Regionalization and Dynamic Parameterization of Quantum Yield of Photosynthesis to Improve the Ocean Primary Production Estimates From Remote Sensing - Zoffoli, Maria Laura; Lee, Zhongping; Marra, John F. (Frontiers in Marine Science, 2018)
Quantum yield of photosynthesis (phi) expresses the efficiency of phytoplankton carbon fixation given certain amount of absorbed light. This photophysiological parameter is key to obtaining reliable estimates of primary production (PPsat) in the ocean based on remote sensing information. Several works have shown that phi changes temporally, vertically, and horizontally in the ocean. One of the primary factors ruling its variability is light intensity and thereby, it can be modeled as a function of Photosynthetically Available Radiation (PAR). We estimated phi utilizing long time-series collected in the North Subtropical Oligotrophic Gyres, at HOT and BATS stations (Pacific and Atlantic oceans, respectively). Subsequently the maximum quantum yield (phi_m) and K_phi (PAR value at half phi_m) were calculated. Median phi_m values were ~0.040 and 0.063 mol C mol photons-1 at HOT and BATS, respectively, with higher values in winter. K_phi values were ~8.0 and 10.8 mol photons m-2 d-1 for HOT and BATS, respectively. Seasonal variability in K_phi showed its peak in summer. Dynamical parameterizations for both regions are indicated by their temporal behaviors, where phi_m is related to temperature at BATS while K_phi to PAR, in both stations. At HOT, phi_m was weakly related to temperature and its median annual value was used for the whole data series. Differences in the study areas, even though both belong to Subtropical Gyres, reinforced the demand for regional parameterizations in PPsat models. Such parameterizations were finally included in a PPsat model based on phytoplankton absorption (PPsat-aphy-based), where results showed that the PPsat-aphy-based model coupled with dynamical parameterization improved PPsat estimates. Compared with PPsat estimates from the widely used VGPM, a model based on chlorophyll concentration (PPsat-chl-based), PPsat-aphy-based reduced model-measurements differences from ~62.8% to ~8.3% at HOT, along with well-matched seasonal cycle of PP (R2 = 0.76). There is not significant reduction in model-measurements differences between PPsat-chl-based and PPsat-aphy-based PP at BATS though (37.8% vs 36.4%), but much better agreement in seasonal cycles with PPsat-aphy-based (R2 increased from 0.34 to 0.71). Our results point to improved estimation of PP from satellite remote sensing by parameterized quantum yield along with phytoplankton absorption coefficient at the core.