Recovery of the Benthic Macroinvertebrate Community in a Small Stream After Long-Term Discharges of Fly Ash

Recovery of the benthic macroinvertebrate community in a small east Tennessee stream impacted by fly ash discharges from a power plant was investigated over a period of 6.5 years. The rate of recovery was greatest in the first 2 years after an initial 75% reduction in coal use led to a similar reduction in ash discharges and associated contaminants; further recovery followed after all fly ash discharges ceased. Recovery of the stream progressed through two phases. In the first phase, which lasted for approximately the first 2 years, most density and richness metrics increased considerably. In the second phase of recovery, the increases in metric values were followed by declines before fluctuating in and out of the lower reference ranges for the metrics. Detrended correspondence analyses and indicator species analyses showed that changes in species composition and community structure were ongoing throughout the second phase. Thus, the first phase was characterized by species additions, while the second phase involved species replacements and shifts in community dominants. Further recovery of the macroinvertebrate community will probably depend on additional flushing of fly ash deposits from the streambed and flood plain, because their continued presence reduces habitat quality in the stream and serves as a potential source of contaminants. Further recovery also may be limited by the availability of vagile species in nearby watersheds.     

Development of synthetic criteria for the ecological evaluation of woodlots and woodlot units

Different criteria have been proposed for the rapid ecological evaluation of wooded areas. It is difficult, however, to determine the criteria most likely to yield results similar to those that would be obtained through detailed surveys and exhaustive evaluation. In order to identify such synthetic criteria, data from a detailed evaluation of Montreal Urban Community woodlots were studied with the help of multivariate analysis. This detailed evaluation was undertaken at two levels—woodlot unit and the woodlots themselves—using 16 different criteria.At the woodlot unit level, area and abundance indices of shade intolerant species in the tree layer could be used as synthetic criteria, while at the woodlot level the ecological value of the constituent units stand out as the first synthetic criterion. These results are compared with criteria proposed in the literature, and the use of multivariate analysis in ecological evaluation is briefly discussed.     

Molecular diversity of arbuscular mycorrhizal fungi in relation to soil chemical properties and heavy metal contamination

Abundance and diversity of arbuscular mycorrhizal fungi (AMF) associated with dominant plant species were studied along a transect from highly lead (Pb) and zinc (Zn) polluted to non-polluted soil at the Anguran open pit mine in Iran. Using an established primer set for AMF in the internal transcribed spacer (ITS) region of rDNA, nine different AMF sequence types were distinguished after phylogenetic analyses, showing remarkable differences in their distribution patterns along the transect. With decreasing Pb and Zn concentration, the number of AMF sequence types increased, however one sequence type was only found in the highly contaminated area. Multivariate statistical analysis revealed that further factors than HM soil concentration affect the AMF community at contaminated sites. Specifically, the soils’ calcium carbonate equivalent and available P proved to be of importance, which illustrates that field studies on AMF distribution should also consider important environmental factors and their possible interactions.     

Protection strategies for drinking groundwater sources in small Quebec municipalities

Awareness of groundwater protection has increased substantially in recent decades. In the Province of Quebec, Canada, the Groundwater Catchment Regulation (GWCR) was promulgated in 2002 to protect water quality in public wells. The goal of the present study was to document groundwater protection in the context of emerging regulations and identify factors explaining the propensity of municipalities applying protection strategies. Two types of information were used in this study: data from a questionnaire-based survey conducted among 665 municipalities in the Province of Quebec and complementary information gathered from various sources. Data from the survey revealed that fewer than half of the municipalities have been able to comply with the GWCR, mainly because of financial limitations. Also, close to half of the municipalities have either identified or are expecting land use conflicts to arise between protection areas required by the GWCR and other land usage, with agriculture being the main conflicting activity. Multivariate logistic regression models served to identify factors explaining the likelihood of municipalities to take groundwater protection measures. Those factors were municipality revenue, history of water contamination in distribution systems, land use near wellheads, location of municipalities within a provincial priority watershed and the importance of groundwater use in a region. Results of the study may prove helpful for government authorities in better understanding the groundwater protection issue and in implementing strategies that improve the ability of municipalities to protect groundwater.     

