**Abstract:** Traditional species distribution modeling (SDM) often struggles with limited data availability and disparate data formats across isolated island ecosystems. This paper introduces the Bayesian Inference Network for Island Endemic Species Distribution Modeling (BIN-IMSDM), a novel framework leveraging multi-modal federated learning and Bayesian inference to develop robust, spatially-explicit SDMs for island endemic species. BIN-IMSDM integrates diverse data streams (satellite imagery, field observations, citizen science data, climate projections) through a federated learning architecture, enabling collaborative model training without data centralization.

Pepper was overtaken by climate change during its post-glacial spread, a new study by the WSL shows.

Aim Species Distribution Models (SDMs) are widely used to map species distribution and predict future responses to climate change. While the risk of selecting biologically non-relevant predictors ha.....

Species distribution models (SDMs), broadly referring to both species distribution and ecological niche modelling frameworks, are widely used to predict habitat suitability. However, their performanc...

Abstract. Although we now have extensive biogeographical datasets for tetrapods, unravelling the drivers of species’ distributions remains challenging, esp

To model and map species’ habitat suitability, we used the N-SDM software11. N-SDM is an end-to-end SDM platform built around a spatially-nested framework. It combines a ‘global’ model, which quantifies the species’ response to bioclimatic conditions across its entire distributional...

Ecological niche models, crucial for estimating the potential distribution of species under global change, can face reduced accuracy when the timing of occurrence data does not align with the environ...

Kingsland, S. in Foundations of Ecology: Classic Papers with Commentaries (eds Real, L. & Brown, J.) 1–13 (Univ. Chicago Press, 1991). Grainger, T. N. et al. An empiricist’s guide to using ecological theory. Am. Nat. 199, 1–20 (2022). Novak, M...

Our study is divided into two sections: (1) a simulation study, where we illustrate the performance of BART in a presence/absence and pseudo-absences simulation and modeling framework, comparing it to other models such as MaxEnt and GAMs; and (2) a...

The scope and scale of past human impacts on both historic and current vegetation is of widespread interest in the historical sciences. In the Atlantic Fores...

This study demonstrated that it is possible with CNN-SDMs to circumvent the small size of a species abundance dataset per site through the combined use of a large presence-only species dataset and tr...

Context Comprehensive understanding of the distribution and habitat requirements of wildlife species is crucial for the development of effective conservation strategies. For cryptic predators, such as...

Theories of biodiversity rest on several macroecological patterns describing the relationship between species abundance and diversity. A central problem is that all theories make similar predictions f...

Understanding the spatial drivers of plant richness in mountainous regions is essential for biodiversity conservation. This study explores vascular plant richness in Spil Mountain, western Türkiye,...

We present a validated HSM for pine martens in Britain which can be used to identify areas for future reintroduction projects, such as Devon and Cumbria, as well as areas where woodland planting coul...

To our knowledge, this is the first empirical study to demonstrate the benefits of long-term dynamic SDMs with spatially matched predictor variables. If predicting the future of biodiversity under la...

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An analysis fusing satellite data with a process-based model of plant growth attributes changes in vegetation activity across terrestrial ecosystems to climatic changes.