甘青新1959-2008年草地气候生产潜力的变化特征与预测研究
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摘要
本文基于甘肃、青海、新疆三省106个国家气象站点1959~2008年逐月气温和降水数据,利用线性趋势线、Miami模型和Tharnthwaite Memorial模型、ArcGIS(Inverse Distance Weighted)插值等方法,对研究区草地生产潜力的时空变化特征进行分析,并根据R/S分析法和二元一次线性回归方程对未来草地生产潜力进行了气候预测。研究结果表明:
1.近50年来,除甘肃降水呈减少趋势,变化倾向率-3.574mm/10a,甘青新气温以及青新降水均呈增加趋势,变化倾向率分别为0.297℃/10a、0.309℃/10a、0.34℃/10a、4.479mm/10a、6.77mm/10a。
2.近50年来,甘肃草地降水生产潜力和蒸散生产潜力均出现减少趋势;甘青新温度生产潜力和青新降水、蒸散生产潜力呈线性增加趋势;各省草地季节和生长季的温度、降水、蒸散生产潜力变化趋势与年变化趋势一致。
3.通过相关性分析,比较得出:甘青新草地年平均和生长季生产潜力与降水量均呈线性相关,相关系数最小的为0.8619(α=0.001),而与气温相关系数最大的仅为0.598,可见,水分条件是研究区草地生产潜力的主导因素。
4.近50年来,甘青新降水量大多呈增加趋势,减少区域较少,主要分布于甘肃;多年平均降水量总体上看,基本从中部向南、向北递增;草地生产潜力变率空间分布和降水量变率整体趋势一致,增幅较大区域主要分布在新疆和青海,草地生产潜力减少的地区中,甘肃所占比例高达76.92%;草地生产潜力空间分布整体上也是从中部向南、向北增加。
5.由R/S分析法得出,甘青新气温、降水和草地生产潜力在未来会持续现在的变化趋势;通过建立二元一次线性回归方程得出,甘肃、青海、新疆草地生产潜力和温度、降水均呈正比例关系。甘肃省草地气候生产潜力每10年会减少19.597kg/(hm~2·a),青海和新疆草地生产潜力每10年会增加106.863kg/(hm~2·a)、170.601kg/(hm~2·a)。
Based on the observed data of monthly temperature and precipitation of 106 weather stations from 1959 to 2008 in Gansu, Qinghai and Xinjiang, characteristics of the temporal and spatial of the potential productivity of grassland are analyzed with methods of the linear trend, Miami and Tharnthwaite Memorial model, ArcGIS. Predict the future potential productivity of grassland according to the R/S method and the binary linear regression equations. The main conclusions are as following:
1. In the recent 50 years, both the annual temperature and precipitation show a linear increase in Qinghai and Xinjiang, the change rate are respectively 0.309℃/10a, 0.34℃/10a, 4.479mm/10a and 6.77mm/10a. The change rate of annual temperature is 0.297℃/10a in Gansu, while the precipitation has a distinctly decreasing tendency,with a speed of -3.574mm/10a.
2. In the recent 50 year, the temperature potential productivity of grassland appear obvious increasing tendency by linear trend in study area. The precipitation and evapotranspiration potential productivity of grassland in Qinghai and Xinjiang also show the increasing tendency, but they come to decrease in Gansu. In spring, summer and autumn, also in growth season the temperature, precipitation and evapotranspiration potential productivity of grassland change tendency is consistent with the annual variation tendency.
3. Through contrast and correlation analysis, it shows the linear correlation basically between the potential productivity of grassland and precipitation in Gansu, Qinghai and Xinjiang. The smallest correlation coefficient reaches as high as 0.861 (α=0.001), but the biggest correlation coefficient is only 0.598 between the potential productivity of grassland and temperature. Obviously, the dominant factor of grassland production potential in the study area is moisture condition.
4. In recent 50 years, the precipitation mostly assumes increasing in study area, the region to be few, mainly in Gansu. The average annual precipitation performed the middle part is the fewest,and increase to either south or north. The potential productivity of grassland change tendency is consistent with the precipitation, the increased area mainly in Xinjiang and Qinghai. In the decreasing area, Gansu accounts for the proportion to reach as high as 76.92%. The potential productivity of grassland is also increases from the middle to south and north.
