中国东北地区自然植被水分利用效率对干旱的响应（英文）

Drought has become a problem that is universally faced by global terrestrial ecosystems. Northeast China is located in a region sensitive to global climate changes, and one of the main impacts of climate changes in Northeast China is manifested as drought in growing seasons. This study analyzes the spatio-temporal evolution law of the water use efficiency(WUE) of the main natural vegetation(i.e., cold-temperate coniferous forests, temperate pine-broad-leaved mixed forests, warm-temperate deciduous broad-leaved forests, and grasslands) in Northeast China based on public MODIS data products, including MCD12 Q1, MOD15 A2 H, MOD16 A2, and MOD17 A3 H, and meteorological data from 2002 to 2013. The influence of drought events on the WUE of different vegetation types and their response to drought events are also investigated. The study findings are as follows:(1) drought in Northeast China frequently occurs in the regions stretching from 114.55°E to 120.90°E, and the percentage of drought area among the forests is lower than that among the grasslands during these years;(2) the annual average WUE of the natural vegetation ranges from 0.82 to 1.08 C/kg~(-1) H_2O, and the WUE of forests(0.82 to 1.08 C/kg~(-1) H_2O) is universally higher than that of grasslands(0.84 to 0.99 C/kg~(-1) H_2O);(3) in 2008, the regions where the WUE in drought conditions is higher than that in normal water conditions account for 86.11% of the study area, and a significant linear positive correlation is found between the WUE in drought conditions and the WUE in normal water conditions, whereas the degree of drought does not influence the WUE of the natural vegetation in an obviously linear manner; and(4) the WUE for the cold-temperate coniferous forests and temperate pine-broad-leaved mixed forests with a high ET or low NPP is more likely to rise in drought conditions; the WUE for the grasslands with a low Evapotranspiration(ET), Net Primary Production(NPP), and Leaf Area Index(LAI) is more likely to rise in drought conditions; and the ET, NPP, and LAI have no significant influence on the WUE for the warm-temperate deciduous broad-leaved forests in drought conditions. This study contributes to improving the evaluation of the influence of drought on natural ecosystems.     

30年来呼伦贝尔地区草地植被对气候变化的响应(英文)

Global warming has led to significant vegetation changes especially in the past 20 years. Hulun Buir Grassland in Inner Mongolia, one of the world’s three prairies, is undergoing a process of prominent warming and drying. It is essential to investigate the effects of climatic change (temperature and precipitation) on vegetation dynamics for a better understanding of climatic change. NDVI (Normalized Difference Vegetation Index), reflecting characteristics of plant growth, vegetation coverage and biomass, is used as an indicator to monitor vegetation changes. GIMMS NDVI from 1981 to 2006 and MODIS NDVI from 2000 to 2009 were adopted and integrated in this study to extract the time series characteristics of vegetation changes in Hulun Buir Grassland. The responses of vegetation coverage to climatic change on the yearly, seasonal and monthly scales were analyzed combined with temperature and precipitation data of seven meteorological sites. In the past 30 years, vegetation coverage was more correlated with climatic factors, and the correlations were dependent on the time scales. On an inter-annual scale, vegetation change was better correlated with precipitation, suggesting that rainfall was the main factor for driving vegetation changes. On a seasonal-interannual scale, correlations between vegetation coverage change and climatic factors showed that the sensitivity of vegetation growth to the aqueous and thermal condition changes was different in different seasons. The sensitivity of vegetation growth to temperature in summers was higher than in the other seasons, while its sensitivity to rainfall in both summers and autumns was higher, especially in summers. On a monthly-interannual scale, correlations between vegetation coverage change and climatic factors during growth seasons showed that the response of vegetation changes to temperature in both April and May was stronger. This indicates that the temperature effect occurs in the early stage of vegetation growth. Correlations between vegetation growth and precipitation of the month before the current month, were better from May to August, showing a hysteresis response of vegetation growth to rainfall. Grasses get green and begin to grow in April, and the impacts of temperature on grass growth are obvious. The increase of NDVI in April may be due to climatic warming that leads to an advanced growth season. In summary, relationships between monthly-interannual variations of vegetation coverage and climatic factors represent the temporal rhythm controls of temperature and precipitation on grass growth largely.     

