C. Milleret

Unravelling the effects of heterogeneity in space use on estimates of connectivity and population size: Insights from spatial capture-recapture modelling

This study evaluates how different approaches to handling space use heterogeneity affect connectivity and population size estimates in spatial capture-recapture models using Pyrenean brown bear data.

Wolverine density distribution reflects past persecution and current management in Scandinavia

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

Spatial variation in red deer density in relation to forest disturbance and ungulate management in a transboundary forest ecosystem

The paper estimates red deer density in a transboundary forest ecosystem and finds that forest disturbances and management practices influence spatial density patterns.

Integrating opportunistic and structured non-invasive surveys with spatial capture-recapture models to map connectivity of the Pyrenean brown bear population

The paper maps connectivity of the Pyrenean brown bear population using spatial capture-recapture models integrating structured and opportunistic data to identify movement barriers.

Modelling spatially autocorrelated detection probabilities in spatial capture-recapture using random effects

This paper introduces and evaluates three Bayesian spatial capture-recapture models to account for spatial heterogeneity in detection probabilities, finding that spatially autocorrelated random effects provide the least biased population size estimates.

Estimating spatially variable and density-dependent survival using open-population spatial capture-recapture models

This paper develops a Bayesian open-population spatial capture-recapture model to estimate spatially variable and density-dependent survival, showing its effectiveness through simulations and providing an R package for implementation.

Does the punishment fit the crime? Consequences and diagnosis of misspecified detection functions in Bayesian spatial capture-recapture modelling

This study evaluates the consequences of misspecified detection functions in Bayesian spatial capture-recapture models and identifies diagnostic tools to detect such misspecifications.

Consequences of ignoring variable and spatially-autocorrelated detection probability in spatial capture-recapture

This study shows that unmodeled spatially autocorrelated detection probability in SCR models can cause severe bias and reduced precision in abundance estimates.

A hierarchical point process model for spatial capture-recapture data

This paper introduces a hierarchical point process model for spatial capture-recapture data using non-invasive genetic sampling, estimating wolverine density without data augmentation.

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

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

Efficient Estimation of Large-Scale Spatial Capture-Recapture Models

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

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

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.