青藏高原月NDVI时空动态变化及其对气候变化的响应
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摘要
青藏高原脆弱的高寒植被对外界干扰十分敏感,使其成为研究植被对气候变化响应的理想区域之一。青藏高原气候变化剧烈,在较短的合成时间研究气候变化对植被的影响十分必要。因此,本文利用GIMMS NDVI时间序列数据集,研究了1982-2012年青藏高原生长季月尺度植被生长的时空动态变化,探讨了其与气温、降水量和日照时数等气候因子的响应关系。结果表明:在区域尺度上,除8月外,其他各月份植被均呈增加趋势,显著增加多发生在4-7月和9月;大部分月份的ND-VI增加速率随着时段的延长显著减小,表明NDVI增加趋势放缓;在像元尺度上,月NDVI显著变化的区域多呈增加趋势,但显著减少范围的扩张多快于显著增加。4月和7月植被生长主要是受气温和日照时数共同作用,6月和9月受气温的控制,而8月则主要受降水量的影响。长时间序列NDVI数据集的出现为采用嵌套时段研究植被生长变化趋势奠定了前提,而植被活动变化趋势的持续性则有助于形象表征植被活动变化过程、深入理解植被对气候变化的响应和预测植被未来生长变化趋势。由此推测,青藏高原月NDVI未来增加趋势总体上趋于缓和,但在像元尺度显著变化的区域趋于增加。
Understanding the spatial pattern and dynamic processes of vegetation changes and their causes is one of the key topics in research on global change of terrestrial ecosystems. Characterized by vulnerable alpine vegetation, which is sensitive to external disturbance, the Qinghai-Tibet Plateau is one of the ideal areas for studying the response of vegetation to climate change. It is necessary to investigate the impacts of climate change on vegetation in a short synthetic period because of the intense climate variations in the Qinghai-Tibet Plateau. Previous studies have not sufficiently investigated NDVI change comparisons between various periods and the persistence of NDVI trends. In this study, we investigated monthly vegetation dynamics in the QinghaiTibet Plateau and their relationships with climatic factors over 15 progressive periods of 18-32 years starting in1982. This was accomplished by using the updated Global Inventory Modeling and Mapping Studies(GIMMS)third generation global satellite Advanced Very High Resolution Radiometer(AVHRR) Normalized Difference Vegetation Index(NDVI) dataset and climate data. The NDVI time-synthesis method of each season masks the trends of NDVI variations within the single month. Except for August, vegetation increased in other six months,with a significant increase occurring in April-July and September. The increase rate of NDVI in most months decreased significantly with the extension of the period, indicating that the increasing trend of NDVI slowed down. At pixel scale, the regions with significant changes(including both increase and decrease) in NDVI showed increasing trends in most months, but the range of significant decreases in NDVI expanded faster than that of significant increases. Vegetation activities in the Qinghai-Tibet Plateau are generally controlled by temperature changes, but the dominant climatic factors affecting vegetation are varied in different months and regions. The vegetation activities in April and July were mainly promoted by temperature and sunshine hours,and those in June and September were controlled by temperature, and in August were mainly affected by precipitation. The emergence of long time series NDVI data sets provides a precondition for application of nested time series to study the trend analysis of vegetation growth and change. The persistence of the trend of vegetation activity may help to visualize the process of vegetation change, understand the vegetation response to climate change, and to predict thevegetation growth trend. It is inferred that the increases of NDVI in the future tend to be more moderate in general, but areas with significant pixel-scale changes in NDVI tend to increase in most months.