中国地区植被对温度变化趋势的响应（英文）

Though many studies have focused on the causes of shifts in trend of temperature, whether the response of vegetation growth to temperature has changed is still not very clear. In this study, we analyzed the spatial features of the trend changes of temperature during the growing season and the response of vegetation growth in China based on observed climatic data and the normalized difference vegetation index(NDVI) from 1984 to 2011. An obvious warming to cooling shift during growing season from the period 1984–1997 to the period 1998–2011 was identified in the northern and northeastern regions of China, whereas a totally converse shift was observed in the southern and western regions, suggesting large spatial heterogeneity of changes of the trend of growing season temperature throughout China. China as a whole, a significant positive relationship between vegetation growth and temperature during 1984 to 1997 has been greatly weakened during 1998–2011. This change of response of vegetation growth to temperature has also been confirmed by Granger causality test. On regional scales, obvious shifts in relationship between vegetation growth and temperature were identified in temperate desert region and rainforest region. Furthermore, by comprehensively analyzing of the relationship between NDVI and climate variables, an overall reduction of impacts of climate factors on vegetation growth was identified over China during recent years, indicating enhanced influences from human associated activities.     

The coupled characteristics of the physical process between sea ice of two poles and Tibetan land surface

In order to discuss the characteristics of sea ice change of strong signal area on Antarctic and Arctic and the correlation between the thermal state on the land surface of Tibetan Plateau and the atmosphere circulation of North Hemisphere or the climate changes in China, and to study the feedback mechanism among “three-pole” factors, the earlier stage “three-pole” strong signal characteristics by using statistic methods such as teleconnection,which affect the regional climate changes in China and East Asia. The cross-correlation feature and coupling effect between ice caps of North and South pole and water-thermal state on Tibetan Plateau surface are discussed as well. The contribution of three-pole's earlier stage factors to China's summer climate change and the influence of its dynamic structure are compared here. The formation mechanisms of global climate change and regional climate change of China are investigated from the aspect of qualitative correlation mode of global sea-land-air-ice.     

中国能源消费与气候变化的关系

Energy consumption has an inevitable connection with economic level and climate. Based on selected data covering annual total energy consumption and its composition and that of all kinds of energy in 1953-1999, the annual residential energy consumption and the coal and electricity consumption in 1980-1999 in China, the acreage of crops under cultivation suffered from drought and flood annually and gross domestic product (GDP) in 1953-1999 in the whole country, and mean daily temperature data from 29 provincial meteorological stations in the whole country from 1970 to 1999, this paper divides energy consumption into socio-economic energy consumption and climatic energy consumption in the way of multinomial. Itchanges between the climate energy consumption andalso goes further into the relations and their changes between the climate energy consumptionenergy consumption and the economic level inand climate factor and between the socio-economic energy between the climate energy level in China with the method of statistical analysis. At present, there are obvious transitions in the changing relationships of the energy consumption to economy and climate, which comprises the transition of economic system from resource-intensive industry to technology-intensive industry and the transition of climatic driving factors of the energy consumption from driven by the disasters of drought and flood to driven by temperature.     

