Literature DB >> 26099480

How to critically read ecological meta-analyses.

Christopher J Lortie1, Gavin Stewart2, Hannah Rothstein3, Joseph Lau4.   

Abstract

Meta-analysis offers ecologists a powerful tool for knowledge synthesis. Albeit a form of review, it also shares many similarities with primary empirical research. Consequently, critical reading of meta-analyses incorporates criteria from both sets of approaches particularly because ecology is a discipline that embraces heterogeneity and broad methodologies. The most important issues in critically assessing a meta-analysis initially include transparency, replicability, and clear statement of purpose by the authors. Specific to ecology, more so than other disciplines, tests of the same hypothesis are generally conducted at different study sites, have variable ecological contexts (i.e., seasonality), and use very different methods. Clear reporting and careful examination of heterogeneity in ecological meta-analyses is thus crucial. Ecologists often also test similar hypotheses with different species, and in these meta-analyses, the reader should expect exploration of phylogenetic dependencies. Finally, observational studies not only provide the substrate for potential current manipulative experiments in this discipline but also form an important body of literature historically for synthesis. Sensitivity analyses of observational versus manipulative experiments when aggregated in the same ecological meta-analysis are also frequent and appropriate. This brief conceptual review is not intended as an instrument to rate meta-analyses for ecologists but does provide the appropriate framing for those purposes and directs the reader to ongoing developments in this direction in other disciplines.
Copyright © 2013 John Wiley & Sons, Ltd.

Keywords:  and synthesis; criteria; ecology; guidelines; interpretation; meta-analysis; reading

Mesh:

Year:  2013        PMID: 26099480     DOI: 10.1002/jrsm.1109

Source DB:  PubMed          Journal:  Res Synth Methods        ISSN: 1759-2879            Impact factor:   5.273


  7 in total

Review 1.  Meta-analysis and the science of research synthesis.

Authors:  Jessica Gurevitch; Julia Koricheva; Shinichi Nakagawa; Gavin Stewart
Journal:  Nature       Date:  2018-03-07       Impact factor: 49.962

2.  Community-level impacts of white-tailed deer on understorey plants in North American forests: a meta-analysis.

Authors:  Christopher W Habeck; Alexis K Schultz
Journal:  AoB Plants       Date:  2015-10-20       Impact factor: 3.276

3.  Introducing Meta-Partition, a Useful Methodology to Explore Factors That Influence Ecological Effect Sizes.

Authors:  Zaida Ortega; Javier Martín-Vallejo; Abraham Mencía; Maria Purificación Galindo-Villardón; Valentín Pérez-Mellado
Journal:  PLoS One       Date:  2016-07-13       Impact factor: 3.240

Review 4.  Meta-evaluation of meta-analysis: ten appraisal questions for biologists.

Authors:  Shinichi Nakagawa; Daniel W A Noble; Alistair M Senior; Malgorzata Lagisz
Journal:  BMC Biol       Date:  2017-03-03       Impact factor: 7.431

5.  Dissecting the null model for biological invasions: A meta-analysis of the propagule pressure effect.

Authors:  Phillip Cassey; Steven Delean; Julie L Lockwood; Jason S Sadowski; Tim M Blackburn
Journal:  PLoS Biol       Date:  2018-04-23       Impact factor: 8.029

6.  Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences.

Authors:  Alec P Christie; David Abecasis; Mehdi Adjeroud; Juan C Alonso; Tatsuya Amano; Alvaro Anton; Barry P Baldigo; Rafael Barrientos; Jake E Bicknell; Deborah A Buhl; Just Cebrian; Ricardo S Ceia; Luciana Cibils-Martina; Sarah Clarke; Joachim Claudet; Michael D Craig; Dominique Davoult; Annelies De Backer; Mary K Donovan; Tyler D Eddy; Filipe M França; Jonathan P A Gardner; Bradley P Harris; Ari Huusko; Ian L Jones; Brendan P Kelaher; Janne S Kotiaho; Adrià López-Baucells; Heather L Major; Aki Mäki-Petäys; Beatriz Martín; Carlos A Martín; Philip A Martin; Daniel Mateos-Molina; Robert A McConnaughey; Michele Meroni; Christoph F J Meyer; Kade Mills; Monica Montefalcone; Norbertas Noreika; Carlos Palacín; Anjali Pande; C Roland Pitcher; Carlos Ponce; Matt Rinella; Ricardo Rocha; María C Ruiz-Delgado; Juan J Schmitter-Soto; Jill A Shaffer; Shailesh Sharma; Anna A Sher; Doriane Stagnol; Thomas R Stanley; Kevin D E Stokesbury; Aurora Torres; Oliver Tully; Teppo Vehanen; Corinne Watts; Qingyuan Zhao; William J Sutherland
Journal:  Nat Commun       Date:  2020-12-11       Impact factor: 14.919

7.  ROBITT: A tool for assessing the risk-of-bias in studies of temporal trends in ecology.

Authors:  Robin J Boyd; Gary D Powney; Fiona Burns; Alain Danet; François Duchenne; Matthew J Grainger; Susan G Jarvis; Gabrielle Martin; Erlend B Nilsen; Emmanuelle Porcher; Gavin B Stewart; Oliver J Wilson; Oliver L Pescott
Journal:  Methods Ecol Evol       Date:  2022-04-06       Impact factor: 8.335

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.