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.     

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.     

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.     

乡村人口迁出对生态脆弱地区植被覆被的影响——以内蒙古自治区为例（英文）

Different government departments and researchers have paid considerable attention at various levels to improving the eco-environment in ecologically fragile areas. Over the past decade, large numbers of people have emigrated from rural areas as a result of the rapid urbanization in Chinese society. The question then remains: to what extent does this migration affect the regional vegetation greenness in the areas that people have moved from Based on normalized difference vegetation index(NDVI) data with a resolution of 1 km, as well as meteorological data and socio-economic data from 2000 to 2010 in Inner Mongolia, the spatio-temporal variation of vegetation greenness in the study area was analyzed via trend analysis and significance test methods. The contributions of human activities and natural factors to the variation of vegetation conditions during this period were also quantitatively tested and verified, using a multi-regression analysis method. We found that:(1) the vegetation greenness of the study area increased by 10.1% during 2000–2010. More than 28% of the vegetation greenness increased significantly, and only about 2% decreased evidently during the study period.(2) The area with significant degradation showed a banded distribution at the northern edge of the agro-pastoral ecotone in central Inner Mongolia. This indicates that the eco-environment is still fragile in this area, which should be paid close attention. The area where vegetation greenness significantly improved showed a concentrated distribution in the southeast and west of Inner Mongolia.(3) The effect of agricultural labor on vegetation greenness exceeded those due to natural factors(i.e. precipitation and temperature). The emigration of agricultural labor improved the regional vegetation greenness significantly.     

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.     

2001-2013年华北地区植被覆盖度与干旱条件的相关分析（英文）

Climate change is one of the most important factors that affect vegetation distribution in North China. Among all climatic factors, drought is considered to have the most significant effect on the environment. Based on previous studies, the climate drought index can be used to assess the evolutionary trend of the ecological environment under various arid climatic conditions. It is necessary for us to further explore the relationship between vegetation coverage(index) and climate drought conditions. Therefore, in this study, based on MODIS-NDVI products and meteorological observation data, the Palmer Drought Severity Index(PDSI) and vegetation coverage in North China were first calculated. Then, the interannual variations of PDSI and vegetation coverage during 2001–2013 were analyzed using a Theil-Sen slope estimator. Finally, an ecoregion perspective of the correlation between them was discussed. The experimental results demonstrated that the PDSI index and vegetation coverage value varied over different ecoregions. During the period 2001–2013, vegetation coverage increased in the southern and northern mountains of North China, while it showed a decreasing trend in the Beijing-Tianjin-Tangshan City Circle area and suburban agricultural zone located in Hebei Province and Henan Province). Over 13 years, the climate of the northeastern part of North China became more humid, while in the southern part of North China, it tended to be dry. According to the correlation analysis results, 73.37% of North China showed a positive correlation between the vegetation coverage and climate drought index. A negative correlation was observed mainly in urban and suburban areas of Beijing, Tianjin, Hebei Province, and Henan Province. In most parts of North China, drought conditions in summer and autumn had a strong influence on vegetation coverage.     

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.     

陕甘宁地区植被恢复对气候变化和人类活动的响应(英文)

The "Grain for Green Project" initiated by the governments since 1999 were the dominant contributors to the vegetation restoration in the agro-pastoral transitional zone of northern China. Climate change and human activities are responsible for the improvement and degradation to a certain degree. In order to monitor the vegetation variations and clarify the causes of rehabilitation in the Shaanxi-Gansu-Ningxia Region, this paper, based on the MODIS-NDVI and climate data during the period of 2000-2009, analyzes the main charac-teristics, spatial-temporal distribution and reasons of vegetation restoration, using methods of linear regression, the Hurst Exponent, standard deviation and other methods. Results are shown as follows. (1) From 2000 to 2009, the NDVI of the study area was improved progres-sively, with a linear tendency being 0.032/10a, faster than the growth of the Three-North Shelter Forest Program (0.007/10a) from 1982 to 2006. (2) The vegetation restoration is characterized by two fast-growing periods, with an "S-shaped" increasing curve. (3) The largest proportion of the contribution to vegetation restoration was observed in the slightly improved area, followed by the moderate and the significantly improved area; the degraded area is distributed sporadically over southern part of Ningxia Hui Autonomous Region as well as eastern Dingbian of Shaanxi province, Huanxian and Zhengyuan of Gansu province. (4) Climate change and human activities are two driving forces in vegetation restoration; more-over anthropogenic factors such as "Grain for Green Project" were the main causes leading to an increasing trend of NDVI on local scale. However, its influencing mechanism remains to be further investigated. (5) The Hurst Exponent of NDVI time series shows that the vegetation restoration was sustainable. It is expected that improvement in vegetation cover will expand to the most parts of the region.     

