Drivers of spatio-temporal population dynamics of game species in a mountain landscape

Since the end of the nineteenth century, socio-economic changes have greatly altered the Central European landscape and the structural and functional quality of habitats. Urban sprawl areas have appeared, a reduction of multiple forest uses has resulted in the densification of forests and agricultural land use has changed fundamentally through specialisation and intensification. Many of these changes affect biodiversity. To determine the important drivers of spatio-temporal dynamics of the population of 28 game species, we first considered a total of 130 potential explanatory variables. Second, we aggregated the main drivers of single-species models for habitat guilds. Third, we evaluated the results to aid in the development and implementation of mitigation measures for different ecoregions. We used harvest data as a surrogate for population density from 1875 to 2014 in South Tyrol, Italy. In generalised linear models, we used environmental characteristics such as climate, landscape diversity and structures, land cover, hunting, wildlife diseases, competition and predation, land-use type, and intensity (including pesticide use) as explanatory variables to predict the spatio-temporal dynamics of game species. The important drivers are land use and management changes (intensification in the agriculturally favourable areas, extensification or abandonment in the unfavourable areas) as well as associated changes in the landscape features, diversity and structure, and hunting management. Climatic variables, interspecific competition and diseases only play a subordinate role. The dynamics of the habitat guilds and their drivers provide concrete indications for measures to maintain or improve the habitat quality for the investigated species. Particularly important are transfer payments to ensure extensive agricultural use, increasingly through the takeover of personnel costs, but also for the installation of an independent body that monitors and evaluates the effectiveness of the measures.