Research Highlight

Photosynthetic parameters in the northern South China Sea in relation to phytoplankton community structure
Updated on£º2015-6-12      Visits£º1882

Title:

Xie, Y., B. Huang, L. Lin, E. A. Laws, L. Wang, S. Shang, T. Zhang, and M. Dai (2015), Photosynthetic parameters in the northern South China Sea in relation to phytoplankton community structure, J. Geophys. Res. Oceans, 120, doi:10.1002/2014JC010415.

Abstract:

Many recent models for retrieval of primary production in the sea from ocean-colour data are temperature-based. But previous studies in low latitudes have shown that models that include phytoplankton community structure can have improved predictive capability. In this study, we measured photosynthetic parameters from photosynthesis-irrandiance (P-E) experiments, phytoplankton absorption coefficients, and phytoplankton community structure derived from algal pigments during four cruises in the northern South China Sea. The maximum quantum yield of CO2 (ΦCm) and the chlorophyll a-normalized P-E curve light-limited slope (αB) varied significantly with the blue-to-red ratio of phytoplankton absorption peaks (aph(435)/aph(676)) (p < 0.001, r = -0.459 and -0.332, respectively). The unexplained variability could be due in part to the absorption associated with non-photosynthetic pigments. The chlorophyll a-normalized light-saturated photosynthesis rate (PBm) at the surface showed a unimodal distribution over the chlorophyll a range during the spring and summer, and significantly increased when Prochlorococcus was outcompeted by other pico-phytoplankton (p < 0.01). Almost 60% of the variance of PBm could be explained by a piecewise regression with phytoplankton absorption coefficients and pigment markers. Unlike previous studies, our data showed that changes of PBm were unrelated to the size structure of phytoplankton. Although a temperature-based approach could not effectively predict αB and PBm in the NSCS, a trophic-based approach can be used for assignment of these parameters in a regional primary production model using ocean-colour data.

Full text available at: http://dx.doi.org/10.1002/2014JC010415