Understanding the spatial pattern and dynamic processes of vegetation changes and their causes is one of the key topics in research on global change of terrestrial ecosystems. Characterized by vulnerable alpine vegetation, which is sensitive to external disturbance, the Qinghai-Tibet Plateau is one of the ideal areas for studying the response of vegetation to climate change. It is necessary to investigate the impacts of climate change on vegetation in a short synthetic period because of the intense climate variations in the Qinghai-Tibet Plateau. Previous studies have not sufficiently investigated NDVI change comparisons between various periods and the persistence of NDVI trends. In this study, we investigated monthly vegetation dynamics in the QinghaiTibet Plateau and their relationships with climatic factors over 15 progressive periods of 18-32 years starting in1982. This was accomplished by using the updated Global Inventory Modeling and Mapping Studies(GIMMS)third generation global satellite Advanced Very High Resolution Radiometer(AVHRR) Normalized Difference Vegetation Index(NDVI) dataset and climate data. The NDVI time-synthesis method of each season masks the trends of NDVI variations within the single month. Except for August, vegetation increased in other six months,with a significant increase occurring in April-July and September. The increase rate of NDVI in most months decreased significantly with the extension of the period, indicating that the increasing trend of NDVI slowed down. At pixel scale, the regions with significant changes(including both increase and decrease) in NDVI showed increasing trends in most months, but the range of significant decreases in NDVI expanded faster than that of significant increases. Vegetation activities in the Qinghai-Tibet Plateau are generally controlled by temperature changes, but the dominant climatic factors affecting vegetation are varied in different months and regions. The vegetation activities in April and July were mainly promoted by temperature and sunshine hours,and those in June and September were controlled by temperature, and in August were mainly affected by precipitation. The emergence of long time series NDVI data sets provides a precondition for application of nested time series to study the trend analysis of vegetation growth and change. The persistence of the trend of vegetation activity may help to visualize the process of vegetation change, understand the vegetation response to climate change, and to predict thevegetation growth trend. It is inferred that the increases of NDVI in the future tend to be more moderate in general, but areas with significant pixel-scale changes in NDVI tend to increase in most months.
引文
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[31]张戈丽,欧阳华,张宪洲,等.基于生态地理分区的青藏高原植被覆被变化及其对气候变化的响应[J].地理研究,2010,29(11):2004-2016.[Zhang G L,Ouyang H,Zhang X Z,et al.Vegetation change and its responses to climatic variation based on eco-geographical regions of Tibetan Plateau[J].Geographical Research,2010,29(11):2004-2016.]
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[2]Pettorelli N,Chauvenet A L,Duffy J P,et al.Tracking the effect of climate change on ecosystem functioning using protected areas:Africa as a case study[J].Ecological Indicators,2012,20(9):269-276.
[3]Cao M K,Prince S D,Small J,et al.Remotely sensed interannual variations and trends in terrestrial net primary poductivity 1981-2000[J].Ecosystems,2004,7(3):233-242.
[4]Piao S L,Wang X H,Ciais P,et al.Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006[J].Global Change Biology,2011,17(10):3228-3239.
[5]Peng J,Liu Z H,Liu Y H,et al.Trend analysis of vegetation dynamics in Qinghai-Tibet Plateau using Hurst Exponent[J].Ecological Indicators,2012,14(1):28-39.
[6]De Jong R,De Bruin S,Schaepman M,et al.Quantitative mapping of global land degradation using Earth observations[J].International Journal of Remote Sensing,2011,32(21):6823-6853.
[7]林金煌,张岸,邓超,等.闽三角城市群地质灾害敏感性评价[J].地球信息科学学报,2018,20(9):1286-1297.[Lin JH,Zhang A,Deng C,et al.Sensitivity assessment of geological hazards in unban agglomeration of Fujian Delta Region[J].Journal of Geo-information Science,2018,20(9):1286-1297.]
[8]冀欣阳,骆磊,王心源,等.基于“DEM-NDVI-土地覆盖分类”的天山博格达自然遗产地植被垂直带提取与变化分析[J].地球信息科学学报,2018,20(9):1350-1360.[Ji X Y,Luo L,Wang X Y,et al.Identification and change analysis of mountain altitudinal zone based on DEM-ND-VI-Land cover classification in Tianshan Bogda Natural Heritage site[J].Journal of Geo-information Science,2018,20(9):1350-1360.]
