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Remote Sensing Assessment of Marine Primary Productivity and Fishery Resources in the Daya Bay, China

Remote Sensing Assessment of Marine Primary Productivity and Fishery Resources in the Daya Bay, China

Jing Yu1*, Jiangmei Mao1,2 and Dongliang Wang1,3

1South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences; Guangdong Provincial Key Laboratory of Fishery Ecology and Environment; China Scientific Observing and Experimental Station of South China Sea Fishery Resources and Environment, Ministry of Agriculture and Rural Affairs; Guangzhou 510300, PR China
2Nanjing Agricultural University, Academy of Science; Plant Phenomics Research Centre, Nanjing 210095, PR China
3College of Marine Science, Shanghai Ocean University, Shanghai 201306, PR China

*      Corresponding author:


Marine primary productivity (PP) is closely related with fishery resources. This study benefited a lot by providing the reference for the use of remote sensing data to inverse PP and then to assess fishery resources in typical offshore fishery waters. The paper adopted the inversion analysis of the primary productivity (PP) in the Daya Bay, China applying the vertical generalized production model (VGPM) with ocean color and sea surface temperature (SST) provided by MODIS-Aqua. On the basis of modified VGPM model, fishery resources in the Daya Bay were evaluated according to the Tait model, Cushing model, and trophic dynamics model. Results showed that the seasonal variation of PP was obvious in the bay, the average PP reached the highest in summer (1595.60 mg C·m-2·d-1) and the second in autumn (1274.67 mg C·m-2·d-1). The space distribution of PP decreased gradually from nearshore (greater than 1000 mg C·m-2·d-1) to offshore and outside (800~1000 mg C·m-2·d-1) of the bay. As one of the most significant influencing factors to PP, chlorophyll a (Chl-a) showed similar characteristics of spatiotemporal distribution. Comparing results of different estimation models, it was found that density of fishery resources assessed by Cushing model matched well with the in-situ investigation data of fishery resources. Marine primary productivity and fishery resources in the Daya Bay were mainly influenced by Chl-a distribution, cage culture and petrochemical sewage (Liu, 2011).

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Pakistan Journal of Zoology


Vol. 54, Iss. 5, Pages 2003-2500


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