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. 2025 Nov 29;16(1):472.
doi: 10.1038/s41598-025-29815-4.

Integrated photovoltaic-agriculture systems enhance soil health in desert ecosystems: evidence from microbial biomass and nutrient synergies

Mingjie Ma  1 , Fan Yang  2 , Xiannian Zheng  3 , Xinghua Yang  4 , Ali Mamtimin  1 , Chenglong Zhou  1 , Chaofan Li  5 , Wen Huo  1 , Xinqian Zheng  6 , Tianhe Wang  7 , Peng He  8 , Qing Gong  9
Affiliations

Integrated photovoltaic-agriculture systems enhance soil health in desert ecosystems: evidence from microbial biomass and nutrient synergies

Mingjie Ma et al. Sci Rep. .

Abstract

This study systematically evaluated the effects of three typical desert restoration models in the Hobq Desert-the integrated photovoltaic-agriculture model (PV-Ag), the artificial shrub aerial seeding model (ASS), and the bare sand with photovoltaic panels model (BS-PV)-on soil physicochemical properties, microbial characteristics, and vegetation recovery. The results indicated that the PV-Ag model performed most prominently in improving soil structure, increasing nutrient content, and enhancing microbial activity. The fine particle content in the soil reached 92.9%, while organic matter and total nitrogen content increased by 388.9-544.4% and 476.7-551.8%, respectively, compared to those in shifting sand dune (LS). Under PV-Ag model, the total soil microbial count increased more than 10 times, and microbial biomass carbon and nitrogen rose by 10.8-13.9 times and 13.4-17.1 times, respectively. The shade provided by photovoltaic panels in the PV-Ag model effectively optimized the soil hydrothermal environment, with humidity (0.043 m3/m3) and temperature (11.75 °C) being significantly better than those under the ASS and LS models, thereby promoting root biomass (1.8 g/kg) and the accumulation of available nitrogen and potassium (average increases of 188.7% and 258.5%). Correlation analysis revealed that species richness was significantly positively correlated with soil organic matter, total nitrogen, and microbial biomass carbon (r ≥ 0.96), and significantly negatively correlated with pH (r = - 0.95). Root biomass showed stronger correlations with total phosphorus, available phosphorus, and fungal abundance (r ≥ 0.80), indicating differentiated driving mechanisms of soil nutrients and microbial communities on vegetation restoration. The comprehensive soil quality index (SQI) evaluation demonstrated that the SQI value under the PV-Ag model was 810-1185 times higher than that of LS, significantly exceeding the values under the ASS (2.5-3.9 times) and BS-PV (11.3 times) models. The study demonstrates that the integrated photovoltaic-agriculture model can significantly improve desert soil quality and ecological function, offering an effective pathway for synergizing ecological restoration and renewable energy development in arid regions of the Hobq Desert.

Keywords: Desertification control; Hobq Desert; Photovoltaic-agriculture integration; Soil quality; Vegetation restoration.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests. Data availability: The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Figures

Fig. 1
Fig. 1
Location of the study area in the Hobq Desert and the vegetation communities corresponding to the three desertification control models.
Fig. 2
Fig. 2
Measurement of biomass and species richness.
Fig. 3
Fig. 3
Observation of soil temperature, moisture, and meteorological elements in different desertification control models (Left to Right: the integrated photovoltaic-agriculture model (PV-Ag), the artificial shrub aerial seeding model (ASS), the shifting sand dune (LS)).
Fig. 4
Fig. 4
Distribution of soil mechanical composition and nutrient elements in vegetation communities under three desertification control models.
Fig. 5
Fig. 5
Distribution of soil physical and chemical properties in vegetation communities under three desertification control models.
Fig. 6
Fig. 6
Distribution of soil total nutrient in vegetation communities under three desertification control models.
Fig. 7
Fig. 7
Distribution of soil microbial properties in vegetation communities under three desertification control models.
Fig. 8
Fig. 8
Distribution of soil microbial biomass carbon and nitrogen in vegetation communities under three desertification control models.
Fig. 9
Fig. 9
Correlation heatmap of soil physicochemical properties, microbial characteristics, and vegetation parameters under different desertification modes.
Fig. 10
Fig. 10
Distribution of soil moisture and temperature under different desertification control modes.
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