Collaborative Research: Forecasting and forestalling tipping points in an aquatic ecosystem

合作研究：预测和预防水生生态系统的临界点

• 批准号: 1144056
• 负责人: Aaron Ellison
• 金额: $ 19.35万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1144056&HistoricalAwards=false
• 关键词: Collaborative; Research; Forecasting; forestalling; tipping

Identifying, forecasting, and managing state changes (also known as thresholds, tipping points, or regime shifts) are central challenges in many fields. Preventing stressed ecosystems from collapsing into altered states that do not provide useful ecosystem services is a major environmental challenge. This project will identify markers for, and potential means to manage, tipping points in aquatic ecosystems such as lakes, rivers, and streams. Nutrients will be added to aquatic microecosystems that form within water-filled leaves of northern pitcher plants in a series of experiments mimicking nutrient pollution and resultant ecosystem collapse seen in larger lakes. Critical thresholds, beyond which intervention cannot stop the breakdown of the system, will be identified. Quantitative methods will be used to identify protein biomarkers that can serve as early warning indicators of ecosystem collapse. Protein biomarkers are hypothesized to be better indicators than traditional ones such as oxygen levels or algal blooms, which reflect impending state changes too late to reverse them or after they have already occurred.Documenting, understanding, forecasting, and averting state changes is of widespread and immediate importance not only to ecologists and environmental scientists, but also to economists, social scientists, policy makers, and environmental managers. Nutrient enrichment from fertilizers, runoff, and atmospheric deposition can cause lakes, rivers, and streams to switch to dramatically different, low oxygen states characterized by algal blooms and fish die-offs. The most significant broader impact of the proposed research will be to provide empirical tests of regime shifts that will help to convince the broader public that scientists can detect and manage state changes. Future applications of this work could lead to the development of simple water-quality test kits that can forecast ecosystem tipping points early enough to prevent them. Resources will be devoted to educating K-12 teachers, undergraduate students and postdoctoral researchers through their continuous involvement in basic ecological research.

识别、预测和管理状态变化(也称为阈值、临界点或政权转变)是许多领域的核心挑战。防止受到压力的生态系统崩溃成为不提供有用生态系统服务的改变状态，是一项重大的环境挑战。该项目将确定湖泊、河流和溪流等水生生态系统中临界点的标志和潜在的管理手段。在一系列实验中，营养物质将被添加到水生微生态系统中，这些微生态系统形成于北方猪笼草充满水的叶子中，模拟营养物质污染和由此导致的生态系统崩溃，在更大的湖泊中出现。将确定关键门槛，超过这些门槛，干预无法阻止系统崩溃。将使用定量方法来确定可以作为生态系统崩溃早期预警指标的蛋白质生物标记物。蛋白质生物标志物被认为是比氧气水平或藻类水华等传统指标更好的指标，后者反映即将发生的状态变化太晚而无法逆转，或者已经发生。记录、理解、预测和避免状态变化不仅对生态学家和环境科学家具有广泛而直接的重要性，而且对经济学家、社会科学家、政策制定者和环境管理人员也具有广泛而直接的重要性。化肥、径流和大气沉积带来的营养丰富会导致湖泊、河流和溪流转变为截然不同的低氧状态，其特征是藻类大量繁殖和鱼类死亡。拟议中的这项研究最重要的更广泛的影响将是为政权更迭提供经验测试，这将有助于让更广泛的公众相信，科学家可以检测和管理国家的变化。这项工作的未来应用可能会导致开发简单的水质测试套件，可以及早预测生态系统临界点，以防止它们。资源将致力于通过不断参与基础生态研究来教育K-12教师、本科生和博士后研究人员。