Time filter

Source Type

Woodstock, United Kingdom

Hing L.S.,Royal Holloway, University of London | Ford T.,Royal Holloway, University of London | Finch P.,Royal Holloway, University of London | Crane M.,WCA Environment Ltd. | Morritt D.,Royal Holloway, University of London
Aquatic Toxicology | Year: 2011

Continuous culture conditions designed to achieve a dynamic equilibrium between phytoplankton growth and nutrient input were established for Phaeodactylum tricornutum, Isochrysis galbana and Chlorella salina. The technique was used to determine the no observed effect concentration (NOEC) and lowest observed effect concentration (LOEC) for algae after spiking with diesel oil. P. tricornutum (NOEC = 0.25. mg/l, LOEC = 0.3. mg/l) was more sensitive than I. galbana (NOEC = 2.5. mg/l, LOEC = 2.6. mg/l), while C. salina (NOEC = 16.0. mg/l, LOEC = 17.0. mg/l) was the most tolerant. Continuous renewal of medium ensured that experimental conditions remained stable throughout the test period and is a more environmentally relevant method for assessing the effects of many contaminants. © 2011 Elsevier B.V. Source

Grist E.P.M.,WCA Environment Ltd. | Jackson G.D.,University of Tasmania | Meekan M.G.,Australian Institute of Marine Science
Environmental Biology of Fishes | Year: 2011

Individual growth patterns in ecology are often determined from population field data through the use of regression and model selection inference analyses. However, such approaches are typically unable to provide insight into dynamic processes when based upon collections of 'snapshot' data that consist of only a single observation for each individual. We caution how model selection inference from size-at-age data may lead to growth models that are mis-specified in the case of species such as squid and fishes that display fast and variable growth and for which, field data of the early part of the lifespan are typically sparse and difficult to obtain. © 2010 Springer Science+Business Media B.V. Source

Peters A.,WCA Environment Ltd. | Merrington G.,WCA Environment Ltd. | de Schamphelaere K.,Ghent University | Delbeke K.,European Copper Institute
Integrated Environmental Assessment and Management | Year: 2011

The chronic Cu biotic ligand model (CuBLM) provides a means by which the bioavailability of Cu can be taken into account in assessing the potential chronic risks posed by Cu at specific freshwater locations. One of the barriers to the widespread regulatory application of the CuBLM is the perceived complexity of the approach when compared to the current systems that are in place in many regulatory organizations. The CuBLM requires 10 measured input parameters, although some of these have a relatively limited influence on the predicted no-effect concentration (PNEC) for Cu. Simplification of the input requirements of the CuBLM is proposed by estimating the concentrations of the major ions Mg 2+, Na +, K +, SO 2- 4, Cl -, and alkalinity from Ca concentrations. A series of relationships between log10 (Ca,mgl -1) and log10 (major ion,mgl -1) was established from surface water monitoring data for Europe, and applied in the prediction of Cu PNEC values for some UK freshwater monitoring data. The use of default values for major ion concentrations was also considered, and both approaches were compared to the use of measured major ion concentrations. Both the use of fixed default major ion concentrations, and major ion concentrations estimated from Ca concentrations, provided Cu PNEC predictions which were in good agreement with the results of calculations using measured data. There is a slight loss of accuracy when using estimates of major ion concentrations compared to using measured concentration data, although to a lesser extent than when fixed default values are applied. The simplifications proposed provide a practical evidence-based methodology to facilitate the regulatory implementation of the CuBLM. © 2011 SETAC. Source

Peters A.,WCA Environment Ltd. | Simpson P.,WCA Environment Ltd. | Moccia A.,University of Insubria
Environmental Science and Pollution Research | Year: 2014

Recent years have seen considerable improvement in water quality standards (QS) for metals by taking account of the effect of local water chemistry conditions on their bioavailability. We describe preliminary efforts to further refine water quality standards, by taking account of the composition of the local ecological community (the ultimate protection objective) in addition to bioavailability. Relevance of QS to the local ecological community is critical as it is important to minimise instances where quality classification using QS does not reconcile with a quality classification based on an assessment of the composition of the local ecology (e.g. using benthic macroinvertebrate quality assessment metrics such as River InVertebrate Prediction and Classification System (RIVPACS)), particularly where ecology is assessed to be at good or better status, whilst chemical quality is determined to be failing relevant standards. The alternative approach outlined here describes a method to derive a site-specific species sensitivity distribution (SSD) based on the ecological community which is expected to be present at the site in the absence of anthropogenic pressures (reference conditions). The method combines a conventional laboratory ecotoxicity dataset normalised for bioavailability with field measurements of the response of benthic macroinvertebrate abundance to chemical exposure. Site-specific QSref are then derived from the 5%ile of this SSD. Using this method, site QSref have been derived for zinc in an area impacted by historic mining activities. Application of QSref can result in greater agreement between chemical and ecological metrics of environmental quality compared with the use of either conventional (QScon) or bioavailability-based QS (QSbio). In addition to zinc, the approach is likely to be applicable to other metals and possibly other types of chemical stressors (e.g. pesticides). However, the methodology for deriving site-specific targets requires additional development and validation before they can be robustly applied during surface water classification. © 2013 Springer-Verlag Berlin Heidelberg. Source

Peters A.,WCA Environment Ltd. | Crane M.,WCA Environment Ltd. | Adams W.,Rio Tinto Alcan
Bulletin of Environmental Contamination and Toxicology | Year: 2011

Matched chemical and ecological monitoring data were used to assess the effects of iron on benthic macroinvertebrate communities. Three measures of iron exposure: dissolved, total, and particulate iron were assessed. Ecological responses were normalised to an unimpacted reference condition to make site-specific predictions of the reference condition. Ecological data were expressed as an Ecological Quality Index (EQI), indicating quality relative to the reference condition. Quantile regression analysis was used to derive thresholds as an EQI value equivalent to the cut-off between good and moderate ecological status for water quality classification. Thresholds for Good Ecological Status ranged from 1.25 to 2.46 mg L -1 depending on the measure of exposure and ecological response. © 2011 Springer Science+Business Media, LLC. Source

Discover hidden collaborations