Achieving higher standards in species distribution modeling by leveraging the diversity of available software - Archive ouverte HAL
Article Dans Une Revue Ecography Année : 2024

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

Jamie Kass
Adam Smith
Dan Warren
Sergio Vignali
Sylvain Schmitt
Matthew Aiello-Lammens
Eduardo Arlé
Ana Márcia Barbosa
Olivier Broennimann
Marlon Cobos
Maya Guéguen
Antoine Guisan
Cory Merow
Babak Naimi
Michael Nobis
Ian Ondo
Luis Osorio-Olvera
Hannah Owens
Gonzalo Pinilla-Buitrago
Andrea Sánchez-Tapia
Roozbeh Valavi
Santiago José Elías Velazco
Alexander Zizka
Damaris Zurell

Résumé

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.

Dates et versions

hal-04804491 , version 1 (26-11-2024)

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Jamie Kass, Adam Smith, Dan Warren, Sergio Vignali, Sylvain Schmitt, et al.. Achieving higher standards in species distribution modeling by leveraging the diversity of available software. Ecography, 2024, ⟨10.1111/ecog.07346⟩. ⟨hal-04804491⟩
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