Vegetation Community Types Research Articles

不同干扰对黄土区典型草原物种多样性和生物量的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 不同干扰对黄土区典型草原物种多样性和生物量的影响 DOI: 10.5846/stxb201201140085 作者: 作者单位: 中国科学院水利部水土保持研究所,中国科学院水利部水土保持研究所,国家林业局中南林业调查规划设计院,西北农林科技大学,中国科学院水利部水土保持研究所,中国科学院水利部水土保持研究所,西北农林科技大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金重点项目(41230852);中国科学院战略性先导科技专项项目(XDA05050202);农业部 "现代农业产业技术体系建设专项资助(CARS-35-40) Effects of different disturbances on diversity and biomass of communities in the typical steppe of loess region Author: Affiliation: Institute of Soil and Water Conservation,Chinese Academy of Sciences and Ministry of Water Resources,Yangling Shaanxi,Institute of Soil and Water Conservation,Chinese Academy of Sciences and Ministry of Water Resources,Yangling Shaanxi,Central South Forest Inventory and Planning Institute of State Forestry Administration,Changsha Hunan,Northwest Agricultural Forestry University,Yangling Shaanxi,,Institute of Soil and Water Conservation,Chinese Academy of Sciences and Ministry of Water Resources,Yangling Shaanxi,Northwest Agricultural Forestry University,Yangling Shaanxi Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:对黄土区典型草原进行封育+施肥(EF)、封育+火烧(EB)、封育(E)和放牧(G)处理,实地调查分析群落盖度、高度、密度、地上现存量和物种多样性,以研究不同干扰对黄土区典型草原群落物种多样性和生物量的影响.结果表明:在4种干扰类型中,施肥+封育草地群落盖度和地上生物量最高,且优势度指数最高,这与禾本科草占优势地位有关,群落均匀度指数和多样性指数最低,符合"生态位理论";放牧地群落高度、盖度、密度和地上现存量最低,群落丰富度指数和多样性指数最高,支持"中度干扰理论";封育地密度和均匀度指数最高;具体表现为:4种干扰类型地上生物量的变化趋势为封育+施肥＞封育+火烧＞封育＞放牧;说明长时间的封育对草地是一种严重干扰.群落丰富度指数(R和Ma)的排列顺序为放牧＞封育+施肥＞封育+火烧＞封育,群落物种多样性指数(H'和D)的排列顺序为放牧＞封育＞封育+火烧＞封育+施肥,优势度指数与多样性指数相反,群落均匀度指数(Jsw和Ea)的排列顺序为封育＞放牧＞封育+火烧＞封育+施肥.不同干扰样地群落生产力与Shannon-Wiener和Simpson多样性指数间呈负相关关系,这个结论可以用地上/地下竞争的相互作用来解释. Abstract:Typical steppe is a type of grassland which forms in inland temperate semi-arid climatic conditions, where xerophytic perennial bush grasses, especially Stipa spp., dominate. Grassland ecosystems are one of the largest terrestrial ecosystems affected by human activities. It is important to study the impact of different types of disturbance on the biodiversity and biomass of grasslands ecosystems during restoration and reconstruction work. Exclosures, grazing, fertilization and burning are four major types of anthropogenic disturbance occurring in grassland ecosystems, and have very important impacts on them. To provide a scientific basis for the protection of grassland biodiversity and the sustainable use of grasslands, the influences of different disturbances on the characteristics of above-ground vegetation were studied in a typical steppe in the loess region of China based on the field investigation and monitoring. We established plots representing four different types of treatments: exclosure (E), exclosure plus fertilization (EF), exclosure plus burning (EB) and grazing (G). All plots had the same soil type, topography and hydrological conditions. During the entire experiment, we determined total coverage, vegetation height, individual density, aboveground biomass and diversity of the plant community in each plot. Our results show the dominant vegetation community type of G plots is Agropyron cristatum+Potentilla acaulis+Artemisia sacrorum, a community which is the result of long-term grazing. The dominant vegetation community type of the E plots is Stipa grandis+Poa sphondylodes+Medicago ruthenica, a result of fencing. The dominant vegetation community type of the EF plots is Carex duriuscula+Stipa bungeana+Stipa grandis. The dominant vegetation community type of the EB plots is Artemisia sacrorum+Stipa bungeana+Stipa grandis. The different disturbance regimes strongly influenced community diversity and biomass. To be more specific, total coverage, above-ground biomass and the dominance indices were all at the highest level in the EF treatments in four types of treatments. This may attributed to grass species which play a dominant role in this community. Also, with low evenness and diversity indices, this result was consistent with niche theory which states differences among species in their environmental tolerances, niche requirements, and competitive abilities determine coexistence. Total coverage, height and aboveground biomass were all lowest for the G treatment, while community richness and diversity indices were higher for G than other three treatments. This result supports the intermediate disturbance hypothesis which states that biodiversity will be greatest in communities subjected to moderate levels of disturbance. Only the individual density and evenness index was higher with the E treatment than with the other treatments. Thus we can document the trend for biomass as EF > EB > E > G. These demonstrate long-term exclosure is a severe type of disturbance in grassland ecosystems. Also, the community richness indices (R and Ma) showed a certain tendency within these four treatments: G > EF > EB > E and community evenness indices (Jsw and Ea) could be sequenced in the order of E > G > EB > EF. Meanwhile, the order of diversity indices (H' and D) was as follows: G > E > EB > EF, while the dominance index was opposite the order of diversity index. Finally, there was negative correlation between community productivity and Shannon-Wiener and Simpson indices, which can be explained by interactions between root and shoot competition. 参考文献 相似文献 引证文献

