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1.
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.  相似文献   

2.
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.  相似文献   

3.
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.  相似文献   

4.
30年来呼伦贝尔地区草地植被对气候变化的响应(英文)   总被引：8，自引：3，他引：5  
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.  相似文献   

5.
气候变化对山东省潘庄灌区冬小麦生长的影响(英文)   总被引：2，自引：1，他引：1  
Global climate change has significant impacts on agricultural production.Future climate change will bring important influences to the food security.The CERES-Wheat model was used to simulate the winter wheat growing process and production in Panzhuang Irrigation District(PID) during 2011-2040 under B2 climate scenario based on the Special Report on Emissions Scenarios(SRES) assumptions with the result of RCMs(Regional Climate Models) projections by PRECIS(Providing Regional Climates for Impacts Studies) system introduced to China from the Hadley Centre for Climate Prediction and Research.The CERES-Wheat model was calibrated and validated with independent field-measured growth data in 2002-2003 and 2007-2008 growing season under current climatic conditions at Yucheng Comprehensive Experimental Station(YCES),Chinese Academy of Sciences(CAS).The results show that a significant impact of climate change on crop growth and yield was noted in the PID study area.Average temperature at Yucheng Station rose by 0.86℃ for 1961-2008 in general.Under the B2 climate scenario,average temperature rose by 0.55℃ for 2011-2040 compared with the baseline period(1998-2008),which drastically shortened the growth period of winter-wheat.However,as the temperature keep increasing after 2030,the top-weight and yield of the winter wheat will turn to decrease.The simulated evapotranspiration shows an increasing trend,although it is not very significant,during 2011-2040.Water use efficiency will increase during 2011-2031,but decrease during 2031-2040.The results indicate that climate change enhances agricultural production in the short-term,whereas continuous increase in temperature limits crop production in the long-term.  相似文献   

6.
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.  相似文献   

7.
Explicitly identifying the spatial distribution of ecological transition zones(ETZs) and simulating their response to climate scenarios is of significance in understanding the response and feedback of ecosystems to global climate change. In this study, a quantitative spatial identification method was developed to assess ETZ distribution in terms of the improved Holdridge life zone(iHLZ) model. Based on climate observations collected from 782 weather stations in China in the T0(1981–2010) period, and the Intergovernmental Panel on Climate Change Coupled Model Intercomparison Project(IPCC CMIP5) RCP2.6, RCP4.5, and RCP8.5 climate scenario data in the T1(2011–2040), T2(2041–2070), and T3(2071–2100) periods, the spatial distribution of ETZs and their response to climate scenarios in China were simulated in the four periods of T0, T1, T2, and T3. Additionally, a spatial shift of mean center model was developed to quantitatively calculate the shift direction and distance of each ETZ type during the periods from T0 to T3. The simulated results revealed 41 ETZ types in China, accounting for 18% of the whole land area. Cold temperate grassland/humid forest and warm temperate arid forest(564,238.5 km~2), cold temperate humid forest and warm temperate arid/humid forest(566,549.75 km~2), and north humid/humid forest and cold temperate humid forest(525,750.25 km~2) were the main ETZ types, accounting for 35% of the total ETZ area in China. Between 2010 and 2100, the area of cold temperate desert shrub and warm temperate desert shrub/thorn steppe ETZs were projected to increase at a rate of 4% per decade, which represented an increase of 3604.2, 10063.1, and 17,242 km~2 per decade under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. The cold ETZ was projected to transform to the warm humid ETZ in the future. The average shift distance of the mean center in the north wet forest and cold temperate desert shrub/thorn grassland ETZs was generally larger than that of other ETZs, with the mean center moving to the northeast and the shift distance being more than 150 km during the periods from T0 to T3.In addition, with a gradual increase of temperature and precipitation, the ETZs in northern China displayed a shifting northward trend, while the area of ETZs in southern China decreased gradually, and their mean center moved to high-altitude areas. The effects of climate change on ETZs presented an increasing trend in China, especially in the Qinghai-Tibet Plateau.  相似文献   

8.
How species diversity–productivity relationships respond to temporal dynamics and land use is still not clear in semi-arid grassland ecosystems. We analyzed seasonal changes of the relationships between vegetation cover, plant density, species richness, and aboveground biomass in grasslands under grazing and exclosure in the Horqin Sandy Land of northern China. Our results showed that in grazed and fenced grassland, vegetation cover, richness, and biomass were lower in April than in August, whereas plant density showed a reverse trend. Vegetation cover during the growing season and biomass in June and August were higher in fenced grassland than in grazed grassland, whereas plant density in April and June was lower in fenced grassland than in grazed grassland. A negative relationship between species richness and biomass was found in August in fenced grassland, and in grazed grassland the relationship between plant density and biomass changed from positive in April to negative in August. The relationship between the density of the dominant plant species and the total biomass also varied with seasonal changes and land use (grazing and exclosure). These results suggest that long-term grazing, seasonal changes, and their interaction significantly influence vegetation cover, plant density, and biomass in grasslands. Plant species competition in fenced grassland results in seasonal changes of the relationship between species richness and biomass. Long-term grazing also affects seasonal changes of the density and biomass of dominant plant species, which further affects the seasonal relationship between plant density and biomass in grasslands. Our study demonstrates the importance of temporal dynamics and land use in understanding the relationship between species richness and ecosystem function.  相似文献   

