Distribution of vegetation is closely coupled with climate; the climate controls distribution of vegetation and the vegetation type reflects regional climates. To reveal vegetation_climate relationships is the foundat...Distribution of vegetation is closely coupled with climate; the climate controls distribution of vegetation and the vegetation type reflects regional climates. To reveal vegetation_climate relationships is the foundation for understanding the vegetation distribution and theoretically serving vegetation regionalization. Vegetation regionalization is a theoretical integration of vegetation studies and provides a base for physiogeographical regionalization as well as agriculture and forestry regionalization. Based on a brief historical overview on studies of vegetation_climate relationships and vegetation regionalization conducted in China, we review the principles, bases and major schemes of previous vegetation regionalization and discuss on several contentious boundaries of vegetation zones in the present paper. We proposed that, under the circumstances that the primary vegetation has been destroyed in most parts of China, the division of vegetation zones/regions should be based on the distribution of primary and its secondary vegetation types and climatic indices that delimit distribution of the vegetation types. This not only reveals the closed relationship between vegetation and climate, but also is feasible practically. Although there still are divergence of views on the name and their boundaries of the several vegetation zones, it is commonly accepted that there are eight major vegetation regions in China, i.e. cold temperate needleleaf forest region, temperate needleleaf and broadleaf mixed forest region, warm temperate deciduous broadleaf forest region, subtropical evergreen broadleaf forest region, tropical monsoon forest and rain forest region, temperate steppe region, temperate desert region, and Qinghai_Xizang (Tibetan) Plateau high_cold vegetation region. Analyzing characteristics of vegetation and climate of major vegetation boundaries, we suggested that: 1) Qinling Mountain_Huaihe River line is an important arid/humid climatic, but not a thermal climatic boundary, and thus can not also be regarded as the northern limit of the subtropical vegetation zone; 2) the northern limit of subtropical vegetation zone in China is along the northern coast of the Yangtze River, from Hangzhou Bay, via Taihu Lake, Xuancheng and Tongling in Anhui Province, through by southern slope of the Dabie Mountains, to Wuhan and its west, coinciding with a warmth index ( WI ) value of 130-140 ℃·month; 3) the tropical region is limited in a very small area in southeastern Hainan Island and southern edge of Taiwan Island; and 4) considering a significant difference in climates between the southern and northern parts of the warm temperate zone, we suggested that the warm temperate zone in China is divided into two vegetation regions, deciduous broadleaf woodland region and deciduous and evergreen broadleaf mixed forest region, the Qinling Mountain_Huaihe River line being as their boundary. We also claimed that the zonal vegetation in North China is deciduous broadleaf woodland. Finally, we emphasized the importance of dynamic vegetation regionalization linked to climate changes.展开更多
This study examined the temporal variation of the Normalized Difference Vegetation Index (NDVI) and its relationship with climatic factors in the Changbai Mountain Natural Reserve (CMNR) during 2000 - 2009. The re...This study examined the temporal variation of the Normalized Difference Vegetation Index (NDVI) and its relationship with climatic factors in the Changbai Mountain Natural Reserve (CMNR) during 2000 - 2009. The results showed as follows. The average NDVI values increased at a rate of 0.0024 year-1. The increase rate differed with vegetation types, such as 0.0034 year-1 for forest and 0.0017 year-1 for tundra. Trend analyses revealed a consistent NDVI increase at the start and end of the growing season but little variation or decrease observed in July during the study period. The NDVI in CMNR showed a stronger correlation with temperature than with precipitation, especially in spring and autumn. A stronger correlation was observed between NDVI and temperature in the tundra zone (2,000-2,600m) than in the coniferous forest (1,100-1,700m) and Korean pine-broadleaved mixed forest (7oo-1,1oom) zones. The results indicate that vegetation at higher elevations is more sensitive to temperature change. NDVI variation had a strong correlation with temperature change (r=0.7311, p〈0.01) but less significant correlation with precipitation change. The result indicates that temperature can serve as a main indicator of vegetation sensitivity in the CMNR.展开更多
