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Temporal and Spatial Dynamics of Phytoplankton Primary Production in Lake Taihu Derived from MODIS Data

Taihu Lake Laboratory Ecosystem Research Station, State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
College of Resources & Environment, GIS Research Center, Hunan Normal University, Changsha 410081, China
Author to whom correspondence should be addressed.
Academic Editors: Linhai Li, Claudia Giardino, Deepak R. Mishra, Xiaofeng Li and Prasad S. Thenkabail
Remote Sens. 2017, 9(3), 195;
Received: 24 November 2016 / Revised: 26 January 2017 / Accepted: 20 February 2017 / Published: 24 February 2017
(This article belongs to the Special Issue Water Optics and Water Colour Remote Sensing)
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We investigated the long-term variations in primary production in Lake Taihu using Moderate Resolution Imaging Spectroradiometer (MODIS) data, based on the Vertically Generalized Production Model (VGPM). We firstly test the applicability of VGPM in Lake Taihu by comparing the results between the model-derived and the in situ results, and the results showed that a strong significant correlation (R2 = 0.753, p < 0.001, n = 63). Then, VGPM was used to map temporal-spatial distributions of primary production in Lake Taihu. The annual mean daily primary production of Lake Taihu from 2003 to 2013 was 1094.06 ± 720.74 mg·C·m−2·d−1. Long-term primary production maps estimated from the MODIS data demonstrated marked temporal and spatial variations. Spatially, the primary production in bays, especially in Zhushan Bay and Meiliang Bay, was consistently higher than that in the open area of Lake Taihu, which was caused by chlorophyll-a concentrations resulting from high nutrient concentrations. Temporally, the seasonal variation of primary production from 2003 to 2013 was: summer > autumn > spring > winter, with significantly higher primary production found in summer and autumn than in winter (p < 0.005, t-test), primarily caused by seasonal variations in water temperature. On a monthly scale, the primary production exerts a clear character of bimodality, increasing from January to May, decreasing in June or July, and finally reaching its highest value during August or September. Wind is another important factor that could affect the spatial variations of primary production in the large, eutrophic and shallow Lake Taihu. View Full-Text
Keywords: primary production; VGPM model; Lake Taihu; carbon cycle; remote sensing estimation primary production; VGPM model; Lake Taihu; carbon cycle; remote sensing estimation

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Deng, Y.; Zhang, Y.; Li, D.; Shi, K.; Zhang, Y. Temporal and Spatial Dynamics of Phytoplankton Primary Production in Lake Taihu Derived from MODIS Data. Remote Sens. 2017, 9, 195.

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