植被与气候之间的相互作用是一个复杂的过程,为了研究植被与气候之间相互作用的机理和评价气候变化对植被影响,植被模型得以迅速发展,并从静态的植被模型发展到了动态全球植被模型(Dynamic Global Vegetation Model,DGVM)。DGVM主要模...植被与气候之间的相互作用是一个复杂的过程,为了研究植被与气候之间相互作用的机理和评价气候变化对植被影响,植被模型得以迅速发展,并从静态的植被模型发展到了动态全球植被模型(Dynamic Global Vegetation Model,DGVM)。DGVM主要模拟植被的生理过程、植被动态、植被物候和营养物质循环,包括动态的生物地球化学模型和动态的生物地球物理模型两类。国际上应用最广泛的DGVM有LPJI、BIS、VECODE和TRIFFID等。目前DGVM研究的焦点主要有4个:①模型本身的完善;②不同模型比较研究;③与气候模型的耦合研究;④碳数据同化系统研究。展开更多
Priority Areas of Biodiversity Conservation(PABCs) are the key areas for future biodiversity conservation in China. In this study, we used 5 dynamic global vegetation models(DGVMs) to simulate the ecosystem function c...Priority Areas of Biodiversity Conservation(PABCs) are the key areas for future biodiversity conservation in China. In this study, we used 5 dynamic global vegetation models(DGVMs) to simulate the ecosystem function changes under future climate change scenario in the 32 terrestrial PABCs. We selected vegetation coverage,vegetation productivity, and ecosystem carbon balance as the indicators to describe the ecosystem function changes.The results indicate that woody vegetation coverage will greatly increase in the Loess Plateau Region, the North China Plain, and the Lower Hilly Region of South China.The future climate change will have great impact on the original vegetation in alpine meadow and arid and semiarid regions. The vegetation productivity of most PABCs will enhance in the coming 100 years. The largest increment will take place in the southwestern regions with high elevation. The PABCs in the Desert Region of InnerMongolia-Xinjiang Plateau are with fastest productivity climbing, and these areas are also with more carbon sink accumulation in the future. DGVM will be a new efficient tool for evaluating ecosystem function changes in future in large scale. This study is expected to provide technical support for the future ecosystem management and biodiversity conservation under climate change.展开更多
Earth System Models （ESMs） are fundamental tools for understanding climate-carbon feedback. An ESM version of the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） was recently developed within the IPCC ...Earth System Models （ESMs） are fundamental tools for understanding climate-carbon feedback. An ESM version of the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） was recently developed within the IPCC AR5 Coupled Model Intercomparison Project Phase 5 （CMIP5） modeling framework, and we describe the development of this model through the coupling of a dynamic global vegetation and terrestrial carbon model with FGOALS-s2. The performance of the coupled model is evaluated as follows. The simulated global total terrestrial gross primary production （GPP） is 124.4 PgC yr-I and net pri- mary production （NPP） is 50.9 PgC yr-1. The entire terrestrial carbon pools contain about 2009.9 PgC, comprising 628.2 PgC and 1381.6 PgC in vegetation and soil pools, respectively. Spatially, in the tropics, the seasonal cycle of NPP and net ecosystem production （NEP） exhibits a dipole mode across the equator due to migration of the monsoon rainbelt, while the seasonal cycle is not so significant in Leaf Area Index （LAI）. In the subtropics, especially in the East Asian monsoon region, the seasonal cycle is obvious due to changes in temperature and precipitation from boreal winter to summer. Vegetation productivity in the northern mid-high latitudes is too low, possibly due to low soil moisture there. On the interannual timescale, the terrestrial ecosystem shows a strong response to ENSO. The model- simulated Nifio3.4 index and total terrestrial NEP are both characterized by a broad spectral peak in the range of 2-7 years. Further analysis indicates their correlation coefficient reaches -0.7 when NEP lags the Nifio3.4 index for about 1-2 months.展开更多
为评估吉林省落叶松林的生产力现状并为我国森林生态系统生产力和植被监测研究提供基础数据,以吉林省落叶松林为研究对象,基于吉林省及其周边100 km范围内41个气象站点资料,采用LPJ-DGVM模型模拟了2000-2019年吉林省落叶松林近20年的净...为评估吉林省落叶松林的生产力现状并为我国森林生态系统生产力和植被监测研究提供基础数据,以吉林省落叶松林为研究对象,基于吉林省及其周边100 km范围内41个气象站点资料,采用LPJ-DGVM模型模拟了2000-2019年吉林省落叶松林近20年的净初级生产力,并采用线性回归趋势分析、变异系数、Hurst指数和相关性分析法对其时空变化、稳定性及其与气候因子的相关关系进行了分析。结果表明:(1)2000-2019年吉林省落叶松林年均净初级生产力(NPP)为592 g C m^(-2)a^(-1),年均增长率为2.81%,随时间推移呈现波动增长的趋势(β=14.55,R^(2)=0.784,P<0.01)。(2)NPP变异系数为0.07-2.33,均值为0.48,除幼龄林外,整体波动较小。Hurst指数介于0.441-0.849之间,均值为0.612,未来吉林省落叶松林NPP呈增加趋势。(3)吉林省落叶松林NPP存在明显的空间异质性,北部和南部区域NPP较高,是近20年NPP增长较快的区域。(4)2000-2019年吉林省落叶松林年均NPP与年总降水、生长季降水量之间均不显著(P>0.05),与年均温呈显著正相关(P<0.05),与生长季均温为极显著正相关(P<0.01),该阶段内温度比降水更能对吉林省落叶松林NPP的年际变化产生影响。LPJ模型模拟吉林省落叶松林2000-2019年NPP与样地实测值极显著相关(P<0.01),可以用于模拟吉林省落叶松林的NPP。展开更多
