中国Holdridge生命地带与潜在植被空间格局研究
|
摘要
科学合理的模拟区域植被一直是科学研究的一个重点问题。在进行全球变化和陆地生态系统的研究中,气候因素是决定地球上植被类型和分布的最主要因素,植被是地球气候最鲜明的反映和标志,因此,研究气候-植被关系具有十分重要的实际意义。为了探究生命地带模型的模拟准确性和中国潜在植被的空间分布状况,本研究依据生命地带模型,在地理信息系统空间分析和AML语言支持下,实现了中国潜在植被的分布模拟,进而探索了中国植被的空间分布和地域分异规律,实现了中国潜在植被的区划。
研究表明:(1)生命地带模型模拟了中国潜在植被空间分布,得到了28个生命地带类型,Kappa检验准确度为46%。我国潜在植被类型中,冷温带草原面积约108.8万km~2,主要分布在阴山鄂尔多斯高原至六盘山一线地区;暖温带湿润森林面积约108.9万km~2,主要分布在长江以南和南岭以北的区域。亚热带湿润森林次之,面积为68.7km~2,主要分布在南岭以南和云贵高原南部。面积最小的为暖温带潮湿森林,面积仅约1km~2,分别分布在浙闽丘陵。(2)根据自然地理环境的地域差异和水热条件,将全国分为东部季风区、西北干旱区和青藏高寒区,在此基础上结合经度范围、海拔、行政区范围和实际植被优势种以及植被的面积,对中国潜在植被分布进行分析。(3)植被作为地理环境的组成部分,由于太阳辐射、海陆差异和海拔等因素的影响,我国东部表现出很强的纬向地带性,从北到南植被类型依次表现为针叶林带-草原-森林草原-森林植被的分布,植被在沿纬线分布的过程都不同程度有间断或是片状分布;我国北部地区主要表现为经向地带性,从东到西植被类型依次表现为森林-草原-草原荒漠-荒漠的过渡分布;青藏高原和西部的高大山脉以垂直地带性为主,随着海拔的升高植被从森林、草原向荒漠冰雪过渡。(4)参考中国自然地理、中国自然区划概要和中国科学院自然区划工作委员会1959年制订的自然区划方案,在划分三大区和7个自然地区的基础上,根据生命地带植被类型与中国实际植被类型结合,进一步划分了41个自然区。(5)数据的精度是保证植被模拟精度的前提。采用DEM数据对月平均气温空间插值进行修正,提高了月平均气温插值的精度,在一定程度上提高了垂直地带性植被模拟的准确性。
Scientific and reasonable simulation of the regional vegetation is always a focus of scientific research. In the global change and the land ecosystem research, the climatic factors is the most primary ones that decide the covered type and the distribution of vegetation, and the vegetation is the crucial reflection and symbol of the Earth climate. Therefore, the determination of the climate - vegetation relations has the vital practical significance. In order to verify the simulation accuracy of the life zone model and the spatial distribution of the Chinese latent vegetation, we have simulated the distribution of the Chinese potential vegetation and explored the spatial distribution and the rule of region differentiation based on the life zone model, which is under the support of the spatial analysis of GIS and the AML language.
Five aspects of work are involved in this thesis. First, the spatial distribution of potential vegetation of China is simulated with the life-zone model. There are 28 life-zone types we receive and the simulation accuracy is 46% under the calculation of the Kappa. In all the types, the cool temperate steppe is about 1,088,000 km~2, mainly located in the line of the Yinshan- Ordos Plateau -Liupan Mountain; The warm temperate moist forest is about 1,089,000 km , which is accounting for 11.5% of the total area of China, mainly in the north of Nanling Mountain and the south of the Yangtze River region. The sub-tropical moist forest is followed by, the distribution area of 687126km~2, mainly located in the south and Yunnan-Guizhou Plateau and the south of Nanling Mountain. The smallest one is the warm temperate moist forest, covering an area of only about 1km~2, located in the Hill of the Zhejiang and Fujian. Second, based on natural geographic environment and the geographical differences of heat and water conditions, three regions are divided. They are the eastern part of the monsoon region, the arid area of northwest China region and the Qinghai-Tibet alpine region. The distribution of potential vegetation is analyzed according as the scope of latitude, elevation distribution, the scope of canton, the type of practical vegetation and the vegetation in area of China. Third, due to solar radiation, land and sea elevation differences and other factors, the rule of territorial differentiation is manifested. The strong performance of eastern areas of China is Latitudinal zonality. From south to north, the vegetation types are the coniferous forest belt-grassland- forest-steppe-forest. The distribution of vegetations is along the latitude, but sometimes it performances the intermittent or patchy distribution; In the north of China, Longitudinal zonality is mainly expressed in zonal areas, and from west to east sequence of vegetation types for the forest- grassland- grassland desertification -desertification; The Qinghai-Tibet Plateau and western tall mountains are mainly vertical zonality. With the increasing of elevation, the vegetation performance from the forests- grasslands and the desert transition to snow. Forth, the Physical Geography of China and the Chinese Academy of Sciences divide China into three regions and seven natural zones. Further 41 natural provinces are divided on the base of the life zone and the types of actual vegetation. Fifth, the accuracy of the data is in the premise of vegetation simulation precision. The use of DEM data for amendment of the spatial interpolation is used in monthly average temperature. It is not only raising the accuracy of interpolation of temperature, but also improving the simulation of the vertical zonal vegetation.
研究表明:(1)生命地带模型模拟了中国潜在植被空间分布,得到了28个生命地带类型,Kappa检验准确度为46%。我国潜在植被类型中,冷温带草原面积约108.8万km~2,主要分布在阴山鄂尔多斯高原至六盘山一线地区;暖温带湿润森林面积约108.9万km~2,主要分布在长江以南和南岭以北的区域。亚热带湿润森林次之,面积为68.7km~2,主要分布在南岭以南和云贵高原南部。面积最小的为暖温带潮湿森林,面积仅约1km~2,分别分布在浙闽丘陵。(2)根据自然地理环境的地域差异和水热条件,将全国分为东部季风区、西北干旱区和青藏高寒区,在此基础上结合经度范围、海拔、行政区范围和实际植被优势种以及植被的面积,对中国潜在植被分布进行分析。(3)植被作为地理环境的组成部分,由于太阳辐射、海陆差异和海拔等因素的影响,我国东部表现出很强的纬向地带性,从北到南植被类型依次表现为针叶林带-草原-森林草原-森林植被的分布,植被在沿纬线分布的过程都不同程度有间断或是片状分布;我国北部地区主要表现为经向地带性,从东到西植被类型依次表现为森林-草原-草原荒漠-荒漠的过渡分布;青藏高原和西部的高大山脉以垂直地带性为主,随着海拔的升高植被从森林、草原向荒漠冰雪过渡。(4)参考中国自然地理、中国自然区划概要和中国科学院自然区划工作委员会1959年制订的自然区划方案,在划分三大区和7个自然地区的基础上,根据生命地带植被类型与中国实际植被类型结合,进一步划分了41个自然区。(5)数据的精度是保证植被模拟精度的前提。采用DEM数据对月平均气温空间插值进行修正,提高了月平均气温插值的精度,在一定程度上提高了垂直地带性植被模拟的准确性。
Scientific and reasonable simulation of the regional vegetation is always a focus of scientific research. In the global change and the land ecosystem research, the climatic factors is the most primary ones that decide the covered type and the distribution of vegetation, and the vegetation is the crucial reflection and symbol of the Earth climate. Therefore, the determination of the climate - vegetation relations has the vital practical significance. In order to verify the simulation accuracy of the life zone model and the spatial distribution of the Chinese latent vegetation, we have simulated the distribution of the Chinese potential vegetation and explored the spatial distribution and the rule of region differentiation based on the life zone model, which is under the support of the spatial analysis of GIS and the AML language.
Five aspects of work are involved in this thesis. First, the spatial distribution of potential vegetation of China is simulated with the life-zone model. There are 28 life-zone types we receive and the simulation accuracy is 46% under the calculation of the Kappa. In all the types, the cool temperate steppe is about 1,088,000 km~2, mainly located in the line of the Yinshan- Ordos Plateau -Liupan Mountain; The warm temperate moist forest is about 1,089,000 km , which is accounting for 11.5% of the total area of China, mainly in the north of Nanling Mountain and the south of the Yangtze River region. The sub-tropical moist forest is followed by, the distribution area of 687126km~2, mainly located in the south and Yunnan-Guizhou Plateau and the south of Nanling Mountain. The smallest one is the warm temperate moist forest, covering an area of only about 1km~2, located in the Hill of the Zhejiang and Fujian. Second, based on natural geographic environment and the geographical differences of heat and water conditions, three regions are divided. They are the eastern part of the monsoon region, the arid area of northwest China region and the Qinghai-Tibet alpine region. The distribution of potential vegetation is analyzed according as the scope of latitude, elevation distribution, the scope of canton, the type of practical vegetation and the vegetation in area of China. Third, due to solar radiation, land and sea elevation differences and other factors, the rule of territorial differentiation is manifested. The strong performance of eastern areas of China is Latitudinal zonality. From south to north, the vegetation types are the coniferous forest belt-grassland- forest-steppe-forest. The distribution of vegetations is along the latitude, but sometimes it performances the intermittent or patchy distribution; In the north of China, Longitudinal zonality is mainly expressed in zonal areas, and from west to east sequence of vegetation types for the forest- grassland- grassland desertification -desertification; The Qinghai-Tibet Plateau and western tall mountains are mainly vertical zonality. With the increasing of elevation, the vegetation performance from the forests- grasslands and the desert transition to snow. Forth, the Physical Geography of China and the Chinese Academy of Sciences divide China into three regions and seven natural zones. Further 41 natural provinces are divided on the base of the life zone and the types of actual vegetation. Fifth, the accuracy of the data is in the premise of vegetation simulation precision. The use of DEM data for amendment of the spatial interpolation is used in monthly average temperature. It is not only raising the accuracy of interpolation of temperature, but also improving the simulation of the vertical zonal vegetation.
引文
[1]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(1):8-17
[2]武吉华,张绅.植物地理学[M].北京:高等教育出版社,1983
[3]扬正宇.四类气候.植被关系模型的比较研究[D].中国科学院植物研究所,2001
[4]张新时.研究全球变化的植被-气候分类系统[J].第四纪研究,1993,5(2):157-1691
[5]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(1):8-17
[6]赵东升,李双成.青藏高原的气候植被模型研究进展[J].地理科学进展,2006,25(4):68-77
[7]宋永昌.植被生态学[M],上海:华东师范大学出版社.2001
[8]刘华民,吴绍洪,郑度等.潜在自然植被研究与展望[J].地理科学进展,2004,23(1):62-70
[9]林金安.植物科学综论[M].哈尔滨:东北林业大学出版社,1993
[10]倪健.植被-气候分类指标及其应用[J].生态学杂志,1998,17(2):33-42
