怒江-萨尔温江流域植被覆盖时空变化趋势及驱动力
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

国家自然基金项目(41961060);国家重点研发计划政府间国际科技创新合作重点专项(2018YFE0184300);四川省科技计划资助(2023NSFSC0754)


Spatio-temporal variation and driving forces of vegetation cover in the Nujiang-Salween River Basin
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 文章评论
    摘要:

    植被作为陆地生态系统的主要组成部分,对区域生态系统环境变化、全球碳循环和气候调节具有非常重要的作用。怒江-萨尔温江流域是东南亚最重要的跨境河流之一,其植被变化会影响区域生态系统和气候。研究以怒江-萨尔温江流域为研究区,基于2000-2021年MODIS NDVI数据,利用BFAST模型、Hurst指数以及地理探测器研究了其植被覆盖时空演变趋势和未来可持续性以及驱动因子。结果表明:(1)2000-2021年,怒江-萨尔温江流域植被覆盖总体呈波动上升趋势,多年平均植被覆盖度FVC (Fractional Vegetation Cover)为0.73,以高植被覆盖和较高植被覆盖为主。植被分布具有明显的空间异质性,下游和中游植被覆盖明显优于上游。(2) BFAST趋势表明,近22年怒江-萨尔温江流域植被覆盖改善和退化的区域面积占比分别为71.24%、28.76%,改善的区域远大于退化的区域,说明研究区植被得到较好的保护。Hurst指数显示,未来植被将持续改善和退化的区域占比分别为94.89%、2.76%。BFAST与Hurst二者叠加共耦合了17种植被覆盖的未来趋势情形,整体上未来植被呈持续改善为主,将持续改善和持续退化状态的面积占比分别为68.99%、29.09%。(3)基于最优参数的地理探测器结果表明,海拔对研究区植被覆盖分布具有宏观控制作用,影响最大,其次是气温、降水等气象因子。各区域植被覆盖影响因素又具有差异性,其中,海拔和土地利用方式对上游地区植被覆盖的影响比中游和下游区域显著;中游高山峡谷地区以海拔以及海拔差异带来的气温、降水差异对植被覆盖影响重大;下游地区以人口、GDP等人为因素影响为主。研究结果对了解研究区生态环境状况及未来变化提供科学数据支持。

    Abstract:

    As the main component of terrestrial ecosystem, vegetation plays a very important role in regional ecosystem environmental change, global carbon cycle, and climate regulation. The Nujiang-Salween River Basin is one of the most important transboundary rivers in Southeast Asia, and its vegetation changes will affect regional ecosystems and climate. This study takes the Nujiang-Salween River Basin as the research area, based on the MODIS NDVI data from 2000 to 2021, using the BFAST model, Hurst exponent, and geographic detectors to study the temporal and spatial evolution trends of vegetation coverage, future sustainability, and driving factors. The results show that:(1) from 2000 to 2021, the vegetation coverage of the Nujiang-Salween River Basin presented an overall fluctuating upward trend, and the annual average Fractional Vegetation Cover (FVC) value was 0.73, mainly with high vegetation coverage and relatively high vegetation coverage. Vegetation distribution had obviously spatial heterogeneity, and the vegetation coverage in the lower and middle reaches was significantly larger than that in the upper reaches. (2) The BFAST trend indicated that in the past 22 years, the proportions of areas with improved and degraded vegetation cover in the Nujiang-Salween River Basin were 71.24% and 28.76%, respectively. The improved areas were much larger than the degraded areas, indicating that the vegetation in the study area has been well protected. The Hurst exponent shows that the proportion of areas where vegetation will continue to improve and degrade in the future is 94.89% and 2.76%, respectively. The superposition of BFAST and Hurst coupled 17 types of future trends in vegetation coverage. Overall, the vegetation in the future will continue to improve, accounting for 68.99% and 29.09% of the areas that will continue to improve and continue to degrade, respectively. (3) The results of Optimal Parameters-based Geographic Detector (OPGD) show that altitude has a macroscopic control effect on the distribution of vegetation coverage in the study area, with the greatest impact, followed by meteorological factors such as temperature and precipitation. There are differences in the influencing factors of vegetation cover among different regions. The altitude and land use methods have more significant impact on vegetation cover in the upper reaches than in the lower and middle reaches. In the alpine and canyon regions of the middle reaches, the altitude and differences in temperature and precipitation brought about by altitude have major impact on vegetation coverage, while the lower reaches is mainly influenced by factors such as population and GDP. The results provide scientific data support for understanding the ecological environment status and future changes in the research area.

    参考文献
    相似文献
    引证文献
引用本文

钟旭珍,王金亮,邓云程,李杰,吴瑞娟,董品亮.怒江-萨尔温江流域植被覆盖时空变化趋势及驱动力.生态学报,2023,43(24):10182~10201

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数: