RAPID: Measuring the response of stream communities to Hurricane Harvey across a semi-arid to sub-humid gradient

了解自然系统如何从灾难性干扰（如大飓风）中变化和恢复，对于帮助社会有效应对这些事件非常重要。像溪流这样的自然系统可以提供缓冲，减轻风暴的影响，加快有利于人类的自然过程的恢复。这项研究旨在了解2017年8月飓风哈维登陆后，德克萨斯州墨西哥湾沿岸的溪流是如何应对洪水和强风的。大量的降雨和相关的风暴潮可能会改变生活在附近溪流中的生物的数量和种类。虽然溪流中的微生物、植物和动物的“群落”预计会发生变化，但也有望随着时间的推移恢复到风暴前的状态。恢复时间被认为在不同的溪流和不同的生物体之间以可预测的方式有所不同。为了验证这个想法，有必要掌握风暴前后的河流流量、物理河流特征和社区组成的数据。该奖项支持的研究人员在“哈维”登陆德克萨斯州南部之前开发并实施了一项溪流监测计划。该合同将允许研究人员在风暴过后和预期的恢复期内立即收集数据。他们将探索恢复周期是否取决于河流是发生在典型的潮湿地区还是典型的干燥地区。该项目的结果将有助于城市规划者和自然资源管理者了解河流对飓风的反应。此外，这项研究还将直接支持教员培训一批多样化的当地科学家和管理人员，这些人可以帮助他们的社区有效地应对未来的飓风。该项目探讨了气候制度如何调节社区对干扰的反应。具体来说，它测试了关于哪些生物群落和相关生态系统过程对气候相关干扰的适应性最强或最弱的预测。这些预测为扰动理论提供了重要的检验，对预测气候变化的生态影响具有重要意义。一个主要的扰动事件，飓风哈维，影响了一个气候梯度从半干旱到半湿润的地区。该研究团队包括一所为西班牙裔提供服务的机构的教职员工和学生，他们将利用一系列沿着气候梯度的河流生态系统，以及风暴前的社区和生态系统数据作为模型系统。在每条河流中，研究小组将对群落（如微生物、无脊椎动物）、生态系统成分（营养物质、底栖藻类、有机物、栖息地）进行高频重复调查，并使用自动记录仪收集连续高频数据（DO、光照、温度、流量、深度）。这些数据将跟踪群落组成、基础资源和生态系统过程的时间变化，共同提供对干扰的即时反应和长期影响的测量。预计在非生物条件下，在随机性较大的干燥系统中，群落对扰动的抵抗力会更高。同样，预计年降水量较高、河岸植被较多的群落将在有机质投入、光照和初级生产增加的驱动下经历正响应。这些一般的功能反应在不同的营养类群中会随着世代时间的变化而变化。

Understanding how natural systems change and recover from a catastrophic disturbance, such as a major hurricane, is important to help society respond effectively to these events. Natural systems, like streams, can provide a buffer to lessen storm impacts and quicken recovery of natural processes that benefit humans. This research aims to understand how streams along the Gulf Coast of Texas responded to flooding and strong winds after Hurricane Harvey made landfall in August 2017. The enormous amount of rainfall and associated storm surges are likely to change the number and kinds of organisms that live in nearby streams. Although the 'community' of microbes, plants and animals in streams is expected to change, it is also expected to recover over time to pre-storm conditions. The time to recovery is thought to differ in predictable ways between streams and between kinds of organisms. To test this idea, it is necessary to have data on stream flows, physical stream characteristics, and community composition before and after the storm. Researchers supported by this award developed and implemented a stream monitoring program prior to Harvey's landfall in south Texas. This award will allow the researchers to collect data immediately after the storm and over the expected recovery period. They will explore if the recovery period depends on whether a stream occurs in a typically wet or typically dry area. Results of this project will help urban planners and natural resource managers understand responses of streams to hurricanes. In addition, the research will directly support faculty to train a diverse group of local scientists and managers who can help their communities respond effectively to future hurricanes. This project addresses how climate regime mediates community response to disturbance. Specifically, it tests predictions about which biotic communities and associated ecosystem processes are most or least resilient to climate-related disturbances. These predictions provide an important test of disturbance theory and are of great relevance to forecasting the ecological impacts of climate variation. A major disturbance event, Hurricane Harvey, affected a region with a sharp climate gradient from semi-arid to sub-humid. The research team, including faculty and students at a Hispanic-serving institution, will use a series of stream ecosystems along the climate gradient, with pre-storm community and ecosystem data, as a model system. In each stream, the research team will conduct high frequency repeated surveys of communities (e.g., microbial, invertebrates), ecosystem components (nutrients, benthic algae, organic matter, habitat), and collect continuous high-frequency data using automated loggers (DO, light, temperature, discharge, depth). These data will track temporal changes in community composition, basal resources, and ecosystem processes that collectively provide measurement of the immediate response and longer-term impacts of the disturbance. It is expected that community resistance to the disturbance will be higher in drier systems with greater stochasticity in abiotic conditions. Likewise, it is expected that communities with higher annual precipitation and more riparian vegetation will experience a positive response driven by organic matter inputs and increased light and primary production. These general functional responses will vary in rate among trophic groups as a function of generation time.