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Improving Fish Stock Assessments (1998)

Chapter: Appendix H

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Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
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H— Information from Interstate Marine Fisheries Commissions and States

To aid the committee's deliberations, information was requested from the Atlantic, Gulf, and Pacific States Marine Fisheries Commissions. The committee specifically asked the commissions for information about what methods their states use to assess marine fish stocks in state waters (to compare with methods used by National Marine Fisheries Service [NMFS] and the regional fishery management councils). The commissions were also asked to relay their concerns about existing stock assessment methods. This information is shown below; they are the views of the commissions and their staff and do not necessarily coincide with the views of the committee. The response from the Atlantic States Marine Fisheries Commission was received first and was forwarded to the other commissions.

Commission and State Concerns and Comments Regarding Stock Assessments

Atlantic States Marine Fisheries Commission (ASMFC)
  1. The complexity of many stock assessments models leads to a lack of understanding among those who may not have a scientific background. More effort is needed to provide less technical explanations of stock assessment models and results.
  2. Discrepancies in model results due to incomplete characterization of input parameters lead to less effective and timely fisheries management, and lack of public confidence in the scientific process and expertise.
  3. Probability analysis should be included as a part of all stock assessments to provide an indication of the level of achieving management and rebuilding goals.
  4. Deficiencies in fisheries-dependent data bases limit the effectiveness of many stock assessments; i.e., catch at age, discards.
  5. Deficiencies in information concerning critical model parameters may limit stock assessments; i.e., fishing and natural mortality, bias in catch data, stock distribution, and life history parameters.
  6. Harvest regulations may affect input data. For example, the effect of size limits may be to truncate length-frequency data thereby affecting the model results.
  7. Biases in model results may occur due to equilibrium assumptions; i.e., yield-per-recruit modeling.
Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×

TABLE H.1 Stock Assessment Methods Used by the Atlantic States Marine Fisheries Commission  

Species  

Stock Assessment Method(s)

American eel  

None

American lobster  

Cohort analysis, egg production per recruit, Delury

Atlantic menhaden  

VPA (basic and separable)

Atlantic sturgeon  

Stock recruitment, egg recruitment

Black sea bass (with MAFMC)  

VPA (ADAPT and ICA)

Bluefish (with MAFMC)  

VPA (ADAPT, Cagean or ICA), tagging

Croaker  

None

Northern shrimp  

Abundance indices

Red drum (with SAFMC)  

VPA (separable)

Scup (with MAFMC)  

VPA (ADAPT)

Sea herring  

VPA (ADAPT, ICA)

Shad and river herring  

Stock recruitment

Spanish mackerel  

VPA (ADAPT)

Spot  

None

Spotted seatrout  

None

Striped bass  

Spawning stock biomass, stock recruitment

Summer flounder (with MAFMC)  

VPA (ADAPT)

Tautog  

VPA (ADAPT, Laurec-Shepard, ESA), catch curves, tagging

Weakfish  

VPA (ESA)

Winter flounder  

VPA (ADAPT)

NOTE: ADAPT = Adaptive approach (age-structured); ESA = extended survivors analysis; ICA = integrated catch analysis; MAFMC = Mid-Atlantic Fishery Management Council; SAFMC = South Atlantic Fishery Management Council; VPA = virtual population analysis.      

  1. Lack of information for stock identification may affect appropriateness of stock assessment models applied to various species.
  2. There is need for fisheries-independent data in stock assessment modeling, particularly as tuning indices for VPA analyses.
  3. Relatively simple models may overlook important parameters that the model is not robust to; i.e., sensitivity to changes in catchability.
  4. Little data is available on the functional relations among co-occurring exploited species and effects of fishing on shifts in ecological relations.
  5. Models used to forecast how management actions will change F do not always take into account economic and social factors.
  6. The quality of the input data affects the precision of the assessments.
Pacific States Marine Fisheries Commission (PSMFC)

There are fisheries on the West Coast that do not have the basic population data necessary to allow adequate assessment modeling. The thresher shark fishery is one example of a fishery that is being managed very conservatively due to the lack of funding for adequate assessments. We believe it is critical that efforts be initiated to develop the databases necessary to manage these fisheries.

Rockfish are targeted by both commercial and recreational fisheries off the West Coast. There has been concern, coast-wide, regarding the management of nearshore rockfish. These concerns have been discussed on a regional basis by the Canada-U.S. Groundfish Committee. This committee listed the following concerns.

  1. The lack of biological information and abundance for many nearshore rockfish species
  2. The generally poor track record of rockfish management coast-wide
Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×

TABLE H.2 Stock Assessment Methods Used by the State of Oregon to Manage Its Fisheries

Species Name

Stock Assessment Model

Comments

Pink shrimp  

No formal assessment. Stock status is monitored using a retrospective, area-based index of recruitment.

