Detecting climate change effects on forest ecosystems in Southwestern Romania using Landsat TM NDVI data

Nowadays, Southwestern Romania faces a large-scale aridization of the climate, revealed by the rise of temperatures and the decline of the amount of precipitations, with negative effects visible, among others, in the desiccation of forest vegetation. The present study means to identify the changes that occurred, quality-wise, in the past two decades （1990-2011） in forest vegetation in Southwestern Romania, and to establish the link between those changes and extant thermal stress in the region, whose particular features are high average annual and seasonal temperatures. In order to capture the evolution in time of cli- mate aridization, a first step consisted in using climate data, the temperature and precipitation parameters from three weather stations; these parameters were analyzed both individually and as aridity indexes （De Martonne and UNEP）. In order to quantify the changes in forest vegetation, NDVI indexes were used and analyzed, starting off from Landsat satellite images, acquired at three distinct moments in time, 1990, 2000 and 2011. In order to identify the link between the changes of NDVI index values and regional thermal stress, a yardstick of climate changes, statistical correlations were established between the peak values of average annual temperatures, represented in space, and negative changes in the NDVI index, as revealed by the change-detection analysis. The results obtained indicated there is an obvious （statistically significant） connection between thermal stress and the desiccation （degradation） of forest species in the analyzed area, with false acacia （Robinia Pseudoacacia） the main species to be impacted.     

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.     

青藏高原植被覆盖变化与降水关系

The temporal and spatial changes of NDVI on the Tibetan Plateau, as well as the relationship between NDVI and precipitation, were discussed in this paper, by using 8-km resolution multi-temporal NOAA AVHRR-NDVI data from 1982 to 1999. Monthly maximum NDVI and monthly rainfall were used to analyze the seasonal changes, and annual maximum NDVI, annual effective precipitation and growing season precipitation (from April to August) were used to discuss the interannual changes. The dynamic change of NDVI and the corre- lation coefficients between NDVI and rainfall were computed for each pixel. The results are as follows: (1) The NDVI reached the peak in growing season (from July to September) on the Tibetan Plateau. In the northern and western parts of the plateau, the growing season was very short (about two or three months); but in the southern, vegetation grew almost all the year round. The correlation of monthly maximum NDVI and monthly rainfall varied in different areas. It was weak in the western, northern and southern parts, but strong in the central and eastern parts. (2) The spatial distribution of NDVI interannual dynamic change was different too. The increase areas were mainly distributed in southern Tibet montane shrub-steppe zone, western part of western Sichuan-eastern Tibet montane coniferous forest zone, western part of northern slopes of Kunlun montane desert zone and southeastern part of southern slopes of Himalaya montane evergreen broad-leaved forest zone; the decrease areas were mainly distributed in the Qaidam montane desert zone, the western and northern parts of eastern Qinghai-Qilian montane steppe zone, southern Qinghai high cold meadow steppe zone and Ngari montane desert-steppe and desert zone. The spatial distribution of correlation coeffi- cient between annual effective rainfall and annual maximum NDVI was similar to the growing season rainfall and annual maximum NDVI, and there was good relationship between NDVI and rainfall in the meadow and grassland with medium vegetation cover, and the effect of rainfall on vegetation was small in the forest and desert area.     

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.     

Vegetation greenness modeling in response to climate change for Northeast Thailand

In Northeast Thailand, the climate change has resulted in erratic rainfall and tem- perature patterns. The region has experienced both periods of drought and seasonal floods with the increasing severity. This study investigated the seasonal variation of vegetation greenness based on the Normalized Difference Vegetation Index （NDVI） in major land cover types in the region. An assessment of the relationship between climate patterns and vegeta- tion conditions observed from NDVI was made. NDVI data were collected from year 2001 to 2009 using multi-temporal Terra MODIS Vegetation Indices Product （MOD13Q1）. NDVI pro- files were developed to measure vegetation dynamics and variation according to land cover types. Meteorological information, i.e. rainfall and temperature, for a 30 year time span from 1980 to 2009 was analyzed for their patterns. Furthermore, the data taken from the period of 2001-2009, were digitally encoded into GIS database and the spatial patterns of monthly rainfall and temperature maps were generated based on kriging technique. The results showed a decreasing trend in NDVI values for both deciduous and evergreen forests. The highest productivity and biomass were observed in dry evergreen forests and the lowest in paddy fields. Temperature was found to be increasing slightly from 1980 to 2009 while no significant trends in rainfall amounts were observed. In dry evergreen forest, NDVI was not correlated with rainfall but was significant negatively correlated with temperature. These re- sults indicated that the overall productivity in dry evergreen forest was affected by increasing temperatures. A vegetation greenness model was developed from correlations between NDVI and meteorological data using linear regression. The model could be used to observe the change in vegetation greenness and dynamics affected by temperature and rainfall.     

Temporal and spatial analysis of vegetation fire activity in the circum-Arctic during 2001–2020

Vegetation fires become the concern worldwide due to their substantial impacts on climate and environment, and in particular in the circum-Arctic. Assessing vegetation fires and associated emissions and causes can improve understanding of fire regime and provide helpful information for vegetation fires solution. In this study, satellitebased vegetation fires and emissions during 2001–2020 were investigated and contributions of different types of fires were analyzed. Furthermore, climate anomalie...     

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.     

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.     

