Influence of large-scale photovoltaic development on carbon storage in an alpine desert grassland ecosystem

doi:10.17521/cjpe.2024.0465

Abstract

Abstract:

Aims Grassland ecosystems store large amounts of organic carbon. In recent years, the construction of large-scale photovoltaic (PV) power plants in grassland areas has dramatically altered the microclimate, vegetation, and soil characteristics of the grassland ecosystem, thereby affecting the carbon cycle. However, there is a lack of systematic research regarding the effects of PV development on vegetation and soil storage.

Methods To investigate the impact on the carbon stock of desertified grassland ecosystems, this study adopts a space-for-time substitution method to analyze the changing patterns of aboveground biomass carbon density, total soil carbon, organic carbon, readily oxidizable organic carbon stock, and other indices at the Tala Beach Photovoltaic Power Station in Republican County, Qinghai Province, considering different years of construction.

Important findings The results showed that: (1) under the PV panels, between the panels, and outside the station in the study area, the average total soil carbon storage were 118.83, 119.08, and 108.15 t·hm^-2, respectively; the organic carbon was 61.97, 61.29, and 58.14 t·hm^-2, respectively; the readily oxidizable organic carbon was 23.95, 25.21, 19.18 t·hm^-2; the aboveground biomass carbon density was 47.58, 43.69, 26.03 g·m^-2, respectively. Except for the organic carbon and readily oxidizable organic carbon storage under the panels, values of other indices under and between panels were significantly larger than those outside the station. (2) As the establishment time of the power station increased, the aboveground biomass carbon density of the vegetation increased at a rate of 6.91 and 10.01 m^-2·a^-1 under the panels and between the panels, respectively. There was a significant positive correlation between soil organic carbon and easily oxidized organic carbon stocks and the number of the establishment year of PV. (3) Above-ground biomass carbon density was mainly affected by the construction of PV and vegetation cover, and the construction of PV also affected the easily oxidized organic carbon stock the most. In conclusion, although the construction of PV did not significantly affect the total soil carbon storage in the short term, it significantly increased the aboveground biomass carbon density soil organic carbon and readily oxidizable organic carbon stock. In the future, the soil in the region will continue to function as a carbon sink as the establishment time of PV increases. Therefore, large-scale photovoltaic development has a positive effect on enhancing the carbon sequestration capacity of alpine desert grassland in China and achieving the goal of carbon neutrality.

Key words: photovoltaic ecological effects, soil carbon sequestration, desertified grasslands, grassland carbon stocks, carbon sinks

LIU Qiang, MA Hong-Yuan, PENG Yun-Feng, LA Ben, YE De-Li, ZHANG Jia-Chen, LAI Jun-Hua. Influence of large-scale photovoltaic development on carbon storage in an alpine desert grassland ecosystem[J]. Chin J Plant Ecol, 2025, 49(11): 1791-1804.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2024.0465

https://www.plant-ecology.com/EN/Y2025/V49/I11/1791

Figures/Tables 15

Fig. 1 Overview of the study area for photovoltaic power plants of different construction years in Talatan.

Table 1 Likelihood ratio test results for different mixed linear models

模型 Model	参数数量 Number of parameters	AIC	BIC	对数似然 Log-likelihood	偏差 Deviation	χ²	自由度 df	p
model_null	4	1 231.62	1 243.85	-611.81	1 223.62	NA	NA	NA
model_board	5	1 233.59	1 248.87	-611.79	1 223.59	0.03	1	0.860
model_depth	6	1 209.19	1 227.53	-598.59	1 197.19	26.40	1	<0.001
model_all	7	1 211.16	1 232.56	-598.58	1 197.16	0.03	1	0.871

Fig. 2 One-way ANOVA of aboveground biomass carbon density under the photovoltaic panels, between the panels, and outside the station. Different lowercase letters represent significant differences between sampling locations (p < 0.05).

Fig. 3 Difference of aboveground biomass carbon density under the photovoltaic panels, between the panels, and outside the station (A), and changes in the net aboveground biomass carbon density (mean ± SE) under the photovoltaic panels and between the panels after photovoltaic power station construction (B).

