摘要
地表植被覆盖与全球气候变化互为因果,相互影响着对方的变化。因此,植被覆盖变化研究也成为全球气候研究的主要对象。由于肃北绿洲地处西北地区,生态环境脆弱,其草原植被对于气候变化比较敏感。所以对这一地区长时间动态植被的研究具有极为重要的意义。
本研究借助于肃北绿洲统计数据、1995年和2000年两期土地利用数据、马鬃山气象站1960-2005年降水量和气温数据、肃北气象站1974-2005年降水量和气温数据,分别对肃北绿洲草原得动态变化特征、草原类型变化景观格局及草原对气候变化的响应和预测进行了研究。以便更好的认识研究区草原资源潜力和自然环境,特别是全球变化背景下,气候变化对草原生产力的影响与响应,通过预测,对不同区域采用不同的防治草原生态恶化的措施,从而促进区域农牧业发展和生态环境的良好循环。研究结果表明:
(1)基于统计资料的分析表明,1995年以前肃北绿洲草原退化比较严重,特别是80年代最为严重。
(2)基于1995和2000年遥感资料分析表明,除未利用土地外,草原是最大的土地利用类型,且1995年以后肃北绿洲草原向着好的方向转变,面积有所增加。
(3)通过遥感资料提取的肃北绿洲不同草类的景观格局变化分析表明,研究区自1995年以后,高、中、低三类草原植被均有所改善,其中,中覆盖度草原植被改善明显。
(4)肃北草原动态变化的原因分析表明,1995年以前,草原退化主要与气候因素、自然灾害、水土流失、水资源逐渐萎缩及草原过牧、过度樵柴等自然和人为因素有关。而1995年以后,则与西部大开发战略的实施和生态环境保护的措施力度加大有关。
(5)通过气候资源评价模型对肃北草原气候资源的评价表明,肃北气候资源丰富程度较差,再加上各气候要素的配合程度不好,致使肃北天然牧草对气候的利用系数较低。
(6)通过采用Miami、Thornthwaite Memorial模型对肃北绿洲草原气候生产潜力的估算表明,温度和降水都会影响草原生产潜力,但降水是影响草原气候产量的最重要的因素。
(7)根据回归方程预测表明,肃北北部年平均温度每升高/降低1℃,草地生产潜力增加/减少0.001 t/hm~2·a,年降水量每增加/减少1 mm,草地生产潜力增加/减少0.008 t/hm~2·a。而肃北南部年平均温度每升高/降低1℃,草地生产潜力增加/减少0.006 t/hm~2·a,年降水量每增加/减少1 mm,草地生产潜力增加/减少0.007 t/hm~2·a。
(8)针对肃北草原植被动态变化及其对气候变化的响应提出具体应对措施。
It’s well known that earth vegetation and global climatic change have effects on each other. They affect each other in change direction. Therefore, the vegetation change has become the main and direct object of the global climatic study. Because of the special geographical position and the frail ecological environment in Subei, the grassland vegetation is much sensitive to the climatic change. Thus, the research on grass dynamic change in a long time series makes extremely great sense.
Based on Statistical data, the two land use maps in 1986 and 2000, precipitation and the temperature data during 1960-2005 of Mazhong shan, precipitation and the temperature data during 1974-2005 of Subei oasis, On this basis, grassland characteristics, feature of all grassland patch types, the response to climate change and predict of SuBei oasis are studied. In order to better understanding of grassland resource potential study area and the natural environment, especially under the background of global change of climate change, the influence and response of grassland productivity, through prediction of different regions, using different grassland ecological deteriorating measures, so as to promote the development of regional agriculture ecological environment and good circulation. The article mainly divides into the following several parts:
(1) The statistical data analysis shows that, before 1995, SuBei oasis was degenerated, especially, the most serious in the 1980s.
(2) Analysis based on 1995 and 2000 remote sensing data shows that, since 1995, Subei oasis grassland in the right direction, grassland area increased.
(3) The feature of three grassland patch types of SuBei oasis extracted by remote sensing data shows that, the study area since 1995, high, medium and low grassland vegetation types are improved, among them, medium grassland vegetation types improved obviously.
(4)The causes of Subei oasis grassland dynamic analysis shows that, before 1995, main factors of grassland degeneration are natural and human factors about degeneration and climate factors, natural disasters, soil erosion, water gradually atrophic and grassland excessive, firewood wood, etc. But, since 1995, main factors of grassland are the strategy of implementation of the western development and protect the ecological environment.
(5) Through the climatic resources evaluation model, the evaluation of SuBei climate resource shows that, SuBei climatic resources abundant degree is bad, Plus the climate elements of cooperation is bad, natural causes of climate forage utilization coefficient is low in SuBei county.
