The climate-vegetation interaction of China is mainly controlled by the atmospheric circulations and topographic characteristics. The distribution and NPP of vegetation zones show a close relationship with a series of...The climate-vegetation interaction of China is mainly controlled by the atmospheric circulations and topographic characteristics. The distribution and NPP of vegetation zones show a close relationship with a series of climatological indexes, such as annual mean temperature, precipitation, various thermal indexes, and potential evapotranspiration rates. The multivariate analysis (DCA) for climate and vegetation, zones in China provides quantitative environmental interpretation for two significant ecological gradients. The first gradient is mainly a thermal gradient, it can be displayed by latitude, altitude, biotemperature, and annual mean temperature. The second gradient is basically a moisture gradient, it correlated highly with longitude and potential evaportranspiration. The quantitative interaction or statistical models between vegetation zones and climato-geographical indexes can provide a fundamental scenario and comparative parameters for the study on climate and vegetation changes in China.展开更多
The Hengduan Mountains Region(HMR) is essential for the future ecological protection, clean energy production,Sichuan-Xizang and Yunnan-Xizang railways, and other major infrastructure projects in China. The distributi...The Hengduan Mountains Region(HMR) is essential for the future ecological protection, clean energy production,Sichuan-Xizang and Yunnan-Xizang railways, and other major infrastructure projects in China. The distributions of climate and vegetation exhibit significant regional differentiation and vertical zonality due to the rugged longitudinal ranges and gorges and the complex disaster-prone environments in HMR. Therefore, it is urgent to develop the climate-vegetation regionalization in HMR to effectively satisfy the national requirements such as agricultural production and ecological protection, mountain disaster risk prevention, and major project construction. We here develop a new scheme of climate-vegetation regionalization with the latest demarcation outcome of HMR, the ground observation from 122 meteorological stations in HMR and its surrounding areas during 1990–2019, and the high-precision remote sensing data of land cover types. The new scheme first constructs the regionalization index system, fully considering the extraordinarily complicated geomorphic pattern of mountains and valleys, the scarcity of meteorological observations, and the remarkable differentiation of climate and vegetation in HMR. The system consists of three primary regionalization indices(i.e., days with daily average temperature steady above 10°C, aridity index, and main vegetation types, dividing the temperature zones, moisture regions, and vegetation subregions, respectively) and three auxiliary indices of the accumulated temperature above 10°C, and the temperatures in January and July. Then, the HMR is divided into five temperature zones, 20 moisture regions, and 55 vegetation subregions. Compared with previous regionalization schemes, the new scheme optimizes the climate spatial interpolation model of thin plate smoothing spline suitable for the unique terrain in HMR. Moreover, the disputed division index threshold between different climatic zones(regions) is scientifically clarified using geographical detectors. Specifically, the stepwise downscaling pane division method is initially proposed to determine the zoning boundary, alleviating the excessive dependence of the traditional zoning method on subjective experience.Besides, the scheme considers the typical regional characteristics of the complex underlying surface and the high gradient zone of climate-vegetation distribution types in HMR. Consequently, the transition zone with quick climate changes between the plateau temperate and mid-subtropical zones is divided into mountainous subtropics, taking into account the spatial distribution characteristics of climate-vegetation regionalization indices. The regionalization scheme will provide practically theoretical support for agricultural production, ecological protection, major project construction, disaster prevention and relief efforts, and other socioeconomic activities in HMR, serving as a classic case of climate-vegetation regionalization for the alpine and canyon regions with intricate underlying surface, striking regional differences, and lack of ground observations.展开更多
Three phrases of the quantitative study of climate-vegetation classification and their characteristics are presented based on the review of advance in climate-vegetation interaction, a key issue of 'global change ...Three phrases of the quantitative study of climate-vegetation classification and their characteristics are presented based on the review of advance in climate-vegetation interaction, a key issue of 'global change and terrestrial ecosystems (GCTE)' which is the core project of International Geosphere-Biosphere Programme (IGBP): (i) characterized by the correlation between natural vegetation types and climate; (? characterized by climatic indices which have obviously been restricted to plant ecophysiology; (iii) characterized by coupling both structure and function of vegetation. Thus, the prospective of climate-vegetation classification for global change study in China was proposed, especially the study coupling climate-vegetation classification models with atmospheric general circulation models (GCMs) was emphasized.展开更多