5. By the R/S method, the temperature, precipitation and the potential productivity of grassland will continue present's change tendency in the future. By establishing a binary linear regression equation, the temperature, precipitation and evapotranspiration potential productivity of grassland in the three regions all present the proportional relations. The potential productivity of grassland will decrease 19.597kg/(hm~2·a) every 10 years in Gansu, while in Qinghai and Xinjiang, it will increase 106.863kg/(hm~2/·a) and 170.601kg/(hm~2/·a) every 10 years.
1.近50年来,除甘肃降水呈减少趋势,变化倾向率-3.574mm/10a,甘青新气温以及青新降水均呈增加趋势,变化倾向率分别为0.297℃/10a、0.309℃/10a、0.34℃/10a、4.479mm/10a、6.77mm/10a。
2.近50年来,甘肃草地降水生产潜力和蒸散生产潜力均出现减少趋势;甘青新温度生产潜力和青新降水、蒸散生产潜力呈线性增加趋势;各省草地季节和生长季的温度、降水、蒸散生产潜力变化趋势与年变化趋势一致。
3.通过相关性分析,比较得出:甘青新草地年平均和生长季生产潜力与降水量均呈线性相关,相关系数最小的为0.8619(α=0.001),而与气温相关系数最大的仅为0.598,可见,水分条件是研究区草地生产潜力的主导因素。
4.近50年来,甘青新降水量大多呈增加趋势,减少区域较少,主要分布于甘肃;多年平均降水量总体上看,基本从中部向南、向北递增;草地生产潜力变率空间分布和降水量变率整体趋势一致,增幅较大区域主要分布在新疆和青海,草地生产潜力减少的地区中,甘肃所占比例高达76.92%;草地生产潜力空间分布整体上也是从中部向南、向北增加。
5.由R/S分析法得出,甘青新气温、降水和草地生产潜力在未来会持续现在的变化趋势;通过建立二元一次线性回归方程得出,甘肃、青海、新疆草地生产潜力和温度、降水均呈正比例关系。甘肃省草地气候生产潜力每10年会减少19.597kg/(hm~2·a),青海和新疆草地生产潜力每10年会增加106.863kg/(hm~2·a)、170.601kg/(hm~2·a)。
Based on the observed data of monthly temperature and precipitation of 106 weather stations from 1959 to 2008 in Gansu, Qinghai and Xinjiang, characteristics of the temporal and spatial of the potential productivity of grassland are analyzed with methods of the linear trend, Miami and Tharnthwaite Memorial model, ArcGIS. Predict the future potential productivity of grassland according to the R/S method and the binary linear regression equations. The main conclusions are as following:
1. In the recent 50 years, both the annual temperature and precipitation show a linear increase in Qinghai and Xinjiang, the change rate are respectively 0.309℃/10a, 0.34℃/10a, 4.479mm/10a and 6.77mm/10a. The change rate of annual temperature is 0.297℃/10a in Gansu, while the precipitation has a distinctly decreasing tendency,with a speed of -3.574mm/10a.
2. In the recent 50 year, the temperature potential productivity of grassland appear obvious increasing tendency by linear trend in study area. The precipitation and evapotranspiration potential productivity of grassland in Qinghai and Xinjiang also show the increasing tendency, but they come to decrease in Gansu. In spring, summer and autumn, also in growth season the temperature, precipitation and evapotranspiration potential productivity of grassland change tendency is consistent with the annual variation tendency.
3. Through contrast and correlation analysis, it shows the linear correlation basically between the potential productivity of grassland and precipitation in Gansu, Qinghai and Xinjiang. The smallest correlation coefficient reaches as high as 0.861 (α=0.001), but the biggest correlation coefficient is only 0.598 between the potential productivity of grassland and temperature. Obviously, the dominant factor of grassland production potential in the study area is moisture condition.
