Inhibition of rainbow trout acetylcholinesterase by aqueous and suspended particle-associated organophosphorous insecticides

Cadmium (Cd) adsorption on 14 non-calcareous New Jersey soils was investigated with a batch method. Both adsorption edge and isotherm experiments were conducted covering a wide range of soil composition, e.g. soil organic carbon (SOC) concentration ranging from 0.18% to 7.15%, and varying Cd concentrations and solution pH. The SOC and solution pH were the most important parameters controlling Cd partition equilibrium between soils and solutions in our experimental conditions. The Windermere humic aqueous model (WHAM) was used to calculate Cd adsorption on soils. The effect of solution chemistry (various pH and Cd concentrations) on Cd adsorption can be well accounted for by WHAM. For different soil compositions, SOC concentration is the most important parameter for Cd binding. Only a fraction of SOC, the so-called active organic carbon (AOC), is responsible for Cd binding. We found a linear relationship between SOC and AOC based on the adsorption edge data. The linear relationship was validated by the independent data sets: adsorption isotherm data, which presumably can be used to predict Cd partition equilibrium across a wide range of soil compositions. The modeling approach presented in this study helps to quantitatively predict Cd behavior in the environment.     

Validation of an ecosystem modelling approach as a tool for ecological effect assessments

In ecotoxicology, derivation of a "safe" environmental concentration is usually achieved by the use of extrapolation factors or by statistical extrapolation from a set of single species toxicity data. These approaches ignore ecological interactions between species in the field. An ecology-based alternative to this pragmatic approach can be ecosystem modelling, which can account for ecological interactions. However, it is largely unexplored how well the predictions of these models quantitatively agree with large-scale experimental studies. Therefore, we evaluated the capacity of a flexible ecosystem model to predict population and ecosystem-level no observed effect concentrations (NOECs) of 7 organic toxicants. These NOECs were compared with population and ecosystem-NOECs observed in 11 micro- and mesocosm studies. For each of the latter studies, the model was customized to account for the specific ecological interactions within these systems and combined with appropriate single-species toxicity data from literature. Population-NOEC predictions were accurate, or at least protective, for 60, and 85% of all considered model populations, respectively. For all 11 studies, a protective ecosystem-NOEC could be derived, being accurate in 7 cases, and conservative in 4 cases. In general, it can be stated that this type of models can serve as an ecology-based alternative to current extrapolation techniques in EEAs and water quality standard setting.     

Environmental risk assessment of metals: tools for incorporating bioavailability

In this paper, some of the main processes and parameters which affect metal bioavailability and toxicity in the aquatic environment and its implications for metal risk assessment procedures will be discussed. It has become clear that, besides chemical processes (speciation, complexation), attention should also be given to physiological aspects for predicting metal toxicity. The development of biotic ligand models (BLMs), which combine speciation models with more biologically oriented models (e.g. GSIM), has offered an answer to this need. The various BLMs which have been developed and/or refined for a number of metals (e.g. Cu, Ag, Zn) and species (algae, crustaceans, fish) are discussed here. Finally, the potential of the BLM approach is illustrated through a theoretical exercise in which chronic zinc toxicity to Daphnia magna is predicted in three regions, taking the physico-chemical characteristics of these areas into account.     

Assumptions in ecosystem service assessments: Increasing transparency for conservation

Conservation efforts are increasingly supported by ecosystem service assessments. These assessments depend on complex multi-disciplinary methods, and rely on a number of assumptions which reduce complexity. If assumptions are ambiguous or inadequate, misconceptions and misinterpretations may arise when interpreting results of assessments. An interdisciplinary understanding of assumptions in ecosystem service science is needed to provide consistent conservation recommendations. Here, we synthesise and elaborate on 12 prevalent types of assumptions in ecosystem service assessments. These comprise conceptual and ethical foundations of the ecosystem service concept, assumptions on data collection, indication, mapping, and modelling, on socio-economic valuation and value aggregation, as well as about using assessment results for decision-making. We recommend future assessments to increase transparency about assumptions, and to test and validate them and their potential consequences on assessment reliability. This will support the taking up of assessment results in conservation science, policy and practice.Electronic supplementary materialThe online version of this article (10.1007/s13280-020-01379-9) contains supplementary material, which is available to authorized users.     