Managed by season and aggregate size limit

Red sea urchin  

No formal assessment. Stock status is monitored using retrospective indices of size distribution and abundance.

Managed by size limit and limited entry

Dungeness crab  

None

Managed by season, sex, and size limit

Pacific herring, Yaquina Bay  

No formal assessment. Spawn deposition surveys conducted to establish harvest guidelines.

Managed by harvest guideline, season, limited entry

  1. The notable difficulty in managing nearshore species

     

  2. The longevity and vulnerability to over-exploitation associated with these species even when some biological parameters are known

Rockfish are managed by the Councils and the states. Most species occur in fisheries managed by different jurisdictions making it difficult to fully assess the populations and fishery impacts.

Another issue is the lack of total catch information in many fisheries. Landing tickets give managers information on those species landed, but very limited data exist for West Coast fisheries total catch. Regulatory and economic discards are virtual unknowns. We believe an effective observer program is essential for the future health of these fish stocks and their attendant fisheries. A voluntary pilot program funded by the West Coast trawl industry is an important start to gather this data. Two states in the region provided information about the stock assessment methods they use: Oregon (Table H.2) and Alaska (Tables H.3 to H.5).

Alaska Department of Fish and Game (ADF&G)
  1. Often we fail to recognize that most samples taken for stock assessment are not random samples. Statistical models behind estimates from stock assessment are built with the concept of samples being representative of populations because these samples were randomly drawn. In stock assessment, samples are almost never randomly drawn. More diagnostic testing should be built into stock assessments to determine if our non-randomly drawn samples are, or are not, representative.
  2. Extrapolation of results from VPA (virtual populations analysis) to manage fisheries in the current year is a poor substitute for annual surveys and mark-recapture experiments. Since these extrapolations reflect past, not current information, results of VPA lag behind actual trends in abundance. Ancillary information from indices such as mean CPUE (catch per unit effort) to compensate adds another layer of assumptions and considerable danger.
  3. Sampling (handling) fish affects their subsequent behavior in ways that could bias stock assessments based on that behavior. Again, more diagnostics are needed to determine influences of handling.
  4. The lack of age structures for most shellfish species has thwarted the development of assessment models for years. For the past three years, ADF&G has focused on development of length-based methods for shellfish stock assessments under a range of data situations (e.g., trawl survey, pot survey, no survey). During the next few years ADF&G will continue to apply these methods to various stocks around the state. ADF&G also plans to
Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×

TABLE H.3 Methods Used to Assess Alaska Shellfish

Species Name/Area  

Stock Assessment Model

Comments

Red king crab

Southeast Alaska  

Catch-survey analysis (CSA)

For CSA methods, see Collie and Kruse (in press)

Bristol Bay

Length-based analysis (LBA)

For LBA methods, see Zheng et al. (1995a,b)

Kodiak

Prince William Sound, Cook Inlet, Alaska Peninsula, Pribilof Islands, Norton Sound.  

CSA, trawl survey, area-swept estimator Trawl survey, area-swept estimator

Plans: LBA

 

Plans: CSA (historical pot surveys) and LBA (ongoing trawl surveys)

Adak

None

Plans: catch-length analysis (CLA) - see Zheng et al. (1996) for methods

Blue king crab

St. Matthew and Pribilof Islands

Trawl survey, area-swept estimator

CSA in progress

Prince William Sound  

None

CPUE index from experimental fishery

Golden king crab

Southeast Alaska, Prince William Sound, Dutch Harbor, Adak  

None

Plans: GIS analysis of fisheries with on-board observer data

Tanner crab

Southeast Alaska  

None

CPUE model used to project attainment of fixed quota

Cook Inlet, Kodiak, Alaska; Peninsula, Bering Sea  

Trawl survey, area-swept estimator

LBA in progress for Bering Sea, LBA planned for Kodiak

Snow crab; Bering Sea  

Trawl survey, area-swept estimator

Needs: growth and M estimates

Hair crab

Bering Sea  

Trawl survey, area-swept estimator

Needs: growth and M estimates

Dungeness crab

Southeast Alaska, Yakutat, Kodiak, Alaska Peninsula

None

CLA possible in future

Prince William Sound, Cook Inlet  

Pot survey, index of abundance

CSA possible in future

Pink shrimp

Cook Inlet, Kodiak, Alaska

Trawl survey, area-swept estimator;

LBA in progress for Cook Inlet

Peninsula

None

CLA possible in future

Southeast Alaska  

 

Weathervane scallop

Prince William Sound, Cook Inlet

Dredge survey, area-swept estimator

Plans: develop age-structured model

Yakutat, Kodiak, Dutch Harbor, Bering Sea  

None

Plans: GIS analysis of onboard fishery observer data

Sea cucumber

Southeast Alaska

Dive survey, surplus production model

Needs: growth and recruitment

Elsewhere  

None

estimates

 

Needs: sampling, basic biological information

Sea urchin

Southeast Alaska

Dive survey, surplus production model

Needs: growth and recruitment

Elsewhere  

None

estimates

 

Needs: sampling, basic biological information

Intertidal clams

Cook Inlet (Kachemak Bay) Elsewhere  

Transect surveys

None

Plans: develop age-structured model

Miscellaneous other shellfish species (crabs, shrimps, clams, etc.)