Examining the direct and indirect effects of climatic factors on vegetation growth is critical to understand the complex linkage between climate change and vegetation dynamics. Based on the Moderate Resolution Imaging...Examining the direct and indirect effects of climatic factors on vegetation growth is critical to understand the complex linkage between climate change and vegetation dynamics. Based on the Moderate Resolution Imaging Spectroradiometer(MODIS) Normalized Difference Vegetation Index(NDVI) data and meteorological data(temperature and precipitation) from 2001 to 2012, the trend of vegetation dynamics were examined in the Ziya-Daqing basins, China. The path analysis was used to obtain the information on the relationships among climatic factors and their effects on vegetation growth. It was found that the trends of growing season NDVI were insignificant in most plain dry land, while the upward trends were significant in forest, grass and dry land in Taihang Mountains. According to the path analysis, in 23% of the basins the inter-annual NDVI variation was dominated by the direct effect of precipitation, in 5% by the direct effects of precipitation and temperature, and in less than 1% by the direct effect of temperature or indirect effects of these two climatic factors. It indicated that precipitation significantly affected the vegetation growth in the whole basins, and this effect was not regulated by temperature. Precipitation increase(especially in July, August and September) was favorable to greenness enhancement. Summer temperature rising showed negative effect on plant productivity enhancement, but temperature rise in April was beneficial for the vegetation growth. When April temperature increases by 1℃, the onset date of greenness for natural vegetation will be 2 days in advance. There was a lag-time effect of precipitation or temperature on monthly NDVI for all land use types except grass.展开更多
Previous studies have revealed a connection between springtime sea surface temperature (SST) in the tropical northern Atlantic (TNA) and the succeeding wintertime El Nino-Southern Oscillation (ENSO). The present...Previous studies have revealed a connection between springtime sea surface temperature (SST) in the tropical northern Atlantic (TNA) and the succeeding wintertime El Nino-Southern Oscillation (ENSO). The present analysis demonstrates that the linkage between springtime TNA SST and the following ENSO experiences an obvious interdecadal change around the early 1980s, with the connection being weak before but significant after. After the early 1980s, springtime positive TNA SST anomalies induce an anomalous cyclone over the northeastern subtropical Pacific and an anomalous Walker circulation with a descending branch over the tropical central-eastern Pacific. This leads to anomalous cold SST in the northeastern Pacific and an anomalous anticyclone over the western-central tropical Pacific, with anomalous easterlies to the equatorward side. As such, springtime TNA SST anomalies are followed by wintertime ENSO after the early 1980s. In contrast, before the early 1980s, anomalous cold SST in the northeastern Pacific and related anomalous easterlies over the western-central tropical Pacific are weak, corresponding to springtime positive TNA SST anomalies and resulting in a weak linkage between springtimeTNA SST and the succeeding wintertime ENSO. Further investigation implies that the change in the TNA SST-ENSO relationship is probably due to a change in springtime mean precipitation over the tropical Atlantic and South America.展开更多
In the study of global warming, one of the main issues is the quantification of the urbanization effect in climate records. Previous studies have contributed much to removing the impact of urbanization from surface ai...In the study of global warming, one of the main issues is the quantification of the urbanization effect in climate records. Previous studies have contributed much to removing the impact of urbanization from surface air temperature by carefully selecting reference stations. However, due to the insufficient number of stations free from the influence of urbanization and the different criteria used to select reference stations, there are still significant controversies about the intensity of the impact of urbanization on temperature records. This study proposes a dynamic method for quantifying natural warming using information on urbanization from every station acquired from remote sensing (RS) data instead of selecting reference stations. Two different spatial scales were applied to examine the impact of urbanization, but little difference was found, indicating the stability of this method. The results showed a significant difference in original temperature data and the homogenized data-urban warming accounted for approximately 64% in the original temperature warming but only approximately 20% in the homogenized temperature records.展开更多
