13 resultados para individual exposure

em CentAUR: Central Archive University of Reading - UK


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The wood mouse is a common and abundant species in agricultural landscape and is a focal species in pesticide risk assessment. Empirical studies on the ecology of the wood mouse have provided sufficient information for the species to be modelled mechanistically. An individual-based model was constructed to explicitly represent the locations and movement patterns of individual mice. This together with the schedule of pesticide application allows prediction of the risk to the population from pesticide exposure. The model included life-history traits of wood mice as well as typical landscape dynamics in agricultural farmland in the UK. The model obtains a good fit to the available population data and is fit for risk assessment purposes. It can help identify spatio-temporal situations with the largest potential risk of exposure and enables extrapolation from individual-level endpoints to population-level effects. Largest risk of exposure to pesticides was found when good crop growth in the “sink” fields coincided with high “source” population densities in the hedgerows. Keywords: Population dynamics, Pesticides, Ecological risk assessment, Habitat choice, Agent-based model, NetLogo

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The potential risk of agricultural pesticides to mammals typically depends on internal concentrations within individuals, and these are determined by the amount ingested and by absorption, distribution, metabolism, and excretion (ADME). Pesticide residues ingested depend, amongst other things, on individual spatial choices which determine how much and when feeding sites and areas of pesticide application overlap, and can be calculated using individual-based models (IBMs). Internal concentrations can be calculated using toxicokinetic (TK) models, which are quantitative representations of ADME processes. Here we provide a population model for the wood mouse (Apodemus sylvaticus) in which TK submodels were incorporated into an IBM representation of individuals making choices about where to feed. This allows us to estimate the contribution of individual spatial choice and TK processes to risk. We compared the risk predicted by four IBMs: (i) “AllExposed-NonTK”: assuming no spatial choice so all mice have 100% exposure, no TK, (ii) “AllExposed-TK”: identical to (i) except that the TK processes are included where individuals vary because they have different temporal patterns of ingestion in the IBM, (iii) “Spatial-NonTK”: individual spatial choice, no TK, and (iv) “Spatial-TK”: individual spatial choice and with TK. The TK parameters for hypothetical pesticides used in this study were selected such that a conventional risk assessment would fail. Exposures were standardised using risk quotients (RQ; exposure divided by LD50 or LC50). We found that for the exposed sub-population including either spatial choice or TK reduced the RQ by 37–85%, and for the total population the reduction was 37–94%. However spatial choice and TK together had little further effect in reducing RQ. The reasons for this are that when the proportion of time spent in treated crop (PT) approaches 1, TK processes dominate and spatial choice has very little effect, and conversely if PT is small spatial choice dominates and TK makes little contribution to exposure reduction. The latter situation means that a short time spent in the pesticide-treated field mimics exposure from a small gavage dose, but TK only makes a substantial difference when the dose was consumed over a longer period. We concluded that a combined TK-IBM is most likely to bring added value to the risk assessment process when the temporal pattern of feeding, time spent in exposed area and TK parameters are at an intermediate level; for instance wood mice in foliar spray scenarios spending more time in crop fields because of better plant cover.