How prepared is prepared enough?

Decisions about disaster preparedness are rarely informed by cost‐benefit analyses. This paper presents an economic model to address the thorny question, ‘how prepared is prepared enough?’ Difficulties related to the use of cost‐benefit analysis in the field of disaster management concern the tension between the large number of high‐probability events that can be handled by a single emergency response unit and the small number of low‐probability events that must be handled by a large number of them. A further special feature of disaster management concerns the opportunity for cooperation between different emergency response units. To account for these issues, we introduce a portfolio approach. Our analysis shows that it would be useful to define disaster preparedness not in terms of capacities, but in terms of the frequency with which response capacity is expected to fall short.     

Pesticide risk mitigation by vegetated treatment systems: a meta-analysis

Pesticides entering agricultural surface waters threaten water quality and aquatic communities. Recently, vegetated treatment systems (VTSs) (e.g., constructed wetlands and vegetated ditches) have been proposed as pesticide risk mitigation measures. However, little is known about the effectiveness of VTSs in controlling nonpoint source pesticide pollution and factors relevant for pesticide retention within these systems. Here, we conducted a meta-analysis on pesticide mitigation by VTSs using data from the scientific literature and the European LIFE ArtWET project. Overall, VTSs effectively reduced pesticide exposure levels (i.e., the majority of pesticide retention performances was >70%). A multiple linear regression analysis of 188 retention performance cases identified the two pesticide properties, organic carbon sorption coefficient value and water-phase 50% dissipation time, as well as the VTS characteristics overall plant coverage and hydraulic retention time for targeting high efficacy of pesticide retention. The application of a Tier I risk assessment (EU Uniform Principle) revealed a higher toxicity reduction for hydrophobic and nonpersistent insecticides compared with less sorptive and not readily degradable herbicides and fungicides. Overall, nearly half (48.5%) of all pesticide field concentrations ( = 130) failed Tier I standard risk assessment at the inlet of VTSs, and 29.2% of all outlet concentrations exceeded conservative acute threshold levels. We conclude that VTSs are a suitable and effective risk mitigation strategy for agricultural nonpoint source pesticide pollution of surface waters. Further research is needed to improve their overall efficacy in retaining pesticides.     

LIMPACT: Ein Expertensystem zur Abschätzung der Pflanzenschutzmittel-Belastung kleiner Fließgewässer mittels der Makroinvertebraten-Fauna

The development and the evaluation of a biological indicator system for pesticide pollution in streams are presented. For small headwater streams with an agricultural catchment area, the expert system LIMPACT estimates the pesticide contamination according to the four classes of Not Detected, Low, Moderate and High contamination without any specification of the chemical agents. The input parameters are the abundance data of benthic macroinvertebrate taxa within four time frames in a year (March/April; May/June; July/August; September/October) and 9 basic water-quality and morphological parameters. The heuristic knowledge base was developed with the shell-kit D3 and contains diagnostic rules with scores to either establish or de-establish a contamination class. We differentiate between positive indicator taxa, which indicate contamination by high abundance values and positive abundance dynamics, and negative indicator taxa, a high abundance of which rules out contamination and indicates an uncontaminated site. We analysed 39 taxa and found 13 positive and 24 negative indicators. The database is comprised of 157 investigations per stream and year. For the evaluation of LIMPACT, we used the same cases. The correct diagnosis for the 157 investigations per stream and year is established by LIMPACT in 66.7 to 85.5% of the cases, with better results for uncontaminated sites. In most of the remaining cases no diagnosis is established instead of an incorrect one.     

Understanding employee innovative behavior: Integrating the social network and leader–member exchange perspectives

By integrating social network theory and leader–member exchange (LMX) theory, we explore the effects of three types of social relationships on employee innovative behavior: weak ties outside the group, LMX, and strong ties within the group. The results from a sample in a high‐tech firm showed that LMX fully mediated the positive relationship between out‐group weak ties and innovative behavior. Furthermore, within‐group strong ties negatively moderated the second stage of this indirect relationship, such that LMX was positively and significantly related to innovative behavior only when the number of within‐group strong ties was low. The theoretical and practical implications of these findings are discussed. Copyright © 2015 John Wiley & Sons, Ltd.