MSA: Integrating biodiversity observations with airborne and satellite data to predict shifts in assemblage diversity and composition under global change

Biodiversity—the living fabric of our planet—is rapidly changing due to alterations in the climate and human activities. These rapid changes are negatively impacting the capacity of ecosystems to provide goods and services to humanity. The development of new ways to characterize and monitor biodiversity that take advantage of advancing remote sensing technologies is critical for developing effective management strategies and conservation actions to address global change. The project will evaluate the capacity of airborne and satellite remote sensing data to produce reliable predictions of plant and bird diversities across the conterminous United States. The broader impacts of this project include several components. First, the project will provide scientific and professional development of an early-stage scientist from an underrepresented group. Second, the project will contribute to the training the next generation of STEM researchers to investigate biodiversity in the Anthropocene. Third, the project scientists will engage the public in biodiversity education through the integration of project results into an undergraduate and graduate course in Biodiversity Science at the University of Minnesota. Fourth, the project will contribute to advancing international efforts to assess and monitor biodiversity globally. Finally, researchers will distribute open-source software to the world-wide research community through online repositories, fostering reproducibility.

The project combines theory and novel methods from different disciplines—including macroecology, community ecology and imaging spectroscopy—to understand the potential of remote sensing data in predicting and monitoring biodiversity. Specifically, researchers will test the hypothesis that diversity measures derived from remote sensing can be used as surrogates of other measures of biodiversity and hence for monitoring biodiversity at large spatial extents. The project addresses important gaps in our ability to predict species distributions and assemblage composition. New insights will be gained for understanding the potential of measures derived from remote sensing—such as spectral alpha and beta diversity—for the prediction of species distributions and assemblage composition. In doing so, the project will contribute to the development of novel approaches for biodiversity monitoring across time and space. Overall, the project provides a flexible framework that allows the integration of multiple means of predicting and detecting species and advances efforts to monitor changes in biodiversity.

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.