植物生态学报 ›› 2021, Vol. 45 ›› Issue (6): 626-640.DOI: 10.17521/cjpe.2021.0042

• 研究论文 • 上一篇    下一篇

中国西南部地区植被对极端气候事件的响应

倪铭, 张曦月, 姜超*(), 王鹤松   

  1. 北京林业大学生态与自然保护学院, 北京 100083
  • 收稿日期:2021-02-01 接受日期:2021-03-26 出版日期:2021-06-20 发布日期:2021-09-09
  • 通讯作者: 姜超
  • 作者简介:*(jiangchao@bjfu.edu.cn)
  • 基金资助:
    国家重点研发计划(2016YFC0502104)

Responses of vegetation to extreme climate events in southwestern China

NI Ming, ZHANG Xi-Yue, JIANG Chao*(), WANG He-Song   

  1. School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China
  • Received:2021-02-01 Accepted:2021-03-26 Online:2021-06-20 Published:2021-09-09
  • Contact: JIANG Chao
  • Supported by:
    National Key R&D Program of China(2016YFC0502104)

摘要:

在全球气候变化背景下, 极端气候事件频发。中国西南部地区植被对于气候变化及极端气候事件的响应较为敏感。为探究西南部地区植被对极端气候事件的响应程度, 该文采用Pettitt检验、趋势分析法对数据进行分析, 并对数据进行去趋势处理, 分析去趋势前后极端气候指数与归一化植被指数(NDVI)的相关关系。结果表明: (1) 1982-2015年西南部地区植被NDVI呈现显著上升的趋势, NDVI在1994年发生突变, 突变前上升不显著, 突变后呈现显著上升的趋势; (2)去趋势前, 1982-2015年间, 极端降水指数与NDVI显著相关的仅有1日最大降水量, 其与NDVI显著正相关; 除气温日较差外, 其他极端温度指数均与NDVI显著相关。1994-2015年间, 1日最大降水量与NDVI显著正相关, 降水日数与NDVI显著负相关; 在极端温度指数中, 日最低气温最大值、暖昼日数、夏季日数、生长季长度和气温日较差与NDVI显著正相关, 冷昼日数、冰冻日数、冷夜日数和霜冻日数与NDVI显著负相关。1982-2015年间NDVI对年平均气温的响应最强, 而在1994-2015年间NDVI对夏季日数和气温日较差的响应强于对年平均气温的响应。(3)去趋势后, 极端降水指数与NDVI的相关性在两个时段都不显著; 而日最高气温最大值、暖昼日数、夏季日数和气温日较差在这两个时段与NDVI显著正相关, 但其与NDVI的相关系数都在1994-2015年间更高。气温日较差在两个时段与NDVI的相关系数都最高。只在1982-2015年冷昼日数与NDVI显著负相关。

关键词: 归一化植被指数(NDVI), 极端气候指数, 全球气候变化, 中国西南部地区

Abstract:

Aims The occurrence of extreme climate events is becoming more frequent worldwide because of the global warming. This study investigated the responses of vegetation to climate extremes in southwestern China, in order to assess the regional eco-security of natural ecosystems related to global climate change.

Methods The normalized difference vegetation index (NDVI) data from the GIMMS V1.0 datasets with a resolution of 0.083° × 0.083° for the period of January 1982 to December 2015 were used in this study for analysis of the spatiotemporal dynamics of vegetation in the study region. The grid data of regional meteorological variables from the CN05.1 for the period of January 1961 to December 2016 were used to develop the overall climate extreme variables, and the values matching the data period of NDVI were eventually adopted in the analysis on the interrelationships between NDVI and the climate extremes using Pettitt test and trend analysis both before and after detrending.

Important findings Results show that in the study region, NDVI generally increased from 1982 to 2015, with occurrence of an abrupt change in 1994. Prior to 1994, the change in NDVI was not significant, but the increase became significant from this point onward. Before data detrending, only the maximum 1-day precipitation was significantly and positively correlated with NDVI in the precipitation-extremes during 1982-2015. The temperature- extreme variables were all significantly correlated with NDVI except the diel air temperature range. From 1994 to 2015, the maximum 1-day precipitation was significantly and positively correlated with NDVI and the number of wet days was significantly and negatively correlated with NDVI. none of the precipitation-extreme variables was significantly correlated with NDVI. The yearly maximum value of daily minimum air temperature, warm days, summer days, length of growing season and diel air temperature range were all significantly and positively correlated with NDVI, but the cool days, frost days, cool nights and icing days were significantly and negatively correlated with NDVI. During 1982-2015, the NDVI was more strongly correlated with annual mean air temperature than with any of the temperature-extreme variables; whereas during 1994-2015, NDVI was more strongly correlated with summer days and diel air temperature range than with annual mean air temperature. After eliminating the trend, there was no significant correlation between the precipitation-extreme variables and NDVI, but the yearly maximum value of daily maximum air temperature, warm days, summer days and diel temperature range were significantly and positively correlated with NDVI for the entire period of 1982-2015 as well as for the period 1994-2015. The response of NDVI to extreme warm events was more pronounced during 1994-2015 than during 1982-2015, with the strongest correlation between diel air temperature range and NDVI. There was a significant and negative correlation between cool days and NDVI for the period 1982-2015.

Key words: normalized differential vegetation index (NDVI), climate extremes variables, global climate change, southwestern China