 

Statewide  

None

Needs: basic biological information and sampling programs

Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×
  1. develop fishery-based assessments for fisheries with onboard observers in a GIS framework. Despite progress, stock assessments are not possible for the majority of Alaskan shellfish stocks due to a lack of basic biological information and funds for sampling programs.
  2. Budgets are declining while the complexity of and conflicts with the fishery management process are increasing. This situation will inevitably lead to a reduction in the quality of stock assessment data. This problem is most acute for stocks where fisheries are developing.
Gulf States Marine Fisheries Commission (GSMFC)

The stock assessment team of the Gulf States Marine Fisheries Commission has reviewed the documents provided by your office and generally offer complete concurrence with the thirteen points raised by the Atlantic States staff. Three comments (which to me represent emphasis) forwarded by GSMFC stock assessors were:

  1. Environmental Concerns. Natural climatological phenomena obviously play a role in success/failure of fishery management measures. While this is taken for granted in a functional sense, there is no practical way to account for these influences in current modeling practices. (Related or similar to ASMFC #5.)
  2. Human Dimensions. Almost totally lacking in stock assessment proceedings is the reactive capability of the fishers. It is typical for fishers to act or react unpredictably to management measures. (Related or similar to ASMFC #12.)
  3. Local vs. Regional Management. Spotted seatrout is an example. While regional management is desirable from an interstate transport perspective, status of local trout stocks can be drastically different within a relatively small geographic region. Regional managers may know very little about the condition of these local stocks. (Imbedded in ASMFC #s, 2, 5, 6, 8, 9, 10, and 13.)
Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×

TABLE H.4 Methods Used to Assess Pacific Salmon

Species Name/Area

Harvest Policy

Stock Assessment Methods

Chinook salmon

 

Southeast Alaska

Preseason quota based on constant harvest rate applied to preseason forecasted abundance with Pacific Salmon Commission Chinook Technical model

Cohort analysis of coded wire tag recoveries from hatchery indicator stocks; wild stock escapement enumeration with weirs, mark-recapture, aerial surveys, foot surveys

Yakutat

Fixed escapement goal

Weir counts

Copper River

Fixed escapement goal

Aerial survey counts

Upper Cook Inlet

Limited directed commercial fishing, reduce bycatch, sport fisheries managed for fixed escapement goals

Sonar counts, weir counts, aerial surveys

Kodiak/Chignik

No directed commercial fishing, fixed escapement goal

Aerial surveys, weir count

Bristol Bay

Fixed escapement goal

Sonar counts, aerial surveys

Kuskokwim River

Commercial fishery quota ranges

Test fishery catches, commercial fishery CPUE

Yukon River

Commercial fishery quota ranges

Test fishery catches, commercial fishery CPUE, mark or recapture, postseason run reconstruction

Coho salmon

 

Southeast Alaska

Scheduled closures of troll fishery based on CPUE of inside fisheries and early escapement; postseason evaluation of escapement relative to goals and harvest rates for indicator stocks

Fishery CPUE, indicator stock assessments (weir counts, mark-recapture of juveniles, exploitation rates CWT marking), fishwheel catches, aerial surveys

Yakutat

Fixed escapement goals

Weir counts, aerial surveys

Copper, Bering River

Fixed escapement goals

Weir counts

Upper Cook Inlet

Stocks in Northern/Central District systems caught incidental to directed sockeye fishery.

Fishery CPUE, limited weir count

 

Directed Westside set net fishery limited to two openings per week and reduced if CPUE low

 

Kodiak

Fixed escapement goal

Aerial survey, weir count

Chignik

Fixed escapement goal

Aerial survey, weir count

Alaska Peninsula

Fixed escapement goal

Aerial survey, weir count

Bristol Bay

Fixed escapement goal

Sonar count, aerial survey

Kuskokwim River

Reduced fishing periods when run strength is weak

Test fishery CPUE

Yukon River

Catch incidental to fall chum fishery, stock not fully exploited

Test fishery CPUE, sonar count

Pink salmon

 

Southeast Alaska

Fixed escapement goals

Aerial survey

Prince William Sound

Fixed escapement goals

Aerial survey, hatchery stock identification based on CWT

Lower Cook Inlet

Fixed escapement goals

Aerial survey

Kodiak

Fixed escapement goals

Aerial survey

Chignik

Fixed escapement goals

Aerial survey

Alaska Peninsula

Fixed escapement goals

Aerial survey

Bristol Bay, Norton Sound

Production highly variable, markets not well developed

None

Chum salmon

 

