A meta-evaluation of the quality of reporting and execution in ecological meta-analyses.

Quantitatively summarizing results from a collection of primary studies with meta-analysis can help answer ecological questions and identify knowledge gaps. The accuracy of the answers depends on the quality of the meta-analysis. We reviewed the literature assessing the quality of ecological meta-analyses to evaluate current practices and highlight areas that need improvement. From each of the 18 review papers that evaluated the quality of meta-analyses, we calculated the percentage of meta-analyses that met criteria related to specific steps taken in the meta-analysis process (i.e., execution) and the clarity with which those steps were articulated (i.e., reporting). We also re-evaluated all the meta-analyses available from Pappalardo et al. [1] to extract new information on ten additional criteria and to assess how the meta-analyses recognized and addressed non-independence. In general, we observed better performance for criteria related to reporting than for criteria related to execution; however, there was a wide variation among criteria and meta-analyses. Meta-analyses had low compliance with regard to correcting for phylogenetic non-independence, exploring temporal trends in effect sizes, and conducting a multifactorial analysis of moderators (i.e., explanatory variables). In addition, although most meta-analyses included multiple effect sizes per study, only 66% acknowledged some type of non-independence. The types of non-independence reported were most often related to the design of the original experiment (e.g., the use of a shared control) than to other sources (e.g., phylogeny). We suggest that providing specific training and encouraging authors to follow the PRISMA EcoEvo checklist recently developed by O'Dea et al. [2] can improve the quality of ecological meta-analyses.
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2023 Pappalardo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)