Arctic Ecological Classifications Derived from Vegetation Community and Satellite Spectral Data

As a result of the warming observed at high latitudes, there is significant potential for the balance of ecosystem processes to change, i.e., the balance between carbon sequestration and respiration may be altered, giving rise to the release of soil carbon through elevated ecosystem respiration. Gross ecosystem productivity and ecosystem respiration vary in relation to the pattern of vegetation community type and associated biophysical traits (e.g., percent cover, biomass, chlorophyll concentration, etc.). In an arctic environment where vegetation is highly variable across the landscape, the use of high spatial resolution imagery can assist in discerning complex patterns of vegetation and biophysical variables. The research presented here examines the relationship between ecological and spectral variables in order to generate an ecologically meaningful vegetation classification from high spatial resolution remote sensing data. Our methodology integrates ordination and image classifications techniques for two non-overlapping Arctic sites across a 5° latitudinal gradient (approximately 70° to 75°N). Ordination techniques were applied to determine the arrangement of sample sites, in relation to environmental variables, followed by cluster analysis to create ecological classes. The derived classes were then used to classify high spatial resolution IKONOS multispectral data. The results demonstrate moderate levels of success. Classifications had overall accuracies between 69%–79% and Kappa values of 0.54–0.69. Vegetation classes were generally distinct at each site with the exception of sedge wetlands. Based on the results presented here, the combination of ecological and remote sensing techniques can produce classifications that have ecological meaning and are spectrally separable in an arctic environment. These classification schemes are critical for modeling ecosystem processes.

Patterns of vegetation greenness during flood, rain and dry resource states in a large, unconfined floodplain landscape

Floodplains are multi-state systems in which vegetation distribution is associated with the presence or absence of water as a resource. Less is known about the associations between the presence and absence of water and vegetation productivity. We examined patterns of vegetation productivity in a large (10 519 km2) unconfined floodplain during flood, rain and dry resource states. Mosaics of vegetation greenness were derived at two scales using the Normalized Difference Vegetation Index: a whole-of-landscape scale and a geomorphic unit scale with a riparian and floodplain unit. The NDVI was also calculated within a-priori vegetation community types within the floodplain. In all resource states over 50% of the floodplain showed no discernible vegetation greenness. When water is added as rain or flooding vegetation greenness increases, but the highest greenness occurs in the flood state. Trees situated in the riparian geomorphic unit maintain greenness during the dry resource state, whereas grasses situated in the floodplain contribute greenness during rain and flood resource states, with the highest greenness in the flood resource state. Aligned with views that dryland floodplains are boom-bust ecosystems, we suggest that flooding is a fundamental driver of vegetation productivity in this unconfined floodplain, contributing functional heterogeneity to the landscape.

