CAREER: Plant traits link disturbance history to carbon uptake across spatiotemporal scales

When more carbon dioxide is released than can be absorbed by Earth’s land and water, the extra carbon dioxide builds up in the atmosphere and absorbs energy. This extra energy warms the atmosphere and lets it hold more water vapor, causing global climate change. Changes in climate and weather, in turn, impact ecosystems and the people who rely on them.

To understand and predict the impacts of climate change, a key first step is to understand how much carbon dioxide is absorbed by the Earth’s land and water. On land, most carbon dioxide is taken up by plants, but this uptake is especially difficult to predict because plants differ in their abilities to absorb carbon and to respond to changes in the environment.

This CAREER award takes a new approach to this challenge by combining historical data from satellites, new data from airborne sensors, and computer modeling to map forest carbon uptake in eastern U.S. forests. This award will be integrated with education and outreach activities, including a field course, teaching modules, digital outreach materials, and public writing, that invite students of all ages to learn about macrosystems ecology.

Current estimates of carbon uptake are limited by a lack of mechanistic understanding of the connections between disturbance, plant physiological and structural traits (‘plant traits’), and gross primary production (GPP). This CAREER award develops the concept of ‘disturbance syndromes’ in forest ecosystems, which posits that temporal patterns of response to disturbances may be similar even among diverse ecosystems.

The project targets three key questions: (1) How much does disturbance syndrome explain current distributions of plant traits?; (2) Which plant traits are most important to predicting GPP?; and (3) Where will disturbance syndromes improve scaled up estimates of GPP? Using nearly 40-years of Landsat satellite data, the project will map disturbance syndromes across eastern U.S. forests.

These maps of disturbance syndromes, along with mapped environmental gradients, will inform a predictive model of GPP mediated by plant trait distributions estimated using the National Ecological Observatory Network’s Airborne Observation Platform. Through the integration of research and education objectives, this project aims to cultivate a more inclusive, diverse, and technically skilled community to understand terrestrial ecosystem patterns and processes and to accelerate the pace of innovation in macrosystems ecology.

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.