4. In recent 50 years, the precipitation mostly assumes increasing in study area, the region to be few, mainly in Gansu. The average annual precipitation performed the middle part is the fewest,and increase to either south or north. The potential productivity of grassland change tendency is consistent with the precipitation, the increased area mainly in Xinjiang and Qinghai. In the decreasing area, Gansu accounts for the proportion to reach as high as 76.92%. The potential productivity of grassland is also increases from the middle to south and north.
5. By the R/S method, the temperature, precipitation and the potential productivity of grassland will continue present's change tendency in the future. By establishing a binary linear regression equation, the temperature, precipitation and evapotranspiration potential productivity of grassland in the three regions all present the proportional relations. The potential productivity of grassland will decrease 19.597kg/(hm~2·a) every 10 years in Gansu, while in Qinghai and Xinjiang, it will increase 106.863kg/(hm~2/·a) and 170.601kg/(hm~2/·a) every 10 years.
引文
[1]蔡福,于贵瑞,祝青林,等.气象要素空间化方法精度的比较研究—以平均气温为例[J].资源科学,2005,27(5):173-179.
[2]陈国南.用迈尔密模型测算我国生物生产量的初步尝试[J].自然资源学报,1987,2(3): 270-278.
[3]陈利军,刘高焕,冯险峰.遥感在植被净第一性生产力研究中的应用[J].生态学杂志,2002,21 (2):53-57.
[4]邓慧平,祝廷成.全球气候变化对松嫩草原土壤水分和生产力影响的研究[J].草地学报,1998, 6(2):147-152.
[5]丁一汇,高素华.痕量气体对我国农业和生态系统影响研究[M].北京:中国科学技术出版社, 1995.148-166.
[6]方精云,唐艳鸿,林俊达,等.全球生态学-气候变化与生态响应[M].北京:高等教育出版社,海德堡施普林格出版社,2000.
[7]冯新灵,冯自立,罗隆诚,等.青藏高原冷暖气候变化趋势的R /S分析及Hurst指数试验研究[J].干旱区地理,2008,31(2):175-181.
[8]冯新灵,罗隆诚,邱丽丽,等.青藏高原至中国东部年雨日变化趋势的分析研究[J].地理研究,2007,26(4):836-843.
[9]冯宗伟,王效科,吴刚.中国森林生态系统的生物量和生产力[M].北京:科学出版社,1999.
[10]傅德平,赵志敏,苏静,等.基于GIS的新疆降水空间插值方法分析[J].水土保持研究.2008,15(6): 35-37.
[11]甘肃省草原总站.甘肃草地资源[M]兰州:甘肃科学技术出版社,1999,10.
[12]公延明,胡玉昆,阿德力·麦地,等.高寒草原对气候生产力模型的适用性分析[J].草业学报,2010, 19(2):7-13.
[13]国家环境保护局自然保护司.中国生态问题报告北京:中国环境出版社,1999.10-53.
[14]贺庆棠,Baumqartner, A.中国植被的可能生产力:农业和林业的气候产量[J].北京林业大学学报,1986,(2):84-98.
[15]侯光良,游松才.用筑后模型估算我国植被气候生产力[J].自然资源学报,1990, 5(1):60-65.
[16]侯西勇.1951-2000年中国气候生产潜力时空动态特征[J].干旱区地理, 2008,31(5):723-730.
[17]姜怒等.草原生态研究方法[M].北京:农业出版社,1988.
[18]江田汉,邓莲堂.Hurst指数估计中存在的若干问题[J].地理科学,2004,24(2):177-182.
[19]靳立亚,符娇兰,陈发虎.近44年来中国西北降水量变化的区域差异以及对全球变暖的响应[J].地理科学, 2005,25(5):568-572.
[20]李存焕.短花针茅草原植物群落生产力与气候波动的关系[J].内蒙古草业,2000,(1):36-40.
[21]李广,黄高宝.北方农牧交错带气候变化及草地生产力的响应—以甘肃省定县为例[J].中国草地,2005,27(1):7-11.
[22]李文华.森林生物生产力的概念及其研究的基本途径[J].自然资源,1978,(1):71-92.
[23]李霞,李晓兵,王宏,等.气候变化对中国北方温带草原植被的影响[M].北京师范大学学报(自然科学版), 2006,42(6):618-623.
