新疆额尔齐斯河流域植被景观格局与生物多样性空间变化规律研究
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摘要
流域是一个完整的地理单元,流域内景观格局是自然与人类活动共同作用的结果。流域景观格局的改变影响着流域内生态过程的发生、发展和变化,关系到流域及周边区域的生态安全。额尔齐斯河(简称额河)发源于阿尔泰山山地,途经山前荒漠平原向西流出境外,因此新疆阿尔泰林区的额河流域包括山地流域景观和平原河谷景观两部分。额河流域具有较高的生物多样性,对北疆生态环境和生态安全具有重要影响。以额河为主线,将额河流域山地和平原河谷作为一个整体,研究其景观时空格局和生物多样性的空间分布规律,有助于认识额河流域景观的整体生态功能,为额河流域的生物多样性保护、资源合理利用和景观生态规划等提供科学依据。本文以新疆阿尔泰林区额河流域典型的山地流域景观(小东沟)和平原河谷景观(北屯)为对象,通过外业调查、遥感影像解译、GIS分析和模型模拟相结合的方法,分析了额河流域植被在景观水平上的时空格局和生物多样性的空间变化规律。通过研究得出以下主要结论:
(1)应用多个景观格局指数定量分析了额河流域北屯段和阿尔泰山小东沟林区景观的空间格局及破碎化特征。将额河流域景观划分为7大类10小类景观类型,其中包括5大类8小类植被类型。景观中5大类植被类型占总面积的比例分别为耕地16.5%、河漫滩林地2.6%、湿地1.6%、草地10.5%、荒漠52.2%。格局分析表明,河漫滩林地在景观中呈小斑块分布,其斑块最大周长、最大面积及平均面积均小于其它植被类型。河漫滩林地的斑块形状比较复杂,其平均斑块形状指数、平均斑块分维数和类型边界密度指数均高于其它植被类型。多个景观指数都表明河漫滩林地在景观中破碎化程度最高。将阿尔泰山小东沟林区景观划分成针叶林、阔叶林、针阔混交林、灌木和草本5个类型。景观格局分析表明,林地是阿尔泰山小东沟林区的景观基质,阔叶林是景观中斑块形状最复杂的。
(2)利用MSS、TM和ETM+三期影像,选取斑块数、平均斑块面积、平均斑块形状指数、平均斑块分维数、多样性指数和均匀度指数,定量分析了额河流域北屯段1972~2000年景观格局的动态变化。28年间,景观内耕地面积增加了9.62%,荒漠减少了11.75%,居民地增加了0.15%,河漫滩林地和湿地则分别减少了0.44%和1.06%。28年间,景观的斑块数增加而平均斑块面积减少了,整个景观变得零散、破碎。平均斑块形状指数和平均斑块分维数的增加,揭示景观斑块形状的复杂化趋势。景观多样性和均匀度指数的增加,表明景观类型异质性程度减弱,各景观类型分布变得均匀化。不同时期各类型转移概率表明河漫滩林地的转化率最高,其主要转化方向是草地,其次是耕地。
(3)以外业调查数据为基础,选取气象、地形因子和样地点距河道远近等指标作为预测变量,通过构建回归方程,预测了额河流域北屯段乔木群落特征因子的空间分布。利用残差图评价各群落特征因子预测精度。克郎河是位于额河主河道北面的一个重要的支流。分别比较了额河及其支流克郎河上、中、下游不同景观单元之间、河流两岸不同河岸带(近、中、远河岸带)之间群落特征因子的差异。额河林分的平均胸径中游>下游>上游,林分蓄积量和郁闭度中游>上游>下游,林分平均高度、物种丰富度及Fisher多样性指数上游>中游>下游,各群落特征因子在上、中、下游之间差异显著。克郎河林分平均树高上游>中游>下游,其余5个群落特征因子上游<中游<下游,除物种丰富度在中游与下游差异不显著外,其余各群落特征因子在上、中、下游之间均差异显著。随与河道距离的增加,仅额河南岸Fisher多样性在近河岸带与中河岸带之间差异显著,其余河岸带内各群落特征因子差异均不显著。对额河与克郎河群落特征因子进行比较,除平均树高额河<克郎河外,其余5个群落特征因子均为额河>克郎河。6个群落特征因子的变化规律主要受额河与克郎河河流形态和地形特征的影响。
(4)为分析环境因子对植被分布的影响,在野外样地调查和主要环境因子测定的基础上,利用聚类和排序对额河流域阿尔泰山小东沟林区的森林植被进行了类型划分,分析了植被与环境因子的关系。利用聚类分析将阿尔泰小东沟林区的木本植物群落划分为6个类型(灌丛、欧洲山杨(Populus tremula)林、苦杨(Populus laurifolia)林、疣枝桦(Betula pendula)林、西伯利亚落叶松(Larix sibirica)林和西伯利亚落叶松与西伯利亚冷杉(Abies sibirica)、云杉(Picea obovata)的针叶混交林)。DCCA排序表明,海拔和坡向等地形因子以及土壤类型、土壤全氮、土壤全磷、土壤水分含量和大石砾含量等土壤因子是影响阿尔泰林区植被分布的主要因子,林区不同群落类型的分布格局主要是由地形和土壤因子的共同作用所控制的。
