Analysis and prediction of global vegetation dynamics:past variations and future perspectives

Spatiotemporal dynamic vegetation changes affect global climate change,energy balances and the hydrological cycle.Predicting these dynamics over a long time series is important for the study and analysis of global environmental change.Based on leaf area index(LAI),climate,and radiation flux data of past and future scenarios,this study looked at historical dynamic changes in global vegetation LAI,and proposed a coupled multiple linear regression and improved gray model(CMLRIGM)to predict future global LAI.The results show that CMLRIGM predictions are more accurate than results predicted by the multiple linear regression(MLR)model or the improved gray model(IGM)alone.This coupled model can effectively resolve the problem posed by the underestimation of annual average of global vegetation LAI predicted by MLR and the overestimate predicted by IGM.From 1981 to 2018,the annual average of LAI in most areas covered by global vegetation(71.4%)showed an increase with a growth rate of 0.0028 a-1;of this area,significant increases occurred in 34.42%of the total area.From 2016 to 2060,the CMLRIGM model has predicted that the annual average global vegetation LAI will increase,accounting for approximately 68.5%of the global vegetation coverage,with a growth rate of 0.004 a-1.The growth rate will increase in the future scenario,and it may be related to the driving factors of the high emission scenario used in this study.This research may provide a basis for simulating spatiotemporal dynamic changes in global vegetation conditions over a long time series.

Vegetation dynamics and its response to climate change in Central Asia

The plant ecosystems are particularly sensitive to climate change in arid and semi-arid regions. However, the responses of vegetation dynamics to climate change in Central Asia are still unclear. In this study, we used the normalized difference vegetation index（NDVI） data to analyze the spatial-temporal changes of vegetation and the correlation of vegetation and climatic variables over the period of 1982–2012 in Central Asia by using the empirical orthogonal function and least square methods. The results showed that the annual NDVI in Central Asia experienced a weak increasing trend overall during the study period. Specifically, the annual NDVI showed a significant increasing trend between1982 and 1994, and exhibited a decreasing trend since 1994. The regions where the annual NDVI decreased were mainly distributed in western Central Asia, which may be caused by the decreased precipitation. The NDVI exhibited a larger increasing trend in spring than in the other three seasons. In mountainous areas, the NDVI had a significant increasing trend at the annual and seasonal scales; further, the largest increasing trend of NDVI mainly appeared in the middle mountain belt（1,700–2,650 m asl）. The annual NDVI was positively correlated with annual precipitation in Central Asia, and there was a weak negative correlation between annual NDVI and temperature. Moreover, a one-month time lag was found in the response of NDVI to temperature from June to September in Central Asia during 1982–2012.

Improving Simulations of Vegetation Dynamics over the Tibetan Plateau:Role of Atmospheric Forcing Data and Spatial Resolution

The efficacy of vegetation dynamics simulations in offline land surface models(LSMs)largely depends on the quality and spatial resolution of meteorological forcing data.In this study,the Princeton Global Meteorological Forcing Data(PMFD)and the high spatial resolution and upscaled China Meteorological Forcing Data(CMFD)were used to drive the Simplified Simple Biosphere model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics(SSiB4/TRIFFID)and investigate how meteorological forcing datasets with different spatial resolutions affect simulations over the Tibetan Plateau(TP),a region with complex topography and sparse observations.By comparing the monthly Leaf Area Index(LAI)and Gross Primary Production(GPP)against observations,we found that SSiB4/TRIFFID driven by upscaled CMFD improved the performance in simulating the spatial distributions of LAI and GPP over the TP,reducing RMSEs by 24.3%and 20.5%,respectively.The multi-year averaged GPP decreased from 364.68 gC m^(-2)yr^(-1)to 241.21 gC m^(-2)yr^(-1)with the percentage bias dropping from 50.2%to-1.7%.When using the high spatial resolution CMFD,the RMSEs of the spatial distributions of LAI and GPP simulations were further reduced by 7.5%and 9.5%,respectively.This study highlights the importance of more realistic and high-resolution forcing data in simulating vegetation growth and carbon exchange between the atmosphere and biosphere over the TP.

