Spatial Distribution Of Vegetation Research Articles

Relationship between topography and the distribution of understory vegetation in a Pinus massoniana forest in Southern China

The poor growth of understory vegetation and the severe losses of soil and water in Pinus massoniana forests have recently become serious concerns in an area in southern China with eroded red soil. The influence of topography on the spatial distribution of vegetation, however, has received little attention. This study combined several multivariate analyses to discern the complicated relationship between understory vegetation and topography. Thirty-six plots (10m×10m) were sampled in a field survey of the vegetation and topography in the central red-soil region. The distributions of the understory vegetation differed significantly amongst the topographies. Most plants grew in gullies, and few grew on ridges. The low coverage (25.2%) and number of species (5 per plot) of the vegetation on ridges was due to serious soil erosion. Surface curvature and slope aspect were the first and second most important topographic factors, respectively, affecting the distribution of the vegetation. The relationship between topography and distribution could be described by a linear model. Surface curvature or slope aspect alone, however, could only explain 22.2–59.2% of the variance in distribution. The adaptation of vegetation to specific topographies should be considered for restorations of P. massoniana forests in the study area. The results of this study will be helpful for selecting potential sites for seeding and vegetation restoration to improve the ecology of the study area. Further studies will be needed to identify the mechanism of the distribution of the understory vegetation in these P. massoniana forests.

Modeling the relationship between elevation, aspect and spatial distribution of vegetation in the Darab Mountain, Iran using remote sensing data

The aim of this paper is to analyze topographic and aspect effects on vegetation indices in the Darab Mountain, Iran. Three commonly used vegetation indices, normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and difference vegetation index (DVI), were computed from Landsat 8 ETM+ vegetation bands. Based on the results obtained by analyzing the vegetation indices, it was found that vegetation growth and vegetation indices increase with increasing elevation and aspect. The vegetation growth is highest between the elevations of 1500–3000 m, with the NDVI, EVI and DVI values being large. The best vegetation in this zone is distributed towards NW 300°.

Numerical Prediction of the Fire Spread in Vegetative Fuels Using NISTWFDS Model

Current study focuses to the application of an advanced physics-based (reaction–diffusion) fire behavior model to the fires spreading through surface vegetation such as grasslands and elevated vegetation such as trees present in forest stands. This model in three dimensions, called Wildland Fire Dynamics Simulator WFDS, is an extension, to vegetative fuels, of the structural FDS developed at NIST. For simplicity, the vegetation was assumed to be uniformly distributed in a tree crown represented by a well defined geometric shape. This work on will focus on predictions of thermal function such as the radiation heat transfer and and thermal function for diverse cases of spatial distribution of vegetation in forest stands. The influence of wind, climate characteristics and terrain topography will also be used to extend and validate the model. The results obtained provide a basis to carry out a risk analysis for fire spread in the studied vegetative fuels in the Mediterranean forest fires.

Responses of vertical soil moisture to rainfall pulses and land uses in a typical loess hilly area, China

Abstract. Soil moisture plays a key role in vegetation restoration and ecosystem stability in arid and semiarid regions. The response of soil moisture to rainfall pulses is an important hydrological process, which is strongly influenced by land use during the implementation of vegetation restoration. In this study, vertical soil moisture variations of woodland (Pinus tabulaeformis), native grassland (Stipa bungeana), shrubland (Hippophea rhamnoides), cropland (Triticum aestivum) and artificial grassland (Onobrychis viciaefolia) in five soil profiles were monitored in a typical loess hilly area during the 2010 growing season. The results demonstrated that rainfall pulses directly affected soil moisture variation. A multi-peak pattern of soil moisture appeared during the growing season, notably in the surface soil layer. Meanwhile, the response of each vegetation type to rainfall was inconsistent, and a time-lag effect before reaching the peak value was detected, following each heavy rainfall event. The response duration of soil moisture, however, varied markedly with the size of rainfall events. Furthermore, higher soil water content was detected in grassland and shrubland. Woodland was characterized by relatively lower soil moisture values throughout the investigation period. Our research suggests that vegetation restoration efforts should give priority to grassland and shrubland at the research site. We suggest that more studies should be focused on the characteristics of community structure and spatial vegetation distribution on soil moisture dynamics, particularly within the grass and shrub ecosystems.

