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.

Funder

Funder name	Awards
Japan Society for the Promotion of Science, Japan	Postdoctoral Fellowships for Foreign Researchers Program - Grants-In-Aid for Scientific Research (KAKENHI) (20F20774)
Alan Graham Fund in Global Change
National Science Foundation, United States	DBI 1661510 - BoCP 2225078
National Aeronautics and Space Administration, United States	80NSSC18K0406. E - 80NSSC22K0883
Azrieli Foundation, Canada	International Postdoctoral Fellowship, in association with the Belmaker Lab – Marine Ecology and Biodiversity
Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica, Mexico	Project IA202824
Consejo Nacional de Humanidades, Ciencias y Tecnologías, Mexico	Ciencia de Frontera CF-2023-I-115
HORIZON EUROPE Marie Sklodowska-Curie Actions, European Union	Grant agreement no. 891702
Villum Fonden, Denmark	Research grant no. 25925
Deutsche Forschungsgemeinschaft, Germany	Grant no. ZU 361/6-1