Examining differential drought responses of forest trees with phylogenies and process-based catchment water age modeling

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Forested ecosystems provide many benefits to human society and the natural environment, such as alleviating floods, sequestering carbon, and supporting habitats for biodiversity. However, the benefits that forests provide are at risk due to the effects of climate change, including higher frequency and greater intensity of drought in forested landscapes. The resilience of temperate, arid, and tropical forests to drought is declining globally; and the reasons for this decline are not clear. One difficulty is that computer models that are used to study changes in forested ecosystems require researchers to accurately estimate the water uptake strategies of plants. However, the information needed for models, to accomplish this goal, are challenged because of the lack of readily available datasets, particularly in data-poor regions of the world. For this project, researchers will investigate methods to improve the representation of plants in ecosystem models by using the evolutionary histories of trees to estimate trait values. The project will then use these improved models to test the hypothesis that changes in forest resilience are related to changes in the elapsed time between precipitation and water uptake by plant roots. This research will inform management practices designed to promote drought resilience in forests, it will advance ecosystem modeling, and build capacity in the scientific workforce.This research will link recent developments from tracer derived water age tracking in soils and vegetation xylem, ecohydrological simulation of plant hydraulics, and phylogenetic data analytics, which are three key areas that are necessary to answer critical questions that bridge hydrology and ecosystems science. The investigators will develop an approach to parameterize vegetation hydraulic traits in hydrologic and ecosystem models through phylogenetic trait estimation (PTE), supporting forest simulations in data-poor regions. The PTE will be integrated into process-based ecohydrological and land surface models. The researchers will then validate this modeling approach for twelve research catchments with rich hydrologic and water isotopic datasets representing diverse climates, geologies, and tree species compositions. The resulting process-based models will be applied to study the combined and interrelated effects of climate change on catchment water ages, forest primary production and transpiration, tree hydraulic strategies, and their composite effect on drought risk and forest resilience.This award is co-funded by the Hydrologic Sciences and the Division of Environmental Biology – Ecosystem Sciences Cluster programs.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.