Impact of anthropogenic activities on vegetation dynamics in a reservoir area: model establishment and a case study of Longkaikou Reservoir in China

Vegetation in hot and arid valleys is a crucial indicator of ecosystem health,but is vulnerable to human activities and environmental change.Using the Longkaikou Reservoir in the Jinsha River in southwestern China as a case study,we developed a spatially explicit model that combined the plant growth,fruiting,seed dispersal,and seed germination stages to reveal the potential impact of multiple human activities(reservoir construction,logging,grazing,and aerial seeding) on the vegetation dynamics of Dodonaea viscosa and Pinus yunnanensis.After reservoir construction,the grassland area of 68 km^(2) in 2003 decreased to 24 km^(2) in 2018,replaced by forest,shrubland,and bodies of water,and the precipitation increased during the dry season,which indicated the improvement of the local plant and soil environment.Our model predicted that when soil moisture decreased by more than 20% compared to current levels,the area of D.viscosa increased greatly at low elevations;however,when at higher soil moisture,P.yunnanensis would occupy more of the study area.Logging and grazing would slightly change the spatial pattern of vegetation and delay P.yunnanensis communities from achieving stability by directly reducing plant biomass.Countermeasures such as aerial seeding would increase the total area by 13.13 km^(2) and 8.09 km^(2) of two plants,respectively,and accelerate the stabilization of plant communities.The effects of multiple human activities on vegetation may counteract each other;for example,logging decreased the P.yunnanensis area whereas aerial seeding increased it,and plant biomass changed in response to this pressure.Given the complex relationships between vegetation and human impacts,our study provides a scientific basis for vegetation restoration and ecological security in this hot and arid valley.

Vegetation dynamics and its response to driving factors in typical karst regions,Guizhou Province,China

Analyzing the vegetation dynamics and its response to driving factors provides a vital reference for understanding regional ecological processes and ecosystem services.However,this issue has been poorly understood in karst areas.Taking Guizhou Province as a case study,based on the Normalized-Difference Vegetation Index of the Global Inventory Modeling and Mapping Studies and on meteorological data sets during 1982-2015,we evaluated vegetation dynamics and its response to climatic factors and human activities.We used several methods:the Mann-Kendall test,rescaled range analysis,partial correlation analysis,and residual analysis.The results are as follows:1)the mean annual Normalized-Difference Vegetation Index was 0.46 and exhibited a significant increasing trend with a variation rate of 0.01/10a during 1982-2015 in Guizhou Province.The vegetation cover showed was spatially heterogeneous:High vegetation cover was distributed mainly in the center and western margin of the study area,while the other parts of the study area mainly distributed with low vegetation cover,although the vegetation cover was higher in the nonkarst areas than in the karst areas;2)in general,the climate was getting warmer and drier in Guizhou Province during 1982-2015.Vegetation cover was positively correlated with temperature and negatively correlated with precipitation.Compared to precipitation,temperature was the dominant climatic factor impacting vegetation dynamics;3)'large-scale ecological restoration projects have obviously increased vegetation cover in Guizhou Province in recent years.The contribution of human activities to vegetation changes was 76%,while the contribution of climatic factors was 24%.In summary,compared to natural forces such as climatic factors and geographic parameters,human activities were the main factor driving the vegetation dynamics in Guizhou Province.

Vegetation dynamics and its response to climate change during the past 2000 years in the Altai Mountains,northwestern China

Over the past 2000 years,a high-resolution pollen record from the Yushenkule Peat(46°45′-46°57′N,90°46′-90°61′E,2374 m a.s.l.)in the south-eastern Altai Mountains of northwestern China has been used to explore the changes in vegetation and climate.The regional vegetation has been dominated by alpine meadows revealed from pollen diagrams over the past 2000 years.The pollen-based climate was warm and wet during the Roman Warm Period(0-520 AD),cold and wet during the Dark Age Cold Period(520-900 AD),warm and wet during the Medieval Warm Period(900-1300 AD),and cold and dry during the Little Ice Age(1300-1850 AD).Combined with other pollen data from the Altai Mountains,we found that the percentage of arboreal pollen showed a reduced trend along the NW-SE gradient with decreasing moisture and increasing climatic continentality of the Altai Mountains over the past 2000 years;this is consistent with modern distributions of taiga forests.We also found that the taiga(Pinus forest)have spread slightly,while the steppe(Artemisia,Poaceae and Chenopodiaceae)have recovered significantly in the Altai Mountains over the past 2000 years.In addition,the relatively warm-wet climate may promote high grassland productivity and southward expansion of steppe,which favors the formation of Mongol political and military power.

