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Life history changes and fisheries assessment performance: a case study for small yellow croaker
Author(s) -
Qi Lee,
Alice Lee,
Zunlei Liu,
Cody Szuwalski
Publication year - 2019
Publication title -
ices journal of marine science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.348
H-Index - 117
eISSN - 1095-9289
pISSN - 1054-3139
DOI - 10.1093/icesjms/fsz232
Subject(s) - fishing , life history , trophic level , fishery , biomass (ecology) , fisheries management , stock assessment , population , geography , life history theory , estimation , environmental science , ecology , biology , demography , economics , management , sociology
Many intensely exploited fish stocks have experienced changes in trophic structure and environmental conditions, resulting in non-stationary population processes. We evaluate the ability of assessment methods to estimate quantities used in management (like target biomasses and fishing mortalities) when life history processes are non-stationary and comprehensive data are not available. We use the small yellow croaker (Larimichthys polyactis) fishery in the East China and Yellow Seas as a case study. We simulate age-structured populations with time-varying fishery and life history characteristics similar to that of the small yellow croaker in China based on historical studies that demonstrate changes in life history. We then fit surplus production and statistical catch-at-age models to simulated catch and index data from these populations. Given our assumptions, both estimation models yielded biased quantities important to management. The production model estimated reference points associated with target biomass with less bias than the age-structured model, while the latter outperformed the former when estimating reference points associated with target fishing mortality. The age-structured model also better captured relative population trends and provided flexibility to consider impacts of life history changes over time. We suggest that assessments of similar stocks consider the potential of life history variation impact management quantities.

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