| Forest ecosystems are the main component of the terrestrial ecosystem and play key roles in protecting biodiversity,maintaining the global carbon cycle,and mitigating global warming.Currently,more than a half of tree species in the global forests are threatened by human activities and climate change,resulting in the degradation of forest ecological functions and services.The temperate forests in the Northeast China are one of the three major natural forests in China,but more than 60% of the natural forests of Northeast China have been degraded into secondary forests.Understanding spatial patterns and their drivers of forest community structure and ecological functions will help to grasp the status of forest resources in Northeast China,and provide scientific basis for the region and nation to formulate forest management policies to cope with climate change and human disturbance.In this study,we analyzed spatial patterns and important drivers of forest community structure and ecological functions for Northeast China,based on multisource data from in situ forest inventories,as well as bioclimatic,topographic,and human footprint data.We derived high-resolution(1km × 1 km)maps of the community structure and ecological functions for this region.The main results of the study are as follows:1.The spatial patterns and its drivers of tree species diversity.(1)Tree species diversity varied greatly across Northeast China.Specifically,the spatial patterns of tree species richness,Shannon diversity and Simpson diversity were similar.The highest diversity areas located in Changbai Mountains,Zhangguang’cai Mountains and the southern part of Xiao Xing’an Ling Mountains,while the lowest diversity areas distributed in Wanda Mountains,the northern part of Xiao Xing’an Ling Mountains and Da Xing’an Ling Mountains.Contrary to the above-mentioned diversity indies,the highest evenness areas mainly concentrated in the Da Xing’an Ling Mountains,while the lowest evenness areas mainly concentrated in the Longgang Mountains,Wanda Mountains and the southern part of the Xiao Xing’an Ling Mountains;(2)The spatial patterns of tree species diversity mainly affected by climate,topography and human disturbance factors.Among them,the first three diversity indexes were positively correlated with annual mean precipitation,elevation,and human footprint.However,tree species evenness was negatively correlated with annual mean precipitation,elevation,and human footprint.2.The spatial patterns and its drivers of functional trait composition and functional diversity.(1)Community functional trait composition(CWM)varied greatly across Northeast China.Among them,the largest woody density areas mainly distributed in Longgang Mountains,Hada Mountains and Wanda Mountains,while the smallest its areas mainly located in the northern part of Xiao Xing’an Ling Mountains,Zhangguang’cai Mountains and Changbai Mountains.The highest maximum tree height areas mainly distributed in the northern part of Da Xing’an Ling Mountains,while the lowest its areas mainly located in the Wanda Mountains,Changbai Mountains and Longgang Mountains.In addition,the largest leaf area and specific leaf area regions mainly distributed in Longgang Mountains and Hada Mountains,while the smallest its regions mainly located in the northern part of Da Xing’an Ling and Xiao Xing’an Ling Mountains.The highest leaf carbon concentration,nitrogen concentration,and nitrogen-phosphorus ratio regions mainly concentrated in Changbai Mountains,Zhangguang’cai Mountains and the southern part of Xiao Xing’an Ling Mountains,while the lowest its regions mainly located in the north of Da Xing’an Ling Mountains;(2)The spatial patterns of different functional diversity indies(FD)were similar.The highest function richness,Rao quadratic entropy function and functional dispersion areas were located in the southern part of Xiao Xing’an Ling Mountains,Zhangguang’cai Mountains and western part of Changbai Mountains,while the lowest its areas mainly distributed in Wanda Mountains,northern part of Xiao Xing’an Ling Mountains and southern part of Da Xing’an Ling Mountains;(3)The spatial patterns of community functional trait composition(CWM)mainly driven by climate and topographic factors,while the spatial patterns of functional diversity indies(FD)mainly affected by climate,topography and human disturbance factors.3.The spatial patterns and its drivers of tree size differentiation.(1)Tree size differentiation based on dbh and height varied greatly across Northeast China.For tree dbh differentiation,the spatial patterns of the coefficient of variation,the Gini coefficient,and Shannon diversity were similar.The highest tree dbh differentiation areas distributed in southern part of Zhangguang’cai Mountains and Changbai Mountains,while the lowest its areas located in Da Xing’an Ling Mountains,the northern part of Xiao Xing’an Ling Mountains and Wanda Mountains.In addition,the spatial patterns of the coefficient of variation,and the Gini coefficient for tree height differentiation were similar.The highest tree height differentiation areas located in the southern part of Xiao Xing’an Ling Mountains,Zhangguang’cai Mountains,and the western part of Changbai Mountain,while the lowest its areas mainly located in the west of Da Xing’an Ling Mountains,Laoye Mountians and Hada Mountains.(2)The spatial patterns of tree size differentiation based on dbh and tree height mainly driven by climate,topography,and human disturbance factors.Specifically,tree size differentiation variables were positively correlated with annual mean precipitation and elevation,but were negatively correlated with annual mean temperature and human footprints.4.The spatial patterns and its drivers of aboveground productivity.(1)Aboveground productivity and temporal stability varied greatly across Northeast China.Firstly,the largest aboveground productivity areas mainly concentrated in Changbai Mountains and the southern part of Zhangguang’cai Mountains,while the lowest its areas mainly located in Da Xing’an Ling Mountains,northern part of Xiao Xing’an Ling Mountains and Longgang Mountains.Secondly,the highest aboveground biomass temporal stability regions distributed in Changbai Mountains,the northern part of Zhangguang’cai Mountain and Laoye Mountains,while the lowest its areas located in the eastern part of Da Xing’an Ling Mountains,northern part of Xiao Xing’an Ling Mountains and Hada Mountains;(2)The spatial patterns of aboveground productivity and temporal stability mainly affected by the tree size differentiation,climate,topography and human disturbance factors.Among them,the aboveground productivity was positively correlated with the Shannon diversity of dbh,annual mean temperature,elevation,and human footprint.In addition,the temporal stability was positively correlated with the Shannon diversity of dbh,the coefficient of variation of dbh,and elevation,but was negatively correlated with leaf nitrogen concentration and human footprint.5.Estimated current and future biomass carbon storage,and the spatial patterns and its drivers of biomass carbon density.(1)The current total biomass carbon stock across the Northeast China was estimated to be 2.53 ± 0.63 Pg C.Planted forests in Northeast China accounted for 0.34 ± 0.08 Pg C in biomass carbon stock while natural forests accounted for 2.19 ± 0.55 Pg C in biomass carbon stock;(2)In 2080,the future total biomass C stock of the three climate change scenarios(Baseline,RCP4.5 and RCP8.5)were estimated to be 4.49 ± 0.93 Pg C,4.90 ± 0.87 Pg C and 5.23 ± 1.18 Pg C;(3)Current biomass carbon density varied greatly across Northeast China.The largest biomass carbon density areas mainly concentrated in Changbai Mountains,Zhangguang’cai Mountains and Laoye Mountains,while the lowest its areas mainly located in the eastern part of Da Xing’an Ling Mountains,the northern part of Xiao Xing’an Ling Mountains and Longgang Mountains.In addition,the current biomass carbon density was mainly positively correlated with the Shannon diversity of dbh,the coefficient of variation of dbh,elevation,leaf phosphorus content,maximum tree height and human footprint. |
