Interacting Impacts of Changes in Mean and Variance of Water Availability on Vegetation Phenology and Productivity in Dryland Ecosystems

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This award investigates how changes in the timing and amount of rainfall impact dryland ecosystems of the southwestern United States. This award will improve predictions of how these ecosystems will respond to future climate change. Worldwide, ecosystems like these play an important role in the global carbon cycle and support 40% of the human population. Improving predictive understanding of dryland responses to climate change is a critical challenge that will have benefits to society and also relevance to policy decision-making. Results from this award directly address an important knowledge gap, and will provide insights that have significance for management and conservation of dryland ecosystems worldwide. The award will leverage experimental infrastructure, already constructed, that alters the amount and the intensity of rainfall events throughout the year at the Sevilleta Long-Term Ecological Research (LTER) site in New Mexico. Research will be conducted in four distinctly different ecosystem types, including two grasslands and two shrublands. Digital cameras will be installed overlooking experimental plots in each ecosystem type and will record thousands of photographs year-round. These photographs will be made publicly available, immediately and without restriction, for research and education. Responses to the experimental treatments will be quantified through automated, quantitative analysis the color of each picture. Broader impacts from this award will include both formal and informal science education. Graduate and undergraduate students recruited from traditionally under-represented groups, will receive training through this project. Public participation in scientific research will be achieved through ongoing collaboration with the Sevilleta LTER site’s “Schoolyard” program, and will bring the science of this project to K-12 teachers and their students.How future climate change will impact dryland ecosystems depends on how these systems respond not only to increases in temperature and changes in mean precipitation, but also to increases in precipitation variance. Researchers will test the overarching hypothesis that changes in the mean and variance of water availability will have independent as well as interacting effects on vegetation phenology, which then will then drive productivity via changes in growing season length. Based on environmental response function theory, unique responses of four distinct dryland ecosystem types are expected. Data products derived from digital camera imagery will be used to quantify the start and end of the active (growing) season, total active season length, as well as to estimate rates of primary production and total annual primary productivity by scaling gross primary productivity quantified from existing CO2 flux measurements at Sevilleta LTER. Project data will be assimilated into an already-developed ecosystem model, which will be used for forecasting and model-based tests of hypotheses. Outcomes from this project will include peer-reviewed publications as well as imagery and datasets that will be relevant to dryland researchers worldwide.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.