In many regions worldwide, effective wildlife management in human-dominated landscapes is important due to increasing numbers of wild ungulates. This is especially true in mountain ranges like the European Alps, where damages to forests caused by wild ungulates not only lead to economic losses but also threaten the integrity and functionality of other forest functions, like the protection against landslides and avalanches. To diminish damages like browsing or bark stripping and thus mitigate human-wildlife conflicts while ensuring viable ungulate populations, sustainable management is required. Concerning this matter, hunting can play an important role by altering the spatial distribution of ungulate species in the landscape and reducing their numbers through harvesting to reach a population size with favourable sex and age structure. Current hunting practices often fail in this context, however, as many ungulates like red deer (Cervus elaphus), roe deer (Capreolus capreolus), or white-tailed deer (Odocoileus virginianus) respond to the presence of humans through an avoidance behaviour to reduce the probability of being harvested. To counteract this phenomenon, tools to inform sustainable management of these species are urgently needed.
In Griesberger et al. we provide for the first time a hunting suitability model for wild ungulate management in mountainous landscapes to visualise hunting suitability objectively and realistically. Using red deer as a model species, we modelled hunting suitability with high spatial resolution (10 x 10 m), based on remote sensing information, field surveys, and expert knowledge of professional hunters. Further, we analysed spatio-temporal habitat selection by radio-collared deer in relation to locations of varying hunting suitability. We found that red deer avoided areas suitable for hunting during daylight hours in the hunting season, but not during the night. We concluded that this species seems to perceive a landscape of heterogeneous anthropogenic predation risk, shaped by locations of various hunting suitability, as we modelled it.
In short and concerning wild ungulate management, our model provides high-resolution predictions of where species like red deer will retreat when perceived anthropogenic predation risk increases. The model also yields useful insights regarding the hunting suitability of particular locations, which is valuable information especially for non-locals. Furthermore, our model can serve as planning tool to inform decisions about where particular hunting strategies can be performed most efficiently to manage wild ungulates and therefore minimize human-wildlife conflicts. Photo credit: Paul Griesberger.
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