Multi-scale Study On Vegetation Phenology And Its Climatic Change Responses In The Amur River Basin

The phenology of terrestrial vegetation is a key ecological parameter reflecting the change of surface vegetation and ecological health,and it is also a sensitive indicator of global climate change.It plays an important role in regulating the absorption of carbon by plants.With the in-depth research on global climate change,the use of remote sensing to monitor plant phenology and its response to climate change has also become a hot issue.Identifying the temporal and spatial differentiation of the response of vegetation phenology to climate change is of great significance for a better understanding of the ecosystem's carbon cycle and prediction of the ecosystem's response to global changes.Contemporary long-term satellite remote sensing data provide a feasible method for monitoring the relationship between vegetation phenology and climate change at different temporal and spatial scales.The study of the temporal and spatial differentiation of vegetation phenology in response to climate change is essential to better understand the carbon cycle process of the ecosystem,and is of great significance to predict the ecosystem's response to global climate change.Using multi-source remote sensing data to monitor the relationship between vegetation phenology and climate change at different time and space scales is one of the most commonly used methods currently.As a cross-regional and multi-vegetation area in the middle and high latitudes,the Amur River Basin is of important ecological and social significance.It passes through a number of high-altitude areas,and its climate change and vegetation are excessively obvious,providing a rare opportunity for remote sensing to monitor climate-driven vegetation phenological changes.The Amur River Basin was selected as the research area in this study.Geographic information system(GIS),remote sensing technology and ESTATFM fusion method were combined,integrating the third-generation GIMMS vegetation index(NDVI3g)data and different resolution MODIS vegetation index products,to construct suitable high spatial resolution NDVI dataset in long-time series.Comprehensive ground phenology observation data,selecting the slope method to extract vegetation phenology indicators,to analyze the spatio-temporal changes of vegetation phenology in the Amur River Basin from 1982 to 2015 from basin scales,different vegetation types,different climatic regions and different resolution data source scales,etc.,combining multiple meteorological factors,to explore the correlation between multi-scale vegetation phenology and various climatic factors.The main findings were as follows:(1)Generally,more than 76% vegetation SOS in the Amur River Basin was concentrated between mid-April and early May,and overall mountainous areas were earlier than plain areas;above 81% vegetation entered the end of the growing season from late October to early November,the higher the latitude in the region,the sooner the vegetation growing season ended.Besides,74% and higher of the peak time of the vegetation growth season was concentrated between mid-July and early August,and the spatial pattern of the northern part was earlier than the southern part and later than the plain area.More than 70% vegetation growth time was mostly between 165 days and 195 days,and it presented a spatial pattern that the vegetation growth time of the plain area was shorter than that of the mountain forest area.(2)From 1982 to 2015,the vegetation growth season in the Amur River Basin has been getting earlier and earlier,the rate was 0.496 days/year;vegetation EOS tended to be delayed,the rate was 0.158 days/year;the vegetation growth period has significantly prolonged,the rate was 0.654 days/year;while no significant variation has been observed in the MOS period of vegetation.When analyses of different vegetation types were performed,it was found that the advancement of the SOS date of grassland vegetation is the most significant,with a rate of 0.205 days/year;followed by forest and farmland,with rates of 0.163 days/year and 0.124 days/year,respectively.While no significant trend has been observed in wetland SOS date.The most remarkable postponement of EOS time was observed in farmland vegetation,with rate of 0.256 days/year;followed by grassland and forest,with rates of 0.222 days/year and 0.212 days/year respectively.While no significant trend has been observed in the EOS time of wetland vegetation.The LOS of forest,grassland and farmland vegetation extended significantly,with a rate higher than 0.4 days/year,while no significant trend for wetland vegetation.On dynamic temporal and spatial scale,the distribution of vegetation phenological indicators in different climatic zones was different.Among them,the SOS time of vegetation in arid climate zones is advanced at a rate of 0.204 days/year,which is faster than that of vegetation in cold temperate climates(0.157 days/year).For the EOS time of vegetation,postponement trends were observed in both arid climate zones and cold-temperate climate zones;and the postponement of vegetation EOS time for in cold-temperate zones was 0.198 days/year,much faster than that of arid climate zones.There is little change for vegetation MOS in arid climate zones and cold-temperate climate zones.The LOS of vegetation in arid climate zones extends more remarkable,with a rate of 0.65 days/year,while it was 0.432 days/year in cold-temperate climate zones.