[11]J.Z.RenA,D,Z.Z.HuB,J.ZhaoC.A grassland classification system and its application in China.Rangeland Journal.CSIRO PUBLISHlNG,2008,30,199-209
[12]张新时.植被的PE(可能蒸散)指标与植被-气候分类(一)-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,1989,13(1):1-91
[13]张新时.植被的PE(可能蒸散)指标与植被-气候分类(二)-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,1989,13(3):197-207
[14]张新时.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
[15]方精云.东亚地区植被气候类型在温度、降水量坐标中的表达[J].生态学报,1994,14(3):290-2941
[16]倪健.KIRA指标的扩展及其在中国植被与气候关系研究中的应用[J].应用生态学报,1997,8(2):161-170
[17]周广胜,王玉辉.全球变化与气候-植被分类研究和展望[J].科学通报,1999,24(44):2587-2593
[18]倪健,张新时.水热积指数的估算及其在中国植被与气候关系研究中的应用[J].植物学报,1997,39(12):1147-1159
[19]孙艳玲,延晓冬.基于布迪科指标的中国植被-气候关系研究[J].资源科学,2006,28(3):23-28
[20]倪健.植被-气候分类指标及其应用[J].生态学杂志,1998,17(2):33-42
[21]陈育峰.自然植被对气候变化响应的研究:建模[J].地理科学进展,1997,16(3):24-27
[22]Franklin,J.Predictive vegetation mapping:geographic modeling of biospatial patterns in relation to environmental gradiets.Progress in Progress in Physical Geograhy,19:474-499
[23]Brzeziecki B,Kienast F,Wildi O A.Simulated map of the potential natural forest vegetation of Switzerland.Journal of Vegetation Science,1993,4:499-508
[24]Guisan A,Theurillat J-P,Kienast,F.Predicting the potential distribution of plant species in an alpine environment.Journal of Vegetation Science,1998,9:65-74
[25]Brown D G.Predicting vegetation types at treeline using topography and biophysical disturbance variables.Journal of Vegetation Science,1994,5:641-656
[26]赵茂盛.气候变化对中国植被可能影响的模拟[J].地理学报,2002,57(1):28-38
[27]赵传燕,冯兆东,南忠仁.李守波黄土高原祖厉河流域潜在植被分布模拟研究[J].地理学报,2007,62(1):52-61
[28]李飞,赵军,郝君明.中国潜在植被空间分布与格局研究[J].生态学报,2008,28(11).5347-5355
[29]李新,程国栋,卢玲.空间内插方法比较[J].地球科学进展,2000,15(3):260-265
[30]朱求安,张万昌,余钧辉.基于GIS的空间插值方法研究[J].江西师范大学学报,2004,28(2):183-188
[31]邹松兵.中国黄土高原潜在植被模拟[D].兰州大学,2006
[32]范泽孟.中国Holdridge生命地带平均中心的时空分布及其偏移趋势[J].生态学报,2004,24(7):1380-1387
[33]Tian Xiang YueT,Ze Meng Fan,Ji Yuan Liu.Changes of major terrestrial ecosystems in China since 1960.Global and Planetary change,287-302
[34]宋永昌著.植被生态学[M].华东师范大学出版社,2001
[35]Whittaker,R.H.Communities and Ecosystems,2nd ed.New York:Macmillan Publishing Co.Inc.,1975
[36]Holdridge.L R.Determination of world plant formations from simple climate data.Science,105(2727):367-368.
[37]Roy,P.S.,2006,Biome mapping in India using vegetation type map derived using temporal satellite data and environmental parameters.Ecological modeling,Indian Institute of Remote Sensing(NASA).Dehradum
[38]周广胜,王玉辉.全球变化与气候-植被分类研究和展望[J].科学通报,1999,44(24):2587-2593
[39]陈育峰.GIS支持的全球气候变化对中国Holdridge生命地带的可能影响研究[J].遥感学报,1997,1(1):74-79
[40]李新,程国栋,卢玲.空间内插方法比较[J].地球科学进展,2000,15(3):260-265
[41]Jun zhao,Fei Li,Haiyue Fu,ying tian,Zizhi Hu.A DEM-based partition adjustment for the interpolation of annual cumulative temperature in china.Geospatial Information Science,2007,6753
[42]Davis,J.C.Statistics and Data Analysis in Geology.2d ed.New York:John Wiley&Sons,1986
[43]Issaks.E.H.and R.M.Srivastava.An Introduction to Applied Geostatistics.Oxford:Oxford University Press,1989
[44]Webster,R.and M.A.Oliver.Statistical Methods in Soil and Land Resource Survey.Oxford:Oxford University Press,1990
[45]Cressie,N.Statistics for Spatial Data.Chichester.NY:John Wiley & Sons,1991
[46]Cohen J.A Coefficient agreement for nominal data.Educational and Psychological Measurement,1960,2(1):37-46.