内蒙古植被覆盖度的时空动态变化及其与气候因子的关系(英文)

The vegetation coverage dynamics and its relationship with climate factors on different spatial and temporal scales in Inner Mongolia during 2001-2010 were analyzed based on MODIS-NDVI data and climate data.The results indicated that vegetation coverage in Inner Mongolia showed obvious longitudinal zonality,increasing from west to east across the region with a change rate of 0.2/10°N.During 2001-2010,the mean vegetation coverage was 0.57,0.4 and 0.16 in forest,grassland and desert biome,respectively,exhibiting evident spatial heterogeneities.Totally,vegetation coverage had a slight increasing trend during the study period.Across Inner Mongolia,the area of which the vegetation coverage showed extremely significant and significant increase accounted for 11.25% and 29.13% of the area of whole region,respectively,while the area of which the vegetation coverage showed extremely significant and significant decrease accounted for 7.65% and 26.61%,respectively.On inter-annual time scale,precipitation was the dominant driving force of vegetation coverage for the whole region.On inter-monthly scale,the change of vegetation coverage was consistent with both the change of temperature and precipitation,implying that the vegetation growth within a year is more sensitive to the combined effects of water and heat rather than either single climate factor.The vegetation coverage in forest biome was mainly driven by temperature on both inter-annual and inter-monthly scales,while that in desert biome was mainly influenced by precipitation on both the two temporal scales.In grassland biome,the yearly vegetation coverage had a better correlation with precipitation,while the monthly vegetation coverage was influenced by both temperature and precipitation.In grassland biome,the impacts of precipitation on monthly vegetation coverage showed time-delay effects.     

Response of revegetation to climate change with meso-and micro-scale remote sensing in an arid desert of China

The revegetation protection system(VPS)on the edge of the Tengger Desert can be referred to as a successful model of sand control technology in China and even the world,and there has been a substantial amount of research on revegetation stability.However,it is unclear how meso-and micro-scale revegetation activity has responded to climatic change over the past decades.To evaluate the relative influence of climatic variables on revegetation activities in a restored desert ecosystem,we analysed the trend of revegetation change from 2002 to 2015 using a satellite-derived normalized difference vegetation index(NDVI)dataset.The time series of the NDVI data were decomposed into trend,seasonal,and random components using a segmented regression method.The results of the segmented regression model indicate a changing trend in the NDVI in the VPS,changing from a decrease(?7×10?3/month)before 2005 to an increase(0.3×10?3/month)after 2005.We found that precipitation was the most important climatic factor influencing the growing season NDVI(P<0.05),while vegetation growth sensitivity to water and heat varied significantly in different seasons.In the case of precipitation reduction and warming in the study area,the NDVI of the VPS could still maintain an overall slow upward trend(0.04×10?3/month),indicating that the ecosystem is sustainable.Our findings suggest that the VPS has been successful in maintaining stability and sustainability under current climate change conditions and that it is possible to introduce the VPS in similar areas as a template for resistance to sand and drought hazards.     

Sensitivity and areal differentiation of vegetation responses to hydrothermal dynamics on the northern and southern slopes of the Qinling Mountains in Shaanxi province

The Qinling Mountains, located at the junction of warm temperate and subtropical zones, serve as the boundary between north and south China. Exploring the sensitivity of the response of vegetation there to hydrothermal dynamics elucidates the dynamics and mechanisms of the main vegetation types in the context of changes in temperature and moisture. Importance should be attached to changes in vegetation in different climate zones. To reveal the sensitivity and areal differentiation of vegetation responses to hydrothermal dynamics, the spatio-temporal variation characteristics of the normalized vegetation index(NDVI) and the standardized precipitation evapotranspiration index(SPEI) on the northern and southern slopes of the Qinling Mountains from 2000 to 2018 are explored using the meteorological data of 32 meteorological stations and the MODIS NDVI datasets. The results show that: 1) The overall vegetation coverage of the Qinling Mountains improved significantly from 2000 to 2018. The NDVI rise rate and area ratio on the southern slope were higher than those on the northern slope, and the vegetation on the southern slope improved more than that on the northern slope. The Qinling Mountains showed an insignificant humidification trend. The humidification rate and humidification area of the northern slope were greater than those on the southern slope. 2) Vegetation on the northern slope of the Qinling Mountains was more sensitive to hydrothermal dynamics than that on the southern slope. Vegetation was most sensitive to hydrothermal dynamics from March to June on the northern slope, and from March to May(spring) on the southern slope. The vegetation on the northern and southern slopes was mainly affected by hydrothermal dynamics on a scale of 3–7 months, responding weakly to hydrothermal dynamics on a scale of 11–12 months. 3) Some 90.34% of NDVI and SPEI was positively correlated in the Qinling Mountains. Spring humidification in most parts of the study area promoted the growth of vegetation all the year round. The sensitivity of vegetation responses to hydrothermal dynamics with increasing altitude increased first and then decreased. Elevations of 800 to 1200 m were the most sensitive range for vegetation response to hydrothermal dynamics. The sensitivity of the vegetation response at elevations of 1200–3000 m decreased with increasing altitude. As regards to vegetation type, grass was most sensitive to hydrothermal dynamics on both the northern and southern slopes of the Qinling Mountains; but most other vegetation types on the northern slope were more sensitive to hydrothermal dynamics than those on the southern slope.     

