In order to systematically quantify the synergistic relationship between environmental factors and their regulation of spatial and temporal patterns of biomass,taking the Xilin River basin as the study area,this study measured the aboveground biomass(AGB),soil water content,soil density,organic carbon mass fraction,total nitrogen mass fraction,soil pH and other environmental factors of the typical grassland ecosystem from May to September 2020.The relationship between AGB and driving factors were analyzed by using the geographic detector method.The results show that:1)Watershed-level AGB increases stably at the beginning stage of the growing season,displays the highest increase rate in July,and reaches the maximum on September 3rd.AGB in the upstream and downstream is 209.12 and 147.19 g/m2,respectively.AGB in the upstream of the watershed is significantly higher than that in the downstream(significance level p＜0.05),and the overall spatial pattern of AGB shows a decreasing trend from the southeast to the northwest in the watershed.2)During the entire vegetation growing season,meteorological factors(precipitation and air temperature)are key factors driving the changes in AGB,with an explanation rate of more than 60.0％in the regression model.At the end of the growing season,in addition to meteorological factors,soil pH also significantly influences the dynamics of AGB in time and space.3)At each stage of the growing season,the interaction between environmental factors shows nonlinear enhancement and double-factor enhancement.At the beginning of the growing season,the interaction between precipitation and dry density of soil shows the most influential.When soil water content reaches a relatively high level,the interaction of soil dry density with other environmental factors(precipitation,air temperature,pH)exerts a significant impact on the AGB in the peak and late stages of the growing season vegetation growth in the basin.
关键词
锡林河流域/草原/地上生物量/环境因子/地理探测器
Key words
Xilin River basin/grassland/aboveground biomass/environmental factors/geographic detectors
维普
万方数据