Impacts of atmospheric pollution on the plant communities of British acid grasslands

Air pollutants are recognised as important agents of ecosystem change but few studies consider the effects of multiple pollutants and their interactions. Here we use ordination, constrained cluster analysis and indicator value analyses to identify potential environmental controls on species composition, ecological groupings and indicator species in a gradient study of UK acid grasslands. The community composition of these grasslands is related to climate, grazing, ozone exposure and nitrogen deposition, with evidence for an interaction between the ecological impacts of base cation and nitrogen deposition. Ozone is a key agent in species compositional change but is not associated with a reduction in species richness or diversity indices, showing the subtly different drivers on these two aspects of ecosystem degradation. Our results demonstrate the effects of multiple interacting pollutants, which may collectively have a greater impact than any individual agent.     

Habitat classification: A comparison using avian species and guilds

Results of breeding bird censuses in 1979 and 1980 were used to compare the relationships of both species and guilds to forest habitats in the White Mountains of New Hampshire. Several age classes of 11 forest cover types were studied: northern hard-woods (Fagus-Betula-Acer), spruce (Picea), spruce-fir (Picea-Abies), birth (Betula), swamp hardwoods (Acer-Pinus-Tsuga), pine (Pinus strobus andP. resinosa), balsam fir (Abies), aspen (Populus tremuloides andP. grandidentata), northern red oak (Quercus), oak-pine (Quercus-Pinus), and hemlock (Tsuga). All types were even-aged; only northern hardwoods had an additional uneven-aged condition. Forest cover types were also pooled to consider generalized habitats: hardwoods, mixed forest, or softwoods. Results of ordinations based on censuses of 74 bird species indicate that foraging guilds are more related to general cover types than are nesting substrate guilds, but bird species reflect habitat differences to a greater degree than do either guild scheme. Also, considerable overlap occurs in bird species distribution between hardwoods and mixed forests; softwoods show little overlap with other types. Discriminant function and classification analyses revealed that bird species composition can be used to correctly classify general forest habitats more accurately (83.8%) than either foraging (63.2%) or nesting substrate guilds (58.4%). These results indicate that, of the habitats studied, avian species compositions are more characteristic than are foraging or nesting substrate guild composition, which tend to be similar across forest habitats.     

Regional Representativeness of Swedish Reference Lakes

/ Recent focus has been placed on ecoregion delineations for providing an appropriate framework for monitoring and assessment of region-specific attainable water/habitat quality. Using an ecoregion approach to stratify variance, this study was conducted to determine whether earlier (subjectively) selected Swedish reference lakes may be considered as regionally representative reference sites when compared with a randomly selected lake population. Predictive modeling by discriminant function analysis with lakes classified by ecoregion and lake surface area and six physicochemical variables showed that the greater majority of reference lakes may be considered as regionally representative. The highest proportion of lake "misclassifications" occurred in the boreonemoral ecoregion, a relatively diverse ecoregion of southern Sweden. This apparent bias may be in part be due to the criteria used in selecting regional reference lakes. In the earlier selection of reference lakes emphasis was placed on lakes not being adversely affected by land usage or pollutant discharges, consequently forest lakes were often overrepresented and sites in agricultural areas underrepresented in the selected reference sites. As a complement to predictive modeling, PCA ordination showed the placement of reference lakes within the random lake population and indicated where reference sites might be missing along potentially important ecological gradients. KEY WORDS: Regionalization; Ecoregion; Representativeness; Reference; Ordination; Modeling; Temperate lakes     

关帝山八水沟天然植物群落时空梯度的数量分析

在ＤＣＡ排序的基础上，应用排序轴分类法对山西关帝山八水沟景观的天然植物群落进行了数量分类，共划分出７类，效果较好．多元线性回归结果表明ＤＣＡ排序轴与环境因子密切相关．方差分析与多重比较结果表明，结合ＤＣＡ第２与３排序轴的二维排序图反映了群落的时空变异，其中第２排序轴反映了群落在坡向与坡度方面的空间梯度，第３排序轴反映了群落的森林演替、灌丛发育以及各类群落的草本层发育的时间梯度     

Large-Scale Effects of Timber Harvesting on Stream Systems in the Ouachita Mountains, Arkansas, USA

Using Basin Area Stream Survey (BASS) data from the United States Forest Service, we evaluated how timber harvesting influenced patterns of variation in physical stream features and regional fish and macroinvertebrate assemblages. Data were collected for three years (1990–1992) from six hydrologically variable streams in the Ouachita Mountains, Arkansas, USA that were paired by management regime within three drainage basins. Specifically, we used multivariate techniques to partition variability in assemblage structure (taxonomic and trophic) that could be explained by timber harvesting, drainage basin differences, year-to-year variability, and their shared variance components. Most of the variation in fish assemblages was explained by drainage basin differences, and both basin and year-of-sampling influenced macroinvertebrate assemblages. All three factors modeled, including interactions between drainage basins and timber harvesting, influenced variability in physical stream features. Interactions between timber harvesting and drainage basins indicated that differences in physical stream features were important in determining the effects of logging within a basin. The lack of a logging effect on the biota contradicts predictions for these small, hydrologically variable streams. We believe this pattern is related to the large scale of this study and the high levels of natural variability in the streams. Alternatively, there may be time-specific effects we were unable to detect with our sampling design and analyses.     

