Retrospective forecasting — evaluating performance of stock projections for New England groundfish stocks
Projections are used to explore scenarios for catch advice and rebuilding and are an important tool for sustainably managing fisheries. We tested each projection specification for 12 groundfish stocks in the Northwest Atlantic to identify sources of bias and evaluate techniques for reducing bias. Pr...
| Published in: | Canadian Journal of Fisheries and Aquatic Sciences |
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| Main Authors: | , |
| Other Authors: | |
| Format: | Article in Journal/Newspaper |
| Language: | English |
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Canadian Science Publishing
2016
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| Online Access: | http://dx.doi.org/10.1139/cjfas-2015-0163 http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2015-0163 http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2015-0163 |
| Summary: | Projections are used to explore scenarios for catch advice and rebuilding and are an important tool for sustainably managing fisheries. We tested each projection specification for 12 groundfish stocks in the Northwest Atlantic to identify sources of bias and evaluate techniques for reducing bias. Projections were made from assessments using virtual population analysis (VPA) with 1–7 years of recent data removed from the full time series and were then compared with results from a VPA assessment on the full time series of data. The main source of bias in projections was the assessment model estimates of the numbers at age in the terminal model year + 1 (N a,T+1 ). Recruitment was responsible for more bias in projections beyond 3 years, when population numbers begin to be dominated by cohorts that were statistically generated. Retrospective analysis was performed and several adjustment factors to reduce bias were tested. Even after adjusting for bias, the remaining bias in projections was non-negligible. The direction of bias generally resulted in projected spawning stock biomass (SSB) and catch being overestimated, and the bias in catch was nearly always larger than in SSB. Scientists need to clearly communicate the direction and magnitude of this bias, managers need to consider this additional uncertainty when specifying future catch limits, and both scientists and managers need to develop more robust control rules so that objectives are achieved. |
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