Dynamic internal drivers of a historically severe cyanobacteria bloom in Lake Champlain revealed through comprehensive monitoring

Isles, P.D.F., Giles, C.D., Gearhart, T.A., Xu, Y., Druschel, G.K., & Schroth, A.W. (2015) Dynamic internal drivers of a historically severe cyanobacteria bloom in Lake Champlain revealed through comprehensive monitoring. Journal of Great Lakes Research, 41(3), 818-829. http://dx.doi.org/10.1016/j.jglr.2015.06.006.

The shallow bays of Lake Champlain have experienced increasingly severe algal blooms over recent decades, but the drivers of inter- and intra-annual variability of bloom severity are poorly understood. Disentangling the relative importance of multiple processes driving cyanobacteria blooms is difficult, in part because traditional monitoring programs often lack adequate temporal resolution, and in part because many studies seek to identify a single dominant mechanism. In this study, a holistic approach was used to identify multiple drivers of a strong cyanobacterial bloom over time in a shallow, eutrophic bay of Lake Champlain utilizing high-temporal-resolution meteorological, water quality, and biogeochemical sensor data; an intensive field sampling program; and a long-term monitoring dataset. In contrast to studies in similar systems, spring runoff and nutrient loads could not explain the severity of the 2012 bloom. Instead, internal nutrient loading and hydrodynamic conditions mediated shifts in resource limitation. The cyanobacteria growth phase was associated with the depletion of available nitrogen and sediment phosphorus release. The peak bloom stage was characterized by multiple limiting resources and stable water column conditions. The decline phase of the bloom was associated with light limitation brought about by wind mixing, and was punctuated by a major storm event, which brought a major biogeochemical shift in the lake system. This study illustrates the complexity of cyanobacteria resource limitation in response to internal and external forcing over time, and also the power of comprehensive monitoring approaches in disentangling complex drivers of eutrophic ecosystem function that vary across temporal and spatial scales.