A multi-sensor approach for mapping plant-derived carbon storage in Amazonian podzols

The Rio Negro basin is characterized by the extensive occurrence of podzol-type soils that store large amounts of organic matter in depth, resulting in the storage of carbon able available to the atmosphere with climate change. The quantification of this carbon requires determination of podzol types and their spatial distribution. Remote-sensing techniques would be helpful in indirect spatializing and segmentation of soil groups in Amazonian podzols. Here we associated remote-sensing images (Shuttle Radar Topographic Mission (SRTM), Operational Land Imager sensor/Landsat 8, and Thermal Infrared Sensor/Landsat 8) and field sample data in order to achieve carbon stock mapping. We found that a multi-sensor approach was critical for a proper segmentation of vegetation groups and spatial distribution of areas with different hydrologic soil regimes.

Investigation of North American vegetation variability under recent climate: A study using the SSiB4/TRIFFID biophysical/dynamic vegetation model

AbstractRecent studies have shown that current dynamic vegetation models have serious weaknesses in reproducing the observed vegetation dynamics and contribute to bias in climate simulations. This study intends to identify the major factors that underlie the connections between vegetation dynamics and climate variability and investigates vegetation spatial distribution and temporal variability at seasonal to decadal scales over North America (NA) to assess a 2‐D biophysical model/dynamic vegetation model's (Simplified Simple Biosphere Model version 4, coupled with the Top‐down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID)) ability to simulate these characteristics for the past 60 years (1948 through 2008). Satellite data are employed as constraints for the study and to compare the relationships between vegetation and climate from the observational and the simulation data sets. Trends in NA vegetation over this period are examined. The optimum temperature for photosynthesis, leaf drop threshold temperatures, and competition coefficients in the Lotka‐Volterra equation, which describes the population dynamics of species competing for some common resource, have been identified as having major impacts on vegetation spatial distribution and obtaining proper initial vegetation conditions in SSiB4/TRIFFID. The finding that vegetation competition coefficients significantly affect vegetation distribution suggests the importance of including biotic effects in dynamical vegetation modeling. The improved SSiB4/TRIFFID can reproduce the main features of the NA distributions of dominant vegetation types, the vegetation fraction, and leaf area index (LAI), including its seasonal, interannual, and decadal variabilities. The simulated NA LAI also shows a general increasing trend after the 1970s in responding to warming. Both simulation and satellite observations reveal that LAI increased substantially in the southeastern U.S. starting from the 1980s. The effects of the severe drought during 1987–1992 and the last decade in the southwestern U.S. on vegetation are also evident from decreases in the simulated and satellite‐derived LAIs. Both simulated and satellite‐derived LAIs have the strongest correlations with air temperature at northern middle to high latitudes in spring reflecting the effect of these climatic variables on photosynthesis and phenological processes. Meanwhile, in southwestern dry lands, negative correlations appear due to the heat and moisture stress there during the summer. Furthermore, there are also positive correlations between soil wetness and LAI, which increases from spring to summer. The present study shows both the current improvements and remaining weaknesses in dynamical vegetation models. It also highlights large continental‐scale variations that have occurred in NA vegetation over the past six decades and their potential relations to climate. With more observational data availability, more studies with different models and focusing on different regions will be possible and are necessary to achieve comprehensive understanding of the vegetation dynamics and climate interactions.