(5)为探讨地形对额河流域阿尔泰山小东沟植被类型分布的影响,借助于GIS将阿尔泰山小东沟影像分类图分别与坡度、坡向、剖面曲率和海拔图叠加,定量分析了各植被类型分布与地形的关系。根据遥感解译把研究区植被斑块类型划分为针叶林、阔叶林、针阔混交林、灌木和草地。各植被类型的最佳生境(地形)因子组合如下:针叶林分布最多的地形条件是斜/陡坡(15~35°)、西北坡、剖面曲率0~3°、海拔1 800~2 000m;阔叶林分布最多的地形条件是斜/陡坡、西北坡、剖面曲率5~10°、海拔1 400~1 600m;针阔混交林分布最多的地形条件是斜/陡坡、北坡、剖面曲率5~10°、海拔1 600~1 800m;灌木分布最多的地形条件是斜/陡坡、西坡、剖面曲率5~10°、海拔1 400~1 600m;草本分布最多的地形条件是斜/陡坡、南坡、剖面曲率5~10°、海拔1 200~1 400m。
(6)利用野外样方调查数据,选取两个物种多样性指数,分析了小东沟北坡物种多样性随海拔梯度的变化规律。小东沟林区物种丰富度指数和Shannon-Wiener多样性指数均为乔木层<灌木层<草本层。不同生活型的物种两个多样性指数沿海拔梯度乔木层和灌木层都表现为先升高再降低的单峰趋势,多样性的峰值均出现在海拔1 600~1 800m。草本层两个多样性指数沿海拔升高,略微有所上升,变化不明显。乔、灌、草总的物种多样性指数均呈现先升高后降低的单峰趋势。海拔1 600~1 700m范围内的针阔群落交错带具有较高物种多样性,从而出现乔木层、灌木层及群落总的物种多样性峰值。
(7)通过选取气象、地形和NDVI植被指数作为预测变量,构建了阿尔泰山小东沟乔木物种丰富度预测模型,利用残差图评价预测精度。将乔木物种丰富度预测图分别与坡度、坡向和海拔图叠加,分析不同地形条件影响乔木物种丰富度空间分布的规律。小东沟乔木物种丰富度主要集中在3~4,占研究区总面积的70.28%。坡度0~5°乔木物种丰富度出现频率最高的数值是3,其余坡度条件下,乔木物种丰富度出现频率最高的数值是4;乔木物种丰富度在西坡和西北坡出现频率最高的数值是3,其余坡向乔木物种丰富度出现频率最高的数值均是4;海拔梯度上,小东沟乔木物种丰富度出现频率最高的数值呈现先增加后减少的单峰型趋势。残差类型统计表明,较强和中等预测水平面积占总面积的94.62%,表明预测效果较好。
(8)以ETM+遥感影像和乔木样地生物量抽样调查数据为基础,选取RVI、NDVI、SAVI、DVI和IPVI等植被指数,分析了植被指数与乔木地上生物量之间的相关性,并构建了基于植被指数的生物量回归模型,利用残差图评价预测精度。在所选取的植被指数中,生物量与NDVI植被指数关系最显著。生物量残差图中较强和中等预测面积分别为66.60%和30.31%。将生物量空间分布预测图分别与坡度、坡向和海拔图叠加分析表明:小东沟林区乔木地上部分的生物量以斜/陡坡(15~35°)最高,平/缓坡(0~15°)次之,急/险坡(>35°)最低。小东沟林区东南、南坡的生物量较低,其余坡向的生物量较高。海拔梯度上,生物量空间分布呈现先增加后减少的单峰型趋势,不同海拔段之间生物量以低海拔的生物量最低,中海拔的最高,高海拔生物量居中。
A basin is an integrated geographical unit, and the landscape patterns within the basin have usually been formed by the interactions of natural and anthropogenic processess. The changes in landscape patterns within the basin can directly affect the ecological processes of the basin, influencing the ecological integrity and safety of the basin and the areas near the basin.
