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Preface
Global marine fish harvest has plateaued and many important commercial
stocks have been depleted. The Ocean Studies Board (OSB), at the request
of the National Marine Fisheries Service (NMFS), has provided advice designed
to improve management of marine fisheries in the United States (NRC, 1994a).
Many of the changes suggested in the 1994 report Improving the Management
of U.S. Marine Fisheries were incorporated in the reauthorized Magnuson-Stevens
Fishery Conservation and Management Act (MSFCMA) in 1996.
NMFS also has asked the OSB for advice on specific issues of Atlantic
bluefin tuna population biology; the OSB presented its results in another
1994 report, An Assessment of Atlantic Bluefin Tuna (NRC, 1994b). Following
the publication of that report, there was a widespread expression of the
need for reviews of several other specific stock assessments. NMFS responded
by requesting a broad review of the methods used in the United States for
stock assessments. The results of that review are presented in this report.
This study would not have been possible without the efforts of NMFS
scientists who carried out blind runs of data provided by the study committee
and participated in the committee's meetings. The cooperation between academic
and agency scientists was commendable and actually led to advances in the
state of the art of fish stock assessments. The OSB offers sincere thanks
to NMFS analysts for their considerable efforts, including Ray Conser,
Jeff Fujioka, Wendy Gabriel, Phil Goodyear, Jim Ianelli, Rick Methot, Jerry
Pella, Clay Porch, Joe Powers, Mike Prager, Victor Restrepo, Gerald Scott,
and Mike Sigler. Other individuals also contributed to the committee's
work and deserve the thanks of the committee and the OSB: Jie Zheng (Alaska
Department of Fish and Game), Andre Punt (Commonwealth Scientific and Industrial
Research Organization, Australia), and David Fournier (Otter Research Ltd.).
The results of this study will serve as an important foundation for
the National Research Council review of the U.S. Northeast fisheries stock
assessments that was mandated by Congress in 1996 as part of the MSFCMA
reauthorization. The recommendations presented herein should also be useful
to ongoing international activities related to fish stock assessments,
such as those of the International Council for the Exploration of the Sea.
Executive Summary
Marine fisheries provide a vital contribution to food supplies, employment,
and culture worldwide. Therefore, matching fishing activities with natural
fluctuations so as to avoid unsustainable harvests and population crashes
is an important goal. In an ideal world, accurate and precise estimates
of the abundance of fish stocks and their dynamics (how and why population
levels change) would be available to set sustainable harvest levels to
accommodate commercial and recreational demand. In reality, fishery management
is based on imperfect estimation of the number, biomass, productivity,
and age structure of fish populations and incomplete knowledge of population
dynamics. The ocean is relatively opaque to light, and acoustic techniques
of remote sensing are not yet sufficiently developed for general use in
estimating fish populations. Thus, it is difficult to count fish through
nondestructive means and fish usually must be caught to be counted, weighed,
and measured. Standardized techniques have been developed to sample a relatively
small proportion of fish from a population and to combine such data with
commercial and recreational catch information to estimate population characteristics.
These techniques yield stock assessments used by managers at state, regional,
national, and international levels.
In addition to monitoring the abundance and productivity of exploited
fish populations, stock assessments can provide a quantitative prediction
of the consequences of possible alternative management actions. The mechanisms
that cause fish populations to change are poorly understood but include
environmental and ecosystem effects, interactions among multiple species,
and effects of humans through harvesting, pollution, habitat disruption,
and other factors. Without accurate stock assessments and their proper
use in management, exploited fish populations can collapse, creating severe
economic, social, and ecological problems. Therefore, ensuring that stock
assessment research progresses and that operational stock assessments use
the best techniques for a given stock are fundamental for ensuring the
sustainability of commercial and recreational marine fisheries.