[24]李银鹏,季劲钧.全球陆地生态系统与大气之间碳交换的模拟研究[J].地理学报,2001,56(4): 379-389.
[25]李镇清,刘振国,陈佐忠,杨宗贵.中国典型草原区气候变化及其对生产力的影响[J].草业学报,2003,12(1):4-10.
[26]联合国开发计划署,联合国环境规划署,世界银行,世界资源研究所.世界资源报告(2000- v2001).北京:中国环境出版社,2000.44.
[27]刘彩红.近45a新疆气候特征及异常研究[D].南京信息工程大学研究生论文.2008:9-10.
[28]刘世荣,郭泉水,王兵.中国森林生产力对气候变化响应的预测研究[J].生态学报,1998,18(5): 478-483.
[29]刘黎明,张凤荣,赵英伟.国草地资源生产潜力分析及其可持续利用对策[J].中国人口·资源与环境,2002,12(4):100-105.
[30]刘卫国,魏文寿,刘志辉.新疆气候变化下植被净初级生产力格局分析[J].干旱区研究,2009,26 (2):206-211.
[31]刘新平,吕晓.新疆牧草地资源利用动态变化及其绩效分析[J].干旱区地理,2009,32(1): 81-86.
[32]马克平,刘玉彦.草地生态系统初级生产力研究综述.齐齐哈尔师范学院学报(自然科学版)[J],1991,11(1):49-55.
[33]牛建明.气候变化对内蒙古草原分布和生产力影响的预测研究[J].草地学报,2001,9(4): 277-282.
[34]朴世龙,方精云,贺金生等.中国草地植被生物量及其空间分布格局[J].植物生态学报,2004,28(4):491-498.
[35]秦大河,丁一汇,苏纪兰等.中国气候与环境演变评估(I):中国气候与环境变化及未来趋势.气候变化研究进展,2005,l(l):4-9.
[36]秦大河.中国西部环境演变评估综合报告[M].北京:科学出版社,2002:56-66.
[37]施雅风,沈永平,李栋梁,等.中国西北气候由暖干向暖湿转型的特征和趋势探讨[J].第四纪研究,2003,23(2):153-164.
[38]孙睿,朱启疆.中国陆地植被净第一性生产力及季节变化研究[J].地理学报,2000,55(1): 36-45.
[39]王春芳,叶茂,徐海量.新疆草地生态系统的服务功能及其价值评估初探[J].石河子大学学报(自然科学版). 2006,24(2):217-222.
[40]王鹏祥,杨金虎,张强,等.近半个世纪来中国西北地面气候变化基本特征[J].地球科学进展, 2007,22(6):649-656.
[41]汪青春.牧草生长发育与气象条件的关系及气候年景研究[J].中国农业气象,1998,19(3): 1-7.
[42]伍光和,江存远.甘肃省综合自然区划[M].兰州:甘肃学科技术出版社,1998.
[43]许国成.甘肃省草地畜牧业可持续发展战略与对策[J].草业科学,2006,23(9):106-108.
[44]杨英莲.青海省天然草地NDVI的时空化与气温和降水的关系分析[D].南京信息工程大学硕士学位论文,2008.
[45]杨正礼,杨改河.中国高寒草地生产潜力与载畜量研究[J].资源科学,2000,22(4):72-77.
[46]张斌,史凯,刘春琼,等.元谋干热河谷近50年分季节降水变化的DFA分析[J].地理科学,2009,29(4):562-566.
[47]张国胜,时兴合,李林,等.黄河源区气候变化及其对草原荒漠化的影响[J].资源生态环境网络研究动态, 2000,11(1):18-22.
[48]张宪洲.我国自然植被净第一性生产力的估算与分布[J].自然资源,1993,(1):15-21.
[49]张新时,杨奠安,倪文革.植被的PE(可能蒸散)指标与植被.气候分类(三)几种主要方法与PEP程序介绍[J].植物生态学与地植物学学报,1993,17(2):97-109.
[50]赵海滨,张维斌.草原干旱对天然牧草生长发育及产量形成的影响[J].内蒙古环境保护,2002,14(2):22-25.