[47]岳天祥,陈述彭.资源环境数学模型手册[M].科学出版社,2003
[48]闫岩,华琳,张建.对诊断一致性kappa系数及评价指标的探讨[J].中国卫生统计,2007,24(3):313-315
[49]布仁仓,常禹.基于Kappa系数的景观变化测度.以辽宁省中部城市群为例[J].生态学报,2005,25(4):779-784
[50]索俊锋.杭州千岛湖镇土地利用变化及其生态效应研究[D].西北师范大学,2007
[51]陈传康,赵济.中国地理[M].北京:高等教育出版社,2004
[52]冯忠江.世界自然地理[M].北京:中国环境科学出版社,2007
[53]赵松乔等.中国自然地理(总论).北京:科学出版社,1985
[54]赵济等.中国自然地理(第三版).北京:高等教育出版社,1995
[2]武吉华,张绅.植物地理学[M].北京:高等教育出版社,1983
[3]扬正宇.四类气候.植被关系模型的比较研究[D].中国科学院植物研究所,2001
[4]张新时.研究全球变化的植被-气候分类系统[J].第四纪研究,1993,5(2):157-1691
[5]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(1):8-17
[6]赵东升,李双成.青藏高原的气候植被模型研究进展[J].地理科学进展,2006,25(4):68-77
[7]宋永昌.植被生态学[M],上海:华东师范大学出版社.2001
[8]刘华民,吴绍洪,郑度等.潜在自然植被研究与展望[J].地理科学进展,2004,23(1):62-70
[9]林金安.植物科学综论[M].哈尔滨:东北林业大学出版社,1993
[10]倪健.植被-气候分类指标及其应用[J].生态学杂志,1998,17(2):33-42
[11]J.Z.RenA,D,Z.Z.HuB,J.ZhaoC.A grassland classification system and its application in China.Rangeland Journal.CSIRO PUBLISHlNG,2008,30,199-209
[12]张新时.植被的PE(可能蒸散)指标与植被-气候分类(一)-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,1989,13(1):1-91
[13]张新时.植被的PE(可能蒸散)指标与植被-气候分类(二)-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,1989,13(3):197-207
[14]张新时.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
[15]方精云.东亚地区植被气候类型在温度、降水量坐标中的表达[J].生态学报,1994,14(3):290-2941
[16]倪健.KIRA指标的扩展及其在中国植被与气候关系研究中的应用[J].应用生态学报,1997,8(2):161-170
[17]周广胜,王玉辉.全球变化与气候-植被分类研究和展望[J].科学通报,1999,24(44):2587-2593
[18]倪健,张新时.水热积指数的估算及其在中国植被与气候关系研究中的应用[J].植物学报,1997,39(12):1147-1159
[19]孙艳玲,延晓冬.基于布迪科指标的中国植被-气候关系研究[J].资源科学,2006,28(3):23-28
[20]倪健.植被-气候分类指标及其应用[J].生态学杂志,1998,17(2):33-42
[21]陈育峰.自然植被对气候变化响应的研究:建模[J].地理科学进展,1997,16(3):24-27
[22]Franklin,J.Predictive vegetation mapping:geographic modeling of biospatial patterns in relation to environmental gradiets.Progress in Progress in Physical Geograhy,19:474-499
[23]Brzeziecki B,Kienast F,Wildi O A.Simulated map of the potential natural forest vegetation of Switzerland.Journal of Vegetation Science,1993,4:499-508
[24]Guisan A,Theurillat J-P,Kienast,F.Predicting the potential distribution of plant species in an alpine environment.Journal of Vegetation Science,1998,9:65-74
[25]Brown D G.Predicting vegetation types at treeline using topography and biophysical disturbance variables.Journal of Vegetation Science,1994,5:641-656