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.     

陕北黄土丘陵区干燥度变化趋势及其对植被恢复的响应(英文)

Detecting variation trend in dry-wet conditions can provide information for developing strategic measures to mitigate the impacts of global warming, particularly in dry regions. Taking the hilly region of northern Shaanxi on the Loess Plateau as a case area, this study analyzed the trend of aridity variation during 1981–2012, and explored the effect of vegetation restoration promoted by the Grain-for-Green(GFG) program implemented in 1999. The results indicated that the aridity in the region was non-significantly increased by 0.88% per year during 1981–2012, showing a drying trend. This drying trend and amplitude were changed by the influence of vegetation restoration promoted by the GFG program, based on two findings. The first one was that the aridity variation tended to increase during 1981–1999 while it turned to decrease during 2000–2012, with the regional mean relative change rate changed from 2.45% to –1.06%. This distinction was more remarkable in the loess gully region, where the vegetation was improved more obviously. The second one was that the mean vegetation coverage as indicated by EVI increased by 0.90% to 4.32% per year at county level, while the aridity decreased by 0.14% to 2.32% per year during 2000–2012. The regression analysis using the mean county data indicated that the change rate of aridity was negatively related to that of EVI with the coefficient of determination(R2) of 0.56, illustrating that around half of the aridity decline was explained by the EVI change. The mechanism of this effect was complicated, but it was found that the wind speed decline induced by the vegetation improvement could be an important contributor. It is concluded that the region became drier during 1981–2012, but the eco-restoration reduced the drying speed. However, this conclusion is involved in uncertainties, and further study based on experiments is needed to confirm the effect of the GFG-promoted vegetation restoration.     

Evaluation of the carbon sequestration of Zhalong Wetland under climate change

Wetland ecosystems are crucial to the global carbon cycle.In this study,the Zhalong Wetland was investigated.Based on remote sensing and meteorological observation data from 1975–2018 and the downscaled fifth phase of the coupled model intercomparison project (CMIP5) climate projection dataset from 1961–2100,the parameters of a net primary productivity (NPP) climatic potential productivity model were adjusted,and the simulation ability of the CMIP5 coupled models was evaluated.On this basis,we analysed the spatial and temporal variations of land cover types and landscape transformation processes in the Zhalong Nature Reserve over the past 44 years.We also evaluated the influence of climate change on the NPP of the vegetation,microbial heterotrophic respiration (Rh),and net ecosystem productivity (NEP) of the Zhalong Wetland and predicted the carbon sequestration potential of the Zhalong Wetland from 2019–2029 under the representative concentration pathways (RCP) 4.5 and RCP 8.5 scenarios.Our results indicate the following:(1) Herbaceous bog was the primary land cover type of the Zhalong Nature Reserve,occupying an average area of 1168.02±224.05 km~2,equivalent to 51.84%of the total reserve area.(2)Since 1975,the Zhalong Nature Reserve has undergone a dry–wet–dry transformation process.Excluding several wet periods during the mid-1980s to early 1990s,the reserve has remained a dry habitat,with particularly severe conditions from 2000 onwards.(3) The 1975–2018 mean NPP,Rh,and NEP values of the Zhalong Wetland were 500.21±52.76,337.59±10.80,and 162.62±45.56 g C·m~(-2)·a~(-1),respectively,and an evaluation of the carbon balance indicated that the reserve served as a carbon sink.(4) From 1975–2018,NPP showed a significant linear increase,Rh showed a highly significant linear increase,while the increase in the carbon absorption rate was smaller than the increase in the carbon release rate.(5) Variations in NPP and NEP were precipitation-driven,with the correlations of NPP and NEP with annual precipitation and summer precipitation being highly significantly positive(P0.001);variations in Rh were temperature-driven,with the correlations of Rh with the average annual,summer,and autumn temperatures being highly significantly positive (P0.001).The interaction of precipitation and temperature enhances the impact on NPP,Rh and NEP.(6) Under the RCP 4.5 and RCP 8.5 scenarios,the predicted carbon sequestration by the Zhalong Wetland from 2019–2029 was 2.421 (±0.225)×10~(11) g C·a~(-1) and 2.407 (±0.382)×10~(11) g C·a~(-1),respectively,which were both lower than the mean carbon sequestration during the last 44 years (2.467 (±0.950)×10~(11) g C·a~(-1)).Future climate change may negatively contribute to the carbon sequestration potential of the Zhalong Wetland.The results of the present study are significant for enhancing the abilities of integrated eco-meteorological monitoring,evaluation,and early warning systems for wetlands.     

