Weltraum-Mikrobiologie

Purpose Approaches in environmental risk assessment for pesticides are becoming more and more realistic. Thereby, risk assessment has to be protective in a way that no long-lasting (adverse) effects on populations will occur in the environment. Since this imperative includes species generally showing high population vulnerability due to their life history traits, prospective risk assessment should be based on realistic worst cases. Based on life history traits, the purpose of the current study was to verify whether a worst case combination of low potential for intrinsic recovery and low ability for recolonisation can be found in the field. Methods Combinations of traits related to dispersal ability and reproduction of macroinvertebrates were investigated using monitoring data from edge of field water bodies in Germany. The relative distribution of traits was analyzed across different agricultural regions and across sites of different potential for exposure to pesticides. Species were sorted in a tiered approach in order to gain a list of realistic worst case species. Results Life history traits were found equally distributed across different regions. Thereby, dispersal ability and voltinism were not randomly combined. Within the data analysed, low dispersal ability was found to be exclusive to semivoltine taxa. Owing to their appearance in reference sites, poor dispersal ability and a long time reproduction, three species were considered potentially worst case. Conclusions The trait approach was found to be suitable in comparing trait distributions within different regions and in compiling a list of critical taxa for consideration in environmental risk assessment

Shared Genetic Etiology Between Alcohol Dependence and Major Depressive Disorder

The clinical comorbidity of alcohol dependence (AD) and major depressive disorder (MDD) is well established, whereas genetic factors influencing co-occurrence remain unclear. A recent study using polygenic risk scores (PRS) calculated based on the first-wave Psychiatric Genomics Consortium MDD meta-analysis (PGC-MDD1) suggests a modest shared genetic contribution to MDD and AD. Using a (∼10 fold) larger discovery sample, we calculated PRS based on the second wave (PGC-MDD2) of results, in a severe AD case–control target sample. We found significant associations between AD disease status and MDD-PRS derived from both PGC-MDD2 (most informative P-threshold=1.0, P=0.00063, R2=0.533%) and PGCMDD1 (P-threshold=0.2, P=0.00014, R2=0.663%) metaanalyses; the larger discovery sample did not yield additional predictive power. In contrast, calculating PRS in a MDD target sample yielded increased power when using PGC-MDD2 (P-threshold=1.0, P=0.000038, R2=1.34%) versus PGC-MDD1 (P-threshold=1.0, P=0.0013, R2=0.81%). Furthermore, when calculating PGC-MDD2 PRS in a subsample of patients with AD recruited explicitly excluding comorbid MDD, significant associations were still found (n=331; P-threshold=1.0, P=0.042, R2=0.398%). Meanwhile, in the subset of patients in which MDD was not the explicit exclusion criteria, PRS predicted more variance (n=999; P-threshold=1.0, P=0.0003, R2=0.693%). Our findings replicate the reported genetic overlap between AD and MDD and also suggest the need for improved, rigorous phenotyping to identify true shared cross-disorder genetic factors. Larger target samples are needed to reduce noise and take advantage of increasing discovery sample size

Predicting population dynamics from the properties of indiciduals: a cross-level test of dynamic energy budget theory.

Individual-based models (IBMs) are increasingly used to link the dynamics of individuals to higher levels of biological organization. Still, many IBMs are data hungry, species specific, and time-consuming to develop and analyze. Many of these issues would be resolved by using general theories of individual dynamics as the basis for IBMs. While such theories have frequently been examined at the individual level, few cross-level tests exist that also try to predict population dynamics. Here we performed a cross-level test of dynamic energy budget (DEB) theory by parameterizing an individualbased model using individual-level data of the water flea, Daphnia magna, and comparing the emerging population dynamics to independent data from population experiments. We found that DEB theory successfully predicted population growth rates and peak densities but failed to capture the decline phase. Further assumptions on food-dependent mortality of juveniles were needed to capture the population dynamics after the initial population peak. The resulting model then predicted, without further calibration, characteristic switches between small- and large-amplitude cycles, which have been observed for Daphnia. We conclude that cross-level tests help detect gaps in current individual-level theories and ultimately will lead to theory development and the establishment of a generic basis for individual-based models and ecology. © 2013 by The University of Chicago

Development and validation of an individual based Daphnia magna population model: The influence of crowding on population dynamics

An individual-based model was developed to predict the population dynamics of Daphnia magna at laboratory conditions from individual life-history traits observed in experiments with different feeding conditions. Within the model, each daphnid passes its individual life cycle including feeding on algae, aging, growing, developing and – when maturity is reached – reproducing. The modelled life cycle is driven by the amount of ingested algae and the density of the Daphnia population. At low algae densities the population dynamics is mainly driven by food supply, when the densities of algae are high, the limiting factor is “crowding” (a density-dependent mechanism due to chemical substances released by the organisms or physical contact, but independent of food competition). The model was calibrated using data from life cycle tests at flow-through conditions with different levels of algae concentrations. In addition to the average life cycle parameters for different food levels, the variability between the individuals was considered by stochastic assignment of values from the observed distributions in the experiments to each individual property. The model was tested on the individual and the population level. Individual growth and reproduction were tested based on the results of life cycle tests conducted under semi-batch conditions; the population level was considered by testing at different food levels under flow-trough and static conditions, including extinction at starvation conditions. The model was not only able to predict the total abundance of the population over time, but also predicted the size structure in good accordance with the observations. The population dynamics emerge directly from the life cycle of the individual daphnids. It depends on the available food and–this had not been considered in other Daphnia models–on crowding effects due to high Daphnia abundance

Extrapolating ecotoxicological effects from individuals to populations: a dynamic approach based on Dynamic Energy Budget theory and individual-based modelling.