Water scarcity is a challenge in many arid and semi-arid regions; this may lead to a series of environmental problems and could be stressed even further by the effects from climate change. This study focused on the wa...Water scarcity is a challenge in many arid and semi-arid regions; this may lead to a series of environmental problems and could be stressed even further by the effects from climate change. This study focused on the water resource management in Shanshan County, an inland arid region located in northwestern China with a long history of groundwater overexploitation. A model of the supply and demand system in the study area from 2006 to2030, including effects from global climate change,was developed using a system dynamics(SD)modeling tool. This SD model was used to 1) explore the best water-resource management options by testing system responses under various scenarios and2) identify the principal factors affecting the responses, aiming for a balance of the groundwater system and sustainable socio-economic development.Three causes were identified as primarily responsible for water issues in Shanshan: low water-use efficiency low water reuse, and increase in industrial waterdemand. To address these causes, a combined scenario was designed and simulated, which was able to keep the water deficiency under 5% by 2030. The model provided some insights into the dynamic interrelations that generate system behavior and the key factors in the system that govern water demand and supply. The model as well as the study results may be useful in water resources management in Shanshan and may be applied, with appropriate modifications, to other regions facing similar water management challenges.展开更多
Using the Moderate Resolution Imaging Spectroradiometer-normalized difference vegetation index(NDVI) dataset,we investigated the patterns of spatiotemporal variation in vegetation coverage and its associated driving f...Using the Moderate Resolution Imaging Spectroradiometer-normalized difference vegetation index(NDVI) dataset,we investigated the patterns of spatiotemporal variation in vegetation coverage and its associated driving forces in the Qinling-Daba(Qinba) Mountains in 2000–2014.The Sen and Mann–Kendall models and partial correlation analysis were used to analyze the data,followed by calculation of the Hurst index to analyze future trends in vegetation coverage.The results of the study showed that(1) NDVI of the study area exhibited a significant increase in 2000–2014(linear tendency,2.8%/10a).During this period,a stable increase was detected before 2010(linear tendency,4.32%/10a),followed by a sharp decline after 2010(linear tendency,–6.59%/10a).(2) Spatially,vegetation cover showed a "high in the middle and a low in the surroundings" pattern.High values of vegetation coverage were mainly found in the Qinba Mountains of Shaanxi Province.(3) The area with improved vegetation coverage was larger than the degraded area,being 81.32% and 18.68%,respectively,during the study period.Piecewise analysis revealed that 71.61% of the total study area showed a decreasing trend in vegetation coverage in 2010–2014.(4) Reverse characteristics of vegetation coverage change were stronger than the same characteristics on the Qinba Mountains.About 46.89% of the entire study area is predicted to decrease in the future,while 34.44% of the total area will follow a continuously increasing trend.(5) The change of vegetation coverage was mainly attributed to the deficit in precipitation.Moreover,vegetation coverage during La Nina years was higher than that during El Nino years.(6) Human activities can induce ambiguous effects on vegetation coverage: both positive effects(through implementation of ecological restoration projects) and negative effects(through urbanization) were observed.展开更多
Climate change and elevated atmospheric CO2 should affect the dynamics of soil organic carbon (SOC). SOC dynamics under uncertain patterns of climate warming and elevated atmospheric CO2 as well as with different so...Climate change and elevated atmospheric CO2 should affect the dynamics of soil organic carbon (SOC). SOC dynamics under uncertain patterns of climate warming and elevated atmospheric CO2 as well as with different soil erosion extents at Nelson Farm during 1998-100 were simulated using stochastic modelling. Results based on numerous simulations showed that SOC decreased with elevated atmospheric temperature but increased with atmospheric CO2 concentration. Therefore, there was a counteract effect on SOC dynamics between climate warming and elevated CO2. For different soil erosion extents, warming 1℃ and elevated atmospheric CO2 resulted in SOC increase at least 15%, while warming 5 ℃ and elevated CO2 resulted in SOC decrease more than 29%. SOC predictions with uncertainty assessment were conducted for different scenarios of soil erosion, climate change, and elevated CO2. Statistically, SOC decreased linearly with the probability. SOC also decreased with time and the degree of soil erosion. For example, in 2100 with a probability of 50%, SOC was 1 617, 1 167, and 892 g m^-2, respectively, for no, minimum, and maximum soil erosion. Under climate warming 5 ℃ and elevated CO2, the soil carbon pools became a carbon source to the atmosphere (P 〉 95%). The results suggested that stochastic modelling could be a useful tool to predict future SOC dynamics under uncertain climate change and elevated CO2.展开更多