Potential Natural Vegetation(PNV)represents the climax of vegetation succession in a natural environment,free from significant disturbances.The reconstruction of PNV is widely used to study climate-vegetation relation...Potential Natural Vegetation(PNV)represents the climax of vegetation succession in a natural environment,free from significant disturbances.The reconstruction of PNV is widely used to study climate-vegetation relationships and predict future vegetation distributions.However,fine-scale PNV maps with high accuracy are still rare in biodiversity hotspots due to the complexity of ecosystems and limited field observations.In this study,we mapped the spatiotemporal distribution of 16 PNV types using adequate field and literature data,and an improved Comprehensive and Sequential Classification System(CSCS)approach under current(2005-2016)and future(2021-2080)climate scenarios in Yunnan province,Southwest China.We found that 1)from T0(2005-2016)to T3(2021-2080),regions with cold alpine PNV types,such as mid-mountain humid evergreen broad-leaved forests(EBLF),are projected to experience more significant temperature increases compared to regions with warm PNV types,like tropic rainforests and monsoon rainforests.High-emission scenarios(SSP585)are expected to result in temperature increases approximately 2°C higher than low-emission scenarios(SSP126).Precipitation is projected to increase for water-deficient PNV types(e.g.,monsoon rainforest and semi-humid EBLF)but decrease for humid PNV types(e.g.,rainforest and mountain mossy EBLF).The SSP370 scenario predicts a slightly smaller increase in precipitation compared to other scenarios.2)All PNV types are expected to shift to higher latitudes(by an average of 0.86°)and higher elevations(by an average of 454 m)by T3,based on their current niches.Alpine PNV types are more sensitive to climate change and are projected to shift more prominently than other types.For example,mountain mossy EBLF is expected to move 1.78°northward,while mid-mountain moist EBLF is projected to rise by 578 m.3)Cold PNV types are likely to be replaced by warm types both in latitude and altitude.Semi-humid EBLF is projected to shrink the most,by 57,984 km2(51.5%of its present range),while monsoon EBLF is expected to expand the most,by 44,881 km2(64.7%of its present range).The suitable habitat for cold-temperate sclerophyllous EBLF and temperate shrublands may disappear entirely in Yunnan.Given the over-estimate of the projected PNV shift without accounting for the lag effects,these findings are still useful in planning future conservation and management efforts,which should prioritize PNV types experiencing drastic changes in temperature(e.g.,mid-mountain moist EBLF),precipitation(e.g.,mountain mossy EBLF),and distribution area(e.g.,semi-humid EBLF and cold-temperate sclerophyllous EBLF).展开更多
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 C...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.展开更多
A new modeling concept, referred to as Modeling Surgery, has been recently developed at University of Wisconsin-Madison. It is specifically designed to diagnose coupled feedbacks between different climate components a...A new modeling concept, referred to as Modeling Surgery, has been recently developed at University of Wisconsin-Madison. It is specifically designed to diagnose coupled feedbacks between different climate components as well as climatic teleconnections within a specific component through systematically modifying the coupling configurations and teleconnective pathways. It thus provides a powerful means for identifying the causes and mechanisms of low-frequency variability in the Earth's climate system. In this paper, we will give a short review of our recent progress in this new area.展开更多
Net Primary Productivity （NPP） is an important parameter, which is closely connected with global climate change, the global carbon balance and cycle. The study of climate- vegetation interaction is the basis for res...Net Primary Productivity （NPP） is an important parameter, which is closely connected with global climate change, the global carbon balance and cycle. The study of climate- vegetation interaction is the basis for research on the responses of terrestrial ecosystemto global change and mainly comprises two important components： climate vegetation classification and the NPP of the natural vegetation. Comparing NPP estimated from the classification indices-based model with NPP derived from measurements at 3767 sites in China indicated that the classification indices-based model was capable of estimating large scale NPP. Annual cumulative temperature above 0~C and a moisture index, two main factors affecting NPP, were spatially plotted with the ArcGIS grid tool based on measured data in 2348 meteorological stations from 1961 to 2006. The distribution of NPP for potential vegetation classes under present climate conditions was simulated by the classification indices-based model. The model estimated the total NPP of potential terrestrial vegetation of China to fluctuate between 1.93 and 4.54 Pg C year-1. It pro- vides a reliable means for scaling-up from site to regional scales, and the findings could potentially favor China＇s position in reducing global warming gases as outlined in the Kyoto Protocol in order to fulfill China＇s commitment of reducing greenhouse gases.展开更多
