Giants' shoulders 15 years later: lessons,challenges and guidelines in fisheries meta‐analysis |
| |
Authors: | James T Thorson Jason M Cope Kristin M Kleisner Jameal F Samhouri Andrew O Shelton Eric J Ward |
| |
Affiliation: | 1. Fisheries Resource Assessment and Monitoring Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA;2. Sea Around Us Project, University of British Columbia, Vancouver, BC, Canada;3. Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA |
| |
Abstract: | Meta‐analysis has been an integral tool for fisheries researchers since the late 1990s. However, there remain few guidelines for the design, implementation or interpretation of meta‐analyses in the field of fisheries. Here, we provide the necessary background for readers, authors and reviewers, including a brief history of the use of meta‐analysis in fisheries, an overview of common model types and distinctions, and examples of different goals that can be achieved using meta‐analysis. We outline the primary challenges in implementing meta‐analyses, including difficulties in discriminating between alternative hypotheses that can explain the data with equal plausibility, the importance of validating results using multiple lines of evidence, the trade‐off between complexity and sample size and problems associated with the use of model output. For each of these challenges, we also provide suggestions, such as the use of propensity scores for dealing with selection bias and the use of covariates to control for confounding effects. These challenges are then illustrated with examples from diverse subfields of fisheries, including (i) the analysis of the stock–recruit relationship, (ii) fisheries management, rebuilding and population viability, (iii) habitat‐specific vital rates, (iv) life‐history theory and (v) the evaluation of marine reserves. We conclude with our reasons for believing that meta‐analysis will continue to grow in importance for these and many other research goals in fisheries science and argue that standards of practice are therefore essential. |
| |
Keywords: | Effect size fisheries models hierarchical models meta‐analysis research synthesis |
|
|