Assessing wildlife diversity using habitat suitability indices and spatial analysis for ecosystem management
Abstract
The concept of multi-species management, habitat suitability indices (HSI) and GIS techniques were used to develop an evaluation procedure for monitoring ecosystem management. This study examined possible ways to use the accumulated knowledge found in HSI to estimate potential wildlife diversity across a landscape for ecosystem management assessment. Species that occur in Missouri Ozark Forest Ecosystem with existing HSI models were selected. Point sample data combined with spatial data from the Missouri Ozark Forest Ecosystem Project (MOFEP) were used to assess ecological organization at the community-ecosystem level. A moving window the size of the home ranges of each species was applied to calculated the average value of each life requisites. Objectives of this study include the development of a procedure to estimate Habitat Suitability Indices for forest stands from point sample data incorporating spatial reasoning and constraints and the development of a multi-species index. Compartment One of the MOFEP was used in this study. It is a dense forest with nearly closed overstory canopies. It is high in density, diversity, with moderate understory and herbaceous crown coverage. Overall, Compartment One has low HSI value for late successional species or species that prefer open forests and high HSI value for early to mid-successional species. HSI values vary widely for species with very specific habitat requirements. Three weighting methods were used to demonstrate the possible ways of combining HSI values. Species richness is also examined as a multi-species index. When examined closely, the diversity group can be explained by the guild concept of multi-species management. The use of a moving window that represents an animal's home range enabled the spatial evaluation of the habitat condition home range by home range. It is recommended that the goal of management be clearly defined or used in the selection of the species of interest and the interpretation of the results. The selection of species in this study is restricted to the available HSI models. However, as more and more HSI models are developed, the same procedure could be applied to more species.
Degree
Ph.D.
Advisors
Mills, Purdue University.
Subject Area
Forestry|Ecology|Environmental science
Off-Campus Purdue Users:
To access this dissertation, please log in to our
proxy server.