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（例如主要飓风）中改变和恢复，这对于帮助社会有效地应对这些事件非常重要。天然系统（如溪流）可以提供缓冲，以减轻风暴的影响并加快使人类受益的自然过程的恢复。 这项研究旨在了解德克萨斯州墨西哥湾沿岸的溪流如何应对洪水和强风，在飓风哈维于2017年8月登陆后。大量的降雨和相关的风暴潮可能会改变居住在附近溪流中的生物的数量和种类。 尽管预计溪流中的微生物，动植物的“社区”，但预计随着时间的流逝，它也将恢复到预先发展状态。 恢复的时间被认为在流之间以及各种生物之间的可预测方式上有所不同。 为了测试这个想法，有必要在风暴之前和之后都有数据流，物理流特征和社区组成的数据。 该奖项支持的研究人员在哈维在南德克萨斯州的登陆之前制定并实施了一项流监测计划。 该奖项将使研究人员能够在暴风雨后和预期的恢复期内立即收集数据。 他们将探索恢复期是否取决于流在典型潮湿还是通常干燥的区域中。该项目的结果将帮助城市规划师和自然资源经理了解流对飓风的反应。 此外，该研究将直接支持教师培训各种各样的当地科学家和经理，他们可以帮助其社区对未来的飓风做出有效反应。 该项目解决了气候制度如何调节社区对干扰的反应。具体而言，它测试了关于哪些生物群落和相关的生态系统过程对与气候相关的障碍有弹性最高的预测。 这些预测提供了障碍理论的重要检验，并且与预测气候变化的生态影响具有很大相关性。一个重大干扰事件，哈维飓风，影响了一个从半干旱到亚游的急剧气候梯度的地区。研究团队，包括西班牙裔服务机构的教职员工和学生，将在气候梯度上使用一系列的流生态系统，并将其带有统计的社区和生态系统数据作为模型系统。在每个流中，研究团队将对社区（例如，微生物，无脊椎动物），生态系统组件（营养，底栖藻类，有机物，栖息地）进行高频重复调查，并使用自动伐木工（DO，光，光，温度，排放，排放，depth）收集连续的高频数据。这些数据将跟踪社区构图，基础资源和生态系统过程的时间变化，这些过程共同提供了对干扰的直接响应和长期影响的衡量。预计在非生物条件下具有更大随机性的更干燥系统中，社区对干扰的抵抗力将更高。 同样，预计年度降水量越高且河岸植被越高的社区将会受到有机物投入以及光线和初级生产增加的积极反应。这些一般的功能响应的速率将随着生成时间的函数而变化。

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.