•Uncertainty about validation is a challenge in using models for decision support.•Confusing terminology is a major cause of scepticism about model application.•Based on the modelling cycle, we ...devised a set of terms related to model evaluation.•We suggest “evaludation” to describe the entire process of model's quality.•Ecological modelling methods are too diverse to provide simple evaluation protocols.
Confusion about model validation is one of the main challenges in using ecological models for decision support, such as the regulation of pesticides. Decision makers need to know whether a model is a sufficiently good representation of its real counterpart and what criteria can be used to answer this question. Unclear terminology is one of the main obstacles to a good understanding of what model validation is, how it works, and what it can deliver. Therefore, we performed a literature review and derived a standard set of terms. ‘Validation’ was identified as a catch-all term, which is thus useless for any practical purpose. We introduce the term ‘evaludation’, a fusion of ‘evaluation’ and ‘validation’, to describe the entire process of assessing a model's quality and reliability. Considering the iterative nature of model development, the modelling cycle, we identified six essential elements of evaludation: (i) ‘data evaluation’ for scrutinising the quality of numerical and qualitative data used for model development and testing; (ii) ‘conceptual model evaluation’ for examining the simplifying assumptions underlying a model's design; (iii) ‘implementation verification’ for testing the model's implementation in equations and as a computer programme; (iv) ‘model output verification’ for comparing model output to data and patterns that guided model design and were possibly used for calibration; (v) ‘model analysis’ for exploring the model's sensitivity to changes in parameters and process formulations to make sure that the mechanistic basis of main behaviours of the model has been well understood; and (vi) ‘model output corroboration’ for comparing model output to new data and patterns that were not used for model development and parameterisation. Currently, most decision makers require ‘validating’ a model by testing its predictions with new experiments or data. Despite being desirable, this is neither sufficient nor necessary for a model to be useful for decision support. We believe that the proposed set of terms and its relation to the modelling cycle can help to make quality assessments and reality checks of ecological models more comprehensive and transparent.
Digital health technologies may support the management and prevention of disease through personalized lifestyle interventions. Wearables and smartphones are increasingly used to continuously monitor ...health and disease in everyday life, targeting health maintenance. Here, we aim to demonstrate the potential of wearables and smartphones to (1) detect eating moments and (2) predict and explain individual glucose levels in healthy individuals, ultimately supporting health self-management. Twenty-four individuals collected continuous data from interstitial glucose monitoring, food logging, activity, and sleep tracking over 14 days. We demonstrated the use of continuous glucose monitoring and activity tracking in detecting eating moments with a prediction model showing an accuracy of 92.3% (87.2–96%) and 76.8% (74.3–81.2%) in the training and test datasets, respectively. Additionally, we showed the prediction of glucose peaks from food logging, activity tracking, and sleep monitoring with an overall mean absolute error of 0.32 (+/−0.04) mmol/L for the training data and 0.62 (+/−0.15) mmol/L for the test data. With Shapley additive explanations, the personal lifestyle elements important for predicting individual glucose peaks were identified, providing a basis for personalized lifestyle advice. Pending further validation of these digital biomarkers, they show promise in supporting the prevention and management of type 2 diabetes through personalized lifestyle recommendations.
Urban rivers may receive contamination from various sources including point sources like domestic sewage and nonpoint sources (e.g., runoff), resulting in contamination with various chemicals. This ...study investigated the occurrence of emerging organic contaminants (3 endocrine disrupting compounds (EDCs), and 17 pharmaceuticals and personal care products (PPCPs)) in six urban rivers of a representative subtropical city, Guangzhou (southern China). Our results showed that EDCs and personal care products were frequently detected in the water phase and sediment phase. 4-nonylphenol (4-NP) was the most predominant compound with the highest concentration of 5050ng/L in the water phase and 14,400ng/g dry weight (dw) in the sediment. Generally, higher total concentrations of EDCs and PPCPs were detected in the four urban streams compared to the main stream Zhujiang River and the Liuxi River at the suburb area. A screening-level risk assessment showed that 4-nonylphenol and triclosan (TCS) pose potential risks to aquatic organisms in most sampling sites. For individual taxa, 4-NP may pose risks to various groups of aquatic organisms, while TCS only might pose high risks to algae.
Higher contamination of EDCs and PPCPs was observed in rivers in urban area; 4-nonylphenol and triclosan showed RQs>1 in >70% of the reported area.