[51]赵慧颖.气候变化对典型草原区牧草气候生产潜力的影响[J].中国农业气象,2007,28(3): 281-284.
[52]赵慧颖,魏学占,乌秋力,等.呼伦贝尔典型草原区牧草气候生产潜力评估[J].干旱地区农业研究,2008,26 (1):138-159.
[53]周广胜,张新时.自然植被净第一性生产力模型初探[J].植物生态学报,1995,19(3):193-200.
[54]周广胜,张新时.全球气候变化的中国自然植被的净第一性生产力研究[J].植物生态学报,1996,20(1):11-19.
[55]朱志辉.自然植被净第一性生产力估算模型[J].科学通报,1993,38(15):1422-1426.
[56]Alward R D,Detling J K,Milehunas D G. Grassland vegetation changes and nocturnal global warming[J]. Science, 1999, 283:229-231.
[57]Bohm W著,薛德榕等译.根系研究法[M].北京:科学出版社,1985.
[58]Boone R B, Galvin K A, Coughenour M B et al. Ecosystem modeling adds value to South African climate forecast. Climatic Change, 2004, 64:317-340.
[59]Breymeyer A. J. and Van Dyne G M. Grasslands, systems and man, IBP 19.1980.
[60]Christensen L, Coughenour M B, Ellis J E et al. Vulnerability of The Asian Typical Steppe to Grazing. Climatic Change. 2004, 63:351-368.
[61]Claussen M, Brovkin V, Ganopolski A et al. Climate change in Northern Africa: the past is not the future. Climatic Change, 2003, 57:99-118.
[62]Coupland R T (ed). Grassland Ecosystems of the World: Analysis of Grasslands and Their User, 1979, Cambridge University Press.
[63]Field C B, J T Randerson, and C M Malstrom. Global net primary production: combining ecology and remote sensing[J].Remote Sensing of Environment, 1995, 51:74-88.
[64]H. J. Smit, M. J. Metzger, F. Ewert. Spatial distribution of grassland productivity and land use in Europe[J]. Agricultural Systems, 2008, 98:208-219.
[65]IGBP. A study of global change. The International Geosphere-Biosphere Programme: The initial core projects. Report 12, Stockholm, 1990.
[66]IGBP. The terrestrial carbon cycle: implications for the Kyoto Protocol[J].Science,1998,280: 1393-1394.
[67]Lieth, H.F.H., Modeling the primary productivity of the world. Nature and Resources, 1972,8(2): 5-10.
[68]Lieth, H., Whittaker, R.H. Primary Productivity of the Biosphere. New York: Springer-Verlag Press, 1975.
[69]Koppen W. Dasgeographisehes system derklimate[A]. In: Koppenwm(eds). Handbueder Klimatologie [C]. Berlin: Gebruder Bornt raeger, 1936, 27(3)337-343.
[70]O'Connor T G, Kiker G A. Collapse of The mapungubwe society: Vulilerability of pastoralism to increasing aridity. Climatic Change, 2004, 66: 49-66.
[71]Ojima D S, Parton V J, Coughenour M B, et al. Impact of climate and atmospheric carbon dioxide changes on grassland of the world[A].In: Breymeyer A I, Hall D O, Melillo J M etal.eds. Global Change: Effects on Coniferous Forests and Grasslands[C].John VGiley and Sons, 1996, 271-311.
[72]Parton W J, Scurlock J M 0, Ojima D S, et al. Impact of climate change on grassland production and carbon worldwide. Global Change Biology. 1995, 1:13-22.
[73]Rangarajan G, Dhananjay A S. Fractal dimensional analysis of Indian climatic dynamics [J]. Chaos, Solitons and Fractals,2004,19(2):285-291.
[74]Rehman S. Study of Saudi Arabian climatic conditions using Hurst exponent and climatic predictability index[J]. Chaos, Solitons and Fractals,2007,39(2):499-509.
[75]Sara Brogaard, Micael Runnstrom and Jonathan W. Seaquist. Primary production of Inner Mongolia, China, 1982 and 1999. estimated by a satellite data-driven light use efficiency model, Global and Planetary Change, 2005, 4(45):31-332.
