Tuesday, August 8, 2017: 2:50 PM
Portland Blrm 256, Oregon Convention Center
Ecosystem regime shifts are abrupt changes from one dynamical state to another, such as the shift from a clear-water state to an algal bloom state in lakes. These transitions are hard to forecast but theory suggests early warning indicators can predict impending regime shifts which may allow for management intervention to prevent or mitigate an unwanted change. The efficacy of early warning indicators has been demonstrated in modeling and laboratory experiments, but rarely in the field where environmental drivers are numerous and interacting. It is unclear if early warning indicators are observable or timely enough to allow for intervention under these conditions. We performed six whole-lake experimental nutrient additions to test the utility of early warning indicators for predicting the regime shift from a clear-water state to a cyanobacterial-dominated state. The lakes were monitored for increases in resilience indicators including rises in standard deviation and autocorrelation of algal pigments and dissolved oxygen saturation. A statistical method, quickest detection, determined when resilience indicators in manipulated lakes deviated substantially from those in a reference ecosystem.
Results/Conclusions: Blooms occurred in five of the six lake-years. Although there was substantial variability in bloom size and timing, at least one indicator foreshadowed the peak chlorophyll a concentration in all but one instance. The number of early warning signals increased with the magnitude of the subsequent bloom. Early warnings occurred 1-61 days prior to a bloom which in some instances may allow managers to notify the public or intervene to prevent blooms. The resilience indicators correctly identified changes in resilience over time within a lake and also correctly ranked differences in resilience among lakes. Our findings suggest that resilience indicators can be used to classify ecosystems on a landscape and across time with respect to proximity to a critical threshold.