1971-2000年青藏高原气候变化趋势

Trends of annual and monthly temperature, precipitation, potential evapotranspi- ration and aridity index were analyzed to understand climate change during the period 1971–2000 over the Tibetan Plateau which is one of the most special regions sensitive to global climate change. FAO56–Penmen–Monteith model was modified to calculate potential evapotranspiration which integrated many climatic elements including maximum and mini- mum temperatures, solar radiation, relative humidity and wind speed. Results indicate gen- erally warming trends of the annual averaged and monthly temperatures, increasing trends of precipitation except in April and September, decreasing trends of annual and monthly poten- tial evapotranspiration, and increasing aridity index except in September. It is not the isolated climatic elements that are important to moisture conditions, but their integrated and simulta- neous effect. Moreover, potential evapotranspiration often changes the effect of precipitation on moisture conditions. The climate trends suggest an important warm and humid tendency averaged over the southern plateau in annual period and in August. Moisture conditions would probably get drier at large area in the headwater region of the three rivers in annual average and months from April to November, and the northeast of the plateau from July to September. Complicated climatic trends over the Tibetan Plateau reveal that climatic factors have nonlinear relationships, and resulte in much uncertainty together with the scarcity of observation data. The results would enhance our understanding of the potential impact of climate change on environment in the Tibetan Plateau. Further research of the sensitivity and attribution of climate change to moisture conditions on the plateau is necessary.     

2000–2011年三江源区植被覆盖时空变化特征(英文)

The Three-River Headwaters Region(TRHR), which is the source area of the Yangtze River, Yellow River, and Lancang River, is of key importance to the ecological security of China. Because of climate changes and human activities, ecological degradation occurred in this region. Therefore, "The nature reserve of Three-River Source Regions" was established, and "The project of ecological protection and construction for the Three-River Headwaters Nature Reserve" was implemented by the Chinese government. This study, based on MODIS-NDVI and climate data, aims to analyze the spatiotemporal changes in vegetation coverage and its driving factors in the TRHR between 2000 and 2011, from three dimensions. Linear regression, Hurst index analysis, and partial correlation analysis were employed. The results showed the following:(1) In the past 12 years(2000–2011), the NDVI of the study area increased, with a linear tendency being 1.2%/10a, of which the Yangtze and Yellow River source regions presented an increasing trend, while the Lancang River source region showed a decreasing trend.(2) Vegetation coverage presented an obvious spatial difference in the TRHR, and the NDVI frequency was featured by a bimodal structure.(3) The area with improved vegetation coverage was larger than the degraded area, being 64.06% and 35.94%, respectively during the study period, and presented an increasing trend in the north and a decreasing trend in the south.(4) The reverse characteristics of vegetation coverage change are significant. In the future, degradation trends will be mainly found in the Yangtze River Basin and to the north of the Yellow River, while areas with improving trends are mainly distributed in the Lancang River Basin.(5) The response of vegetation coverage to precipitation and potential evapotranspiration has a time lag, while there is no such lag in the case of temperature.(6) The increased vegetation coverage is mainly attributed to the warm-wet climate change and the implementation of the ecological protection project.     

