Sensitivity of, and Bias in, Catch-Survey Analysis (CSA) Estimates of Stock Abundance
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Catch-survey analysis (CSA) is an assessment method designed to estimate absolute stock abundance from total catch and relative indices, by filtering the latter through a simple two-stage population dynamics model. It qualifies as a tool for data-limited contexts since it does not require data on the full age composition, which are the main impediment to using conventional age-based approaches, either because age data are too costly to obtain routinely, or because some species cannot be reliably aged. This paper focuses on three issues that are not clearly settled in the sparse literature dealing with CSA:
- The sensitivity of stock size estimates to the ratio of recruits to fully recruited survey catchabilities, which needs to be set by the user based on external information; this study shows that sensitivity is not dependent on the magnitude of this parameter.
- The biases due to changes in catchability, which are to be expected when commercial CPUE data are used as indices; as with other methods, CSA estimates are biased high when increasing trends in the ratio between indices and abundance are not accounted for.
- The effects of occasional missing indices, which are an element of data limitations; in this example, these effects are found to be small and ephemeral.
Investigation of these questions was carried out using artificial data generated with a different, length- and age-structured model, providing true population states for comparisons with CSA estimates.
- Item number: AK-SG-05-02am
- Year: 2005
- DOI: https://doi.org/10.4027/famdis.2005.39