旱区排水沟植被空间分布格局与土壤因子的关系

揭示旱区排水沟植被空间分布格局与土壤因子间的关系,可为旱区农田排水沟渠湿地的生态环境修复与生态灌区构建提供理论依据和技术指导。以陕西富平卤泊滩盐碱地的排水干沟和斗沟为例,采用野外调查、方差分析、相关性分析、典型相关分析和RDA分析方法,研究了排水沟边坡植被和土壤因子(含水率、电导率和pH)的时空分布特征以及植被和土壤因子间的相关关系。结果表明:(1)排水沟边坡植被分区明显(芦苇区、过渡区和共生区),干沟物种多样性高于斗沟、物种优势度低于斗沟;干沟和斗沟不同分区的植被Simpson优势度指数均随距排水沟距离的增大而减小,物种丰富度指数、Shannon多样性指数和Pielou均匀度指数随着距排水沟距离的增大而增大;(2)3月土壤含水率(均值23.7%)最高,9月土壤电导率(均值576.97μS·cm^(-1))和pH(均值8.95)最高,但不同时期间差异不显著;干沟芦苇区的土壤含水率、电导率和pH最大,斗沟芦苇区的土壤含水率最高、过渡区的土壤电导率和pH最大,且不同分区间差异显著;(3)决定旱区排水沟植被空间分布和物种丰富度的关键土壤因子是含水率与电导率。根据研究结果,本文提出了控制排水和铺设预制植被毯来调控旱区生态排水沟植被演替和植被构建的人工干预方法和措施,研究结果可为生态灌区建设提供科学依据。

大香格里拉地区植被空间分布的环境特征

以植被种类丰富的大香格里拉地区为研究区,利用气象站点数据、数字高程数据(DEM)以及该地区植被分布图,通过最大熵模型(Maxent)和ArcGIS软件的空间分析功能,研究该地区典型植被空间分布的环境特征,分析了大香格里拉地区植被分布的气候特征和地形特征,量化了植被空间分布的气候范围,并根据二者的关系特征,得到了植被与气候因子关系模型。同时,界定了不同植被分布的海拔、坡度、坡向范围。发现大香格里拉地区影响不同植被空间分布的气候因子不同,影响草甸分布的是多年平均最低气温和多年7月平均气温,影响针叶林分布的是多年平均最低气温和多年平均日照时数,影响灌丛分布的较分散。同时不同植被的海拔分布界限和坡度不同,坡向对植被分布的影响不明显。研究结果可为该地区植被保护和管理,以及植被的气候变化响应提供基础参考。

放水冲刷条件下坡面植被空间布局对坡沟系统侵蚀产沙的影响研究

植被在有效防治水土流失、改善生态环境中具有不可替代的重要作用。研究表明,土壤表面没有植被的降雨侵蚀量是未扰动森林土壤的16倍[1]。Zheng在子午岭林区的研究也发现,当地表植被生长良好时,降雨、地形、坡度等因素对土壤侵蚀量的影响很小。而土壤表层一旦失去植被保护或根系的固结时,

乌梁素海东侧明安沙地植被类型及其分布

明安沙地位于河套平原乌梁素海东侧,是由河湖沉积及来自两侧山地的风化冲积物吹扬堆积形成的,目前关于明安沙地的研究较少。文章将卫星遥感技术与实地考察相结合分析明安沙地的植被类型及其分布特征,结论如下:(1)该区维管植物共有28科、87属、132种。其中,菊科、禾本科、豆科和藜科等4科较多;多年生杂类草、一二年生植物、半灌木和多年生丛生禾草等4个生活型功能群比例较多。(2)明安沙地的植被类型主要有流动沙地先锋植物群落、半固定沙地半灌木蒿类植被、固定沙地灌丛植被、固定沙地盐化草甸植被、固定沙地荒漠草原植被和其他人工植被等,其中,柠条锦鸡儿群落分布面积最大,占明安沙地总面积的30.82%。(3)明安沙地植被呈明显的东西向和南北向分异规律。自西向东分别发育了固定沙地小果白刺群落、柠条锦鸡儿群落、盐化草甸植被→半固定沙地黑沙蒿群落→流动沙地先锋植物群落→固定沙地柠条锦鸡儿群落和小针茅荒漠草原植被。南北向形成了小针茅荒漠草原—沙地植被—人工植被的替代分布。本论文的研究结果可以为明安沙地的生态治理以及乌梁素海周边生态环境的改善提供科学参考。

