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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
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--> 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?
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--> 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?
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