[76]Scurlock J M O, Hall D O.T he global carbon sink: a grassland perspective[J].Global Change Biology,1998,4: 229-233.
[77]Scurlock J M O, Johnson K,Olson R J.Estimating net primary productivity from grassland biomass dynamics measurements[J].Global Change Biology,2002,8:736-753.
[78]Yan Dyne G M., Perspectives on the ELM model and modeling efforts, In: Grassland Simulation Model, Ed, G. S. Innis. Springer-verlag. 1978.
[2]陈国南.用迈尔密模型测算我国生物生产量的初步尝试[J].自然资源学报,1987,2(3): 270-278.
[3]陈利军,刘高焕,冯险峰.遥感在植被净第一性生产力研究中的应用[J].生态学杂志,2002,21 (2):53-57.
[4]邓慧平,祝廷成.全球气候变化对松嫩草原土壤水分和生产力影响的研究[J].草地学报,1998, 6(2):147-152.
[5]丁一汇,高素华.痕量气体对我国农业和生态系统影响研究[M].北京:中国科学技术出版社, 1995.148-166.
[6]方精云,唐艳鸿,林俊达,等.全球生态学-气候变化与生态响应[M].北京:高等教育出版社,海德堡施普林格出版社,2000.
[7]冯新灵,冯自立,罗隆诚,等.青藏高原冷暖气候变化趋势的R /S分析及Hurst指数试验研究[J].干旱区地理,2008,31(2):175-181.
[8]冯新灵,罗隆诚,邱丽丽,等.青藏高原至中国东部年雨日变化趋势的分析研究[J].地理研究,2007,26(4):836-843.
[9]冯宗伟,王效科,吴刚.中国森林生态系统的生物量和生产力[M].北京:科学出版社,1999.
[10]傅德平,赵志敏,苏静,等.基于GIS的新疆降水空间插值方法分析[J].水土保持研究.2008,15(6): 35-37.
[11]甘肃省草原总站.甘肃草地资源[M]兰州:甘肃科学技术出版社,1999,10.
[12]公延明,胡玉昆,阿德力·麦地,等.高寒草原对气候生产力模型的适用性分析[J].草业学报,2010, 19(2):7-13.
[13]国家环境保护局自然保护司.中国生态问题报告北京:中国环境出版社,1999.10-53.
[14]贺庆棠,Baumqartner, A.中国植被的可能生产力:农业和林业的气候产量[J].北京林业大学学报,1986,(2):84-98.
[15]侯光良,游松才.用筑后模型估算我国植被气候生产力[J].自然资源学报,1990, 5(1):60-65.
[16]侯西勇.1951-2000年中国气候生产潜力时空动态特征[J].干旱区地理, 2008,31(5):723-730.
[17]姜怒等.草原生态研究方法[M].北京:农业出版社,1988.
[18]江田汉,邓莲堂.Hurst指数估计中存在的若干问题[J].地理科学,2004,24(2):177-182.
[19]靳立亚,符娇兰,陈发虎.近44年来中国西北降水量变化的区域差异以及对全球变暖的响应[J].地理科学, 2005,25(5):568-572.
[20]李存焕.短花针茅草原植物群落生产力与气候波动的关系[J].内蒙古草业,2000,(1):36-40.
[21]李广,黄高宝.北方农牧交错带气候变化及草地生产力的响应—以甘肃省定县为例[J].中国草地,2005,27(1):7-11.
[22]李文华.森林生物生产力的概念及其研究的基本途径[J].自然资源,1978,(1):71-92.
[23]李霞,李晓兵,王宏,等.气候变化对中国北方温带草原植被的影响[M].北京师范大学学报(自然科学版), 2006,42(6):618-623.
[24]李银鹏,季劲钧.全球陆地生态系统与大气之间碳交换的模拟研究[J].地理学报,2001,56(4): 379-389.
[25]李镇清,刘振国,陈佐忠,杨宗贵.中国典型草原区气候变化及其对生产力的影响[J].草业学报,2003,12(1):4-10.
[26]联合国开发计划署,联合国环境规划署,世界银行,世界资源研究所.世界资源报告(2000- v2001).北京:中国环境出版社,2000.44.
