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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…

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,…

The difficulty to measure or predict species community composition at fine spatio-temporal resolution and over large spatial scales severely hampers our ability to understand species assemblages and take appropriate conservation measures.…

This paper describes GeoPl@ntNet, an interactive web application designed to make Essential Biodiversity Variables accessible and understandable to everyone through dynamic maps and fact sheets. Its core purpose is to allow users to explore…

定量方法 · 定量生物学 2026-04-15 Lukas Picek , César Leblanc , Alexis Joly , Pierre Bonnet , Rémi Palard , Maximilien Servajean

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…

机器学习 · 计算机科学 2024-11-07 Nina van Tiel , Robin Zbinden , Emanuele Dalsasso , Benjamin Kellenberger , Loïc Pellissier , Devis Tuia

Multimodal Foundation Models (FMs) offer a path to learn general-purpose representations from heterogeneous ecological data, easily transferable to downstream tasks. However, practical biodiversity modelling remains fragmented; separate…

Biodiversity research requires complete and detailed information to study ecosystem dynamics at different scales. Employing data-driven methods like Machine Learning is getting traction in ecology and more specific biodiversity, offering…

定量方法 · 定量生物学 2025-10-27 Stylianos Stasinos , Martino Mensio , Elena Lazovik , Athanasios Trantas

Understanding the spatio-temporal distribution of species is a cornerstone of ecology and conservation. By pairing species observations with geographic and environmental predictors, researchers can model the relationship between an…

计算机视觉与模式识别 · 计算机科学 2025-10-01 Christophe Botella , Benjamin Deneu , Diego Marcos , Maximilien Servajean , Theo Larcher , Cesar Leblanc , Joaquim Estopinan , Pierre Bonnet , Alexis Joly

The EUNIS habitat classification is crucial for categorising European habitats, supporting European policy on nature conservation and implementing the Nature Restoration Law. To meet the growing demand for detailed and accurate habitat…

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…

计算机视觉与模式识别 · 计算机科学 2024-12-30 Theresa Chen , Yao-Yi Chiang

We discuss species distribution models (SDM) for biodiversity studies in ecology. SDM plays an important role to estimate abundance of a species based on environmental variables that are closely related with the habitat of the species. The…

应用统计 · 统计学 2023-05-01 Osamu Komori , Yusuke Saigusa , Shinto Eguchi

We focus on species distribution modeling using global-scale presence-only data, leveraging geographical and environmental features to map species ranges, as in previous studies. However, we innovate by integrating taxonomic classification…

计算机视觉与模式识别 · 计算机科学 2025-09-09 Srikumar Sastry , Xin Xing , Aayush Dhakal , Subash Khanal , Adeel Ahmad , Nathan Jacobs

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…

机器学习 · 计算机科学 2024-10-24 Shiran Yuan , Hao Zhao

Marine biodiversity monitoring requires scalability and reliability across complex underwater environments to support conservation and invasive-species management. Yet existing detection solutions often exhibit a pronounced deployment gap,…

计算机视觉与模式识别 · 计算机科学 2026-01-21 Marco Piccolo , Qiwei Han , Astrid van Toor , Joachim Vanneste

Accurately predicting the geographic ranges of species is crucial for assisting conservation efforts. Traditionally, range maps were manually created by experts. However, species distribution models (SDMs) and, more recently, deep…

定量方法 · 定量生物学 2024-08-29 Filip Dorm , Christian Lange , Scott Loarie , Oisin Mac Aodha

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…

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…

种群与进化 · 定量生物学 2024-01-12 Joaquim Estopinan , Pierre Bonnet , Maximilien Servajean , François Munoz , Alexis Joly

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…

机器学习 · 计算机科学 2021-07-23 Sara Beery , Elijah Cole , Joseph Parker , Pietro Perona , Kevin Winner

The mapping of plant biodiversity represents a fundamental stage in establishing conservation priorities, particularly in identifying groups of species that share ecological requirements or evolutionary histories. This is often achieved by…

种群与进化 · 定量生物学 2025-07-09 Maxime Lenormand , Jean-Baptiste Féret , Guillaume Papuga , Samuel Alleaume , Sandra Luque

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…

机器学习 · 计算机科学 2017-02-22 Di Chen , Yexiang Xue , Shuo Chen , Daniel Fink , Carla Gomes
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