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.

虽然自然通常变化缓慢，但有时大的变化发生得很快。渔业崩溃，牧场减少，入侵物种迅速扩张，往往给人类社会带来高昂的代价。生态系统的巨大变化是难以预测的，但最近的理论研究和实验表明，在这些变化之前会有早期预警。这些早期预警就像经济指标，可以在可以经常测量的环境变量中发现。原则上，当检测到早期预警指标时，行动可以避免不必要的变化，比如对汽车的检查引擎灯做出反应，或者帮助降低风险，比如对龙卷风警报做出反应。该项目将通过检测早期预警信号来测试避免湖泊不必要变化的可能性。几个湖泊将被试验性地施肥，以创造藻类大量生长的潜力。早期预警信号将通过使用现代电子传感器持续监测湖泊来检测。在进一步的实验中，研究人员将对指示即将发生变化的信号做出反应，并停止向一个湖泊添加营养物质，以避免藻类繁殖到令人讨厌的水平。对其他湖泊的处理将继续进行，以便包括所有可能的应对措施。这个项目将确定是否可以开发探测早期预警信号的方法。这项研究的结果将扩展到一个已经在世界各地的湖泊上建立了连续测量系统的研究人员网络。如果成功，其结果将广泛适用于一系列自然系统的管理，而不仅仅是湖泊。该项目将培训研究生和本科生，并为弗吉尼亚州和威斯康星州的大学以及纽约加里生态系统研究所的高级专题课程提供教材。