Aims Recent warmer and wetter climate in northern China remains a hot topic in recent years,yet its effect on vegetation growth has not been fully understood.This study investigated the temporal change of vegetation c...Aims Recent warmer and wetter climate in northern China remains a hot topic in recent years,yet its effect on vegetation growth has not been fully understood.This study investigated the temporal change of vegetation cover and its correlations with climatic variables from 1982 to 2018 for grasslands in northern China.Our aim is to clarify whether the warmer and wetter climate in recent years drives the greening of the vegetation in this region.Methods We investigated the temporal dynamic of vegetation normalized difference vegetation index(NDVI)and its driving forces based on long time-series data.Piecewise regression was used to examine whether there was a turning point of the trend of NDVI and climatic variables.Pearson correlation analyses were conducted to quantify the relationship between NDVI and climatic factors.Stepwise multivariable regression was used to quantify the contributions of climate variables to the temporal variations in NDVI.Important Findings We found a turning point of NDVI trend in 2008,with GIMMS NDVI indicating a slight increase of 0.00022 yr?1 during 1982–2008 to an increase of 0.002 yr?1 for GIMMS NDVI during 2008–2015 and 0.0018 yr?1 for MODIS NDVI during 2008–2018.Precipitation was the predominant driver,and air temperature and vapor pressure deficit exerted a minor impact on the temporal dynamics of NDVI.Overall,our results suggest a turning point of NDVI trend,and that recent warmer and wetter climate has caused vegetation greening,which provides insights for better predicting the vegetation cover in this region under changing climate.展开更多
文摘Distribution of vegetation is closely coupled with climate; the climate controls distribution of vegetation and the vegetation type reflects regional climates. To reveal vegetation_climate relationships is the foundation for understanding the vegetation distribution and theoretically serving vegetation regionalization. Vegetation regionalization is a theoretical integration of vegetation studies and provides a base for physiogeographical regionalization as well as agriculture and forestry regionalization. Based on a brief historical overview on studies of vegetation_climate relationships and vegetation regionalization conducted in China, we review the principles, bases and major schemes of previous vegetation regionalization and discuss on several contentious boundaries of vegetation zones in the present paper. We proposed that, under the circumstances that the primary vegetation has been destroyed in most parts of China, the division of vegetation zones/regions should be based on the distribution of primary and its secondary vegetation types and climatic indices that delimit distribution of the vegetation types. This not only reveals the closed relationship between vegetation and climate, but also is feasible practically. Although there still are divergence of views on the name and their boundaries of the several vegetation zones, it is commonly accepted that there are eight major vegetation regions in China, i.e. cold temperate needleleaf forest region, temperate needleleaf and broadleaf mixed forest region, warm temperate deciduous broadleaf forest region, subtropical evergreen broadleaf forest region, tropical monsoon forest and rain forest region, temperate steppe region, temperate desert region, and Qinghai_Xizang (Tibetan) Plateau high_cold vegetation region. Analyzing characteristics of vegetation and climate of major vegetation boundaries, we suggested that: 1) Qinling Mountain_Huaihe River line is an important arid/humid climatic, but not a thermal climatic boundary, and thus can not also be regarded as the northern limit of the subtropical vegetation zone; 2) the northern limit of subtropical vegetation zone in China is along the northern coast of the Yangtze River, from Hangzhou Bay, via Taihu Lake, Xuancheng and Tongling in Anhui Province, through by southern slope of the Dabie Mountains, to Wuhan and its west, coinciding with a warmth index ( WI ) value of 130-140 ℃·month; 3) the tropical region is limited in a very small area in southeastern Hainan Island and southern edge of Taiwan Island; and 4) considering a significant difference in climates between the southern and northern parts of the warm temperate zone, we suggested that the warm temperate zone in China is divided into two vegetation regions, deciduous broadleaf woodland region and deciduous and evergreen broadleaf mixed forest region, the Qinling Mountain_Huaihe River line being as their boundary. We also claimed that the zonal vegetation in North China is deciduous broadleaf woodland. Finally, we emphasized the importance of dynamic vegetation regionalization linked to climate changes.