デジタルカメラを用いた落葉針葉樹カラマツ林の植生解析

To understand global climate change, it is important to monitor the temporal and spatial distributions of vegetation. Digital cameras are relatively inexpensive to operate, and have small labor requirements, allowing the detection of subtle seasonal variation at high spatial resolution. Recent studies have reported camera-based indices that are calculated from the digital values of blue, green and red are useful to grasp the seasonal variation of vegetation phenology such as leaf expansion or fall. To examine this possibility, we investigated the characteristics of seasonal variation of camera-based indices for Larix kaempferi. Our camera adjusts the white balance automatically so that the 3 color components are modified by the lighting conditions. By normalizing respective components with their arithmetic mean, the dispersion becomes smaller than the raw digital value. However, the influence of solar radiation remains. We surveyed the relationship between the 3 components and solar radiation, and developed new vegetation indices independent of solar radiation by utilizing the normalized components. These indices are very useful for the analysis of seasonal change of Larix kaempferi.

Geostatistical analyses and spatial distribution patterns of tundra vegetation in Council, Alaska

Abstract The arctic tundra is an important ecosystem in terms of the organic carbon cycle and climate change, and therefore, detailed analysis of vegetation distribution patterns is required to determine their association. We used grid-sampling method and applied geostatistics to analyze spatial variability and patterns of vegetation within a two-dimensional space, and calculated the Moran’s I statistics and semivariance to assess the spatial autocorrelation of vegetation. Spatially au-tocorrelated vegetation consisted of moss, Eriophorum vaginatum , Betula nana , and Rubus chamaemorus . Interpola-tion maps and cross-correlograms revealed spatial specificity of Carex aquatilis and a strong negative spatial correlation between E. vaginatum and C. aquatilis . These results suggest differences between the species in water requirements for survival in the arctic tundra. Geostatistical methods could offer valuable information for identifying the vegetation spatial distribution. Key words: alaska, arctic tundra, geostatistics, spatial patterns, vegetation

Integration of Satellite Imagery, Topography and Human Disturbance Factors Based on Canonical Correspondence Analysis Ordination for Mountain Vegetation Mapping: A Case Study in Yunnan, China

The integration between vegetation data, human disturbance factors, and geo-spatial data (Digital Elevation Model (DEM) and image data) is a particular challenge for vegetation mapping in mountainous areas. The present study aimed to incorporate the relationships between species distribution (or vegetation spatial distribution pattern) and topography and human disturbance factors with remote sensing data, to improve the accuracy of mountain vegetation maps. Two different mountainous areas located in Lancang (Mekong) watershed served as study sites. An Artificial Neural Network (ANN) architecture classification was used as image classification protocol. In addition, canonical correspondence analysis (CCA) ordination was applied to address the relationships between topography and human disturbance factors with the spatial distribution of vegetation patterns. We used ordinary kriging at unobserved locations to predict the CCA scores. The CCA ordination results showed that the vegetation spatial distribution patterns are strongly affected by topography and human disturbance factors. The overall accuracy of vegetation classification was significantly improved by incorporating DEM or four CCA axes as additional channels in both the northern and southern study areas. However, there was no significant difference between using DEM or four CCA axes as extra channels in the northern steep mountainous areas because of a strong redundancy between CCA axes and DEM data. In the southern lower mountainous areas, the accuracy was significantly higher using four CCA axes as extra bands, compared to using DEM as an extra band. In the southern study area, the variance of vegetation data explained by human disturbance factors was larger than the variance explained by topographic attributes.

