Assessing habitat quality of the mountain nyala Tragelaphus buxtoni in the Bale Mountains, Ethiopia

作     者：Paul H. EVANGELISTA John NORMAN III Paul SWARTZINKI3,Paul SWARTZINKI3,Paul SWARTZINKI Nicholas E. YOUNG 

作者机构：Natural Resource Ecology Laboratory Colorado State University Fort Collins CO 80524-1499 USA Natural Resource Conservation Service Shepardson Bldg. Colorado State University Fort Collins CO 80524 USA AECOM 1601 Prospect Pkwy Fort Collins CO 80303 USA 

出 版 物：《Current Zoology》 (动物学报（英文版）)

年 卷 期：2012年第58卷第4期

页      面：525-535页

核心收录：

学科分类：0907[农学-林学] 090705[农学-野生动植物保护与利用] 08[工学] 09[农学] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0834[工学-风景园林学（可授工学、农学学位）] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Expert knowledge FunConn model Habitat mapping Land cover Mountain nyala Wildlife conservation 

摘      要：Populations of the endangered mountain nyala Tragelaphus buxtoni are significantly threatened by the loss of critical habitat. Population estimates are tentative, and information on the species＇ distribution and available habitat is required for for-mulating immediate management and conservation strategies. To support management decisions and conservation priorities, we integrated information from a number of small-scale observational studies, interviews and reports from multiple sources to define habitat parameters and create a habitat quality model for mountain nyala in the Bale Mountains. For our analysis, we used the FunConn model, an expertise-based model that considers spatial relationships （i.e., patch size, distance） between the species and vegetation type, topography and disturbance to create a habitat quality surface. The habitat quality model showed that approxi- mately 18,610 km^2 （82.7% of our study area） is unsuitable or poor habitat for the mountain nyala, while 2,857 km^2 （12.7%） and 1,026 km^2 （4.6%） was ranked as good or optimal habitat, respectively. Our results not only reflected human induced habitat deg-radation, but also revealed an extensive area of intact habitat on the remote slopes of the Bale Mountain＇s southern and southeast- ern escarpments. This study provides an example of the roles that expert knowledge can still play in modem geospatial modeling of wildlife habitat. New geospatial tools, such as the FunConn model, are readily available to wildlife managers and allow them to perform spatial analyses with minimal software, data and training requirements. This approach may be especially useful for species that are obscure to science or when field surveys are not practical .