Local climate determines the NDVI-based primary productivity and flooding creates heterogeneity in semi-arid floodplain ecosystem

Water is clearly the key driver of ecosystem functioning in arid and semi-arid floodplain environment. Both local rainfall and overbank flow contribute to water accessible by a plant. Variability in rainfall and hydrological regimes at seasonal and longer time scales exerts strong influences shaping ecosystem structure and function in arid and semi-arid floodplains. Yet there are few studies exploring how the interplay of climatic and hydrologic factors affects the integrity of floodplain ecosystems, especially the intermittently flooded vegetated wetlands. In fact, the importance of hydrological regimes prevailingly dominates the literature on floodplain ecology. Consequently, re-establishing and maintaining hydrological regimes has become the cornerstone underpinning most large scale floodplain conservation and restoration programs. In this study, we quantified the relative contribution of climatic and hydrologic variables to ecosystem functioning in the generalized additive modelling (GAM) framework using indicators derived from time series of MODIS 250m NDVI (Normalized Difference Vegetation Index). Results from the “best fitted” GAM models reveal that local rainfall has a closer and more important relationship with wetland mean NDVI (a surrogate of system primary productivity) although the co-variability between primary productivity and inflow is significantly positive. On the other hand, inflows play a dominant role in creating and maintaining the spatial heterogeneity represented by standard deviation of wetland NDVI while local rainfall has an opposite effect. Further, different vegetation community types exhibit distinct seasonality patterns in the NDVI-based primary productivity. These results illustrate the complexity of interactions between vegetation type, climate variations, and hydrology in floodplain wetlands. These results also demonstrate the sensitivity of floodplain wetlands to the perturbations in rainfall and temperature regimes, which would be more intense under the projected climate change.

High-resolution niche models via a correlative approach: Comparing and combining correlative and process-based information

Correlative and process-based approaches to describing the ecological niche in a spatially explicit fashion have often been compared in an adversarial framework. We sought to compare niche models developed via classic (correlative only), niche (process-based information), and hybridized (correlative augmented with process-based derived information) approaches, with the goal of determining if the added effort of process-based model development yielded better model fit. Correlative data layers (i.e., habitat models) included vegetation community types, Euclidean distance statistics, neighborhood analyses, and topographically-derived information. Mechanistic data layers were estimates of thermal suitability derived from field-collected datasets and biophysical calculations, and estimates of prey biomass interpolated from monitoring stations. We applied these models at high resolution (1m×1m pixel size) to habitat occupied by a population of Texas horned lizards (Phrynosoma cornutum) located in central Oklahoma. Results suggested that our treatment of process-based information offered dramatically better identification of suitable habitat when compared to correlative information, but that these results were likely due to low variability of niche variable pixel values. Niche layers nearly perfectly predicted lizard locations; the interpretation of these results suggest that lizards occupy habitat based on thermal suitability over the duration of a field season. Given the low variability observed in thermal suitability layers, we question the ecological reality of these predictions. Correlative models may accurately describe the niche at small spatial scales, and may suffice in situations where time and financial resources are limiting constraints on project goals. Process-based information continues to be an important part of the niche, and may offer additional predictive accuracy via correlative approaches when included in an ecologically meaningful context.

