polymorphisms (SNPs) under diversifying
selection provide increased accuracy and precision in mixed-stock analyses of sockeye salmon from the
Copper River, Alaska. Transactions of the American Fisheries Society 140(3):865-881.
ADF&G (Alaska Department of Fish and Game) (2001) Policy for the Management of Sustainable Salmon
Fisheries. Available at
http://www.housemajority.org/coms/jcis/pdfs/Sustainable_Salmon_Fisheries_Policy.pdf [Accessed March
2013]
Augerot X and Foley DN (2005) Atlas of Pacific Salmon. Berkeley, University of California Press.
Begg GA and Waldman JR (1999) An holistic approach to fish stock identification. Fisheries Research
43(1):35-44.
Beverton RJH and Holt SJ (1957) On the Dynamics of Exploited Fish Populations. Fishery Investigations
Series II Volume XIX, Ottawa, Ministry of Agriculture, Fisheries and Food.
Botz J, Hollowell G, Sheridan T, Brenner R and Moffitt S (2012) 2010 Prince William Sound area finfish
management report. Fishery Management Report No. 12-06. Anchorage, Alaska Department of Fish and
Game.
Booke HE (1981) The conundrum of the stock concept – are nature and nurture definable in fisheries
science? Journal of Fisheries and Aquatic Sciences 38(12):1479-1480.
Bradford MJ, Myers RA and Irvine JR (2000) Reference points for coho salmon (Oncorhynchus kisutch)
harvest rates and escapement goals based on freshwater production. Canadian Journal of Fisheries and
Aquatic Sciences 57:677-686.
Brazil C, Bue D, Carroll H and Elison T (2011) 2010 Kuskokwim area management report. Fishery
Management Report No. 11-67. Anchorage, Alaska Department of Fish and Game.
Bugaev, VF (2010) Sockeye of the Kamchatka River. Petropavlovsk-Kamchatksy, Kamchatpress.
Busack C and Marshall AR (1995) Defining units of genetic diversity in Washington salmonids. In: Genetic
diversity units and major ancestral lineages of salmonid fishes in Washington (C Busack and Shaklee JB,
eds). Olympia, Washington State Department of Fish and Wildlife.
Busby PJ, Wainwright TC, Bryant GJ, Lierheimer L, Waples RS, Waknitz FW and Lagomarsino IV (1996)
Status review of west coast steelhead from Washington, Idaho, Oregon, and California. NOAA Technical
Memorandum NMFS-NWFSC-27.
Caddy JF and Mahon R (1995) Reference points for fisheries management. FAO Fisheries Technical Paper
347. Rome, FAO.
Cannon J (2007) FishSource Scores: How they’re calculated and what they represent. Version 1.0.
Sustainable Fisheries Partnership Foundation. Available at www.fishsource.org/indices_overview.pdf
[accessed 1 March 2013].
www.msc.org/science-series/volume-02
110
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Carroll A (2005) What are escapement goals? Alaska Fish and Wildlife News. Available at
www.adfg.alaska.gov/index.cfm?adfg=wildlifenews.main&issue_id=23 [accessed 6 July 2013]
Chaput G, Cass A, Grant S, Huang A-M and Veinott G (2013) Considerations for defining reference points
for semelparous species, with emphasis on anadromous salmonid species including iteroparous salmonids.
Document 2012/146. Ottawa, Canadian Science Advisory Secretariat.
Cohen BI (2012) Commission of Inquiry into the Decline of Sockeye Salmon in the Fraser River – Final
Report. Ottawa, Public Works and Government Services Canada.
COSEWIC (2011) Guidelines for recognising Designatable Units. Available at:
http://www.cosewic.gc.ca/eng/sct2/sct2_5_e.cfm [accessed 5 July 2013].
Cox-Rodgers S, Hume JMB, Shortreed KS and Spilsted B (2010) A risk assessment model for Skeena
River sockeye salmon. Canadian Manuscript Report of Fisheries and Aquatic Sciences 2920. Prince
Rupert, Department of Fisheries and Oceans Canada.
Crandall KA, Bininda-Emonds ORP, Mace GM and Wayne RK (2000) Considering evolutionary processes
in conservation biology. Trends in Ecology and Evolution 15(7):290-295.
CTC (Chinook Technical Committee) (2012) Annual Report of Catch and Escapement for 2011. Pacific
Salmon Commission Report TCCHINOOK (12)-3. Vancouver, Pacific Salmon Commission. Available at
http://www.psc.org/pubs/TCCHINOOK12-3.pdf [accessed 24 January 2013].