新疆阿勒泰两河源自然保护区植被信息提取与分析

高山地区地形复杂,植被分布无序,且森林植被光谱信息相近,因而高山植被类型的确定依然成为遥感植被分类的难点。以2014年资源三号卫星影像作为基础数据,分别采用面向对象法和像元法提取了两河源保护区植被信息,并在面向对象法中引入了海拔(DEM)信息辅助分类,基于分类结果,分析讨论了不同植被类型的面积比例和空间分布格局。结果显示:(1)面向对象法的分类精度明显高于像元分类法,总体分类精度达到了93.11%,Kappa系数为0.89。(2)研究区植被类型以针阔混交林和草甸为主,分别占研究区总面积的26.37%和22.87%,灌丛、草原占15.2%和10.98%,水体和高山植被占8.23%和5.57%。(3)针阔混交林主要分布在阴坡或山地河谷,草甸在平原、低地河漫滩、森林、高山均有分布,地带性规律不明显。草原成窄条状、斑块状贯穿整个研究区,灌丛呈块状镶嵌在草原内部。高山植被呈斑块状零散分布于两河源的流石滩、砾石山坡和高山准平原上。(4)研究区发育了5个完整的自然垂直带谱,自下而上依次为草原带、灌丛带、针阔混交林带、草甸带、高山植被带和冰川积雪带。

流域植被整体防蚀作用及景观结构剖析

根据景观生态学的观点 ,对流域的产沙特征及其与林草植被的关系进行了探讨 ,表明流域土壤侵蚀状况是由其农、林、草地等生态系统之间产流与拦蓄两种作用相互影响的结果 ,其中作为地表径流滞纳区的林草植被斑块起重要作用。林草覆盖率越高 ,植被对侵蚀的绝对控制能力越强 ,否则流域地形因素的影响亦不可忽视。还分析了流域临界林草覆盖率的定义 ,表明临界林草覆盖率随其平均坡度的增大而增大。当流域林草植被整体覆盖率达 50 %以上时 ,植被可稳定高效地抑制水土流失。进一步分析认为 ,利用计算机技术并借助有关图件深入研究植被的空间格局才能完整阐明植被的整体防蚀作用 ,同时探讨植被斑块对富集叠加径流的滞纳作用也是必要的。

基于面向对象的石漠化山区植被信息提取及分布特征研究

重庆东北部地区是重庆岩溶石漠化重点治理区,该区地形复杂,山高坡陡,植被退化现象严重。了解该地区的植被分布特征,对该区环境的改善和石漠化治理具有十分重要的现实意义。基于Landsat OLI等数据,运用面向对象分类方法对研究区植被信息进行提取,然后对分类后的数据进行统计、制图和分析,并在空间布局上进行总结和探讨,旨在了解该区域植被的空间分布特征和规律。结果表明:(1)在e Cognition 9.0软件中进行多尺度分割,再结合地物类型特征使用隶属度函数法进行分类,该方法符合山地地物类型的分布规律和特点,分类精度达到81.35%;(2)研究区属典型的中山地区,海拔在500~1 500 m之间的地区约占64.49%,林地和耕地是该区域主要的地物类型,所占总面积为8 872.22 km^2,占研究区总面积的96.50%,各地物类型分布受地形地势的影响较大;(3)综合研究区地形因子(高程和坡度)与植被分布的相关性可知,耕地和草灌主要分布在高程为200~1 500 m且坡度等级在2~4级(5°~35°)之间,该区域人类活动频繁,故受人类活动影响较大,植被覆盖度低,群落生长不稳定,容易受到干扰。针阔混交林主要分布在高程>500 m且坡度等级在2~4级(5°~35°)之间。马尾松林、阔叶林和柏木林主要分布在高程大于500 m且坡度等级在2~5级(5°~45°)之间。

