Species Distribution and Climate Change

This paper integrates structured and opportunistic species distribution data using a spatiotemporal model to improve predictions for mobile species.

The paper develops a multi-modal ResNet model to predict coastal fish occurrences using environmental seascape data, achieving high performance for some species but lower for others.

This study compares species-level and bioclimatic component prioritization in conservation planning, finding that bioclimatic prioritization better captures environmental heterogeneity and niche diversity.

This study identifies spatial priorities for protecting climatic niche variability and stability in European vertebrates, finding overlaps and trade-offs between conservation strategies.

The paper assesses the adequacy of occurrence data for predicting the distribution of common wild mammal species across Europe and identifies data gaps.

The paper introduces HDURBAN, a metric using ROC-AUC to quantify species' responses to urbanization, validated across multiple scenarios and species.

This study links bird observations to extreme weather risk maps, showing that accounting for extreme weather reduces species range sizes and biodiversity estimates.

This study shows that hornbills significantly influence plant range shifts under climate change, with dispersal limitation being a key constraint.

This study quantifies uncertainty in species distribution model-based blacklists for invasive plants by evaluating the impact of occurrence data, environmental predictors, algorithms, and thresholding methods.

This study identifies temperature and solar radiation as key drivers of Oxycarenus lavaterae range expansion using Maxent models and occurrence data.

This paper improves species-habitat modeling by integrating AI-derived multimodal habitat data and interpretable AI features for better conservation planning.

This paper introduces a framework to derive population and organismal-level ecological niches from individual-level niches, showing how higher-level niche properties can be partitioned into individual contributions and how species-level niche shifts can be estimated from individual responses.

This study shows that IUCN Red List methods underestimate extinction risk for species shifting ranges due to climate change, and suggests updates to the guidelines.

This paper introduces a method to identify species associations from citizen science data by analyzing spatial overlaps and filtering spurious correlations.

The paper models landscape suitability and range expansion for trumpeter swans, estimating a 4.4% annual expansion rate from 2023 to 2033.

This study evaluates whether including biotic factors improves species distribution models for three trophic levels, finding no significant difference in predictive power between models with abiotic-only, biotic-only, or combined factors.

This study maps the habitat suitability of Culex pipiens in Europe using ensemble bioclimatic modelling and identifies imperviousness as the most influential predictor.

This study uses Species Distribution Models to analyze how climate change affects four subspecies of Mus musculus in Asia, finding varying habitat changes and emphasizing the need for conservation strategies.

This study models the current and future distributions of two dominant Indian savanna tree species under climate change, finding significant habitat loss by 2100.

The paper uses herbarium specimens to show that closely related wildflower species, despite occupying diverse annual climates, track similar seasonal climate conditions through phenological shifts and spatial refugia.

This study models how climate change affects the distribution of the Junin virus reservoir, Calomys musculinus, identifying potential disease transmission hotspots under different climate scenarios.

The paper uses machine learning to classify flowering phenology from citizen science images, revealing peak flower production and flowering season length for many South African plant species.

This study predicts the future distribution of Juniperus procera under climate change scenarios and recommends conservation strategies to mitigate habitat loss and support adaptation.

This study improves species distribution modelling by identifying ecological parameters that reflect species-specific habitat preferences in red- and yellow-bellied toads.

This paper assesses the feasibility of reintroducing the black-veined white butterfly in England by evaluating habitat suitability, climate compatibility, and dispersal potential.

This study assesses climate change exposure across European protected areas and species, identifying regions with high risk and recommending network connectivity for adaptation.

This paper adapts joint species distribution models to ecological networks to model Eltonian niches, revealing trait and phylogeny relationships and enabling interaction predictions without empirical data.

The paper assesses how North American bird species mitigated climate niche loss through geographical redistribution over 20 years, finding partial success with significant remaining exposure to warming.

The paper develops demographic models to forecast range shifts of a dioecious plant species under climate change, showing that sex-specific responses affect predictions.

The paper uses species distribution modeling and spatial analysis to identify high-suitability habitats for the Philippine Eagle overlapping with mining concessions and indigenous lands, highlighting conservation risks and proposing mitigation strategies.