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How to estimate life history ratios to simplify data-poor fisheries assessment
Journal article   Open access   Peer reviewed

How to estimate life history ratios to simplify data-poor fisheries assessment

Jeremy D. Prince, Chris Wilcox and Norman Hall
ICES journal of marine science, Vol.80(10), pp.2619-2629
2023
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Published1.09 MBDownloadView
CC BY V4.0 Open Access

Abstract

Fisheries Life Sciences & Biomedicine Marine & Freshwater Biology Oceanography Physical Sciences Science & Technology
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 L-m/L-infinity 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.

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Collaboration types
Domestic collaboration
Citation topics
3 Agriculture, Environment & Ecology
3.2 Marine Biology
3.2.92 Fisheries Ecology
Web Of Science research areas
Fisheries
Marine & Freshwater Biology
Oceanography
ESI research areas
Plant & Animal Science
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