Understanding Water and Carbon Dynamics for Improved Prediction of Tropical Tree Function and Demographics


Nate McDowell1*(nate.mcdowell@pnnl.gov), Alexandria Pivovaroff2, Mizanur Rahman1, Alfonso Zambrano3, Joe Wright3, Bruno Gimenez4, Cristina Santos da Silva4, Valdiek da Silva Menezes4, Gustavo Spanner4, Regison Oliveira4, Jeff Warren5, Niro Higuchi4, Jeffrey Chambers6


1Pacific Northwest National Laboratory, Richland, WA; 2Occidental College, Los Angeles, CA; 3Smithsonian Tropical Research Institute, Gamboa, Panama; 4National Institute for Amazonian Research, Manaus, Brazil; 5Oak Ridge National Laboratory, Oak Ridge, TN; 6Lawrence Berkeley National Laboratory, Berkeley, CA



Understanding and modeling the carbon and water fluxes and stores of tropical trees is critical for improving predictive capacity for forest function under a changing climate. This study investigated the processes regulating plant carbon and water balance in Panama and Brazil with the goals of testing hypotheses and providing parameterization and benchmarking datasets for FATES-Hydro. Resilience of tropical forests to climate perturbations appears to be decreasing globally, with plant hydraulics playing a large role in regulating this resilience.

Hydraulic constraints on photosynthesis become increasingly dependent on vapor pressure deficit as drought worsens, leading to novel constraints on canopy gas exchange. Hydraulic traits and mortality exhibit large shifts over time at Barro Colorado Island, Panama, consistent with climate-driven changes in the most adaptive physiological characteristics. Such shifts in hydraulic traits are also observed over a large precipitation gradient in Panama, suggesting that climate drives adaptive changes in hydraulic traits. Current work is focused on providing sapflow estimates of transpiration along with additional measurements for further tests of the hydraulic mechanisms underlying survival and mortality. This work is ongoing in both Panama and Brazil. ModEx linkages to FATES-Hydro are direct through parameterization and benchmarking of the model, along with conceptual knowledge gains that are incorporated into the model.