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Species distribution models (SDMs) aim to predict the distribution of species by relating occurrence data with environmental variables. Recent applications of deep learning to SDMs have enabled new avenues, specifically the inclusion of…

Machine Learning · Computer Science 2024-11-07 Nina van Tiel , Robin Zbinden , Emanuele Dalsasso , Benjamin Kellenberger , Loïc Pellissier , Devis Tuia

Species Distribution Models (SDMs) play a vital role in biodiversity research, conservation planning, and ecological niche modeling by predicting species distributions based on environmental conditions. The selection of predictors is…

Machine Learning · Computer Science 2025-08-22 Robin Zbinden , Nina van Tiel , Gencer Sumbul , Chiara Vanalli , Benjamin Kellenberger , Devis Tuia

Joint species distribution models are popular in ecology for modeling covariate effects on species occurrence, while characterizing cross-species dependence. Data consist of multivariate binary indicators of the occurrences of different…

Methodology · Statistics 2025-07-08 Federica Stolf , David B. Dunson

The post-2020 global biodiversity framework needs ambitious, research-based targets. Estimating the accelerated extinction risk due to climate change is critical. The International Union for Conservation of Nature (IUCN) measures the…

Populations and Evolution · Quantitative Biology 2024-01-12 Joaquim Estopinan , Pierre Bonnet , Maximilien Servajean , François Munoz , Alexis Joly

Climate change poses an extreme threat to biodiversity, making it imperative to efficiently model the geographical range of different species. The availability of large-scale remote sensing images and environmental data has facilitated the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-30 Theresa Chen , Yao-Yi Chiang

Conservation science depends on an accurate understanding of what's happening in a given ecosystem. How many species live there? What is the makeup of the population? How is that changing over time? Species Distribution Modeling (SDM) seeks…

Machine Learning · Computer Science 2021-07-23 Sara Beery , Elijah Cole , Joseph Parker , Pietro Perona , Kevin Winner

Do ecosystems primarily reflect evolutionary history or current environment? Predicting land-atmosphere exchange hinges on this unresolved question. Plant traits adapt to particular environments over evolutionary timescales, yet their…

Geophysics · Physics 2025-12-16 Jianing Fang , Kevin Bowman , Wenli Zhao , Xu Lian , Pierre Gentine

Biodiversity is declining at an unprecedented rate, impacting ecosystem services necessary to ensure food, water, and human health and well-being. Understanding the distribution of species and their habitats is crucial for conservation…

Understanding the environmental drivers of forest transpiration is critical for improving global predictions of water availability and ecosystem health. Due to many competing controls on plant water stress and ecosystem transpiration,…

Quantitative Methods · Quantitative Biology 2026-05-22 Morgan Thornwell , David Yang , Cheng-Wei Huang , Peyman Abbaszadeh , Samantha Hartzell

Species distribution models (SDMs) are important statistical tools for ecologists to understand and predict species range. However, standard SDMs do not explicitly incorporate dynamic processes like dispersal. This limitation may lead to…

Populations and Evolution · Quantitative Biology 2021-08-27 Julie Louvrier , Julien Papaïx , Christophe Duchamp , Olivier Gimenez

Habitats integrate the abiotic conditions, vegetation composition and structure that support biodiversity and sustain nature's contributions to people. Most habitats face mounting pressures from human activities, which requires accurate,…

Understanding how species are distributed across landscapes over time is a fundamental question in biodiversity research. Unfortunately, most species distribution models only target a single species at a time, despite strong ecological…

Machine Learning · Computer Science 2017-02-22 Di Chen , Yexiang Xue , Shuo Chen , Daniel Fink , Carla Gomes

Accelerating global biodiversity loss has highlighted the role of complex relationships and shared patterns among species in determining their responses to environmental changes. The structure of an ecological community, represented by…

Applications · Statistics 2025-09-03 Braden Scherting , Otso Ovaskainen , David B. Dunson

Most deep-learning frameworks for understanding biological swarms are designed to fit perceptive models of group behavior to individual-level data (e.g., spatial coordinates of identified features of individuals) that have been separately…

Computational Engineering, Finance, and Science · Computer Science 2021-08-24 Taeyeong Choi , Benjamin Pyenson , Juergen Liebig , Theodore P. Pavlic

Monitoring species distribution is vital for conservation efforts, enabling the assessment of environmental impacts and the development of effective preservation strategies. Traditional data collection methods, including citizen science,…

Machine Learning · Computer Science 2025-10-23 Chirag Padubidri , Pranesh Velmurugan , Andreas Lanitis , Andreas Kamilaris

Species distribution models (SDM) are a key tool in ecology, conservation and management of natural resources. Two key components of the state-of-the-art SDMs are the description for species distribution response along environmental…

Methodology · Statistics 2021-11-08 Jarno Vanhatalo , Marcelo Hartmann , Lari Veneranta

1. Joint Species Distribution models (JSDMs) explain spatial variation in community composition by contributions of the environment, biotic associations, and possibly spatially structured residual covariance. They show great promise as a…

Quantitative Methods · Quantitative Biology 2023-03-28 Maximilian Pichler , Florian Hartig

One of the first beings affected by changes in the climate are trees, one of our most vital resources. In this study tree species interaction and the response to climate in different ecological environments is observed by applying a joint…

Populations and Evolution · Quantitative Biology 2019-10-14 Hyun Choi , Ali Sadeghian , Sergio Marconi , Ethan White , Daisy Zhe Wang

This paper focuses on a core task in computational sustainability and statistical ecology: species distribution modeling (SDM). In SDM, the occurrence pattern of a species on a landscape is predicted by environmental features based on…

Machine Learning · Computer Science 2021-02-19 Eugene Seo , Rebecca A. Hutchinson , Xiao Fu , Chelsea Li , Tyler A. Hallman , John Kilbride , W. Douglas Robinson

Species distribution models (SDMs) are increasingly applied across macroscales. Such models typically assume that a single set of regression coefficients can adequately describe species-environment relationships and/or population trends.…

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