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Collaborative Research: MRA: A lineage-based framework to advance grassland macroecology and Earth System Modeling

Objective

Humanity depends on grasses like corn, wheat, and switchgrass for food, fuel, and fiber. Grasslands and savannas play an important role in carbon and water cycling. They are heavily impacted by humans. They are widespread ground cover for many other ecosystems. Despite their importance, grasses are often omitted from plant databases and studies so have less attention than trees and other woody plants. This project will advance predictability of grassy ecosystem responses to global change by measuring many grass species traits. The new data will be incorporated into new modeling approaches. The project will enhance understanding of grass ecology, with many applications in agriculture and natural resource management. It will also provide important training opportunities for young scientists and will share results with K-12 teachers for use into their classrooms.<br/><br/>In this work, a novel, integrative framework that reorganizes grass vegetation types around phylogeny-driven functional diversity will be developed. Lineage-based trait coordination and distribution will be investigated along environmental gradients in North America at select NEON and LTER sites by collecting an unprecedented suite of trait and leaf spectral data and integrating the information with existing databases. The method is fundamentally different from previous approaches, as it uses phylogenetic relatedness to create lineage-based functional types (LFTs), which anchors trait data in an evolutionary context. Developing and implementing LFTs will increase the accuracy of site-, regional-, and Earth-System-Model-scale predictions, and provide a synthesis of grass functional ecology that is critical for forecasting how grassy biomes will respond to increasing CO2, climate change, and disturbance. This project will provide training and career development opportunities for interdisciplinary research to 3 graduate students and 1 postdoctoral researcher. The education and training centerpiece will be an immersive graduate student workshop that will train dozens of graduate students in state-of-the-art ecophysiological and spectroscopic techniques that underpin a broad swath of plant ecology and precision agriculture.<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.

Investigators
Jesse Nippert
Institution
Kansas State University
Start date
2019
End date
2022
Project number
1926345