Author

S. Benhamou

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Ecology· 4

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 4 Research Focus:ecology & biodiversity· 3 Assay:behavioral assay· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Assay:imaging· 1 Organism:non-human primate· 1

Frequent Co-Authors

D. A. Ahmed· 1 shared E. Lebarbier· 1 shared J. C. Manning· 1 shared M. B. Bonsall· 1 shared M.-P. Etienne· 1 shared N. Courbin· 1 shared R. Patin· 1 shared S. Chamaille-Jammes· 1 shared

Activity by Year

2018-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 10 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperEcology

D. A. Ahmed

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Spatial interactions between parrotfishes and implications for species coexistence

J. C. Manning, S. J. McCoy, S. Benhamou

The paper examines spatial interactions among parrotfish species to understand how home range behavior and spatial overlap influence coexistence on coral reefs.

bioRxiv · Oct 21, 2022 · PreprintEcology

Accounting for central place foraging constraints in habitat selection studies

S. Benhamou, N. Courbin

The paper addresses bias in habitat selection studies for central place foragers by proposing methods to correct for mechanical effects of foraging behavior.

bioRxiv · Oct 21, 2022Ecology

Three-dimensional random walk models of individual animal movement and their application to trap counts modelling

D. A. Ahmed, S. Benhamou, M. B. Bonsall, S. V. Petrovskii

This study develops 3D random walk models to analyze trap counts for flying insects, finding that trap shape and diffusion affect capture efficiency.

bioRxiv · Jul 28, 2020Ecology

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

R. Patin, M.-P. Etienne, E. Lebarbier, S. Chamaille-Jammes, S. Benhamou

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.

bioRxiv · Oct 17, 2018Ecology