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Improving models of stand and watershed carbon and water fluxes with more accurate representations of soil-plant-water dynamics in southern pine ecosystems

Active Dates 9/1/2022-8/31/2025
Program Area Environmental Systems Science
Project Description
Improving models of stand and watershed carbon and water fluxes with more accurate representations of soil-plant-water dynamics in southern pine ecosystems

            Plant responses to water limitations involve a complex set of interactions with soil, the atmosphere, and other plants. While there is strong fundamental knowledge about the key processes through which plant hydraulics affect productivity, we currently lack several key components necessary for a predictive understanding of ecosystem response to future climate conditions. These components include (1) mechanistic understanding of plant-mediated hydraulic processes in under-studied systems and (2) representations of biophysical factors affecting coupled water-carbon cycles in models. To address these challenges, we will employ a Model-Data Experiment (MoDEx) design informed by our project team’s previous field experiments and numerical model development.

            To improve our mechanistic understanding of coupled carbon-water processes and to collect necessary data to parameterize and test models, we will conduct an intensive set of field measurements at existing AmeriFlux sites operated by the project team. While a wealth of past work has examined the role of plant-mediated effects on ecosystem water cycling, particularly in arid ecosystems, less is known about these mechanisms in the southeastern U.S., a humid subtropical region characterized by high productivity but experiencing increasing temperature and drought frequency and intensity. Climate change, combined with large-scale structural and compositional changes in vegetation, limit our ability to use existing observational data to predict future responses. This project will focus on longleaf pine ecosystems, once a dominant forest type in the region that is undergoing large-scale efforts to restore it through much of its native range. These savannah-like systems consist of an evergreen pine overstory and grassy understory and are generally found on well-drained, sandy soils with highly variable water tables. While usually characterized as drought tolerant, carbon sequestration rates are dependent on interactions between climate, soil type, hydrology, and plant composition, such that predictions based on simple, empirical responses to environmental drivers are not adequate. Our work will examine plant-level hydraulic coordination of groundwater and soil water uptake, hydraulic redistribution (HR), plant water storage (PWS), transpiration, and leaf-level conductance, as well as competition among plants and the combined effects of hydrologic processes on ecosystem carbon dynamics.

            To address mechanisms missing in current land surface models, we significantly expand the functionality of an existing numerical model, developed by members of the project team, by adding components to resolve dynamic groundwater-root-hydraulic interactions and ecosystem respiration. The result will be a novel model that can resolve fully coupled interactions between groundwater, soil moisture, plants, and the atmosphere. We use the extensive field measurements to parameterize and validate the expanded functionality of the new model and use it to test hypotheses that isolate the processes that compete for plant-stored water and quantify the resulting effects on ecosystem water and carbon fluxes. Finally, a series of simulations driven with Energy Exascale Earth System Model (E3SM) future climate scenarios will predict the ability of HR and PWS to buffer longleaf pine productivity under projected extremes of the hydrologic cycle, including higher vapor pressure deficit and periods of drought. The advances in mechanistic understanding of ecohydrological processes and model development generated from this project will be applicable to a broader set of ecosystems and will help to direct future experimental field and modeling efforts.
Award Recipient(s)
  • Duke University (PI: Domec, Jean-Christophe)
  • Portland State University Portland (PI: Hartzell, Samantha)
  • Clemson University (PI: O'Halloran, Thomas)
  • U. S. Forest Service (PI: Oishi, Andrew)