Collaborative Research: Cracking the code of grass distributions: Using physiology, phenology, and phylogeny to build better mechanistic distribution models

About This Grant

Grasses are beneficial to human society by creating habitat for bees, and other pollinators, that ensure crops produce fruit and seeds, improve the quality of water, trap carbon, and provide food for animals upon which people rely for nutrition. However, grasses are a large group of over 11,000 species, which cover ~50% of the earth’s surface, and there are differences in their ability to perform beneficial ecological functions. For example, they can differ in the time of year they grow (also called phenology), how fast they grow, and their ability to tolerate and survive droughts. Importantly, there are often trade-offs between these characteristics, such that species that only grow in the spring may not be very tolerant of drought, and species that only grow during the summer generally do not grow very fast. Therefore, environmental changes during different seasons may prevent some species from thriving in their current locations, altering the ecosystem services they provide. To effectively manage resilient grasslands for the future, we need better information on the phenology, growth rates, and drought tolerance of a broader range of grass species. Most projects that measure these characteristics have focused on trees, leaving major gaps in our understanding of these traits in grasses. Using novel techniques to observe processes occurring inside the leaf and new mapping methods, our project will provide critical information about plant traits and tradeoffs in different environments to help predict how grass distributions will respond to changing weather patterns and environmental conditions. Changes to plant communities are continually occurring as plants disappear, appear, and re-arrange in ecosystems across the globe as rising temperatures and changing precipitation patterns reduce the available water for plant growth. Plant responses to these dynamic conditions dictate whether a species can persist in a region or must shift distributionally. Modern approaches to modeling species distributions rarely include the mechanistic underpinnings of organismal responses but, instead, rely on bivariate relationships between individual traits and annual summaries of abiotic conditions. This approach ignores the fact that networks of traits, rather than any single trait, generate different drought-coping strategies and that drastic differences in grass phenology decouples plant growth conditions from annual summaries of abiotic conditions. To improve predictions of future species distributions and inform restoration projects of ideal seed-mixes, the overall objective of our study is to improve the accuracy of species distribution models through a better understanding of grass species resilience by including trait networks and growth phenology. Using a set of species that spans the entire grass family, the investigators will identify mechanistic trait networks leading to different drought-coping strategies, including mechanisms leading to embolism formation, a key drought-coping trait rarely studied in grasses. Integrating these key traits will provide information on species responses and distribution shifts and the experimental design will also provide information on how these traits may evolve independently or in unison within the grass family. 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.