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•Investigation of EDCs and PPCPs in urban rivers in megacity Guangzhou;•Higher contamination of EDCs and PPCPs was observed in rivers in urban area;•Concentration levels of EDCs and PPCPs were consistent with physicochemical parameters;•4-nonylphenol and triclosan showed RQs >1 in more than 70% of the reported area;
Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, ...additively or antagonistically. Here, we use process‐based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer‐resource) for a two‐stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence. Our results help explain why meta‐analyses of multiple stressor experimental results have struggled to identify predictors of consistently non‐additive interactions in the natural environment. Experiments run over extended temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management.
Here, we use process‐based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer‐resource) for a two‐stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic inter‐actions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence
Nanopesticides or nano plant protection products represent an emerging technological development that, in relation to pesticide use, could offer a range of benefits including increased efficacy, ...durability, and a reduction in the amounts of active ingredients that need to be used. A number of formulation types have been suggested including emulsions (e.g., nanoemulsions), nanocapsules (e.g., with polymers), and products containing pristine engineered nanoparticles, such as metals, metal oxides, and nanoclays. The increasing interest in the use of nanopesticides raises questions as to how to assess the environmental risk of these materials for regulatory purposes. Here, the current approaches for environmental risk assessment of pesticides are reviewed and the question of whether these approaches are fit for purpose for use on nanopesticides is addressed. Potential adaptations to existing environmental risk assessment tests and procedures for use with nanopesticides are discussed, addressing aspects such as analysis and characterization, environmental fate and exposure assessment, uptake by biota, ecotoxicity, and risk assessment of nanopesticides in aquatic and terrestrial ecosystems. Throughout, the main focus is on assessing whether the presence of the nanoformulation introduces potential differences relative to the conventional active ingredients. The proposed changes in the test methodology, research priorities, and recommendations would facilitate the development of regulatory approaches and a regulatory framework for nanopesticides.
Field collected aquatic invertebrates are often used as test organisms in the refinement of the standard Tier 1 risk assessment of various pollutants. This approach can provide insights into the ...effects of pollutants on the natural environment. However, researchers often pragmatically select test organisms of a specific sex and/or size, which may not represent the sensitivity of the whole population. To investigate such intraspecies sensitivity differences, we performed standard acute toxicity and toxicokinetic tests with different size classes and sex of Gammarus pulex and Asellus aquaticus. Furthermore, toxicokinetics and toxicodynamics models were used to understand the mechanism of the intraspecies sensitivity differences. We used neonates, juveniles and male and female adults in separate dedicated experiments, in which we exposed the animals to imidacloprid and its bioactive metabolite, imidacloprid-olefin. For both species, we found that neonates were the most sensitive group. For G. pulex, the sensitivity decreased linearly with size, which can be explained by the size-related uptake rate constant in the toxicokinetic process and size-related threshold value in the toxicodynamic process. For A. aquaticus, female adults were least sensitive to imidacloprid, which could be explained by a low internal biotransformation of imidacloprid to imidacloprid-olefin. Besides, imidacloprid-olefin was more toxic than imidacloprid to A. aquaticus, with differences being 8.4 times for females and 2.7 times for males. In conclusion, we established size-related sensitivity differences for G. pulex and sex-related sensitivity for A. aquaticus, and intraspecies differences can be explained by both toxicokinetic and toxicodynamic processes. Our findings suggest that to protect populations in the field, we should consider the size and sex of focal organisms and that a pragmatic selection of test organisms of equal size and/or sex can underestimate the sensitivities of populations in the field.
•For both species, neonates were the most sensitive group to imidacloprid.•For Gammarus pulex, the uptake rate constant decreased with size.•For Gammarus pulex, the threshold value increased with size.•For Asellus aquaticus, the biotransformation of IMI was different in sexes.•Toxicokinetics – toxicodynamics models explain intraspecies sensitivity well.
Estimating antibiotic pollution and antibiotic resistance development risks in environmental compartments is important to design management strategies that advance our stewardship of antibiotics. In ...this study we propose a modelling approach to estimate the risk of antibiotic resistance development in environmental compartments and demonstrate its application in aquaculture production systems. We modelled exposure concentrations for 12 antibiotics used in Vietnamese Pangasius catfish production using the ERA-AQUA model. Minimum selective concentration (MSC) distributions that characterize the selective pressure of antibiotics on bacterial communities were derived from the European Committee on Antimicrobial Susceptibility Testing (EUCAST) Minimum Inhibitory Concentration dataset. The antibiotic resistance development risk (RDR) for each antibiotic was calculated as the probability that the antibiotic exposure distribution exceeds the MSC distribution representing the bacterial community. RDRs in pond sediments were nearly 100% for all antibiotics. Median RDR values in pond water were high for the majority of the antibiotics, with rifampicin, levofloxacin and ampicillin having highest values. In the effluent mixing area, RDRs were low for most antibiotics, with the exception of amoxicillin, ampicillin and trimethoprim, which presented moderate risks, and rifampicin and levofloxacin, which presented high risks. The RDR provides an efficient means to benchmark multiple antibiotics and treatment regimes in the initial phase of a risk assessment with regards to their potential to develop resistance in different environmental compartments, and can be used to derive resistance threshold concentrations.
