The Eurasian jackal (Canis aureus) is one of the species that experienced rapid expansion in Europe in modern times. It has been a regular annual visitor in Slovenia since the 1980s, with the first territorial packs formed in 2009. Since then, the population has increased to 750 – 1000 in 2019 and has spread throughout Slovenia. To learn more about the species ecology, we created a dynamic hierarchical occupancy model that quantified relationships with environmental variables we knew from the literature. The model was fed with data collected by hunters as part of the National Jackal Monitoring Programme between 2016 and 2019. We used the Unmarked package in Programme R. We selected the best model by comparing environmental variables in the candidate set of models using Akaike’s Information Criterion (AICc). We selected the best model where detection probability (d) depended on the number of days with snow cover between September and March, initial occupancy (psi1) depended on the distance to the nearest settlement and the average index of forest fragmentation, colonisation probability (gamma) depended on the average index of forest fragmentation and annual days with snow cover, and extinction probability (epsilon) depended on the average elevation and distance to the nearest settlement. The results of the highest scoring models showed a positive correlation of occurrence with shorter duration of snow cover. We extrapolated the values of the parameters to a 3 x 3 km grid covering Slovenia. We also made a prediction of the change of the parameter values for the year 2050, according to the climate change scenarios RCP 4.5 and 8.5. We couldn’t prove any significant expansion of areal under the climate change scenarios. From the model results, we conclude that potential habitat exclusion by wolves exists.
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