Fig. 4 One-way ANOVA of soil carbon stocks under the photovoltaic panels, between the panels, and outside the station. EOC, readily oxidizable organic carbon; SOC, organic carbon; TC, total carbon. Different lowercase letters represent significant differences between sampling locations (p < 0.05).

Fig. 5 Comparison of organic carbon stocks under the photovoltaic panels, between the panels, and outside the photovoltaic power station with different years of construction.

Table 2 Estimates of optimal mixed linear model parameters for soil organic carbon stock (SOC)

固定因子 Fixed factor	系数估计 Coefficient estimation	标准差 Standard deviation	自由度 df	t	p
截距 Intercept	0.539	3.198	49.697	0.169	0.867
光伏建成年数 Years after construction (a)	1.081	0.382	50.799	2.832	0.007^**
10-20 cm深度 Depth 10-20 cm	0.466	2.674	48.612	0.174	0.862
20-40 cm深度 Depth 20-40 cm	-12.959	2.683	49.168	-4.830	<0.001^***

Fig. 6 Comparison of easily oxidizable organic carbon stocks under the photovoltaic panels, between the panels, and outside the photovoltaic power station with different years of construction.

Table 3 Estimates of optimal mixed linear model parameters for readily oxidizable organic carbon stock (EOC)

固定因子 Fixed factor	系数估计 Coefficient estimation	标准差 Standard deviation	自由度 df	t	p
截距 Intercept	-8.915	3.907	45.12	-2.282	0.027^*
光伏建成年数 Years after construction (a)	2.384	0.476	48.88	5.011	<0.001^***
10-20 cm深度 Depth 10-20 cm	1.582	3.357	45.13	0.471	0.640
20-40 cm深度 Depth 20-40 cm	-4.163	3.323	45.85	-1.253	0.217

Fig. 7 Comparison of total carbon stocks under the photovoltaic panels, between the panels, and outside the photovoltaic power station with different years of construction.

Table 4 Estimates of optimal mixed linear model parameters for total carbon stock (TC)

固定因子 Fixed factor	系数估计 Coefficient estimation	标准差 Standard deviation	自由度 df	t	p
截距 Intercept	7.904	7.964	44.781	0.992	0.326
光伏建成年数 Years after construction (a)	0.922	0.938	45.854	0.984	0.331
10-20 cm深度 Depth 10-20 cm	0.349	5.618	42.610	0.062	0.951
20-40 cm深度 Depth 20-40 cm	7.747	5.697	44.849	1.360	0.181

Fig. 8 Structural equation model of drivers of aboveground biomass carbon density. Solid black lines represent significant positive impacts; dashed black lines represent significant negative impacts; solid gray lines represent non-significant positive impacts; and dashed gray lines represent non-significant negative impacts. *, p < 0.05; **, p < 0.01; ***, p < 0.001. AGBD, above ground biomass carbon density; C, Margalef richness index; D, Simpson dominance index; E, Pielou evenness index; H′, Shannon-Wiener diversity index; PV, photovoltaic power plant construction time; VEGOVC, vegetation coverage.

Fig. 9 Total effect values of the factors on the aboveground biomass carbon density in the structural equation model. AGBD, above ground biomass carbon density; C, Margalef richness index; D, Simpson dominance index; E, Pielou evenness index; H′, Shannon-Wiener diversity index; PV, photovoltaic power plant construction time; VEGOVC, vegetation coverage.

Fig. 10 Structural equation model of drivers of easily oxidizable organic carbon stock (EOC) in soils. AGBD, above ground biomass carbon density; BD, soil bulk density; DUL, field capacity; PV, power plant construction year; Sand, soil sand content; STK, soil total potassium content; STN, soil total nitrogen content; STP, soil total phosphorus content. Solid black lines represent significant positive impacts; dashed black lines represent significant negative impacts; solid gray lines represent non-significant positive impacts. *, p < 0.05; **, p < 0.01; ***, p < 0.001.

Fig. 11 Total effect values of the factors on readily oxidizable organic carbon stock (EOC) in soils in the structural equation model. AGBD, above ground biomass carbon density; BD, soil bulk density; DUL, field capacity; PV, power plant construction year; Sand, soil sand content; STK, soil total potassium content; STN, soil total nitrogen content; STP, soil total phosphorus content.

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