植物生态学报 ›› 2021, Vol. 45 ›› Issue (3): 213-223.DOI: 10.17521/cjpe.2020.0096

所属专题: 青藏高原植物生态学:遥感生态学

• 研究论文 •    下一篇

中国生态功能保护区归一化植被指数动态及气候因子驱动

徐光来1,2, 李爱娟1,2, 徐晓华1,*(), 杨先成1,2, 杨强强1,2   

  1. 1安徽师范大学地理与旅游学院, 安徽芜湖 241002
    2安徽省江淮流域地表过程与区域响应重点实验室, 安徽芜湖 241002
  • 收稿日期:2020-04-07 接受日期:2020-06-03 出版日期:2021-03-20 发布日期:2021-05-17
  • 通讯作者: 徐晓华
  • 作者简介:* (xuxh1113@126.com)
    徐光来: ORCID:0000-0002-4203-5346
  • 基金资助:
    国家自然科学基金(41301029)

NDVIdynamics and driving climatic factors in the Protected Zones for Ecological Functions in China

XU Guang-Lai1,2, LI Ai-Juan1,2, XU Xiao-Hua1,*(), YANG Xian-Cheng1,2, YANG Qiang-Qiang1,2   

  1. 1School of Geography and Tourism, Anhui Normal University, Wuhu, Anhui 241002, China
    2Anhui Key Laboratory of Natural Disaster Process and Prevention, Wuhu, Anhui 241002, China
  • Received:2020-04-07 Accepted:2020-06-03 Online:2021-03-20 Published:2021-05-17
  • Contact: XU Xiao-Hua
  • Supported by:
    National Natural Science Foundation of China(41301029)

摘要:

为揭示生态功能保护区归一化植被指数(NDVI)与气候因子相关性, 为今后该区域植被动态监测提供有用的信息, 该研究基于2000-2015年MODIS NDVI数据和逐月格点降水与气温数据, 采用生态功能保护区和像元两种空间尺度, 应用线性倾向分析、偏相关分析、复相关分析等方法研究了46个生态功能保护区NDVI变化及其与气候因子的关系, 在此基础上基于相关系数显著性水平对生态功能保护区NDVI动态进行了气候因子驱动分区。主要结果: (1)生态功能保护区NDVI总体呈增加趋势, 其增率加权平均值为0.045·a-1。像元分析表明, NDVI显著增加的区域主要分布在中部和东北部。(2)生态功能保护区NDVI与降水的偏相关系数在-0.30-0.72之间, 在32个分区呈正相关关系。NDVI与气温的偏相关性在-0.36-0.92之间, 在39个分区呈正相关关系。像元分析表明, 50.6%的像元NDVI与降水呈显著正偏相关关系, 主要分布在东北及西北地区。64.6%的像元NDVI与气温呈显著正偏相关关系, 主要分布在东北及青藏高原北缘地区。(3)气温-降水强驱动型是主要驱动类型, 占总面积的38.7%; 气温驱动型为次要驱动类型, 占27.3%; 非气候因子驱动型占17.6%。以上结果表明, 生态功能保护区NDVI与气温、降水气候因子改变具有显著相关性, 气候因子驱动的地区共占82.4%。研究气候变暖背景下生态功能保护区NDVI变化及其对气候因子的响应, 对于认识该区植被动态变化规律具有重要作用。

关键词: 生态功能保护区, 归一化植被指数, 气候因子, 偏相关分析, 气候驱动分区

Abstract:

Aims This study demonstrates the consistencies and discrepancies of correlations between climate factors and normalized difference vegetation index (NDVI) in the Protected Zones for Ecological Functions (EFPZs) in China, which provide useful information for monitoring in subsequent studies of vegetation dynamics.
Methods Based on the MODISNDVI data and the grid data for monthly precipitation and air temperatures from 2000 to 2015, the dynamics of NDVI and correlations with climatic factors were examined across 46 EFPZs at two spatial scales, by individual EFPZs and the pixels, using linear tendency and partial correlation methods. In accordance to the analyses, the EFPZs were categorized into different types of climatic influences.
Important findings The overall NDVI across the EFPZs showed an increasing trend, with the average linear slope of 0.045·a-1. Pixel scale analysis showed that NDVIincreased significantly in the central regions and the northeast of China. Partial correlation coefficients between NDVI and precipitation in the EFPZs varied between -0.30 to 0.72, and were positive for 32 in the EFPZs. Partial correlation between NDVI and air temperature ranged from -0.36 to 0.92, with positive correlations in 39 in the EFPZs. In 50.6% of the pixels, NDVIwas positively correlated with precipitation, mainly in northeast and northwest China. In 64.6% of the pixels,NDVI was positively correlated with air temperatures, mainly in the northeastern and the northern edge of the Qingzang Plateau. Strong temperature-precipitation driving is the main type of climatic influences on NDVI changes across the EFPZs, accounting for 38.7% of the total, with temperature driving type being secondary, accounting for 27.3%; non-climatic driving type accounts for 17.6%. Our results show the NDVI in the EFPZs are significantly correlated with climatic factors concerning precipitation and air temperatures, and that NDVI dynamics in 82.4% of the areas are driven by climate factors. Studying the changes in NDVI and the responses of NDVI to climate factors is very important for understanding the dynamics of vegetation in the EFPZs under climate warming.

Key words: the Protected Zones for Ecological Functions (EFPZs), normalized difference vegetation index (NDVI), climatic factor, partial correlation analysis, climate driving type zone