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Ecosystem and community-based model for zonation in Nino Konis Santana National Park, Timor-Leste
Thesis Abstract:
In order to contribute to the management of Nino Konis Santana National Park, an ecosystem and community-based model for zonation was designed. The study focused on data exploration of the potential assets of ecological, physical, and socioeconomic factors as basis in designing zonation. Zonation scheme was done systematically by conducting several stages of processes such as assessment on high conservation values areas (HCVAs), delineation of priorities conservation areas (PCAs), and evaluation of the socioeconomic characteristics of the community in six villages covered. Assessment of HCVA occurrence was based on several maps such as land cover, digital terrain model, IUCN listed species, and socioeconomic characteristics. Land cover map was classified based on Landsat TM5 acquired in November 2006, digital terrain model analysis by generated slopes, and elevation maps based on the United States Geological Survey-Shuttle Radar Thematic Mapping points data. Socioeconomic data analysis focused on the pressures by population density and household activities in gathering forest products.
Integration of several methods of analyses was used such as satellite imagery processing, surface analysis, and spatial analysis. The product of the study was the Biosphere Reserves Zonation Model for the terrestrial part of Nino Konis Santana National Park. Coverage area were core areas, 180.90 km² (26.7%); buffer zones, 215.3 km² (32.9%); and transition areas, 279.8 km² (40.46%). Core areas included PCA-1 Jaco Island, Tutuala Beach and adjacent forests, Paitchao mountain range, and Lore reserve forests dominantly distributed in villages such Lore I and Tutuala. Buffer zones consisted of PCA-2 forest habitat corridor, PCA-3 Iralalaro and Numunira Lake, PCA-3 Oaoloho swamp forests, and PCA-4 north dry lowland forests. Buffer zones were mainly distributed in Mehara and Muapitine villages. Transition area included areas that have no sufficient data to extract the conservation values that might exist.