盐城淤泥质潮滩湿地潮沟发育及其对米草扩张的影响

Wetland ecosystems are landscapes of the highest biodiversity in nature and one of the most important environmental resources for human welfares. Their important ecosystem functions sometimes are regarded as "the earth' s filtration system". Yancheng coastal wetland now remains a typical mudflat by frequent tidal reaction. A more complex, changing creek system is formed by the mudflat development with a process of tidal movement. The creek system as a typical geomorphologic factor has formed at mudflat and become a pivotal pathway to continuously exchange matter,energy and information within and outside of the system. It is also important for distribution of the tidal water and sediment supply. And creek system development has a direct impact on the wetland ecologically environmental change and spatial distribution of vegetation. Therefore it has become an important indicator for the evolution of the mudflat. Spartina is a salt,flooded tolerant and perennial plant growing in a vast intertidal zone. It is growing at low tide with well-developed root system,and it could strongly intercept sediment. Accompanied with the formation of Spartina,hydrodynamic force and sediment transport conditions change in its mudflat surface, caused by changes of tidal flat sedimentary characteristics and topography,thereby affecting the development of trenches. And Spartina tidal trenches are specially established. Yancheng coastal wetland was chosen as the study area. Based on the remote sensing images of 1996—2012,using GIS techniques and field survey,we extract tidal creek system in this study. And a 16-year trend was analyzed on the mutual relations of Spartina expansion and tidal creek system development between 1996 and 2012 of Yancheng coastal wetland. Research results show that: Under the control of the tidal and terrain,no large-scale distribution of trenches present in this study area. The size of the trenches gradually increased from north to south. Their elevation is 0—1. 8m. Distinct morphology exists in salt marsh and bare mudflat. Trenches covered by Spartina indicate a unique feature,which present narrow and deep; Trenches are very dense with covering of 1539m / km2; They reach up to 4—5 grades; And lateral movement is less than longitudinal. The trenches are wide and deep,the main trenches are generally about 17m and branches between 3— 9m. The trenches are becoming deep at low grade; both sides of the edges of the trenches often development in asymmetry coastal embankment with ranging different height. The edges of the salt marsh have developed scarps and gullies with stretches throughout the Spartina zone. Inside the salt marsh,tidal creek development leads to Spartina inland expansion, expansion of the width and amplitude largely depends on the density and size of the tidal creek areas; Outside of the salt marsh,creeks activity in bare tidal will slow down with the reduction of the rate of expansion of Spartina. The wetlands microrelief variation has been further understand with this study. The baseline information greatly supports the Yancheng coastal wetlands and management,and benefits regional social and economic development in an effective manner.

2000-2012年京津风沙源治理区植被覆盖时空演变特征

Due to grassland degradation and expansion of desertification,the Northern China continuously suffered from several sandstorms in the spring of 2000. In order to control the desertification trend in Beijing and surroundings and improve the ecological condition and environment in Beijing-Tianjin Sandstorm Source Region( BTSSR),the Chinese government launched the Beijing-Tianjin Sandstorm Source Control Program in July 2000. This program has been working for thirteen years. However,it is unknown that how the vegetation and ecosystems were restored and whether or not the program functioned in the BTSSR. It is necessary to assess the effectiveness of this program. The assessment deals not only with the changes of vegetation cover in the ecological vulnerable area,but also with the effectiveness of the policy. The objective of this study was to analyze the spatiotemporal characteristics of vegetation cover changes and the factors that affect the changes in the core control area of the BTSSR using the time series of normalized difference vegetation index( NDVI)derived from a Moderate Resolution Imaging Spectro-Radiometer( MODIS) product MODIS02 B for the time period of2000—2012. Linear trend analysis,standard deviation,Hurst index and correlation analysis were employed. Resultsshowed that( 1) During the past thirteen years,although annual NDVI values fluctuated slightly,overall there was an increased trend of vegetation cover in the BTSSR with the coefficient of determination: R2= 0. 70. The NDVI value increased with 0. 01 per year. In 2012,the maximum NDVI value reached to 0. 324 and increased by 135. 62% compared to that in 2000. However,the change rate and degree varied from place to place. The greatest increase of NDVI took place in the Northern arid area( Bbghq),then in the Hsdk area( Hsdkq),and the vegetation cover was relatively stable in the agro-pastoral ecotone( Nmjcq);( 2) The annual NDVI values in the BTSSR varied spatially. It was found that as elevation increased,the average NDVI increased at the beginning,reached its maximum and then decreased. The minimum value 0.257 was mainly distributed in the areas with elevation of 1000 to 1500 m. The NDVI values also increased as the increasing slope;( 3) In the program region,the area in which vegetation growing showed improved was obviously larger than the vegetation degraded area. There was an area of 94. 31% in which the vegetation cover statistically increased significantly at a risk level of 0. 1. Hurst index analysis showed that in the sandstorm control area,overall the vegetation showed growing and the vegetation cover continuously increased. The total area of vegetation growing occupied about 64. 48%. The results of comprehensive analysis implied that in the program area the vegetation showed a tendency of healthy development. But,it had to be pointed out that there was still an area of 35. 3% in which the vegetation was continuously degraded or only slightly improved;( 4) Human activities,especially ecological restoration,were the main factor that drove the increase of vegetation cover. Among the natural factors,precipitation was critical because it limited the growth and spatial distribution of vegetation in the BTSSR. The effect of temperature was relatively weak. All the findings greatly enhanced our understanding of how human activities impacted vegetation cover in arid and semi-arid environments and provided scientific guidelines for the management of ecological restoration programs and future directions.

