Abstract

The phytoplankton size class (PSC) plays an important role in biogeochemical processes in the ocean. In this study, a regional model of PSCs is proposed to retrieve vertical PSCs from the total minus water absorption coefficient (at-w(λ)) and Chlorophyll a concentration (Chla). The PSC model is developed by first reconstructing phytoplankton absorption and Chla from at-w(λ), and then extracting PSC from them using the support vector machine (SVM). In situ bio-optical data collected in the South China Sea from 2006 to 2013 were used to train the SVM. The proposed PSC model was subsequently validated using an independent PSC dataset from the Northeast South China Sea Cruise in 2015. The results indicate that the PSC model performed better than the three components model, with a value of r2 between 0.35 and 0.66, and the absolute percentage difference between 56% and 181%. On the whole, our PSC model shows a remarkable utility in terms of inferring vertical PSCs from the South China Sea.

Highlights

  • Marine phytoplankton contribute approximately 40%–50% of the total primary production on Earth, and modulates the exchange of CO2 gas between the air and the sea [1,2,3]

  • Figure 7j–l shows scatters of phytoplankton size class (PSC) retrieved from support vector machine (SVM)-Bricaud95

  • Scatters of the PSCs (Cm, Cn, and Cp) retrieved from SVM-Type2 against measurements for the training and test datasets were generally close to the 1:1 line in terms of r2 from 0.58 to 0.9, with APD values ranging from 26.99% to 50.14%

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Summary

Introduction

Marine phytoplankton contribute approximately 40%–50% of the total primary production on Earth, and modulates the exchange of CO2 gas between the air and the sea [1,2,3]. The nutrient uptake and cycles, energy transfer through the marine food web, the rate of photosynthesis, deep-ocean carbon export, and gas exchange with the atmosphere are directly or indirectly related to the size of phytoplankton [5,6,7,8,9]. The phytoplankton size class (PSC) method involves partitioning the autotrophic pool into groups of different sizes, i.e., pico-plankton (20 μm) [10]. This classification can effectively distinguish their functional types in biogeochemical processes

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