DFO (Department of Fisheries and Oceans Canada) (2005) Canada’s Policy for Conservation of Wild
Pacific Salmon. Available at http://www.pac.dfo-mpo.gc.ca/fm-gp/species-especes/salmon-saumon/wsppss/docs/wsp-pss-eng.pdf [accessed 10 February 2013].
DFO (Department of Fisheries and Oceans Canada) (2012) Integrated Fisheries Management Plan:
Salmon. Northern B.C. June 1, 2012 to May 31, 2013. Available at http://www.dfompo.gc.ca/Library/346917.pdf [accessed 15 March 2013].
Fried SM (1994) Pacific salmon spawning escapement goals for the Prince William Sound, Cook Inlet, and
Bristol Bay areas of Alaska. Special Publication No. 8. Juneau, Alaska Department of Fish and Game,
Commercial Fisheries Management and Development Division.
Geiger HJ and Gharrett AJ (1998) Salmon stocks at risk: what’s the stock, and what’s the risk? Alaska
Fishery Research Bulletin 4(2):178-180.
Gustafson RG, Wainwright TC, Winans GA, Waknitz FW, Parker LT and Waples RS (1997) Status review
of sockeye salmon from Washington and Oregon. NOAA Technical Memorandum NMFS-NWFSC-33.
Hard JJ, Kope RG, Grant WS, Waknitz FW, Parker LT and Waples RS (1996) Status review of pink salmon
from Washington, Oregon, and California. NOAA Technical Memorandum NMFS-NWFSC-25.
Hilborn R and Walters CJ (1992) Quantitative Fisheries Stock Assessment: Choice, Dynamics and
Uncertainty. New York, Chapman and Hall.
Holt CA (2009) Evaluation of benchmarks for conservation units in Canada’s Wild Salmon Policy: Technical
Documentation. Research Document 2009/059. Ottawa, Canadian Science Advisory Secretariat.
Holt CA and Irvine JR (2013) Distinguishing benchmarks of biological status from management reference
points: A case study on Pacific salmon in Canada. Environmental Conservation 40(4):345–355.
www.msc.org/science-series/volume-02
111
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Holtby LB and Ciruna KA (2007) Conservation units for Pacific salmon under the wild salmon policy.
Research Document 2007/070. Ottawa, Canadian Science Advisory Secretariat.
Johnson OW, Grant WS, Kope RG, Neely K, Waknitz FW and Waples RS (1997) Status review of chum
salmon from Washington, Oregon, and California. NOAA Technical Memorandum NMFS-NWFSC-32.
Johnson OW, Ruckelshaus MH, Grant WS, Waknitz FW, Garrett AM, Bryant GJ, Neely K and Hard JJ,
(1999) Status review of coastal cutthroat trout from Washington, Oregon, and California. NOAA Technical
Memorandum NMFS-NWFSC-37.
Johnston NT, Parkinson EA, Tautz AF and Ward BR (2002) A Conceptual Framework for the management
of steelhead, Oncorhynchus mykiss. Fisheries Project Report No. RS101. Vancouver, Ministry of Water,
Land and Air Protection, BC Fisheries Branch.
Koenings JP and Burkett RD (1987) Population characteristics of sockeye salmon (Oncorhynchus nerka)
smolts relative to temperature regimes, euphotic volume, fry density, and forage base within Alaskan lakes.
In: Sockeye Salmon (Oncorhynchus nerka) Population Biology and Future Management (Smith HD,
Margolis L and Wood CC, eds). Ottawa, NRC Research Press.
Korman J and Cox-Rodgers S (2012) Summary of Preliminary Benchmark Analysis for Lake Sockeye in the
Skeena Watershed. Available at http://skeenawatershedinitiative.com/libraryfiles/lib1006.pdf [accessed 27
March 2013].
Larkin PA (1972) The stock concept and management of Pacific salmon. In: The stock concept in Pacific
salmon (Simon RC and Larkin PA, eds). Vancouver: University of British Columbia, H.R MacMillian
Lectures in Fisheries.
Larkin PA (1977) An epitaph for the concept of maximum sustained yield. Transactions of the American
Fisheries Society, 106:1-11.
Makeev SS (2010) Regulating the escapement of Adult Salmon. Yuzhno-Sakhalinsk, Sakhalin Salmon
Initiative.
Makeev SS (2011) New Approaches to Assessing Habitat Capacity of Sakhalin Rivers. Vladimir Ya.
Levanidov's Biennial Memorial Meetings 5:329-345.
Milton DA and Shaklee JB (1987) Biochemical genetics and population structure of blue grenadier,
Macruronus novazelandie (Hector) (pisces: Merluccidae), from Australian waters. Australian Journal of
Marine Freshwater Research 38(1):727-742.
Ministry of the Environment (2013) Red List of Threatened Fishes of Japan. Available at:
http://www.biodic.go.jp/english/rdb/rdb_e.html [accessed 28 March 2013].
