APPENDIX C
TIER GOALS AND ASSESSMENT LEVELS IN NMFS’ STOCK ASSESSMENT IMPROVEMENT PLAN
The Stock Assessment Improvement Plan drafted by the NMFS National Task Force on Improving Fish Stock Assessments sets goals for improved stock assessments at three tiers above existing assessments.
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Tier 1—Improve assessments using existing data
Tier 2—Elevate all assessments to a nationally acceptable level
Tier 3—Next generation assessments
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STOCK ASSESSMENT LEVELS 1
The complexity of assessment methods used for a given stock generally reflects the availability of data and the value or importance of the fishery. The assessment level codes have the following meanings:
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Level 0—Although some data may have been collected on this species, these data have not been examined beyond simple time series plots or tabulations of catch.
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Level 1—Either:
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a time series of a (potentially imprecise) abundance index calculated as raw or standardized CPUE in commercial, recreational, or survey vessel data, or
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a one-time estimation of absolute abundance made on the basis of tagging results, a depletion study, or some form of calibrated survey.
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Level 2—Simple equilibrium models applied to life history information; for example, yield per recruit or spawner per recruit functions based on mortality, growth, and maturity schedules; catch curve analysis; survival analysis; or length cohort analysis.
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Level 3—Equilibrium and non-equilibrium production models aggregated both spatially and over age and size; for example, the Schaefer model and the Pella-Tomlinson model.
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Level 4—Size-, stage-, or age-structured models such as cohort analysis and untuned and tuned VPA analyses, age-structured production models, CAGEAN, stock synthesis, size or age-structured Bayesian models, modified DeLury methods, and size or age-based mark-recapture models.
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Level 5—Assessment models incorporating ecosystem considerations and spatial and seasonal analyses in addition to Levels 3 or 4. Ecosystem considerations include one or more of the following:
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one or more time-varying parameters, either estimated as constrained series, or driven by environmental variables,
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multiple target species as state variables in the model, or
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living components of the ecosystem other than the target species included as state variables in the model.
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