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Chenesseau, D.

Publications and source records attributed to Chenesseau, D..

3 recordsLinked to original sources

What if wildlife health surveillance was not just for veterinarians? - Opportunistic use of population monitoring by camera traps for syndromic surveillance of the Eurasian lynx (Lynx lynx)

Fifty years after the reintroduction of the Eurasian lynx Lynx lynx to the Vosges and Swiss Jura mountains, the species remains in danger of extinction in France. The main threats it faces are habitat fragmentation, high anthropogenic mortality (mainly vehicle collision but also illegal killing) and low genetic diversity, but little is known about the importance of disease. Camera trapping surveillance provides crucial information for understanding population health status but includes many biases. To be more efficient, surveillance must combine several modalities. This work first presents the development of a protocol for clinical data collection by camera trapping, intended for biologists in charge of the populations monitoring. This method was then applied to the 3574 events, i.e. 270 identified individuals, present between 1997 and 2020 in the lynx photo identification database of the Wolf-Lynx Network (Reseau Loup-Lynx) of the French Biodiversity Agency (Office Francais de la Biodiversite). Seventeen percent of the lynx studied showed at least one change indicative of disease. The most common changes were skin disorders. The others were body condition, ocular or locomotor changes, lack of auriculas and rarely respiratory, behavioral, or digestive troubles. The latter changes were concentrated at the end of the study period, which also corresponded to the period with the most camera traps and therefore the most data. Finally, these observations complemented postmortem surveillance of the French lynx population carried out by the French network of epidemiological surveillance (Reseau SAGIR).

ecology↗

Annotating opportunistic camera-trap images with conditions ofrecording, for the disease surveillance of Eurasian lynx (Lynxlynx)

The French population of the Eurasian lynx (Lynx lynx) is small and fragmented. Any emerging disease would endanger it even further, so health surveillance is crucial. Currently, health monitoring relies on lynx carcass surveillance. In parallel, the Eurasian lynx population is being monitored since 1997 through a large network of observers in different regions and this trove of camera-trap images could allow for the opportunistic detection of clinical signs. Camera traps have been used for a very long time in ecology and, more recently, in epidemiology to study e.g. sarcoptic mange. However, the quality of the images from camera traps varies, the details of the animals body are more or less clearly visible. This work examines how the quality of the images relates to the ability to detect cutaneous changes and abnormal body conditions. Different factors affect image quality and the detection of changes: intrinsic camera parameters like the type and settings of the camera trap, extrinsic factors like the external lighting conditions or the position of the animal in relation to the camera. In our data set, clearly visible cutaneous changes were associated with a different set of factors than visible abnormal body conditions. The camera-trap conditions currently used for ecological monitoring of the lynx are sufficiently diverse to allow for the general surveillance of abnormal health signs. However, for monitoring specific health signs, the camera settings as well as the shooting context should be optimized to ensure the best possible sensitivity and specificity of the detection.

ecology↗

Bringing circuit theory into spatial occupancy models to assess landscape connectivity

Connectivity shapes species distribution across fragmented landscapes. Assessing landscape resistance to dispersal is challenging because dispersal events are rare and difficult to detect especially for elusive species. To address these issues, spatial occupancy models have been developed to integrate the resistance surface concept of landscape ecology and model patch occupancy dynamics through colonization and extinction while accounting for imperfect species detection. However, the most recent approach is based on least-cost path distances which assume that individuals disperse along the optimal route. Here, we develop a new spatial occupancy model that incorporates commute distances derived from circuit theory to model dispersal across sites. Our approach allows for explicit estimation of landscape connectivity and direct measure of uncertainty from detection/non-detection data. To illustrate our approach, we study the recolonisation of two carnivores in France, and quantify the degree to which rivers facilitate Eurasian otter (Lutra lutra) dispersal and highways impede Eurasian lynx (Lynx lynx) recolonisation. Overall, spatial occupancy models provide a flexible framework to acccommodate any distance metric designed to align with species dispersal ecology. Open Research StatementData and code used in this research are available on Zenodo at https://zenodo.org/record/8376577

ecology↗