Stock assessment is a multistage process. Steps include (1) definition
of the geographic and biological extent of the stock, (2) choice of data
collection procedures and collection of data, (3) choice of an assessment
model and its parameters and conduct of assessments, (4) specification
of performance indicators and evaluation of alternative actions, and (5)
presentation of results. This report concentrates on evaluating assessment
models, with less extensive treatment of the other steps. Chapter 1 discusses
these steps in greater detail. Techniques of stock assessment range from
informal estimates to more sophisticated modeling approaches used to combine
data of various types. Assessment models predict rates of change in biomass
and productivity based on information about yield from fisheries and the
rates at which fish enter the harvestable population (recruitment), grow
in size, and exit the population (natural and fishing mortality).
Stock assessments for fish living in the U.S. exclusive economic zone
(3 to 200 nautical miles from shore) and for some highly migratory species
are conducted by scientists from the National Oceanic and Atmospheric Administration's
(NOAA's) National Marine Fisheries Service (NMFS) and independent species
group commissions (e.g., the International Pacific Halibut Commission and
the Inter-American Tropical Tuna Commission). In addition, interstate fishery
management commissions were created to facilitate the coordination of state
assessment scientists in working with each other and with federal scientists
to assess and manage stocks shared among states in their coastal waters
(within 3 nautical miles from shore on open coasts, as well as bays and
estuaries). These organizations include the Atlantic States, Gulf States,
and Pacific States Marine Fisheries Commissions. Some states (e.g., Alaska,
Oregon, and Florida) also perform assessments for fisheries conducted in
their own state waters.
Fishery management organizations use the results of stock assessments
to design and implement various controls for the total catch that can be
removed from fish populations under their jurisdictions. Commercial catch
can be managed by specifying the amount of harvesting allowed; the areas
of fishing and times of the year that fishing can take place; the gear
that can be used; minimum fish size limits; and in some cases, the amount
of fish that any single fisher, community, company, or other entity can
catch. Recreational fisheries more often impose minimum size limits, daily
catch limits, seasons, and sometimes gear restrictions and requirements
to release fish that are caught.
STUDY PROCESS
The National Research Council (NRC) Committee on Fish Stock Assessment
Methods was formed in early 1996 to review existing stock assessment methods
and to consider alternative approaches for the future. The committee's
statement of task was two-fold:1. Conduct a scientific review of stock
assessment methods and models for marine fisheries management. 2. Compare
models using actual and simulated data having a variety of characteristics,
to test the sensitivity and robustness of the models to data quality and
type.
As part of this study, the committee asked selected stock assessment
scientists to conduct blind runs of simulated data sets using five different
models. Models tested included a production model, a delay-difference model,
and three age-structured methods (described in detail in Chapter 3). The
goal of the simulation study was to evaluate the performance of stock assessment
methods for simulated fish populations for which the true population parameters
were known (to the committee, but not to the analysts) and some of the
assumptions usually made in stock assessments were violated. One type of
data set was typical of the catch biomass, age composition of the catch,
and catch per unit effort (CPUE) that are obtained from commercial and
recreational fisheries. The other type of data set was typical of that
collected by fishery-independent surveys.
Each analyst was asked to evaluate five 30-year sets of simulated commercial
and survey data, alone and in combination. The five data sets provided
different combinations of parameters in terms of the following:
• Increasing or decreasing stock size over time (population trend)
• Constant versus changing age of fish caught (fishery selectivity)
over time
• Accuracy of catch reported by fishers
• Ability of fishery and survey vessels to catch fish (fishery and survey
catchability)
The analysts were given essential information about fish growth and
maturity, the probability of mis-estimating fish ages, and selected information
about the structure of the populations and the data. Analysts were not
provided information about natural mortality, catchability, selectivity,
recruitment, or the amount of underreporting (although they were warned
that underreporting might have occurred).
