Journal
ECOLOGICAL MODELLING
Volume 165, Issue 2-3, Pages 251-264Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/S0304-3800(03)00077-2
Keywords
habitat modelling; expert knowledge; GIS; sambar deer
Categories
Ask authors/readers for more resources
Expert knowledge regarding the distribution of sambar deer (Cervis unicolor) in Lake Eildon National Park (LENP), Victoria was used to build a Wildlife habitat model to assist with park management. The paper presents two methods for eliciting expert knowledge. These were a quantitative geographical information system (GIS)-based approach using a customised graphical user interface, and a qualitative approach that uses semi-structured-interviews. The GIS approach is valuable as it is objective, repeatable and provides a spatial context for knowledge elicitation. Experts were asked to provide estimates of sambar sightings and predicted densities with the assistance of contextual environmental data including terrain, roads, hydrology and rainfall surfaces. The quantitative knowledge elicitation process did not identify any sambar environmental niches in the Park, and the experts disagreed about the location of likely habitat. On the other hand, the qualitative assessment showed very strong expert agreement and a combination of this information and published literature was used to build a habitat map. The results of the analysis indicate that sambar deer occur throughout the entire Park. It is envisaged that the results can be used as baseline information for population modelling and natural resource management in the Park. Elicitation of knowledge is complicated by a number of factors including computer proficiency and study site familiarity. The relatively large cohort used in this study and the inherent inconsistencies that were encountered indicate that wildlife managers should interpret results carefully from habitat models that use only a relatively small cohort of experts. Published by Elsevier Science B.V.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available