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
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
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
Terrestrial vegetation is a crucial component of the Earth system,and its changes not only represent one of the most distinct aspects of climate change but also exert significant feedback within the climate system by ...Terrestrial vegetation is a crucial component of the Earth system,and its changes not only represent one of the most distinct aspects of climate change but also exert significant feedback within the climate system by exchanging energy,moisture,and carbon dioxide.To quantitatively and mechanistically study climate-vegetation feedback,numerical vegetation models have been developed on the theory of ecophysiological constraints on plant functional types.The models eventually can simulate vegetation distribution and succession across different spatial and temporal scales,and associated terrestrial carbon cycle processes by categorizing vegetation into biomes according different plant functional types and their associated environmental factors.Here we review the developing history of vegetation models and provide recent advances and future directions.Before 21st century,static vegetation models,as developed statistical models,can only simulate equilibrated characteristics of vegetation distribution.In last several decades,Dynamic Global Vegetation Models(DGVMs)have been developed to simulate instantaneous responses of vegetation to climate change and associated dynamics,and can be coupled with Earth system models to investigate interactions among atmosphere,ocean,and land.DGVMs are also widely applied to investigate the dynamics accounting for changes in the geographic distribution patterns of land surface vegetation at different spatial and temporal scales and to assess the impacts of terrestrial carbon and water fluxes and land use changes.We suggest that future vegetation modeling could integrate with machine learning,and explore vegetation transient response and feedback as well as impacts of process hierarchies and human activities on climate and ecosystem.展开更多
陆地植被是地球系统的重要组成部分,其变化既是气候变化最鲜明的反应和标志之一,又通过能量、水分和二氧化碳的交换对气候系统内部产生重要的反馈.为了定量且机理性地研究植被与气候之间的双向反馈,植被模型得以迅速发展.植被模型以植...陆地植被是地球系统的重要组成部分,其变化既是气候变化最鲜明的反应和标志之一,又通过能量、水分和二氧化碳的交换对气候系统内部产生重要的反馈.为了定量且机理性地研究植被与气候之间的双向反馈,植被模型得以迅速发展.植被模型以植物功能型的生态生理限定性为理论基础,通过将植被按照植物功能型及其关联的环境因子归并到生物群区,模拟它在不同时空尺度上的分布和演替,并进而深入探究陆地碳循环过程.本文回顾植被模型的发展历程,并提出未来发展的建议.在统计模型基础上发展起来的静态植被模型只能模拟植被与气候背景达到平衡状态下的分布特征,而全球动态植被模型(Dynamic Global Vegetation Models, DGVMs)能模拟植被对气候变化的瞬时响应和长期动态变化,并可耦合于地球系统模式中模拟大气-海洋-陆地的相互作用以及地球系统的变化.目前DGVMs应用广泛,主要集中在模拟不同时空尺度陆表植被地理分布格局的动态变化,以及估算陆地碳水通量及土地利用变化的影响等方面.未来植被模型可围绕植被模式层级、古植被瞬变模拟、人类活动的影响和机器学习等方面进行改进与发展.展开更多
动态全球植被模型(dynamic global vegetation models,DGVMs)在模拟和预测陆地生态系统对气候变化响应中表现出很大的不确定性,重要原因之一在于动态全球植被模型将定义植物功能型的性状值设置为常数,忽略了植物功能性状对环境变化的响...动态全球植被模型(dynamic global vegetation models,DGVMs)在模拟和预测陆地生态系统对气候变化响应中表现出很大的不确定性,重要原因之一在于动态全球植被模型将定义植物功能型的性状值设置为常数,忽略了植物功能性状对环境变化的响应.动态全球植被模型现有的植物功能型框架已经严重地阻碍了其发展,因此迫切需要一种新的方法来克服这种局限性.植物功能性状不仅可以反映植物对环境连续变化的响应,而且与生态系统的结构和功能密切相关,可提升当前动态全球植被模型对生态系统过程的模拟和功能的预测.本文从动态全球植被模型发展和植物功能型局限性入手,详细介绍了植物功能性状发展现状及其对动态全球植被模型改进的重要价值,归纳总结了植物功能性状对动态全球植被模型改进的主要方法,并指明植物功能性状对动态全球植被模型改进的发展方向.以期通过凝练植物功能性状在构建下一代动态全球植被模型中发挥作用,推动动态全球植被模型在我国的发展和应用.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
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
Vegetation dynamics could lead to changes in the global carbon and hydrology cycle,as well as feedbacks to climate change.This paper reviews the response of forest dynamics to climate change.Based on palaeoecological ...Vegetation dynamics could lead to changes in the global carbon and hydrology cycle,as well as feedbacks to climate change.This paper reviews the response of forest dynamics to climate change.Based on palaeoecological studies,we summarized the features and modes of vegetation response to climate change and categorized the impacts of climate change on vegetation dynamics as three types:climate stress on vegetation,buffer effects by non-climatic factors,and perturbation of the vegetation distribution by stochastic events.Due to the openness of the vegetation system and the integrated effects of both climatic and non-climatic factors,the vegetation-climate relationship deviates far from its equilibrium.The vegetation distribution shows a non-linear response to climate change,which also makes it difficult to quantify the modern vegetation distribution in terms of specific climatic factors.Past analog,space-for-time-substitution and Dynamic Global Vegetation Models(DGVMs)are three approaches to predicting the future vegetation distribution,but they have all been established on the assumption of vegetation-climate equilibrium.We propose that improving DGVMs is a future task for studies of vegetation dynamics because these are process-based models incorporating both disturbance(e.g.fire)and the variability in Plant Functional Types(PFTs).However,palaeoecological results should be used to test the models,and issues like spatial and temporal scale,complexity of climate change,effects of non-climatic factors,vegetation-climate feedback,and human regulation on vegetation dynamics are suggested as topics for future studies.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。
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 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.
