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

IF 5.4 1区环境科学与生态学 Q1 BIODIVERSITY CONSERVATION

Ecography Pub Date : 2024-11-19 DOI:10.1111/ecog.07346

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

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引用次数: 0

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.

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利用现有软件的多样性，实现物种分布建模的更高标准

生物多样性数据的在线可用性不断提高，生态建模技术不断进步，导致开源建模工具激增。特别是，用于物种分布建模的 R 软件包不断增多，但却没有指导如何将它们结合起来使用，导致研究人员高度忠实于一个或几个软件包。在此，我们将对种类繁多的物种分布模型（SDM）软件进行评估，并重点介绍这些软件包如何在建模工作流程的每个步骤中协同工作，以实现分析的多样化和扩展性。我们还介绍了新的 R 软件包 "sdmverse"，它可以对软件包的元数据进行编目，根据方法功能对软件包进行聚类，并可视化它们之间的关系。为了展示软件使用的多元化如何有助于改进 SDM 工作流程，我们提供了三份内容广泛、记录完整的分析报告，其中使用了多个软件包的建模和可视化工具，然后根据最新的方法标准对这些教程进行评分。最后，我们指出了当前工具在功能上的差距，并强调了在开发 SDM 软件方面面临的突出挑战。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Ecography 环境科学-生态学

CiteScore

11.60

自引率

3.40%

发文量

122

审稿时长

8-16 weeks

期刊介绍： ECOGRAPHY publishes exciting, novel, and important articles that significantly advance understanding of ecological or biodiversity patterns in space or time. Papers focusing on conservation or restoration are welcomed, provided they are anchored in ecological theory and convey a general message that goes beyond a single case study. We encourage papers that seek advancing the field through the development and testing of theory or methodology, or by proposing new tools for analysis or interpretation of ecological phenomena. Manuscripts are expected to address general principles in ecology, though they may do so using a specific model system if they adequately frame the problem relative to a generalized ecological question or problem. Purely descriptive papers are considered only if breaking new ground and/or describing patterns seldom explored. Studies focused on a single species or single location are generally discouraged unless they make a significant contribution to advancing general theory or understanding of biodiversity patterns and processes. Manuscripts merely confirming or marginally extending results of previous work are unlikely to be considered in Ecography. Papers are judged by virtue of their originality, appeal to general interest, and their contribution to new developments in studies of spatial and temporal ecological patterns. There are no biases with regard to taxon, biome, or biogeographical area.