Spatio-temporal variations in trends of vegetation and drought changes in relation to climate variability from 1982 to 2019 based on remote sensing data from East Asia

Studying the significant impacts on vegetation of drought due to global warming is crucial in order to understand its dynamics and interrelationships with temperature,rainfall,and normalized difference vegetation index(NDVI).These factors are linked to excesses drought frequency and severity on the regional scale,and their effect on vegetation remains an important topic for climate change study.East Asia is very sensitive and susceptible to climate change.In this study,we examined the effect of drought on the seasonal variations of vegetation in relation to climate variability and determined which growing seasons are most vulnerable to drought risk;and then explored the spatio-temporal evolution of the trend in drought changes in East Asia from 1982 to 2019.The data were studied using a series of several drought indexes,and the data were then classified using a heat map,box and whisker plot analysis,and principal component analysis.The various drought indexes from January to August improved rapidly,except for vegetation health index(VHI)and temperature condition index(TCI).While these indices were constant in September,they increased again in October,but in December,they showed a descending trend.The seasonal and monthly analysis of the drought indexes and the heat map confirmed that the East Asian region suffered from extreme droughts in 1984,1993,2007,and 2012among the study years.The distribution of the trend in drought changes indicated that more severe drought occurred in the northwestern region than in the southeastern area of East Asia.The drought tendency slope was used to describe the changes in drought events during 1982–2019 in the study region.The correlations among monthly precipitation anomaly percentage(NAP),NDVI,TCI,vegetation condition index(VCI),temperature vegetation drought index(TVDI),and VHI indicated considerably positive correlations,while considerably negative correlations were found among the three pairs of NDVI and VHI,TVDI and VHI,and NDVI and TCI.This ecological and climatic mechanism provides a good basis for the assessment of vegetation and drought-change variations within the East Asian region.This study is a step forward in monitoring the seasonal variation of vegetation and variations in drought dynamics within the East Asian region,which will serve and contribute to the better management of vegetation,disaster risk,and drought in the East Asian region.

Dynamics of mediterranean pine forests reforested after fires

Forest fires are frequent under a Mediterranean climate and have shaped the landscape of the region but are currently altered by human action and climate change.Fires have historically conditioned the presence of pine forests,depending on severity and forest regeneration.Regeneration of Mediterranean pine forests is not always successful,and a transition to shrublands or stands of resprouting species can occur,even after reforestation.This study analyses vegetation changes in two Mediterranean pine forests after severe fires and both reforested.The pines had difficulty to regenerate,even despite post-fire reforestation.The problem is the difficulty of young seedlings to survive,possibly due to increased summer drought.Problems are greater in pine species at the limit of their ecological tolerance:Pinus pinea had a much better recovery success while P.sylvestris and P.nigra virtually disappeared.Pinus pinaster had intermediate results but recovery was generally poor.A transition has taken place in many burnt areas to scrubland or to thickets of the resprouting Quercus rotundifolia,although it is not possible to know whether they will evolve into forests or remain in a sub climatic state.Resprouting species may increase fire severity but facilitates post-fire colonisation.Post-fire recovery difficulties are closely linked to issues of natural regeneration.Fire could initiate the disappearance of pine forests,but even in the absence of fire they may disappear in the long-term due to the lack of regeneration.Action is needed to increase the resilience of these forests,ensuring natural regeneration,and incorporating resprouting species in the understorey.