基于RBFN的桂西北喀斯特区植被碳密度空间分布影响因素分析

Karst landscapes in Southwest China may be an important carbon sink after the implementation of ecological engineering. The carbon pool in vegetation plays a more important role in the ecosystem carbon budget than that in shallow soils with a limited carbon savings. However,due to the special nature of the geological settings of the Karst region,the spatial distribution of vegetation has a three-dimensional characteristics of discontinuity and fragmentation,which results in the difficulty in obtaining the belowground section of vegetation. This study examined the influencing factors on spatial distribution of vegetation carbon density in the karst area of northwest Guangxi,China,based on 1377 samples of 13environment factors investigated in 2010 and the model of radial basis function network. The results show that: the four most important impact factors on the spatial distribution of vegetation carbon density are land type,forest type,forest category and vegetation type,and the significance of standardization above 50% for all of these factors; The second group of important impact factors are rocky desertification degree,humus layer thickness,size class,overall vegetation cover and soil thickness,and the significance of standardization is about 15% —30%; The least important factors on the spatial distribution of vegetation carbon density are location,slope,aspect and elevation,and the importance of standardization is only 2% —11%. Our study indicates that,and land type,forest type,forest category and vegetation type changed by human activities are the predominant factors in controlling the spatial distribution of vegetation carbon density,and the impact of topographic factors on are limited. This study suggests that the eco-environment immigration,returning farmland to forests,rocky desertification control measures have positive impacts on the spatial distribution of vegetation carbon density.

Spatio-temporal variation of vegetation carbon storage and density in karst areas of Northwest Guangxi based on remote sensing images

本研究基于1990年、2000年和2005年遥感影像数据, 结合高程、气象与样地调查等数据, 运用地理信息系统技术, 对桂西北喀斯特区植被碳储量及密度进行了分析。研究结果表明: 从1990年到2005年, 研究区域植被碳储量与密度呈增加趋势, 1990年、2000年和2005年植被碳储量分别为1.03×10⁸ t、1.41×10⁸ t和1.63×10⁸ t, 植被碳密度分别为14.82 t·hm^-2、20.38 t·hm^-2和23.49 t·hm^-2, 基本与四川省(18.47 t·hm^-2)、江西省(25.38 t·hm^-2)植被碳密度值一致; 在空间分布上, 区域植被储量与碳密度大致呈现西高东低、中低山(海拔>500 m)高而峰丛洼地(海拔<500 m)低的分布格局, 1990年西部大部分县市的植被碳密度为15~22 t·hm^-2, 而中东部大部分县市的植被碳密度为8~15 t·hm^-2; 而时间上的变化在空间上表现为, 植被碳储量与密度不同程度地表现为低值区的东部增加, 高值区的西部减少或轻微增加, 典型喀斯特区植被碳密度增加明显(1990年和2005年植被碳储量比例分别为45.54%和51.99%)。研究结果表明, 峰丛洼地植被碳储量与密度显著增加, 生态环境移民、退耕还林等石漠化治理措施效果显著, 有利于增强区域植被碳汇。

Using live vegetation volume to analyze the effects of plot Pinus massoniana Lamb on water and soil conservation under natural rainfall events