The abilities of 12 earth system models（ESMs） from the Coupled Model Intercomparison Project Phase5（CMIP5） to reproduce satellite-derived vegetation biological variables over the Tibetan Plateau（TP） were examine...The abilities of 12 earth system models（ESMs） from the Coupled Model Intercomparison Project Phase5（CMIP5） to reproduce satellite-derived vegetation biological variables over the Tibetan Plateau（TP） were examined.The results show that most of the models tend to overestimate the observed leaf area index（LAI）and vegetation carbon above the ground,with the possible reasons being overestimation of photosynthesis and precipitation.The model simulations show a consistent increasing trend with observed LAI over most of the TP during the reference period of 1986-2005,while they fail to reproduce the downward trend around the headstream of the Yellow River shown in the observation due to their coarse resolutions.Three of the models：CCSM4,CESM1-BGC,and NorESM1-ME,which share the same vegetation model,show some common strengths and weaknesses in their simulations according to our analysis.The model ensemble indicates a reasonable spatial distribution but overestimated land coverage,with a significant decreasing trend（-1.48%per decade） for tree coverage and a slight increasing trend（0.58%per decade） for bare ground during the period 1950-2005.No significant sign of variation is found for grass.To quantify the relative performance of the models in representing the observed mean state,seasonal cycle,and interannual variability,a model ranking method was performed with respect to simulated LAI.INMCM4,bcc-csm-1.1m,MPI-ESM-LR,IPSL CM5A-LR,HadGEM2-ES,and CCSM4 were ranked as the best six models in reproducing vegetation dynamics among the 12 models.展开更多
Environmental changes are expected to shift the distribution and abundance of vegetation by determining seedling estab- lishment and success. However, most current ecosystem models only focus on the impacts of abiotic...Environmental changes are expected to shift the distribution and abundance of vegetation by determining seedling estab- lishment and success. However, most current ecosystem models only focus on the impacts of abiotic factors on biogeophysics （e.g., global distribution, etc.）, ignoring their roles in the population dynamics （e.g., seedling establishment rate, mortality rate, etc.） of ecological communities. Such neglect may lead to biases in ecosystem population dynamics （such as changes in population density for woody species in forest ecosystems） and characteristics. In the present study, a new establishment scheme for introducing soil water as a function rather than a threshold was developed and validated, using version 1.0 of the IAP-DGVM as a test bed. The results showed that soil water in the establishment scheme had a remarkable influence on forest transition zones. Compared with the original scheme, the new scheme significantly improved simulations of tree population density, especially in the peripheral areas of forests and transition zones. Consequently, biases in forest fractional coverage were reduced in approximately 78.8% of the global grid cells. The global simulated areas of tree, shrub, grass and bare soil performed better, where the relative biases were reduced from 34.3% to 4.8%, from 27.6% to 13.1%, from 55.2% to 9.2%, and from 37.6% to 3.6%, respectively. Furthermore, the new scheme had more reasonable dependencies of plant functional types （PFTs） on mean annual precipitation, and described the correct dominant PFTs in the tropical rainforest peripheral areas of the Amazon and central Africa.展开更多
