MSA: Linking functional biodiversity and airborne imaging to improve predictions of terrestrial ecosystem productivity across climatic gradients

Colorado State University, Fort Collins CO

Investigators

Abstract

Biodiversity is changing at local to global scales in response to climate changes, habitat loss and fragmentation, and more. Meanwhile, ecosystem functions and services that support life depend on biodiversity. With current unprecedented rates of biodiversity loss, the importance of understanding the consequences of biodiversity change has never been greater. Hundreds of controlled experiments with artificially assembled communities have shown that loss of plant biodiversity reduces the productivity of terrestrial ecosystems. Despite this mounting evidence, it remains unclear how important biodiversity is for the functioning of naturally assembled communities. Monitoring biodiversity in natural systems continues to be challenging with traditional field-based approaches, which are time consuming, require lots of human resources and can be extremely expensive. Thus, we need more efficient ways to characterize and monitor biodiversity to understand the potential consequences of biodiversity change for the functioning of terrestrial ecosystems. This study uses a standardized network of observational studies to evaluate the effects of multiple dimensions of biodiversity on terrestrial ecosystem productivity. The broader impacts of this project include: i) advancing the career and professional development of two early career scientists from an underrepresented group; and ii) contributing to the training of undergraduate students in STEM in the use of spatial technologies to characterize plant biodiversity across large environmental gradients. Finally, the project will quantify different facets of biodiversity across NEON domains using remote sensing, which will be essential to provide an updated status of trends of biodiversity globally. The project will integrate theory, remote sensing technologies, and field-based observations to understand the impacts of plant biodiversity for the productivity of grasslands and forests. The study will test the hypothesis that plant biodiversity will increase the productivity of grasslands and forest ecosystems. This hypothesis will be evaluated with a conceptual framework to identify the potential mechanisms explaining how primary productivity increases with plant biodiversity. The project will evaluate the extent to which different facets of biodiversity estimated using remote sensing techniques can predict primary productivity of evergreen, deciduous, and mixed forests across the United States. Thus, the project addresses important gaps in our ability to predict terrestrial ecosystem functions using remotely-sensed biodiversity across major biomes. This research will address fundamental questions about how biodiversity changes across regional scales, and the potential consequences of that change for ecosystem functioning. The research is innovative as it will provide an integrative framework that combines ground-based data, airborne imagery, and biogeochemical cycles to improve our understanding on how plant communities influence ecosystem productivity. The generated models across regional scales and biomes will also provide a baseline to develop more accurate land surface models to improve predictions on how carbon and fluxes will respond to predicted climate changes. 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.