不同坡面植被空间布局对坡沟系统产流产沙影响的实验

植被在有效控制水土流失、改善生态环境中具有重要作用。为探讨坡面不同植被覆盖度、不同植被空间布局对坡沟系统侵蚀产沙的影响,以4 m长坡面(坡度为20°)和3 m长沟坡(坡度为50°)组成的坡沟系统为研究对象,采用不同放水流量(3.2 L/min、5.2 L/min)的放水冲刷实验,研究了不同放水流量、不同植被覆盖度、不同植被布设部位对坡-沟系统及沟坡侵蚀产沙的影响。结果表明,在实验条件下,不同植被布设部位在相同放水流量、相同植被覆盖度条件下对坡沟系统侵蚀产沙有明显影响,而对产流量无明显影响;沟坡部分侵蚀产沙量不随坡面植被覆盖度的增大而减小,相反呈增大趋势。说明在实验条件下,对坡沟系统而言,仅在坡面部分布设植被,尽管能在一定程度上减少坡沟系统侵蚀产沙,但并不能有效减小沟坡部分的侵蚀产沙,甚至引起沟坡部分侵蚀产沙的增大。因此,水土流失治理过程中采取有效措施进行坡沟兼治将是减少水土流失的有效手段。

基于RGB-NIR图像匹配的作物光谱指数特征可视化分析

归一化植被指数(NDVI)基于可见光的红色波段(630~680nm)和近红外区(780~1 100nm)的反射光谱进行计算,被认为是作物营养与长势诊断的重要指标。为了低成本、快速、无损的检测作物叶绿素含量,计算植株的NDVI并呈现作物的NDVI分布情况,并通过不同角度图像的分析,监测作物营养分布与动态。利用可见光和近红外波段双目成像技术获取图像,在讨论可见光(RGB)和近红外(NIR)图像的匹配算法的基础上,经图像分割与光照影响校正后,针对不同测试角度建立了作物植被指数空间分布图,并对其空间分布特征与影响因素进行了可视化分析。试验利用可见光和近红外双目相机对51株玉米植株,分别在90°,54°和35°视角下同步采集RGB和NIR图像。对RGB和NIR图像分别进行高斯滤波和拉普拉斯算子增强预处理后,选取了SURF,SIFT和ORB共3种图像匹配算法,并首先利用其进行RGB-NIR图像匹配对齐,以匹配时间(Time),峰值信噪比(PSNR),信息熵(MI)和结构相似性(SSIM)4个参数作为匹配性能评价指标,分别从时间、准确性、稳定性三个方面综合确定最优匹配方法。其次,研究玉米植株的分割方法包括超绿算法(ExG)和最大类间方差算法(OTSU),分别实现图像中作物和背景的分离,提取分割后的RGB图像R(Red),G(Green),B(Blue)分量和NIR图像分量。基于HSI颜色模型,提取I分量讨论了光照对图像的影响,并利用多灰度级标准板建立了植株光谱反射率校正线性公式。然后,利用R(Red)和NIR图像分量计算图像中每个像素的NDVI值,绘制作物植被指数的空间分布图,从而对比分析了不同拍摄角度下光谱植被指数的分布特征。通过不同角度图像的NDVI分布情况,展示监测作物植株不同位置的叶绿素分布情况。结果显示,RGB-NIR图像匹配时间SIFT(1.865s)>SURF(1.412s)>ORB(1.121s),匹配准确性上SURF≈SIFT>ORB,匹配稳定性上SURF>SIFT>ORB,综合比较选取SURF为最优匹配算法。采用4灰度级标准板对R,G,B,NIR分量校正模型的R2分别为0.78,0.76,0.74,0.77。90°和35°视角分别展现了作物叶和茎的NDVI植被指数分布情况,可为分析和监测作物的营养分布提供技术支持。

Storage,Patterns and Controls of Soil Nitrogen in China

Soil holds the largest nitrogen(N)pool in terrestrial ecosystems,but estimates of soil N stock remain controversial. Storage and spatial distribution of soil N in China were estimated and the relationships between soil N density and environmental factors were explored using data from China's Second National Soil Survey and field investigation in northwest China and the Tibetan Plateau.China's soil N storage at a depth of one meter was estimated at 7.4 Pg,with an average density of 0.84 kg m^(-2).Soil N density appeared to be high in southwest and northeast China and low in the middle areas of the country.Soil N density increased from the arid to semi-arid zone in northern China,and decreased from cold-temperate to tropical zone in the eastern part of the country.An analysis of general linear model suggested that climate and vegetation determined the spatial pattern of soil N density for natural vegetation,which explained 75.4% of the total variance.