基金supported by the Science and Technology Innovation Platforms Initiative of Northeast Normal University under the project "Ecological Security and Data Assemblage of the Changbai Mountains International Georegion(Project No.106111065202)"the National Grand Fundamental Research 973 Program of China (Project No.2009CB426305)
文摘This study examined the temporal variation of the Normalized Difference Vegetation Index (NDVI) and its relationship with climatic factors in the Changbai Mountain Natural Reserve (CMNR) during 2000 - 2009. The results showed as follows. The average NDVI values increased at a rate of 0.0024 year-1. The increase rate differed with vegetation types, such as 0.0034 year-1 for forest and 0.0017 year-1 for tundra. Trend analyses revealed a consistent NDVI increase at the start and end of the growing season but little variation or decrease observed in July during the study period. The NDVI in CMNR showed a stronger correlation with temperature than with precipitation, especially in spring and autumn. A stronger correlation was observed between NDVI and temperature in the tundra zone (2,000-2,600m) than in the coniferous forest (1,100-1,700m) and Korean pine-broadleaved mixed forest (7oo-1,1oom) zones. The results indicate that vegetation at higher elevations is more sensitive to temperature change. NDVI variation had a strong correlation with temperature change (r=0.7311, p〈0.01) but less significant correlation with precipitation change. The result indicates that temperature can serve as a main indicator of vegetation sensitivity in the CMNR.
基金Under the auspices of National Natural Science Foundation of China(No.41471026,31171451)Strategic Science and Technology Program in the Thirteenth Five-Year Plan of Institute of Geographical Sciences and Natural Resources Research,Chinese Academy of Sciences(No.2012ZD003)
文摘Examining the direct and indirect effects of climatic factors on vegetation growth is critical to understand the complex linkage between climate change and vegetation dynamics. Based on the Moderate Resolution Imaging Spectroradiometer(MODIS) Normalized Difference Vegetation Index(NDVI) data and meteorological data(temperature and precipitation) from 2001 to 2012, the trend of vegetation dynamics were examined in the Ziya-Daqing basins, China. The path analysis was used to obtain the information on the relationships among climatic factors and their effects on vegetation growth. It was found that the trends of growing season NDVI were insignificant in most plain dry land, while the upward trends were significant in forest, grass and dry land in Taihang Mountains. According to the path analysis, in 23% of the basins the inter-annual NDVI variation was dominated by the direct effect of precipitation, in 5% by the direct effects of precipitation and temperature, and in less than 1% by the direct effect of temperature or indirect effects of these two climatic factors. It indicated that precipitation significantly affected the vegetation growth in the whole basins, and this effect was not regulated by temperature. Precipitation increase(especially in July, August and September) was favorable to greenness enhancement. Summer temperature rising showed negative effect on plant productivity enhancement, but temperature rise in April was beneficial for the vegetation growth. When April temperature increases by 1℃, the onset date of greenness for natural vegetation will be 2 days in advance. There was a lag-time effect of precipitation or temperature on monthly NDVI for all land use types except grass.
