Algal blooms, the rapid proliferation of algal biomass often to nuisance or harmful levels, diminish aquatic ecosystem services. As such, understanding both the long-term trajectories and short-term dynamics of blooms provides critical information for protecting ecosystem and human health.
Over the past decades, the interaction between eutrophication and climate change has been hypothesized to drive widespread intensification of blooms in inland waters, although there is little empirical evidence that this trend is pervasive.
An evaluation of decadal time series of chlorophyll-a in over 300 U.S. lakes revealed that bloom intensification has not been widespread. Instead, we found that the complex interactions among local and regional processes are shaping the trajectory of algal biomass in lakes.
While it is encouraging that bloom intensification does not appear to currently be widespread in this region, individual lakes still experience severe blooms on an annual basis. The transition from a clear-water state to an algal-dominated state is theoretically preceded by statistical indicators of a change in resilience.
We tested the hypothesis that resilience indicators could be used as an early warning system to predict blooms using a suite of whole-lake experiments and “real world” monitoring. These experiments suggested that resilience indicators are effective early warnings of declining resilience preceding strong blooms while weak changes gave more ambiguous signals.
Using new mathematical tools, we are now exploring how increasing dissolved organic carbon and nutrient loading, due to a combination of human activities in the watershed and climate change, alter ecosystem resilience to blooms.