ENM2020: A Free Online Course and Set of Resources on Modeling Species' Niches and Distributions

Abstract

The field of distributional ecology has seen considerable recent attention, particularly surrounding the theory, protocols, and tools for Ecological Niche Modeling (ENM) or Species Distribution Modeling (SDM). Such analyses have grown steadily over the past two decades—including a maturation of relevant theory and key concepts—but methodological consensus has yet to be reached. In response, and following an online course taught in Spanish in 2018, we designed a comprehensive English-language course covering much of the underlying theory and methods currently applied in this broad field. Here, we summarize that course, ENM2020, and provide links by which resources produced for it can be accessed into the future. ENM2020 lasted 43 weeks, with presentations from 52 instructors, who engaged with >2500 participants globally through >14,000 hours of viewing and >90,000 views of instructional video and question-and-answer sessions. Each major topic was introduced by an “Overview” talk, followed by more detailed lectures on subtopics. The hierarchical and modular format of the course permits updates, corrections, or alternative viewpoints, and generally facilitates revision and reuse, including the use of only the Overview lectures for introductory courses. All course materials are free and openly accessible (CC-BY license) to ensure these resources remain available to all interested in distributional ecology.

Landscape‐level heterogeneity of agri‐environment measures improves habitat suitability for farmland birds

“…Our study aimed at assessing the contribution of AEMs to farmland birds' habitat conservation over a large agricultural region: Although the relationship between population size and area and quality of habitat is complex and species‐specific, avian SDMs from presence/absence data were shown to correlate positively and significantly with population densities and abundances (Carrascal et al, 2015; Oliver et al, 2012). Moreover, despite the constantly growing availability of resources and methods for SDMs (Peterson et al, 2022), modeling and predicting spatial variation in abundances remains a challenging task, and extrapolated abundance predictions under changing environmental scenarios often have high uncertainty (Waldock et al, 2022). New methodological frameworks linking changes in area of habitat to species persistence have recently been developed (Durán et al, 2020).…”

Modelling the distribution of marine fishery resources: Where are we?

“…The growing number of articles is also related to the growing computational power that allows researchers to develop models with some mastery. Additionally, the expansion of free software, open languages (e.g., R, Python), forums, tutorials, and courses (Cobos et al, 2019; Peterson et al, 2022) is increasing users familiarity. Computational power also increases the number of possible answers given by scientists, who have been incorporating increasing complexity into the models (Coll et al, 2020).…”

“…TA B L E 3 Number of studies among the taxonomic groups and focus of research publishing about ENMs/SDMs in fishery resources The frequency may be based in counts larger than the total amount of retained articles (378) due to the possibility of multiple fitting among categories.to growing computational power that allows researchers to develop models with some mastery. Additionally, the expansion of free software, open languages (e.g., R, Python), forums, tutorials, and courses(Cobos et al, 2019;Peterson et al, 2022) is increasing users familiarity. Computational power also increases the number of possible answers given by scientists, who have been incorporating increasing complexity into the models(Coll et al, 2020).…”

The integration of whole‐genome resequencing and ecological niche modelling to conserve profiles of local adaptation

“…Here we exploit the rising number of WGR studies to demonstrate why and how WGR should be integrated with ENM with particular focus on the ability of WGR data to illuminate adaptive genetic characteristics. Efforts to integrate genomics and ENM are accelerating (e.g., the recent WIGGIS workshop, https://wiggis.eu/) as WGR becomes more affordable (Wetterstrand, 2021) and as ENM applications broaden (Peterson et al., 2022). Like others (e.g., Waldvogel et al., 2020), we think that comprehensive, integrative studies of individual genomes and their distributions in space and time have great potential to identify adaptation profiles and help guide conservation efforts.…”