Spatial Distribution of Land Cover and Vegetation Activity along Topographic Gradient in an Arid River Valley, SW China

Anthropogenic activities have become more and more important in characterizing the landscape, but their impacts are still restricted by natural environments. This paper discusses the interactions of anthropogenic activity, vegetation activity and topography through describing the spatial distribution of land cover and vegetation activity (represented by Normalized Difference Vegetation Index, NDVI) along topographic gradient in a mountainous area of southwestern China. Our results indicate that the existing landscape pattern is controlled by anthropogenic activities as well as topographic factors. Intensive anthropogenic activities mainly occur in areas with relatively low elevation, gentle and concave slopes, as these areas are easy and convenient to attain for human. Because of the destruction by human, some land cover types (mainly grassland and shrub) are only found in relatively harsher environments. This study also finds that topographic wetness index (W) used in other places only reflects runoff generation capacity, but not indicate the real spatial pattern of soil water content in this area. The relationships between NDVI and W, and NDVI and length slope factor (LSF) show that runoff and erosion have complex effects on vegetation activity. Greater values of W and LSF will lead to stronger capacity to produce runoff and transport sediment, and thereby increase soil water content and soil deposition, whereas beyond a certain threshold runoff and erosion are so strong that they would destruct vegetation growth. This study provides information needed to successfully restore native vegetation, improve land management, and promote sustainable development in mountainous areas, especially for developing regions.

Variation of Thornthwaite Moisture Index in Hengduan Mountains, China

The Thornthwaite moisture index, an index of the supply of water （precipitation） in an area relative to the climatic demand for water （potential evapotranspiration）, was used to examine the spatial and temporal variation of drought and to verify the influence of environmental factors on the drought in the Hengduan Mountains, China. Results indicate that the Thornthwaite moisture index in the Hengduan Mountains had been increasing since 1960 with a rate of 0.1938/yr. Annual Thomthwaite moisture index in Hengduan Mountains was between -97.47 and 67.43 and the spatial heterogeneity was obvious in different seasons. Thomthwaite moisture index was high in the north and low in the south, and the monsoon rainfall had a significant impact on its spatial distribution. The tendency rate of Thomthwaite moisture index variation varied in different seasons, and the increasing trends in spring were greater than that in summer and autumn. However, the Thomthwaite moisture index decreased in winter. Thomthwaite moisture index increased greatly in the north and there was a small growth in the south of Hengduan Mountains. The increase of precipitation and decrease of evaporation lead to the increase of Thomthwaite moisture index. Thornthwaite moisture index has strong correlation with vegetation coverage. It can be seen that the correlation between Normalized Difference Vegetation Index （NDVI） and Thomthwaite moisture index was positive in spring and summer, but negative in autumn and winter. Correlation between Thornthwaite moisture index and relative soil relative moisture content was positive in spring, summer and autumn, but negative in winter. The typical mountainous terrain affect the distribu- tion of temperature, precipitation, wind speed and other meteorological factors in this region, and then affect the spatial distribution of Thomthwaite moisture index. The unique ridge-gorge terrain caused the continuity of water-heat distribution from the north to south, and the water-heat was stronger than that from the east to west part, and thus determined the spatial distribution of Thornthwaite mois- ture index. The drought in the Hengduan Mountains area is mainly due to the unstable South Asian monsoon rainfall time.

Linking vegetation cover patterns to hydrological responses using two process-based pattern indices at the plot scale

Vegetation cover pattern is one of the factors controlling hydrological processes. Spatially distributed models are the primary tools previously applied to document the effect of vegetation cover patterns on runoff and soil erosion. Models provide precise estimations of runoff and sediment yields for a given vegetation cover pattern. However, difficulties in parameterization and the problematic explanation of the causes of runoff and sedimentation rates variation weaken prediction capability of these models. Landscape pattern analysis employing pattern indices based on runoff and soil erosion mechanism provides new tools for finding a solution. In this study, the vegetation cover pattern was linked with runoff and soil erosion by two previously de- veloped pattern indices, which were modified in this study, the Directional Leakiness Index （DL[） and Flowlength. Although they use different formats, both indices involve connectivity of sources ,areas （interpatch bare areas）. The indices were revised by bringing in the functional heterogeneity of the plant cover types and the landscape position. Using both artificial and field verified vegetation cover maps, observed runoff and sediment production on experiment plots, we tested the indices＇ efficiency and compared the indices with their antecedents. The results illustrate that the modified indices are more effective in indicating runoff at the plot/hillslope scale than their antecedents. However, sediment export levels are not provided by the modified indices. This can be attributed to multi-factor interaction on the hydrological process, the feedback mechanism between the hydrological function of cover patterns and threshold phenomena in hydrological processes.