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 avai...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 .展开更多
文摘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 .
