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Results of best LLM model used to evaluate the spatial and seasonal variation in day range. The model includes population ID, combining study area and species, as a random effect factor.
Source publication
A better understanding of population density (i.e. the number of individuals per unit area) is essential for wildlife conservation and management. Despite the fact that a wide variety of methods with which to estimate population density have already been described and broadly used, there are still relevant gaps. In the last few decades, the use of...
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Camera trapping is widely used in different ecological studies and is particularly important for remote locations and extreme environments. However, the application of camera traps in Arctic regions remains very limited. One of the challenges is the formation of hoar on the lens of cameras. In this article, we propose a solution to address this pro...
Citations
... Te random encounter model (REM) [30] was applied to estimate the population density of the target species (i.e., wild boar, roe deer, and wolf ). Te REM has been validated as a reliable method to estimate population density when individual identifcation is not possible [24] and has been applied as a reference method to monitor wild boar density [31][32][33][34]. It has also been evidenced the utility of the REM to estimate the population density of the community of mammals inhabiting an area [24,27]. ...
... Te random encounter model is a camera trap-based method that allows the estimation of population density without the need to individually identify animals [30] and spatial autocorrelation in the camera trap placements. Tis provides the fexibility of a given survey design to estimate the density of more than one species [24,27,30,32,33]. Reliable data on the abundance of multiple species after an ASF outbreak will improve decision-making. ...
African swine fever (ASF) is a highly contagious disease affecting all suids and wild boar (Sus scrofa). Since 2007, ASF has spread to more than 30 countries in Europe and Asian regions, and the most recent outbreak has been in mainland Italy (reported on January 2022). When the genotype II of the ASF virus infects a population, a mortality rate close to 90% is usually reported. This drop in wild boar abundance produces a cascade effect in the entire ecosystem. In this context, effective monitoring tools for deriving management parameters are a priority aspect, and the utility of camera trapping could have been overlooked. Here, sampling the infected area in north Italy, we showed the utility of camera traps in the context of ASF infection. Specifically, we used 43 camera traps randomly distributed to (i) estimate movement parameters and population density of wild boar, roe deer (Capreolus capreolus), and wolf (Canis lupus); (ii) quantify wild boar recruitment; and (iii) assess whether the human restriction rules are being met. On the first spring after the outbreak detection, our results for wild boar indicated a density of 0.27 ind·km−2 ± 0.11 (standard error, SE), a daily activity level of 0.49 ± 0.07 (i.e., 11.76 h·day−1), a daily distance travelled of 9.07 ± 1.80 km·day−1, a litter size of 1.72 piglets·group−1, and a 72% of pregnant females. Despite human outdoor activities being restricted in the infected zone, we recorded human presence in 19 camera traps. The wide range of parameters estimated from the camera trap data, together with some intrinsic and practical advantages of this tool, allows us to conclude that camera traps are well positioned to be a reference approach to monitor populations affected by ASF. The population-specific parameters are of prime importance for optimizing ASF control efforts.