The Ants of Nantucket: Unexpectedly High Biodiversity in an Anthropogenic Landscape

This first comprehensive assessment of the ant fauna of Nantucket Island, MA revealed that 43% of New England ant species and 70% of New England ant genera occur on an island occupying only 0.07% of New England's land area. Ants collected by four different research groups between 2000 and 2009 included 32, 158 individual ants (2911 incidences) from 384 spatially and temporally distinct samples representing 14 different vegetation community types. The majority of the ant species were collected from anthropogenically derived and maintained sandplain grasslands, sandplain heathlands, and Scrub Oak shrublands. These three communities are state-ranked S1 community types; the lower state-ranked communities of beaches and sand dunes, bogs, salt marshes, and forest fragments had distinct ant assemblages with much lower species richness. The large number of samples described here, from a wide range of vegetation community types, expands the known list of Nantucket ant species more than three-fold and provides a baseline for future assessment of the effects of ongoing, long-term ecosystem management on Nantucket.

Spatial variation and prediction of forest biomass in a heterogeneous landscape

Large areas assessments of forest biomass distribution are a challenge in heterogeneous landscapes, where variations in tree growth and species composition occur over short distances. In this study, we use statistical and geospatial modeling on densely sampled forest biomass data to analyze the relative importance of ecological and physiographic variables as determinants of spatial variation of forest biomass in the environmentally heterogeneous region of the Big Sur, California. We estimated biomass in 280 forest plots (one plot per 2.85 km2) and measured an array of ecological (vegetation community type, distance to edge, amount of surrounding non-forest vegetation, soil properties, fire history) and physiographic drivers (elevation, potential soil moisture and solar radiation, proximity to the coast) of tree growth at each plot location. Our geostatistical analyses revealed that biomass distribution is spatially structured and autocorrelated up to 3.1 km. Regression tree (RT) models showed that both physiographic and ecological factors influenced biomass distribution. Across randomly selected sample densities (sample size 112 to 280), ecological effects of vegetation community type and distance to forest edge, and physiographic effects of elevation, potential soil moisture and solar radiation were the most consistent predictors of biomass. Topographic moisture index and potential solar radiation had a positive effect on biomass, indicating the importance of topographicallymediated energy and moisture on plant growth and biomass accumulation. RT model explained 35% of the variation in biomass and spatially autocorrelated variation were retained in regession residuals. Regression kriging model, developed from RT combined with kriging of regression residuals, was used to map biomass across the Big Sur. This study demonstrates how statistical and geospatial modeling can be used to discriminate the relative importance of physiographic and ecologic effects on forest biomass and develop spatial models to predict and map biomass distribution across a heterogeneous landscape.

Quantitative simulation on soil moisture contents of two typical vegetation communities in Sanjiang Plain, China

Different types of vegetation occupy different geomorphology and water gradient environments in the San- jiang Plain, indicating that the soil moisture dynamics and water balance patterns of the different vegetation communi- ties might differ from each other. In this paper, a lowland system, perpendicular to the Nongjiang River in the Honghe National Nature Reserve (HNNR), was selected as the study area. The area was occupied by the non-wetland plant forest and the typical wetland plant meadow. The Microsoft Windows-based finite element analysis software package for simulating water, heat, and solute transport in variably saturated porous media (HYDRUS), which can quantita- tively simulate water, heat, and/or solute movement in variably-saturated porous media, was used to simulate soil moisture dynamics in the root zone (20-40 cm) of those two plant communities during the growing season in 2005. The simulation results for soil moisture were in a good agreement with measured data, with the coefficient of determi- nation (R 2 ) of 0.44-0.69 and root mean square error (RMSE) ranging between 0.0291 cm 3 /cm 3 and 0.0457 cm 3 /cm 3 , and index of agreement (d) being from 0.612 to 0.968. During the study period, the volumetric soil moisture content of meadow increased with the depth and its coefficient of variation decreased with the depth (from 20 cm to 40 cm), while under the forest the soil moisture content at different depths varied irregularly. The calculated result of water budget showed that the water budget deficit of the meadow was higher than that of the forest, suggesting that the meadow is more likely to suffer from water stress than the forest. The quantitative simulation by HYDRUS in this study did not take surface runoff and plant growth processes into account. Improved root water uptake and surface

Variations in reflectance with seasonality and viewing geometry: implications for semi-arid vegetation mapping with MISR data

