National Academies Press: OpenBook

Improving Fish Stock Assessments (1998)

Chapter: Appendix D

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

Table D.1 contains a checklist of items that should be included and/or considered in a stock assessment. The assumptions given in Table D.1 should be considered in choosing a model and specific parameter values.

TABLE D.1 Checklist for Conducting or Reviewing Stock Assessments

Step

 

Important Considerations

1.0

Stock Definition

Stock structure

Single or multispecies

What is the spatial definition of a ''stock"?

Should the assessment be spatially structured or assumed to be spatially homogeneous?

Choose single-species or multi-species assessment?

Use tagging, micro-constituents, genetics, and/or morphometrics to define stock structure?

2.0

Data

 

2.1

Removal

Catch

Discarding

Fishing-induced mortality

Are removals included in the assessment?

Are biases and sampling design documented?

2.2

Indices of abundance

For all indices, consider whether an index is absolute or relative, sampling design, standardization, linearity between index and population abundance, what portion of stock is indexed (spawning stock, vulnerable biomass).

 

Catch per unit effort (CPUE)

What portions of the fleet should be included and how should data be standardized? How are zero catches treated? What assumptions are made about abundance in areas not fished? Spatial mapping of CPUE is especially informative.

 

Gear surveys (trawl,

longline, pot)

Is gear saturation a problem? Does survey design cover the entire range of the stock? How is gear selectivity assessed?

 

Acoustic surveys

Validate species mix and target strength.

 

Egg surveys

Estimate egg mortality, towpath of nets, and fecundity of females.

 

Line transect, strip counting

 

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

Step

 

Important Considerations

2.3

Age, size, and sex-structure information

 

 

Catch at age

Weight at age

Maturity at age

Size at age

Age-specific reproductive information

Consider sample design, sample size, high-grading selectivity, and ageing errors.

2.4

Tagging data

Consider both tag loss and shedding and tag return rates. Was population uniformly tagged or were samples recovered?

2.5

Environmental data

How should such data be used in the assessment? What are the dangers of searching databases for correlates?

2.6

Fishery information

Are people familiar with the fishery, who have spent time on fishing boats, consulted and involved in discussions of the value of different data sources?

3.0

Assessment Model

 

3.1

Age-, size-, length-, or sex-structured model?

Are alternative structures considered?

3.2

Spatially explicit or not?

 

3.3

Key model parameters

 

 

Natural mortality

Vulnerability

Fishing mortality

Catchability

Are these parameters assumed to be constant or are they estimated? If they are estimated, are prior distributions assumed? Are they assumed to be time invariant?

 

Recruitment

Is a relationship between spawning stock and recruitment assumed? If so, what variance is allowed? Is depensation considered as a possibility? Are environmentally driven reductions (or increases) in recruitment considered?

3.4

Statistical formulation

 

 

What process errors?

What observation errors?

What likelihood distributions?

If the model is in the form of weighted sum of squares, how are terms weighted? If the model is in the form of maximum likelihood, are variances estimated or assumed known?

3.5

Evaluation of uncertainty

 

 

Asymptotic estimates of variance

Likelihood profile Bootstrapping

Bayes posteriors

How is uncertainty in model parameters or between alternative models calculated? What is actually presented, a distribution or only confidence bounds?

3.6

Retrospective evaluation

Are retrospective patterns evaluated and presented?

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

Step

 

Important Considerations

4.0

Policy Evaluation

 

4.1

Alternative hypotheses

What alternatives are considered: parameters for a single model or different structural models?

How are the alternative hypotheses weighted?

What assumptions are used regarding future recruitment, environmental changes, stochasticity, and other factors?

Is the relationship between spawners and recruits considered? If so, do future projections include autocorrelation and depensation?

4.2

Alternative actions

What alternative harvest strategies are considered?

What tactics are assumed to be used in implementation?

How do future actions reflect potential changes in future population size?

Is implementation error considered?

Are errors autocorrelated?

How does implementation error relate to uncertainty in the assessment model?

4.3

Performance indicators

What is the real "objective" of the fishery? What are the best indicators of performance? What is the time frame for biological, social, and economic indices? How is "risk" measured? Are standardized reference points appropriate? Has overfishing been defined formally?

5.0

Presentation of Results

How are uncertainties in parameters and model structure presented? Can decision tables be used to summarize uncertainty and consequences? Is there explicit consideration of the trade-off between different performance indicators?

Do the decision-makers have a good understanding of the real uncertainty in the assessment and the trade-offs involved in making a policy choice?

Suggested Citation:"Appendix D." 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 D." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×
Page 137
Suggested Citation:"Appendix D." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×
Page 138
Suggested Citation:"Appendix D." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×
Page 139
Suggested Citation:"Appendix D." National Research Council. 1998. Improving Fish Stock Assessments. Washington, DC: The National Academies Press. doi: 10.17226/5951.
×
Page 140
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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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