文摘The climate-vegetation interaction of China is mainly controlled by the atmospheric circulations and topographic characteristics. The distribution and NPP of vegetation zones show a close relationship with a series of climatological indexes, such as annual mean temperature, precipitation, various thermal indexes, and potential evapotranspiration rates. The multivariate analysis (DCA) for climate and vegetation, zones in China provides quantitative environmental interpretation for two significant ecological gradients. The first gradient is mainly a thermal gradient, it can be displayed by latitude, altitude, biotemperature, and annual mean temperature. The second gradient is basically a moisture gradient, it correlated highly with longitude and potential evaportranspiration. The quantitative interaction or statistical models between vegetation zones and climato-geographical indexes can provide a fundamental scenario and comparative parameters for the study on climate and vegetation changes in China.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA23090302)the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)(Grant No.2019QZKK0903)。
文摘The Hengduan Mountains Region(HMR) is essential for the future ecological protection, clean energy production,Sichuan-Xizang and Yunnan-Xizang railways, and other major infrastructure projects in China. The distributions of climate and vegetation exhibit significant regional differentiation and vertical zonality due to the rugged longitudinal ranges and gorges and the complex disaster-prone environments in HMR. Therefore, it is urgent to develop the climate-vegetation regionalization in HMR to effectively satisfy the national requirements such as agricultural production and ecological protection, mountain disaster risk prevention, and major project construction. We here develop a new scheme of climate-vegetation regionalization with the latest demarcation outcome of HMR, the ground observation from 122 meteorological stations in HMR and its surrounding areas during 1990–2019, and the high-precision remote sensing data of land cover types. The new scheme first constructs the regionalization index system, fully considering the extraordinarily complicated geomorphic pattern of mountains and valleys, the scarcity of meteorological observations, and the remarkable differentiation of climate and vegetation in HMR. The system consists of three primary regionalization indices(i.e., days with daily average temperature steady above 10°C, aridity index, and main vegetation types, dividing the temperature zones, moisture regions, and vegetation subregions, respectively) and three auxiliary indices of the accumulated temperature above 10°C, and the temperatures in January and July. Then, the HMR is divided into five temperature zones, 20 moisture regions, and 55 vegetation subregions. Compared with previous regionalization schemes, the new scheme optimizes the climate spatial interpolation model of thin plate smoothing spline suitable for the unique terrain in HMR. Moreover, the disputed division index threshold between different climatic zones(regions) is scientifically clarified using geographical detectors. Specifically, the stepwise downscaling pane division method is initially proposed to determine the zoning boundary, alleviating the excessive dependence of the traditional zoning method on subjective experience.Besides, the scheme considers the typical regional characteristics of the complex underlying surface and the high gradient zone of climate-vegetation distribution types in HMR. Consequently, the transition zone with quick climate changes between the plateau temperate and mid-subtropical zones is divided into mountainous subtropics, taking into account the spatial distribution characteristics of climate-vegetation regionalization indices. The regionalization scheme will provide practically theoretical support for agricultural production, ecological protection, major project construction, disaster prevention and relief efforts, and other socioeconomic activities in HMR, serving as a classic case of climate-vegetation regionalization for the alpine and canyon regions with intricate underlying surface, striking regional differences, and lack of ground observations.
文摘Three phrases of the quantitative study of climate-vegetation classification and their characteristics are presented based on the review of advance in climate-vegetation interaction, a key issue of 'global change and terrestrial ecosystems (GCTE)' which is the core project of International Geosphere-Biosphere Programme (IGBP): (i) characterized by the correlation between natural vegetation types and climate; (? characterized by climatic indices which have obviously been restricted to plant ecophysiology; (iii) characterized by coupling both structure and function of vegetation. Thus, the prospective of climate-vegetation classification for global change study in China was proposed, especially the study coupling climate-vegetation classification models with atmospheric general circulation models (GCMs) was emphasized.