柴达木盆地植被覆盖度的分析与模拟——空间自相关方法的运用(英文)

Relationship between vegetation and environmental factors has always been a major topic in ecology, but it has also been an important way to reveal vegetation’s dynamic response to and feedback effects on climate change. For the special geographical location and climatic characteristics of the Qaidam Basin, with the support of traditional and remote sensing data, in this paper a vegetation coverage model was established. The quantitative prediction of vegetation coverage by five environmental factors was initially realized through multiple stepwise regression (MSR) models. However, there is significant multicollinearity among these five environmental factors, which reduces the performance of the MSR model. Then through the introduction of the Moran Index, an indicator that reflects the spatial auto-correlation of vegetation distribution, only two variables of average annual rainfall and local Moran Index were used in the final establishment of the vegetation coverage model. The results show that there is significant spatial autocorrelation in the distribution of vegetation. The role of spatial autocorrelation in the establishment of vegetation coverage model has not only improved the model fitting R2 from 0.608 to 0.656, but also removed the multicollinearity among independents.     

2000-2010年黄河上游流域植被年际变化及其对气候要素的响应(英文)

To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index(NDVI) time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive: regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.     

Inter-annual variations in vegetation and their response to climatic factors in the upper catchments of the Yellow River from 2000 to 2010

To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index（NDVI） time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive： regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.     

Spatial-temporal patterns of vegetation dynamics and their relationships to climate variations in Qinghai Lake Basin using MODIS time-series data

Global warming has led to significant vegetation changes in recent years. It is necessary to investigate the effects of climatic variations（temperature and precipitation） on vegetation changes for a better understanding of acclimation to climatic change. In this paper, we focused on the integration and application of multi-methods and spatial analysis techniques in GIS to study the spatio-temporal variation of vegetation dynamics and to explore the vegetation change mechanism. The correlations between EVI and climate factors at different time scales were calculated for each pixel including monthly, seasonal and annual scales respectively in Qinghai Lake Basin from the year of 2001 to 2012. The primary objectives of this study are to reveal when, where and why the vegetation change so as to support better understanding of terrestrial response to global change as well as the useful information and techniques for wise regional ecosystem management practices. The main conclusions are as follows：（1） Overall vegetation EVI in the region increased 6% during recent 12 years. The EVI value in growing seasons（i.e. spring and summer） exhibited very significant improving trend, accounted for 12.8% and 9.3% respectively. The spatial pattern of EVI showed obvious spatial heterogeneity which was consistent with hydrothermal condition. In general, the vegetation coverage improved in most parts of the area since nearly 78% pixel of the whole basin showed increasing trend, while degraded slightly in a small part of the area only.（2） The EVI change was positively correlated with average temperature and precipitation. Generally speaking, in Qinghai Lake Basin, precipitation was the dominant driving factor for vegetation growth; however, at different time scale its weight to vegetation has differences.（3） Based on geo-statistical analysis, the autumn precipitation has a strong correlation with the next spring EVI values in the whole region. This findings explore the autumn precipitation is an important indicator     

Spatiotemporal changes in vegetation coverage and its driving factors in the Three-River Headwaters Region during 2000–2011简