[27]刘彩红.近45a新疆气候特征及异常研究[D].南京信息工程大学研究生论文.2008:9-10.
[28]刘世荣,郭泉水,王兵.中国森林生产力对气候变化响应的预测研究[J].生态学报,1998,18(5): 478-483.
[29]刘黎明,张凤荣,赵英伟.国草地资源生产潜力分析及其可持续利用对策[J].中国人口·资源与环境,2002,12(4):100-105.
[30]刘卫国,魏文寿,刘志辉.新疆气候变化下植被净初级生产力格局分析[J].干旱区研究,2009,26 (2):206-211.
[31]刘新平,吕晓.新疆牧草地资源利用动态变化及其绩效分析[J].干旱区地理,2009,32(1): 81-86.
[32]马克平,刘玉彦.草地生态系统初级生产力研究综述.齐齐哈尔师范学院学报(自然科学版)[J],1991,11(1):49-55.
[33]牛建明.气候变化对内蒙古草原分布和生产力影响的预测研究[J].草地学报,2001,9(4): 277-282.
[34]朴世龙,方精云,贺金生等.中国草地植被生物量及其空间分布格局[J].植物生态学报,2004,28(4):491-498.
[35]秦大河,丁一汇,苏纪兰等.中国气候与环境演变评估(I):中国气候与环境变化及未来趋势.气候变化研究进展,2005,l(l):4-9.
[36]秦大河.中国西部环境演变评估综合报告[M].北京:科学出版社,2002:56-66.
[37]施雅风,沈永平,李栋梁,等.中国西北气候由暖干向暖湿转型的特征和趋势探讨[J].第四纪研究,2003,23(2):153-164.
[38]孙睿,朱启疆.中国陆地植被净第一性生产力及季节变化研究[J].地理学报,2000,55(1): 36-45.
[39]王春芳,叶茂,徐海量.新疆草地生态系统的服务功能及其价值评估初探[J].石河子大学学报(自然科学版). 2006,24(2):217-222.
[40]王鹏祥,杨金虎,张强,等.近半个世纪来中国西北地面气候变化基本特征[J].地球科学进展, 2007,22(6):649-656.
[41]汪青春.牧草生长发育与气象条件的关系及气候年景研究[J].中国农业气象,1998,19(3): 1-7.
[42]伍光和,江存远.甘肃省综合自然区划[M].兰州:甘肃学科技术出版社,1998.
[43]许国成.甘肃省草地畜牧业可持续发展战略与对策[J].草业科学,2006,23(9):106-108.
[44]杨英莲.青海省天然草地NDVI的时空化与气温和降水的关系分析[D].南京信息工程大学硕士学位论文,2008.
[45]杨正礼,杨改河.中国高寒草地生产潜力与载畜量研究[J].资源科学,2000,22(4):72-77.
[46]张斌,史凯,刘春琼,等.元谋干热河谷近50年分季节降水变化的DFA分析[J].地理科学,2009,29(4):562-566.
[47]张国胜,时兴合,李林,等.黄河源区气候变化及其对草原荒漠化的影响[J].资源生态环境网络研究动态, 2000,11(1):18-22.
[48]张宪洲.我国自然植被净第一性生产力的估算与分布[J].自然资源,1993,(1):15-21.
[49]张新时,杨奠安,倪文革.植被的PE(可能蒸散)指标与植被.气候分类(三)几种主要方法与PEP程序介绍[J].植物生态学与地植物学学报,1993,17(2):97-109.
[50]赵海滨,张维斌.草原干旱对天然牧草生长发育及产量形成的影响[J].内蒙古环境保护,2002,14(2):22-25.
[51]赵慧颖.气候变化对典型草原区牧草气候生产潜力的影响[J].中国农业气象,2007,28(3): 281-284.
[52]赵慧颖,魏学占,乌秋力,等.呼伦贝尔典型草原区牧草气候生产潜力评估[J].干旱地区农业研究,2008,26 (1):138-159.
[53]周广胜,张新时.自然植被净第一性生产力模型初探[J].植物生态学报,1995,19(3):193-200.