The Irtysh River originates from the Altai Mountains in Xinjiang of northwest China, it flows down via the desert plains on the south foot of the Altai Mountains, goes to the west and out of the border of China, finally flows into the arctic sea through Kazakstan and Russia. Irtysh River Basin in the Altai forest region is composed of two parts: the mountain watershed landscape and the riparian plain landscape, which are connected as an integrative system by the river. The Irtysh River basin nourishes rich biodiversities in Xinjiang, playing important roles in maintaining the ecological integrity and safety of north Xinjiang. Analyzing the landscape pattern and spatial distribution of biodiversity both in mountain watershed and in the riparian plain could help us in understanding the ecological functions of the whole basin landscape, which can provide scientific basis for future reasonable resources use, biodiversity conservation and ecological landscape planning. In this thesis, we selected two typical landscape types in the Irtysh River basin of Xinjiang as the study area, Xiaodonggou representing the mountain watershed landscape and Beitun representing the riparian plain landscape, By combining methods of field investigations, remote sensing image interpretation, GIS analyses and simulation models, the pattern and dynamics of the landscape and spatial distribution of biodiversity in the Irtysh River basin of Xinjiang were explored. The main conclusions are as follows:
(1)The landscape pattern and fragmentation in Beitun of Irtysh River Basin and Xiaodongou of Altai Mountains in Xingjian was analyzed. Quantitative indices of landscape pattern were chosen to examine landscape pattern and fragmentation. The landscape in Beitun was classified into 7 types and 10 subtypes, including 5 vegetation types and 8 sub vegetation types. The area percentage of the five vegetation types (farmland, riparian forest, wetland, grassland and desert vegetation ) in the landscape was 16.5%, 2.6%, 1.6%, 10.5%, and 52.2% respectively. The patch maximal perimeter, patch maximal area and mean area indices of riparian forest were lower than the other vegetation types, implying that the riparian forest distributed in smaller patches in the whole landscape. The value of mean patch shape, fractal dimension index, and edge density index of the riparian forest were higher than those of the other vegetation types, indicating that the riparian forest had more complex patch shape. All the pattern indices demonstrated that the riparian forest was the most fragmented type in the Irtysh River Basin. The landscape in Xiaodonggou of Altai Mountains was classified into coniferous forest, broadleaved forest, conifer-broadleaf mixed forest, shrub, grassland. The landscape pattern analysis results showed that forest was the matrix in Xiaodonggou of Altai Mountains, and the broadleaved forest had most patch shape.
(2)The landscape pattern and dynamics in Beitun of Irtysh River Basin from 1972 to 2000 were analyzed by using remote sensing image of MSS, TM, and ETM+. Quantitative indices of landscape pattern included patch numbers, mean patch size, mean patch shape index, mean patch fractal dimension, Shannon diversity index, and Shannon evenness index. The results showed that desert was the matrix of the landscape. In the 28 years, the farmland area percent increased 9.62%, the desert area percent decreased 11.75%, residence area increased 0.15%, while the areas of riparian forest and wetland decreased 0.44% and 1.06% respectively. The patch number increased and the mean patch size decreased in the landscape, which indicated that landscape in 2000 was more fragmentized than the landscape in 1972. Both the mean patch shape index and mean patch fractal dimension index had increased from 1972 to 2000, which showed that landscape patch shape were becoming more complex. The Shannon diversity index and Shannon evenness both had a trend of increase from 1972 to 2000, indicating that the landscape heterogeneity decreased and landscape types distributed more evenly.Transition matrix of landscape types from 1972 to 2000 indicated that the riparian forest was the most unstable type, which was usually conversed into grassland or farmland.
(3)Predicting the spatial distribution maps of forest stand factors were done in Beitun of Irtysh River based on the field investigation data and GIS. The predicting environmental factors included climate, topography and the distance to river. Residual maps were used to evaluate the accuracy of predicting. Keyran River was one of an important tributaries which located in the north of Irtysh River. The differences of forest communities characteristics were compared between upper, central, and lower part in the Irtysh River and the Keyran River of Beitun respectively. The difference of forest community characteristicss between near, middle, and far riparian zones were also compared in the south vs. north banks of the Irtysh River, and south vs. north banks of the Keyran River of Beitun respectively. The results showed that in the Irtysh River, the order for the mean DBH of the riparian stands was central reach >lower reach >upper reach. The standing volume and canopy density order was central reach >upper reach >lower reach. Tree mean height, species richness, and Fisher diversity index order was upper reach >central reach >lower reach. In the Keyran River, the tree mean height order was upper reach >central reach >lower reach, the order for the other five stand factors was upper reachKeyran River. The changes of the stand factors were affected by the shape and topography of the Irthsh River and the Keyran River in Beitun.