Monitoring vegetation drought in the nine major river basins of China based on a new developed Vegetation Drought Condition Index

The effect of global climate change on vegetation growth is variable.Timely and effective monitoring of vegetation drought is crucial for understanding its dynamics and mitigation,and even regional protection of ecological environments.In this study,we constructed a new drought index(i.e.,Vegetation Drought Condition Index(VDCI))based on precipitation,potential evapotranspiration,soil moisture and Normalized Difference Vegetation Index(NDVI)data,to monitor vegetation drought in the nine major river basins(including the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin,Yangtze River Basin,Southeast River Basin,Pearl River Basin,Southwest River Basin and Continental River Basin)in China at 1-month–12-month(T1–T12)time scales.We used the Pearson's correlation coefficients to assess the relationships between the drought indices(the developed VDCI and traditional drought indices including the Standardized Precipitation Evapotranspiration Index(SPEI),Standardized Soil Moisture Index(SSMI)and Self-calibrating Palmer Drought Severity Index(scPDSI))and the NDVI at T1–T12 time scales,and to estimate and compare the lag times of vegetation response to drought among different drought indices.The results showed that precipitation and potential evapotranspiration have positive and major influences on vegetation in the nine major river basins at T1–T6 time scales.Soil moisture shows a lower degree of negative influence on vegetation in different river basins at multiple time scales.Potential evapotranspiration shows a higher degree of positive influence on vegetation,and it acts as the primary influencing factor with higher area proportion at multiple time scales in different river basins.The VDCI has a stronger relationship with the NDVI in the Songhua River and Liaohe River Basin,Haihe River Basin,Yellow River Basin,Huaihe River Basin and Yangtze River Basin at T1–T4 time scales.In general,the VDCI is more sensitive(with shorter lag time of vegetation response to drought)than the traditional drought indices(SPEI,scPDSI and SSMI)in monitoring vegetation drought,and thus it could be applied to monitor short-term vegetation drought.The VDCI developed in the study can reveal the law of unclear mechanisms between vegetation and climate,and can be applied in other fields of vegetation drought monitoring with complex mechanisms.

Evaluation of the New Dynamic Global Vegetation Model in CAS-ESM

In the past several decades, dynamic global vegetation models（DGVMs） have been the most widely used and appropriate tool at the global scale to investigate vegetation-climate interactions. At the Institute of Atmospheric Physics, a new version of DGVM（IAP-DGVM） has been developed and coupled to the Common Land Model（CoLM） within the framework of the Chinese Academy of Sciences＇ Earth System Model（CAS-ESM）. This work reports the performance of IAP-DGVM through comparisons with that of the default DGVM of CoLM（CoLM-DGVM） and observations. With respect to CoLMDGVM, IAP-DGVM simulated fewer tropical trees, more ＂needleleaf evergreen boreal tree＂ and ＂broadleaf deciduous boreal shrub＂, and a better representation of grasses. These contributed to a more realistic vegetation distribution in IAP-DGVM,including spatial patterns, total areas, and compositions. Moreover, IAP-DGVM also produced more accurate carbon fluxes than CoLM-DGVM when compared with observational estimates. Gross primary productivity and net primary production in IAP-DGVM were in better agreement with observations than those of CoLM-DGVM, and the tropical pattern of fire carbon emissions in IAP-DGVM was much more consistent with the observation than that in CoLM-DGVM. The leaf area index simulated by IAP-DGVM was closer to the observation than that of CoLM-DGVM; however, both simulated values about twice as large as in the observation. This evaluation provides valuable information for the application of CAS-ESM, as well as for other model communities in terms of a comparative benchmark.

A spatial-explicit dynamic vegetation model that couples carbon,water,and nitrogen processes for arid and semiarid ecosystems

Arid and semiarid ecosystems, or dryland, are important to global biogeochemical cycles. Dryland＇s community structure and vegetation dynamics as well as biogeochemical cycles are sensitive to changes in climate and atmospheric composition. Vegetation dynamic models has been applied in global change studies, but the com- plex interactions among the carbon （C）, water, and nitrogen （N） cycles have not been adequately addressed in the current models. In this study, a process-based vegetation dynamic model was developed to study the responses of dryland ecosystems to environmental changes, emphasizing on the interactions among the C, water, and N proc- esses. To address the interactions between the C and water processes, it not only considers the effects of annual precipitation on vegetation distribution and soil moisture on organic matter （SOM） decomposition, but also explicitly models root competition for water and the water compensation processes. To address the interactions between C and N processes, it models the soil inorganic mater processes, such as N mineralization/immobilization, denitrifica- tion/nitrification, and N leaching, as well as the root competition for soil N. The model was parameterized for major plant functional types and evaluated against field observations.