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A wide variety of exposure models are currently employed for health risk assessments. Individual models have been developed to meet the chemical exposure assessment needs of Government, industry and academia. These existing exposure models can be broadly categorised according to the following types of exposure source: environmental, dietary, consumer product, occupational, and aggregate and cumulative. Aggregate exposure models consider multiple exposure pathways, while cumulative models consider multiple chemicals. In this paper each of these basic types of exposure model are briefly described, along with any inherent strengths or weaknesses, with the UK as a case study. Examples are given of specific exposure models that are currently used, or that have the potential for future use, and key differences in modelling approaches adopted are discussed. The use of exposure models is currently fragmentary in nature. Specific organisations with exposure assessment responsibilities tend to use a limited range of models. The modelling techniques adopted in current exposure models have evolved along distinct lines for the various types of source. In fact different organisations may be using different models for very similar exposure assessment situations. This lack of consistency between exposure modelling practices can make understanding the exposure assessment process more complex, can lead to inconsistency between organisations in how critical modelling issues are addressed (e.g. variability and uncertainty), and has the potential to communicate mixed messages to the general public. Further work should be conducted to integrate the various approaches and models, where possible and regulatory remits allow, to get a coherent and consistent exposure modelling process. We recommend the development of an overall framework for exposure and risk assessment with common approaches and methodology, a screening tool for exposure assessment, collection of better input data, probabilistic modelling, validation of model input and output and a closer working relationship between scientists and policy makers and staff from different Government departments. A much increased effort is required is required in the UK to address these issues. The result will be a more robust, transparent, valid and more comparable exposure and risk assessment process. (C) 2006 Elsevier Ltd. All rights reserved.

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Two clones of Daphnia magna (Standard and Ruth) were exposed for 7 days to sub-lethal concentrations of acephate (5.0 and 10.0 mg/L). Survivorship, individual growth, reproduction and the population growth rate (lambda) were evaluated over three weeks. Acetylcholinesterase (AChE) activity was measured on days 2, 7 and 21. Acephate exposure inhibited AChE activity but had no direct effect on life history (LH) traits. There was also no effect of clone on AChE activity, LH and lambda. However, a significant interaction between clone and acephate concentration was found on both fecundity and AChE inhibition at 48 h was associated with a decrease in lambda the Standard clone and an increase in lambda in clone Ruth. Therefore, our findings show that genotypic variation will influence the link between AChE activity and toxic effects at higher levels of biological organisation in D. magna. (c) 2007 Elsevier Inc. All rights reserved.

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Objective: To determine the risk of lung cancer associated with exposure at home to the radioactive disintegration products of naturally Occurring radon gas. Design: Collaborative analysis of individual data from 13 case-control studies of residential radon and lung cancer. Setting Nine European countries. Subjects 7148 cases Of lung cancer and 14 208 controls. Main outcome measures: Relative risks of lung cancer and radon gas concentrations in homes inhabited during the previous 5-34 years measured in becquerels (radon disintegrations per second) per cubic incite (Bq/m(3)) Of household air. Results: The mean measured radon concentration in homes of people in tire control group was 97 Bq/m(3), with 11% measuring > 200 and 4% measuring > 400 Bq/m(3). For cases of lung cancer the mean concentration was 104 Bq/m(3). The risk of lung cancer increased by 8.4% (95% confidence interval 3.0% to 15.8%) per 100 Bq/m(3) increase in measured radon (P = 0.0007). This corresponds to an increase of 16% (5% to 31%) per 100 Bq/m(3) increase in usual radon-that is, after correction for the dilution caused by random uncertainties in measuring radon concentrations. The dose-response relation seemed to be linear with no threshold and remained significant (P=0.04) in analyses limited to individuals from homes with measured radon < 200 Bq/m(3). The proportionate excess risk did not differ significantly with study, age, sex, or smoking. In the absence of other causes of death, the absolute risks of lung cancer by age 75 years at usual radon concentrations of 0, 100, and 400 Bq/m(3) would be about 0.4%, 0.5%, and 0.7%, respectively, for lifelong non-smokers, and about 25 times greater (10%, 12%, and 16%) for cigarette smokers. Conclusions: Collectively, though not separately, these studies show appreciable hazards from residential radon, particularly for smokers and recent ex-smokers, and indicate that it is responsible for about 2% of all deaths from cancer in Europe.