[9]Prince S D,Becker-Reshef I,Rishmawi K.Detection and mapping of long-term land degradation using local net production scaling:Application to Zimbabwe[J].Remote Sensing of Environment,2010,113(5):1046-1057.
[10]Wessels K J,Prince S D,Malherbe J,et al.Can human-induced land degradation be distinguished from the effects of rainfall variability?A case study in South Africa[J].Journal of Arid Environments,2007,68(2):271-297.
[11]Fensholt R,Langanke T,Rasmussen K,et al.Greenness in semi-arid areas across the globe 1981-2007:An earth observing satellite based analysis of trends an drivers[J].Remote Sensing of Environment,2012,121(6):144-158.
[12]Shen M G,Tang Y H,Chen J,et al.Influence of temperature and precipitation before the growing season on spring phenolgoy in grasslands of the central and eastern Qinghai-Tibetan Plateau[J].Agricultural and Forest Meteorology,2011,151(12):1711-1722.
[13]Bai Z G,Dent D.Recent Land Degradation and Improvement in China.AMBIO[J].A Journal of the Human Environment,2009,38(3):150-156.
[14]Fensholt R,Rasmussen K.Analysis of trend in the Sahelian'rain-use efficiency'using GIMMS NDVI,RFE and GPCP rainfall data[J].Remote Sensing of Environment,2011,115(2):438-451.
[15]翟雅倩,张翀,周旗,等.秦巴山区植被覆盖与土壤湿度时空变化特征及其相互关系[J].地球信息科学学报,2018,20(7):967-977.[Zhai Y Q,Zhang C,Zhou Q,et al.Spatio-temporal variation and interrelationship of vegetation cover and soil moisture in Qinling-Daba Mountains[J].Journal of Geo-information Science,2018,20(7):967-977.]
[16]Van L W,Orr B J,Marsh S E,et al.Multi-sensor NDVIdata continuity:Uncertainties and implications for vegetation monitoring applications[J].Remote Sensing of Environment,2006,100:67-81.
[17]Shen M G,Zhang G X,Cong N,et al.Increasing altitudinal gradient of spring vegetation phenology during the last decade on the Qinghai-Tibetan Plateau[J].Agricultural and Forest Meteorology,2014,189-190:71-80.
[18]Ding M J,Zhang Y L,Sun X M,et al.Spatiotemporal variation in alpine grassland phenology in the Qinghai-Tibetan Plateau from 1999 to 2009[J].Chinese Science Bulletin,2013,58(3):396-405.
[19]孟梦,牛铮,马超,等.青藏高原NDVI变化趋势及其对气候的响应[J].水土保持研究,2018,25(3):360-365,372.[Meng M,Niu Z,Ma C,et al.Variation trend of NDVIand response to climate change in Tibetan Plateau[J].2018,25(3):360-365,372.]
[20]Piao S L,Cui M D,Chen A P,et al.Altitude and temperature dependence of change in the spring vegetation greenup date from 1982 to 2006 in the Qinghai-Xizang Plateau[J].Agricultural and Forest Meteorology,2011,151(12):1599-1608.
[21]Zhang G L,Zhang Y J,Dong J W,et al.Green-up dates in the Tibetan Plateau have continuously advanced from1982 to 2011[J].Proceeding of the National Academy of Science,2013,110(11):4309-4314.
[22]Zhou D W,Fan G Z,Huang R H et al.Interannual variability of the normalized difference vegetation index on the tiebetan plateau and its relationship with climate change[J].Advances in Atmospheric Sciences,2007,24(3):474-484.
[23]Zhang L,Guo H D,Lei L P,et al.Monitoring vegetation greenness variations in Qinghai-Tebet Plateau with MO-DIS vegetation index[J].IEEE,2011,760-762.
[24]Yang K,Ye B S,Zhou D G,et al.Response of hydrological cycle to recent climate changes in the Tibetan Plateau[J].Climate Change,2011,109(3-4):517-534.