(4)Based on the field investigation plots data and environmental factors, cluster analysis and ordination were used to analyze forest vegetations in Xiaodonggou. The cluster analysis identified 6 woody community types, including 5 tree communities and 1 shrub community. The 6 community types included: shrub, Populus tremula,, Populus laurifolia, Betula pendula, Larix sibirica, and Abies sibirica + Larix sibirica+ Picea obovata dominated plant communities, which had different distribution patterns along the major environmental gradients in the Altai mountains. The DCCA ordination showed that the topographical factors and soil factors were the dominant environmental factors affecting plant species distribution in the Xiaodonggou area. The distribution of the vegetations in the area was mainly controlled by the interactions of topographical and soil factors.
(5)Relationship between the vegetation distribution and topographic factors were explored based on overlays of remote sensing classification map with the maps of slope, aspect, profile curvature and altitude which derived from DEM. The imagery interpreted vegetation types included coniferous forest, broadleaved forest, conifer-broadleaf mixed forest, shrub, and grassland in Xiaodonggou. The optimal habitat combination of topography for these vegetation types in Xiaodonggou were as follows: coniferous forest was mainly distributed in slope from 15°to 35°, west-north aspect, the profile curvature ranged from 0°to 3°and altitude ranged from 1 800m to 2 000m. Broadleaved forest was mainly distributed in slope from 15°to 35°, west-north aspect, the profile curvature ranged from 5°to 10°and altitude ranged from 1 400m to 1600m. Conifer-broadleaf mixed forest was mainly distributed in slope from 15°to 35°, north aspect, the profile curvature ranged from 5°to 10°and altitude ranged from 1 600m to 1 800m. Shrub was mainly distributed in slope from 15°to 35°, west aspect, the profile curvature ranged from 5°to 10°and altitude ranged from 1 400m to 1 600m. Grassland was mainly distributed in slope from 15°to 35°, south aspect, the profile curvature ranged from 5°to 10°and altitude ranged from 1 200m to 1 400m.
(6)Patterns of species diversity along altitude in northern slope of Altai Mountain were studied based on the data of vegetation plots in Xiaodonggou. Species richness and Shannon-Wiener diversity index were chosen for the analysis. Diversity order of the three life forms was: trees < shrubs < herbaceous. Diversity indices along altitudinal gradient of the three life forms exhibited different trends. Tree diversity index exhibited an unimodal pattern with the increase of elevation, peaking at the altitude range of 1 600 m to 1 700 m; The shrubs showed a similar altitudinal gradient pattern. The herbaceous plant diversity index exhibited a different trend, which increased slightly with increasing elevation, but the change was not significant. The total diversity of trees, shrubs, and herbaceous showed an unimodal pattern with the increase of elevation. Altitude from 1 600m to 1 700m was an ecotone between conifer and broad-leaved stands, where maximum diversities occurred.
(7)The predicting model for tree species richness was constructed on basis of field plot investigation and environmental variables in Xiaodonggou. The environmental predictor variables included climate, topography, and NDVI. The residual map was used to evaluate the validity of the model. The predicted spatial distribution map of species richness was overlaid with the slope, aspect and elevation maps respectively. The tree species richness of most areas in Xiodonggou ranged between 3 and 4, which occupied 70.28% of the total study area. In slopes from 0°to 5°, tree species richness value of 3 had the highest presence frequency, while in other range of slopes, the species richness value of 4 had the highest presence frequency. In aspects of west and west-north, the tree species richness of 3 had the highest presence frequency, while in the others aspect the tree species richness value of 4 had the highest presence frequency. Along the altitudinal gradient, the tree species richness showed an unimodal pattern of distribution. The residual type results showed that strongly predicting area and moderately predicting area reached 94.62% of the total area, which implied that the predicting model was accurate enough.
