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

RAPID：测量半干旱到半湿润梯度河流群落对飓风哈维的响应

• 批准号: 1761677
• 负责人: Christopher Patrick
• 金额: $ 20万
• 依托单位: Texas A&M University Corpus Christi
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-15 至 2021-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1761677&HistoricalAwards=false
• 关键词: RAPID; Measuring; response; stream; communities

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.

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。自然系统，如河流，可以提供缓冲，以减轻风暴的影响，并加快恢复有利于人类的自然过程。 这项研究旨在了解德克萨斯州墨西哥湾沿岸沿着的溪流如何应对2017年8月飓风哈维登陆后的洪水和强风。 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，但随着时间的推移，预计也会恢复到风暴前的状态。 恢复的时间被认为是不同的河流和不同种类的生物体之间的可预测的方式。 为了验证这一想法，有必要获得风暴前后的河流流量、河流物理特征和群落组成的数据。 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河流监测计划。 该奖项将使研究人员能够在风暴发生后立即收集数据，并在预期的恢复期内收集数据。 他们将探索恢复期是否取决于溪流是出现在典型的潮湿地区还是典型的干燥地区。该项目的成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，这项研究将直接支持教师培训一批多样化的当地科学家和管理人员，他们可以帮助他们的社区有效地应对未来的飓风。 该项目探讨了气候机制如何介导社区对干扰的反应。具体而言，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最具或最不具弹性的预测。 这些预测提供了一个重要的测试扰动理论和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，哈维飓风，影响了一个从半干旱到半湿润的气候梯度很大的地区。该研究小组，包括教师和学生在西班牙裔服务机构，将使用一系列溪流生态系统沿着气候梯度，与风暴前的社区和生态系统数据，作为一个模型系统。在每个流中，研究团队将对社区进行高频率重复调查（例如，这些数据包括生物（微生物、无脊椎动物）、生态系统组成部分（营养物、底栖藻类、有机物、生境），并使用自动记录仪收集连续的高频数据（溶解氧、光照、温度、排放、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，这些变化共同提供了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具有更大随机性的干燥系统中，群落对干扰的抵抗力将更高。 同样，预计年降水量较高和河岸植被较多的社区将在有机物投入和增加光照和初级生产的驱动下经历积极的反应。这些一般的功能性反应将在不同的营养组作为一代时间的函数率。

项目成果

A System Level Analysis of Coastal Ecosystem Responses to Hurricane Impacts

• DOI: 10.1007/s12237-019-00690-3
• 发表时间: 2020-04
• 期刊: Estuaries and Coasts
• 影响因子: 2.7
• 作者: C. Patrick;L. Yeager;A. Armitage;F. Carvallo;V. M. Congdon;K. Dunton;M. Fisher;A. Hardison;J. D. Hogan;J. Hosen;Xinping Hu;B. Reese;S. Kinard;J. Kominoski;X. Lin;X. Lin;Zhanfei Liu;P. Montagna;S. Pennings;Lily M. Walker;C. Weaver;M. Wetz

A Research Framework to Integrate Cross-Ecosystem Responses to Tropical Cyclones

• DOI: 10.1093/biosci/biaa034
• 发表时间: 2020-06-01
• 期刊: BIOSCIENCE
• 影响因子: 10.1
• 作者: Hogan, J. Aaron;Feagin, Rusty A.;Patrick, Christopher J.
• 通讯作者: Patrick, Christopher J.