[25]Qin J,Yang K,Liang S L,et al.The altitudinal dependence of recent rapid warming over the Tibetan Plateau[J].Climatic Change,2009,97(1-2):321-327.
[26]Lei Z,Su Z B,Ma Y M,et al.Accelerated changes of environmental conditions on the Tibetan Plateau caused by climate change[J].Journal of Climate,2011,24:6540-6550.
[27]Huang L,Liu J Y,Shao Q Q,et al.Changing inland lakes responding to climate warming in Northeastern Tibetan Plateau[J]Climatic Change,2011,109(3-4):479-502.
[28]Chen H,Zhu Q A,Wu N,et al.Delayed spring phenology on the Tibetan Plateau may also be attributable to other factors than winter and spring warming[J].Proceeding of the National Academy of Science,2011,108(19):E93.
[29]Peng J,Liu Z H,Liu Y H,et al.Trend analysis of vegetation dynamics in Qinghai-Tibet Plateau using Hurst Exponent[J].Ecological Indicators,2012,14(1):28-39.
[30]丁明军,张镱锂,刘林山,等.1982-2009年青藏高原草地覆盖度时空变化特征[J].自然资源学报,2010,25(12):2114-2122.[Ding M J,Zhang Y L,Liu L S,et al.Temporal and spatial distribution of grassland coverage change in Tibetan Plateau since 1982[J].Journal of Natural Resources,2010,25(12):2114-2122.]
[31]张戈丽,欧阳华,张宪洲,等.基于生态地理分区的青藏高原植被覆被变化及其对气候变化的响应[J].地理研究,2010,29(11):2004-2016.[Zhang G L,Ouyang H,Zhang X Z,et al.Vegetation change and its responses to climatic variation based on eco-geographical regions of Tibetan Plateau[J].Geographical Research,2010,29(11):2004-2016.]
[32]杨元合,朴世龙.青藏高原草地植被覆盖变化及其与气候因子的关系[J].植物生态学报,2006,30(1):1-8.[Yang YH,Piao S L.Variations in grassland vegetation cover in relation to climatic factors on the Tibetan Plateau[J].Journal of Plant Ecology,2006,30(1):1-8.]
[33]Yu H Y,Luedeling E,Xu J C.Winter and spring warming result in delayed spring phenology on the Tibetan Plateau[J].Proceeding of the National Academy of Science,2010,107(51):22151-22156.
[34]Yu H Y,Xu J C,Erick O,et al.Seasonal response of grasslands to climate change on the Tibetan Plateau[J].Plos One,2012,11(7):e49230.
[35]孙鸿烈,郑度,姚檀栋,等.青藏高原国家生态安全屏障保护与建设[J].地理学报,2012,67(1):3-12.[Sun H L,Zheng D,Yao T D,et al.Protection and construction of the national ecological security shelter zone on Tibetan Plateau[J].Acta Geographica Sinica,2012,67(1):3-12.]
[36]Pinzon J,Tucker C.A Non-Stationary 1981-2012AVHRR NDVI3g time Series[J].Remote Sensing,2014,6(8):6929-6960.
[37]https://nex.nasa.gov/nex/projects/1349/[EB/OL].
[38]Wang J,Dong J,Liu J,et al.Comparison of gross primary productivity derived from GIMMS NDVI3g,GIMMS,and MODIS in southeast asia[J].Remote Sensing,2014,6(3):2108-2133.
[39]Zeng F W,Collatz G,Pinzon J,et al.Evaluating and quantifying the climate-driven interannual variability in global inventory modeling and mapping studies(GIMMS)normalized difference vegetation index(NDVI3g)at global scales[J].Remote Sensing,2013,5(8):3918-3950.
[40]http://data.cma.cn/[EB/OL].
[41]Zhao X,Tan K,Zhao S,et al.Changing climate affects vegetation growth in the arid region of the northwest China[J].Journal of Arid Environments,2011,75(10):946-952.
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