基金The Major Program for Basic Research Project of Yunnan Province,No.202101B C070002The Second Comprehensive Scientific Expedition of the Qinghai-Tibet Plateau,No.2019QZKK 04020101。
文摘Potential Natural Vegetation(PNV)represents the climax of vegetation succession in a natural environment,free from significant disturbances.The reconstruction of PNV is widely used to study climate-vegetation relationships and predict future vegetation distributions.However,fine-scale PNV maps with high accuracy are still rare in biodiversity hotspots due to the complexity of ecosystems and limited field observations.In this study,we mapped the spatiotemporal distribution of 16 PNV types using adequate field and literature data,and an improved Comprehensive and Sequential Classification System(CSCS)approach under current(2005-2016)and future(2021-2080)climate scenarios in Yunnan province,Southwest China.We found that 1)from T0(2005-2016)to T3(2021-2080),regions with cold alpine PNV types,such as mid-mountain humid evergreen broad-leaved forests(EBLF),are projected to experience more significant temperature increases compared to regions with warm PNV types,like tropic rainforests and monsoon rainforests.High-emission scenarios(SSP585)are expected to result in temperature increases approximately 2°C higher than low-emission scenarios(SSP126).Precipitation is projected to increase for water-deficient PNV types(e.g.,monsoon rainforest and semi-humid EBLF)but decrease for humid PNV types(e.g.,rainforest and mountain mossy EBLF).The SSP370 scenario predicts a slightly smaller increase in precipitation compared to other scenarios.2)All PNV types are expected to shift to higher latitudes(by an average of 0.86°)and higher elevations(by an average of 454 m)by T3,based on their current niches.Alpine PNV types are more sensitive to climate change and are projected to shift more prominently than other types.For example,mountain mossy EBLF is expected to move 1.78°northward,while mid-mountain moist EBLF is projected to rise by 578 m.3)Cold PNV types are likely to be replaced by warm types both in latitude and altitude.Semi-humid EBLF is projected to shrink the most,by 57,984 km2(51.5%of its present range),while monsoon EBLF is expected to expand the most,by 44,881 km2(64.7%of its present range).The suitable habitat for cold-temperate sclerophyllous EBLF and temperate shrublands may disappear entirely in Yunnan.Given the over-estimate of the projected PNV shift without accounting for the lag effects,these findings are still useful in planning future conservation and management efforts,which should prioritize PNV types experiencing drastic changes in temperature(e.g.,mid-mountain moist EBLF),precipitation(e.g.,mountain mossy EBLF),and distribution area(e.g.,semi-humid EBLF and cold-temperate sclerophyllous EBLF).
基金supported by the China Meteorological Administration through Grant GYHY (QX) 2007-25the 973 projectunder Grant 2005CB321703+1 种基金the Fund for Innovative Re-search Groups under Grant No. 40221503the National Natural Science Foundation of China (NSFC) project un-der Grant No. 40225013
文摘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.
文摘A new modeling concept, referred to as Modeling Surgery, has been recently developed at University of Wisconsin-Madison. It is specifically designed to diagnose coupled feedbacks between different climate components as well as climatic teleconnections within a specific component through systematically modifying the coupling configurations and teleconnective pathways. It thus provides a powerful means for identifying the causes and mechanisms of low-frequency variability in the Earth's climate system. In this paper, we will give a short review of our recent progress in this new area.
文摘Net Primary Productivity （NPP） is an important parameter, which is closely connected with global climate change, the global carbon balance and cycle. The study of climate- vegetation interaction is the basis for research on the responses of terrestrial ecosystemto global change and mainly comprises two important components： climate vegetation classification and the NPP of the natural vegetation. Comparing NPP estimated from the classification indices-based model with NPP derived from measurements at 3767 sites in China indicated that the classification indices-based model was capable of estimating large scale NPP. Annual cumulative temperature above 0~C and a moisture index, two main factors affecting NPP, were spatially plotted with the ArcGIS grid tool based on measured data in 2348 meteorological stations from 1961 to 2006. The distribution of NPP for potential vegetation classes under present climate conditions was simulated by the classification indices-based model. The model estimated the total NPP of potential terrestrial vegetation of China to fluctuate between 1.93 and 4.54 Pg C year-1. It pro- vides a reliable means for scaling-up from site to regional scales, and the findings could potentially favor China＇s position in reducing global warming gases as outlined in the Kyoto Protocol in order to fulfill China＇s commitment of reducing greenhouse gases.