The effects of water flow and temperature on thermal regime around a culvert built on permafrost

Temperature and water flow through a culvert beneath the Alaska Highway near Beaver Creek,Yukon,were measured at hourly intervals between June and October 2013.These data were used to simulate the effect of the culvert on the thermal regime of the road embankment and subjacent permafrost.A 2-D thermal model of the embankment and permafrost was developed with TEMP/W and calibrated using field observations.Empirical relations were obtained between water temperatures at the entrance to the culvert,flow into the culvert,and water temperatures inside the structure.Water temperatures at the entrance and inside the culvert had a linear relation,while water temperatures inside the culvert and water flow were associated by a logarithmic relation.A multiple linear regression was used to summarize these relations.From this relationship,changes in the flow rate and water temperatures at the entrance of the culvert were simulated to obtain predicted water temperatures in the culvert.The temperatures in the culvert were used in the thermal model to determine their effects on the ground thermal regime near the culvert.Variation of ±10% in water flow rate had no impact on the thermal regime underneath the culvert.Variation of water temperature at the entrance of the culvert had a noticeable influence on the thermal regime.A final simulation was conducted without insulation beneath the culvert.The thaw depth was 30 cm with insulation,and 120 cm without insulation,illustrating the importance of insulation to the ground thermal regime.     

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.     

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.     

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.     

How changes of groundwater level affect the desert riparian forest ecosystem in the Ejina Oasis,Northwest China

Groundwater is a key factor controlling the growth of vegetation in desert riparian systems. It is important to recognise how groundwater changes affect the riparian forest ecosystem. This information will not only help us to understand the ecological and hydrological process of the riparian forest but also provide support for ecological recovery of riparian forests and water-resources management of arid inland river basins. This study aims to estimate the suitability of the Water Vegetation Energy and Solute Modelling(WAVES) model to simulate the Ejina Desert riparian forest ecosystem changes,China, to assess effects of groundwater-depth change on the canopy leaf area index(LAI) and water budgets, and to ascertain the suitable groundwater depth for preserving the stability and structure of desert riparian forest. Results demonstrated that the WAVES model can simulate changes to ecological and hydrological processes. The annual mean water consumption of a Tamarix chinensis riparian forest was less than that of a Populus euphratica riparian forest, and the canopy LAI of the desert riparian forest should increase as groundwater depth decreases. Groundwater changes could significantly influence water budgets for T. chinensis and P. euphratica riparian forests and show the positive and negative effects on vegetation growth and water budgets of riparian forests. Maintaining the annual mean groundwater depth at around 1.7-2.7 m is critical for healthy riparian forest growth. This study highlights the importance of considering groundwater-change impacts on desert riparian vegetation and water-balance applications in ecological restoration and efficient water-resource management in the Heihe River Basin.     

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.     

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.     

Forest phenological patterns of Northeas China inferred from MODIS data

The role of remote sensing in phenological studies is increasingly regarded as a key to understand large area seasonal phenomena. This paper describes the application of Moderate Resolution Imaging Spectroradiometer (MODIS) time series data for forest phenological patterns. The forest phenological phase of Northeast China (NE China) and its spatial characteristics were inferred using 1-km 10-day MODIS normalized difference vegetation index (NDVI) datasets of 2002. The threshold-based method was used to estimate three key forest phenological variables, which are the start of growing season (SOS), the end of growing season (EOS) and growing season length (GSL).Then the spatial patterns of forest phenological variables of NE China were mapped and analyzed. The derived phenological variables were validated by the field observed data from published papers in the same study area. Results indicate that forest phenological phase from MODIS data is comparable with the observed data. As the derived forest phenological pattern is related to forest type distribution, it is helpful to discriminate between forest types.     

Wavelet analysis of quasi-3-year temperature oscillations in China in last 50 years, and predicted changes in the next 20 years

The wavelet analysis method is used to analyze the annual and winter temperature data of 98 observation stations in China in eight climate zones during the last 50 years （1961-2009）. The periodicities of temperature changes are investigated, and the possible temperature change trends in China in the next 20 years （2012-2029） are also predicted. Our results show that in the inter-annual temperature variability there are pervasive quasi-3- to quasi-4-year cycles, and these cycle changes are relatively steady. The periodic characteristics of the annual temperature changes are clearly different between northern and southern China, and our period superimposition extrapolation shows that both annual and winter temperatures in China will continue to increase in the next 20 years, more so in northern China and in the Qinghai-Xizang Plateau （QXP） than in the southern region, except in the southwest. If temperatures follow historic increasing linear trends, the overall temper- ature is expected to increase by 1℃ between 2010 and 2029.     

Analysis about the influence on the thermal regime in permafrost regions with different underlying surfaces

In the last several decades, the underlying surface conditions on the Qinghai-Tibet Plateau have changed dramatically, causing permafrost degradation due to climate change and human activities. This change severely influenced the cold regions environment and engineering infrastructure built above permafrost. Permafrost is a product of the interaction between the atmosphere and the ground. The formation and change of permafrost are determined by the energy exchange between earth and atmosphere system. Fieldwork was performed in order to learn how land surface change influenced the thermal regime in permafrost regions. In this article, the field data observed in the Fenghuo Mountain regions was used to analyze the thermal conditions under different underlying surfaces on the Qinghai-Tibet Plateau. Results show that underlying surface change may alter the primary energy balance and the thermal conditions of permafrost. The thermal flux in the permafrost regions is also changed, resulting in rising upper soil temperature and thickening active layer. Vegetation could prevent solar radiation from entering the ground, cooling the ground in the warm season. Also, vegetation has heat insulation and heat preservation functions related to the ground surface and may keep the permafrost stable. Plots covered with black plastic film have higher temperatures compared with plots covered by natural vegetation. The reason is that black plastic film has a low albedo, which could increase the absorbed solar radiation, and also decrease evapotranspiration. The ＂greenhouse effect＂ of transparent plastic film might effectively reduce the emission of long-wave radiation from the surface, decreasing heat loss from the earth＇s surface, and prominently increasing ground surface temperature.