Section: Ecology
Topic:
Ecology,
Statistics
Using informative priors to account for identifiability issues in occupancy models with identification errors
Corresponding author(s): Monchy, Célian (celian.monchy@cefe.cnrs.fr)
10.24072/pcjournal.511 - Peer Community Journal, Volume 5 (2025), article no. e8.
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Non-invasive monitoring techniques like camera traps, autonomous recording units and environmental DNA are increasingly used to collect data for understanding species distribution. These methods have prompted the development of statistical models to suit specific sampling designs and get reliable ecological inferences. Site occupancy models estimate species occurrence patterns, accounting for the possibility that the target species may be present but unobserved. Here, two key processes are crucial: detection, when a species leaves signs of its presence, and identification where these signs are accurately recognized. While both processes are prone to error in general, wrong identifications are often considered as negligible with in situ observations. When applied to passive bio-monitoring data, characterized by datasets requiring automated processing, this second source of error can no longer be ignored as misclassifications at both steps can lead to significant biases in ecological estimates. Several model extensions have been proposed to address these potential errors. We propose an extended occupancy model that accounts for the identification process in addition to detection. Similar to other recent attempts to account for false positives, our model may suffer from identifiability issues, which usually require another source of data with perfect identification to resolve them. As an alternative when such data are unavailable, we propose leveraging existing knowledge of the identification process within a Bayesian framework by incorporating this knowledge through an informative prior. Through simulations, we compare different prior choices that encode varying levels of information, ranging from cases where no prior knowledge is available, to instances with accurate metrics on the performance of the identification, and scenarios based on generally accepted assumptions. We demonstrate that, compared to using a default prior, integrating information about the identification process as a prior reduces bias in parameter estimates. Overall, our approach mitigates identifiability issues, reduces estimation bias, and minimizes data requirements. In conclusion, we provide a statistical method applicable to various monitoring designs, such as camera trap, bioacoustics, or eDNA surveys, alongside non-invasive sampling technologies, to produce ecological outcomes that inform conservation decisions.
Type: Research article
Monchy, Célian 1; Etienne, Marie-Pierre 2; Gimenez, Olivier 1
CC-BY 4.0
@article{10_24072_pcjournal_511,
author = {Monchy, C\'elian and Etienne, Marie-Pierre and Gimenez, Olivier},
title = {Using informative priors to account for identifiability issues in occupancy models with identification errors},
journal = {Peer Community Journal},
eid = {e8},
publisher = {Peer Community In},
volume = {5},
year = {2025},
doi = {10.24072/pcjournal.511},
language = {en},
url = {https://peercommunityjournal.org/articles/10.24072/pcjournal.511/}
}
TY - JOUR AU - Monchy, Célian AU - Etienne, Marie-Pierre AU - Gimenez, Olivier TI - Using informative priors to account for identifiability issues in occupancy models with identification errors JO - Peer Community Journal PY - 2025 VL - 5 PB - Peer Community In UR - https://peercommunityjournal.org/articles/10.24072/pcjournal.511/ DO - 10.24072/pcjournal.511 LA - en ID - 10_24072_pcjournal_511 ER -
%0 Journal Article %A Monchy, Célian %A Etienne, Marie-Pierre %A Gimenez, Olivier %T Using informative priors to account for identifiability issues in occupancy models with identification errors %J Peer Community Journal %D 2025 %V 5 %I Peer Community In %U https://peercommunityjournal.org/articles/10.24072/pcjournal.511/ %R 10.24072/pcjournal.511 %G en %F 10_24072_pcjournal_511
Monchy, Célian; Etienne, Marie-Pierre; Gimenez, Olivier. Using informative priors to account for identifiability issues in occupancy models with identification errors. Peer Community Journal, Volume 5 (2025), article no. e8. doi : 10.24072/pcjournal.511. https://peercommunityjournal.org/articles/10.24072/pcjournal.511/
PCI peer reviews and recommendation, and links to data, scripts, code and supplementary information: 10.24072/pci.ecology.100699
Conflict of interest of the recommender and peer reviewers:
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.
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