Olivier Giménez

This study compares eDNA sampling and camera trapping for detecting coypu populations, finding eDNA more effective for presence confirmation while camera traps provide complementary behavioral insights.

This paper provides a practical guide to using stochastic dynamic programming for invasive species management, with examples and R implementations.

The paper compares the efficiency of eDNA, camera traps, and scat surveys for detecting Eurasian otters across four catchments in southern France, finding scat surveys most effective and highlighting method complementarity.

This paper introduces a method to incorporate classification uncertainty from machine learning into ecological models using Monte Carlo simulations, showing it leads to more reliable ecological estimates.

This study assesses the effectiveness of wolf lethal control in reducing livestock attacks in France using a spatio-temporal analysis framework.

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.

The paper compares discrete- and continuous-time models for detecting covariates in occupancy and N-mixture models, showing that temporal resolution affects detection estimates but not abundance or occupancy.

The paper develops a Bayesian occupancy model that incorporates informative priors to address identifiability issues caused by identification errors in passive bio-monitoring data.

This study evaluates the reliability of inferring species co-occurrence from occupancy models under different conditions and recommends a minimum of 150 sampling sites for accurate results.

The paper develops a spatial occupancy model using circuit theory to assess landscape connectivity by incorporating commute distances, applied to study carnivore recolonization in France.

The paper examines how elephant carcass abundance affects hyaena and prey population dynamics in Hwange National Park using long-term data and statistical models.

This study compares discrete- and continuous-time occupancy models for analyzing continuously collected biodiversity data, finding that simpler models often suffice for occupancy estimation.