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Human activities and natural processes like mixing and/or upwelling driven by climate change have a strong influence on water quality in the coastal regions. Human activities are the dominant factor for water quality in the mouth of the Sanya River. This region exhibited the maximum influence of discharge from the Saya estimated by higher nutrient levels and chlorophyll a (Chl a). Natural processes are the dominant factor regarding water quality in outer bay. Both human activities and natural processes play important roles on water quality in Sanya Bay. Each hydrologic and ecological zone has a specific water quality response associated with the relative importance of both human activities and natural processes. Therefore, the information would be useful for regional agencies in developing a strategy to carry out scientific plans for resource use based on marine system functions. [ABSTRACT FROM AUTHOR]

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Regional climate models used to resolve high-resolution local circulation by dynamically downscaling from a coarse-resolution analysis may have difficulty in keeping large-scale information the same as in the analysis. Such difficulty produces large-scale error or bias, mainly due to mathematically ill-posed lateral boundary conditions. To reduce this type of error, in this paper the authors propose a scheme called local mean bias correction (LMBC). LMBC has means in x and in y directions locally over the model domain, but not a single mean over the entire domain. In spectral space, local means are represented by the zero wavenumber in the x direction with all wavenumbers in the y direction, and the zero wavenumber in the y direction with all the wavenumbers in the x direction. The local mean perturbation can be removed to correct the local mean bias where the perturbation is defined as the difference between a regional field and a base field from the analysis. The LMBC constitutes a simple methodology to ameliorate the influence of the lateral boundary conditions (LBCs) on the integration of the regional climate model (RCM); using it in this study improved the regional climate simulation of the 1998 South China Sea (SCS) summer monsoon. Generally speaking, this scheme proved to have a well-simulated circulation during all periods of monsoon activities examined. Circulation errors during the SCS summer monsoon onset can be corrected using this LMBC scheme, though the rainfall amount was always underestimated as compared to the observation. This research demonstrated that shifting the domain north, east, west, and south as well as enlarging domain size produced results that are consistent in different cases over different years. [ABSTRACT FROM AUTHOR]

Vertical variations of bacterial community composition in the South China Sea was investigated on 18 September 2009 by denaturing gradient gel electrophoresis (DGGE) and analyzed by multivariate analysis. Twenty-seven sequences retrieved from DGGE bands fell into five groups based on BLAST analysis. The dominant bacteria were Cyanobacteria (35.7%) and Proteobacteria (39.2%). The DGGE profile showed Proteobacteria mostly obtained from samples from the deeper layers while sequences related to Cyanobacteria only existed in the euphotic layer. Other phylogenetic groups have been identi?ed as Firmicutes (10.7%), Actinobacteria (7.1%), and Deinococcus-Thermus (3.6%). The unweighted pair group method with arithmetic mean has been employed to cluster the samples, and results indicated that all samples tended to group together on the basis of depth and could be further subclassified into two subgroups: Group I (including samples from 0 m, 50 m, 75 m, 100 m, and 150 m) and Group II (including samples from 200 m, 400 m, 500 m, 600 m, 700 m, and 900 m). Canonical correspondence analysis revealed the temperature was the most significant factor in determining the vertical distribution of the bacterial community (P=0.018, P<0.05). [ABSTRACT FROM AUTHOR]