9.
LIU Yujie  YUAN Guofu 《地理学报》2010,20(6):861-875
Global climate change has significant impacts on agricultural production. Future climate change will bring important influences to the food security. The CERES-Wheat model was used to simulate the winter wheat growing process and production in Panzhuang Irrigation District (PID) during 2011–2040 under B2 climate scenario based on the Special Report on Emissions Scenarios (SRES) assumptions with the result of RCMs (Regional Climate Models) projections by PRECIS (Providing Regional Climates for Impacts Studies) system introduced to China from the Hadley Centre for Climate Prediction and Research. The CERES-Wheat model was calibrated and validated with independent field-measured growth data in 2002–2003 and 2007–2008 growing season under current climatic conditions at Yucheng Comprehensive Experimental Station (YCES), Chinese Academy of Sciences (CAS). The results show that a significant impact of climate change on crop growth and yield was noted in the PID study area. Average temperature at Yucheng Station rose by 0.86℃ for 1961–2008 in general. Under the B2 climate scenario, average temperature rose by 0.55℃ for 2011–2040 compared with the baseline period (1998–2008), which drastically shortened the growth period of winter-wheat. However, as the temperature keep increasing after 2030, the top-weight and yield of the winter wheat will turn to decrease. The simulated evapotranspiration shows an increasing trend, although it is not very significant, during 2011–2040. Water use efficiency will increase during 2011–2031, but decrease during 2031–2040. The results indicate that climate change enhances agricultural production in the short-term, whereas continuous increase in temperature limits crop production in the long-term.  相似文献   

10.
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  相似文献   

11.
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.  相似文献   

12.
Daily average temperature data from 48 meteorological stations in Chinese oases that are within the distribution area of Populus euphratica were analyzed to determine the spatiotemporal responses of this tree to climate change. Specifically, the start and end date as well as the number of days that comprised the growing season were analyzed with a multi-year trend line and using the Mann-Kendall mutation test, inverse distance weighted interpolation(IDW) in the software Arc GIS, a Morlet wavelet power spectrum, and correlation analysis. The results of this study show that, over the last 56 years, the start date of the P. euphratica growing season has advanced, while the end date has been postponed, and the number of days that comprise the growing season have gradually increased. The changing trend rates recovered in this analysis for these three time slices are –1.34 d/10 a, 1.33 d/10 a, and 2.66 d/10 a(α≥ 0.001), respectively. Data show that while spatial disparity is extremely significant, it is nevertheless the case that along a southwest-to-northeast transect of Chinese oases, the later the start date of the P. euphratica season, the sooner the end data and the shorter the growing season. Mutations points in start and end date, as well as for the growing season overall were observed in 2001, 1989, and 1996, respectively, and the data presented in this paper show that, in particular, the date of this end of this period is most sensitive to climate warming. Growing season cycles for P. euphratica are between 3.56 years and 7.14 years, consistent with the periodicity of El Ni?o events, while a start date cycle between 3.56 years and 4.28 years is consistent with atmospheric circulation cyclicity. The causal analysis presented in this paper shows that the Asian polar vortex area index(APVAI), the Qinghai-Tibet Plateau index(TPI), the westerly circulation index(WCI), and carbon dioxide emissions(CDE) are the main factors influencing spatiotemporal changes in the growth of P. euphratica, the effect of latitude during the growing season is more significant than altitude, and the start date of the growing season is more significantly influenced by these factors than end date. In addition, data show that the start date, end date, and length of the growing season are all significantly correlated with their average corresponding monthly temperature(corre-lation coefficients are –0.875, 0.770, and 0.897; α≥0.001). Thus, if the average temperature in March increases by 1℃, the start date of the growing season will advance by 2.21 days, while if the average temperature in October increases by the same margin then the seasonal end date will be delayed by 2.76 days. Similarly, if the average temperature between March and October increases by 1℃, the growing season will be extended by 7.78 days. The results of this study corroborate the fact that changes in the P. euphratica growing are sensitive to regional warming and are thus of considerable theoretical significance to our understanding of the responses of Chinese vegetation to climate change as well as to ecological restoration.  相似文献   