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     

历史及未来气候变化下中国潜在植被NPP的脆弱性研究（英文）

Using the Integrated Biosphere Simulator, a dynamic vegetation model, this study initially simulated the net primary productivity(NPP) dynamics of China's potential vegetation in the past 55 years(1961–2015) and in the future 35 years(2016–2050). Then, taking the NPP of the potential vegetation in average climate conditions during 1986–2005 as the basis for evaluation, this study examined whether the potential vegetation adapts to climate change or not. Meanwhile, the degree of inadaptability was evaluated. Finally, the NPP vulnerability of the potential vegetation was evaluated by synthesizing the frequency and degrees of inadaptability to climate change. In the past 55 years, the NPP of desert ecosystems in the south of the Tianshan Mountains and grassland ecosystems in the north of China and in western Tibetan Plateau was prone to the effect of climate change. The NPP of most forest ecosystems was not prone to the influence of climate change. The low NPP vulnerability to climate change of the evergreen broad-leaved and coniferous forests was observed. Furthermore, the NPP of the desert ecosystems in the north of the Tianshan Mountains and grassland ecosystems in the central and eastern Tibetan Plateau also had low vulnerability to climate change. In the next 35 years, the NPP vulnerability to climate change would reduce the forest–steppe in the Songliao Plain, the deciduous broad-leaved forests in the warm temperate zone, and the alpine steppe in the central and western Tibetan Plateau. The NPP vulnerability would significantly increase of the temperate desert in the Junggar Basin and the alpine desert in the Kunlun Mountains. The NPP vulnerability of the subtropical evergreen broad-leaved forests would also increase. The area of the regions with increased vulnerability would account for 27.5% of China.     

近20年来伊洛河流域典型地区森林景观格局动态

Based on the information from forest resources distribution maps of Luoning County of 1983 and 1999,six indices were used to analyze spatial patterns and dynamics of forest landscapes of the typical region in the middle of the Yihe-Luohe river basin.These indices include patch number,mean patch area,fragment index,patdch extension index,etc,The results showed that;(1) There was a rapid increase in the number of patch and total area from 1983 to 1999 in the study area,The fragment degree became very high.(2) The area of all the forest patch types had witnessed great changes,The fractal degree of each forest patch type became big from 1983 to 1999 ,The mean extension index of Robinia pseudoacacia forest ,non- forest shrub forest ,sparse forest ,and Quercus species forest in creased rapidly,but that of economic forest became zero ,The fractal dimension each showed that forest coverage has been promoted.(3)The changes of landscape patterns were different in different geomprhic regions.From 1983 to 1999 the vegetation cover area,the gross number and the density of patch,diversity and evenness of landscape were all reduced greatly in gullies and ravines,but the maximum area and the mean area of patch types were increased ,In hilly region,both the forest cover area and the number of patch increased from 1983 to 1999,but the mean area of patch was reduced greatly,In mountain region,even though the area under forest canopy reduced from 1983 to 1999 ,the patch number was increased greatly,the mean area of all patch types was reduced ,the extension index,diversity index and evenness index of landscape were all increased.Furthermore,because of different types of land use,human activtiy and terratin ,the vegetation changes on northern and southern mountain slopes were different.According to these analyses,the main driving forces,such as the policies of management,market economy,influence of human activities etc.are brought out.     

