International Dissertation Enhancement Research: Natural Forest Management Plans in Costa Rica: A Potential Framework For Assessing Tree Biodiversity

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This Americas Program dissertation research will support doctoral student Juan P. Arroyo under the supervision of Dr. Robin Chazdon of the University of Connecticut and under the sponsorship of Dr. Luis D. Gomez, Scientific Director of the La Selva Biological Station of the Organization of Tropical Studies (OTS) in Costa Rica. The research intends to address and test the utility and accuracy of pre-harvesting tree inventory data generated by natural forest management plans for assessment of tree biodiversity at the local, landscape and regional levels in the San Juan- La Selva Biological Corridor in Costa Rica. The proposed study has four components: 1) tree biodiversity assessment at local, landscape, and regional scales based on databases generated from existing natural forest management plans (NFMP); 2) tree diversity assessment based on an independent, standardized biodiversity inventory methodology in the same farms; 3) comparison of results between NFMP data and standardized biodiversity data; and 4) a population viability analysis of selected commercial and non-commercial tree species of conservation concern within the regional landscape. The study could serve as a model to be widely applied across many tropical countries where natural forest management plans are available, permitting the development of tree diversity databases for use in biodiversity assessment, baseline conservation data, and land-use planning. At the conclusion of this project, a workshop will be organized and held at La Selva Biological Station to share methodology, results, and conclusions with farm owners, forestry technicians, local conservation groups, researchers, and government personnel. The workshop will demonstrate how regional conservation and biodiversity research programs can benefit from data generated from forest management plans and how these plans could be modified or supplemented by independent survey data to supply data needed for conservation planning at the regional level.