Rigorous meta-analysis of life history correlations by simultaneously analyzing multiple population dynamics models

Area of Science:

• Ecology
• Population Dynamics
• Fisheries Science

Background:

• Life history parameter correlations are crucial in ecology but often estimated with flawed methods.
• Existing approaches ignore uncertainty and inter-species differences in demographic rate estimations.

Purpose of the Study:

• To develop and validate an improved method for estimating correlations among life history parameters.
• To address limitations in current ecological modeling by incorporating uncertainty and multi-species data.

Main Methods:

• Utilized multivariate likelihood profiles to approximate multi-species mixed-effects modeling.
• Synthesized information from multiple population dynamics models for improved accuracy.
• Applied the method to estimate natural mortality (M)/growth (k) ratios for 11 groundfish species.

Main Results:

• The multi-species approach demonstrated minimal bias and improved precision with more species.
• Estimated M/k ratio for Pacific rockfishes (Sebastes spp.) as 1.26, with a coefficient of variation of 76% for M given k.
• Provided the first estimate of life history parameter correlations for marine fishes using multiple age-structured models.

Conclusions:

• The developed method offers a robust standard for life history correlation studies in both marine and terrestrial species.
• Results for Pacific rockfishes can serve as a Bayesian prior for natural mortality estimation in fisheries management.
• Recommended compiling fish population dynamics models into a global database for meta-analyses.