台灣黑熊棲息地利用及分布預測模式

Habitat Use and Distribution Model of Formosan Black Bears (Ursus thibetanus formosanus)

棲息地的喪失及破碎化為現今保育和經營管理大型食肉目動物最主要的議題，有效經營管理野生動物遂繫於瞭解動物對棲息地的需求和預測其分布。台灣黑熊（Wtuwu'vjkdgvcpwu'hqtoqucpwu）為亞洲黑熊（W0' vjkdgvcpwu）於台灣之特有亞種，是瀕臨絕種的保育類動物。分析本島除高雄市及台北市以外海拔100m 以上的研究樣區，黑熊出現地區紀錄所屬的環境因素，包括海拔、坡度、植生指標、自然度指標、道路密度、離溪流最近距離、離道路最近距離，皆與研究樣區的環境屬性呈現顯著差異（Mann-Whitney U test, r<0.001），顯示這些環境因素影響黑熊的棲息所在（chi-square test, r<0.001），而此現象不僅反映出動物的選擇性，也與人為有關的死亡率風險有關。台灣黑熊分布預測模式（基因演算法）預測結果顯示，黑熊主要分布於中央山脈，在海岸山脈亦有零星分布。與1990 年的紀錄相較，台灣黑熊的地理分布有縮減的趨勢，其棲息地的選擇除了受到食物資源豐富度以及相關物候環境影響之外，人為干擾更是關鍵因素。建議未來的預測模式，除了應該加強有熊及無熊資料的精準度之外，同時應該整合人類活動類型及位置，尤其是非法狩獵壓力、食物豐富度（包括植物及動物），以及不同類型道路系統等變因，以達更精確的分布預測。 Habitat loss and fragmentation are primary issues in the conservation and management of large carnivores. Successful wildlife management requires an understanding of animal habitat requirements and accurate prediction of its distribution. The Formosan black bear (Ursus thibetanus formosanus), an endemic subspecies of Asiatic black bear (U. thibetanus) inhabiting Taiwan, is listed as a locally endangered species. Grid cells where Formosan black bears were detected differed significantly from the availability of habitats across the entire study area (＞100 m in elevation, excluding Taipei and Kaohsiung cities) in all seven environment variables measured, including elevation, slope, NDVI (normalized difference vegetation index), naturalness, road density, and shortest distance to river and road (Mann-Whitney U test, p＜0.001). The results indicated that these variables affected where bears tended to live (a reflection of their choices as well as spatial differences in human-related mortality risks; chi-square test, p＜0.001). The genetic algorithm for rule-set prediction model predicted that bears occurred mainly along the Central Mountain Ranges, whereas few lived in the isolated Eastern Coastal Mountain Range. The geographic distribution of Formosan black bears appears to have declined, as compared to the distribution data recorded in 1990. Their habitat use was not only limited by food abundance and natural physical factors but also by human disturbance. The predictability of our model would be enhanced by improving the accuracy of bear presence-absence data and by incorporating more explanatory variables, such as types and locations of human activities (especially illegal hunting), food abundance, and various road networks.