Phytosociological inference and resource management

The application of vegetation information to resource management problems is reviewed in four areas: (1) the stratification of vegetation data by classification and gradient analysis, (2) the storage and retrieval of these data, (3) the sources of vegetation information, and (4) the accuracy and resolution requirements posed by different management applications. Conclusions indicate that the successful application of inference methods to resource management problems requires an appropriate integration of these four components.     

Assessing representativeness of places for conservation reservation and heritage listing

Problems arising from application of the representative criterion for conservation and natural heritage evaluation are discussed. An ecological basis to this criterion is suggested that focuses on those key environmental factors dominating biotic response. A methodology is proposed that utilizes computer-based methods of establishing and interrogating spatial data bases (geographic information systems), environmental modeling, and numeric analysis. An example is presented illustrating some of the advantages and limitations of classification and dimension reduction techniques in both defining bioenvironments and displaying their spatial distribution. The advantages of this method for representativeness evaluation are that it maximizes the utility of available data, is explicit and repeatable, and enables large areas to be analyzed at relatively fine scales.     

Metal accumulation in mosses across national boundaries: uncovering and ranking causes of spatial variation

This study aimed at cross-border mapping metal loads in mosses in eight European countries in 1990, 1995, and 2000 and at investigating confounding factors. Geostatistics was used for mapping, indicating high local variances but clear spatial autocorrelations. Inference statistics identified differences of metal concentrations in mosses on both sides of the national borders. However, geostatistical analyses did not ascertain discontinuities of metal concentrations in mosses at national borders due to sample analysis in different laboratories applying a range of analytical techniques. Applying Classification and Regression Trees (CART) to the German moss data as an example, the local variation in metal concentrations in mosses were proved to depend mostly on different moss species, potential local emission sources, canopy drip and precipitation.     

An evaluation of the vegetation developed after artificially stabilizing South African coastal dunes with indigenous species

A total of 17 sites along the eastern Cape coastline, which had been established with indigenous species, were sampled to assess species composition and abundance. The areas sampled ranged from small blowout dunes of 1 ha, to extensive transverse dune fields of 134 ha; age at the time of sampling ranged from 2 to 20 yr. The total mean percentage cover and density, alpha diversity and importance values of all the species were calculated and used to describe each site. A TWINSPAN analysis grouped sites of similar localities, mainly on the basis of their species composition. A DECORANA plot revealed that axis 1 corresponded to the position of sites along the coastline rather than other factors, such as age. The variability in species composition was related more to the types of species used for stabilization, rather than the natural distribution of the indigenous dune vegetation. The species ordination showed a similar gradient, and it was possible from this analysis to determine which species were more commonly used and better suited for dune stabilization. It is concluded that successful stabilization can be achieved using indigenous species.     

Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters

Two artificial neural networks (ANNs), unsupervised and supervised learning algorithms, were applied to suggest practical approaches for the analysis of ecological data. Four major aquatic insect orders (Ephemeroptera, Plecoptera, Trichoptera, and Coleoptera, i.e. EPTC), and four environmental variables (elevation, stream order, distance from the source, and water temperature) were used to implement the models. The data were collected and measured at 155 sampling sites on streams of the Adour–Garonne drainage basin (South-western France). The modelling procedure was carried out following two steps. First, a self-organizing map (SOM), an unsupervised ANN, was applied to classify sampling sites using EPTC richness. Second, a backpropagation algorithm (BP), a supervised ANN, was applied to predict EPTC richness using a set of four environmental variables. The trained SOM classified sampling sites according to a gradient of EPTC richness, and the groups obtained corresponded to geographic regions of the drainage basin and characteristics of their environmental variables. The SOM showed its convenience to analyze relationships among sampling sites, biological attributes, and environmental variables. After accounting for the relationships in data sets, the BP used to predict the EPTC richness with a set of four environmental variables showed a high accuracy (r=0.91 and r=0.61 for training and test data sets respectively). The prediction of EPTC richness is thus a valuable tool to assess disturbances in given areas: by knowing what the EPTC richness should be, we can determine the degree to which disturbances have altered it. The results suggested that methodologies successively using two different neural networks are helpful to understand ecological data through ordination first, and then to predict target variables.