Different Responses of Vegetation to Frozen Ground Degradation in the Source Region of the Yellow River from 1980 to 2018

Frozen ground degradation under a warming climate profoundly influences the growth of alpine vegetation in the source region of the Qinghai-Tibet Plateau.This study investigated spatiotemporal variations in the frozen ground distribution,the active layer thickness(ALT)of permafrost(PF)soil and the soil freeze depth(SFD)in seasonally frozen soil from 1980 to 2018 using the temperature at the top of permafrost(TTOP)model and Stefan equation.We compared the effects of these variations on vegetation growth among different frozen ground types and vegetation types in the source region of the Yellow River(SRYR).The results showed that approximately half of the PF area(20.37%of the SRYR)was projected to degrade into seasonally frozen ground(SFG)during the past four decades;furthermore,the areal average ALT increased by 3.47 cm/yr,and the areal average SFD decreased by 0.93 cm/yr from 1980 to 2018.Accordingly,the growing season Normalized Difference Vegetation Index(NDVI)presented an increasing trend of 0.002/10 yr,and the increase rate and proportion of areas with NDVI increase were largest in the transition zone where PF degraded to SFG(the PF to SFG zone).A correlation analysis indicated that variations in ALT and SFD in the SRYR were significantly correlated with increases of NDVI in the growing season.However,a rapid decrease in SFD(<-1.4 cm/10 yr)could have reduced the soil moisture and,thus,decreased the NDVI.The NDVI for most vegetation types exhibited a significant positive correlation with ALT and a negative correlation with SFD.However,the steppe NDVI exhibited a significant negative correlation with the SFD in the PF to SFG zone but a positive correlation in the SFG zone,which was mainly limited by water condition because of different change rates of the SFD.

The impact of Pinus halepensis afforestation on Mediterranean spontaneous vegetation:do soil treatment and canopy cover matter?

We investigated central Mediterranean Pinus halepensis plantations under semi-arid climate in order to evaluate the combined effect of soil treatment and afforestation practices on spontaneous plant species composition, richness and evenness, and on the trend and speed of vegetation dynamics. Phytosociological releves of three different plot typologies, i.e. （1） soil-treatment and plantation, （2） only soil-treatment, （3） no soil-treatment and no plantation, were compared by （a） multivari- ate analysis and （b） with reference to species richness and evenness. Moreover, in order to compare vegetation dynamics within the planta- tions with those ones ongoing in semi-natural garrigue communities, we compared life form and syntaxonomic spectra between phytosociological relev6s taken at 8 years of distance. DCA showed that floristic species composition and similarity are influenced by the canopy cover of Pine trees as well as by soil-treatment practices. Although species richness and evenness are not clearly related to neither soil treatment nor Pine afforestation, canopy cover clearly plays a major role： in fact, the highest Ph cover rates correspond to the lowest values of understory species richness. This is true also if only species of biogeographical/conservation interest are considered. Regarding vegetation dynamics, sites with dense Pine canopy cover evolve much slower than the adjacent garrigue communities. The same factors invoqued to explain the patterns of floristic composition and similarity （i.e. allelopathy and competition for light, water and nutrients） may also explain the lowering of diversity of therophytes and the strong decline of the cover perfomed by both therophytes and hemicryptophytes underneath the canopy of dense Ph plantations. Thus, in sites where Ph cover exceeds about 80%, thinning is recommended not only in order to accelerate succession, but also to give a natural ＇shape＇ to afforestations.

Improving the Vegetation Dynamic Simulation in a Land Surface Model by Using a Statistical-dynamic Canopy Interception Scheme

Canopy interception of incident precipitation, as a critical component of a forest＇s water budget, can affect the amount of water available to the soil, and ultimately vegetation distribution and function. In this paper, a statistical-dynamic approach based on leaf area index and statistical canopy interception is used to parameterize the canopy interception process. The statistical-dynamic canopy interception scheme is implemented into the Community Land Model with dynamic global vegetation model （CLM-DGVM） to improve its dynamic vegetation simulation. The simulation for continental China by the land surface model with the new canopy interception scheme shows that the new one reasonably represents the precipitation intercepted by the canopy. Moreover, the new scheme enhances the water availability in the root zone for vegetation growth, especially in the densely vegetated and semi-arid areas, and improves the model＇s performance of potential vegetation simulation.

