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A Mechanism Coupling Sewage Effluent to the Dark Survival of the Toxic Diatom Pseudo-nitzschia sp. and Subsequent Initiation of Toxic Blooms by Coastal Upwelling

Abstract

Toxic diatom blooms of Pseudonitzschia spp. are becoming a severe threat to the California coastal ecosystem and fishery. Generally, eutrophication is considered the likely cause for the "worldwide epidemic" of increased frequency and severity of harmful algal blooms (Smayda, 1990). However, for the domoic acid producing Pseudonitzschia blooms the link is less clear. In order to mitigate these blooms and associated financial loss to fisheries environmental triggers for Pseudonitzschia blooms need to be identified. Based on current knowledge, a model has emerged that would predict a Pseudonitzschia bloom to emerge after the upwelling of a seed population from the deep ocean. The model also predicts that Pseudonitzschia survives near the bottom due to its capability of taking up organic nutrients, which would be enhanced by eutrophication. My research intends to supplement research currently funded by the Coastal Environmental Quality Initiative, to test the following hypothesis aiming at validating this model:

I. Pseudonitzschia is capable of adapting to an extreme light shift, such as associated with an upwelling event from dim light near the bottom to high light at the surface.

II. Pseudonitzschia survival and viability in the dark near the bottom is enhanced due to eutrophication.

While upwelling of seed populations is a natural phenomenon over which state agencies have no control, eutrophication via runoff and sewage outfall can and is being managed by state agencies. If my experiments support the physical/biological coupling of upwelling and sewage effluent as a mechanism driving the initiation of Pseudonitzschia blooms, monitoring programs need to expand to include sampling of the phytoplankton community near the bottom, particularly near areas of sewage and wastewater discharge. Together with results from two Coastal Environmental Quality Initiatives underway, validation of this model will improve the predictability of location and timing of such harmful blooms in the future.

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