Ecosystem‐based forecasts of recruitment in two menhaden species
| Autor: | Gerald M. Pao, Amy M. Schueller, George Sugihara, Ethan R. Deyle, Hao Ye |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
biology 010604 marine biology & hydrobiology Menhaden Management Monitoring Policy and Law Aquatic Science Oceanography biology.organism_classification 010603 evolutionary biology 01 natural sciences Ecosystem-based management Fishery Clupeidae Predictive power Ecosystem Atlantic menhaden Predictability Ecology Evolution Behavior and Systematics Stock (geology) |
| Zdroj: | Fish and Fisheries. 19:769-781 |
| ISSN: | 1467-2979 1467-2960 |
| DOI: | 10.1111/faf.12287 |
| Popis: | Gulf (Brevoortia patronus, Clupeidae) and Atlantic menhaden (Brevoortia tyrannus, Clupeidae) support large fisheries that have shown substantial variability over several decades, in part, due to dependence on annual recruitment. Nevertheless, traditional stock–recruitment relationships lack predictive power for these stocks. Current management of Atlantic menhaden explicitly treats recruitment as a random process. However, traditional methods for understanding recruitment variability carry the very specific hypothesis that the effect of adult biomass on subsequent recruitment occurs independently of other ecosystem factors such as food availability and predation. Here, we evaluate the predictability of menhaden recruitment using a model‐free approach that is not restricted by these strong assumptions. We find that menhaden recruitment is predictable, but only when allowing for interdependence of stock with other ecological factors. Moreover, while the analysis confirms the presence of environmental effects, the environment alone does not readily account for the complexity of menhaden recruitment dynamics. The findings set the stage for revisiting recruitment prediction in management and serve as an instructive example in the ongoing debate about how to best treat and understand recruitment variability across species and fisheries. |
| Databáze: | OpenAIRE |
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