The Three-River Headwaters Region （TRHR）, which is the source area of the Yangtze River, Yellow River, and Lancang River, is of key importance to the ecological secu- rity of China. Because of climate changes and human activities, ecological degradation oc- curred in this region. Therefore, ＂The nature reserve of Three-River Sou,＇ce Regions＂ was established, and ＂The project of ecological protection and construction for the Three-River Headwaters Nature Reserve＂ was implemented by the Chinese government. This study, based on MODIS-NDVI and climate data, aims to analyze the spatiotemporal changes in vegetation coverage and its driving factors in the TRHR between 2000 and 2011, from three dimensions. Linear regression, Hurst index analysis, and partial correlation analysis were employed. The results showed the following： （1） In the past 12 years （2000-2011）, the NDVI of the study area increased, with a linear tendency being 1.2%/10a, of which the Yangtze and Yellow River source regions presented an increasing trend, while the Lancang River source region showed a decreasing trend. （2） Vegetation coverage presented an obvious spatial difference in the TRHR, and the NDVI frequency was featured by a bimodal structure. （3） The area with improved vegetation coverage was larger than the degraded area, being 64.06% and 35.94%, respectively during the study period, and presented an increasing trend in the north and a decreasing trend in the south. （4） The reverse characteristics of vegetation cov- erage change are significant. In the future, degradation trends will be mainly found in the Yangtze River Basin and to the north of the Yellow River, while areas with improving trends are mainly distributed in the Lancang River Basin. （5） The response of vegetation coverage to precipitation and potential evapotranspiration has a time lag, while there is no such lag in the case of temperature. （6） The increased vegetation coverage is mainly attributed to the warm-wet climate change and the implementation of the ecological protection project.     

Impact of global warming on drought in China

Spatial and temporal change patterns of air temperature (T), precipitation (P), relative humidity (RH), lower vapor pressure (VP), potential evapotranspiration (PET) and drought situation of 690 meteorological stations for all of China were evaluated in this study to understand the effects of warming on regional drought and hydrological processes. Here, the drought extent is expressed by aridity index (AI), which is the ratio of precipitation and reference crop evapotranspiration (ET₀) calculated by FAO Penman-Monteith equation, taking into account air temperature, atmospheric humidity, solar radiation, and wind. Our results indicate that there are different patterns of climate change from 1961 to 2008 and from 1981 to 2008. Little precipitation change occurred in China and ET₀ decreased from 1961 to 2008. But, the warming trend has intensified and the area with significant increasing precipitation has reduced since the early 1980’s and ET₀ has increased in most areas of China from 1981 to 2008 and decreased from 1961 to 2008. The areas affected by drought have shifted from North China and Northeast China to East China and South China since 1981. It is speculated that the increasing warming intensity after 1981 possibly strengthened the power of potential evapotranspiration and resulted in drought in most areas of Northeast China, North China, eastern Southwest China, and especially in East China and South China.     

2000-2014年秦巴山区植被覆盖时空变化特征及其归因（英文）

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.     

京津冀干旱时空演变规律分析（英文）

Spatio-temporal patterns of drought from 1961 to 2013 over the Beijing-Tianjin-Hebei(BTH) region of China were analyzed using the Palmer Drought Severity index(PDSI) based on 21 meteorological stations. Overall, changes in the mean-state of drought detected in recent decades were due to decreases in precipitation and potential evapotranspiration. The Empirical Orthogonal Functions(EOF) method was used to decompose drought into spatio-temporal patterns, and the first two EOF modes were analyzed. According to the first leading EOF mode(48.5%), the temporal variability(Principal Components, PC1) was highly positively correlated with annual series of PDSI(r=+0.99). The variance decomposition method was further applied to explain the inter-decadal temporal and spatial variations of drought relative to the total variation. We find that 90% of total variance was explained by time variance, and both total and time variance dramatically decreased from 1982 to 2013. The total variance was consistent with extreme climate events at the inter-decadal scale(r=0.71, p0.01). Comparing the influence of climate change on the annual drought in two different long-term periods characterized by dramatic global warming(P1: 1961–1989 and P2: 1990–2013), we find that temperature sensitivity in the P2 was three times more than that in the P1.     

