Biology subjects

Calenge, C.

Publications and source records attributed to Calenge, C..

6 recordsLinked to original sources

bioRxiv2025

Evaluating camera trap methods for monitoring population trends in ungulates: insights from simulation

Camera traps have been widely used in the last decade to monitor abundance of unmarked animal populations. Most estimation methods rely either on the number of times animals pass through the detection zones, like random encounter models (REM) or on the number of capture occasions in a time-lapse program when animals were seen on the pictures, like the instantaneous sampling approach (IS). Yet, the ability of these two popular method classes to both reliably detect population trends and estimate population size has rarely been evaluated. We filled this gap by simulating a setup of either 100 or 25 camera traps randomly distributed on a 2600-ha area (respectively {approx} 4 and 1 trap/km2), along with the movements of a fictional population of 300 roe deer (Capreolus capreolus). Simulations were informed by field data on habitat, habitat selection and activity patterns of GPS-monitored roe deer. Under idealized conditions (e.g., perfect knowledge of day range and visibility), both IS and REM provided unbiased population estimates, though uncertainty remained substantial (CV from 15% to 30% with 4 and 1 trap/km2 respectively). However, our results show that neglecting imperfect detectability leads to severe biases in absolute density estimation. Moreover, despite idealized conditions and large sampling efforts, a simulated 20% population decline over 5 years went undetected by both approaches in 65-75% of simulations at high trap density and 80% at low trap density. Testing other sampling strategies to improve sensitivity either led to an unchanged population size estimation precision (stratified sampling) or to biased estimated trends (sampling only in high-quality habitats). Simulating animals with a 10 times larger home-range, led to miss the decline less frequently (5% - 40% at high trap density, 33% - 67% at low trap density). These results suggest that the key metric for camera trap use is the average number of different traps visited per animal, which in turn depends on trap density, home-range size and space use heterogeneity. We provide a R package allowing the reader to reproduce these simulations, and carry out their own.

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bioRxiv2025

Camera trap monitoring of unmarked animals: a map of the relationships between population size estimators

The use of camera traps to monitor unmarked animal populations has expanded during the last decade, leading to the development of several density estimation methods. This plethora of methods may be confusing for the newcomer to the field. Some methods, such as the random encounter model, require the knowledge of the mean travel speed of the animals, while others, such as camera trap distance sampling, do not rely on such assumptions. Different methods, like instantaneous sampling, camera trap distance sampling, and the association model, rely on similar types of data, but do not seem identical. In this article, I explore the relationships between different density estimators, including the random encounter model, the random encounter and staying time model, the time in front of camera approach, the time-to-event model, camera-trap distance sampling, the association model, and the space-to-event model. I show how these different estimators are related under two simplifying assumptions (perfect detectability, and animals moving as molecules in an ideal gas). I develop a map of mathematical relationships between these estimators. This framework helps readers understand how these methods are interconnected, providing a clearer conceptual foundation for selecting and implementing density estimation studies.

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bioRxiv2024

Relevance of the synergy of surveillance and populational networks in understanding the Usutu virus outbreak within common blackbirds (Turdus merula) in Metropolitan France, 2018

Usutu virus (USUV) was first isolated in Africa in 1959 and has since spread to and through Europe with a typical enzootic mosquito-bird cycle. In France, it was first detected in birds in 2015, but during summer 2018 the spread of USUV was particularly significant throughout the country, killing mainly common blackbirds (Turdus merula) and to a lesser extent great grey owls (Strix nebulosa), among other captive and non-captive wild bird species. Previous studies of USUV in France have focused on reconstructing pathways of introduction, but not on structural aspects of virus spread within the country. Data (RT-PCR of geolocated dead birds) on this 2018 outbreak were collected through both an event-based wildlife network named SAGIR and the health surveillance of the French-speaking Association of Zoo Veterinarians (AFVPZ). In addition, common blackbird populations could be monitored through another network (REZOP). Statistical analysis (spatial, temporal, spatiotemporal and environmental determinants) of the SAGIR and AFVPZ network data helped to highlight the early appearance of separate large clusters of USUV cases in mid-July 2018, the subsequent diffusion into smaller and secondary clusters at the end of August 2018, and a meanwhile enlargement of the first clusters with an increase in the number of cases. High human density (top 10.5% densest areas in France) and wetland concentration (top 19.3% most likely wetland areas) were significant factors in USUV case locations. Using generalised additive mixed models on REZOP data, we also highlighted the decline in common blackbird population trends in areas with medium and even more with high USUV pressure (areas defined based on SAGIR-AFVPZ data) following the 2018 outbreak (respectively -7.4% [-11.4; -3.9]95% and -15.7% [-16.2; -9.1]95%). A large area (radius [~]150 km) in the centre and centre-west of France, and smaller areas in the south-east, north and north-east of France (each with a radius [~] 50 km) were particularly affected. We conclude on the importance to work with synergistic networks to assess infection spread in wild bird species, as well as the negative impact of an emerging arbovirus. The responsiveness of such a network system could be improved by automating alerts.

