生态与环境

基于地理探测器的宁夏草地植被覆被时空分异及驱动因子

  • 文妙霞 ,
  • 何学高 ,
  • 刘欢 ,
  • 张婧 ,
  • 罗晨 ,
  • 贾丰铭 ,
  • 王义贵 ,
  • 胡云云
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  • 国家林业和草原局西北调查规划院,旱区生态水文与灾害防治国家林业和草原局重点实验室,陕西 西安 710048
文妙霞(1971-),女,高级工程师,主要从事林草资源调查和监测工作. E-mail: 1943203393@qq.com

收稿日期: 2023-01-27

  修回日期: 2023-03-17

  网络出版日期: 2023-08-24

基金资助

国家林业和草原局计划项目“黄河流域林草生态资源专题监测技术研究”(LC-2-02)

Analysis of the spatiotemporal variation characteristics and driving factors of grassland vegetation cover in Ningxia based on geographical detectors

  • Miaoxia WEN ,
  • Xuegao HE ,
  • Huan LIU ,
  • Jing ZHANG ,
  • Chen LUO ,
  • Fengming JIA ,
  • Yigui WANG ,
  • Yunyun HU
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  • Northwest Surveying and Planning Institute of National Forestry and Grassland Administration, Key Laboratory of National Forestry and Grassland Administration on Ecological Hydrology and Disaster Prevention in Arid Regions, Xi’an 710048, Shaanxi, China

Received date: 2023-01-27

  Revised date: 2023-03-17

  Online published: 2023-08-24

摘要

以2000—2019年SPOT/VEGETATION的NDVI时间序列数据集为数据源,采用年均值法、Theil-Sen Median倾斜度分析和Mann-Kendall检验方法,研究宁夏草地植被覆被的时空分布及变化特征,利用Hurst指数方法分析草地植被覆被的可持续性特征和未来发展趋势。同时,基于地理探测器量化了平均降水量、海拔、地区生产总值(GDP)等13个因子对其时空分布的影响。结果表明:(1) 2000—2019年间,宁夏草地植被年均NDVI呈波动增加趋势,增速为0.005?a-1,区域波动差异性较大;空间上呈现南高北低的分布特征,极高植被覆被和高植被覆被区域集中分布在固原市六盘山地区以及沿黄河灌溉地带;(2) 20 a间植被覆被状况显著改善,总体变化趋势向好,但仍有59.341%的草地未来可能存在持续退化或由改善向退化转变的潜在风险;(3) 草地植被分布响应最敏感的环境因子是降水,交互解释力整体最强的是气候与土壤;影响草地植被分布和变化特征的因子之间交互作用的主要表现形式为相互增强或非线性增强关系,因子之间不存在独立关系。

本文引用格式

文妙霞 , 何学高 , 刘欢 , 张婧 , 罗晨 , 贾丰铭 , 王义贵 , 胡云云 . 基于地理探测器的宁夏草地植被覆被时空分异及驱动因子[J]. 干旱区研究, 2023 , 40(8) : 1322 -1332 . DOI: 10.13866/j.azr.2023.08.13

Abstract

This study aims to examine the spatiotemporal variation characteristics of grassland vegetation cover at the regional scale and analyze its driving factors. The findings will provide a scientific reference and decision-making basis for the scientific formulation of protection and restoration models, treatment measures, and the sustainable management of the grassland ecosystem in Ningxia, which are crucial for maintaining the balance of the regional grassland ecosystem and promoting ecological protection and high-quality development in the Yellow River Basin. In this study, the NDVI time series dataset of SPOT/VEGETATION (2000-2019) was used as the data source. The annual mean method, Theil-Sen Median trend analysis, and Mann-Kendall test were employed to study the spatiotemporal distribution and variation characteristics of grassland vegetation cover in Ningxia. Furthermore, the Hurst index method was used to analyze the sustainability characteristics and future development trends of grassland vegetation cover. Simultaneously, the influence of 13 factors, such as average precipitation, altitude, and gross domestic product, on the spatiotemporal distribution was quantified based on the geographical detectors approach. The results show that from 2000 to 2019, the average annual NDVI of vegetation in Ningxia grassland showed a fluctuating growth trend, with a growth rate of 0.005 per year. The regional fluctuation was quite different, with extremely high and high vegetation cover areas concentrated in the Liupan Mountains and the irrigation area along the Yellow River. Overall, the NDVI change showed a low to medium fluctuation trend, and the regional fluctuation was quite different. The vegetation cover condition improved significantly over the 20-year period, with a small degradation area and a favorable overall change trend. However, 59.341% of the grasslands are projected to face potential risks of continuous degradation or transformation from improvement to degradation in the future. The most sensitive environmental factor influencing grassland vegetation distribution response was precipitation, and climate and soil had the strongest interaction explanatory power overall. The relationship between the factors affecting the distribution and variation characteristics of grassland vegetation primarily manifested as mutual reinforcement or nonlinear enhancement, with no independent relationship between the factors. This study provides a scientific reference and decision-making basis for the sustainable management of the grassland ecosystem in Ningxia.

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