基金supported by the National Natural Science Foundation of China[grant numbers 41530425 and 41605050]the China Postdoctoral Science Foundation[grant number2015M581151]
文摘Previous studies have revealed a connection between springtime sea surface temperature (SST) in the tropical northern Atlantic (TNA) and the succeeding wintertime El Nino-Southern Oscillation (ENSO). The present analysis demonstrates that the linkage between springtime TNA SST and the following ENSO experiences an obvious interdecadal change around the early 1980s, with the connection being weak before but significant after. After the early 1980s, springtime positive TNA SST anomalies induce an anomalous cyclone over the northeastern subtropical Pacific and an anomalous Walker circulation with a descending branch over the tropical central-eastern Pacific. This leads to anomalous cold SST in the northeastern Pacific and an anomalous anticyclone over the western-central tropical Pacific, with anomalous easterlies to the equatorward side. As such, springtime TNA SST anomalies are followed by wintertime ENSO after the early 1980s. In contrast, before the early 1980s, anomalous cold SST in the northeastern Pacific and related anomalous easterlies over the western-central tropical Pacific are weak, corresponding to springtime positive TNA SST anomalies and resulting in a weak linkage between springtimeTNA SST and the succeeding wintertime ENSO. Further investigation implies that the change in the TNA SST-ENSO relationship is probably due to a change in springtime mean precipitation over the tropical Atlantic and South America.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA05090201)the National Basic Research Program of China(2009CB723904)
文摘In the study of global warming, one of the main issues is the quantification of the urbanization effect in climate records. Previous studies have contributed much to removing the impact of urbanization from surface air temperature by carefully selecting reference stations. However, due to the insufficient number of stations free from the influence of urbanization and the different criteria used to select reference stations, there are still significant controversies about the intensity of the impact of urbanization on temperature records. This study proposes a dynamic method for quantifying natural warming using information on urbanization from every station acquired from remote sensing (RS) data instead of selecting reference stations. Two different spatial scales were applied to examine the impact of urbanization, but little difference was found, indicating the stability of this method. The results showed a significant difference in original temperature data and the homogenized data-urban warming accounted for approximately 64% in the original temperature warming but only approximately 20% in the homogenized temperature records.
文摘Water scarcity is a challenge in many arid and semi-arid regions; this may lead to a series of environmental problems and could be stressed even further by the effects from climate change. This study focused on the water resource management in Shanshan County, an inland arid region located in northwestern China with a long history of groundwater overexploitation. A model of the supply and demand system in the study area from 2006 to2030, including effects from global climate change,was developed using a system dynamics(SD)modeling tool. This SD model was used to 1) explore the best water-resource management options by testing system responses under various scenarios and2) identify the principal factors affecting the responses, aiming for a balance of the groundwater system and sustainable socio-economic development.Three causes were identified as primarily responsible for water issues in Shanshan: low water-use efficiency low water reuse, and increase in industrial waterdemand. To address these causes, a combined scenario was designed and simulated, which was able to keep the water deficiency under 5% by 2030. The model provided some insights into the dynamic interrelations that generate system behavior and the key factors in the system that govern water demand and supply. The model as well as the study results may be useful in water resources management in Shanshan and may be applied, with appropriate modifications, to other regions facing similar water management challenges.
