Marie‐Pierre Étienne

Monte Carlo simulations to propagate the uncertainty of machine-learning classification into ecological models

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.

When does temporal resolution matter? Including detection covariates in discrete- versus continuous-time occupancy and N-mixture models

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.

Unveiling the Hidden Feast: translating molecular detection into predation rate. An example on biological control by generalist predators in agricultural fields.

The paper develops a Hierarchical Bayesian Model to estimate predation rates using molecular detection data and field/laboratory observations, applied to carabid beetles in agricultural fields.

Using informative priors to account for identifiability issues in occupancy models with identification errors

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