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Maraun M.,University of Gottingen | Erdmann G.,University of Gottingen | Fischer B.M.,University of Innsbruck | Pollierer M.M.,University of Gottingen | And 3 more authors.
Soil Biology and Biochemistry | Year: 2011

In this review we summarize our knowledge of using stable isotopes (15N/14N, 13C/12C) to better understand the trophic ecology of oribatid mites. Our aims are (a) to recapitulate the history of stable isotope research in soil animals with a focus on oribatid mites, (b) to present new stable isotope data for oribatid mites and overview the current state of knowledge of oribatid mite trophic niche differentiation, (c) to compile problems and limitations of stable isotope based analyses of trophic relationships and (d) to suggest future challenges, questions and problems that may be solved using stable isotope analyses and other novel techniques for improving our understanding on the trophic ecology of soil invertebrates. We conclude that (1) in addition to 15N/14N ratios, 13C/12C ratios contribute to our understanding of the trophic ecology of oribatid mites, allowing, e.g. separation of lichen- and moss-feeding species, (2) there likely are many lichen but few moss feeding oribatid mite species, (3) oribatid mite species that are endophagous as juveniles are separated by their stable isotope signatures from all other oribatid mite species, (4) fungivorous oribatid mite species cannot be separated further, e.g. the fungal taxa they feed on cannot be delineated. A particular problem in using stable isotope data is the difficulty in determining signatures for basal food resources, since decomposing material, fungi and lichens comprise various components differing in stable isotope signatures; 13C/12C ratios and potentially other isotopes may help in identifying the role of these resources for decomposer animal nutrition. © 2011 Elsevier Ltd. Source


Gericke D.,Rifcon GmbH
Journal of environmental science and health. Part. B, Pesticides, food contaminants, and agricultural wastes | Year: 2010

According to the EU directive 91/414/EEC potential environmental concentrations of pesticides have to be assessed with environmental fate models. For the calculation of pesticide concentrations it is necessary to provide an application date which has to match the specific Biologische Bundesanstalt, Bundesamt, Chemische Industrie (BBCH) stage at which the pesticide shall be applied. If these application dates are not available for a specific stage, crop and country they must be estimated, which adds an additional uncertainty to the predicted concentrations. In the present study, we therefore evaluate to which extent application dates can be derived from phenological data. For this analysis phenological data, converted to BBCH stages, of two field crops provided by the German Weather Service (DWD) were analyzed. We found a linear correlation between BBCH stages and the respective appearance dates, which can be used for interpolation of appearance dates of specific BBCH stages. Remarkably, when comparing BBCH stages from Germany and the Czech Republic almost identical correlations of appearance dates and BBCH stages were found. In the next step, soil and climate data from Joint Research Centre (JRC) were analyzed together with phenological data in order to evaluate if BBCH stages can be estimated for countries with other climate or soil conditions. This analysis revealed that temperature, global radiation and evaporation were the parameters with the strongest impact. These parameters were used for estimating appearance dates of BBCH stages for other countries. Exemplarily, appearance dates for maize BBCH were calculated for Italy. Estimated and observed appearance dates showed a high concordance (on average six days difference). Finally, the political of impact a variation of a few days on calculated pesticide concentration was analyzed. Exemplarily, the pesticide fate model FOCUS PEARL was used to estimate pesticide groundwater concentrations. When calculating concentrations for application dates varying by ± two weeks, concentrations in groundwater usually varied very little. The highest variation was found for application at BBCH 30 in maize (6.6 % variation over all scenarios). These results showed that the uncertainty included in the estimation of appearance dates of BBCH stages for other countries has a relatively small effect on the results of PEARL and consequentially on the decision of the pesticide risk assessment by changing only the application date. Source


Wang M.,Rifcon GmbH | Luttik R.,National Institute for Public Health and the Environment
Environmental Sciences Europe | Year: 2012

Population models are increasingly being considered as a tool for pesticide risk assessment in order to evaluate how potential effects act on the population level and population recovery. While the importance and difficulties of such models have been discussed by various authors during the past decade, mainly with a focus on how to describe or develop such models, several biological and methodological aspects have never been addressed so far, which are relevant for the application of models in risk assessment. These include a critical review of our knowledge of a species, the use of field data by taking methodological constraints into account, how to include uncertainty in model validation or how to measure effects. Although these aspects will be critical for the acceptance of population models by authorities, most of them apply not only to population models, but also to standard risk assessment. In the present article, we give practical recommendations for addressing these questions in population level risk assessments. © 2012 Wang and Luttik; licensee Springer. Source


Despite various attempts to establish population models as standard tools in pesticide risk assessment, population models still receive limited acceptance by risk assessors and authorities in Europe. A main criticism of risk assessors is that population models are often not, or not sufficiently, validated. Hence the realism of population-level risk assessments conducted with such models remains uncertain. We therefore developed an individual-based population model for the common vole, Microtus arvalis, and demonstrate how population models can be validated in great detail based on published data. The model is developed for application in pesticide risk assessment, therefore, the validation covers all areas of the biology of the common vole that are relevant for the analysis of potential effects and recovery after application of pesticides. Our results indicate that reproduction, survival, age structure, spatial behavior, and population dynamics reproduced from the model are comparable to field observations. Also interannual population cycles, which are frequently observed in field studies of small mammals, emerge from the population model. These cycles were shown to be caused by the home range behavior and dispersal. As observed previously in the field, population cycles in the model were also stronger for longer breeding season length. Our results show how validation can help to evaluate the realism of population models, and we discuss the importance of taking field methodology and resulting bias into account. Our results also demonstrate how population models can help to test or understand biological mechanisms in population ecology. Integr Environ Assess Manag. © 2012 SETAC. Source


Sidorenko Y.,Rifcon GmbH
Food and Chemical Toxicology | Year: 2011

Probabilistic methods, in particular Monte Carlo methods, have become widely used in assessment of dietary risks from plant protection products. However, if the critical exposure occurs rarely, estimating its probability with commonly used Monte Carlo approaches can require an unrealistically big number of iterations. A simple method proposed in this paper, referred to as food combination analysis (FCA), finds out subsets of input values necessary for occurrence of a critical exposure event. In particular, for a critical event to occur consumption of a certain combination of contaminated foods could be required. Sometimes by finding the probability that such a food combination is consumed one could directly get an acceptable estimate of the risk, without Monte Carlo simulations. The method performs especially well if available data sets of consumed amounts of foods and residue concentrations of a chemical contain a large fraction of zeros. Based on a literature example, it is shown that the probability of the critical exposure estimated with the FCA could be more than 10 times lower than the estimate of a Monte Carlo approach with 50,000 iterations. The present approach also provides a platform for adaptation and development of more sophisticated methods to estimate low dietary risks. © 2011 Elsevier Ltd. Source

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