豫西伏牛山地森林植被对水热条件变化的响应研究(英文)

This paper uses HJ-1 satellite multi-spectral and multi-temporal data to extract forest vegetation information in the Funiu Mountain region. The S-G filtering algorithm was employed to reconstruct the MODIS EVI(Enhanced Vegetation Index) time-series data for the period of 2000–2013, and these data were correlated with air temperature and precipitation data to explore the responses of forest vegetation to hydrothermal conditions. The results showed that:(1) the Funiu Mountain region has relatively high and increasing forest coverage with an average EVI of 0.48 over the study period, and the EVI first shows a decreasing trend with increased elevation below 200 m, then an increasing trend from 200–1700 m, and finally a decreasing trend above 1700 m. However, obvious differences could be identified in the responses of different forest vegetation types to climate change. Broad-leaf deciduous forest, being the dominant forest type in the region, had the most significant EVI increase.(2) Temperature in the region showed an increasing trend over the 14 years of the study with an anomaly increasing rate of 0.27℃/10a; a fluctuating yet increasing trend could be identified for the precipitation anomaly percentage.(3) Among all vegetation types, the evergreen broad-leaf forest has the closest EVI-temperature correlation, whereas the mixed evergreen and deciduous forest has the weakest. Almost all forest types showed a weak negative EVI-precipitation correlation, except the mixed evergreen and deciduous forest with a weak positive correlation.(4) There is a slight delay in forest vegetation responses to air temperature and precipitation, with half a month only for limited areas of the mixed evergreen and deciduous forest.     

Glacial changes in the Gangdisê Mountains from 1970 to 2016

Based on the revised First Chinese Glacier Inventory(FCGI), the Second Chinese Glacier Inventory(SCGI) and Landsat OLI images for 2015–2016, we analyzed the spatial-temporal variation characteristics of glaciers in the Gangdisê Mountains from 1970 to 2016. The results showed that there were 3953 glaciers with a total area of 1306.45 km~2 and ice volume of ～58.16 km~3 in the Gangdisê Mountains in 2015–2016. Glaciers with sizes of 0.1–5 km~2 and 0.5 km~2 accounted for the largest area and the most amounts of glaciers in the Gangdisê Mountains, respectively. Over the past five decades, the area of glaciers in the Gangdisê Mountains decreased by 854.05 km~2(-1.09%·a~(-1)), accounting for 39.53% of the total glacier area in 1970. The increase in temperature during the ablation period was the most important cause for glacier retreat. Compared to other mountains in western China, the Gangdisê Mountains have experienced the strongest glacial retreat, and the rate of recession has increased in recent years. The decrease of glacier area was mainly concentrated at elevations of 5600–6100 m, and no change in glacier area was observed at elevations above 6500 m. The number and area of glaciers decreased in all orientations in the Gangdisê Mountains except for south-and southeast-oriented glaciers. Among them, north-oriented glaciers suffered the largest loss of glacier area, while glacier retreat saw the fastest in northwest-oriented glaciers. The rate of glacier retreat increased from west to east in the Gangdisê Mountains. The relative rate of glacier area change was the highest in the eastern section of the Gangdisê Mountains(-1.72%·a~(-1)), followed by the middle section(-1.67%·a~(-1)) and the western section(–0.83%·a~(-1)).     

