Formalizing the definition of meta‐analysis in Molecular Ecology

Abstract

Meta-analysis, the statistical synthesis of pertinent literature to develop evidence-based conclusions, is relatively new to the field of molecular ecology, with the first metaanalysis published in the journal Molecular Ecology in 2003 (Slate & Phua 2003). The goal of this article is to formalize the definition of meta-analysis for the authors, editors, reviewers and readers of Molecular Ecology by completing a review of the meta-analyses previously published in this journal. We also provide a brief overview of the many components required for meta-analysis with a more specific discussion of the issues related to the field of molecular ecology, including the use and statistical considerations of Wright's F ST and its related analogues as effect sizes in meta-analysis. We performed a literature review to identify articles published as 'metaanalyses' in Molecular Ecology, which were then evaluated by at least two reviewers. We specifically targeted Molecular Ecology publications because as a flagship journal in this field, meta-analyses published in Molecular Ecology have the potential to set the standard for meta-analyses in other journals. We found that while many of these reviewed articles were strong meta-analyses, others failed to follow standard meta-analytical techniques. One of these unsatisfactory meta-analyses was in fact a secondary analysis. Other studies attempted metaanalyses but lacked the fundamental statistics that are considered necessary for an effective and powerful metaanalysis. By drawing attention to the inconsistency of studies labelled as meta-analyses, we emphasize the importance of understanding the components of traditional meta-analyses to fully embrace the strengths of quantitative data synthesis in the field of molecular ecology.

Evolutionary processes driving spatial patterns of intraspecific genetic diversity in river ecosystems

“…However, the nonrandom distribution of genetic diversity in these systems may have a strong influence on the ability of populations to adapt to local conditions (Kawecki & Holt 2002). We hence believe that the time is ripe to make a valuable use of the large amount of data that has been collected in the last decades in population genetics, so as to transform a collection of independent case studies into general rules (ArchMiller et al 2015). As describing and understanding the patterns of biological diversity is one of the bases of integrative and efficient conservation measures (Chave 2013), this should become a priority for population and conservation geneticists.…”

Peer Review #2 of "Diversity, spatial distribution and activity of fungi in freshwater ecosystems (v0.1)"

“…When proper analytical treatment is applied, meta-analyses are powerful analytical tools to decipher the structure and ecology of microbial communities (ArchMiller et al, 2015). When analyzing the global microbial eukaryotic diversity in freshwaters, using the same dataset as in our study, Debroas et al (2017) showed that fungi represented 17% of this diversity.…”

Nonindependence and sensitivity analyses in ecological and evolutionary meta‐analyses

“…; Koricheva & Gurevitch ; ArchMiller et al . ). In our paper, we have described how nonindependence can affect the calculation of effect size statistics, and result in correlations among effect size estimates.…”

“…; Koricheva & Gurevitch ; ArchMiller et al . ), suggesting a major under appreciation of its potential impact on study conclusions.…”