The 3-D spatial distributions of vegetation are of great significance for water and soil conservation but are rarely concerned in literatures. The live vegetation volume (LVV) was used to relate to water/soil loss under 144 natural erosive rainfall events from 2007 to 2010 in a typical water-eroded area of southern China. Quadratic polynomial regression models were established for five pure tree (Pinus massoniana Lamb) plots between LVV and water (runoff)/soil conservation effects (RE/SE). RE/SE corresponds to the ratios of runoff depth/soil loss of the pure tree plots to that of the control plot under each rainfall event. Increasing LVV exhibits descending (DS), descending-ascending (DA), ascending-descending (AD), and ascending (AS) trends in the LVV–RE and LVV–SE curves. The effects of soil conservation on the plots were generally more noticeable than the effects of water conservation, and most of the RE and SE values reflected the positive effects of water and soil conservation. The effects were mainly positive under heavy rains (e.g., rainfall erosivity, R = 140 MJ mm ha−1 h, maximum 30 min intensity, I30 = 16 mm h−1), whereas the effects were mainly negative under light rains (e.g., R = 45 MJ mm ha−1 h, I30 = 8 mm h−1). The trees' water/soil conservation effects notably transformed when rainfall erosivity and intensity were lower than the positive or negative effects to a certain threshold. About 50% rainfall events led to obvious transform effects when LVVs were near 0.5 or 0.6. These results are able to aid in the decision making on the forest reconstruction in water-eroded areas.

Seed morphology characteristics in relation to seed loss by water erosion in the Loess Plateau

The role of water erosion on seed loss and on plant establishment and distribution is unknown on the Chinese Loess Plateau, which suffers serious soil erosion. The seed susceptibility of 16 local species to removal by water erosion from loess slopes was determined by rainfall simulation experiments. The experiments were performed on slopes with gradients of 10°, 15°, 20° and 25° for a 60-min duration at an intensity of 50 mm/h, 100 mm/h and 150 mm/h, respectively. The total seed removal rate obviously increased with rainfall intensity but did not obviously change with slope gradient, and the responses were varied among the species. The morphological characteristics affecting seed loss of the various species are quite different. Our experiments showed that the seed removal from some species are mainly due to seed weight, some species are mainly affected by seed shape, some are affected by appendage, some by surface structure, some by the comprehensive effects of the different morphological characteristics, while seeds having mucilage secretion are not easily moved by water erosion. We argued that the seed removal during water erosion can clearly effect seed redistribution and deposition, and consequently, species composition and vegetation spatial distribution.

Wetland inundation monitoring by the synergistic use of ENVISAT/ASAR imagery and ancilliary spatial data

Wetlands are among the most ecologically important ecosystems on Earth and their sustainability depends critically on the water resources. In a scenario of climate change and increased anthropogenic pressure, detailed monitoring of the water resources provides a fundamental tool to assess the ecosystem health and identify potential threats.Doñana wetlands, in Southwest Spain, dry out every summer and progressively flood in fall and winter to a maximum extent of 30,000ha. The wetland filling up process was monitored in detail during the 2006–2007 hydrologic cycle by means of twenty-one Envisat/ASAR scenes, acquired at different incidence angles in order to maximize the observation frequency. Flood mapping from the two uncorrelated ASAR channel data alone was proved unfeasible due to the complex casuistic of Doñana cover backscattering. This study addresses the synergistic utilization of the ASAR data together with Doñana's digital elevation model and vegetation map in order to achieve flood mapping.Filtering and clustering algorithms were developed for the automated generation of Doñana flood maps from the ASAR images. The use of irregular filtering neighborhoods adapted to the elevation contours drastically improved the ASAR image filtering. Edge preservation was excellent, since natural edges closely follow terrain contours. Isotropic neighborhoods were assumed of a single class and their intensities were averaged. As a result, intensity fluctuations due to speckle and texture over areas of the same cover type were smoothed remarkably.The clustering and classification algorithm operate on individual sub-basins, as the pixel elevation is more accurately related to the cover classes within them. Vegetation and elevation maps plus knowledge of Doñana backscattering characteristics from preceding studies were initially used to select seed pixels with high confidence on their class membership. Next, a region growing algorithm extends the seed regions with new pixels based on their planimmetric adjacency and backscattering Mahalanobis distance to the seeds.During the seed region growth, new pixels' possible classes are not constrained to their cover type according to the vegetation map, so the algorithm is able to capture temporal changes in the vegetation spatial distribution. Comparison of the resultant classification and concurrent ground truth yielded 92% of flood mapping accuracy. The flood mapping method is applicable to the available ASAR images of Doñana from six other hydrologic cycles.