基金Major Project of High-resolution Earth Observation SystemBeijing Natural Science Foundation,No.8144052
文摘Using the Moderate Resolution Imaging Spectroradiometer-normalized difference vegetation index(NDVI) dataset,we investigated the patterns of spatiotemporal variation in vegetation coverage and its associated driving forces in the Qinling-Daba(Qinba) Mountains in 2000–2014.The Sen and Mann–Kendall models and partial correlation analysis were used to analyze the data,followed by calculation of the Hurst index to analyze future trends in vegetation coverage.The results of the study showed that(1) NDVI of the study area exhibited a significant increase in 2000–2014(linear tendency,2.8%/10a).During this period,a stable increase was detected before 2010(linear tendency,4.32%/10a),followed by a sharp decline after 2010(linear tendency,–6.59%/10a).(2) Spatially,vegetation cover showed a "high in the middle and a low in the surroundings" pattern.High values of vegetation coverage were mainly found in the Qinba Mountains of Shaanxi Province.(3) The area with improved vegetation coverage was larger than the degraded area,being 81.32% and 18.68%,respectively,during the study period.Piecewise analysis revealed that 71.61% of the total study area showed a decreasing trend in vegetation coverage in 2010–2014.(4) Reverse characteristics of vegetation coverage change were stronger than the same characteristics on the Qinba Mountains.About 46.89% of the entire study area is predicted to decrease in the future,while 34.44% of the total area will follow a continuously increasing trend.(5) The change of vegetation coverage was mainly attributed to the deficit in precipitation.Moreover,vegetation coverage during La Nina years was higher than that during El Nino years.(6) Human activities can induce ambiguous effects on vegetation coverage: both positive effects(through implementation of ecological restoration projects) and negative effects(through urbanization) were observed.
基金Supported by the National Natural Science Foundation of China(Nos.51039007 and 51179212)the Fundamental Research Funds for the Central Universities
文摘Climate change and elevated atmospheric CO2 should affect the dynamics of soil organic carbon (SOC). SOC dynamics under uncertain patterns of climate warming and elevated atmospheric CO2 as well as with different soil erosion extents at Nelson Farm during 1998-100 were simulated using stochastic modelling. Results based on numerous simulations showed that SOC decreased with elevated atmospheric temperature but increased with atmospheric CO2 concentration. Therefore, there was a counteract effect on SOC dynamics between climate warming and elevated CO2. For different soil erosion extents, warming 1℃ and elevated atmospheric CO2 resulted in SOC increase at least 15%, while warming 5 ℃ and elevated CO2 resulted in SOC decrease more than 29%. SOC predictions with uncertainty assessment were conducted for different scenarios of soil erosion, climate change, and elevated CO2. Statistically, SOC decreased linearly with the probability. SOC also decreased with time and the degree of soil erosion. For example, in 2100 with a probability of 50%, SOC was 1 617, 1 167, and 892 g m^-2, respectively, for no, minimum, and maximum soil erosion. Under climate warming 5 ℃ and elevated CO2, the soil carbon pools became a carbon source to the atmosphere (P 〉 95%). The results suggested that stochastic modelling could be a useful tool to predict future SOC dynamics under uncertain climate change and elevated CO2.
基金This research was supported by the National Natural Science Foundation of China(31922053,31570437)the National Key Research and Development Program of China(2017YFA0604801).
文摘Aims Recent warmer and wetter climate in northern China remains a hot topic in recent years,yet its effect on vegetation growth has not been fully understood.This study investigated the temporal change of vegetation cover and its correlations with climatic variables from 1982 to 2018 for grasslands in northern China.Our aim is to clarify whether the warmer and wetter climate in recent years drives the greening of the vegetation in this region.Methods We investigated the temporal dynamic of vegetation normalized difference vegetation index(NDVI)and its driving forces based on long time-series data.Piecewise regression was used to examine whether there was a turning point of the trend of NDVI and climatic variables.Pearson correlation analyses were conducted to quantify the relationship between NDVI and climatic factors.Stepwise multivariable regression was used to quantify the contributions of climate variables to the temporal variations in NDVI.Important Findings We found a turning point of NDVI trend in 2008,with GIMMS NDVI indicating a slight increase of 0.00022 yr?1 during 1982–2008 to an increase of 0.002 yr?1 for GIMMS NDVI during 2008–2015 and 0.0018 yr?1 for MODIS NDVI during 2008–2018.Precipitation was the predominant driver,and air temperature and vapor pressure deficit exerted a minor impact on the temporal dynamics of NDVI.Overall,our results suggest a turning point of NDVI trend,and that recent warmer and wetter climate has caused vegetation greening,which provides insights for better predicting the vegetation cover in this region under changing climate.