Quantitative arsenic speciation in two species of earthworms from a former mine site

The relationship between the total arsenic concentration and the chemical speciation of arsenic in two species of earthworm (Lumbricus rubellus and Dendrodrilus rubidus) in relation to the host soil, was investigated for 13 sites of varying arsenic content, including a background level garden soil and a former mine site at the Devon Great Consols, UK. Earthworms were collected with the host soil (As soil concentration range 16-12, 466 mg kg(-1) dry weight) and measured for their total arsenic (concentration range 7-595 mg kg(-1) dry weight) using inductively coupled plasma mass spectrometry (ICP-MS). A methanol-water mixture was used to extract arsenic species from the earthworms prior to determination of the individual arsenic species by a combination of anion and cation exchange high performance liquid chromatography coupled to inductively coupled plasma mass spectrometry (HPLC-ICP-MS). A gradient elution anion exchange method is presented whereby nine arsenic species could be measured in one sample injection. Arsenic species were identified by comparison of retention times and sample spiking with known standards and a fully characterised seaweed extract. Arsenic was generally present in the earthworm as arsenate (As(V)) or arsenite (As(III)) and arsenobetaine (AB). Methylarsonate (MA), dimethylarsinate (DMA) and three arsenosugars (glycerol, phosphate, sulfate) were present as minor constituents. These results are discussed in relation to the mechanisms for coping with exposure to soil bound arsenic.     

Critical technical elements of state bioassessment programs: a process to evaluate program rigor and comparability

We developed a systematic process to evaluate state/tribal bioassessment programs to provide information about the rigor of the technical approach. This is accomplished via on-site interviews to produce an evaluation that assigns one of four levels of rigor as an outcome. Level 4 is the most rigorous and reflects a technical capacity to accurately determine incremental condition and support management programs. The remaining three levels are less able to assess incremental condition and are appropriate for only some management support needs. Accurately determining impairment and diagnosing pollution-specific stressors are fundamental tasks that states/tribes must accomplish to provide management support. This goal is fulfilled to varying degrees by most states/tribes. The evaluation employs a checklist and a sliding scale of rigor for 13 technical elements. Feedback is provided to each state/tribe via a technical memorandum that describes the technical components of the monitoring program, highlights strengths, and recommends improvements for specific technical issues. This can be used to refine the bioassessment and monitoring programs to better support management programs. The results of 14 state/tribal evaluations are included here. The majority (nine states, one tribe) revealed that most operate at level 2 with developmental activities that will elevate the level of program rigor already underway. Two states operate level 4 programs and each have numeric biocriteria and refined designated uses in their water quality standards. This is the ultimate goal of the process of engaging states in the development of bioassessment programs in the U.S.     

Characterizing spatial structure of sediment E. coli populations to inform sampling design

Escherichia coli can persist in streambed sediments and influence water quality monitoring programs through their resuspension into overlying waters. This study examined the spatial patterns in E. coli concentration and population structure within streambed morphological features during baseflow and following stormflow to inform sampling strategies for representative characterization of E. coli populations within a stream reach. E. coli concentrations in bed sediments were significantly different (p?=?0.002) among monitoring sites during baseflow, and significant interactive effects (p?=?0.002) occurred among monitoring sites and morphological features following stormflow. Least absolute shrinkage and selection operator (LASSO) regression revealed that water velocity and effective particle size (D ₁₀) explained E. coli concentration during baseflow, whereas sediment organic carbon, water velocity and median particle diameter (D ₅₀) were important explanatory variables following stormflow. Principle Coordinate Analysis illustrated the site-scale differences in sediment E. coli populations between disconnected stream segments. Also, E. coli populations were similar among depositional features within a reach, but differed in relation to high velocity features (e.g., riffles). Canonical correspondence analysis resolved that E. coli population structure was primarily explained by spatial (26.9–31.7 %) over environmental variables (9.2–13.1 %). Spatial autocorrelation existed among monitoring sites and morphological features for both sampling events, and gradients in mean particle diameter and water velocity influenced E. coli population structure for the baseflow and stormflow sampling events, respectively. Representative characterization of streambed E. coli requires sampling of depositional and high velocity environments to accommodate strain selectivity among these features owing to sediment and water velocity heterogeneity.     

Estimating carbon in savanna ecosystems: rational distribution of effort

Minimising the cost of repeatedly estimating C (C) stocks is crucial to the financial viability of projects that seek to sell C credits. Depending on the price of C, this may imply less or more sampling effort than would be applied for science objectives. In systems with heterogeneous C pools, such as savannas, this translates into a variable-effort sampling strategy that maximises the marginal additional C that can be claimed per incremental unit of effort expended. Analysis of a savanna in north-eastern South Africa indicates relatively modest returns per hectare due to the small C quantities and low sequestration rates. Under these conditions, areas in excess of 1,000 ha and infrequent sampling frequencies of 5–10 years are required to make such projects financially viable. For such projects the sample variance, number of samples, cost per sample and establishment costs have negligible impacts on financial viability. It was also found that the soil-C pool contributes up to three times the net returns of the aboveground C pool and provides a strong argument to monitor soil C for certification and market trading. The financial viability estimates, however, do not include the management or opportunity costs incurred in changing the land use. The economies of scale identified in this study combined with the massive area covered by savannas indicate that these additional costs can be covered. Further research is recommended to quantify these costs and interrogate the feasibility of large scale (in excess of 10,000 ha) C-sink projects in savanna systems.     

Software tools to support incident reporting in safety-critical systems

Incident reporting systems are playing an increasingly important role in the development and maintenance of safety-critical applications. The perceived success of the FAA's Aviation Safety Reporting System (ASRS) and the FDA's MedWatch has led to the establishment of similar national and international schemes. These enable individuals and groups to report their safety concerns in a confidential or anonymous manner. Unfortunately, many of these systems are becoming victims of their own success. The ASRS and MedWatch have both now received over 500,000 submissions. In consequence, the administrators of incident reporting systems increasingly rely upon software tools to support the administration of their systems. In the past, these systems have relied upon ad hoc applications of conventional database technology. However, there are several reasons why this technology is inadequate for many large-scale reporting schemes. In particular, the problems of query formation often result in poor precision and recall. This, in turn, has profound implications for safety-critical applications. Users may fail to identify similar incidents within national or international collections. These ad hoc approaches also neglect the opportunities provided by recent developments in computer assisted interviewing and in the monitoring of retrieval activities to build models of user behavior. These techniques offer a number of potential benefits. For instance, it is possible to automatically detect potential biases in the way that investigators analyze particular incidents.