In addition to the results of these basic analyses, (1) some analysts
repeated their model runs with the true average natural mortality (provided
by the committee), (2) key management variables were calculated by analysts
and the committee, and (3) retrospective analyses were conducted by the
committee to determine the persistence of over- or underestimation of population
parameters over time by the different models. Greater detail about the
study process is given in Chapter 5 and Appendix E.
FINDINGS AND RECOMMENDATIONS
The committee focused its examination on the data that are used in assessments,
model performance, use of harvest strategies, new assessment techniques,
periodic review and quality control of assessments and assessment methods,
and education and training of stock assessment scientists. The committee
based its recommendations on the results of the simulations and on its
collective experience. Caveats about how the analyses conducted for this
study compare to actual stock assessments are given in Chapter 5. Accomplishing
the recommendations of this report will require concerted and cooperative
action by all interested parties (academic and government scientists, fishery
managers, user groups, and environmental nongovernmental organizations)
to improve the stock assessment process and products.
Data Collection And Assessment Methods
The committee concludes that stock assessments do not always provide
enough information to evaluate data quality and to estimate model parameters,
and it recommends a checklist that would promote more complete data collection
for use in stock assessments. The results of the committee's simulations
demonstrated that the availability of continuous sets of data collected
by using standardized and calibrated methods is important for the use of
existing stock assessment models. The best index of fish abundance is one
for which extraneous influences (e.g., changes in gear and seasonal coverage,
changes in fishers' behavior) can be controlled. The committee recommends
that at least one reliable abundance index should be available for each
significant stock. CPUE data from commercial fisheries, if not properly
standardized, do not usually provide the most appropriate index. Likewise,
CPUE data from recreational fisheries require standardization to serve
as a good index of abundance.
Fishery-independent surveys offer the best opportunity for controlling
sampling conditions over time and the best choice for achieving a reliable
index if they are designed well with respect to location, timing, sampling
gear, and other considerations of statistically valid survey design. NMFS
should support the long-term collection of fishery-independent data, using
either the NOAA fleet or calibrated independent vessels. Diminishing the
quality of fishery-independent data by failing to modernize NOAA fishery
research vessels or by changing sampling methods and gear without proper
calibration could reduce the usefulness of existing and future data sets.
The simulation study demonstrated that assessments are sensitive to
underlying structural features of fish stocks and fishery practices, such
as natural mortality, age selectivity, catch reporting, and variations
in these or other quantities. Auxiliary information in the form of indices
or survey estimates of abundance, population structure information, and
accurate estimates of other population parameters (e.g., natural or fishing
mortality, growth, catchability) improves the accuracy of assessments.
Formally reviewed sampling protocols for collection of commercial fisheries
statistics have not been implemented in many geographic regions. The lack
of formalized, peer-reviewed data collection methods in commercial fisheries
is problematic because bias and improper survey conduct may exist, with
unknown impact on data reliability. Greater attention should be devoted
to sampling design based on an understanding of the statistical properties
of the estimators for catch at age and other factors. Sampling and subsequent
analysis should also consider the issue of systematic biases that emerge
with factors such as misreporting. Formalized sampling protocols have been
developed for recreational fisheries in the form of the Marine Recreational
Fisheries Statistics Survey (MRFSS). MRFSS data and methods, albeit imperfect,
have undergone independent peer review, are readily available, and could
serve as a model for commercial fisheries. The committee recommends that
a standardized and formalized data collection protocol be established for
commercial fisheries nationwide.
Models
Both harvesting strategies and decision rules for regulatory actions
have to be evaluated simultaneously to determine their combined ability
to sustain stocks. Simulation models should be realistic and encompass
a wide range of possible stock responses to management actions and natural
fluctuations consistent with experience. The committee recommends that
fish stock assessments present realistic measures of the uncertainty in
model outputs whenever feasible. Although a simple model can be a useful
management tool, more complex models are needed to better quantify the
unknown aspects of the system and to address the long-term consequences
of specific decision rules adequately. Retrospective analyses performed
by the committee showed that persistent over- or underestimation can occur
over a number of years of assessment, regardless of which model is used.
