| Summary: | Tese de mestrado, Biologia da Conservação, Universidade de Lisboa, Faculdade de Ciências, 2020 Large carnivores are recovering in many regions of Europe, which generates many conflicts with different stakeholders. Bükk National Park in Hungary is a suitable area to study the effects of the natural return of the wolf (Canis lupus) on local wildlife. Wolf and ungulate densities, and the effect of wolf presence on its prey species, are often highlighted by local practitioners. One way to determine whether the wolf’s prey, such as red deer (Cervus elaphus), roe deer (Capreolus capreolus), wild boar (Sus scrofa), and a potential competitor, as the red fox (Vulpes vulpes), are adapted to the presence of the wolf, is to analyse the overlap of activity periods using camera trap data. In order to have reliable population densities, Random Encounter Model (REM) was used to estimate prey and predator population densities from camera trap data without individual recognition. According to the study results, wolf has adapted its activity to the daily cycles of its main prey species, however at certain sensitive seasons of the year (e.g. rutting period or when young is born), wild boars and roe deer might use temporal segregation as a measure to avoid encounters with wolves. Wild boars showed the least overlap (Δ=0.5) at the time of gestation and when piglets are born. Second lowest overlap was between wolf and roe deer at rutting period (Δ=0.64), while interestingly, at its rutting period, red deer showed high overlap with wolves (Δ=0.79). Camera trap-based population density estimations are similar to the National Park’s STR marker-based genetic references from the area (STRn=14 while ????????????????̅=16 individuals; ????????̅̅̅̅= 1.28 individuals), thus REM can be recommended to complement existing wildlife monitoring strategies in order to cross-check data from used methods (like visual observations, STR marker-based genetic analysis) and have a more reliable and cost-effective result in the end. No presente, as populações de grandes ...
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