<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Journal Article</dc:product_type><dc:title>A meta-evaluation of the quality of reporting and execution in ecological meta-analyses</dc:title><dc:creator>Pappalardo, Paula; Song, Chao; Hungate, Bruce A.; Osenberg, Craig W.</dc:creator><dc:corporate_author/><dc:editor>Silva, Daniel de</dc:editor><dc:description>&lt;p&gt;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.&lt;/p&gt;</dc:description><dc:publisher>PlosOne</dc:publisher><dc:date>2023-10-12</dc:date><dc:nsf_par_id>10479615</dc:nsf_par_id><dc:journal_name>PLOS ONE</dc:journal_name><dc:journal_volume>18</dc:journal_volume><dc:journal_issue>10</dc:journal_issue><dc:page_range_or_elocation>e0292606</dc:page_range_or_elocation><dc:issn>1932-6203</dc:issn><dc:isbn/><dc:doi>https://doi.org/10.1371/journal.pone.0292606</dc:doi><dcq:identifierAwardId>1655426</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>