(6) Using Miami and Thornthwaite Memorial models, Climate-Production of the natural grassland in Subei Oasis shows that, precipitation is the most important factors to Climate-Production of the natural grassland
(7) Regression equation prediction shows that, in the north of Subei Oasis, average temperature increase or decrease 1℃, Climate-Production of the natural grassland increase or decrease 0.001 t/hm~2·a, annual precipitation increase or decrease 1 mm, Climate-Production of the natural grassland increase or decrease 0.008 t/hm~2·a. but in the south of Subei Oasis, average temperature increase or decrease 1℃, Climate-Production of the natural grassland increase or decrease 0.006 t/hm~2·a, annual precipitation increase or decrease 1 mm, Climate-Production of the natural grassland increase or decrease 0.007 t/hm~2·a.
(8) Fifthly, based on the research results, countermeasures have been put forward, which in order to promote respectful grassland vegetation dynamic change and their response in climatic change in Subei Oasis.
引文
[1]柴永青,常寿,索义拉.草业知识实用指南[M]. 2000.
[2]程积民,邹厚远.黄土高原草原合理利用与草原植被演替过程的试验研究[J].草业学报, 1995, 4:17-22.
[3]陈效逑,王恒. 1982-2003年内蒙古植被带和植被覆盖度的时空变化[J].地理学报, 2009, 64(1).
[4]池宏康.沙地油篙群落覆盖度的遥感定量化研究[J].植物生态学报, 2000, 24(4):494-497.
[5]邓朝平,郭铌,王介民,马金辉.近20余年来西北地区植被变化特征分析[J].冰川冻土, 2006, 28 (5) :686-693.
[6]冯永忠,杨改河,王得祥等.近40年来江河源区草地生态压力动态分析[J].生态学报, 2009, 29 (1) :492-498.
[7]季劲钧,黄玫,刘青.气候变化对中国中纬度半干旱草原生产力影响机理的模拟研究[J].气象学报,2005,6(3):257-268.
[8]纪亚君.放牧对草地植被及土壤的影响[J].青海畜牧兽医杂志, 2002, 32(4):42-44.
[9]金之庆,方娟,葛道阔等.全球气候变化影响我国冬小麦生产之前[J].作物学报, 1994, 20(2) :186-197.
[10]黄敬峰.NOAA气象卫星草地遥感研究动态.国外畜牧业[J].草原与牧草, 1993, 1:15-20.
[11]李建龙,黄敬峰,王秀珍.草地遥感[M].北京:气象出版社, 1993.
[12]李金桐.基于GIS的MODIS环境荒漠化监测中的应用方法研究[J].新疆气象, 2002, 2:21-23.
[13]李双才,孔亚平,符素华.北京山区植被盖度季节变化规律模拟研究[J].北京师范大学学报(自然科学版), 2002, 38(2):273-278.
[14]李霞,李晓兵,王宏,喻锋,余弘婧,杨华.气候变化对中国北方温带草原植被的影响[J].北京师范大学学报(自然科学版), 2006, 42(6) :618-623.
[15]李晓兵,史培军.基于NOAA/ AVHRR数据的中国主要植被类型NDVI变化规律研究[J].植物学报, 1999 , 41 (3) .
[16]李裕元,邵明安,上官周平等.黄土高原北部紫花苜蓿草地退化过程与植被演替研究[J].草叶学报, 2006,2(3):314-324.
[17]李荣平,闫巧玲.放牧与刈割对科尔沁草甸植被演替的影响[J].干旱区资源与环境,2006,20(2):180-184.
[18]李震,阎福礼,范湘涛.中国西北地区NDVI变化及其与温度和降水的关系[J].遥感学报, 2005, 9(3):8~13.
[19]刘纪远,徐新良,邵全琴.近30年来青海三江源地区草地退化的时空特征进行[J].地学,2008,63(4):364-376.
[20]刘江.中国农业发展战略[M].北京:中国农业出版社, 2000.
[21]刘黎明,张凤荣,赵英伟.我国草地资源生产潜力分析及其可持续利用对策[J].中国口·资源与环境, 2002, 12(4) :100-105.
[22]刘荣堂,孙祥云.肃北县草原生态环境的主要问题与利用保护对策[J].草业科学, 2003, 20(10) :13-16.
[23]刘钟龄.锡林郭勒草原退化状况和生态环境评价.科技部科研院所社会公益研究专项资金项目“北方草原生态系统野外观测基础数据库和共享”, 2002.
[24]卢玲.黑河流域景观结构与景观变化研究[D].中国科学院硕士论文, 2003,(2):232-236.
[25]梅安新,彭望琭,秦其明等.遥感导论[M].北京,高等教育出版社, 2001.
[26]钱拴,毛留喜,张艳红.中国天然草地植被生长气象条件评价模型[J].生态学杂志, 2007,26(9):1500-1504.
