Collaborative research: Cascade “Ecohydromics” in the Amazonian Headwater System

水通过景观运动支持植物，动物和人类的生活，并通过蒸发影响云的过程和大规模的大气环流。亚马逊盆地通过径流和蒸发循环的水比世界上任何其他邻近的森林都多，树木的蒸腾作用--根系吸收的水并释放到大气中--是这个循环的关键部分。了解植物的根、茎和叶如何与土壤水相互作用，共同调节整个景观的森林蒸腾作用，是一个关键的知识空白，特别是在气候变化的情况下。森林很可能适应亚马逊河景观不同部分不同的土壤水分条件。具体而言，位于地下水深厚的高原上的森林为抵御干旱而保守地用水，而位于地下水浅的潮湿山谷中的森林则自由地用水，但可能对气候变化造成的未来干旱准备不足。要了解景观水文，雨林的组成，以及它们对全球变化的敏感性，水的流动是如何从上游到下游的植物和土壤调节的综合理解是必需的。这种理解对于地球系统建模也至关重要，该模型用于预测亚马逊雨林的命运并量化其对气候的未来影响。该项目将不同的学科-植物生理学，生态学，水文学-联系起来，并将它们整合到景观功能模型中。该项目还将帮助培训下一代科学家，无论是在美国和巴西，跨学科的研究方法，并通过对植被和水文过程的计算机建模暑期学校。该项目将开发一个新颖的科学推广计划，将K-12学生与实时亚马逊树数据联系起来，以及一个简短的课程和一系列视频，教学生如何解释数据，理解更广泛的科学背景，并与科学家和实时“会说话的树”建立个人联系该项目描述了生理和水文过程中的景观变化，并将观测与流域建模和假设检验相结合。项目活动的重点是亚马逊河上游集水区中部特有的高原和山谷在空间上错综复杂的组合。本研究假设：（H1）森林蒸腾量的强烈景观差异来自高原树木的独特特征（没有根系进入地下水）和山谷（H2）以前未量化的“混合”土壤水力学控制土壤水通量和连接高原和山谷的过境时间;（H3）高原森林通过调节地表水从较高景观区向较低景观区的流动，影响河谷森林的组成和功能。研究地点位于巴西亚马逊河流域：马瑙斯附近的“KM 34”包含一个装有仪器的分水岭，其山坡水文学历史数据和研究比原始潮湿热带森林中的任何其他分水岭都要多，而圣塔伦附近的“KM 67”位于一个广阔的高原上，以前部署了深层土壤水分坑，可以隔离平坦高原的典型过程。这两个网站都包含涡流通量塔，树冠通道，以及丰富的生态研究历史和可用的数据集。KM 67附近的一个新的山谷子站点将作为KM 34在山谷中观测的独立复制。植被生态生理学，地下水文学和地下水的过程为基础的模型将参数化与叶生理学，树木形态特征，土壤水分和物理特性，地下水位和径流的观察。这些模型将采用概率学习和不确定性量化的新工具进行集成，以进行适当的参数化，并通过对树液流、生态系统气体交换和能量平衡的独立观察进行验证。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

Water movement through landscapes supports plant, animal, and human life, and through evaporation affects cloud processes and large-scale atmospheric circulation. The Amazon Basin cycles more water through streamflow and evaporation than any other contiguous forest in the world, and transpiration by trees – water taken up by roots and released to the atmosphere – is a critical part of this cycle. Understanding how plant roots, stems, and leaves interact with soil water to jointly regulate forest transpiration across landscapes is a critical knowledge gap, especially as climate changes. Forests are likely adapted to distinct soil moisture conditions in different parts of Amazonian landscapes. Specifically, forests on elevated plateaus with deep groundwater use water conservatively in order to tolerate drought, while those in wet valleys with shallow groundwater use water freely but may be poorly prepared for droughts of the future caused by the climate change. To understand landscape hydrology, rainforest compositions, and their susceptibility to global change, an integrated understanding of how water flows are regulated from upstream-to-downstream by plants and soil is required. This understanding is also critical for Earth-system modeling used to project the fate of Amazonian rainforests and quantify their future influence on climate. This project links diverse disciplines – plant physiology, ecology, hydrology – and integrates them into a model of landscape function. This project will also help train the next generation of scientists, both in the U.S. and Brazil, on interdisciplinary approaches in research, and through a summer school on computer modeling of vegetation and hydrologic processes. The project will develop a novel science outreach program connecting K-12 students to real-time Amazon tree data as well as a short class curriculum and a series of videos that teach students how to interpret data, understand the broader scientific context, and build a personal connection with scientists and real-time “talking trees” from the world’s most famous tropical forest.This project characterizes landscape variation in physiological and hydrological processes, and integrate observations with watershed modeling and hypothesis testing. Project activities focus on the spatially intricate mosaic of plateaus and valleys characteristic of central Amazonian headwater catchments. This research hypothesizes that: (H1) strong landscape variation in forest transpiration capacity arises from distinct characteristics of trees residing on plateaus (no root access to groundwater) and valleys (root access to groundwater) zones; (H2) previously unquantified “hybrid” soil hydraulics govern soil water fluxes and transit times connecting plateaus and valleys; and (H3) plateau forests influence the composition and function of valley forests by regulating subsurface water flows from higher to lower landscape areas. Study sites are located in the Brazilian Amazon: “KM34” near Manaus contains an instrumented watershed with more historical data and research on hillslope hydrology than any other watershed in a pristine wet tropical forest, and “KM67” near Santarém sits on a broad plateau with previously deployed deep soil moisture pits, allowing the isolation of processes typical for flat, elevated plateaus. Both sites contain eddy flux towers, canopy access walkways, and a rich history of ecological research and available datasets. A new valley subsite near KM67 will serve as an independent replicate of KM34 observations in valleys. Process-based models of vegetation ecophysiology, subsurface hydrology, and groundwater will be parameterized with observations of leaf physiology, tree morphological traits, soil moisture and physical properties, water table, and streamflow. These models will be integrated employing novel tools in probabilistic learning and uncertainty quantification for proper parameterization and validated with independent observations of tree sapflow, and ecosystem gas exchange and energy balance.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.