Soil erosion and its response to the changes of precipitation and vegetation cover on the Loess Plateau

Soil erosion is a major threat to our terrestrial ecosystems and an important global environmental problem. The Loess Plateau in China is one of the regions that suffered more severe soil erosion and undergoing climate warming and drying in the past decades. The vegetation restoration named Grain-to-Green Program has now been operating for more than 10 years. It is necessary to assess the variation of soil erosion and the response of precipita- tion and vegetation restoration to soil erosion on the Loess Plateau. In the study, the Revised Universal Soil Loss Equation （RUSLE） was applied to evaluate annual soil loss caused by water erosion. The results showed as follows. The soil erosion on the Loess Plateau between 2000 and 2010 averaged for 15.2 t hm-2 a 1 and was characterized as light for the value less than 25 t hm-2 a-1. The severe soil erosion higher than 25 t hm-2 a-~ was mainly distributed in the gully and hilly regions in the central, southwestern, and some scattered areas of earth-rocky mountainous areas on the Loess Plateau. The soil erosion on the Loess Plateau showed a deceasing trend in recent decade and reduced more at rates more than 1 t hm 2 a 1 in the areas suffering severe soil loss. Benefited from the improved vegetation cover and ecological construction, the soil erosion on the Loess Plateau was significantly declined, es- pecially in the east of Yulin, most parts of Yah＇an prefectures in Shaanxi Province, and the west of Luliang and Linfen prefectures in Shanxi Province in the hilly and gully regions. The variation of vegetation cover responding to soil erosion in these areas showed the relatively higher contribution than the precipitation. However, most areas in Qingyang and Dingxi pre- fectures in Gansu Province and Guyuan in Ningxia Hui Autonomous Region were predomi- nantly related to precipitation.     

过去2000年中国气候重建与极端事件研究最新进展（英文）

China is distinguished by a prominent monsoonal climate in the east of the country, a continental arid climate in the northwest and a highland cold climate on the Qinghai-Tibet Plateau. Because of the long history of Chinese civilization, there are abundant and well-dated documentary records for climate variation over the whole of the country as well as many natural archives(e.g., tree-rings, ice cores, stalagmites, varved lake sediments and corals) that enable high-resolution paleoclimatic reconstruction. In this paper, we review recent advances in the reconstruction of climate and extreme events over the last 2000 years in China. In the last 10 years, many new reconstructions, based on multi-proxies with wide spatial coverage, have been published in China. These reconstructions enable us to understand the characteristics of climate change across the country as well as the uncertainties of regional reconstructions. Synthesized reconstructed temperature results show that warm intervals over the last 2000 years occurred in AD 1–200, AD 551–760, AD 951–1320, and after AD 1921, and also show that cold intervals were in AD 201–350, AD 441–530, AD 781–950, and AD 1321–1920. Extreme cold winters, seen between 1500 and 1900, were more frequent than those after 1950. The intensity of regional heat waves, in the context of recent global warming, may not in fact exceed natural climate variability seen over the last 2000 years. In the eastern monsoonal region of China, decadal, multi-decadal and centennial oscillations are seen in rainfall variability. While the ensemble mean for drought/flood spatial patterns across all cold periods shows a meridional distribution, there is a tri-pole pattern with respect to droughts south of 25°N, floods between 25° and 30°N, and droughts north of 30°N for all warm periods. Data show that extreme drought events were most frequent in the periods AD 301–400, AD 751–800, AD 1051–1150, AD 1501–1550, and AD 1601–1650, while extreme flood events were frequent in the periods AD 101–150, AD 251–300, AD 951–1000, AD 1701–1750, AD 1801–1850, and AD 1901–1950. Between AD 1551–1600, extreme droughts and flood events occurred frequently. In arid northwest China, climate was characterized by dry conditions in AD 1000–1350, wet conditions in AD 1500–1850, and has tended to be wet over recent decades. On the northeastern Qinghai-Tibet Plateau, centennial-scale oscillations in precipitation have occurred over the last 1000 years, interrupted by several multidecadal-scale severe drought events. Of these, the most severe were in the 1480 s and 1710 s. In southwest China, extreme droughts as severe as those seen in Sichuan and Chongqing in 2006 are known to have occurred during historical times.