(8)Using ETM+ data and the biomass by typical sample investigation plots, the Pearson correlation between RVI、NDVI、SAVI、DVI、IPVI and plots biomass was made respectively, the linear regression models for aboveground biomass in Xiaodonggou were constructed. Residual map was used to evaluate the accuracy of predicting accuracy. The correlation between NDVI and biomass was much better among the chosen vegetation indices. The residual type results showed that strongly predicting area and moderately predicting area reached 66.60% and 30.31% respectively, which implied the predicting model was accurate. The map of tree aboveground biomass spatial distribution was overlaid with the slope, aspect and elevation maps respectively. The results showed that the tree aboveground biomass order was inclined/steep slope >flat/gentle slope> rapid/dangerous slope. In aspect, the east-south and south aspect had the lower biomass than the other aspects. In elevation, the biomass order was mid elevation > high elevation > low elevation, from low elevation to high elevation, the biomass exhibited an unimodal pattern.
(1)应用多个景观格局指数定量分析了额河流域北屯段和阿尔泰山小东沟林区景观的空间格局及破碎化特征。将额河流域景观划分为7大类10小类景观类型,其中包括5大类8小类植被类型。景观中5大类植被类型占总面积的比例分别为耕地16.5%、河漫滩林地2.6%、湿地1.6%、草地10.5%、荒漠52.2%。格局分析表明,河漫滩林地在景观中呈小斑块分布,其斑块最大周长、最大面积及平均面积均小于其它植被类型。河漫滩林地的斑块形状比较复杂,其平均斑块形状指数、平均斑块分维数和类型边界密度指数均高于其它植被类型。多个景观指数都表明河漫滩林地在景观中破碎化程度最高。将阿尔泰山小东沟林区景观划分成针叶林、阔叶林、针阔混交林、灌木和草本5个类型。景观格局分析表明,林地是阿尔泰山小东沟林区的景观基质,阔叶林是景观中斑块形状最复杂的。
(2)利用MSS、TM和ETM+三期影像,选取斑块数、平均斑块面积、平均斑块形状指数、平均斑块分维数、多样性指数和均匀度指数,定量分析了额河流域北屯段1972~2000年景观格局的动态变化。28年间,景观内耕地面积增加了9.62%,荒漠减少了11.75%,居民地增加了0.15%,河漫滩林地和湿地则分别减少了0.44%和1.06%。28年间,景观的斑块数增加而平均斑块面积减少了,整个景观变得零散、破碎。平均斑块形状指数和平均斑块分维数的增加,揭示景观斑块形状的复杂化趋势。景观多样性和均匀度指数的增加,表明景观类型异质性程度减弱,各景观类型分布变得均匀化。不同时期各类型转移概率表明河漫滩林地的转化率最高,其主要转化方向是草地,其次是耕地。
(3)以外业调查数据为基础,选取气象、地形因子和样地点距河道远近等指标作为预测变量,通过构建回归方程,预测了额河流域北屯段乔木群落特征因子的空间分布。利用残差图评价各群落特征因子预测精度。克郎河是位于额河主河道北面的一个重要的支流。分别比较了额河及其支流克郎河上、中、下游不同景观单元之间、河流两岸不同河岸带(近、中、远河岸带)之间群落特征因子的差异。额河林分的平均胸径中游>下游>上游,林分蓄积量和郁闭度中游>上游>下游,林分平均高度、物种丰富度及Fisher多样性指数上游>中游>下游,各群落特征因子在上、中、下游之间差异显著。克郎河林分平均树高上游>中游>下游,其余5个群落特征因子上游<中游<下游,除物种丰富度在中游与下游差异不显著外,其余各群落特征因子在上、中、下游之间均差异显著。随与河道距离的增加,仅额河南岸Fisher多样性在近河岸带与中河岸带之间差异显著,其余河岸带内各群落特征因子差异均不显著。对额河与克郎河群落特征因子进行比较,除平均树高额河<克郎河外,其余5个群落特征因子均为额河>克郎河。6个群落特征因子的变化规律主要受额河与克郎河河流形态和地形特征的影响。
