NSF Award
2326013
This project will use satellite imaging and species location records in primary forests of the Caribbean to determine which species are threatened with extinction and how their loss will affect ecosystem function across the landscape. The outcomes will help focus limited resources on protecting the most vulnerable and functionally important species in these highly vulnerable areas. Biodiversity is essential for the processes that support life, including food security, medicines and public health. However, with a changing climate, forests are disappearing around the world, leading to a major loss of species. This research will improve on current methods of assessing extinction risk by increasing precision and automation of methods, and by extending the application to all regional species. The project will also map the location of primary forest habitats, which are regions of original forest not previously disturbed that hold the most biodiversity with the greatest number of ecological functions. An additional outcome of the project will be to identify the most critical areas for better protection of biodiversity. <br/><br/>Greater knowledge of functional biodiversity will increase understanding of how ecosystems work and how they will change in coming decades through human modifications of habitat and climate, and through other threats to species. Knowing how, when, and where biodiversity changes will occur will help society prepare for the future and mitigate the losses. This project brings together expertise from satellite remote sensing, distribution modeling, organismal biology, and conservation biology to integratively address biodiversity loss through the development of innovative analytical methods. The project will focus on primary forest, which has more functional diversity than secondary forests, because it includes more structure and ecological specialists. The high-resolution land cover data sets with primary forest included that will be produced are currently rarely available. The system, which updates as new satellite imagery, climatic, and biodiversity data become available, is ideally suited for large areas of biodiversity, where remote sensing and environmental data are the primary sources of information for extinction risk. This project focuses on animals and plants in the Caribbean region to test hypotheses of functional diversity change across landscapes and through time.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
