Achieving higher standards in species distribution modeling by leveraging the diversity of available software

The increasing online availability of biodiversity data and advances in ecological modeling have led to a proliferation of open‐source modeling tools. In particular, R packages for species distribution modeling continue to multiply without guidance on how they can be employed together, resulting in high fidelity of researchers to one or several packages. Here, we assess the wide variety of software for species distribution models (SDMs) and highlight how packages can work together to diversify and expand analyses in each step of a modeling workflow. We also introduce the new R package ‘sdmverse' to catalog metadata for packages, cluster them based on their methodological functions, and visualize their relationships. To demonstrate how pluralism of software use helps improve SDM workflows, we provide three extensive and fully documented analyses that utilize tools for modeling and visualization from multiple packages, then score these tutorials according to recent methodological standards. We end by identifying gaps in the capabilities of current tools and highlighting outstanding challenges in the development of software for SDMs.

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Institutions

Publication Details

Journal
Ecography
Published
2024-11-19
DOI
https://doi.org/10.1111/ecog.07346
Citations
11
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
10.12

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article

Achieving higher standards in species distribution modeling by leveraging the diversity of available software

Cory Merow, Marlon E. Cobos, Dan L. Warren, Gonzalo E. Pinilla‐Buitrago et al.
11 citations
Ecography
Species Distribution and Climate Change
10.12
article

Achieving higher standards in species distribution modeling by leveraging the diversity of available software

Cory Merow, Marlon E. Cobos, Dan L. Warren, Gonzalo E. Pinilla‐Buitrago, Adam B. Smith, Hannah L. Owens, Ian Ondo, Santiago José Elías Velazco, Michael P. Nobis, Damaris Zurell, Antoine Guisan, Sylvain Schmitt, Matthew E. Aiello‐Lammens, Roozbeh Valavi, A. Márcia Barbosa, Sergio Vignali, Jamie M. Kass, Wilfried Thuiller, Babak Naimi, Luis Osorio‐Olvera, Eduardo Arlé, Alexander Zizka, Maya Guéguen, Olivier Broennimann, Andrea Sánchez‐Tapia
article en
11 citations

Abstract

The increasing online availability of biodiversity data and advances in ecological modeling have led to a proliferation of open‐source modeling tools. In particular, R packages for species distribution modeling continue to multiply without guidance on how they can be employed together, resulting in high fidelity of researchers to one or several packages. Here, we assess the wide variety of software for species distribution models (SDMs) and highlight how packages can work together to diversify and expand analyses in each step of a modeling workflow. We also introduce the new R package ‘sdmverse' to catalog metadata for packages, cluster them based on their methodological functions, and visualize their relationships. To demonstrate how pluralism of software use helps improve SDM workflows, we provide three extensive and fully documented analyses that utilize tools for modeling and visualization from multiple packages, then score these tutorials according to recent methodological standards. We end by identifying gaps in the capabilities of current tools and highlighting outstanding challenges in the development of software for SDMs.

EcographyVol. 2025(2)
University of Bern (CH), The Graduate Center, CUNY (US), University of Copenhagen (DK), City College of New York (US), Pace University (US), Commonwealth Scientific and Industrial Research Organisation (AU), Centre National de la Recherche Scientifique (FR), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (FR), Florida Museum of Natural History (US), University of Connecticut (US), Okinawa Institute of Science and Technology Graduate University (JP), University of Kansas (US), Charles Sturt University (AU), Philipps University of Marburg (DE), Tel Aviv University (IL), UN Environment Programme World Conservation Monitoring Centre (GB), Universidad Autónoma de la Ciudad de México (MX), City University of New York (US), University of Potsdam (DE), National University of Misiones (AR), Utrecht University (NL), Université de Montpellier (FR), Tohoku University (JP), San Diego State University (US), Royal Botanic Gardens, Kew (GB), Swiss Federal Institute for Forest, Snow and Landscape Research (CH), German Centre for Integrative Biodiversity Research (DE), Missouri Botanical Garden (US), University of Florida (US), Centro de Estudos em Geografia e Ordenamento do Territorio (PT), Forests and Societies (FR), Instituto de Pesquisas Jardim Botânico do Rio de Janeiro (BR), Laboratoire d'Écologie Alpine (FR), Instituto de Biología Subtropical (AR), Instituto de Ecología (MX), Universidad Nacional Autónoma de México (MX), Université Grenoble Alpes (FR), University of Lausanne (CH)
National Science Foundation, National Aeronautics and Space Administration, Villum Fonden, Deutsche Forschungsgemeinschaft, Nuclear Safety and Security Commission, Azrieli Foundation, Japan Society for the Promotion of Science
Life in Land
Openalex Percentile: Top 2%
Species Distribution and Climate Change
10.12
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