| Global climate change has been gradually transformed from natural ecological problems to social problems,and the impact of climate change on terrestrial ecosystems has attracted worldwide attention.Vegetation phenology is the most direct and sensitive indicator which terrestrial ecosystem response to climate change.Grassland is the main type of terrestrial ecosystem,and the influence of climate change on grassland phenology has attracted the attention of scholars.It is important to study the spatial and temporal dynamics of different grassland types and their response to global climate.This research focuses on the phenology of China’s northern grasslands in different types of grassland(alpine meadow,alpine grassland,desert grassland,meadow steppe and temperate steppe and typical steppe)and its response to climate change trend.This article is based on 1985-2010 GIMMS NDVI data and meteorological data(annual mild years precipitation),using Arcgis,Matlab,Sigmaplot,SPASS,R and related software and related analysis(redundancy analysis,statistical methods),researching the spatial and temporal variation characteristics of grassland in the northern grassland of China from 1985 to 2010.And research the spatial and temporal variation characteristics of different grassland types and their response to climate factors(temperature,rainfall).The purpose of this study is to understand the spatial and temporal variation characteristics and relevance of grassland vegetation and climate in northern China over the past 25 years.The results can provide a basis for the response of regional scale to climate change in the context of global warming.The main conclusions of this paper are as follows:(1)Grassland in northern China,the spatial distribution of the number average phenology is associated with regional distribution rules.Beginning from the southeast to the northwest,the vegetation growing season period(the Start of the growing Season,SOS)gradually postponed,grows peak period(the Peak value of the growing Season,POS)delaying gradually,the end of the growing season(End of the growing Season,EOS)in advance gradually,the growing season length(the Length of the growing Season,LOS)gradually reduced.(2)From 1985 to 2010,the overall trend of SOS,POS and EOS in China’s northern grasslands are in advance the overall trend of change and amplitude of variation is 0.02 d/a(R~2=0.007,P=0.68)、0.07 d/ a(R~2=0.07,P=0.19)and 0.12 d/ a(R~2=0.09,P=0.14),respectively.The overall trend of LOS are in advance the overall trend of change and amplitude of variation is 0.11 d/ a(R~2=0.06,P=0.22).SOS in alpine steppe and alpine meadow is delaying,and POS and EOS is advance,so LOS is shorten.SOS,POS and EOS in desert grassland are advance,and LOS is shorted.SOS and POS in typical grassland,meadow steppe and temperate grassland are advance,and EOS is delaying,LOS extended.(3)The SOS,POS,EOS and LOS and average temperature of grassland vegetation in northern China are negatively correlated.That is,the increase of temperature may lead to the early growth season,the growth season and the end of the growth season in the northern grassland vegetation,shortening the length of the growth season.The SOS of grassland vegetation in northern China is negatively correlated with annual rainfall,and POS,EOS and LOS are positively correlated with annual rainfall.It is suggested that the increase of rainfall may lead to the early stage of vegetation growth season in the northern grasslands,vegetation growth season peak and late stage,and the length of vegetation growth season is prolonged.(4)Annual average temperature has greater influence on the SOS(2.815%),POS(8.776%),and LOS(7.054%)in China’s northern grasslands and annual precipitation has greater influence on the LOS(7.054%)in China’s northern grasslands.Annual precipitation is the main factor of SOS,POS in China’s northern grasslands,EOS in desert grassland,LOS in alpine meadow.In addition to the EOS in desert grassland and LOS in alpine meadow,annual average temperature is the main factor of EOS and LOS in China’s northern grasslands. |