Moritz C (1994) Defining ‘Evolutionarily Significant Units’ for conservation. Trends in Ecology and Evolution.
9(10):373-375.
MRAG Americas, Inc. (2012) Final certification report: Ozernaya sockeye salmon fishery. Available at
www.msc.org [accessed 1 January 2013].
MSC (Marine Stewardship Council) (2010) Fisheries Assessment Methodology and Guidance to
Certification Bodies: Including Default Assessment Tree and Risk-Based Framework. Version 2.1. Available
at www.msc.org [accessed 1 September 2011].
www.msc.org/science-series/volume-02
112
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
MSC (Marine Stewardship Council) (2012) Consultation Document: Draft Annex CM: Modifications to the
Default Assessment Tree for Salmon Fisheries. Available at: http://improvements.msc.org/database/defaultassessment-tree-for-enhanced-salmon-fisheries/consultations/late-stage-consultation-default-assessmenttree-for-salmon [accessed 1 August 2012].
Munro AR, Habicht C, Dann TH, Eggers DM, Templin WD, Witteveen MJ, Baker TT, Howard KG, Jasper
JR, Rogers Olive SD, Liller HL, Chenoweth EL and Volk EC (2012) Harvest and harvest rates of chum
salmon stocks in fisheries of the Western Alaska Salmon Stock Identification Program (WASSIP), 2007–
2009. Special Publication No. 12-25. Anchorage, Alaska Department of Fish and Game.
Munro AR and Volk EC (2012) Summary of Pacific salmon escapement goals in Alaska with a review of
escapements from 2003 to 2011. Fishery Manuscript Series FMS No. 12-03. Anchorage, Alaska
Department of Fish and Game.
Myers JM, Kope RG, Bryant GJ, Teel D, Lierheimer LJ, Wainwright TC, Grant WS, Waknitz FW, Neeley K,
Lindley ST and Waples RS (1998) Status review of chinook salmon from Washington, Idaho, Oregon, and
California’. NOAA Technical Memorandum NMFSNWFSC-35.
Nagata M (2010) MSC: Eco-Label for the Sustainability of Salmon. Available at
http://eprints.lib.hokudai.ac.jp/dspace/bitstream/2115/44251/1/3_Nagata.pdf [accessed 10 January 2013].
NPFMC (North Pacific Fisheries Management Council) and NMFS (National Marine Fisheries Service)
(1990) Fishery Management Plan for the Salmon Fisheries in the Exclusive Economic Zone off the Coast of
Alaska. Available at http://alaskafisheries.noaa.gov/npfmc/PDFdocuments/fmp/Salmon/SalmonFMP311.pdf
[accessed 27 March 2013].
Pestal GP, Huang AM, Cass A and the FRSSI Working Group (2011) Updated Methods for Assessing
Harvest Rules for Fraser River Sockeye Salmon (Oncorhynchus nerka). DFO Can. Sci. Advis. Sec. Res.
Doc. 2011/133. Available at: http://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocsDocRech/2011/2011_133-eng.pdf [accessed 20 January 2013].
Pinsky ML, Springmeyer DB, Goslin M and Augerot X (2009). Range-wide selection of catchments for
Pacific salmon conservation. Conservation Biology 23(3):680-691.
Portley, N and Geiger, HJ (2014) Limit reference points for Pacific salmon fisheries, North American
Journal of Fisheries Management 34(2):401410
PSC (Pacific Salmon Commission) (2012) Report of the Fraser River Panel to the Pacific Salmon
Commission on the 2008 Fraser River Sockeye Salmon Fishing Seasons. Available at
http://www.psc.org/publications_annual_fraserreport.htm [accessed 10 January 2013].
Portley N and Sousa P (2013) The FishSource method for scoring salmon fisheries; a statistical approach
for aligning the FishSource salmon fishery assessment method with Marine Stewardship Council ratings.
Sustainable Fisheries Partnership Foundation. 60 p. Available at www.fishsource.com [accessed 1 March
2013].
Puget Sound Indian Tribes and WDFW (Washington Department of Fish and Wildlife) (2010)
Comprehensive Management Plan for Puget Sound Chinook: Harvest Management Component. Available
at http://wdfw.wa.gov/publications/00854/wdfw00854.pdf [accessed 9 March 2013].
Quinn TJ II, Fagen R and Zheng J (1990) Threshold management policies for exploited populations.
Canadian Journal of Fisheries and Aquatic Sciences 47:2016-2029.
Quinn TJ II and Deriso RB (1999) Quantitative Fish Dynamics. New York, Oxford University Press.
www.msc.org/science-series/volume-02
113
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Quinn TJ II, (2003) Ruminations on the development and future of population dynamics models in fisheries.
