Evolutionary Ecology

, Volume 26, Issue 5, pp 1153–1167

Gauging the impact of meta-analysis on ecology

  • Marc W. Cadotte
  • Lea R. Mehrkens
  • Duncan N. L. Menge
Original Paper

DOI: 10.1007/s10682-012-9585-z

Cite this article as:
Cadotte, M.W., Mehrkens, L.R. & Menge, D.N.L. Evol Ecol (2012) 26: 1153. doi:10.1007/s10682-012-9585-z


Meta-analyses are an increasingly used set of statistical tools that allow for data from multiple studies to be drawn together allowing broader, more generalizable conclusions. The extent to which the increase in the number of meta-analyses in ecology, relative to other types of papers, has influenced how questions are asked and the current state of knowledge has not been assessed before. Here, we gauge the impact of meta-analyses in ecology quantitatively and qualitatively. For the quantitative assessment, we conducted an analysis of 240 published meta-analyses to examine trends in ecological meta-analyses. Our examination shows that publication rates of meta-analyses in ecology have increased through time, and that more recent meta-analyses have been more comprehensive, including more studies and a greater temporal range of studies. Meta-analyses in ecology are the result of larger collaborations with meta-analyses being authored by larger teams than other studies, and those funded by collaborative centers have even larger collaborations. These larger collaborations result in a larger scope and scale of the analyses—by using more papers, datasets, species and years of data. Qualitatively, we discuss three examples: the strength of competition, the nature of how biodiversity affects ecosystem function, and the response of species to global climate change, where meta-analyses supplied the critical evaluation of accepted ecological explanations. As scientific criticism and controversy mount, the true power of meta-analyses is to serve as the capstone evidence supporting the validity of an explanation and to possibly herald the shift to other potential explanations.


BiodiversityCollaborationCompetitionDebateEcosystem functionHypothesis testing

Supplementary material

10682_2012_9585_MOESM1_ESM.docx (18 kb)
Supplementary material 1 (DOCX 18 kb)
10682_2012_9585_MOESM2_ESM.txt (22 kb)
Supplementary material 2 (TXT 22 kb)

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Marc W. Cadotte
    • 1
    • 2
  • Lea R. Mehrkens
    • 3
  • Duncan N. L. Menge
    • 4
    • 5
  1. 1.Biological SciencesUniversity of Toronto-ScarboroughTorontoUSA
  2. 2.Ecology and Evolutionary BiologyUniversity of TorontoTorontoUSA
  3. 3.School of Veterinary MedicineUniversity of CaliforniaDavisUSA
  4. 4.Department of Ecology and Evolutionary BiologyPrinceton UniversityPrincetonUSA
  5. 5.Department of BiologyStanford UniversityStanfordUSA