Simon Chamaillé‐Jammes

This study determines optimal buffer sizes for African swine fever containment by analyzing wild boar movement patterns and environmental factors across Europe.

This paper systematically reviews drivers of birth phenology in large herbivores, finding strong support for seasonality and predation hypotheses but highlighting gaps in Asian and South/Central American species.

This study examines how prey abundance and catchability at waterholes influence lion visitation patterns in a savannah ecosystem, finding that these factors only weakly explain visit frequency and duration.

This paper improves camera trap classification models by incorporating self-attention to leverage information from multiple animal detections, enhancing species classification accuracy in both mono- and multi-species scenarios.

This study uses social network analysis and non-invasive antibody detection to explore pathogen exposure in wildlife communities, identifying key species and areas for epidemiological monitoring.

This study assesses the effectiveness of wolf lethal control in reducing livestock attacks in France using a spatio-temporal analysis framework.

The paper examines spatial relationships between wild boars and other mammals in peri-urban areas, finding no spatial covariation but strong spatial structuring driven by small carnivores.

This study uses vision-language foundation models to classify animal behaviors in camera trap images without prior training, achieving over 91% accuracy in three ungulate species.

This study shows that ignoring invisible landscapes, like individual experience, can bias habitat selection estimates and future population distribution projections.

This study investigates movement patterns of plains zebras in mixed-species groups with giraffes, finding zebras adjust movement decisions based on giraffe presence and exhibit higher group cohesion.

This study evaluates the calibration of deep learning models for camera trap image sequences, showing that temperature scaling improves confidence score interpretability for ecological applications.