Author

B. T. Hirsch

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

Biology Disciplines

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Animal Behavior & Cognition· 2 Ecology· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Organism:mouse· 2 Research Focus:cell type annotation· 1 Research Focus:ecology & biodiversity· 1 Approach:experimental assay· 1 Assay:imaging· 1 Organism:multiple species· 1

Frequent Co-Authors

M. C. Crofoot· 4 shared A. Strandburg-Peshkin· 2 shared C. H. Fleming· 2 shared E. M. Grout· 2 shared J. Ortega· 2 shared M. J. Noonan· 2 shared P. Minasandra· 2 shared R. Kays· 2 shared

Activity by Year

2021-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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4 shared papersAnimal Behavior & Cognition

M. C. Crofoot

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Author profile →

4 papers

Recent·Most cited

Behavioral sequences across multiple animal species in the wild share common structural features

P. Minasandra, E. M. Grout, K. Brock, M. C. Crofoot, V. Demartsev, A. S. Gersick, B. T. Hirsch, K. E. Holekamp, L. Johnson-Ulrich, A. Nayak, J. Ortega, M. A. Roch, E. D. Strauss, A. Strandburg-Peshkin

The paper analyzes behavioral sequences in three wild mammal species and finds consistent structural patterns across all species, individuals, and behavioral states.

bioRxiv · Jan 20, 2024Animal Behavior & Cognition

Whole group tracking reveals that relatedness drives consistent subgrouping patterns in white-nosed coatis

E. M. Grout, J. Ortega, P. Minasandra, M. J. Quin, M. C. Crofoot, A. Strandburg-Peshkin, B. T. Hirsch

The study tracks GPS movements of white-nosed coatis to show that genetic relatedness, not physiological similarity, drives consistent subgrouping patterns in social groups.

bioRxiv · Dec 14, 2023Animal Behavior & Cognition

Population-level inference for home-range areas

C. H. Fleming, I. Deznabi, S. Alavi, M. C. Crofoot, B. T. Hirsch, E. P. Medici, M. J. Noonan, R. Kays, W. F. Fagan, D. Sheldon, J. M. Calabrese

This paper introduces a framework for population-level home-range analysis that accounts for temporal autocorrelation and uncertainty, applied to multiple species to quantify differences in movement patterns.

bioRxiv · Jul 5, 2021Ecology

Estimating encounter location distributions from animal tracking data

M. J. Noonan, R. Martinez-Garcia, G. H. Davis, M. C. Crofoot, R. Kays, B. T. Hirsch, E. Payne, A. Sih, D. L. Sinn, O. Spiegel, W. F. Fagan, C. H. Fleming, J. Calabrese

This paper introduces a new theoretical framework to estimate encounter location probabilities from animal tracking data and demonstrates its application using GPS data from capuchins and lizards.

Methods in Ecology and Evolution · May 14, 2021Peer-reviewedEcology