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Published on: August 22, 2018
Metaresearch for Evaluating Reproducibility in Ecology and Evolution.
Fiona Fidler1, Yung En Chee1, Bonnie C Wintle1
1Associate Professor Fiona Fidler (fidlerfm@unimelb.edu.au) holds a joint appointment in the School of BioSciences and the School of Historical and Philosophical Studies (History and Philosophy of Science Discipline) at the University of Melbourne, Australia; Fiona is interested in how scientists and experts make decisions. Bonnie C. Wintle is a postdoctoral fellow and Mark Burgman and Michael McCarthy are professors in the School of BioSciences at the University of Melbourne, Australia; they are interested in a broad range of topics related to environmental decisionmaking. Bonnie Wintle is now a research fellow at the Centre for Research in the Arts, Social Sciences and Humanities, University of Cambridge. Yung En Chee is a senior research fellow in the School of Ecosystem and Forest Sciences at the University of Melbourne, Australia; Yung applies ecological and decision-analytic theory and models to conservation problems. Ascelin Gordon is a senior research fellow in the Interdisciplinary Conservation Science Research Group in the School of Global, Urban, and Social Studies at RMIT University, in Melbourne, Australia; Ascelin is broadly interested in modeling approaches for understanding the impacts of environmental policies. FF, YC, BW, MB and MM were involved in discussion group about reproducibility and type 1 errors in ecology in 2014, which helped develop the outline for this article. AG and FF independently discussed the application of open science initiatives in ecology. FF wrote the first draft; YC wrote sections on data and code sharing with substantial input from AG. BW, MB, and MM made edits throughout.
Replication in ecology is facing challenges due to issues like low statistical power and publication bias. This study proposes metaresearch to assess the reproducibility of ecological evidence, offering proxy measures where direct replication is difficult.
Area of Science:
- Ecology and Evolutionary Biology
- Metaresearch
- Scientific Reproducibility
Background:
- Replication projects in other fields reveal low reproducibility, indicating potential unverifiable claims.
- Ecology shares conditions that hinder reproducibility, including low statistical power and publication bias.
- Journal policies and research culture may exacerbate irreproducibility in ecological sciences.
Purpose of the Study:
- To systematically evaluate the reproducibility of the evidence base in ecology and evolution.
- To address the challenges of direct replication in ecological research due to temporal and spatial dependencies.
- To propose metaresearch projects offering proxy measures for ecological research reproducibility.
Main Methods:
- Analysis of factors contributing to irreproducibility in ecology.
- Identification of conditions mirroring those in other disciplines.
- Proposal of metaresearch strategies as proxy measures for reproducibility.
Main Results:
- Ecological research exhibits conditions similar to other disciplines with low reproducibility.
- Direct replication in ecology is often challenging due to inherent study system complexities.
- Metaresearch projects are proposed as a viable alternative to assess reproducibility.
Conclusions:
- The current state of ecological research warrants a systematic evaluation of its reproducibility.
- Proxy measures through metaresearch are necessary due to the difficulties in direct replication.
- Ensuring the reliability of ecological evidence is crucial for advancing the field.
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