[27]苏建平,李麒麟,仵彦卿.祁连山西段与酒泉盆地草地资源可持续利用分析[J].西北植物学报2003, 23(10) :1735-1739.
[28]孙红雨,王长耀,牛铮等.中国地表植被夜盖变化及其与气候因子关系—基于NOVV时间序列数据分析[J].遥感学报, 1998, 2: 204-209.
[29]陶格涛,陈敏,柳景辉.退化羊草Leymuschinensis草原恢复演替动态的研究[J].内蒙古大学学报(自然科学版), 1996, 27(1):354-360.
[30]王根绪,程国栋,沈永平等.近50年来河西走廊区域生态环境变化特征与综合防治对策[J].自然资源学报.
[31]王浩等.西北地区水资源合理配置和承载力研究[J].郑州:黄河水利出版社, 2003.
[32]王鑫厅,王炜,梁存柱.典型草原退化群落不同恢复演替阶段羊草种群空间格局的比较[J].植物生态学报,2009, 33(1):63-70.
[33]魏凤英.现代气候统计诊断与预测技术[M].北京:气象出版社, 1999: 115-131.
[34]巫荣征.草原化荒漠天然牧草产量与气象条件的关系[A].《畜牧气象文集》编委会.畜牧气象文集[C].北京:气象出版社1991, 78~83.
[35]严作良,周华坤,刘伟等.江河源区草地退化状况及成因[J].中国草地, 2003, (1):74-79.
[36]姚洪林,闰德仁,杨文斌,余伟在,刘永军,于树平.内蒙古沙漠化土地与植被演替规律的研究[J].内蒙古林业科技, 2001, 04:7-12.
[37]姚玉璧,王毅荣,张存杰等.黄土高原作物气候生产力对气候变化的响应[J].南京气象学院学报, 2006, 29 (1) :101-106.
[38]尹东,王长根.中国北方牧区牧草气候资源评价模型[J].自然资源学报, 2002, 17(4): 494-498.
[39]云红琦等,北蒙古自治县畜牧业志. [M]. 2000
[40]张宏斌.基于多源遥感数据的草原植被状况变化研究[D].中国农业科学院博士论文, 2007, 9.
[41]张继义,赵哈林.尔沁沙地草地植被恢复演替进程中群落优势种群空间分布格局研究[J].生态学杂志, 2004, 23(2):l-6.
[42]张贞明.甘肃河西走廊草业生态可持续发展探讨[J].农村生态环境保护, 2007, 11.
[43]赵静.三峡库区1988~2007年植被覆盖动态变化研究[D].华中农业大学博士论文, 2008.
[44]赵茂盛,符淙斌,延晓东等.应用遥感数据研究中国植被生态系统与气候的关系[J].地理学报, 2001, 56 (3): 287-296.
[45]赵英时等.遥感应用分析原理与方法[M].北京:科学出版社. 2003.
[46]邹亚荣,张增祥,赵晓丽等. GIS支持下我国干旱区草地资源动态分析[J].环境科学研究, 2003, 16(1).
[47]张连义,刘爱军,邢旗等.内蒙古典型草原区植被动态与植被恢复——以锡林郭勒盟典型草原区为例[J].干旱区资源与环境,2006,20(2):185-190.
[48]张云霞,李晓兵,陈云浩.草地植被盖度的多尺度遥感与实地测量方法综述[J].地球科学进展, 2003, 18(1):85-93.
[49]周广胜,张新时.全球变化的中国气候.植被分类研究[J].植物学报, 1996, 38(l) :8-17.
[50]周华坤,周立,刘伟等.青海省玛多县草地退化原因及畜牧业可持续发展[J].中国草地, 2003, 26(6): 64-68.
[51]周辛平.甘肃草产业发展方略研究[J].甘肃农业, 2001, 8, 1-11.
[52]周振林.飞播草原植被演替动态研究[J].内蒙古草业, 1995, 21.
[53] Alfredo D. Collado, Emilio Chuvieeo, Ana Camarasa. Satellite remote sensing anatysis to monitor desertification processes in the crop-rangeland boundary of Argentina, Journal of Arid Environments, 2002, 1(52):121-133.
[54] Bogaert J, Zhou L, Tucker C, et al. Evidence for a persistent and extensive greening trend in Eurasia inferred from satellite vegetation index data. Journal of Geophysical Research, 2002, 107(10):1~13.
[55] Breymeyer A.J.and Van Dyne G M., Grasslands, systems and man, IBP19.1980.
[56] Corenblit D, abacchi E,Steiger J,Gurnell AM(2007).Reciprocal interactions and adjustments between flu-vial landforms and vegetation dynamics in river corridors: a review of complementary approaches.Earth-Science Reviews,84,56-86.
