Practical interpretation of ecological meta-analyses

Department of Biology, York University, Toronto, ON, Canada
Centre for Reviews and Dissemination, University of York, York, UK
Department of Management, Baruch College, New York, New York, USA
Center for Clinical Evidence Synthesis, Brown University, Providence, RI, USA
DOI
10.7287/peerj.preprints.38v1
Subject Areas
Ecology, Statistics
Keywords
ecology, meta-analysis, synthesis, methods, statistics, interpretation, criteria
Copyright
© 2013 Lortie et al.
Licence
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.
Cite this article
Lortie CJ, Stewart G, Rothstein H, Lau J. 2013. Practical interpretation of ecological meta-analyses. PeerJ PrePrints 1:e38v1

Abstract

Meta-analysis offers ecologists a powerful tool for knowledge synthesis. There is however obvious and subtle issues to consider specific to ecology with respect to the appropriate interpretation of meta-analyses once the statistics are completed. Meta-analysts in any field must clearly define a priori the scope of inference and the purpose of the meta-analysis, but ecological meta-analysis often faces issues particular to this field. For example, the primary studies being combined, even for tests of the same hypothesis, in ecology are generally conducted at different study sites or have difference ecological contexts (i.e. often few studies are not conducted in a laboratory) and use very different methods to test a single hypothesis. General objectives of the meta-analysis could include assessment of confidence limits of the treatment or ecological process of interest, detection of differences in treatments from no effect, identification of research gaps, and differences between groups such as different populations or communities. Meta-analyses can also be used in ecology to assess whether the scope of tests of a hypothesis are adequate. Reporting more than one summary statistic such as different effect size metrics is an excellent means to enhance synthetic potential for ecologists. Magnitude and sign of effect sizes can also be interpreted in novel ways for ecology given the broad scope of forms of hypotheses explored in this discipline. Ecology is now poised to take advantage of the synthesis developments common in other disciplines and this brief conceptual methods review provides the appropriate framing for this endeavor.