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Gewählte Master / Diploma Thesis:

Master / Diploma Thesis - Institut für Wildbiologie und Jagdwirtschaft (IWJ), BOKU-Universität für Bodenkultur, pp 58. UB BOKU obvsg FullText

Data Source: ZID Abstracts
A variety of different stakeholders is interested in using mountainous areas in the Alps, causing potentially negative effects on natural habitats and wildlife. Habitat models are common tools to predict the impact of human activities on wild animals and answer further questions in the context of wildlife and habitat. Logistic Regression (LR) has proven to be a useful method for habitat modelling. Being part of a monitoring project of black grouse (Tetrao tetrix) in Vorarlberg the small-scale habitat use was examined to allow for conclusions on habitat quality and resulting management demands. As a first step main habitat parameters such as vegetation cover, occurrence of single trees, the intensity of pasturing etc. were recorded in the field during July – September 2014 in three distinct areas of interest (“Portla”, “Feuerstätter”, “Zeinis”). Furthermore, presence-absence data of black grouse, represented by indirect signs of presence (droppings, feathers) was collected in each study area. Study plots were located on a 100 x 100m grid and had a radius of 25m. Within a total of 290 study plots indirect signs were found in 119 cases (i.e. 41%). Based on this data a habitat model for each study area as well as one overall model was derived. The final overall model contained the following explanatory variables indicating their high for black grouse: • patchiness • ant hills • single trees • hiking paths • intensity of pasturing • height of grass This final LR model correctly classified 83% of the study plots regarding black grouse presence or absence. The influence of the six explanatory variables corresponded to results of other studies in the Alps. The habitat models should lead to a better understanding of occurrence and absence patterns of Black grouse and provide a basis for future habitat improvement measures.

Beurteilende(r): Gossow Hartmut
1.Mitwirkender: Nopp-Mayr Ursula

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