The committee recommends the use of Bayesian methods both for creating
distributions of input variables and for evaluating alternative management
policies. Other methods for including realistic levels of uncertainty in
models also should be investigated.
In the simulations, model performance became erratic as more variability
or errors were introduced to data sets. Newer modeling methods offer promise
for reducing bias in key parameter estimates, although using mathematically
sophisticated assessment models did not mitigate poor data quality. Different
assessment models should be used to analyze the same data to help recognize
poor data and to improve the quality of assessment results. Results from
such comparisons can be used to direct survey programs to improve data
quality and to assess the degree of improvement in data achieved over time.
Greater attention should also be devoted to including independent estimates
of natural mortality and its variability in assessment models. Further
simulation work of this kind is also needed to determine whether the simulation
results and the conclusions based on these results remain the same over
multiple replications.
The committee believes that single-species assessments provide the best
approach at present for assessing population parameters and providing short-term
forecasting and management advice. Recent interest in bringing ecological
and environmental considerations and multi-species interactions into stock
assessments should be encouraged, but not at the expense of a reduction
in the quality of stock assessments.
Harvest Strategies
Although the committee did not evaluate alternative harvest strategies,
it believes that assessment methods and harvest strategies should be evaluated
together because harvest strategies can affect stock assessments and the
uncertainty inherent in stock assessments should be reflected in harvest
strategies. Despite the uncertainty in stock assessments, fishery scientists
may be able to identify robust management measures that can at least prevent
overfishing, even if they cannot optimize performance. Conservative management
procedures include management tools specific to the species managed, such
as minimum biomass levels, size limits, gear restrictions, and area closures
(for sedentary species). Management procedures by which the allowable catch
is set as a constant fraction of biomass (used for many U.S. fisheries)
generally perform better than many alternative procedures. However, errors
in implementation due to assessment uncertainties could result in substantial
reductions in long-term average harvests in some years if biomass estimates
are highly uncertain. Assessment methods and harvest strategies need to
be evaluated simultaneously to determine their ability to achieve management
goals. Application of risk-adjusted reference points (based on fishing
mortality or biomass) would immediately lead to reduced total allowable
catch and thus create an economic incentive for investment in improved
data gathering and assessment procedures to reduce the coefficient of variation
of biomass estimates.
There are at least four alternatives to harvesting a constant fraction
of exploitable biomass that may result in levels of total mortality that
are consistent with maintaining a fish stock. First, target fishing mortality
can be reduced as a stock decreases in size to reduce risks. Second, a
minimum biomass level can be established, below which fishing would be
halted (this is done for some U.S. fisheries). Third, the size of fish
captured can be increased by changing requirements for harvest gear. This
restriction might allow smaller fish to escape and spawn, but could be
ineffective if harvesters apply more effort to the larger fish. Finally,
geographic areas can be closed to limit mortality for sedentary species
if the distribution of organisms is well known and if the fishing mortality
in other areas is not increased. Area closures have been implemented or
proposed for many fisheries worldwide in the form of marine reserves and
sanctuaries.
New Approaches
NMFS and other organizations responsible for fisheries management should
support the development of new techniques that can better accommodate incomplete
and variable data and can account for the effects of environmental fluctuations
on fisheries. Such techniques should allow the specification of uncertainty
in key parameters (rather than assuming constant, known values), should
be robust to measurement error, and should include the ability to show
the risks associated with estimated uncertainty.
A few prominent recommendations for new approaches emerged from the
study. Scientists that conduct stock assessments and organizations that
depend on assessments should
• incorporate Bayesian methods and other techniques to include realistic
uncertainty in stock assessment models;
• develop better assessment models for recreational fisheries and methods
to evaluate the impacts of the quality of recreational data on stock assessments;
• account for effects of directional changes in environmental variables
(e.g., those that would accompany climate change) in new models; and
• develop new means to estimate changes in average catchability, selectivity,
and mortality over time, rather than assuming that these parameters remain
constant.