The purpose of this article is to understand the effect of multi-temporal multi-angle data on vegetation community type mapping in desert regions. Based on data from the multi-angle imaging spectroradiometer (MISR), a set of 46 multi-temporal classification experiments were carried out in the Jornada Experimental Range in New Mexico, USA. Besides multi-angle observations, bidirectional reflectance distribution function (BRDF) model parameters were also used as input data for the classifications. The experiments used two widely accepted BRDF models, the Rahman–Pinty–Verstraete (RPV) model and the Ross-thin Li-sparse reciprocal (RTnLS) model. The experiments show that multi-temporal multi-angle classifications can yield a more accurate mapping than multi-temporal nadir classifications, and multi-temporal BRDF model parameters combined with a single nadir image can provide an accuracy roughly the same as all multi-temporal multi-angle observations for the vegetation mapping. These findings opened not only a path of reducing data dimensionality for multi-temporal multi-angle classifications, but also a way of merging products of both MISR and moderate resolution imaging spectroradiometer (MODIS) to improve semi-arid vegetation mapping.

Environmental and landscape factors influencing ant and plant diversity in suburban riparian corridors

Urban riparian zones are highly valuable for a range of environmental, social and economic reasons. Despite their ecological complexity, legislative instruments underpinning riparian protection focus predominantly on minimum corridor widths required to fulfill environmental functions. This study sought to identify the dominant environmental variables that influence riparian corridor biodiversity in northern Sydney, Australia. Ant and plant assemblages were sampled from 18 riparian corridors of various widths. Environmental data pertaining to each corridor were collected using field and desktop surveys. Generalised Linear Modelling found perimeter:area ratio and the gradient of the slope perpendicular to the stream to predict significantly ant and plant richness. Plant richness was also influenced by vegetation community type and corridor width. When streamside vegetation communities were considered in isolation, many of the same factors were found to influence species richness. Likewise, Distance-based Linear Modelling identified vegetation community type and landscape connectivity as significant predictors of ant composition both in streamside habitats and those located across the full width of each riparian corridor sampled. While width was the best predictor of plant assemblage composition across the whole riparian corridor, streamside vegetation was influenced more significantly by soil pH. This result arose principally due to a dominance of exotic plants in alkaline soils. Although wider corridors were likely to encompass a greater variety of biotic assemblages, landscape and site scale environmental characteristics appeared to be of greater ecological significance. Environmental managers should therefore consider these factors and target weed invasion when seeking to enhance biodiversity in urban riparian corridors.

Timing Constraints on Remote Sensing of Wildland Fire Burned Area in the Southeastern US

Remote sensing using Landsat Thematic Mapper (TM) satellite imagery is increasingly used for mapping wildland fire burned area and burn severity, owing to its frequency of collection, relatively high resolution, and availability free of charge. However, rapid response of vegetation following fire and frequent cloud cover pose challenges to this approach in the southeastern US. We assessed these timing constraints by using a series of Landsat TM images to determine how rapidly the remotely sensed burn scar signature fades following prescribed burns in wet flatwoods and depression swamp community types in the Apalachicola National Forest, Florida, USA during 2006. We used both the Normalized Burn Ratio (NBR) of reflectance bands sensitive to vegetation and exposed soil cover, as well as the change in NBR from before to after fire (dNBR), to estimate burned area. We also determined the average and maximum amount of time following fire required to obtain a cloud-free image for burns in each month of the year, as well as the predicted effect of this time lag on percent accuracy of burn scar estimates. Using both NBR and dNBR, the detectable area decreased linearly 9% per month on average over the first four months following fire. Our findings suggest that the NBR and dNBR methods for monitoring burned area in common southeastern US vegetation community types are limited to an average of 78–90% accuracy among months of the year, with individual burns having values as low as 38%, if restricted to use of Landsat 5 TM imagery. However, the majority of burns can still be mapped at accuracies similar to those in other regions of the US, and access to additional sources of satellite imagery would improve overall accuracy.