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bioRxiv2023

Assessing the dynamics of Mycobacterium bovis infection in three French badger populations

The Sylvatub system is a national surveillance program established in 2011 in France to monitor infections caused by Mycobacterium bovis, the main etiologic agent of bovine tuberculosis, in wild species. This participatory program, involving both national and local stakeholders, allowed us to monitor the progression of the infection in three badger populations in clusters covering between 3222 km2 and 7698 km2 from 2013 to 2019. In each cluster, badgers were trapped and tested for M. bovis. Our first aim was to describe the dynamics of the infection in these clusters. We developed a Bayesian model of prevalence accounting for the spatial structure of the cases, the imperfect and variable sensitivity of the diagnostic tests, and the correlation of the infection status of badgers in the same commune caused by local factors (e.g., social structure and proximity to infected farms). This model revealed that the prevalence increased with time in one cluster (Dordogne/Charentes), decreased in the second cluster (Burgundy), and remained stable in the third cluster (Bearn). In all the clusters, the infection was strongly spatially structured, whereas the mean correlation between the infection status of the animals trapped in the same commune was negligible. Our second aim was to develop indicators for monitoring M. bovis infection by stakeholders of the program. We used the model to estimate, in each cluster, (i) the mean prevalence level at mid-period, and (ii) the proportion of the badger population that became infected in one year. We then derived two indicators of these two key quantities from a much simpler regression model, and we showed how these two indicators could be easily used to monitor the infection in the three clusters. We showed with simulations that these two simpler indicators were good approximations of these key quantities.

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bioRxiv2022

Parasitized or non-parasitized, why? A study of factors influencing tick burden in roe deer neonates.

Ixodes ricinus, the most common species of tick in Europe, is known to transmit major pathogens to animals and humans such as Babesia spp. or Borrelia spp.. Its abundance and distribution have been steadily increasing in Europe during recent decades, due to global environmental changes. Indeed, as ticks spend most of their life in the environment, their activity and life cycle are highly dependent on environmental conditions, and therefore on climate or habitat changes. Simultaneously, wild ungulates have expanded their range and increased dramatically in abundance worldwide, in particular roe deer (Capreolus capreolus), have allowed tick populations to grow and spread. Currently, tick infestation on newborn wild ungulates is poorly documented. However, newborn ungulates are considered more sensitive to tick bites and pathogen transmission because of their immature immune system. Thus, improving knowledge about the factors influencing tick infestation on newborns is essential to better understand their health risks. This study was conducted at Trois-Fontaines forest, Champagne-Ardenne, France (1992-2018). Based on a long-term monitoring of roe deer fawns, we used a novel Bayesian model of the infestation of fawns to identify which biotic or abiotic factors are likely to modify the level of infestation by ticks of 965 fawns over time. We show that tick burden increased faster during the first days of life of the fawns and became constant when fawns were 5 days old and more, which could be explained by the depletion of questing ticks or the turnover of ticks feeding on fawns. Moreover, the humidity, which favors tick activity, was weakly positively related to the tick burden. Our results demonstrate that tick infestation was highly variable among years, particularly between 2000 and 2009. We hypothesize that this results from a modification of habitat caused by hurricane Lothar.

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bioRxiv2018

Comparison of ecological, biological and anthropogenic causes of vehicle-wildlife collisions among three large herbivore species

Wildlife-vehicle collisions are of increasing concern with regards to the continuous and accelerating anthropogenic development. Preventing and mitigating collisions with wildlife will require a better understanding of the environmental and biological drivers of collision risks. Because species of large mammals differ in terms of food requirements, habitat selection and movement behaviours we tested at the management unit level if the density of collisions with red deer, roe deer and wild boar differed in terms of spatial distribution and explanatory factors. From 20,275 documented collisions in France between years 1990 and 2006, we found marked differences in the most influential environmental factors accounting for the density of collisions among the three species. The effect of road density was higher for the red deer than for the two other species and did not level off at our spatial-scale of observation. As expected, the annual hunting harvest - interpreted as a proxy of population abundance - was positively associated with the density of collisions for all species, being the strongest for red deer. While the collision density decreased with the proportion of forest in a management unit for wild boar, it increased with the fragmentation of forests for red deer that commute among forest patches between day and night. To reduce the number of wildlife- vehicle collisions, our results suggest to generalise road fencing and/or a control of abundance of large herbivore populations. Mitigation measures should target units where the collision risk is the highest for the most problematic species.

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