[54]周广胜,张新时.全球气候变化的中国自然植被的净第一性生产力研究[J].植物生态学报,1996,20(1):11-19.
[55]朱志辉.自然植被净第一性生产力估算模型[J].科学通报,1993,38(15):1422-1426.
[56]Alward R D,Detling J K,Milehunas D G. Grassland vegetation changes and nocturnal global warming[J]. Science, 1999, 283:229-231.
[57]Bohm W著,薛德榕等译.根系研究法[M].北京:科学出版社,1985.
[58]Boone R B, Galvin K A, Coughenour M B et al. Ecosystem modeling adds value to South African climate forecast. Climatic Change, 2004, 64:317-340.
[59]Breymeyer A. J. and Van Dyne G M. Grasslands, systems and man, IBP 19.1980.
[60]Christensen L, Coughenour M B, Ellis J E et al. Vulnerability of The Asian Typical Steppe to Grazing. Climatic Change. 2004, 63:351-368.
[61]Claussen M, Brovkin V, Ganopolski A et al. Climate change in Northern Africa: the past is not the future. Climatic Change, 2003, 57:99-118.
[62]Coupland R T (ed). Grassland Ecosystems of the World: Analysis of Grasslands and Their User, 1979, Cambridge University Press.
[63]Field C B, J T Randerson, and C M Malstrom. Global net primary production: combining ecology and remote sensing[J].Remote Sensing of Environment, 1995, 51:74-88.
[64]H. J. Smit, M. J. Metzger, F. Ewert. Spatial distribution of grassland productivity and land use in Europe[J]. Agricultural Systems, 2008, 98:208-219.
[65]IGBP. A study of global change. The International Geosphere-Biosphere Programme: The initial core projects. Report 12, Stockholm, 1990.
[66]IGBP. The terrestrial carbon cycle: implications for the Kyoto Protocol[J].Science,1998,280: 1393-1394.
[67]Lieth, H.F.H., Modeling the primary productivity of the world. Nature and Resources, 1972,8(2): 5-10.
[68]Lieth, H., Whittaker, R.H. Primary Productivity of the Biosphere. New York: Springer-Verlag Press, 1975.
[69]Koppen W. Dasgeographisehes system derklimate[A]. In: Koppenwm(eds). Handbueder Klimatologie [C]. Berlin: Gebruder Bornt raeger, 1936, 27(3)337-343.
[70]O'Connor T G, Kiker G A. Collapse of The mapungubwe society: Vulilerability of pastoralism to increasing aridity. Climatic Change, 2004, 66: 49-66.
[71]Ojima D S, Parton V J, Coughenour M B, et al. Impact of climate and atmospheric carbon dioxide changes on grassland of the world[A].In: Breymeyer A I, Hall D O, Melillo J M etal.eds. Global Change: Effects on Coniferous Forests and Grasslands[C].John VGiley and Sons, 1996, 271-311.
[72]Parton W J, Scurlock J M 0, Ojima D S, et al. Impact of climate change on grassland production and carbon worldwide. Global Change Biology. 1995, 1:13-22.
[73]Rangarajan G, Dhananjay A S. Fractal dimensional analysis of Indian climatic dynamics [J]. Chaos, Solitons and Fractals,2004,19(2):285-291.
[74]Rehman S. Study of Saudi Arabian climatic conditions using Hurst exponent and climatic predictability index[J]. Chaos, Solitons and Fractals,2007,39(2):499-509.
[75]Sara Brogaard, Micael Runnstrom and Jonathan W. Seaquist. Primary production of Inner Mongolia, China, 1982 and 1999. estimated by a satellite data-driven light use efficiency model, Global and Planetary Change, 2005, 4(45):31-332.
[76]Scurlock J M O, Hall D O.T he global carbon sink: a grassland perspective[J].Global Change Biology,1998,4: 229-233.
[77]Scurlock J M O, Johnson K,Olson R J.Estimating net primary productivity from grassland biomass dynamics measurements[J].Global Change Biology,2002,8:736-753.
[78]Yan Dyne G M., Perspectives on the ELM model and modeling efforts, In: Grassland Simulation Model, Ed, G. S. Innis. Springer-verlag. 1978.