| This thesis is an investigation of the use of Geographic Information Systems (GIS) and the Genetic Algorithm for Rule-set Prediction (GARP) to model endemic bird species richness, as an indicator of biodiversity, in the Sierra de Manantlan Biosphere Reserve (SMBR), Mexico. The GARP model uses geo-referenced occurrence point data combined with environmental and climatic maps to predict spatial distributions of species based on ecological niches. Twenty endemic bird species and seven environmental layers (forest type, soil, land-cover, elevation, geology, temperature, and precipitation) were used in this research to develop a biodiversity map to assess the current zonation of the SMBR. Of particular interest were the core zones, as these areas within the reserve receive highest priority for conservation. It was determined that 71.21% of the SMBR core zones contained very high levels of endemism (16-20 species predicted present) and, as such, are afforded a strong level of protection. |
