Collaborative Research: Whole Ecosystem Experiments on Early Warnings for Regime Shifts to Cyanobacteria in Lakes

合作研究：湖泊蓝藻政权转变早期预警的全生态系统实验

• 批准号: 1144683
• 负责人: Stephen Carpenter
• 金额: $ 44.01万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-02-01 至 2017-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1144683&HistoricalAwards=false
• 关键词: Collaborative; Research; Whole; Ecosystem; Experiments

While nature often changes slowly, sometimes large changes occur fast. Fisheries collapse, rangelands decline, and invasive species expand rapidly often with high costs to human society. Big changes in ecological systems are difficult to forecast but recent theoretical studies and experiments indicate that they are preceded by early warnings. These early warnings are like economic indicators and can be detected in environmental variables that can be measured frequently. In principle when early warning indicators are detected actions can either avert unwanted changes, like responding to a check engine light in a car, or help minimize risk, like responding to a tornado siren. This project will test the potential to avoid unwanted changes in lakes by detecting early warning signals. Several lakes will be experimentally fertilized with nutrients to create the potential for massive growths of algae. Early warning signals will be detected by continuously monitoring the lakes with modern electronic sensors. In a further experiment, the researchers will respond to signals that indicate impending changes and stop the nutrient additions to one lake in an attempt to avoid algae proliferating to nuisance levels. Treatments to the other lakes will continue so that all possible responses are included.This project will determine if methods for detecting early warnings signals can be developed. The findings from this study will be extended to a network of researchers who have established continuous measurement systems on lakes throughout the world. If successful, the results should be widely applicable for the management of a range of natural systems, not only lakes. The project will train graduate and undergraduate students and contribute to teaching materials for courses at universities in Virginia and Wisconsin, as well as advanced special topics courses at the Cary Institute of Ecosystem Studies in New York.

虽然自然常常变化缓慢，但有时发生较大的变化很快。 渔业崩溃，牧场下降，入侵物种经常迅速扩展，人类社会成本很高。 生态系统的重大变化很难预测，但是最近的理论研究和实验表明它们在早期警告之前。 这些早期警告就像经济指标一样，可以在可以经常衡量的环境变量中检测到。 原则上，当检测到预警指标时，操作可以避免有害的变化，例如对汽车中的检查引擎响应，或者有助于降低风险，例如对龙卷风警报器做出响应。 该项目将通过检测预警信号来避免湖泊的不必要变化的潜力。 几个湖泊将在实验中用营养物质受精，以创造大量藻类生长的潜力。 通过连续用现代电子传感器监视湖泊，将检测到预警信号。 在进一步的实验中，研究人员将响应表明即将发生变化的信号，并阻止一个湖中的营养成分，以避免藻类增殖到滋扰水平。对其他湖泊的治疗将继续，以便包括所有可能的反应。该项目将确定是否可以开发用于检测早期警告信号的方法。这项研究的发现将扩展到一个研究人员网络，这些研究人员已经建立了对全球湖泊的连续测量系统。如果成功，结果应广泛适用于一系列自然系统的管理，不仅是湖泊。 该项目将培训毕业生和本科生，并为弗吉尼亚州和威斯康星大学大学的课程以及纽约Cary生态系统研究所的高级特殊主题课程做出贡献。