基于浮游植物吸收系数和光合有效辐射的南海区域性分粒级初级生产力算法初探

doi:10.11978/2022019

Abstract

Abstract:

Marine primary production is an important part of the ocean carbon cycle, affecting biogeochemical cycles and global climate change. Phytoplankton, as the main contributor to marine primary production, can be classified as micro- (>20μm), nano- (2~20μm), and pico- (<2μm) phytoplankton depending on particle size. Different phytoplankton size classes contribute differently to primary production (PP_size) and thus play different roles in the oceanic circulation of matter or energy and ocean carbon cycle. Based on the bio-optical dataset collected at 12 stations in the western South China Sea in 2019, this study presented the spatial variability of size-fractionated primary production and chlorophyll a concentration of phytoplankton and their percentage contribution. The size-fractionated primary productivity of phytoplankton was well estimated from the product of size-fractionated phytoplankton absorption coefficient at 670nm [a_ph-size(670)] and photosynthetically active radiation (PAR) [a_ph-size(670)×PAR]. The coefficients of determination R² between log[a_ph-size(670)×PAR] and log(PP_size) were 0.64, 0.76, and 0.67 for the micro-, nano-, and pico-phytoplankton dataset, respectively. The cross-validation of the algorithm based on the size-fractionated phytoplankton absorption coefficient and PAR has shown a good generalization performance. This algorithm could better predict the size-fractionated primary productivity compared to the size-fractionated phytoplankton absorption coefficient as the only input. This result indicates that PAR is one of the important factors to estimate the size-fractionated primary productivity. Meanwhile, the performance of the chlorophyll a concentration-based algorithm for estimating primary productivity at each size was closer to that of the algorithm constructed in this paper for both micro- and pico- phytoplankton dataset, but significantly lower for the nano-phytoplankton, probably due to the weak correlation between the absorption coefficients and chlorophyll a concentration of nano-phytoplankton.

Key words: size-fractionated phytoplankton absorption coefficient, size-fractionated primary production, photosynthetically active radiation, size-fractionated chlorophyll a

ZHAO Hongwuyi, ZHOU Wen, ZENG Kai, DENG Lin, LIAO Jianzu, CAO Wenxi. A study of the regional size-fractionated primary production algorithm based on phytoplankton absorption coefficient and photosynthetically active radiation in the South China Sea[J].Journal of Tropical Oceanography, 2023, 42(1): 43-55.

Figures/Tables 11

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References 68

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初级生产力算法类型	公式	参量意义
基于浮游植物叶绿素a浓度	PP=Chl a×Q×R/K	PP为浮游植物初级生产力; Chl a为浮游植物叶绿素a浓度; Q为在光饱和情况下, 单位时间内单位质量叶绿素a同化的碳量; R是相对光合速率, 随海表光照强度变化; K是每米水层消光系数
基于浮游植物吸收系数	PP=ϕ×a_ph×E	PP为浮游植物初级生产力; a_ph为浮游植物吸收系数; ϕ为光合作用光量子产率; E为光照强度
基于浮游植物碳	PP=C×μ×Z_eu×f(I₀)	PP为浮游植物初级生产力; C为浮游植物碳; μ为生长速率; Z_eu为真光层深度; f(I₀)是表面光强的函数, 描述了固碳速率的剖面分布

	PAR衰减百分比	近岸珠江口海域						外海海域
		micro占比/%		nano占比/%		pico占比/%		micro占比/%		nano占比/%		pico占比/%
		均值±$\sigma$	范围	均值±$\sigma$	范围	均值±$\sigma$	范围	均值±$\sigma$	范围	均值±$\sigma$	范围	均值±$\sigma$	范围
初级生产力	0%	36±2	19~51	31±0.4	20~42	33±1	18~52	6±0.05	2~8	28±0.6	23~41	67±0.7	54~74
	44%	21±0.4	15~28	30±2	16~37	49±3	35~69	3±0.006	2~4	20±0.2	14~28	77±0.3	68~83
	78%	25±3	3~38	25±1	11~39	50±5	22~86	3±0.01	1~5	15±0.1	13~21	82±0.1	76~84
	93%	16±2	2~36	20±1	9~33	63±6	31~89	18±2	2~41	22±2	8~40	60±9	19~90
	99%	21±1	9~42	30±1	19~48	48±1	38~69	18±1	9~38	27±2	15~50	55±5	29~75
叶绿素a	0%	74±1	58~88	11±0.1	7~16	16±0.8	5~28	11±0.03	8~13	23±0.2	18~28	66±0.4	60~73
	44%	57±2	50~71	16±0.2	12~20	26±0.7	17~33	10±0.008	9~11	23±0.06	20~26	67±0.1	63~71
	78%	55±1	17~84	18±0.9	7~30	27±3	9~54	11±0.02	9~12	24±0.03	23~26	65±0.1	62~69
	93%	53±10	13~92	21±2	1~42	26±3	7~45	32±4	17~64	31±0.2	22~34	37±3	14~50
	99%	57±7	28~91	19±2	2~34	24±3	6~47	39±3	19~61	29±0.2	23~34	32±2	16~50

参与建模的波段	回归参数和评价指标	micro	nano	pico
443nm	$\quad\textit{R}^2_{443}$	0.57	0.72	0.66
	k₄₄₃	0.69	0.56	0.59
	b₄₄₃	-2.8	-3.1	-3.0
670nm	$\quad\textit{R}^2_{670}$	0.64	0.76	0.67
	k₆₇₀	0.72	0.57	0.60
	b₆₇₀	-2.4	-2.8	-2.6
线性拟合最高R²及对应的k、b	$\quad\textit{R}^2_{max}$	0.65(667nm)	0.78(688nm)	0.68(684nm)
	k_max	0.73(667nm)	0.59(688nm)	0.58(684nm)
	b_max	-2.4(667nm)	-2.6(688nm)	-2.6(684nm)

A study of the regional size-fractionated primary production algorithm based on phytoplankton absorption coefficient and photosynthetically active radiation in the South China Sea

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算法	micro			nano			pico
算法	R²	RMSE	N	R²	RMSE	N	R²	RMSE	N
$\log(\mathrm{PP})=k\log\left[a_{\mathrm{bh}}(\lambda_0)\times\mathrm{PAR}\right]+b$	0.64	0.61	25	0.76	0.43	28	0.67	0.42	47
$\log(\mathrm{PP})=k\log\left[a_{\mathrm{bh}}(\lambda_0)\times\mathrm{PAR}\right]+b$	0.54	0.69	25	0.58	0.56	28	0.14	0.67	47
$\log(\mathrm{PP}_2)=k_2\log(\mathrm{Chl}a\times\mathrm{PAR})+b_2$	0.69	0.56	25	0.50	0.61	28	0.65	0.43	47