[26]赵茂盛.气候变化对中国植被可能影响的模拟[J].地理学报,2002,57(1):28-38
[27]赵传燕,冯兆东,南忠仁.李守波黄土高原祖厉河流域潜在植被分布模拟研究[J].地理学报,2007,62(1):52-61
[28]李飞,赵军,郝君明.中国潜在植被空间分布与格局研究[J].生态学报,2008,28(11).5347-5355
[29]李新,程国栋,卢玲.空间内插方法比较[J].地球科学进展,2000,15(3):260-265
[30]朱求安,张万昌,余钧辉.基于GIS的空间插值方法研究[J].江西师范大学学报,2004,28(2):183-188
[31]邹松兵.中国黄土高原潜在植被模拟[D].兰州大学,2006
[32]范泽孟.中国Holdridge生命地带平均中心的时空分布及其偏移趋势[J].生态学报,2004,24(7):1380-1387
[33]Tian Xiang YueT,Ze Meng Fan,Ji Yuan Liu.Changes of major terrestrial ecosystems in China since 1960.Global and Planetary change,287-302
[34]宋永昌著.植被生态学[M].华东师范大学出版社,2001
[35]Whittaker,R.H.Communities and Ecosystems,2nd ed.New York:Macmillan Publishing Co.Inc.,1975
[36]Holdridge.L R.Determination of world plant formations from simple climate data.Science,105(2727):367-368.
[37]Roy,P.S.,2006,Biome mapping in India using vegetation type map derived using temporal satellite data and environmental parameters.Ecological modeling,Indian Institute of Remote Sensing(NASA).Dehradum
[38]周广胜,王玉辉.全球变化与气候-植被分类研究和展望[J].科学通报,1999,44(24):2587-2593
[39]陈育峰.GIS支持的全球气候变化对中国Holdridge生命地带的可能影响研究[J].遥感学报,1997,1(1):74-79
[40]李新,程国栋,卢玲.空间内插方法比较[J].地球科学进展,2000,15(3):260-265
[41]Jun zhao,Fei Li,Haiyue Fu,ying tian,Zizhi Hu.A DEM-based partition adjustment for the interpolation of annual cumulative temperature in china.Geospatial Information Science,2007,6753
[42]Davis,J.C.Statistics and Data Analysis in Geology.2d ed.New York:John Wiley&Sons,1986
[43]Issaks.E.H.and R.M.Srivastava.An Introduction to Applied Geostatistics.Oxford:Oxford University Press,1989
[44]Webster,R.and M.A.Oliver.Statistical Methods in Soil and Land Resource Survey.Oxford:Oxford University Press,1990
[45]Cressie,N.Statistics for Spatial Data.Chichester.NY:John Wiley & Sons,1991
[46]Cohen J.A Coefficient agreement for nominal data.Educational and Psychological Measurement,1960,2(1):37-46.
[47]岳天祥,陈述彭.资源环境数学模型手册[M].科学出版社,2003
[48]闫岩,华琳,张建.对诊断一致性kappa系数及评价指标的探讨[J].中国卫生统计,2007,24(3):313-315
[49]布仁仓,常禹.基于Kappa系数的景观变化测度.以辽宁省中部城市群为例[J].生态学报,2005,25(4):779-784
[50]索俊锋.杭州千岛湖镇土地利用变化及其生态效应研究[D].西北师范大学,2007
[51]陈传康,赵济.中国地理[M].北京:高等教育出版社,2004
[52]冯忠江.世界自然地理[M].北京:中国环境科学出版社,2007
[53]赵松乔等.中国自然地理(总论).北京:科学出版社,1985
[54]赵济等.中国自然地理(第三版).北京:高等教育出版社,1995