The Tibetan Plateau(TP),known as the“Third Pole of Earth”,and its ecosystem is quite sensitive to climate change(Yao et al.,2012;Qiu,2008).In recent decades,the main TP has experienced warming and humidification(alt...The Tibetan Plateau(TP),known as the“Third Pole of Earth”,and its ecosystem is quite sensitive to climate change(Yao et al.,2012;Qiu,2008).In recent decades,the main TP has experienced warming and humidification(although there has been a drying trend in the southern region),and researchers anticipate that this change will continue in the future(Jiang et al.,2023;Sun et al.,2020;Chen et al.,2015).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
Structural information of grassland changes on the Tibetan Plateau is essential for understanding alterations in critical ecosystem functioning and their underlying drivers that may reflect environmental changes.Howev...Structural information of grassland changes on the Tibetan Plateau is essential for understanding alterations in critical ecosystem functioning and their underlying drivers that may reflect environmental changes.However,such information at the regional scale is still lacking due to methodological limitations.Beyond remote sensing indicators only recognizing vegetation productivity,we utilized multivariate data fusion and deep learning to characterize formation-based plant community structure in alpine grasslands at the regional scale of the Tibetan Plateau for the first time and compared it with the earlier version of Vegetation Map of China for historical changes.Over the past 40 years,we revealed that(1)the proportion of alpine meadows in alpine grasslands increased from 50%to 69%,well-reflecting the warming and wetting trend;(2)dominances of Kobresia pygmaea and Stipa purpurea formations in alpine meadows and steppes were strengthened to 76%and 92%,respectively;(3)the climate factor mainly drove the distribution of Stipa purpurea formation,but not the recent distribution of Kobresia pygmaea formation that was likely shaped by human activities.Therefore,the underlying mechanisms of grassland changes over the past 40 years were considered to be formation dependent.Overall,the first exploration for structural information of plant community changes in this study not only provides a new perspective to understand drivers of grassland changes and their spatial heterogeneity at the regional scale of the Tibetan Plateau,but also innovates large-scale vegetation study paradigm.展开更多
基金supported by the Basic Science Center for Tibetan Plateau Earth System(No.41988101)the Science and Technology Plan Project of the Xizang Autonomous Region(No.XZ202201ZD0005G01)。
文摘The Tibetan Plateau(TP),known as the“Third Pole of Earth”,and its ecosystem is quite sensitive to climate change(Yao et al.,2012;Qiu,2008).In recent decades,the main TP has experienced warming and humidification(although there has been a drying trend in the southern region),and researchers anticipate that this change will continue in the future(Jiang et al.,2023;Sun et al.,2020;Chen et al.,2015).
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 Second Tibetan Plateau Scientific Expedition and Research Program(2019QZKK0304-02)Joint Chinese Academy of Sciences(CAS)-Max Planck Society(MPG)Research Project(HZXM20225001MI)+3 种基金the Strategic Priority Research Program A of Chinese Academy of Sciences(XDA20050104)the National Natural Science Foundation of China(42041005)CAS Light of West China Programthe Fundamental Research Funds for the Central Universities。
文摘Structural information of grassland changes on the Tibetan Plateau is essential for understanding alterations in critical ecosystem functioning and their underlying drivers that may reflect environmental changes.However,such information at the regional scale is still lacking due to methodological limitations.Beyond remote sensing indicators only recognizing vegetation productivity,we utilized multivariate data fusion and deep learning to characterize formation-based plant community structure in alpine grasslands at the regional scale of the Tibetan Plateau for the first time and compared it with the earlier version of Vegetation Map of China for historical changes.Over the past 40 years,we revealed that(1)the proportion of alpine meadows in alpine grasslands increased from 50%to 69%,well-reflecting the warming and wetting trend;(2)dominances of Kobresia pygmaea and Stipa purpurea formations in alpine meadows and steppes were strengthened to 76%and 92%,respectively;(3)the climate factor mainly drove the distribution of Stipa purpurea formation,but not the recent distribution of Kobresia pygmaea formation that was likely shaped by human activities.Therefore,the underlying mechanisms of grassland changes over the past 40 years were considered to be formation dependent.Overall,the first exploration for structural information of plant community changes in this study not only provides a new perspective to understand drivers of grassland changes and their spatial heterogeneity at the regional scale of the Tibetan Plateau,but also innovates large-scale vegetation study paradigm.
