Introduced and cryptogenic species in Port Phillip Bay, Victoria, Australia

Port Phillip Bay (PPB) is a large (1,930 km²), temperate embayment in southern Victoria, Australia. Extensive bay-wide surveys of PPB have occurred since 1840. In 1995/1996 the Commonwealth Scientific and Industrial Research Organization (CSIRO) Centre for Research on Introduced Marine Pests (CRIMP) undertook an intensive evaluation of the region with the aims of developing a comprehensive species list of native and introduced biota and contrasting previous bay-wide assessments with a current field survey in order to detect new incursions and discern alterations to native communities. Two methods were used to meet these aims: a re-evaluation of regional museum collections and published research in PPB to identify and determine the timing of introductions; and field surveys for benthic (infauna, epifauna and encrusting) organisms between September 1995 to March 1996. One hundred and sixty introduced (99) and cryptogenic (61) species were identified representing over 13% of the recorded species of PPB. As expected, the majority of these are concentrated around the shipping ports of Geelong and Melbourne. Invasions within PPB appear to be increasing, possibly due to an increase in modern shipping traffic and an increase in aquaculture (historically associated with incidental introductions); however the records of extensive biological surveys suggest that this may, in part, be an artefact of sampling effort. In contrast to Northern Hemisphere studies, PPB (and Southern Hemisphere introductions in general) have significantly different suites of successfully invading taxa. PPB is presented as one of the most invaded marine ecosystems in the Southern Hemisphere.Communicated by M.S. Johnson, Crawley     

A comparison of different lysis buffers to assess allele dropout from single cells for preimplantation genetic diagnosis

Single cell polymerase chain reaction (PCR) for preimplantation genetic diagnosis (PGD) requires high efficiency and accuracy. Allele dropout (ADO), the random amplification failure of one of the two parental alleles, remains the most significant problem in PCR-based PGD testing since it can result in serious misdiagnosis for compound heterozygous or autosomal dominant conditions. A number of different strategies (including the use of lysis buffers to break down the cell and make the DNA accessible) have been employed to combat ADO with varying degrees of success, yet there is still no consensus among PGD centres over which lysis buffer should be used (ESHRE PGD Consortium, 1999 ). To address this issue, PCR amplification of three genes (CFTR, LAMA3 and PKP1) at different chromosomal loci was investigated. Single lymphocytes from individuals heterozygous for mutations within each of the three genes were collected and lysed in either alkaline lysis buffer (ALB) or proteinase K/SDS lysis buffer (PK). PCR amplification efficiencies were comparable between alkaline lysis and proteinase K lysis for PCR products spanning each of the three mutated loci (ΔF508 in CFTR 90% vs 88%; R650X in LAMA3 82% vs 78%; and Y71X in PKP1 91% vs 87%). While there was no appreciable difference between ADO rates between the two lysis buffers for the LAMA3 PCR product (25% vs 26%), there were significant differences in ADO rates between ALB and PK for the CFTR PCR product (0% vs 23%) and the PKP1 PCR product (8% vs 56%). Based on these results, we are currently using ALB in preference to PK/SDS buffer for the lysis of cells in clinical PGD. Copyright © 2001 John Wiley & Sons, Ltd.     

Analysing the sensitivity behaviour of two hydrology models

Recently, the New Morris Method has been presented as an effective sensitivity analysis tool for mathematical models. The New Morris Method estimates the sensitivity of an output parameter to a given set of input parameters (first-order effects) and the extent these parameters interact with each other (second-order effects). This method requires the specification of two parameters (runs and resolution) that control the sampling of the output parameter to determine its sensitivity to various inputs. The criteria for these parameters have been set on the analysis of a well-behaved analytical function (see Cropp and Braddock, Reliab. Eng. Syst. Saf. 78:77–83, 2002), which may not be applicable to other physical models that describe complex processes. This paper will investigate the appropriateness of the criteria from (Cropp and Braddock, 2002) and hence the effectiveness of the New Morris Method to determine the sensitivity behaviour of two hydrologic models: the Soil Erosion and Deposition System and Griffith University Representation of Urban Hydrology. In the first case, this paper will separately analyse the sensitivity of an output parameter on a set of input parameters (first- and second-order effects) for each model and discuss the physical meaning of these sensitivities. This will be followed by an investigation into the sampling criteria by exploring the convergence of the sensitivity behaviour for each model as the sampling of the parameter space is increased. By comparing these trends to the convergence behaviour from Cropp and Braddock (2002), we will determine how well the New Morris Method estimates the sensitivity for each model and whether the sampling criteria are appropriate for these models. It will be shown that the New Morris Method can provide additional insight into the functioning of these models, and that, under a different metric, the sensitivity behaviour of these models does converge confirming the sampling criteria set by Cropp and Braddock.     