Groundwater nitrogen and the distribution of groundwater-dependent vegetation in riparian areas in agricultural catchments

Eutrophication is a major threat for several species-rich habitat types e.g. fens and meadows in riparian discharge areas throughout Europe, but few data are available to support the supposition that nutrient-contaminated groundwater from agricultural land is the direct cause for the continued decline of these formerly widespread habitat types. In the present study we investigated the role of nitrogen for the distribution of groundwater-dependent vegetation types in discharge areas in Denmark. Specifically we hypothesised (1) that the nitrogen availability in riparian discharge areas is linked to agricultural intensity in the topographic catchment and (2) that the spatial distribution of vegetation in riparian areas is influenced by nitrogen in the groundwater e.g. high productive reed beds dominate in areas with high levels of groundwater nitrogen, whereas species rich fens occur in areas with lower levels of groundwater nitrogen reflecting that incoming nutrients influence the productivity within the areas. We find evidence that the percentage of agriculture in the topographic catchment directly influenced the amount of nitrate in the discharging groundwater in the study areas and that groundwater nitrogen is closely coupled to the distribution of groundwater-dependent vegetation. Meadow and reed bed vegetation being highly productive were associated with higher levels of nitrate in the groundwater compared to low productive rich fen vegetation. From these findings we recommend that protected groundwater-dependent vegetation is mapped in groundwater discharge areas and that only those without presence of protected habitats are considered in rewetting plans to mitigate nutrient loss from agricultural production.

Study on Correlation between Vegetation Restoration and Physics and Chemistry Characters of Soil in Embankment Slope

By study features of recovering vegetation and physics and chemistry characters of soil in embankment slopes of 3 years and10 years respectively, the correlation among those factors were investigated . The results show: the physics and chemistry characters of soil vary observably with recovering process; Soil bulk density decreases while soil moisture, TP, TN and organic matter content increase evidently; Although the coverage of vegetation changes little, the structure of vegetation community becomes more complex and spatial distribution is more even; The correlation between spatial distribution of vegetation and characters of soil is most remarkable. With process of restoration, the vegetation is affected more effectively by water and nutrients in site.

Features of the spatial organization of forest-steppe vegetation in a valley of Dzhida River (Western Transbaikalia)

The organization of the spatial distribution of vegetation of exposure forest-steppe has been considered. Large-scale map of vegetation with allocation of homogeneous and heterogeneous units was made.

Simulating potential vegetation distribution in a mountainous region of the Eastern Tibetan Plateau: A case study of Barkam County

The main objective of this study is to simulate the potential vegetation types on the basis of environmental parameters. The paper took Barkam County in a mountainous region of the Eastern Tibetan Plateau as the study area. The vegetation distribution was mapped in 1994 and 2007 based on TM remote sensing images by object-oriented interpretation method. We overlaid the two maps to find out the vegetation patches which have not changed, and took them as stable types. Fifty per cent of the stable patches were randomly sampled to operate the logistic regression with related environmental parameters; others were used as test data of simulated results. Seven environmental parameters were mapped, including elevation, slope, aspect, surface curvature, solar radiation, temperature and precipitation, based on DEM data and meteorological site data by GIS technology. The relationship between the spatial distribution of vegetation and environmental variables were quantified by logistic regression. The distribution pr...