Fitzgerald Maegan, Coulson Robert, Lawing A Michelle, Matsuzawa Tetsuro, Koops Kathelijne
Department of Ecosystem Science and Management, Texas A&M University, College Station, TX, 77843, USA.
Knowledge Engineering Laboratory, Department of Entomology, Texas A&M University, College Station, TX, USA.
Primates. 2018 Jul;59(4):361-375. doi: 10.1007/s10329-018-0657-8. Epub 2018 Mar 9.
Tropical forests and the biodiversity within them are rapidly declining in the face of increasing human populations. Resource management and conservation of endangered species requires an understanding of how species perceive and respond to their environments. Species distribution modeling (SDM) is an appropriate tool for identifying conservation areas of concern and importance. In this study, SDM was used to identify areas of suitable chimpanzee (Pan troglodytes verus) habitat within the Greater Nimba Landscape, Guinea, West Africa. This location was ideal for investigating the effects of landscape structure on habitat suitability due to the topographic variation of the landscape and the Critically Endangered status of the Western chimpanzee. Additionally, this is the only mountainous, long-term chimpanzee study site and little is known about the effects of topography on chimpanzee behavior. Suitable habitat was predicted based on the location of direct and indirect signs of chimpanzee presence and the spatial distribution of 12 biophysical variables within the study area. Model performance was assessed by examining the area under the curve. The overall predictive performance of the model was 0.721. The variables most influencing habitat suitability were the normalized difference vegetation index (37.8%), elevation (27.3%), hierarchical slope position (11.5%), surface brightness (6.6%), and distance to rivers (5.4%). The final model highlighted the isolation and fragmentation of chimpanzee habitat within the Greater Nimba Landscape. Understanding the factors influencing chimpanzee habitat suitability, specifically the biophysical variables considered in this study, will greatly contribute to conservation efforts by providing quantitative habitat information and improving survey efficiency.
面对不断增长的人口,热带森林及其内部的生物多样性正在迅速减少。濒危物种的资源管理和保护需要了解物种如何感知和响应其环境。物种分布建模(SDM)是识别重要保护区域的合适工具。在本研究中,利用物种分布建模来确定西非几内亚大宁巴山地区内适合黑猩猩(Pan troglodytes verus)栖息的区域。由于该地区的地形变化以及西部黑猩猩的极度濒危状态,此地是研究景观结构对栖息地适宜性影响的理想地点。此外,这是唯一的山地长期黑猩猩研究地点,人们对地形对黑猩猩行为的影响知之甚少。基于黑猩猩存在的直接和间接迹象的位置以及研究区域内12个生物物理变量的空间分布,预测了适宜栖息地。通过检查曲线下面积评估模型性能。该模型的总体预测性能为0.721。对栖息地适宜性影响最大的变量是归一化植被指数(37.8%)、海拔(27.3%)、分层坡度位置(11.5%)、地表亮度(6.6%)和距河流距离(5.4%)。最终模型突出了大宁巴山地区内黑猩猩栖息地的隔离和破碎化。了解影响黑猩猩栖息地适宜性的因素,特别是本研究中考虑的生物物理变量,将通过提供定量的栖息地信息和提高调查效率,极大地有助于保护工作。