基金supported by the China’s National Key Research and Development Projects(Grant No.2023YFF0805200)the National Natural Science Foundation of China(Grant Nos.41988101&42075047&31870462)+2 种基金the FORMAS of Sweden(Grant No.2020-02267)the Crafoord(Grant No.20220564)the National Key Scientific and Technological Infrastructure Project“Earth System Science Numerical Simulator Facility”(Earthlab)。
文摘Terrestrial vegetation is a crucial component of the Earth system,and its changes not only represent one of the most distinct aspects of climate change but also exert significant feedback within the climate system by exchanging energy,moisture,and carbon dioxide.To quantitatively and mechanistically study climate-vegetation feedback,numerical vegetation models have been developed on the theory of ecophysiological constraints on plant functional types.The models eventually can simulate vegetation distribution and succession across different spatial and temporal scales,and associated terrestrial carbon cycle processes by categorizing vegetation into biomes according different plant functional types and their associated environmental factors.Here we review the developing history of vegetation models and provide recent advances and future directions.Before 21st century,static vegetation models,as developed statistical models,can only simulate equilibrated characteristics of vegetation distribution.In last several decades,Dynamic Global Vegetation Models(DGVMs)have been developed to simulate instantaneous responses of vegetation to climate change and associated dynamics,and can be coupled with Earth system models to investigate interactions among atmosphere,ocean,and land.DGVMs are also widely applied to investigate the dynamics accounting for changes in the geographic distribution patterns of land surface vegetation at different spatial and temporal scales and to assess the impacts of terrestrial carbon and water fluxes and land use changes.We suggest that future vegetation modeling could integrate with machine learning,and explore vegetation transient response and feedback as well as impacts of process hierarchies and human activities on climate and ecosystem.
文摘陆地植被是地球系统的重要组成部分,其变化既是气候变化最鲜明的反应和标志之一,又通过能量、水分和二氧化碳的交换对气候系统内部产生重要的反馈.为了定量且机理性地研究植被与气候之间的双向反馈,植被模型得以迅速发展.植被模型以植物功能型的生态生理限定性为理论基础,通过将植被按照植物功能型及其关联的环境因子归并到生物群区,模拟它在不同时空尺度上的分布和演替,并进而深入探究陆地碳循环过程.本文回顾植被模型的发展历程,并提出未来发展的建议.在统计模型基础上发展起来的静态植被模型只能模拟植被与气候背景达到平衡状态下的分布特征,而全球动态植被模型(Dynamic Global Vegetation Models, DGVMs)能模拟植被对气候变化的瞬时响应和长期动态变化,并可耦合于地球系统模式中模拟大气-海洋-陆地的相互作用以及地球系统的变化.目前DGVMs应用广泛,主要集中在模拟不同时空尺度陆表植被地理分布格局的动态变化,以及估算陆地碳水通量及土地利用变化的影响等方面.未来植被模型可围绕植被模式层级、古植被瞬变模拟、人类活动的影响和机器学习等方面进行改进与发展.
文摘动态全球植被模型(dynamic global vegetation models,DGVMs)在模拟和预测陆地生态系统对气候变化响应中表现出很大的不确定性,重要原因之一在于动态全球植被模型将定义植物功能型的性状值设置为常数,忽略了植物功能性状对环境变化的响应.动态全球植被模型现有的植物功能型框架已经严重地阻碍了其发展,因此迫切需要一种新的方法来克服这种局限性.植物功能性状不仅可以反映植物对环境连续变化的响应,而且与生态系统的结构和功能密切相关,可提升当前动态全球植被模型对生态系统过程的模拟和功能的预测.本文从动态全球植被模型发展和植物功能型局限性入手,详细介绍了植物功能性状发展现状及其对动态全球植被模型改进的重要价值,归纳总结了植物功能性状对动态全球植被模型改进的主要方法,并指明植物功能性状对动态全球植被模型改进的发展方向.以期通过凝练植物功能性状在构建下一代动态全球植被模型中发挥作用,推动动态全球植被模型在我国的发展和应用.
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 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 National Natural Science Foundation of China(41071124 and 31021001)
文摘Vegetation dynamics could lead to changes in the global carbon and hydrology cycle,as well as feedbacks to climate change.This paper reviews the response of forest dynamics to climate change.Based on palaeoecological studies,we summarized the features and modes of vegetation response to climate change and categorized the impacts of climate change on vegetation dynamics as three types:climate stress on vegetation,buffer effects by non-climatic factors,and perturbation of the vegetation distribution by stochastic events.Due to the openness of the vegetation system and the integrated effects of both climatic and non-climatic factors,the vegetation-climate relationship deviates far from its equilibrium.The vegetation distribution shows a non-linear response to climate change,which also makes it difficult to quantify the modern vegetation distribution in terms of specific climatic factors.Past analog,space-for-time-substitution and Dynamic Global Vegetation Models(DGVMs)are three approaches to predicting the future vegetation distribution,but they have all been established on the assumption of vegetation-climate equilibrium.We propose that improving DGVMs is a future task for studies of vegetation dynamics because these are process-based models incorporating both disturbance(e.g.fire)and the variability in Plant Functional Types(PFTs).However,palaeoecological results should be used to test the models,and issues like spatial and temporal scale,complexity of climate change,effects of non-climatic factors,vegetation-climate feedback,and human regulation on vegetation dynamics are suggested as topics for future studies.