(4)为分析环境因子对植被分布的影响,在野外样地调查和主要环境因子测定的基础上,利用聚类和排序对额河流域阿尔泰山小东沟林区的森林植被进行了类型划分,分析了植被与环境因子的关系。利用聚类分析将阿尔泰小东沟林区的木本植物群落划分为6个类型(灌丛、欧洲山杨(Populus tremula)林、苦杨(Populus laurifolia)林、疣枝桦(Betula pendula)林、西伯利亚落叶松(Larix sibirica)林和西伯利亚落叶松与西伯利亚冷杉(Abies sibirica)、云杉(Picea obovata)的针叶混交林)。DCCA排序表明,海拔和坡向等地形因子以及土壤类型、土壤全氮、土壤全磷、土壤水分含量和大石砾含量等土壤因子是影响阿尔泰林区植被分布的主要因子,林区不同群落类型的分布格局主要是由地形和土壤因子的共同作用所控制的。
(5)为探讨地形对额河流域阿尔泰山小东沟植被类型分布的影响,借助于GIS将阿尔泰山小东沟影像分类图分别与坡度、坡向、剖面曲率和海拔图叠加,定量分析了各植被类型分布与地形的关系。根据遥感解译把研究区植被斑块类型划分为针叶林、阔叶林、针阔混交林、灌木和草地。各植被类型的最佳生境(地形)因子组合如下:针叶林分布最多的地形条件是斜/陡坡(15~35°)、西北坡、剖面曲率0~3°、海拔1 800~2 000m;阔叶林分布最多的地形条件是斜/陡坡、西北坡、剖面曲率5~10°、海拔1 400~1 600m;针阔混交林分布最多的地形条件是斜/陡坡、北坡、剖面曲率5~10°、海拔1 600~1 800m;灌木分布最多的地形条件是斜/陡坡、西坡、剖面曲率5~10°、海拔1 400~1 600m;草本分布最多的地形条件是斜/陡坡、南坡、剖面曲率5~10°、海拔1 200~1 400m。
(6)利用野外样方调查数据,选取两个物种多样性指数,分析了小东沟北坡物种多样性随海拔梯度的变化规律。小东沟林区物种丰富度指数和Shannon-Wiener多样性指数均为乔木层<灌木层<草本层。不同生活型的物种两个多样性指数沿海拔梯度乔木层和灌木层都表现为先升高再降低的单峰趋势,多样性的峰值均出现在海拔1 600~1 800m。草本层两个多样性指数沿海拔升高,略微有所上升,变化不明显。乔、灌、草总的物种多样性指数均呈现先升高后降低的单峰趋势。海拔1 600~1 700m范围内的针阔群落交错带具有较高物种多样性,从而出现乔木层、灌木层及群落总的物种多样性峰值。
(7)通过选取气象、地形和NDVI植被指数作为预测变量,构建了阿尔泰山小东沟乔木物种丰富度预测模型,利用残差图评价预测精度。将乔木物种丰富度预测图分别与坡度、坡向和海拔图叠加,分析不同地形条件影响乔木物种丰富度空间分布的规律。小东沟乔木物种丰富度主要集中在3~4,占研究区总面积的70.28%。坡度0~5°乔木物种丰富度出现频率最高的数值是3,其余坡度条件下,乔木物种丰富度出现频率最高的数值是4;乔木物种丰富度在西坡和西北坡出现频率最高的数值是3,其余坡向乔木物种丰富度出现频率最高的数值均是4;海拔梯度上,小东沟乔木物种丰富度出现频率最高的数值呈现先增加后减少的单峰型趋势。残差类型统计表明,较强和中等预测水平面积占总面积的94.62%,表明预测效果较好。
(8)以ETM+遥感影像和乔木样地生物量抽样调查数据为基础,选取RVI、NDVI、SAVI、DVI和IPVI等植被指数,分析了植被指数与乔木地上生物量之间的相关性,并构建了基于植被指数的生物量回归模型,利用残差图评价预测精度。在所选取的植被指数中,生物量与NDVI植被指数关系最显著。生物量残差图中较强和中等预测面积分别为66.60%和30.31%。将生物量空间分布预测图分别与坡度、坡向和海拔图叠加分析表明:小东沟林区乔木地上部分的生物量以斜/陡坡(15~35°)最高,平/缓坡(0~15°)次之,急/险坡(>35°)最低。小东沟林区东南、南坡的生物量较低,其余坡向的生物量较高。海拔梯度上,生物量空间分布呈现先增加后减少的单峰型趋势,不同海拔段之间生物量以低海拔的生物量最低,中海拔的最高,高海拔生物量居中。
A basin is an integrated geographical unit, and the landscape patterns within the basin have usually been formed by the interactions of natural and anthropogenic processess. The changes in landscape patterns within the basin can directly affect the ecological processes of the basin, influencing the ecological integrity and safety of the basin and the areas near the basin.
