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

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.

森林生态系统为人类社会和自然环境提供了许多好处，例如减轻地板，隔离碳和支持生物多样性的栖息地。但是，由于气候变化的影响，森林提供的益处受到风险，包括更高的频率和森林景观中的干旱强度更高。温度，干旱和热带森林对干旱的弹性正在全球下降。而且这种下降的原因尚不清楚。一个困难的是，用于研究森林生态系统变化的计算机模型需要研究人员准确估计植物的水吸收策略。但是，由于缺乏随时可用的数据集，尤其是在世界各地的数据区域，模型所需的信息才能实现这一目标。对于该项目，研究人员将通过使用树木的进化历史来估计特征值来研究改善生态系统模型中植物表示的方法。然后，该项目将使用这些改进的模型来检验以下假设：森林弹性的变化与植物根部降水和水吸收水之间经过的时间的变化有关。这项研究将为旨在促进森林中的干旱复原力的管理实践提供信息，它将推动生态系统建模，并在科学劳动力中建立能力。这项研究将与木质部木质部和植被木质部中的水年龄追踪的最新发展联系起来，对植物水合物的生态水合学模拟，以及这些关键的科学问题，这些问题与三个关键的科学问题构成了重要的问题，这些问题是至关重要的问题。研究人员将通过系统发育特征估计（PTE）开发一种方法来在水文和生态系统模型中参数化植被氢化特征，从而支持数据贫困地区的森林模拟。 PTE将集成到基于过程的生态和陆地表面模型中。然后，研究人员将使用代表潜水员气候，地质和树种组成的丰富水文和水的同位素数据集验证十二个研究集水区的建模方法。由此产生的基于过程的模型将用于研究气候变化对流域水时代，森林初级生产和蒸腾作用，氢化策略的结合和相互关联的影响，以及它们对干旱风险和森林复原力的综合效应。该奖项由水文科学和环境生物学授予 - 生态系统宣传奖和统计范围内的纽约市诉讼。通过使用基金会的知识分子和更广泛影响的评论标准来通过评估来支持。