Dissolved and Total Copper in a Coal Ash Effluent and Receiving Stream: Assessment of In Situ Biological Effects

An in situ chemical and biological study was conducted in the lower Muskingum River (southeast Ohio, U.S.A.) to evaluate potential effects of copper (Cu) discharged from a coal ash effluent. Effluent total Cu, dissolved Cu, TSS and pH measurements were performed monthly during January-December 1995. Benthic macroinvertebrates were sampled at five river locations using artificial substrate samplers, and in situ Cu analyses were conducted. Effluent Cu (total) ranged from 8 to 142 microg L(-1) (mean = 58 microg L(-1)), but dissolved Cu never exceeded 78 microg L(-1) (mean = 20 microg L(-1)). The mean ratio of dissolved Cu to total Cu in these samples was 32%. Total Cu concentrations at the biological sampling sites adjacent to the effluent discharge were higher than levels at ambient sites, but dissolved Cu levels were similar among all sites. The macroinvertebrate community proximal to the coal ash effluent had the highest number of taxa and total number of individuals; a high number of mayfly and caddis fly taxa; and the highest Invertebrate Community Index score. The high water velocity of the discharge (which likely contained particulate organic matter) apparently created a favorable microhabitat that, combined with Cu-complexing constituents in the discharge, superceded potential adverse effects of high Cu levels. This study emphasizes the importance of instream biological data when obtained in conjunction with chemical analyses.     

A framework to assess regional environmental impacts of dedicated energy crop production

Numerous studies have evaluated air quality and greenhouse gas mitigation benefits of biomass energy systems, but the potential environmental impacts associated with large-scale changes in land-use patterns needed to produce energy crops have not been quantified. This paper presents a framework to assess the potential soil, water, and biodiversity impacts that may result from the large-scale production of dedicated energy crops. The framework incorporates producer economic decision models with environmental models to assess changes in land use patterns and to quantify the consequent environmental impacts. Economic and policy issues that will affect decisions to produce energy crops are discussed. The framework is used to evaluate erosion and chemical runoff in two Tennessee regions. The analysis shows that production of dedicated energy crops in place of conventional crops will significantly reduce erosion and chemical runoff.     

Risk of polycyclic aromatic hydrocarbon (PAH) exposure from ingested food: the Azerbaijan case study

Risks due to polycyclic aromatic hydrocarbons (PAHs) exposure from food consumption for the population of Azerbaijan were determined using deterministic and probabilistic methods. The guidelines and methods described and presented in the United States Environmental Protection Agency (U.S. EPA) Risk Assessment Guidance for Superfund (RAGS) Part A was used in performing the risk assessments. The current study utilized concentration data from different sources representing international studies performed over the past decade to determine those food products that contribute the most exposure to PAHs through ingestion for the Azeri population. Due to lack of concentration data from middle-Eastern countries, only European countries were considered and used for this analysis. Using the benzo[a]pyrene (BaP) toxicity equivalency factors (TEFs) to adjust the concentrations of the individual PAH compounds to BaP equivalent concentrations, risk analyses were performed. Deterministic risk estimates fell within probabilistic risk estimates. Child risks were consistently four to seven times higher in magnitude than adult risks. Risk potentials determined for the food exposure pathway were also determined to be up to ten times higher in magnitude than risks determined from exposures due to other pathways such as soil contamination. It was observed that three major factors contributed to the variability in the assessment results, which were child and adult body weights, consumption rates of the different food groups, and the variances of the input data. The most prevalent pathways of PAH exposure from the dietary patterns of the Azerbaijani population were determined to be from bread and bakery products, milk and dairy products, and egg products.     

Percentile estimation using variable censored data

Much progress has been made in recent years to address the estimation of summary statistics, using data that are subject to censoring of results that fall below the limit of detection (LOD) for the measuring instrument. Truncated data methods (e.g., Tobit regression) and multiple-imputation are two approaches for analyzing data results that are below the LOD. To apply these methods requires an assumption about the underlying distribution of the data. Because the log-normal distribution has been shown to fit many data sets obtained from environmental measurements, the common practice is to assume that measurements of environmental factors can be described by log-normal distributions. This article describes methods for obtaining estimates of percentiles and their associated confidence intervals when the results are log-normal and a fraction of the results are below the LOD. We present limited simulations to demonstrate the bias of the proposed estimates and the coverage probability of their associated confidence intervals. Estimation methods are used to generate summary statistics for 2,3,7,8-tetrachloro dibenzo-p-dioxin (2,3,7,8-TCDD) using data from a 2001 background exposure study in which PCDDs/PCDFs/cPCBs in human blood serum were measured in a Louisiana population. Because the congener measurements used in this study were subject to variable LODs, we also present simulation results to demonstrate the effect of variable LODs on the multiple-imputation process.     

Climate change adaptation strategies for transportation infrastructure in Prince George,Canada

Transport infrastructure is particularly vulnerable to climate impacts as it is designed for long operational lives, and both episodic and seasonal conditions contribute to deterioration, disruption and unsafe incidents. There are some examples of adaptation in transportation design, but many communities do not have the capacity to incorporate climate change considerations into infrastructure planning and management. Researchers worked closely with the City of Prince George, in Central British Columbia, Canada, to build on existing work and explore how the City could plan, design, and maintain roads and other structures to account for climate change. A local steering committee was formed, and created and evaluated 23 potential research topics. Two focus areas were selected for further investigation and explored during a workshop with practitioners, researchers, consultants and other representatives. The workshop precipitated an investigation of projected impacts of climate change on road maintenance and road safety, and plans to explore alternative paving techniques. Outcomes of the case study provide insights regarding climate change and local transportation infrastructure, including: how researchers can engage with local experts to explore adaptation; issues local governments perceive as important; and barriers communities face as they attempt to address vulnerabilities.