The Irtysh River originates from the Altai Mountains in Xinjiang of northwest China, it flows down via the desert plains on the south foot of the Altai Mountains, goes to the west and out of the border of China, finally flows into the arctic sea through Kazakstan and Russia. Irtysh River Basin in the Altai forest region is composed of two parts: the mountain watershed landscape and the riparian plain landscape, which are connected as an integrative system by the river. The Irtysh River basin nourishes rich biodiversities in Xinjiang, playing important roles in maintaining the ecological integrity and safety of north Xinjiang. Analyzing the landscape pattern and spatial distribution of biodiversity both in mountain watershed and in the riparian plain could help us in understanding the ecological functions of the whole basin landscape, which can provide scientific basis for future reasonable resources use, biodiversity conservation and ecological landscape planning. In this thesis, we selected two typical landscape types in the Irtysh River basin of Xinjiang as the study area, Xiaodonggou representing the mountain watershed landscape and Beitun representing the riparian plain landscape, By combining methods of field investigations, remote sensing image interpretation, GIS analyses and simulation models, the pattern and dynamics of the landscape and spatial distribution of biodiversity in the Irtysh River basin of Xinjiang were explored. The main conclusions are as follows:
(1)The landscape pattern and fragmentation in Beitun of Irtysh River Basin and Xiaodongou of Altai Mountains in Xingjian was analyzed. Quantitative indices of landscape pattern were chosen to examine landscape pattern and fragmentation. The landscape in Beitun was classified into 7 types and 10 subtypes, including 5 vegetation types and 8 sub vegetation types. The area percentage of the five vegetation types (farmland, riparian forest, wetland, grassland and desert vegetation ) in the landscape was 16.5%, 2.6%, 1.6%, 10.5%, and 52.2% respectively. The patch maximal perimeter, patch maximal area and mean area indices of riparian forest were lower than the other vegetation types, implying that the riparian forest distributed in smaller patches in the whole landscape. The value of mean patch shape, fractal dimension index, and edge density index of the riparian forest were higher than those of the other vegetation types, indicating that the riparian forest had more complex patch shape. All the pattern indices demonstrated that the riparian forest was the most fragmented type in the Irtysh River Basin. The landscape in Xiaodonggou of Altai Mountains was classified into coniferous forest, broadleaved forest, conifer-broadleaf mixed forest, shrub, grassland. The landscape pattern analysis results showed that forest was the matrix in Xiaodonggou of Altai Mountains, and the broadleaved forest had most patch shape.
(2)The landscape pattern and dynamics in Beitun of Irtysh River Basin from 1972 to 2000 were analyzed by using remote sensing image of MSS, TM, and ETM+. Quantitative indices of landscape pattern included patch numbers, mean patch size, mean patch shape index, mean patch fractal dimension, Shannon diversity index, and Shannon evenness index. The results showed that desert was the matrix of the landscape. In the 28 years, the farmland area percent increased 9.62%, the desert area percent decreased 11.75%, residence area increased 0.15%, while the areas of riparian forest and wetland decreased 0.44% and 1.06% respectively. The patch number increased and the mean patch size decreased in the landscape, which indicated that landscape in 2000 was more fragmentized than the landscape in 1972. Both the mean patch shape index and mean patch fractal dimension index had increased from 1972 to 2000, which showed that landscape patch shape were becoming more complex. The Shannon diversity index and Shannon evenness both had a trend of increase from 1972 to 2000, indicating that the landscape heterogeneity decreased and landscape types distributed more evenly.Transition matrix of landscape types from 1972 to 2000 indicated that the riparian forest was the most unstable type, which was usually conversed into grassland or farmland.
(3)Predicting the spatial distribution maps of forest stand factors were done in Beitun of Irtysh River based on the field investigation data and GIS. The predicting environmental factors included climate, topography and the distance to river. Residual maps were used to evaluate the accuracy of predicting. Keyran River was one of an important tributaries which located in the north of Irtysh River. The differences of forest communities characteristics were compared between upper, central, and lower part in the Irtysh River and the Keyran River of Beitun respectively. The difference of forest community characteristicss between near, middle, and far riparian zones were also compared in the south vs. north banks of the Irtysh River, and south vs. north banks of the Keyran River of Beitun respectively. The results showed that in the Irtysh River, the order for the mean DBH of the riparian stands was central reach >lower reach >upper reach. The standing volume and canopy density order was central reach >upper reach >lower reach. Tree mean height, species richness, and Fisher diversity index order was upper reach >central reach >lower reach. In the Keyran River, the tree mean height order was upper reach >central reach >lower reach, the order for the other five stand factors was upper reach
(4)Based on the field investigation plots data and environmental factors, cluster analysis and ordination were used to analyze forest vegetations in Xiaodonggou. The cluster analysis identified 6 woody community types, including 5 tree communities and 1 shrub community. The 6 community types included: shrub, Populus tremula,, Populus laurifolia, Betula pendula, Larix sibirica, and Abies sibirica + Larix sibirica+ Picea obovata dominated plant communities, which had different distribution patterns along the major environmental gradients in the Altai mountains. The DCCA ordination showed that the topographical factors and soil factors were the dominant environmental factors affecting plant species distribution in the Xiaodonggou area. The distribution of the vegetations in the area was mainly controlled by the interactions of topographical and soil factors.