黄土丘陵区雨强对水流含沙量的影响

To study the effects of changes in the rainfall intensity on sediment concentrations in the Loess Plateau,the observed rainfall intensities and sediment concentrations from three typical small watersheds were used to analyze the relationship between these parameters.The results showed that the sediment concentration generally increased with the increasing rainfall intensity on slope scale.However,at watershed scale,a significant threshold phenomenon was observed for the effects of the rainfall intensity on the sediment concentration.When the rainfall intensity exceeds the threshold,the flood sediment concentration will no longer increase with the increase in the rainfall intensity.The rainfall intensity threshold increased with increasing vegetation coverage.The rainfall intensity threshold was 10–15 mm/h during 1956–1969,reached 20 mm/h from 1990 to 1997 and is approximately 40 mm/h at present.Due to a rainfall intensity of 10–15 mm/h almost happened every year,the vegetation did not change much from the 1950s to 1980s.Sediment yield mainly depends on soil erosion caused by surface flow,but the surface flow speed does not increase indefinitely with the increase in the flow discharge.Thus,the annual maximum sediment concentration of the tributaries in the loess area has been basically stable before the 1990s.     

伏牛山地森林植被物候及其对气候变化的响应（英文）

This paper reports the phenological response of forest vegetation to climate change(changes in temperature and precipitation) based on Moderate Resolution Imaging Spectroradiometer(MODIS) Enhanced Vegetation Index(EVI) time-series images from 2000 to 2015. The phenological parameters of forest vegetation in the Funiu Mountains during this period were determined from the temperature and precipitation data using the Savitzky–Golay filter method, dynamic threshold method, Mann-Kendall trend test, the Theil-Sen estimator, ANUSPLIN interpolation and correlation analyses. The results are summarized as follows:(1) The start of the growing season(SOS) of the forest vegetation mainly concentrated in day of year(DOY) 105–120, the end of the growing season(EOS) concentrated in DOY 285–315, and the growing season length(GSL) ranged between 165 and 195 days. There is an evident correlation between forest phenology and altitude. With increasing altitude, the SOS, EOS and GSL presented a significant delayed, advanced and shortening trend, respectively.(2) Both SOS and EOS of the forest vegetation displayed the delayed trend, the delayed pixels accounted for 76.57% and 83.81% of the total, respectively. The GSL of the forest vegetation was lengthened, and the lengthened pixels accounted for 61.21% of the total. The change in GSL was mainly caused by the decrease in spring temperature in the region.(3) The SOS of the forest vegetation was significantly partially correlated with the monthly average temperature in March, with most correlations being negative; that is, the delay in SOS was mainly attributed to the temperature decrease in March. The EOS was significantly partially correlated with precipitation in September, with most correlations being positive; that is, the EOS was clearly delayed with increasing precipitation in September. The GSL of the forest vegetation was influenced by both temperature and precipitation throughout the growing season. For most regions, GSL was most closely related to the monthly average temperature and precipitation in August.     

Evaluating the reliability of global historical land use scenarios for forest data in China

Global historical land use scenarios are widely used to simulate the climatic and ecological effects of changes in land cover; however, reliability evaluation of these scenarios for data on China's forests is missing. By using a historical document-derived Chinese forest dataset(CHFD) for the years 1700–2000, we evaluated the reliability of data on forests in China over three global scenarios—SAGE(Center for Sustainability and the Global Environment), PJ(Pongratz Julia), and KK10(Kaplan and Krumhardt 2010)—through trend-related, quantitative, and spatial comparisons. The results show the following:(1) Although the area occupied by forests in China in the SAGE, PJ, KK10, and CHFD datasets decreased over the past 300 years, there were large differences between global scenarios and CHFD. The area occupied by forests in China in the SAGE scenario for 1700–1990 was 20%–40% more than that according to CHFD, and that occupied by forests in the KK10 from 1700 to 1850 was 32%–46% greater than that in CHFD. The difference between the PJ and CHFD was lower than 20% for most years.(2) Large differences were detected at the provincial and grid cell scales, where the PJ scenario was closer to CHFD in terms of total forested area. Provinces with large differences in terms of trend and quantity were 84% and 92% of all provinces, respectively. Grid cells with relative differences greater than 70% accounted for 60%–80% of all grids.(3) These global historical land use scenarios do not accurately reveal the spatiotemporal pattern of Chinese forests due to differences in the data sources, methods of reconstruction, and spatial scales.