Stock and habitat use of alpine owls in the Gesäuse National Park

Karl Franzens University of Graz, Institute of Zoology Graz Using the self-collected data and data provided by BirdLife, the free software Maxent (MAXimum Entropy software for species habitat modeling, version 3.3.1) was used to model and attempt to predict the occurrence of the three species throughout the national park. These data sets served as the basis for the modeling mentioned above. Habitat models are very well suited as a complement to mapping work, on the one hand, since they narrow down the potential habitats of the respective target species, on the other hand, as they represent an optimal way of assessing areas that are difficult to map, for example due to their inaccessibility. The results of the maxent modelling were largely in line with the data from the literature and the results of the inspections: The dependence of chewing species on certain altitudes, tree species compositions and age groups of forests was confirmed. Nevertheless, it must always be borne in mind that a model is only one model and many other essential habitat factors, such as the presence of prey animals or the presence of breeding caves, etc., could not be included in the modelling process. The data, results and reflections of the present work should ideally serve as a basis or support for further monitoring, as meaningful results can only be obtained through long-term observation.格拉茨卡尔·弗朗岑斯大学（Karl Franzens University of Graz）格拉茨动物学研究所 研究团队依托自主采集的数据以及国际鸟盟（BirdLife）提供的数据集，采用开源软件Maxent（物种栖息地建模最大熵软件，MAXimum Entropy software for species habitat modeling，版本3.3.1），对该国立公园内三个物种的出现情况开展建模与预测工作，上述数据集为本次建模提供了核心依据。栖息地模型具备极高的制图补充价值：一方面，可有效缩小目标物种的潜在栖息范围；另一方面，能够为难以实地测绘的区域（如因地形难以抵达的区域）提供最优的评估方案。 Maxent建模结果整体与文献数据及实地调查结果高度吻合：研究证实了咀嚼取食类物种对特定海拔、林木组成及林分年龄结构的依赖性。但需始终明确，模型仅为单一的模拟结果，诸多其他关键栖息地因子——例如猎物存在、繁殖洞穴存在等——均未被纳入建模流程。本研究的数据集、建模结果与反思总结，理应作为后续监测工作的基础与支撑；唯有通过长期持续观测，方可获得具备实际意义的研究成果。