Simulating Production Capacity Of Grassland In Northeastern China And Analysising Its Spatiotemporal Patterns

As the most widely distributed vegetation type on earth,grassland plays an important role in the terrestrial carbon cycle.The production capacity of grassland refers to the quantity of products produced on the grassland per unit area in a certain period.Productivity and biomass are two standards to evaluate the productivity of grassland.Accurate estimation of grassland production capacity and elucidation of the temporal and spatial variations and driving factors are crucial for understanding the global carbon cycle and projecting future climate.This thesis taking the production capacity of grassland in northeastern China as the research core,constructing and validating light use efficiency model and biomass random forest models based on eddy covariance flux data,field investigation data,remote sensing and climate data,explored the spatiotemporal patterns,and driving factors on this basis.The research results are as follows:1.Constructing light use efficiency（LUE）model of grassland in northeastern China.The fraction of absorbed photosynthetically active radiation（FPAR）and water stress factor were modified.Based on in-situ FPAR and flux gross primary productivity（GPP）,it was found that there was a 1:1 relationship between the normalized difference phenology index（NDPI）and FPAR in the study area,NDPI had a better performance in interpreting than normalized difference vegetation index（NDVI）and enhanced vegetation index（EVI）,FPAR was represented by NDPI in the modified LUE model.The land surface water index（LSWI）is a normalized ratio index calculated by near infrared and short-wave infrared;it can effectively reflect the moisture content of vegetation canopy.LSWI had the highest correlation with GPP among the water stress parameters,and the model with LSWI+0.5 as the water stress had the highest accuracy among the three water stress models based on LSWI,so water stress factor was represented by LSWI+0.5 in the modified LUE model.2.Comparing and validating northeastern China grassland primary productivity model.Based on the flux data of four grassland stations,the R² of the modified LUE model was 0.855,which was higher than that of MODIS GPP（R²=0.719）and VPM GPP products（R²=0.848）.MAE and RMSE of the modified LUE model were 0.374 g Cm^-2 and 0.735 g Cm^-2,respectively,which were lower than that of MODIS GPP(MAE=0.562 g Cm^-2,RMSE=1.026 g Cm^-2)and VPM GPP products(MAE=0.667 g Cm^-2,RMSE=1.339 g Cm^-2).VPM GPP product generally overestimated the flux GPP;MODIS GPP product significantly overestimated typical steppe GPP in dry years,and significantly underestimated meadow steppe GPP.Although the modified GPP model was higher than the typical steppe flux GPP in the dry years,its overestimation degree is less than that of MODIS GPP and VPM GPP products.The modified LUE model is superior to MODIS GPP and VPM GPP products in terms of model accuracy and dynamic consistency.The modified of water stress and FPAR was the reason for the improvement of LUE model accuracy,and the relative contribution of water stress is greater.The modified LUE model also has higher accuracy in simulating net primary productivity（NPP）.3.Constructing and validating remote sensing model of grassland biomass in northeastern China.Constructing and validating the biomass random forest（RF）models based on extensive in-situ measurements of both aboveground biomass（AGB）and belowground biomass（BGB）.Both the AGB RF model(R²=0.47,MAE=21.06 g Cm^-2,RMSE=27.52 g Cm^-2)and BGB RF model(R²=0.44,MAE=173.02 g Cm^-2,RMSE=244.20 g Cm^-2)had acceptable precision.Lacking grassland height represented parameter may be the reason for the underestimation of high-AGB grassland and lacking soil fertility represented parameter may be the reason for the underestimation of high-BGB grassland.4.Spatiotemporal patterns of grassland production capacity in northeastern China.The NPP showed higher values in the Greater Khingan Mountains and decreased gradually to the east and west sides.The mean NPP density was 258.08 g Cm^-2 and the total grassland NPP were145.40×10⁶ Mg C in northeastern China.Across the region,77.89%of the grasslands showed increasing trend in NPP.On average,NPP increased by 2.51 g Cm^-2yr^-1.The AGB and BGB showed higher values in the Greater Khingan Mountains and decreased gradually to the east and west sides.By comparing the average and coefficient of variation（CV）of the annual biomass over the period 2000-2018,we found that the areas with higher average biomass had lower CV and vice versa.High-biomass steppe which have higher species diversity is more resilient to climate change and/or human disturbance than steppe with low species diversity.The mean AGB and BGB density in northeastern China was 62.16 g Cm^-2 and 531.35 g Cm^-2,respectively,and the total grassland AGB and BGB were 35.26×10⁶ Mg C and 299.26×10⁶ Mg C,respectively.Across the region,72.34%and 63.16%of the grasslands showed increasing trend in AGB and BGB over the period2000-2018,respectively.On average,AGB and BGB increased by 0.37 g Cm^-2 yr^-1 and 0.96 g Cm^-2 yr^-1,respectively.5.Quantitative assessment of production capacity driving forces of grassland in northeastern China.The pastoral and semi-pastoral counties were divided into four spatial independent groups based on the PCA of environmental factors:Group 1 was mostly Hulunber prairie and Xilingol prairie,Group 2 was in the north of the Greater Khingan Mountains,Group 3 was the south of the Greater Khingan Mountains,and Group 4 concentratively in Horqin prairie and Songnen prairie.The general linear model（GLM）results indicated that mean annual precipitation（MAP）was the dominant factor of NPP change in Groups1,3 and 4,while mean annual temperature（MAT）was the dominant factor of NPP change in Group 2.MAP dominated the AGB of all groups.MAT was the dominant factor of BGB change in Group 1,2 and3,while MAP was the dominant factor of BGB change in Group 4.The contribution of human activities to production capacity variation is very small.In general,in most part of the study area,drought was the main limiting factor of NPP and AGB,while temperature rising was the main limiting factor of BGB in the growth season.The relationships between environmental factors and production capacity also varied across the region.Our results provide scientific data for the scientific management of animal husbandry and guarantee the sustainable development of grassland ecology in northeastern China.