Natural Resource Modeling 16(4):341-392.
Rand PS (2008) Oncorhynchus nerka. In: IUCN Red List of Threatened Species. Version 2010.4.
Cambridge, IUCN.
Ricker WE (1954) Stock and recruitment. Journal of Fisheries Research Board of Canada 11:559–623.
Ricker WE (1972) Hereditary and environmental factors affecting certain salmonid populations. In: The
stock concept in Pacific salmon (Simon, RC and Larkin, PA, eds). Vancouver: University of British
Columbia, HR MacMillian Lectures in Fisheries.
Ricker WE (1975) Computation and interpretation of biological statistics of fish populations. Fisheries
Research Board of Canada Bulletin 191. Ottawa.
Ryder OA (1986) Species conservation and systematics: the dilemma of subspecies. Trends in Ecology
and Evolution 1:9-10.
Sakhalin Oblast Regional Government (1994) Sakhalin Oblast Geographical Overview. In: Sakhalin Oblast
Atlas. Resources and Economics. Yuzhno-Sakhalinsk, Sakhalin Book Publishers.
Sasaki K, Saito T and Nagasawa T (2012) Japan Salmon Commercial Fisheries Catch Statistics for 2011.
North Pacific Anadromous Fish Commission Document 1401. Available at
http://www.npafc.org/new/publications/Documents/PDF%202012/1401(Japan).pdf [accessed 20 February
2013].
SCS (Scientific Certification Systems, Inc.) (2007) The Commercial Alaska Salmon Fisheries Managed by
the Alaska Department of Fish and Game: A 5-Year Re-Assessment Based on the Marine Stewardship
Council Program. Available at www.msc.org [accessed on 29 March 2013].
Shevlyakov EA (2006) Management of Pacific salmon Oncorhynchus resources in Kamchatka and the
mixed-stock fishery. Voproci Rybolovstvo 7(1-25):22-41.
Shevlyakov A and Maslov AV (2011) Key rivers for production of Pacific salmon on Kamchatka, and their
use in escapement assessment. Izvestia TINRO 164:114-139.
Springmeyer D, Pinsky ML, Portley N, Bonkoski J and Rand PS (2007) Ranking Sakhalin river basins for
salmonid conservation. Transactions of the Sakhalin Research Institute of Fisheries and Oceanography
9(1):264-293.
Sustainable Fisheries Partnership (2013) Dataset: Analysis of MSC scoring of salmon stock status.
Unpublished.
Stewart DC, Smith GW and Youngson AF (2002) Tributary-specific variation in the timing of adult Atlantic
salmon has a genetic component. Canadian Journal of Fisheries and Aquatic Sciences 59:276-281.
Stewart DC, Middlemas, SJ and Youngson, AF (2006) Population structuring in Atlantic salmon: evidence
of genetic influence on the timing of smolt migration in sub-catchment stocks. Ecology of Freshwater Fish
15:552-558.
TINRO (Pacific Ocean Institute for Fisheries and Oceanography) (2012) Salmon 2012. Vladivostok, TINROCentre.
www.msc.org/science-series/volume-02
114
Stock Management Units and Limit Reference Points in Salmon Fisheries:
Best Practice Review and Recommendations to the MSC
Volk E, Evenson MJ and Clark RA, (2009) Escapement goal recommendations for select Arctic-YukonKuskokwim Region salmon stocks, 2010. Fishery Manuscript No. 09-07. Anchorage, Alaska Department of
Fish and Game.
Waples RS (1991) Pacific salmon, Oncorhynchus spp., and the definition of ‘‘species’’ under
the Endangered Species Act. Marine Fisheries Review 53:11–22.
Waples RS, Gustafson RG, Weitkamp LA, Myers JM, Johnson OW, Busby PJ, Hard JJ, Bryan GJ, Waknitz
FW, Neely K, Teel D, Grant WS, Winans GA, Phelps S, Marshall A and Baker B (2001) Characterizing
diversity in salmon from the Pacific Northwest. Journal of Fish Biology 59(A):1-41.
Weitkamp LA, Wainwright TC, Bryant GJ, Milner GB, Teel DJ, Kope RG and Waples RS (1995) Status
review of coho salmon from Washington, Oregon, and California. NOAA Technical Memo NMFS-NWFSC24.
Witherell D (2010) Second National Meeting of the Regional Fishery Management Councils’ Scientific and
Statistical Committees. Report of a National SSC Workshop on Establishing a Scientific Basis for Annual
Catch Limits, November 10-13, 2009. St. Thomas, Caribbean Fishery Management Council.
www.msc.org/science-series/volume-02
115