Author

H. Broseth

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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Ecology· 5

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Approach:statistical model· 5 Research Focus:ecology & biodiversity· 3 Research Focus:benchmarking· 1

Frequent Co-Authors

C. Milleret· 4 shared P. Dupont· 3 shared R. Bischof· 3 shared D. Turek· 2 shared P. de Valpine· 2 shared A. Corradini· 1 shared A. Dutsov· 1 shared A. Ertürk· 1 shared

Activity by Year

2019-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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4 shared papersEcology

C. Milleret

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5 papers

Recent·Most cited

Including biotic interactions in species distribution models improves the understanding of species niche: a case of study with the brown bear in Europe

P. M. Lucas, W. Thuiller, M. V. Talluto, E. Polaina, J. Albrecht, N. Selva, M. De Barba, L. Maiorano, V. Penteriani, M. Guegen, N. Balkenhol, T. Dutta, A. Fedororca, S. C. Frank, A. Zedrosser, , Ion

This study shows that including biotic interactions in species distribution models improves predictions of future range shifts for brown bears in Europe under climate and land use change scenarios.

bioRxiv · Mar 10, 2023 · PreprintEcology

Wolverine density distribution reflects past persecution and current management in Scandinavia

E. Moqanaki, C. Milleret, P. Dupont, H. Broseth, R. Bischof

This study identifies landscape-level factors influencing current wolverine density in Scandinavia, showing that historical persecution and modern management practices both shape their distribution.

bioRxiv · Nov 14, 2022Ecology

Instrumented individuals are not representative of the population. Survival of wolverines with and without GPS collars

C. Milleret, R. Bischof, P. Dupont, H. Broseth, J. Odden, J. Mattisson

The paper compares survival rates of GPS-collared and non-collared wolverines, finding collared individuals had lower mortality from non-culling causes.

bioRxiv · Sep 22, 2020 · PreprintEcology

Efficient Estimation of Large-Scale Spatial Capture-Recapture Models

D. Turek, C. Milleret, T. Ergon, H. Broseth, P. de Valpine

The paper improves MCMC estimation for large-scale spatial capture-recapture models by optimizing computational methods, achieving significant speedups and efficiency gains.

bioRxiv · May 7, 2020Ecology

Estimating abundance with interruptions in data collection using open population spatial capture-recapture models

C. Milleret, P. Dupont, J. Chipperfield, D. Turek, H. Broseth, O. Gimenez, P. de Valpine, R. Bischof

This study evaluates the reliability of open population spatial capture-recapture models in estimating abundance despite sampling interruptions, finding that interruptions increase uncertainty but not systematic bias.

bioRxiv · Jun 14, 2019Ecology