Evaluating the Dependence of Vegetation on Climate in an Improved Dynamic Global Vegetation Model

The capability of an improved Dynamic Global Vegetation Model （DGVM） in reproducing the impact of climate on the terrestrial ecosystem is evaluated. The new model incorporates the Community Land Model- DGVM （CLM3.0-DGVM） with a submodel for temperate and boreal shrubs, as well as other revisions such as the ＂two-leaf＂ scheme for photosynthesis and the definition of fractional coverage of plant functional types （PFTs）. Results show that the revised model may correctly reproduce the global distribution of temperate and boreal shrubs, and improves the model performance with more realistic distribution of di？erent vege- tation types. The revised model also correctly reproduces the zonal distributions of vegetation types. In reproducing the dependence of the vegetation distribution on climate conditions, the model shows that the dominant regions for trees, grasses, shrubs, and bare soil are clearly separated by a climate index derived from mean annual precipitation and temperature, in good agreement with the CLM4 surface data. The dominant plant functional type mapping to a two dimensional parameter space of mean annual temperature and precipitation also qualitatively agrees with the results from observations and theoretical ecology studies.

Development of the IAP Dynamic Global Vegetation Model

ABSTRACT The lAP Dynamic Global Vegetation Model （IAP-DGVM） has been developed to simulate the distribution and structure of global vegetation within the framework of Earth System Models. It incorporates our group＇s recent developments of major model components such as the shrub sub-model, establishment and competition parameterization schemes, and a process-based fire parameterization of intermediate complexity. The model has 12 plant functional types, including seven tree, two shrub, and three grass types, plus bare soil. Different PFTs are allowed to coexist within a grid cell, and their state variables are updated by various governing equations describing vegetation processes from fine-scale biogeophysics and biogeochemistry, to individual and population dynamics, to large-scale biogeography. Environmental disturbance due to fire not only affects regional vegetation competition, but also influences atmospheric chemistry and aerosol emissions. Simulations under observed atmospheric conditions showed that the model can correctly reproduce the global distribution of trees, shrubs, grasses, and bare soil. The simulated global dominant vegetation types reproduce the transition from forest to grassland （savanna） in the tropical region, and from forest to shrubland in the boreal region, but overestimate the region of temperate forest.

Improvements of a Dynamic Global Vegetation Model and Simulations of Carbon and Water at an Upland-Oak Forest

The interest in the development and improvement of dynamic global vegetation models （DGVMs）, which have the potential to simulate fluxes of carbon, water and nitrogen, along with changes in the vegetation dynamics, within an integrated system, has been increasing. In this paper, some numerical schemes and a higher resolution soil texture dataset were employed to improve the Sheffield Dynamic Global Vegetation Model （SDGVM）. Using eddy covariance-based measurements, we then tested the standard version of the SDGVM and the modified version of the SDGVM. Detailed observations of daily carbon and water fluxes made at the upland oak forest on the Walker Branch Watershed in Tennessee, USA offered a unique opportunity for these comparisons. The results revealed that the modified version of the SDGVM did a reasonable job of simulating the carbon and water flux and the variation of soil water content （SWC）. However, at the end of the growing season, it failed to simulate the effect of the limitations on the soil respiration dynamics and as a result underestimated this respiration. It was also noted that the modified version overestimated the increase in the SWC following summer rainfall, which was attributed to an inadequate representation of the ground water and thermal cycle.

Sensitivity of the Carbon Storage of Potential Vegetation to Historical Climate Variability and CO_2 in Continental China