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Cytochrome P450 activity in individual Chironomus riparius larvae was measured using a microtiter plate adaptation of the ethoxyresorufin-O-deethylase (EROD) assay. The sensitivity of this biomarker was tested by exposing larvae to phenobarbital (0.5 and 1.0 mM) and permethrin (1 and 10 mug/g). Both chemicals induced EROD activity in C. riparius larvae by up to 1.58-fold with PB and 2.47-fold with permethrin. EROD induction was more pronounced after 48 h. The initially high EROD activity in the controls suggested that P450s are induced by stress. Feeding levels prior to exposure also had a significant effect on EROD activity. EROD activity compared to the control was highest when larvae were fed double the normal ration. These results indicate that EROD activity in individual C. riparius may be a useful biomarker to add to a suite of biomarkers for the detection of freshwater pollution. (C) 2002 Elsevier Science (USA). All rights reserved.

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Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental pollutants that frequently accumulate in soils. There is therefore a requirement to determine their levels in contaminated environments for the purposes of determining impacts on human health. PAHs are a suite of individual chemicals, and there is an ongoing debate as to the most appropriate method for assessing the risk to humans from them. Two methods predominate: the surrogate marker approach and the toxic equivalency factor. The former assumes that all chemicals in a mixture have an equivalent toxicity. The toxic equivalency approach estimates the potency of individual chemicals relative to the usually most toxic Benzo(a)pyrene. The surrogate marker approach is believed to overestimate risk and the toxic equivalency factor to underestimate risk. When analysing the risks from soils, the surrogate marker approach is preferred due to its simplicity, but there are concerns because of the potential diversity of the PAH profile across the range of impacted soils. Using two independent data sets containing soils from 274 sites across a diverse range of locations, statistical analysis was undertaken to determine the differences in the composition of carcinogenic PAH between site locations, for example, rural versus industrial. Following principal components analysis, distinct population differences were not seen between site locations in spite of large differences in the total PAH burden between individual sites. Using all data, highly significant correlations were seen between BaP and other carcinogenic PAH with the majority of r2 values > 0.8. Correlations with the European Food Standards Agency (EFSA) summed groups, that is, EFSA2, EFSA4 and EFSA8 had even higher correlations (r2 > 0.95). We therefore conclude that BaP is a suitable surrogate marker to represent mixtures of PAH in soil during risk assessments.

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Abstract: Long-term exposure of skylarks to a fictitious insecticide and of wood mice to a fictitious fungicide were modelled probabilistically in a Monte Carlo simulation. Within the same simulation the consequences of exposure to pesticides on reproductive success were modelled using the toxicity-exposure-linking rules developed by R.S. Bennet et al. (2005) and the interspecies extrapolation factors suggested by R. Luttik et al.(2005). We built models to reflect a range of scenarios and as a result were able to show how exposure to pesticide might alter the number of individuals engaged in any given phase of the breeding cycle at any given time and predict the numbers of new adults at the season’s end.

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Abstract: Following a workshop exercise, two models, an individual-based landscape model (IBLM) and a non-spatial life-history model were used to assess the impact of a fictitious insecticide on populations of skylarks in the UK. The chosen population endpoints were abundance, population growth rate, and the chances of population persistence. Both models used the same life-history descriptors and toxicity profiles as the basis for their parameter inputs. The models differed in that exposure was a pre-determined parameter in the life-history model, but an emergent property of the IBLM, and the IBLM required a landscape structure as an input. The model outputs were qualitatively similar between the two models. Under conditions dominated by winter wheat, both models predicted a population decline that was worsened by the use of the insecticide. Under broader habitat conditions, population declines were only predicted for the scenarios where the insecticide was added. Inputs to the models are very different, with the IBLM requiring a large volume of data in order to achieve the flexibility of being able to integrate a range of environmental and behavioural factors. The life-history model has very few explicit data inputs, but some of these relied on extensive prior modelling needing additional data as described in Roelofs et al.(2005, this volume). Both models have strengths and weaknesses; hence the ideal approach is that of combining the use of both simple and comprehensive modeling tools.

