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From Long-Term Data to Understanding: Toward a Predictive Ecology
2015 LTER ASM Estes Park, CO - August 30 - September 2, 2015

Spatial Variability in Phytoplankton Bloom Dynamics and Mechanism Throughout the Southern Ocean

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Tyler Rohr
Matt Long
Scott Doney

In light of the recently proposed ‘disturbance-recovery’ hypothesis, in model testing is combined with historic remote sensing observations to examine the effect of top down (grazing pressure) versus bottom up (growth conditions, i.e. light, nutrients) controls on phytoplankton ecosystem dynamics throughout the Southern Ocean.  A high-resolution daily mean output CESM run with a relatively high degree of biogeochemical complexity and recently improved quantification of photosynthesis under sea ice is used in conjunction with MODIS ocean color and particle backscattering observations to explore spatial variability in phytoplankton bloom phenology, magnitude, and mechanism. Variability in the relative timing and magnitude of events alongside correlations between interannual physical processes and ecosystem properties are used to identify ecologically distinct regions. Next, qualitative and quantitative offsets between population specific growth rates and cell specific division rates are studied in conjunction with an explicit analysis of in-model grazing rates and nutrient limitations to tease apart which biological, trophic and/or physical controlling mechanisms may dominate regionally and account for the observed variability in ecosystem dynamics. Results suggest that that the relative importance of any individual mechanism varies strongly in space. Specifically the open ocean and seasonally ice-covered regions in the South Pacific and South Atlantic are compared.  While deep winter mixing appears to serve as a trigger for bloom initiation in the open ocean south Pacific, partially relieved iron stress in the open ocean South Atlantic and seasonal ice coverage at higher latitude present more complicated systematics.  As climate driven alterations moderate the relevant physical processes understanding variability in their role controlling bloom dynamics will help provide predictive insight to how future phytoplankton ecosystems will respond to a changing climate.

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