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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

With the internet, a massive amount of information on species abundance can be collected under citizen science programs. However, these data are often difficult to use directly in statistical inference, as their collection is generally…

Applications · Statistics 2015-02-27 Christophe Giraud , Clément Calenge , Camille Coron , Romain Julliard

Precise and reliable climate projections are required for climate adaptation and mitigation, but Earth system models still exhibit great uncertainties. Several approaches have been developed to reduce the spread of climate projections and…

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 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

The US weather radar archive holds detailed information about biological phenomena in the atmosphere over the last 20 years. Communally roosting birds congregate in large numbers at nighttime roosting locations, and their morning exodus…

Computer Vision and Pattern Recognition · Computer Science 2020-04-28 Zezhou Cheng , Saadia Gabriel , Pankaj Bhambhani , Daniel Sheldon , Subhransu Maji , Andrew Laughlin , David Winkler

Due to recent climate changes, we have seen more frequent and severe wildfires in the United States. Predicting wildfires is critical for natural disaster prevention and mitigation. Advances in technologies in data processing and…

Machine Learning · Computer Science 2022-09-22 Hyung-Jin Yoon , Petros Voulgaris

1. Animal movement patterns contribute to our understanding of variation in breeding success and survival of individuals, and the implications for population dynamics. 2. Over time, sensor technology for measuring movement patterns has…

Quantitative Methods · Quantitative Biology 2018-01-11 Leah R. Johnson , Philipp H. Boersch-Supan , Richard A. Phillips , Sadie J. Ryan

The advancements in the state of the art of generative Artificial Intelligence (AI) brought by diffusion models can be highly beneficial in novel contexts involving Earth observation data. After introducing this new family of generative…

Computer Vision and Pattern Recognition · Computer Science 2024-02-20 Fulvio Sanguigni , Mikolaj Czerkawski , Lorenzo Papa , Irene Amerini , Bertrand Le Saux

Wetlands constitute critical ecosystems that support both biodiversity and human well-being; however, they have experienced a significant decline since the 20th century. Back in the 1970s, researchers began to employ remote sensing…

Computer Vision and Pattern Recognition · Computer Science 2025-04-22 Shuai Yuan , Xiangan Liang , Tianwu Lin , Shuang Chen , Rui Liu , Jie Wang , Hongsheng Zhang , Peng Gong

Joint Species Distribution Models are essential for understanding how ecological drivers shape species communities. However, most existing approaches are limited by rigid parametric distributions for count data and the inability to model…

Methodology · Statistics 2025-12-05 Lukas Graz , Luisa Barbanti , Roland Brandl , Torsten Hothorn

Models of the spatial distribution of animals provide useful tools to help ecologists quantify species-environment relationships, and they are increasingly being used to help determine the impacts of climate and habitat changes on species.…

Methodology · Statistics 2020-09-04 Joe Watson , Ruth Joy , Dominic Tollit , Sheila J Thornton , Marie Auger-Méthé

Species distribution models (SDMs), which aim to predict species occurrence based on environmental variables, are widely used to monitor and respond to biodiversity change. Recent deep learning advances for SDMs have been shown to perform…

Machine Learning · Computer Science 2025-11-14 Catherine Villeneuve , Benjamin Akera , Mélisande Teng , David Rolnick

Understanding the geographic distribution of species is a key concern in conservation. By pairing species occurrences with environmental features, researchers can model the relationship between an environment and the species which may be…

Computer Vision and Pattern Recognition · Computer Science 2020-04-10 Elijah Cole , Benjamin Deneu , Titouan Lorieul , Maximilien Servajean , Christophe Botella , Dan Morris , Nebojsa Jojic , Pierre Bonnet , Alexis Joly

The BIOSCAN project, led by the International Barcode of Life Consortium, seeks to study changes in biodiversity on a global scale. One component of the project is focused on studying the species interaction and dynamics of all insects. In…

Computer Vision and Pattern Recognition · Computer Science 2022-11-07 Nicholas Pellegrino , Zahra Gharaee , Paul Fieguth

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,…

We are losing biodiversity at an unprecedented scale and in many cases, we do not even know the basic data for the species. Traditional methods for wildlife monitoring are inadequate. Development of new computer vision tools enables the use…

Machine Learning · Computer Science 2019-08-08 Matteo Foglio , Lorenzo Semeria , Guido Muscioni , Riccardo Pressiani , Tanya Berger-Wolf

Determining spatial distributions of species and communities are key objectives of ecology and conservation. Joint species distribution models use multi-species detection-nondetection data to estimate species and community distributions.…

Applications · Statistics 2022-12-15 Jeffrey W. Doser , Andrew O. Finley , Sudipto Banerjee

Climate change and other anthropogenic factors have led to a catastrophic decline in insects, endangering both biodiversity and the ecosystem services on which human society depends. Data on insect abundance, however, remains woefully…

Computer Vision and Pattern Recognition · Computer Science 2024-06-21 Aditya Jain , Fagner Cunha , Michael Bunsen , Léonard Pasi , Anna Viklund , Maxim Larrivée , David Rolnick

In the face of significant biodiversity decline, species distribution models (SDMs) are essential for understanding the impact of climate change on species habitats by connecting environmental conditions to species occurrences.…

Machine Learning · Computer Science 2024-03-13 Robin Zbinden , Nina van Tiel , Marc Rußwurm , Devis Tuia