LiDAR-Based Classification of Sagebrush Community Types

Abstract Sagebrush ( Artemisia spp.) communities constitute the largest temperate semidesert in North America and provide important rangelands for livestock and habitat for wildlife. Remote sensing methods might provide an efficient method to monitor sagebrush communities. This study used airborne LiDAR and field data to measure vegetation heights in five different community types at the Reynolds Creek Experimental Watershed, southwestern Idaho: herbaceous-dominated, low sagebrush ( Artemisia arbuscula ) –dominated, big sagebrush ( Artemisia tridentata spp.) –dominated, bitterbrush ( Purshia tridentata ) -dominated, and other vegetation community types. The objectives were 1) to quantify the correlation between field-measured and airborne LiDAR-derived shrub heights, and 2) to determine if airborne LiDAR-derived mean vegetation heights can be used to classify the five community types. The dominant vegetation type and vegetation heights were measured in 3 × 3 m field plots. The LiDAR point cloud data were converted into a raster format to generate a maximum vegetation height map in 3-m raster cells. The regression relationship between field-based and airborne LiDAR-derived shrub heights was significant ( R 2 =0.77; P value P values

Experimental wet heath translocation in Dorset, England

Heathland has become fragmented throughout its European range with many countries losing 60–90% of their heathland area during the 20th century. A small, isolated area of wet heathland within permitted ball clay workings in Dorset (England) was translocated in October 1993 to an engineered receptor cell fed by groundwater and direct precipitation in order to mitigate the otherwise total loss of the wet heath. The aims were to rescue the wet heathland and to re-establish a community type similar to the wet heath that originally occurred at the donor site prior to the recent development of vegetation communities and birch colonisation associated with drier conditions. Vegetation monitoring over 12 years up to 2005 indicated that the experimental translocation successfully fulfilled the aims for a period of 7 years when the hydrological regime of the receptor site was actively managed. There was development of a mosaic of wet heath and mire vegetation community types including Sphagnum lawns and open bog pools. However, when active management ceased, the receptor site became drier and species were lost. Multivariate analysis revealed a trajectory of progressive rapid chronological change during 1994 and 1995 followed by a period of relative stability between 1996 and 2000 which coincided with greater species density. Subsequently up to 2005, the plant community became less species-rich and the plant community reverted to a species structure similar to that which occurred in 1994/1995. The importance of hydrological regime for plant community structure was tested using fixed-quadrat data and the water level measurements made in the period 1995–1998. Canonical Correspondence Analysis (CCA) multivariate analysis revealed a hydrological gradient with a significant seasonal effect of water table depth in the first half of the year and close association of the least wet quadrat location and non-mire species. Overall, the results support the use of translocation as a means of rescuing wet heath habitat which would otherwise be lost due to change in land use. There is a risk of failure when translocating a complex ecosystem such as wet heath but ecological engineering provides an insight into defining the risk. Our results demonstrated that an ecologically acceptable outcome for a wet heath translocation can be achieved with careful design and implementation and sensitive management of the receptor site. However, it is essential to secure long-term hydrological and vegetation management in order to provide a sustainable outcome for long-term survival of a target wet heath community.

Factors influencing the distribution of Azorean mountain vegetation: implications for nature conservation

In order to understand the main ecological factors that influence the distribution of mountain vegetation in Azores and to use it as a model for nature conservation, a study on Santa Barbara Mountain on Terceira Island was performed. A multivariate analysis was done on vegetation data and the abiotic factors governing the vegetation pattern are discussed. The major factors contributing to the observed vegetation patterns are wind exposure, soil water saturation and historical human impacts. The vegetation analysis showed that Azorean Mountain habitats have a high variation of vegetation structure as a result of the habitat heterogeneity and the extreme ecological conditions. Using the co-dominant plants as indicator species, eco-zones are distinguished, characterized by the combination of different ecological–human factors which contribute to the distribution of specific types of natural vegetation communities. The studies of vegetation distribution give important information about the relation between vegetation and landscape that is essential for conservation, restoration proposals and landscape planning. Azores terrestrial Natura 2000 sites are largely dominated by mountain vegetation, therefore this work provides essential background data for the management plans of these sites.