[57] Du Plessis W R. Linear regression relationships between NDVI, vegetation and rainfall in Etosha National Park Namibia. Journal of Arid Environments, 1999, (42) :235- 260.
[58] Dykstethuis,E.J. Condition and management of rangeland based on quantitative ceology. J. Remgt, 1949,2:104-115.
[59] Dymond, J.D. ShePherd, J.Qi. A simple Physical model of Vegetation reflectance for Standardizing optical satellite imagery, Remote Sensing of Environment, 2001 (77):230-239.
[60] Gregory J. Retallack. Late Oligocene bunch grassland and early Miocene sod grassland paleosols from central Oregon, USA. Palaeogeography, Palaeoclimatology, Palaeoecology, 2004, (207):203-237.
[61] Gupta, Pcnanda.喜马拉雅山西部的草地类型及其生态演替.第十一届国际草地会议论文集.
[62] Hostert, Achim. Coupling spectral unmixing and trend analysis for Monitoring of long-term vegetation dynamics in Mediterranean rangelands,Remote Sensing of Environrnent, 2001, 87(3):183-197.
[63] Liu G,etal.A Process-based boreal ecosystem productivity simulator using remote in Puts [J]. Remote sensing of Environment,1997,62:158-75.
[64] Marianne C. Edwardsa, Jane Wellensb, Dawud AI-Eisawie. Monitoring the grazing resources of the Badia region, Jordan, using remote sensing, Applied Geography, 1999(19):385-398.
[65] Moulin S, Kergoat L, Viovy N, et al. Global-scale assessment of vegetation phenology using NOAA/AVHRR satellite measurements. Journal of Climate, 1997, 10 :1154-1170.
[66] Nicholas S.G. Williams. Environmental, landscape and social predictors of native grassland loss in western Victoria, Australia. Biological Conservation, 2007, 137(2):308-318
[67] Nightingale J M, Phinn S, Assessment of relationships between precipitation and satellite derived vegetation condition with in south Ausralia. Australian Geographical Studies, 2003, 41(2) :180-195.
[68] Prince S D. Satellite Remote Sensing of Primary Produetion: Comparison of Results for sahelian Grasslands 1981-1988, International Journal of Remote Sensing, 1991, 12(6): 1301 - 1311.
[69] Ojima D S, Xiao X, Chuluun T, etal. Asian grassland blogeochemistry: factors affecting past and future dynamic of Asian grasslands. Asian Change in the Context of Global Climate Change In: Galloway J N, Melillo J M eds. International Geospere2Biospere Publication Series 3.Cambridge: Cambridge University Press,1998.128-44.
[70] Parton W J,Seurloek JMO,Ojima D S,etal. Impact of climate change on grassland Production and carbon worldwide.Global Change Biology.1995,1:13-2.
[71] Sehimel D S,etal. Continental scale variability in ecosystem proeesses: models, data, and the role of disturbance[J].Ecological Monographs,1997,67(2):251-71.
[72] Shoshany M, Kutiel P, Lavee H. Monitoring temporal vegetation cover changes in Mediterranean And arid ecosystems using a remote sensing technique : case study of the Judean Mountain and the Judean Desert, Joumal of Arid Environrnents Volume 33, Issuel, May1996:9-21.
[73] Simon B. Bird, Jeffrey E. Herrick, et al. Multi-scale variability in soil aggregate stability: Implications for understanding and predicting semi-arid grassland degradation. Geoderma, 2007, (140): 106-118.
[74] Sudipta S, Menas K. Interannual variability of vegetation over the Indian sub-continent and its relation to the different meteorological parameters. Remote Sensing of Environment, 2004, 90(2) :268~280.
[75] Sullivan S, Rohde R. On non-equilibrium in arid and semi-arid grazing systems. Journal of Biogeography. 2002, (29): 1595 - 1618.
[76] Sun H Y, Wang C Y, Niu Z et al. Analysis of the vegetation cover change and the relationship between NDVI and environmental factors by using NOAA time series data. Journal of Remote Sensing, 1998, 2(3):205-210.
[77] Taylor B. E et al. Determination of seasonal and interannual variation in New Zealand pasture growth from NOAA 7 data. Remote Sensing of Environment, 1985, 18:177-192.
[78] Tueker C. J et al. Satellite remote sensing of total herbaceous biomass production in the Senegelase Sahel: 1980-1984.Remote Sensing of Environment. 1983 (17):233-249.
[79] Tueker C. J et al. Satellite remote sensing of Primary Production. Int. J. Remote Sensing, 1987, 7 (11) :1395-1416.
[80] Yassir, J. van der Kamp, P. Buurman. Secondary succession after fire in Imperata grasslands of East Kalimantan, Indone. Agriculture, Ecosystems & Environment, 2010, (137):172-182.