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Learned helplessness is a maladaptive response to uncontrollable stress characterized by impaired motor escape responses, reduced motivation and learning deficits. There are important individual differences in the likelihood of becoming helpless following exposure to uncontrollable stress but little is known about the neural mechanisms underlying these individual differences. Here we used structural MRI to measure gray and white matter in individuals with chronic pain, a population at high risk for helplessness due to prolonged exposure to a poorly controlled stressor (pain). Given that self-reported helplessness is predictive of treatment outcomes in chronic pain, understanding such differences might provide valuable clinical insight. We found that the magnitude of self-reported helplessness correlated with cortical thickness in the supplementary motor area (SMA) and midcingulate cortex, regions implicated in cognitive aspects of motor behavior. We then examined the white matter connectivity of these regions and found that fractional anisotropy of connected white matter tracts along the corticospinal tract was associated with helplessness and mediated the relationship between SMA cortical thickness and helplessness. These data provide novel evidence that links individual differences in the motor output pathway with perceived helplessness over a chronic and poorly controlled stressor.

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Population modelling is increasingly recognised as a useful tool for pesticide risk assessment. For vertebrates that may ingest pesticides with their food, such as woodpigeon (Columba palumbus), population models that simulate foraging behaviour explicitly can help predicting both exposure and population-level impact. Optimal foraging theory is often assumed to explain the individual-level decisions driving distributions of individuals in the field, but it may not adequately predict spatial and temporal characteristics of woodpigeon foraging because of the woodpigeons’ excellent memory, ability to fly long distances, and distinctive flocking behaviour. Here we present an individual-based model (IBM) of the woodpigeon. We used the model to predict distributions of foraging woodpigeons that use one of six alternative foraging strategies: optimal foraging, memory-based foraging and random foraging, each with or without flocking mechanisms. We used pattern-oriented modelling to determine which of the foraging strategies is best able to reproduce observed data patterns. Data used for model evaluation were gathered during a long-term woodpigeon study conducted between 1961 and 2004 and a radiotracking study conducted in 2003 and 2004, both in the UK, and are summarised here as three complex patterns: the distributions of foraging birds between vegetation types during the year, the number of fields visited daily by individuals, and the proportion of fields revisited by them on subsequent days. The model with a memory-based foraging strategy and a flocking mechanism was the only one to reproduce these three data patterns, and the optimal foraging model produced poor matches to all of them. The random foraging strategy reproduced two of the three patterns but was not able to guarantee population persistence. We conclude that with the memory-based foraging strategy including a flocking mechanism our model is realistic enough to estimate the potential exposure of woodpigeons to pesticides. We discuss how exposure can be linked to our model, and how the model could be used for risk assessment of pesticides, for example predicting exposure and effects in heterogeneous landscapes planted seasonally with a variety of crops, while accounting for differences in land use between landscapes.

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Recent concern over global pollinator declines has led to considerable research on the effects of pesticides on bees1, 2, 3, 4, 5. Although pesticides are typically not encountered at lethal levels in the field, there is growing evidence indicating that exposure to field-realistic levels can have sublethal effects on bees, affecting their foraging behaviour1, 6, 7, homing ability8, 9 and reproductive success2, 5. Bees are essential for the pollination of a wide variety of crops and the majority of wild flowering plants10, 11, 12, but until now research on pesticide effects has been limited to direct effects on bees themselves and not on the pollination services they provide. Here we show the first evidence to our knowledge that pesticide exposure can reduce the pollination services bumblebees deliver to apples, a crop of global economic importance. Bumblebee colonies exposed to a neonicotinoid pesticide provided lower visitation rates to apple trees and collected pollen less often. Most importantly, these pesticide-exposed colonies produced apples containing fewer seeds, demonstrating a reduced delivery of pollination services. Our results also indicate that reduced pollination service delivery is not due to pesticide-induced changes in individual bee behaviour, but most likely due to effects at the colony level. These findings show that pesticide exposure can impair the ability of bees to provide pollination services, with important implications for both the sustained delivery of stable crop yields and the functioning of natural ecosystems.