The interest in the national levels of the terrestrial carbon sink and its spatial and temporal variability with the climate and CO2 concentrations has been increasing. How the climate and the increasing atmospheric CO2 concentrations in the last century affect the carbon storage in continental China was investigated in this study by using the Modified Sheffield Dynamic Global Vegetation Model （M-SDGVM）. The estimates of the M-SDGVM indicated that during the past 100 years a combination of increasing CO2 with historical temperature and precipitation variability in continental China have caused the total vegetation carbon storage to increase by 2.04 Pg C, with 2.07 Pg C gained in the vegetation biomass but 0.03 Pg C lost from the organic soil carbon matter. The increasing CO2 concentration in the 20th century is primarily responsible for the increase of the total potential vegetation carbon. These factorial experiments show that temperature variability alone decreases the total carbon storage by 1.36 Pg C and precipitation variability alone causes a loss of 1.99 Pg C. The effect of the increasing CO2 concentration alone increased the total carbon storage in the potential vegetation of China by 3.22 Pg C over the past 100 years. With the changing of the climate, the CO2 fertilization on China＇s ecosystems is the result of the enhanced net biome production （NBP）, which is caused by a greater stimulation of the gross primary production （GPP） than the total soil-vegetation respiration. Our study also shows notable interannual and decadal variations in the net carbon exchange between the atmosphere and terrestrial ecosystems in China due to the historical climate variability.

Impact of Spin-up Forcing on Vegetation States Simulated by a Dynamic Global Vegetation Model Coupled with a Land Surface Model

A dynamic global vegetation model （DGVM） coupled with a land surface model （LSM） is generally initialized using a spin-up process to derive a physically-consistent initial condition. Spin-up forcing, which is the atmospheric forcing used to drive the coupled model to equilibrium solutions in the spin-up process, varies across earlier studies. In the present study, the impact of the spin-up forcing in the initialization stage on the fractional coverages （FCs） of plant functional type （PFT） in the subsequent simulation stage are assessed in seven classic climate regions by a modified Community Land Model’s Dynamic Global Vegetation Model （CLM-DGVM）. Results show that the impact of spin-up forcing is considerable in all regions except the tropical rainforest climate region （TR） and the wet temperate climate region （WM）. In the tropical monsoon climate region （TM）, the TR and TM transition region （TR-TM）, the dry temperate climate region （DM）, the highland climate region （H）, and the boreal forest climate region （BF）, where FCs are affected by climate non-negligibly, the discrepancies in initial FCs, which represent long-term cumulative response of vegetation to different climate anomalies, are large. Moreover, the large discrepancies in initial FCs usually decay slowly because there are trees or shrubs in the five regions. The intrinsic growth timescales of FCs for tree PFTs and shrub PFTs are long, and the variation of FCs of tree PFTs or shrub PFTs can affect that of grass PFTs.

Spatial-temporal dynamics of alpine grassland coverage and its response to climate warming in Mt.Qomolangma Nature Preserve during 2000-2019

The Qinghai-Tibet Plateau(QTP)has the largest and highest alpine grassland ecosystem in the world,which is considered to be the most sensitive and vulnerable ecosystem to climate change.Its dynamic changes and driving mechanism have always been widely researched.The Qomolangma National Nature Preserve(QNNP),with the largest altitude difference in the world,was selected as the study area to analyse the spatial-temporal dynamics of grassland coverage and the different characteristics of elevation gradients at the southern slope(SS)and northern slope(NS)with MODIS MOD13Q1 NDVI and MOD11A2 land surface temperature data from 2000to 2019 using the Mann-Kendall trend test and Theil-Sen slope methods.Further,the response mechanism of grassland coverage to climate warming is discussed.The results revealed that from 2000 to 2019,the grassland coverage change in the study area is mainly stable.The increased area proportion of grassland coverage on the southern slope is significantly higher than that on the northern slope,and the decreased area proportion of grassland coverage on the northern slope is significantly greater than that on the southern slope.The change characteristics of grassland coverage in the QNNP exhibit an obvious elevation gradient;the higher the elevation,the greater the increased area proportion of grassland coverage,particularly on the SS.The land surface temperature can be used as a proxy for analysing the temporal and spatial variation trends of air temperature in the QNNP.With the increase of the altitude,the land surface temperature rise rate on both the southern slope and northern slope exhibited an increasing trend,and the sensitivity of grassland coverage to temperature rise was higher on the northern slope.The water condition was the decisive factor for the horizontal and vertical spatial heterogeneity of the dynamic change of grassland coverage,and the melting of glaciers and thawing of permafrost were important sources of water for grassland growth in the QNNP.Climate warming promotes the growth of grassland in areas with a sufficient water supply,but adversely affects the growth of grassland in areas with insufficient water supplies,which will be further intensified by human activities.