Individual-based models (IBMs) predict how dynamics at higher levels of biological organization emerge from individual-level processes. This makes them a particularly useful tool for ecotoxicology, where the effects of toxicants are measured at the individual level but protection goals are often aimed at the population level or higher. However, one drawback of IBMs is that they require significant effort and data to design for each species. A solution would be to develop IBMs for chemical risk assessment that are based on generic individual-level models and theory. Here we show how one generic theory, Dynamic Energy Budget (DEB) theory, can be used to extrapolate the effect of toxicants measured at the individual level to effects on population dynamics. DEB is based on first principles in bioenergetics and uses a common model structure to model all species. Parameterization for a certain species is done at the individual level and allows to predict population-level effects of toxicants for a wide range of environmental conditions and toxicant concentrations. We present the general approach, which in principle can be used for all animal species, and give an example using Daphnia magna exposed to 3,4-dichloroaniline. We conclude that our generic approach holds great potential for standardized ecological risk assessment based on ecological models. Currently, available data from standard tests can directly be used for parameterization under certain circumstances, but with limited extra effort standard tests at the individual would deliver data that could considerably improve the applicability and precision of extrapolation to the population level. Specifically, the measurement of a toxicant's effect on growth in addition to reproduction, and presenting data over time as opposed to reporting a single EC50 or dose response curve at one time point. © 2013 Springer Science+Business Media New York

Mechanistic modelling of toxicokinetic processess within Mytiophyllum

Effects of chemicals are, in most cases, caused by internal concentrations within organisms which rely on uptake and elimination kinetics. These processes might be key components for assessing the effects of time-variable exposure of chemicals which regularly occur in aquatic systems. However, the knowledge of toxicokinetic patterns caused by time-variable exposure is limited, and gaining such information is complex. In this work, a previously developed mechanistic growth model of Myriophyllum spicatum is coupled with a newly developed toxicokinetic part, providing a model that is able to predict uptake and elimination of chemicals, as well as distribution processes between plant compartments (leaves, stems, roots) of M. spicatum. It is shown, that toxicokinetic patterns, at least for most of the investigated chemicals, can be calculated in agreement with experimental observations, by only calibrating two chemical- specific parameters, the cuticular permeability and a plant/water partition coefficient. Through the model-based determination of the cuticular permeabilities of Isoproturon, Iofensulfuron, Fluridone, Imazamox and Penoxsulam, their toxicokinetic pattern can be described with the model approach. For the use of the model for predicting toxicokinetics of other chemicals, where experimental data is not available, equations are presented that are based on the log (Poct/wat) of a chemical and estimate parameters that are necessary to run the model. In general, a method is presented to analyze time-variable exposure of chemicals more in detail without conducting time and labour intensive experiments

Population-level effects and recovery of aquatic invertebrates after multiple applications of an insecticide

Standard risk assessment of plant protection products (PPP) combines “worst-case” exposure scenarios with effect thresholds using assessment (safety) factors to account for uncertainties. If needed, risks can be addressed applying more realistic conditions at higher tiers, which refine exposure and/or effect assessments using additional data. However, it is not possible to investigate the wide range of potential scenarios experimentally. In contrast, ecotoxicological mechanistic effect models do allow for addressing a multitude of scenarios. Furthermore, they may aid the interpretation of experiments such as mesocosm studies, allowing extrapolation to conditions not covered in experiments. Here, we explore how to use mechanistic effect models in the aquatic risk assessment of a model insecticide (Modelmethrin), applied several times per season but rapidly dissipating between applications. The case study focuses on potential effects on aquatic arthropods, the most sensitive group for this substance. The models provide information on the impact of a number of short exposure pulses on sensitive and/or vulnerable populations and, when impacted, assess recovery. The species to model were selected based on their sensitivity in laboratory and field (mesocosm) studies. The general unified threshold model for survival (GUTS) model, which describes the toxicokinetics and toxicodynamics of chemicals in individuals, was linked to 3 individual-based models (IBM), translating individual survival of sensitive organisms into population-level effects. The impact of pulsed insecticide exposures on populations were modeled using the spatially explicit IBM metapopulation model for assessing spatial and temporal effects of pesticides (MASTEP) for Gammarus pulex, the Chaoborus IBM for populations of Chaoborus crystallinus, and the “IdamP” model for populations of Daphnia magna. The different models were able to predict the potential effects of Modelmethrin applications to key arthropod species inhabiting different aquatic ecosystems; the most sensitive species were significantly impacted unless respective mitigation measures were implemented (buffer zones resulting in reduced exposure). As expected the impact was stronger in shallow ditches as compared to deeper pond scenarios. Furthermore, as expected, recovery depended on factors such as temperature (affecting population growth rate and number of generations) and the occurence of nonimpacted aquatic ecosystems (their frequency and connectivity). These model predictions were largely in line with field observations and/or the results of a mesocosm study, providing additional evidence on the suitability and reliability of the models for risk assessment purposes. Because of their flexibility, models may predict the likelihood of unacceptable effects—based on previously defined protection goals—for a range of insecticide exposure scenarios and freshwater habitat