The overarching objective of this interdisciplinary science project is to leverage new theory and observations in land, atmospheric and space-based research to improve estimates of the partitioning of global carbon fluxes between terrestrial ecosystems and the atmosphere at high spatial and temporal resolution.
This project will use eddy-covariance observations together with a suite of NASA, DOE and other partner agency data, to provide improved estimates of the partitioning of carbon between the biosphere and the atmosphere, advance theory on ecosystem scale photosynthetic light- and water-use efficiency, and develop a high-resolution framework that uses machine learning to combine these advances. By bringing together the "bottom up" and the "top down," we aim to elucidate the controls of inter-annual variability and transform our ability to characterize carbon-climate feedbacks. This will improve insight into the processes that govern global carbon uptake and functional responses that control the magnitude of carbon cycle feedbacks, a key goal in order to improve our ability to predict the future evolution of the Earth System.
Publications: 23 (March 2019). See list here.PI: Keenan
Co-Is: Fisher (JPL), Michalak (Stanford)
Funding: NASA, DOE
Plants adapt and have the potential to acclimate, through changes in resource allocation, to the environment. This project aims to develop a theory of photosynthetic acclimation from first principles.
Under this project we are developing photosynthetic theory and using it to generate and test hypotheses regarding the mechanisms governing the biotic control of photosynthesis in response to climate. We combine recent understanding of optimal resource allocation with a large global databases of physiological measurements. Our results suggest that plants acclimate to growth conditions in a manner that fulfills co-optimality criteria. The resulting hypotheses regarding acclimation responses have large implications for the response of vegetation, and thus the global carbon cycle, to ongoing climate change.
Publications: 9 (March 2019). See list here.PI: Keenan
Flash droughts are typically distinguished from conventional droughts on the basis of their rapid onset and/or duration. This project aims to examine the role of vegetation in flash drought events.
Flash droughts come on seemingly without warning, and sometimes with devastating effects. Another distinguishing feature of flash droughts is that they are largely driven by evaporative demand. This has implications for the dynamics and predictability of flash droughts in a changing climate. It also suggests that understanding and prediction of flash droughts is inherently linked to understanding and prediction of high evaporative demand periods, including heat extremes that persist for several days to weeks. In this NSF PREEVENTS project, we are working to advance the understanding and subseasonal-to-seasonal prediction of flash droughts and their associated heat extremes. At Berkeley, we are developing machine-learning based estimates of photosynthesis, evapotranspiration and respiration at high resolution, in combination with remotely sensed estimates of evaporative stress, to define and characterize flash drought events.
Publications: We're just getting started. Watch this space!PI: Zaitchik (Johns Hopkins)
Co-Is: Keenan, Badr (Johns Hopkins), Otkin (U. Wisconsin-Madison), Anderson (USDA)
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