A checklist for choosing between R packages in ecology and evolution
Abstract The open source and free programming language R is a phenomenal mechanism to address a multiplicity of challenges in ecology and evolution. It is also a complex ecosystem because of the diversity of solutions available to the analyst. Packages for R enhance and specialize the capacity to ex...
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doaj-08c941b344a9407b89bceff18fe2f24a2021-04-02T12:56:32ZengWileyEcology and Evolution2045-77582020-02-011031098110510.1002/ece3.5970A checklist for choosing between R packages in ecology and evolutionChristopher J. Lortie0Jenna Braun1Alessandro Filazzola2Florencia Miguel3Department of Biology York University Toronto ON CanadaDepartment of Biology York University Toronto ON CanadaBiological Sciences University of Alberta Edmonton AB CanadaNational Scientific and Technical Research Council CONICET Buenos Aires ArgentinaAbstract The open source and free programming language R is a phenomenal mechanism to address a multiplicity of challenges in ecology and evolution. It is also a complex ecosystem because of the diversity of solutions available to the analyst. Packages for R enhance and specialize the capacity to explore both niche data/experiments and more common needs. However, the paradox of choice or how we select between many seemingly similar options can be overwhelming and lead to different potential outcomes. There is extensive choice in ecology and evolution between packages for both fundamental statistics and for more specialized domain‐level analyses. Here, we provide a checklist to inform these decisions based on the principles of resilience, need, and integration with scientific workflows for evidence. It is important to explore choices in any analytical coding environment—not just R—for solutions to challenges in ecology and evolution, and document this process because it advances reproducible science, promotes a deeper understand of the scientific evidence, and ensures that the outcomes are correct, representative, and robust.https://doi.org/10.1002/ece3.5970checklistguidelinesheuristicopen sourceparadox of choiceR programming language |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Christopher J. Lortie Jenna Braun Alessandro Filazzola Florencia Miguel |
spellingShingle |
Christopher J. Lortie Jenna Braun Alessandro Filazzola Florencia Miguel A checklist for choosing between R packages in ecology and evolution Ecology and Evolution checklist guidelines heuristic open source paradox of choice R programming language |
author_facet |
Christopher J. Lortie Jenna Braun Alessandro Filazzola Florencia Miguel |
author_sort |
Christopher J. Lortie |
title |
A checklist for choosing between R packages in ecology and evolution |
title_short |
A checklist for choosing between R packages in ecology and evolution |
title_full |
A checklist for choosing between R packages in ecology and evolution |
title_fullStr |
A checklist for choosing between R packages in ecology and evolution |
title_full_unstemmed |
A checklist for choosing between R packages in ecology and evolution |
title_sort |
checklist for choosing between r packages in ecology and evolution |
publisher |
Wiley |
series |
Ecology and Evolution |
issn |
2045-7758 |
publishDate |
2020-02-01 |
description |
Abstract The open source and free programming language R is a phenomenal mechanism to address a multiplicity of challenges in ecology and evolution. It is also a complex ecosystem because of the diversity of solutions available to the analyst. Packages for R enhance and specialize the capacity to explore both niche data/experiments and more common needs. However, the paradox of choice or how we select between many seemingly similar options can be overwhelming and lead to different potential outcomes. There is extensive choice in ecology and evolution between packages for both fundamental statistics and for more specialized domain‐level analyses. Here, we provide a checklist to inform these decisions based on the principles of resilience, need, and integration with scientific workflows for evidence. It is important to explore choices in any analytical coding environment—not just R—for solutions to challenges in ecology and evolution, and document this process because it advances reproducible science, promotes a deeper understand of the scientific evidence, and ensures that the outcomes are correct, representative, and robust. |
topic |
checklist guidelines heuristic open source paradox of choice R programming language |
url |
https://doi.org/10.1002/ece3.5970 |
work_keys_str_mv |
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1721567039466766336 |