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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…

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

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

Climate change is a major driver of biodiversity loss, changing the geographic range and abundance of many species. However, there remain significant knowledge gaps about the distribution of species, due principally to the amount of effort…

Computer Vision and Pattern Recognition · Computer Science 2023-05-03 Mélisande Teng , Amna Elmustafa , Benjamin Akera , Hugo Larochelle , David Rolnick

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

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

Microclimate models are essential for linking climate to ecological processes, yet most physically based frameworks estimate temperature independently for each spatial unit and rely on simplified representations of lateral heat exchange. As…

Machine Learning · Computer Science 2026-03-17 Idan Sulami , Alon Itzkovitch , Michael R. Kearney , Moni Shahar , Ofir Levy

Species distribution models (SDMs) are widely used to predict species' geographic distributions, serving as critical tools for ecological research and conservation planning. Typically, SDMs relate species occurrences to environmental…

Machine Learning · Computer Science 2025-08-12 Hager Radi Abdelwahed , Mélisande Teng , Robin Zbinden , Laura Pollock , Hugo Larochelle , Devis Tuia , David Rolnick

We address an important problem in ecology called Species Distribution Modeling (SDM), whose goal is to predict whether a species exists at a certain position on Earth. In particular, we tackle a challenging version of this task, where we…

Machine Learning · Computer Science 2024-10-24 Shiran Yuan , Hao Zhao

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

The difficulty of monitoring biodiversity at fine scales and over large areas limits ecological knowledge and conservation efforts. To fill this gap, Species Distribution Models (SDMs) predict species across space from spatially explicit…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Lukas Picek , Christophe Botella , Maximilien Servajean , César Leblanc , Rémi Palard , Théo Larcher , Benjamin Deneu , Diego Marcos , Pierre Bonnet , Alexis Joly

The modeling of environmental ecosystems plays a pivotal role in the sustainable management of our planet. Accurate prediction of key environmental variables over space and time can aid in informed policy and decision-making, thus improving…

Computation and Language · Computer Science 2024-08-13 Haoran Li , Junqi Liu , Zexian Wang , Shiyuan Luo , Xiaowei Jia , Huaxiu Yao

This paper presents a novel approach in wildfire prediction through the integration of multisource spatiotemporal data, including satellite data, and the application of deep learning techniques. Specifically, we utilize an ensemble model…

Machine Learning · Computer Science 2025-01-07 Ayoub Jadouli , Chaker El Amrani

Increasing climate change and habitat loss are driving unprecedented shifts in species distributions. Conservation professionals urgently need timely, high-resolution predictions of biodiversity risks, especially in ecologically diverse…

Quantitative Methods · Quantitative Biology 2025-12-03 Hammed A. Akande , Abdulrauf A. Gidado

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

This paper describes a cascading multimodal pipeline for high-resolution biodiversity mapping across Europe, integrating species distribution modeling, biodiversity indicators, and habitat classification. The proposed pipeline first…

Artificial Intelligence · Computer Science 2025-04-08 César Leblanc , Lukas Picek , Benjamin Deneu , Pierre Bonnet , Maximilien Servajean , Rémi Palard , Alexis Joly

Estimating the geographical range of a species from sparse observations is a challenging and important geospatial prediction problem. Given a set of locations where a species has been observed, the goal is to build a model to predict…

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

Earthworms are key drivers of soil function, influencing organic matter turnover, nutrient cycling, and soil structure. Understanding the environmental controls on their distribution is essential for predicting the impacts of land use and…

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
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