Viral Lysogeny as a Potential Mechanism for Termination of a Red Tide Event

Abstract:

Red tides are high-biomass blooms in the coastal ocean typically caused by dinoflagellates. While some red tides are harmful (via toxin production, high biomass, and oxygen depletion during decay), they also provide an important source of energy and carbon for other trophic levels. Red tides are often ephemeral, so while it is easy to identify one, what causes these events to terminate can vary. It has been hypothesized that viral lysis and parasitic infection may be important vectors of termination for these blooms. This study sought to compare the decay of one such bloom in Monterey Bay, California to in situ and mesocosm studies where bloom termination was due to viral lysis. To achieve this goal we used MODIS ocean color Level 2 data with spatial resolution of 1km; we identified and averaged R_RS from 9 pixels within the northern "red tide incubator” region of Monterey Bay where a dinoflagellate bloom was identified. We applied the quasi-analytical algorithm (QAA) to derive the backscatter coefficient (b_bp(λ)), absorption due to chlorophyll (a_Chl), and the gelbstoff absorption coefficient (a_g). Separate equations were used to find the volume scattering function (β(ψ,λ) where ψ =140°) and the particle size distribution hyperbolic slope (ξ). A MODIS satellite time series of five days (during an eight-day period) confirmed optical changes similar to documented shifts in laboratory-controlled experiments examining viral lysis. As predicted from previous results, the decrease in chlorophyll – essentially the deterioration of the algal bloom – resulted in the anticipated decrease in b_bp(λ) and VSF values as well as an increase in ξ. a_Chl and a_g were also compared to the Morel 2009 band algorithm for Colored Dissolved Organic Matter (CDOM) and the OC3 band algorithm for chlorophyll concentration. Results indicate that the QAA retrievals cannot be statistically distinguished (using a paired t-test) from the Morel and OC3 band algorithms. Analyzing more bloom events would refine this method’s results and would provide the potential to determine how a bloom is terminated – e.g. by viral lysis, parasitic infection, or nutrient depletion. This could in turn lead to a better understanding of bloom termination generally, perhaps leading to improved mitigation efforts for red tides and harmful algal blooms.