Spatial Conservation Planning Framework for Assessing Conservation and Restoration Opportunities in the Atlantic Forest of Brazil.

摘要

Rapid rates of habitat change and growing exploitation of natural resources have resulted in threats to biodiversity. With the purpose of minimizing anthropogenic pressures on biodiversity and insuring the perpetuation of remaining natural areas, various conservation approaches for protected natural areas have been developed. However, the degradation of natural areas is still a growing concern and has become especially problematic in tropical regions. These regions have the highest biodiversity richness and are often found within developing countries with high population growth rates and severe socio-economic problems.;Most remaining patches of the Brazilian Atlantic Forest are embedded in a mosaic of secondary growth, anthropogenic forests, pastures, and agricultural crops. This forest is one of the top five global biodiversity hotspots yet only 11.4% of the original forest remains and alarming deforestation rates have made it one of the most endangered ecosystems in the world.;In the past, conservation plans for the Atlantic Forest have typically been formulated at the local scale. As a result, the network of protected areas for the entire region is not economical. In the future, the effectiveness of the Atlantic Forest's protected areas may be improved through the use of systematic conservation planning methods at the regional scale. During the design of a conservation area network, systematic conservation planning assesses the "complementarity" value of each site that is a candidate to be put under a conservation plan, which is the extent to which the site represents new features of biodiversity that are not represented adequately in sites selected earlier. The use of complementarity results in a more economical set of protected areas by reducing the extent to which new sites duplicate the biodiversity contents of existing protected areas.;The objective of my analysis is to use complementarity-based site selection to prioritize habitat for threatened avifauna in the Atlantic Forest. This study makes the following new contributions. First, I use radar remote sensing to model suitable habitat for forest birds in the Atlantic Forest, an approach that has proved effective at mapping species' distributions in the Amazon. Second, I construct ecological niche models for avifauna at the 1 km resolution using a maximum entropy algorithm, which is known to be among the best performing methods for modeling species' distributions. Third, sustaining natural habitats and their biodiversity processes demands the development of larger continuums of forests. I predicted the most suitable areas for forest restoration by using graph algorithms to prioritize areas for forest regeneration to establish connectivity among conservation areas in the Atlantic Forest. The connectivity analysis incorporates a recent model of intact vegetation in the Atlantic Forest. Insofar as deforestation in the study region is similar to land conversion in other biodiversity hotspots, I expect our methodology to be applicable to conservation efforts elsewhere in the world.