The strategies of plant growth play an important role not only in ecosystem structure,but also in global carbon and water cycles.In this work,the individual carbon allocation scheme of tree PFTs and its impacts were e...The strategies of plant growth play an important role not only in ecosystem structure,but also in global carbon and water cycles.In this work,the individual carbon allocation scheme of tree PFTs and its impacts were evaluated in China with Institute of Atmospheric Physics-Dynamic Global Vegetation Model,version 1.0（IAP-DGVM1.0）as a test-bed.The results showed that,as individual growth,the current scheme tended to allocate an increasing proportion of annual net primary productivity（NPP）to sapwood and decreasing proportions to leaf and root accordingly,which led to underestimated individual leaf biomass and overestimated individual stem biomass.Such biases resulted in an overestimation of total ecosystem biomass and recovery time of mature forests,and an underestimation of ecosystem NPP and tree leaf area index in China.展开更多
文摘植被与气候之间的相互作用是一个复杂的过程,为了研究植被与气候之间相互作用的机理和评价气候变化对植被影响,植被模型得以迅速发展,并从静态的植被模型发展到了动态全球植被模型(Dynamic Global Vegetation Model,DGVM)。DGVM主要模拟植被的生理过程、植被动态、植被物候和营养物质循环,包括动态的生物地球化学模型和动态的生物地球物理模型两类。国际上应用最广泛的DGVM有LPJI、BIS、VECODE和TRIFFID等。目前DGVM研究的焦点主要有4个:①模型本身的完善;②不同模型比较研究;③与气候模型的耦合研究;④碳数据同化系统研究。
基金supported by the Environmental Protection Public Service Project of China(201209031)
文摘Priority Areas of Biodiversity Conservation(PABCs) are the key areas for future biodiversity conservation in China. In this study, we used 5 dynamic global vegetation models(DGVMs) to simulate the ecosystem function changes under future climate change scenario in the 32 terrestrial PABCs. We selected vegetation coverage,vegetation productivity, and ecosystem carbon balance as the indicators to describe the ecosystem function changes.The results indicate that woody vegetation coverage will greatly increase in the Loess Plateau Region, the North China Plain, and the Lower Hilly Region of South China.The future climate change will have great impact on the original vegetation in alpine meadow and arid and semiarid regions. The vegetation productivity of most PABCs will enhance in the coming 100 years. The largest increment will take place in the southwestern regions with high elevation. The PABCs in the Desert Region of InnerMongolia-Xinjiang Plateau are with fastest productivity climbing, and these areas are also with more carbon sink accumulation in the future. DGVM will be a new efficient tool for evaluating ecosystem function changes in future in large scale. This study is expected to provide technical support for the future ecosystem management and biodiversity conservation under climate change.
基金supported by the CAS Strategic Priority Research Program(Grant No.XDA05110303)the"973"programs(Grant Nos.2012CB417203 and 2010CB950404)+1 种基金the"863"program(Grant No.2010AA012305)the National Science Foundation of China(Grant Nos.41023002 and 40805038)
文摘Earth System Models （ESMs） are fundamental tools for understanding climate-carbon feedback. An ESM version of the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） was recently developed within the IPCC AR5 Coupled Model Intercomparison Project Phase 5 （CMIP5） modeling framework, and we describe the development of this model through the coupling of a dynamic global vegetation and terrestrial carbon model with FGOALS-s2. The performance of the coupled model is evaluated as follows. The simulated global total terrestrial gross primary production （GPP） is 124.4 PgC yr-I and net pri- mary production （NPP） is 50.9 PgC yr-1. The entire terrestrial carbon pools contain about 2009.9 PgC, comprising 628.2 PgC and 1381.6 PgC in vegetation and soil pools, respectively. Spatially, in the tropics, the seasonal cycle of NPP and net ecosystem production （NEP） exhibits a dipole mode across the equator due to migration of the monsoon rainbelt, while the seasonal cycle is not so significant in Leaf Area Index （LAI）. In the subtropics, especially in the East Asian monsoon region, the seasonal cycle is obvious due to changes in temperature and precipitation from boreal winter to summer. Vegetation productivity in the northern mid-high latitudes is too low, possibly due to low soil moisture there. On the interannual timescale, the terrestrial ecosystem shows a strong response to ENSO. The model- simulated Nifio3.4 index and total terrestrial NEP are both characterized by a broad spectral peak in the range of 2-7 years. Further analysis indicates their correlation coefficient reaches -0.7 when NEP lags the Nifio3.4 index for about 1-2 months.