Remote Sensing and GIS as an Advance Space Technologies for Rare Vegetation Monitoring in Gobustan State National Park, Azerbaijan

This paper describes remote sensing methodologies for monitoring rare vegetation with special emphasis on the Image Statistic Analysis for set of training samples and classification. At first 5 types of Rare Vegetation communities were defined and the Initial classification scheme was designed on that base. After preliminary Statistic Analysis for training samples, a modification algorithm of the classification scheme was defined: one led us to creating a 4 class’s scheme (Final classification scheme). The different methods analysis such as signature statistics, signature separability and scatter plots are used. According to the results, the average separability (Transformed Divergence) is 1951.14, minimum is 1732.44 and maximum is 2000 which shows an acceptable level of accuracy. Contingency Matrix computed on the results of the training on Final classi- fication scheme achieves better results, in terms of overall accuracy, than the training on Initial classification scheme.

Soil oribatid mite in four typical vegetation communities of Misiones forest in the Iguazú area, Argentina

The objective of this work was to assess the soil oribatid mite communities in four sites of the Upper Paraná Bosque Atlántico, in the Iguazú National Park, Argentina and in surrounding areas: bamboo forest, palm forest and two mixed forests. A comparison between each pair of sites, based on the presence-absence of oribatid species, was performed using Jaccard's index. This is the first systematic sampling of oribatid mites in this area. A total of 56 genera and 96 oribatid species were found, 25 and 49 of them, respectively, are new citation for Argentina. The highest similarity was found between mixed forests. Almost 68% and 34% of the genera were cited for similar biotopes in Brazil and Paraguay, respectively.

An empirical study on the utility of BRDF model parameters and topographic parameters for mapping vegetation in a semi‐arid region with MISR imagery

In this study we show that multiangle remote sensing is useful for increasing the accuracy of vegetation community type mapping in desert regions. Using images from the National Aeronautics and Space Administration (NASA) Multiangle Imaging Spectroradiometer (MISR), we compared roles played by Bidirectional Reflectance Distribution Function (BRDF) model parameters with those played by topographic parameters in improving vegetation community type classifications for the Jornada Experimental Range and the Sevilleta National Wildlife Refuge in New Mexico, USA. The BRDF models used were the Rahman–Pinty–Verstraete (RPV) model and the RossThin‐LiSparseReciprocal (RTnLS) model. MISR nadir multispectral reflectance was considered as baseline because nadir observation is the most basic remote sensing observation. The BRDF model parameters and the topographic parameters were considered as additional data. The BRDF model parameters were obtained by inversion of the RPV model and the RTnLS model against the MISR multiangle reflectance data. The results of 32 classification experiments show that the BRDF model parameters are useful for vegetation mapping; they can be used to raise classification accuracies by providing information that is not available in the spectral‐nadir domain, or from ancillary topographic parameters. This study suggests that the Moderate Resolution Imaging Spectroradiometer (MODIS) and MISR BRDF model parameter data products have great potential to be used as additional information for vegetation mapping.

Vegetation structure and heavy metal uptake by plants in the mining-impacted and non mining-impacted sites of Southern Lake Victoria Wetlands

This study assessed the plant species composition and the heavy metal uptake by plants in the mining-impacted and non mining-impacted areas of the southern Lake Victoria basin. The vegetation of the wetlands was stratified into riverine forest, riverine thickets, swampy grassland, open woodland and floodplain grassland. Plant diversity at Nyamtukuza ranged between 2.34 to 2.70; at Geita was 2.29 to 2.57 and Mwakitolyo was between 1.08 to 1.70, which was significantly lower than the other two sites; whereas variation in plant species richness was not significant. TWINSPAN classification resulted into four clusters of the vegetation communities. Cluster A, a shrubby community with Combretum molle, Bersama abyssinica, Acalypha ornata and Acacia brevispica indicated previous cutting of woody species from the area. Cluster B was a severely disturbed community with Bidens pilosa and Anthocleista grandiflora as early successors. Cluster C was a community with moderate disturbance levels and cluster D was of wetland vegetation community types with indicator species such as Pistia stratiotes and Corchorus aestuans that are characteristic permanent wetland species. CCA ordination showed a significant positive correlation of the soil mineral elements to those in plants at axis 1. The influence of soil minerals on plant species distribution pattern was not significant at axis 1. Tanzania Journal of Science Vol. 32 (2) 2006: pp. 39-50