Designing environmental monitoring networks to measure extremes

This paper discusses challenges arising in the design of networks for monitoring extreme values over the domain of a random environmental space-time field {X _ij } i = 1, . . . , I denoting site and j = 1, . . . denoting time (e.g. hour). The field of extremes for time span r over site domain i = 1, . . . ,I is given by \(\{Y_{i(r+1)}=\max_{j=k}^{k+n-1} X_{ij}\}\) for k = 1 + rn, r = 0, . . . ,. Such networks must not only measure extremes at the monitored sites but also enable their prediction at the non-monitored ones. Designing such a network poses special challenges that do not seem to have been generally recognized. One of these problems is the loss of spatial dependence between site responses in going from the environmental process to the field of extremes it generates. In particular we show empirically that the intersite covariance Cov(Y _i(r+1),Y _i′(r+1)) can generally decline toward zero as r increases, for site pairs i ≠ i′. Thus the measured extreme values may not predict the unmeasured ones very precisely. Consequently high levels of pollution exposure of a sensitive group (e.g. school children) located between monitored sites may be overlooked. This potential deficiency raises concerns about the adequacy of air pollution monitoring networks whose primary role is the detection of noncompliance with air quality standards based on extremes designed to protect human health. The need to monitor for noncompliance and thereby protect human health, points to other issues. How well do networks designed to monitor the field monitor their fields of extremes? What criterion should be used to select prospective monitoring sites when setting up or adding to a network? As the paper demonstrates by assessing an existing network, the answer to the first question is not well, at least in the case considered. To the second, the paper suggests a variety of plausible answers but shows through a simulation study, that they can lead to different optimum designs. The paper offers an approach that circumvents the dilemma posed by the answer to the second question. That approach models the field of extremes (suitably transformed) by a multivariate Gaussian-Inverse Wishart hierarchical Bayesian distribution. The adequacy of this model is empirically assessed in an application by finding the relative coverage frequency of the predictive credibility ellipsoid implied by its posterior distribution. The favorable results obtained suggest this posterior adequately describes that (transformed) field. Hence it can form the basis for designing an appropriate network. Its use is demonstrated by a hypothetical extension of an existing monitoring network. That foundation in turn enables a network to be designed of sufficient density (relative to cost) to serve its regulatory purpose.     

Identifying crash type propensity using real-time traffic data on freeways

Introduction: We examine the effects of various traffic parameters on type of road crash. Method: Multivariate probit models are specified on 4-years of data from the A4-A86 highway section in the Ile-de-France region, France. Results: Empirical findings indicate that crash type can almost exclusively be defined by the prevailing traffic conditions shortly before its occurrence. Rear-end crashes involving two vehicles were found to be more probable for relatively low values of both speed and density, rear-end crashes involving more than two vehicles appear to be more probable under congested conditions, while single-vehicle crashes appear to be largely geometry-dependent. Impact on Industry: Results could be integrated in a real-time traffic management application.     

Follow-up trends of parasite community alteration in a marine fish after the Prestige oil-spill: shifting baselines?

This study evaluates the follow-up trends in the composition and structure of the parasite communities in the marine sparid Boops boops after the Prestige oil-spill. A total of 400 fish comprising 11 seasonal samples was analyzed from three impacted localities on the Atlantic coast of Spain. A large number of parasite species was recovered only after the spill thus suggesting a substantial alteration of the marine food webs. Post-spill communities exhibited higher richness and abundance due to the significant changes in the abundance of the common species, the latter indicating accelerated parasite transmission rates. Multivariate analyses at two nested scales detected a directional trend in parasite community succession towards the pre-spill situation, however, with no full support for community recovery. The state of parasite communities in 2005-2006 may provide the new baseline data which can serve as a framework for quantifying the impact of potential future spills in the region.     

Organochlorine pesticides in soils around Guanting Reservoir,China

Fifty-six representative samples of topsoil were collected around Guanting Reservoir, which is an important water source for Beijing. Concentrations of the insecticides HCH, DDT, and their metabolites were quantified by use of gas chromatography (GC) with electron capture detection (ECD). Organochlorine pesticides (OCPs) are still present in surface soils in the Guanting area. DDT accounts for about 93% of the total OCP content. Concentrations of α/γ, β/γ, and DDT/DDE are the result not only of historical use, but also of more recent depositions. Statistical analyses, including principal component analysis (PCA) and cluster analysis (CA), revealed associations between concentrations of OCPs and major soil characteristics. Geographical information system (GIS) technology was used to develop maps of the distributions of OCP concentrations. The areas of greatest contamination were primarily in the central part of the study area and were correlated with greater population density, heavier traffic, and more industrial activity.     

多元线性回归与灰色联合模型在湖泊水质预测中的应用

根据对湖泊水体中所含高锰酸盐指数、氨氮、总磷等主要化学指标及其相关因素人口、工业产值和污水排放量的数据,采用了多元线性回归方法建立了湖泊水质预测的数学模型。并用多元线性回归和灰色模型联合的方法进行实际预测,多元线性回归模型通过F检验认为回归方程的效果比较显著,灰色模型精度检验达到二级,收到了良好效果。     

Comparative performance of generalized additive models and multivariate adaptive regression splines for statistical modelling of species distributions

Two statistical modelling techniques, generalized additive models (GAM) and multivariate adaptive regression splines (MARS), were used to analyse relationships between the distributions of 15 freshwater fish species and their environment. GAM and MARS models were fitted individually for each species, and a MARS multiresponse model was fitted in which the distributions of all species were analysed simultaneously. Model performance was evaluated using changes in deviance in the fitted models and the area under the receiver operating characteristic curve (ROC), calculated using a bootstrap assessment procedure that simulates predictive performance for independent data. Results indicate little difference between the performance of GAM and MARS models, even when MARS models included interaction terms between predictor variables. Results from MARS models are much more easily incorporated into other analyses than those from GAM models. The strong performance of a MARS multiresponse model, particularly for species of low prevalence, suggests that it may have distinct advantages for the analysis of large datasets. Its identification of a parsimonious set of environmental correlates of community composition, coupled with its ability to robustly model species distributions in relation to those variables, can be seen as converging strongly with the purposes of traditional ordination techniques.