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中国沙漠 ›› 2026, Vol. 46 ›› Issue (5): 126-135.DOI: 10.7522/j.issn.1000-694X.2026.00082

• • 上一篇    

新疆伊犁半干旱区光伏电站植被-土壤耦合特性

童永尚1(), 陈月芳1, 李政升1, 张生楹2, 李玉乐1, 牛克昌1,3, 巴雅尔塔1, 段沛琪1   

  1. 1.伊犁师范大学 生物科学与技术学院/新疆伊犁河谷资源植物保护与利用重点实验室,新疆 伊宁 835000
    2.尼勒克县草原工作站,新疆 尼勒克 835700
    3.南京大学 生命科学学院,江苏 南京 210023
  • 收稿日期:2026-03-20 修回日期:2026-05-14 出版日期:2026-09-20 发布日期:2026-11-02
  • 作者简介:童永尚(1996—),男,甘肃金昌人,博士,主要从事草地生态与环境保护研究。E-mail: tongys2022@126.com
  • 基金资助:
    国家自然科学基金项目(32560918);新疆领军人才引进计划重点高校引才项目(XJRC-2025-JY-YJ-GX-QNQZ-031)

Vegetation-soil coupling characteristics of photovoltaic power stations in the semi-arid region of Yili, Xinjiang, China

Yongshang Tong1(), Yuefang Chen1, Zhengsheng Li1, Shengying Zhang2, Yule Li1, Kechang Niu1,3, Bayarta1, Peiqi Duan1   

  1. 1.College of Biological Science and Technology/ Key Laboratory of Plant Resources Protection and Utilization in Xinjiang Yili Valley,Yili Normal University,Yining 835000,Xinjiang,China
    2.Grassland Workstation of Nilka County,Nilka 835700,Xinjiang,China
    3.School of Life Sciences,Nanjing University,Nanjing 210023,China
  • Received:2026-03-20 Revised:2026-05-14 Online:2026-09-20 Published:2026-11-02

摘要:

为解析半干旱区光伏开发对植被-土壤系统的影响机制,以新疆伊犁尼勒克县运行5年的光伏电站为研究对象,设置光伏板下、光伏板行间和光伏电站外3种微生境,测定植被群落特征与土壤理化指标,并结合冗余分析(RDA)、方差分解分析(VPA)及结构方程模型(SEM)探讨其耦合关系及驱动机制。结果表明:不同光伏微生境的植被与土壤指标差异显著,光伏板下土壤含水量、植被盖度及地上生物量最优,光伏板行间的植被高度和土壤速效养分更突出,光伏电站外物种丰富度最高。pH、电导率和土壤含水量是影响植被变化的关键土壤因子,土壤水分与速效养分对植被特征变异的联合解释率达52%。结构方程模型分析进一步表明,光伏环境主要通过调控土壤含水量和速效养分,间接影响植被盖度与地上生物量变化。

关键词: 伊犁, 半干旱区, 光伏电站, 光伏微生境, 植被-土壤耦合

Abstract:

To elucidate the mechanisms by which photovoltaic development affects the vegetation-soil system in the semi-arid Yili region of Xinjiang, a photovoltaic power station in Nilka County, Yili, Xinjiang, that has been in operation for five years was selected as the study site. Three microhabitats, namely beneath the photovoltaic panels, between the panel rows, and outside the photovoltaic station, were established for comparison. Vegetation community characteristics and soil physicochemical properties were measured, and their coupling relationships and driving mechanisms were further explored using redundancy analysis (RDA), variance partitioning analysis (VPA), and structural equation modeling (SEM). The results showed that vegetation and soil attributes differed significantly among the three photovoltaic microhabitats. Soil moisture content, vegetation cover, and aboveground biomass were highest beneath the photovoltaic panels, whereas vegetation height and soil available nutrients were more prominent between the panel rows. Species richness was highest outside the photovoltaic station. Soil pH, electrical conductivity, and soil moisture content were identified as the key soil factors affecting vegetation variation, and the joint explanatory power of soil moisture and available nutrients for vegetation characteristic variation reached 52%. Furthermore, the SEM results demonstrated that the photovoltaic environment indirectly influenced changes in vegetation cover and aboveground biomass primarily by regulating soil moisture and available nutrients. This study reveals the regulatory effects of photovoltaic microhabitats on the vegetation-soil system in the semi-arid Yili region and provides a scientific basis for ecological management and the coordinated development of energy production and ecosystem functions in photovoltaic power stations in this region.

Key words: Yili, semi-arid region, photovoltaic power plant, photovoltaic microhabitat, vegetation-soil coupling

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