The results from the simulation exercise should be sobering to scientists,
managers, and the users of fishery resources. The majority of the estimates
of exploitable biomass exceeded true values by more than 25%; assessments
that used accurate abundance indices performed roughly twice as well as
those that use faulty indices. A disturbing feature of the assessment methods
is their tendency to lag in their detection of trends in the simulated
population abundance over time. For example, some methods with some types
of data consistently overestimate exploitable biomass during periods of
decreasing simulated abundance and underestimate exploitable biomass during
periods of increasing simulated abundance.
Although no stock assessment model was free from significant error in
the simulations, it is also true that few of the models failed consistently.
Hence, the message of this report is not that stock assessment models should
not be used, but rather that data collection, stock assessment techniques,
and management procedures need to be improved in terms of their ability
to detect and respond to population declines. The simulation results and
some actual fishery management examples suggest that overestimation of
stock biomass and overfishing of a population can occur due to inaccurate
stock assessments and that the overestimation can persist over time. The
committee believes that the two most important management actions to mitigate
this problem are: (1) to model and express uncertainty in stock assessments
explicitly, and (2) to incorporate uncertainty explicitly into management
actions such as harvesting strategies.
The absence of adequate data is the primary factor constraining accurate
stock assessments. The differences between estimated and true values derived
from the simulated data were most likely not introduced by any mistakes
made by the analysts. Rather, the large differences that occurred under
some scenarios were primarily the result of poor data and model misspecification
stemming from incomplete knowledge of the true situation by the analysts.
The surplus production and delay difference models did not include the
ability to account for changes over time in key parameters for the simulated
populations. The simulated data sets were better structured for analysis
by age-structured methods; hence, these kinds of models performed better.
When they did not perform well, it was generally because the models used
biased information (e.g., the fishery CPUE index) or did not account for
changes in selectivity and catchability over time. Had the analysts been
told about these data features, it is likely that they could have compensated
for them and obtained better assessments. Some of the newer models appear
to be able to achieve such compensation through the introduction of process
errors. Nevertheless, modeling will never be able to provide estimates
that are as accurate as direct knowledge obtained by measurement and experimentation.
Thus, if future stock assessments are to avoid some of the past problems,
management agencies must devote the necessary resources to monitor and
investigate fish populations in a stable research environment that fosters
creative approaches.
Peer Review
It is imperative that stock assessment procedures and results be understood
better and trusted more by all stakeholders. One means to achieve such
trust is to conduct independent peer review of fishery management methods
and results including (1) the survey sampling methods used in data collection,
(2) stock assessment procedures, and (3) risk assessment and management
strategies. When applied properly to stock assessments, peer review yields
an impartial evaluation of the quality of assessments as well as constructive
suggestions for improvement. Such reviews are most beneficial when conducted
periodically, for example, every 5 to 10 years, as new information and
practices develop. In addition, a complete review of methods for collection
of data from commercial fisheries should be conducted in the near future
by an independent panel of experts, which could lead to the adoption of
formal protocols.
Education and Training
Reduction in the supply of stock assessment scientists would endanger
the conduct of fishery assessments by the federal government, interstate
commissions, and international management organizations and would hinder
progress in the development and implementation of new stock assessment
methods. NMFS and other bodies that conduct and depend on fish stock assessments
should cooperate to ensure a steady supply of well-trained stock assessment
scientists by using mechanisms such as personnel exchanges among universities,
government laboratories, and industry and by funding stock assessment research
activities. The training of stock assessment scientists should endow them
with skills in applied mathematics, fisheries biology, and oceanography.
Education of fisheries scientists should be organized and executed in such
a way that it complements and augments the NMFS research mission and leads
to improved management strategies for fisheries in the future.
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