Spatiotemporal variation and influencing factors of vegetation dynamics based on Geodetector: A case study of the northwestern Yunnan Plateau, China

被引:99
|
作者
Huo, Hong [1 ]
Sun, Changping [2 ]
机构
[1] Kunming Univ, Coll Architecture & Civil Engn, Kunming 650214, Yunnan, Peoples R China
[2] State Forestry & Grassland Adm, Kunming Inst Survey & Design, Kunming 650031, Yunnan, Peoples R China
关键词
Vegetation dynamics; Quantitative analysis; Interactions; Geodetector; Northwestern Yunnan Plateau; CLIMATE-CHANGE; RIVER-BASIN; GEOGRAPHICAL DETECTOR; SOUTHWEST CHINA; COVER CHANGE; IMPACTS; TRENDS; VARIABILITY; GREENNESS; RESPONSES;
D O I
10.1016/j.ecolind.2021.108005
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Exploring vegetation dynamics and their responses to different natural and anthropogenic factors is crucial for understanding ecosystem processes in the context of global change. As an important ecological security barrier in Southwest China, the northwestern Yunnan Plateau (NYP) provides a variety of ecosystem services. In this study, we investigated the spatiotemporal variation in vegetation cover and quantitatively analysed the relative contributions of potential influencing factors and their interactions to vegetation change on the NYP from 2005 to 2015 using a novel spatial analysis method, the Geodetector model (GDM). Additionally, the most suitable types or ranges of the main influencing factors that were conducive to vegetation growth were identified. Our results showed that the trend of vegetation cover on the NYP was generally negative, with a rate of - 0.0031 yr 1 during the 11-year study period, and was spatially heterogeneous. Areas with obviously decreasing trends were almost twice as large as those with increasing trends (27.49% and 14.37%, respectively) and were mainly concentrated in southeastern and northern Dali as well as the central part of Diqing. Vegetation dynamics were primarily driven by soil type (24.8%), elevation (18.6%), geomorphic type (16.1%), and vegetation type (13.2%), and anthropogenic factors played a weak role in vegetation change, with a contribution of less than 10%, demonstrating that the influences of natural factors on vegetation change were greater than those of anthropogenic factors. Moreover, the interaction of pairwise factors played a more important role in affecting vegetation dynamics than did each factor individually. These findings are helpful for better understanding the complex mechanisms of vegetation change and providing scientific suggestions for the prevention of vegetation degradation in fragile ecosystems.
引用
收藏
页数:10
相关论文
共 50 条
  • [41] Spatiotemporal dynamics and driving factors of county-level carbon storage in the Loess Plateau: A case study in Qingcheng County, China
    Wang, Ningfei
    Chen, Xingpeng
    Zhang, Zilong
    Pang, Jiaxing
    ECOLOGICAL INDICATORS, 2022, 144
  • [42] Spatiotemporal characteristics and influencing factors of vegetation water use efficiency on the Tibetan Plateau in 2001-2020
    He, Chenyang
    Wang, Yanjiao
    Yan, Feng
    Lu, Qi
    JOURNAL OF GEOGRAPHICAL SCIENCES, 2025, 35 (01) : 39 - 64
  • [43] Study on Spatiotemporal Variation Pattern of Vegetation Coverage on Qinghai-Tibet Plateau and the Analysis of Its Climate Driving Factors
    Deng, Xiaoyu
    Wu, Liangxu
    He, Chengjin
    Shao, Huaiyong
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (14)
  • [44] Evaluation of spatiotemporal variation and impact factors for vegetation net primary productivity in a typical open-pit mining ecosystem in northwestern China
    Wang, Jinyang
    Cui, Kuankuan
    Yang, Fei
    Li, Jun
    Zhang, Chengye
    Du, Tianmeng
    Zhang, Haoran
    LAND DEGRADATION & DEVELOPMENT, 2024, 35 (12) : 3756 - 3770
  • [45] Dynamic change, driving mechanism and spatiotemporal prediction of the normalized vegetation index: a case study from Yunnan Province, China
    Han, Yang
    Lin, Yilin
    Zhou, Peng
    Duan, Jinjiang
    Cao, Zhaoxiang
    FRONTIERS IN ECOLOGY AND EVOLUTION, 2023, 11
  • [46] Evaluating Spatiotemporal Distribution of Residential Sprawl and Influencing Factors Based on Multi-Dimensional Measurement and GeoDetector Modelling
    Zhang, Linlin
    Qiao, Guanghui
    Huang, Huiling
    Chen, Yang
    Luo, Jiaojiao
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2021, 18 (16)
  • [47] Spatiotemporal Variation of Runoff and Its Influencing Factors in the Yellow River Basin, China
    Cui, Jingkai
    Jian, Shengqi
    WATER, 2023, 15 (11)
  • [48] Spatiotemporal Variation and Influencing Factors of Atmospheric CO2 Concentration in China
    Zhu, Weixin
    Zhang, Hong
    Zhang, Xiaoyu
    Guo, Haohao
    Liu, Yong
    CHINESE GEOGRAPHICAL SCIENCE, 2025, 35 (01) : 149 - 160
  • [49] Spatiotemporal variation of surface albedo and its influencing factors in northern Xinjiang, China
    Shuai Yuan
    Yongqiang Liu
    Yan Qin
    Kun Zhang
    Journal of Arid Land, 2023, 15 : 1315 - 1339
  • [50] Spatiotemporal variation of surface albedo and its influencing factors in northern Xinjiang, China
    Yuan, Shuai
    Liu, Yongqiang
    Qin, Yan
    Zhang, Kun
    JOURNAL OF ARID LAND, 2023, 15 (11) : 1315 - 1339