13.
Ephedraceae has been applied largely as a drought indicator to reconstruct Cenozoic paleoenvironment and paleoclimate. However, temperature indication of Ephedraceae has been largely ignored. Here, we provide a record of Ephedraceae percentage spanning from the Early Eocene to Middle Miocene (52–17 Myr B.P.) in the Xining Basin, northeastern Tibetan Plateau. This record is comparable to a compiled Cenozoic Ephedraceae record from five other basins in northwestern China. Both records show Ephedraceae percentages were high during the Early Eocene, and decreased gradually from the Middle Eocene to Late Oligocene, then maintained a stable level since the Late Oligocene. By comparing these two Ephedraceae records with the marine oxygen isotope record, we discuss the variation of Ephedraceae percentage in Middle Cenozoic in response to global temperature change. Ephedraceae percentage was high in the Early Paleogene, associated with subtropical or tropical vegetation types in a global greenhouse climate, and decreased in Early Oligocene, associated with global cooling, suggesting that Ephedraceae is warm-tolerant during the Paleogene. The low Ephedraceae percentages in the Late Oligocene and Miocene were uncoupled with global warming, which may imply that Ephedraceae began to adapt to a eurythermic climate in the inland desert environment of western China. Such adaptation may be a response to the high topography of the Tibetan Plateau.  相似文献   

14.
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.  相似文献   

15.
With the global warming, crop phenological shifts in responses to climate change have become a hot research topic. Based on the long-term observed agro-meteorological phenological data(1981–2009) and meteorological data, we quantitatively analyzed temporal and spatial shifts in maize phenology and their sensitivities to key climate factors change using climate tendency rate and sensitivity analysis methods. Results indicated that the sowing date was significantly delayed and the delay tendency rate was 9.0 d·10a-1. But the stages from emergence to maturity occurred earlier(0.1 d·10a-1θ1.7 d·10a-1, θ is the change slope of maize phenology). The length of vegetative period(VPL)(from emergence to tasseling) was shortened by 0.9 d·10a-1, while the length of generative period(GPL)(from tasseling to maturity) was lengthened by 1.7 d·10a-1. The growing season length(GSL)(from emergence to maturity) was lengthened by 0.4 d·10a-1. Correlation analysis indicated that maize phenology was significantly correlated with average temperature, precipitation, sunshine duration and growing degree days(GDD)(p0.01). Average temperature had significant negative correlation relationship, while precipitation, sunshine duration and growing degree days had significant positive correlations with maize phenology. Sensitivity analysis indicated that maize phenology showed different responses to variations in key climate factors, especially at different sites. The conclusions of this research could provide scientific supports for agricultural adaptation to climate change to address the global food security issue.  相似文献   

16.
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.  相似文献   

17.
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.  相似文献   

18.
近600年来北极与中国气候变化的对比   总被引：2，自引：2，他引：0  
A compilation of paleoclimate records from lake sediments, trees, ice cores, and historical documents provide a view of China and Arctic environmental changes in the last 600 years. Many of these changes have also been identified in sedimentary and geochemical signatures in deep-sea sediment cores from the North Atlantic Ocean, Arctic and Greenland and ice cores from the Qinghai-Tibet Plateau, confirming the linkage of environmental changes of different time scales between the Arctic and China. It is shown that the changes of precipitation, temperature and sea ice cover in Arctic were correlated with climate changes in China. This paper also developed a comparative research on the climate changes between Arctic and China both during the Little Ice Age (LIA) and the instrumental observation period. Cycles and trend of temperature variations during LIA and temperature and precipitation during the instrumental observation period are performed. We found some similarities and differences of environmental changes between Arctic and China.  相似文献   

19.
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.  相似文献   

20.
Yu  Wanhui  Zhang  Lijuan  Zhang  Hongwen  Jiang  Lanqi  Zhang  Ankang  Pan  Tao 《地理学报(英文版)》2020,30(3):439-454
The effects of human activities on climate change are a significant area of research in the field of global environmental change. Land use and land cover change(LUCC) has a greater effect on climate than greenhouse gases, and the effect of farmland expansion on regional drought is particularly important. From the 1910 s to the 2010 s, cultivated land in Songnen Plain increased by 2.67 times, the area of cultivated land increased from 4.92×10~4 km~2 to 13.14×10~4 km~2, and its percentage of all land increased from 25% to 70%. This provides an opportunity to study the effects of the conversion of natural grassland to farmland on climate. In this study, the drought indices in Songnen Plain were evaluated from the 1910 s to the 2010 s, and the effect of farmland expansion on drought was investigated using statistical methods and the Weather Research and Forecasting Model based on UK's Climatic Research Unit data. The resulting dryness index, Palmer drought severity index, and standardized precipitation index values indicated a significant drying trend in the study area from 1981 to 2010. This trend can be attributed to increases in maximum temperature and diurnal temperature range, which increased the degree of drought. Based on statistical analysis and simulation, the maximum temperature, diurnal temperature range, and sensible heat flux increased during the growing season in Songnen Plain over the past 100 years, while the minimum temperature and latent heat flux decreased. The findings indicate that farmland expansion caused a drying trend in Songnen Plain during the study period.  相似文献   

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