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•A modelling approach is proposed to assess antibiotic resistance development risks.•The approach is grounded on probabilistic risk assessment theory.•It was applied to assess resistance development in pond aquaculture environments.•The study shows that pond sediments are hot-spots for resistance development.•The modelling approach can be used in the prospective risk assessment of antibiotics.
In this study we propose a modelling approach to estimate antibiotic resistance development risks in environmental compartments and apply it to estimate risks in an intensive aquaculture pond scenario. Our study indicates that aquaculture pond sediments can be considered hot-spots for antibiotic resistance development and sets the ground for the inclusion of antibiotic resistance endpoints in the prospective risk assessment of antibiotics.
The use of organophosphate pesticides (OPPs) to protect a variety of crops has increased in Bangladesh. OPPs may contaminate surrounding aquatic environments through several routes including spray ...drift, surface runoff and groundwater leaching. Since it is unknown how much OPP end ups in aquatic environment in Bangladesh, the objectives of the present study were to quantify the residues of ten most commonly used OPPs in water and sediment of water bodies of north-west Bangladesh and to assess their ecological risks for aquatic organisms. The risks of the pesticides in surface water and sediment were assessed using a first-tier risk quotient (RQ) approach. The higher-tier PERPEST model was used to refine the ecological risks of pesticides when RQ indicated a potential risk. Results showed the most frequently detected pesticides that appeared in high concentrations were chlorpyrifos, diazinon and quinalphos in surface water and sediment. The highest concentration of OPPs measured in water was 9.1 μg chlorpyrifos/L (median of 1.95 μg/L), while this was 51 μg diazinon/kg dw (median of 11 μg/kg dw) for sediment. Furthermore, results showed high acute and/or chronic RQs (RQ > 1) in surface water and sediment for chlorpyrifos, diazinon, quinalphos, malathion and fenitrothion. The higher-tier PERPEST model confirmed risks of chlorpyrifos, diazinon, quinalphos and fenitrothion for aquatic insects, micro- and macro-crustaceans which were previously derived by RQ-based risk assessment for aquatic organisms. Furthermore, the results of the PERPEST model also indicated possible indirect effects of these pesticides on algae and macrophytes, community metabolism, rotifers and other macro-invertebrates.
•Chlorpyrifos, diazinon and quinalphos were more frequent in water and sediment samples.•The highest concentration of OPPs in water was measured for chlorpyrifos as 9.1 μg/L.•The highest concentration of OPPs in sediment was measured for diazinon as 51 μg/kg.•RQs showed higher risks of most OPPs for Daphnia than fish and algae.•The higher-tier PERPEST model refined the risks for invertebrates.
We used resonant inelastic x-ray scattering to reveal the nature of magnetic interactions in Sr2IrO4, a 5d transition-metal oxide with a spin-orbit entangled ground state and J(eff)=1/2 magnetic ...moments. The magnon dispersion in Sr2IrO4 is well-described by an antiferromagnetic Heisenberg model with an effective spin one-half on a square lattice, which renders the low-energy effective physics of Sr2IrO4 much akin to that in superconducting cuprates. This point is further supported by the observation of exciton modes in Sr2IrO4, whose dispersion is strongly renormalized by magnons, which can be understood by analogy to hole propagation in the background of antiferromagnetically ordered spins in the cuprates.
Doping graphene with metal contacts Giovannetti, G; Khomyakov, P A; Brocks, G ...
Physical review letters,
07/2008, Volume:
101, Issue:
2
Journal Article
Peer reviewed
Open access
Making devices with graphene necessarily involves making contacts with metals. We use density functional theory to study how graphene is doped by adsorption on metal substrates and find that weak ...bonding on Al, Ag, Cu, Au, and Pt, while preserving its unique electronic structure, can still shift the Fermi level with respect to the conical point by approximately 0.5 eV. At equilibrium separations, the crossover from p-type to n-type doping occurs for a metal work function of approximately 5.4 eV, a value much larger than the graphene work function of 4.5 eV. The numerical results for the Fermi level shift in graphene are described very well by a simple analytical model which characterizes the metal solely in terms of its work function, greatly extending their applicability.
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