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MACROCOSM: Monitor And Constrain tROpical eCOsystem Sensitivity to Moisture

Active Dates 9/1/2022-8/31/2025
Program Area Environmental Systems Science
Project Description
Water drives ecosystem dynamics and functions in a wide range of terrestrial biomes, including tropical forests that receive meters of precipitation every year. Quantifying ecosystem sensitivity to changes in moisture conditions, especially droughts, is pivotal to predicting the future fates of our terrestrial biosphere under climate change. In the tropics, dense vegetation strongly shapes ecosystem carbon and water cycling. However, large knowledge gaps remain in how plants respond to and regulate ecosystem water dynamics. This has led to considerable uncertainty in ecohydrological predictions across state-of-the-art Earth system models. In this project, we aim to improve our understanding of how drought impacts tropical forests by artificially removing natural water input into forest stands in a Puerto Rican moist forest. We further combine the manipulative experiment with advanced computational modeling to shed light on the critical ecophysiology that governs forest sensitivity to moisture, which will provide critical information on the resilience of tropical forests to climate change.

        We propose to monitor soil moisture and vegetation water content at the experimental site using an array of state-of-the-art remote sensing techniques (TLS, GPR, and GNSS). Combined with other traditional observations, these new non-destructive measurements can continuously track high-resolution 3D patterns of both above- and below-ground water dynamics and thus characterize fine-scale heterogeneity in soil and vegetation water dynamics. We will further integrate these water content observations with process-level measurements on vegetation hydrodynamics to understand how these processes respond to moisture changes under experimental drought. Key measurements include root sap flow that quantifies hydraulic redistribution and changes in canopy leaf angle distributions, both of which are key unknown plant processes that can control ecosystem-level water dynamics. We will then assimilate these new data streams and other available or ongoing ecohydrological measurements into a state-of-the-art process-based terrestrial biosphere model ED2.2-hydro. The data assimilation will enable model development and calibration on the key above- and below-ground ecohydrological processes that drive simulated ecosystem sensitivity to moisture. After testing the updated ED2.2-hydro with site-level numerical experiments, we will import calibrated parameters, functions, and modules to DOE’s ELM-FATES model and test the generality of the knowledge gained from ED2.2-hydro. Finally, we will explore the implications of tropical ecosystem sensitivity to moisture constrained by the TFE experiment by conducting regional simulations with contemporary and projected hydroclimate in the neotropics.

        Our proposed research will deliver comprehensive data collections over a long-term ecosystem experiment that is essential for developing an integrated, scale-aware, and predictive understanding of ecosystem responses to environmental change. The novel integration of ground-based remote sensing observations can help to prototype transformational ecological monitoring systems, which can apply beyond tropical biomes. The tight coupling between ecosystem monitoring and modeling in our project will scale our site-level research findings to inform regional to global ecosystem sensitivity to moisture. Altogether, the project directly addresses the DOE’s research focus on plant-mediated ecohydrology across scales, will complement and synergize with other DOE-funded projects on tropical ecosystem dynamics (TRACE, NGEE-Tropics), and is expected to have sustained impacts on various fields of Earth system and environmental sciences.
Award Recipient(s)
  • Cornell University (PI: Xu, Xiangtao)