文摘为评估吉林省落叶松林的生产力现状并为我国森林生态系统生产力和植被监测研究提供基础数据,以吉林省落叶松林为研究对象,基于吉林省及其周边100 km范围内41个气象站点资料,采用LPJ-DGVM模型模拟了2000-2019年吉林省落叶松林近20年的净初级生产力,并采用线性回归趋势分析、变异系数、Hurst指数和相关性分析法对其时空变化、稳定性及其与气候因子的相关关系进行了分析。结果表明:(1)2000-2019年吉林省落叶松林年均净初级生产力(NPP)为592 g C m^(-2)a^(-1),年均增长率为2.81%,随时间推移呈现波动增长的趋势(β=14.55,R^(2)=0.784,P<0.01)。(2)NPP变异系数为0.07-2.33,均值为0.48,除幼龄林外,整体波动较小。Hurst指数介于0.441-0.849之间,均值为0.612,未来吉林省落叶松林NPP呈增加趋势。(3)吉林省落叶松林NPP存在明显的空间异质性,北部和南部区域NPP较高,是近20年NPP增长较快的区域。(4)2000-2019年吉林省落叶松林年均NPP与年总降水、生长季降水量之间均不显著(P>0.05),与年均温呈显著正相关(P<0.05),与生长季均温为极显著正相关(P<0.01),该阶段内温度比降水更能对吉林省落叶松林NPP的年际变化产生影响。LPJ模型模拟吉林省落叶松林2000-2019年NPP与样地实测值极显著相关(P<0.01),可以用于模拟吉林省落叶松林的NPP。
基金Supported by the National Basic Research and Development (973) Program of China(2010CB950503 and 2013CB956004)Research Fund for Climate Change of the China Meteorological Administration(CCSF201403)
文摘The abilities of 12 earth system models（ESMs） from the Coupled Model Intercomparison Project Phase5（CMIP5） to reproduce satellite-derived vegetation biological variables over the Tibetan Plateau（TP） were examined.The results show that most of the models tend to overestimate the observed leaf area index（LAI）and vegetation carbon above the ground,with the possible reasons being overestimation of photosynthesis and precipitation.The model simulations show a consistent increasing trend with observed LAI over most of the TP during the reference period of 1986-2005,while they fail to reproduce the downward trend around the headstream of the Yellow River shown in the observation due to their coarse resolutions.Three of the models：CCSM4,CESM1-BGC,and NorESM1-ME,which share the same vegetation model,show some common strengths and weaknesses in their simulations according to our analysis.The model ensemble indicates a reasonable spatial distribution but overestimated land coverage,with a significant decreasing trend（-1.48%per decade） for tree coverage and a slight increasing trend（0.58%per decade） for bare ground during the period 1950-2005.No significant sign of variation is found for grass.To quantify the relative performance of the models in representing the observed mean state,seasonal cycle,and interannual variability,a model ranking method was performed with respect to simulated LAI.INMCM4,bcc-csm-1.1m,MPI-ESM-LR,IPSL CM5A-LR,HadGEM2-ES,and CCSM4 were ranked as the best six models in reproducing vegetation dynamics among the 12 models.
基金supported by the project of the National Natural Science Foundation of China(Grant No.41305098)the Chinese Academy of Sciences Strategic Priority Research Program(Grant No.XDA05110103)the National Natural Science Foundation of China(Grant No.41305096)
文摘Environmental changes are expected to shift the distribution and abundance of vegetation by determining seedling estab- lishment and success. However, most current ecosystem models only focus on the impacts of abiotic factors on biogeophysics （e.g., global distribution, etc.）, ignoring their roles in the population dynamics （e.g., seedling establishment rate, mortality rate, etc.） of ecological communities. Such neglect may lead to biases in ecosystem population dynamics （such as changes in population density for woody species in forest ecosystems） and characteristics. In the present study, a new establishment scheme for introducing soil water as a function rather than a threshold was developed and validated, using version 1.0 of the IAP-DGVM as a test bed. The results showed that soil water in the establishment scheme had a remarkable influence on forest transition zones. Compared with the original scheme, the new scheme significantly improved simulations of tree population density, especially in the peripheral areas of forests and transition zones. Consequently, biases in forest fractional coverage were reduced in approximately 78.8% of the global grid cells. The global simulated areas of tree, shrub, grass and bare soil performed better, where the relative biases were reduced from 34.3% to 4.8%, from 27.6% to 13.1%, from 55.2% to 9.2%, and from 37.6% to 3.6%, respectively. Furthermore, the new scheme had more reasonable dependencies of plant functional types （PFTs） on mean annual precipitation, and described the correct dominant PFTs in the tropical rainforest peripheral areas of the Amazon and central Africa.
基金supported by a project of the National Natural Science Foundation of China[grant number 41305098]Strategic Priority research Program of the Chinese Academy of Sciences[grant numbers XDA05110103 and XDA05110201]
文摘The strategies of plant growth play an important role not only in ecosystem structure,but also in global carbon and water cycles.In this work,the individual carbon allocation scheme of tree PFTs and its impacts were evaluated in China with Institute of Atmospheric Physics-Dynamic Global Vegetation Model,version 1.0（IAP-DGVM1.0）as a test-bed.The results showed that,as individual growth,the current scheme tended to allocate an increasing proportion of annual net primary productivity（NPP）to sapwood and decreasing proportions to leaf and root accordingly,which led to underestimated individual leaf biomass and overestimated individual stem biomass.Such biases resulted in an overestimation of total ecosystem biomass and recovery time of mature forests,and an underestimation of ecosystem NPP and tree leaf area index in China.
