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Media type:
E-Article
Title:
How to estimate life history ratios to simplify data-poor fisheries assessment
Contributor:
Prince, Jeremy D;
Wilcox, Chris;
Hall, Norman
imprint:
Oxford University Press (OUP), 2023
Published in:ICES Journal of Marine Science
Language:
English
DOI:
10.1093/icesjms/fsad026
ISSN:
1054-3139;
1095-9289
Origination:
Footnote:
Description:
<jats:title>Abstract</jats:title>
<jats:p>Less variable than life history parameters (LHPs), it is life history ratios (LHRs) that define how taxa allocate energy between growth, maintenance and reproduction, and respond to fishing pressure. Limited by small samples, variable data quality, and a focus on LHP estimation, previous meta-analyses have failed to settle debate about the extent to which LHRs are relatively invariant across all taxa or characteristic of specific taxa. We collected de novo 1335 published studies and applying rigorous standardization and quality control procedures developed, and make available, a database of high-quality M/K and Lm/L∞ estimates. We describe two parallel but independent meta-analyses: a cross-validation study of the predictability of M/K by taxonomic category and an evaluation of alternative relationships between the LHRs using Akaike information criteria. These analyses demonstrate that the LHRs are correlated and vary predictably by taxa, with aggregation to the level of family and genera having the most predictive power in our database. We postulate that the LHRs of taxa may relate to their stoichiometric niches, which could open up interesting lines for ecological research and provide new tools for predicting the LHRs of poorly studied taxa.</jats:p>