Photophysiological and light absorption properties of phytoplankton communities in the river‐dominated margin of the northern Gulf of Mexico

Spatial and temporal variability in photophysiological properties of phytoplankton were examined in relationship to phytoplankton community composition in the river‐dominated continental margin of the northern Gulf of Mexico (NGOM). Observations made during five research cruises in the NGOM included phytoplankton photosynthetic and optical properties and associated environmental conditions and phytoplankton community structure. Distinct patterns of spatial and temporal variability in photophysiological parameters were found for waters dominated by different phytoplankton groups. Photophysiological properties for locations associated with dominance by a particular group of phytoplankton showed evidence of photoacclimation as reflected by differences in light absorption and pigment characteristics in relationship to different light environments. The maximum rate of photosynthesis normalized to chlorophyll ( [Formula: see text]) was significantly higher for communities dominated (>60% biomass) by cyanobacteria + prochlorophyte (cyano + prochl). The initial slope of the photosynthesis‐irradiance (P‐E) curve normalized to chlorophyll ( [Formula: see text]) was not clearly related to phytoplankton community structure and no significant differences were found in [Formula: see text] and [Formula: see text] between different geographic regions. In contrast, maximum quantum yield of carbon fixation in photosynthesis (Φ(cmax)) differed significantly between regions and was higher for diatom‐dominated communities. Multiple linear regression models, specific for the different phytoplankton communities, using a combination of environmental and bio‐optical proxies as predictor variables showed considerable promise for estimation of the photophysiological parameters on a regional scale. Such an approach may be utilized to develop size class‐specific or phytoplankton group‐specific primary productivity models for the NGOM.