Southeast Alaska

Generally catches incidental to pink salmon, except for hatchery terminal harvest

Aerial surveys, poor quality due to presence of pink salmon

Prince William Sound

Generally catches incidental to pink salmon, except for hatchery terminal harvests

Aerial surveys, poor quality due to presence of pink salmon

Kodiak

Generally catches incidental to pink salmon, except for hatchery terminal harvests

Aerial surveys, poor quality due to presence of pink salmon

Alaska Peninsula

Generally catches incidental to pink salmon

Aerial surveys, poor quality due to presence of pink salmon

Bristol Bay

Harvests incidental to directed sockeye fishery

Nushagak sonar, aerial survey

Kuskokwim River

Fixed escapement goal

Sonar count, test fishery catches, weir counts, aerial survey

Yukon River

Fixed escapement goals, in river allocation plan, subsistence priority summer run fishery is market limited

Sonar count, test fishery catches

Norton Sound

Fixed escapement goal, large-run fisheries are market limited

Lower counts, aerial surveys, weir counts

Kotzebue Sound

Fixed escapement goal

Sonar count, aerial survey, test fishery catches

Sockeye salmon

 

Southeast Alaska

Fixed escapement goals, interception fishery limited by quota

Weir count, mark-recapture

Yakutat

Fixed escapement goal

Weir count, aerial survey

Copper/Bering River

Fixed escapement goal

Sonar count, aerial survey

Upper Cook Inlet

Fixed escapement goal

Sonar count, test fishery catches

Kodiak

Fixed escapement goal

Weir count, test fishery catches

Chignik

Fixed escapement goal

Weir count, test fishery catches

Alaska Peninsula

Fixed escapement goal, June interception quota set on Bristol Bay sockeye preseason forecast and chum cap

Weir count, aerial survey, test fishery catches

Bristol Bay

Fixed escapement goal

Lower count, sonar count, aerial survey, test fishery catches

Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×

TABLE H.5 Methods Used to Assess Pacific Herring

Area

Harvest Policy

Stock Assessment Methods

Southeast Alaska

Fixed harvest rate with threshold

Age-structured analysis tuned to biomass estimated with spawn deposition surveys

Prince William Sound

Fixed harvest rate with threshold

Age-structured analysis tuned to biomass estimated with spawn deposition surveys, aerial surveys

Lower Cook Inlet

Quota based on historical catches that maintained stable abundances; quota increments or decrements based on in-season abundance indices

Aerial surveys

Kodiak

Quota based on historical catches that maintained stable abundances; quota increments or decrements based on in-season abundance indices

Aerial surveys

Bristol Bay

Fixed harvest rate with threshold

Aerial surveys

Kuskokwim Bay

Quota based on historical catches that maintained stable abundances; quota increments or decrements based on in-season abundance indices

Aerial surveys

Norton Sound

Quota based on historical catches that maintained stable abundances; quota increments or decrements based on in-season abundance indices

Aerial surveys

Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×

TABLE H.6 Stock Assessment Methods Used by the Gulf States Marine Fisheries Commission

Species Name

Stock Assessment Methods

Comments

Gulf sturgeon

None—coast-wide annual population estimate in some Florida rivers

Listed as threatened; habitat and population status largely unknown

Striped mullet

VPA (GXPOPS, Florida) SSBR, SPR coast-wide

 

Gulf menhaden

VPA (basic and separable)

 

Black drum

VPA

Length cohort analysis

 

Striped bass

Limited SSBR

Tagging studies

 

Oyster

None

Local annual predictive models

Blue crab

None

Stock assessment to be attempted for 1997 FMP revision

Spanish mackerel

Surplus production yield per recruit

VPA—Florida

 

Gulf shrimp

Indices of abundance

 

Spotted seatrout

VPA

SPR

FMP to be published in 1997

Flounder

In progress (VPA, SPR)

FMP to be published in 1997

NOTE: FMP = fishery management plan; SPR = spawning biomass per recruit; SSBR = spawning stock biomass per recruit; VPA = virtual population analysis.

Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×
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Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×
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Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
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Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
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Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
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Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
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Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
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Suggested Citation:"Appendix H." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
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Page 160
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Ocean harvests have plateaued worldwide and many important commercial stocks have been depleted. This has caused great concern among scientists, fishery managers, the fishing community, and the public. This book evaluates the major models used for estimating the size and structure of marine fish populations (stock assessments) and changes in populations over time. It demonstrates how problems that may occur in fisheries data—for example underreporting or changes in the likelihood that fish can be caught with a given type of gear—can seriously degrade the quality of stock assessments. The volume makes recommendations for means to improve stock assessments and their use in fishery management.

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