Vegetation communities in continental boreal wetlands along a salinity gradient: Implications for oil sands mining reclamation

Oil sands mining is a major disturbance to boreal landscapes in north-eastern Alberta, Canada. Freshwater peatlands dominate the landscape prior to mining, but the post-mining reclamation landscape will have wetlands that span a salinity gradient. Little is known about the native vegetation communities in subsaline and saline marshes in the boreal region, yet these communities offer the best potential for reclamation of wetlands after oil sands mining. The overall intent of this study is to provide information on natural wetland communities along a gradient of salinities that can be used to enhance oil sands wetland reclamation. Our specific study objectives were to: (1) characterize environmental conditions of industrial and natural wetlands, (2) characterize vegetation communities (composition and diversity) in these wetlands, (3) and explore how vegetation communities (composition and diversity) may be influenced by environmental conditions. We surveyed vegetation communities and environmental variables in 25 natural boreal wetlands along a salinity gradient and in 10 industrial marshes in the oil sands mining region. We observed an electrical conductivity (EC) range of 0.5–28 mS cm −1 in the wetlands, indicating that salinity similar to or higher than anticipated for oil sands reclamation is naturally present in some boreal wetlands. We observed low species richness in both industrial and natural wetlands. There were 101 plant species observed in all the wetlands, with 82 species recorded in the natural wetlands and 44 species in industrial wetlands. At the plot level, richness decreased with increasing EC and pH, but increased with soil organic matter. Using Cluster Analysis and indicator species analysis we defined 16 distinct vegetation community types, each dominated by one or two species of graminoid vegetation. In general these communities resembled those of boreal or prairie marshes. Electrical conductivity, pH, and water depth were important factors correlating with community composition of the wetlands, however peat depth and soil organic content did not differ among community types. Not all community types were present in industrial wetlands, indicating that these communities may need to be planted to enhance overall diversity in future reclaimed oil sands wetlands.

Comparative diet selection by cattle and sheep grazing two contrasting heathland communities

In the UK the funding mechanism for moorland restoration is being implemented primarily through agri-environment schemes, yet to date remarkably few comparative grazing studies with domesticated livestock have been conducted on this type of vegetation community. In this experiment the diet composition of four groups of animals grazing heathland swards with low (8%) and high (61%) percentages of cover of Calluna vulgaris was estimated from faeces profiles of n-alkanes and long-chain fatty alcohols. Two breeds of sheep (Welsh Mountain (WM) and Scottish Blackface (SBF)), and two breeds of cattle (Welsh Black (WB) and Continental cross (CX)) grazed the experimental sites during two separate 14-day sampling sessions, in July and September respectively. Both species were selective feeders, consuming grasses (selectivity indices 0.20–1.0) in preference to dwarf shrubs (selectivity indices 0.20–1.0), but there were significant differences in the proportions of various plant groups within the diets. Although the sheep diets contained significantly more C. vulgaris, the quantities consumed were small (<10% of the diet), even on the High site, reflecting the biomass of the graminoid species present, and hence availability of preferred items. The SBF sheep were the only animal type to increase consumption of C. vulgaris later in the season. There were a number of significant differences in the composition of the diets selected by the two hill breeds of sheep used in the study, with the SBF sheep recorded as consuming more C. vulgaris. These results imply that through choice of breed land managers may be able to meet environmental goals more effectively without compromising returns from conventional production systems. In contrast, the overall diet composition of the two breed types of cattle was similar. This indicates that commercial breeds have the potential to deliver the types of environmental benefits associated with grazing of traditional breeds.