On the Spatial and Temporal Variations of Primary Production in the South China Sea
Luping Song, Zhongping Lee, Shaoling Shang, Bangqin Huang, Jinghui Wu, Zelun Wu, Wenfang Lu, Xin Liu
Abstract
Primary production (PP) of the South China Sea (SCS) basin area (waters depth deeper than 200 m) is estimated using satellite products, with an overarching goal to reliably characterize the spatial distribution and temporal variation of PP of this important marginal sea. Among the PP models used, the absorption-based model (AbPM) showed better performance ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R^{2}=0.47$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N =39$ </tex-math></inline-formula> ). In comparison, the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> value is 0.26 for a chlorophyll-based model [vertically generalized production model (VGPM)] and 0.15 for the carbon-based model (CbPM). Furthermore, we observed that the PP spatial patterns obtained from these models were similar but disagree on the annual PP magnitude, where VGPM and CbPM, respectively, obtained <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim $ </tex-math></inline-formula> 50% lower and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim $ </tex-math></inline-formula> 40% higher annual PP compared to that obtained by AbPM. In particular, after analysis using empirical orthogonal functions (EOFs), the upwelling-induced high PP off Luzon (winter) and Vietnam coast (summer) was clearly reflected in the first EOF mode of the AbPM results, and its principal component 1 has shown a decreasing trend for the period of 2003–2019 (−15.0% yr <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{-1}$ </tex-math></inline-formula> for winter, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p < 0.05$ </tex-math></inline-formula> ; −14.7% yr <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$^{-1}$ </tex-math></inline-formula> for summer, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p < 0.05$ </tex-math></inline-formula> ), which reflects the impact of weakening wind and higher sea surface temperature in the SCS. For the results of VGPM and CbPM, however, no strong relationships were found with the main regional oceanographic features. These results suggested that the spatiotemporal variations of SCS PP obtained from AbPM are more reasonable and further highlight the importance of a robust model in reliably capturing large-scale spatiotemporal dynamics of PP in marine environments.