(3)From the phenological indicators monitored by the ground observation station to the vegetation phenological remote sensing retrieval indicators at different resolution scales of 250 m,500 m,1 km and 8 km,the SOS date of vegetation in the Amur River Basin from 1982 to 2015 based on remote sensing monitoring was earlier than the date by the ground observation station.The date of vegetation EOS was later than the time when the vegetation started to fall in the ground monitoring record.In general,there was a significant correlation(p<0.05)between the vegetation phenology index recorded by the ground phenology observation station and the vegetation phenology remote sensing monitoring data(p<0.05).Among the vegetation phenology indicators developed,the vegetation phenology indicators retrieved based on the 250 m NDVI were the most consistent with those recorded by the ground phenology observation station.(4)From 1982 to 2015,the climate in the Amur River Basin became warmer and drier gradually,with a significant increase for the average temperature in summer(p <0.01)and autumn(p <0.01),with a significant decreasing trend for cumulative precipitation,while with an increasing trend for accumulated precipitation in spring and winter.When the response of vegetation phenology to climate change was performed,it was found that heavy precipitation has a certain inhibitory effect on the vegetation greening and growth.With the increase of precipitation,the postponement rate was 0.0125 days/mm;with the increase of precipitation,the rate of vegetation yellowing advance was 0.0109 days/mm.In general,the vegetation growing season extended by 2.0957 days,and the annual cumulative precipitation increased by 1mm,and the vegetation growing season will shorten 0.0234 days,corresponded to each 1? increase in annual average temperature.On different seasonal scales,a certain lag was found in the response of vegetation phenology to climate change.Specifically,vegetation SOS responded significantly to temperature and precipitation in the first two months of spring,and vegetation EOS responded to summer temperature,autumn temperature and pre-season temperature in the first month of the season.Statistics on the pixel scale showed that the percentage of vegetation pixels with a significant negative response to spring temperature by vegetation SOS was 45.59%.The percentage of pixels that delayed the start of vegetation growth due to heavy rainfall before the season accounted for 33.13%;the percentages of pixels where the increase in temperature in summer and autumn caused significant delays in vegetation EOS were 31.07% and 53.75%,respectively;the percentage of pixels with a negative response to the pre-season heavy rainfall on the date of vegetation EOS was 36.32%.(5)The phenological indicators of different vegetation types had different responses to changes in different climate factors.Wetland vegetation has the strongest response to pre-season temperature and precipitation,with a significant lag period.Among them,wetland and farmland vegetation SOS that were significantly advanced due to the increase in pre-season temperature accounted for 50.6% and 72.56%,respectively,and the grassland and forest vegetation SOS that were significantly advanced due to the increase in average annual temperature accounted for 51.73% and 57.25%,respectively.The lag effect of vegetation SOS response to pre-season precipitation mainly occurred in wetlands and grasslands.Among them,wetland had a significant positive correlation with cumulative precipitation in the first two months of the season,accounting for 47.67% of the variation;while grassland has a positive correlation with cumulative precipitation in the first two months of the season,accounting for 50.83% of the variation.The response of vegetation EOS to the preseason temperature is reflected in the post-season with the increase of temperature in the first two months of the season,and the earlier with the increase of precipitation in the first two months of the season.Among them,the EOS date of wetland vegetation has a significant positive correlation with the average temperature of the first two months of the season,accounting for 29.34%,and there was a significant negative correlation with the cumulative precipitation in the first two months of the season,accounting for 55.16%.The EOS date of grassland vegetation was positively correlated with the average temperature and negatively correlated with the precipitation in two months before the season,accounting for 45.07% and 41.55% respectively.The EOS date of forest vegetation had a significant positive correlation with the average temperature in the first two months of the season,accounting for 67.38%,and a significant negative correlation with the cumulative precipitation of the two months before the season,accounting for 48.45%.The date of farmland vegetation EOS was significantly positively correlated with the average temperature of the first two months of the season,accounting for 74.14%;and the proportion of pixels that were significantly positively correlated with the precipitation of the first two months of the season is 41.79%.When the response of vegetation phenology characteristics to changes in climate factors with different climatic zones were analyzed,it was found that the SOS date of vegetation in arid climate zones was mainly affected by the average temperature and the cumulative precipitation in the first two months of the season,with a remarkable lag effect.At the end of the growing season,the spatial correlation between average temperature in the first two months of the season and the accumulated precipitation in autumn was mainly a significant positive correlation.The main climatic factors that affected vegetation in cold temperate climate zones were the average preseason temperature and accumulated precipitation before season;the average annual temperature and accumulated precipitation before season will significantly affected the growth of vegetation in cold temperate climate zones,and accordingly affected the end time of vegetation growth.