(5)Relationship between the vegetation distribution and topographic factors were explored based on overlays of remote sensing classification map with the maps of slope, aspect, profile curvature and altitude which derived from DEM. The imagery interpreted vegetation types included coniferous forest, broadleaved forest, conifer-broadleaf mixed forest, shrub, and grassland in Xiaodonggou. The optimal habitat combination of topography for these vegetation types in Xiaodonggou were as follows: coniferous forest was mainly distributed in slope from 15°to 35°, west-north aspect, the profile curvature ranged from 0°to 3°and altitude ranged from 1 800m to 2 000m. Broadleaved forest was mainly distributed in slope from 15°to 35°, west-north aspect, the profile curvature ranged from 5°to 10°and altitude ranged from 1 400m to 1600m. Conifer-broadleaf mixed forest was mainly distributed in slope from 15°to 35°, north aspect, the profile curvature ranged from 5°to 10°and altitude ranged from 1 600m to 1 800m. Shrub was mainly distributed in slope from 15°to 35°, west aspect, the profile curvature ranged from 5°to 10°and altitude ranged from 1 400m to 1 600m. Grassland was mainly distributed in slope from 15°to 35°, south aspect, the profile curvature ranged from 5°to 10°and altitude ranged from 1 200m to 1 400m.
(6)Patterns of species diversity along altitude in northern slope of Altai Mountain were studied based on the data of vegetation plots in Xiaodonggou. Species richness and Shannon-Wiener diversity index were chosen for the analysis. Diversity order of the three life forms was: trees < shrubs < herbaceous. Diversity indices along altitudinal gradient of the three life forms exhibited different trends. Tree diversity index exhibited an unimodal pattern with the increase of elevation, peaking at the altitude range of 1 600 m to 1 700 m; The shrubs showed a similar altitudinal gradient pattern. The herbaceous plant diversity index exhibited a different trend, which increased slightly with increasing elevation, but the change was not significant. The total diversity of trees, shrubs, and herbaceous showed an unimodal pattern with the increase of elevation. Altitude from 1 600m to 1 700m was an ecotone between conifer and broad-leaved stands, where maximum diversities occurred.
(7)The predicting model for tree species richness was constructed on basis of field plot investigation and environmental variables in Xiaodonggou. The environmental predictor variables included climate, topography, and NDVI. The residual map was used to evaluate the validity of the model. The predicted spatial distribution map of species richness was overlaid with the slope, aspect and elevation maps respectively. The tree species richness of most areas in Xiodonggou ranged between 3 and 4, which occupied 70.28% of the total study area. In slopes from 0°to 5°, tree species richness value of 3 had the highest presence frequency, while in other range of slopes, the species richness value of 4 had the highest presence frequency. In aspects of west and west-north, the tree species richness of 3 had the highest presence frequency, while in the others aspect the tree species richness value of 4 had the highest presence frequency. Along the altitudinal gradient, the tree species richness showed an unimodal pattern of distribution. The residual type results showed that strongly predicting area and moderately predicting area reached 94.62% of the total area, which implied that the predicting model was accurate enough.
(8)Using ETM+ data and the biomass by typical sample investigation plots, the Pearson correlation between RVI、NDVI、SAVI、DVI、IPVI and plots biomass was made respectively, the linear regression models for aboveground biomass in Xiaodonggou were constructed. Residual map was used to evaluate the accuracy of predicting accuracy. The correlation between NDVI and biomass was much better among the chosen vegetation indices. The residual type results showed that strongly predicting area and moderately predicting area reached 66.60% and 30.31% respectively, which implied the predicting model was accurate. The map of tree aboveground biomass spatial distribution was overlaid with the slope, aspect and elevation maps respectively. The results showed that the tree aboveground biomass order was inclined/steep slope >flat/gentle slope> rapid/dangerous slope. In aspect, the east-south and south aspect had the lower biomass than the other aspects. In elevation, the biomass order was mid elevation > high elevation > low elevation, from low elevation to high elevation, the biomass exhibited an unimodal pattern.
引文
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