S. Chamaille-Jammes

Do mixed-species groups travel as one? An investigation on large African herbivores using animal-borne video collars

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.

Zero-shot animal behavior classification with vision-language foundation models

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.

Can overlooking "invisible landscapes" bias habitat selection estimation and population distribution projections?

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

Being confident in confidence scores : calibration in deep learning models for camera trap image sequences

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.

A reformulation of the selection ratio shed light on resource selection functions and leads to a unified framework for habitat selection studies.

The paper reformulates the selection ratio (SR) to provide a unified framework for habitat selection studies, clarifying debates around resource selection functions (RSF) and introducing the selection effect on use (SE) as a complementary metric.

MoveFormer: a Transformer-based model for step-selection animal movement modelling

MoveFormer is a Transformer-based model that predicts animal movement steps using past trajectories and environmental covariates, showing the importance of context and history.

Hogs sleep like logs: wild boars reduce the risk of anthropic disturbance by adjusting where they rest

This study finds wild boars adjust resting site selection to minimize disturbance risk by prioritizing vegetation cover over proximity to human structures.

Time-varying habitat selection analysis: a model and applications for studying diel, seasonal and post-release changes

This paper introduces dynamic logistic models to analyze time-varying habitat selection without time discretization, demonstrating their effectiveness with simulations and real-world applications on blue wildebeest.

Good moms: dependent-young and their mothers cope better than others with longer dry season in plains zebras

The paper examines how plains zebra survival and reproduction are affected by seasonal changes, finding that reproductive females and their dependent young cope better with longer dry seasons.

How to describe and measure phenology? An investigation on the diversity of metrics using phenology of births in large herbivores

This paper evaluates 52 phenology metrics for birth timing in large herbivores, finding that simpler metrics are often better and that circular statistics and distribution tests are most effective.

Can citizen science analysis of camera trap data be used to study reproduction? Lessons from Snapshot Serengeti program

This study evaluates if citizen science volunteers can reliably detect juvenile animals in camera trap data to study reproduction, finding moderate accuracy for some species.

Revisiting giraffe photo-identification using deep learning and network analysis

The paper develops a deep learning pipeline for giraffe re-identification using image similarity networks and CNNs, achieving 90% Top-1 accuracy in identifying known individuals from 4,000 photographs.

A theory of the use of information by enemies in the predator-prey space race

This paper develops a simulation model with a genetic algorithm to study how predators and prey use information in different environments, finding that movement unpredictability is key for both, but differs in magnitude and environmental dependence.

Identifying stationary phases in multivariate time-series for highlighting behavioural modes and home range settlements

This paper introduces a segmentation-clustering method to identify stationary phases in multivariate time-series, applied to animal movement data to detect behavioural modes and home range shifts.