An energy budget agent-based model of earthworm populations and its application to study the effects of pesticides

Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.

Enhancing the crystallization and orientation of electrospinning poly (lactic acid) (PLLA) by combining with additives

PLLA is a thermoplastic biopolymer and can be used in industrial applications for medical and filtration applications. The brittleness of PLLA is attributed to slow crystallization rates and its glass transition temperature (Tg) is high (60 °C); for this reason, its applications are limited. The orientation, morphology, and crystal structure of the electrospun fibers was investigated by SEM, POM, DSC, FTIR, XRD, and SAXS. Combining with additives leads to a large decrease of fiber diameter, viscosity, and changes of fiber morphology and crystal structure compared to pure PLLA. DSC showed that the Tg of PLLA decreased about 15 °C and there was no change in relaxation enthalpy by the addition of plasticizer. FT-IR indicate a strong interaction between PLLA and additives; a new band appears in the PLLA blend at 1,756 cm−1 at room temperature as a crystalline band without any annealing. In addition, WAXD indicated that the intensities of the two peaks at (200/110) and (203) increased for the blend at room temperature without any annealing in comparison with PLLA; this means that PHB crystallizes in the amorphous region of PLLA. The POM experiments agree with the results from DSC, FTIR, and WAXS measurements, confirming that adding PHB results in an increase in the number of nuclei with much smaller spherulites and enhances the crystallization behavior of this material, thereby improving its potential for applications.

Evaluating the ability of process based models to project sea-level change

We evaluate the ability of process based models to reproduce observed global mean sea-level change. When the models are forced by changes in natural and anthropogenic radiative forcing of the climate system and anthropogenic changes in land-water storage, the average of the modelled sea-level change for the periods 1900–2010, 1961–2010 and 1990–2010 is about 80%, 85% and 90% of the observed rise. The modelled rate of rise is over 1 mm yr−1 prior to 1950, decreases to less than 0.5 mm yr−1 in the 1960s, and increases to 3 mm yr−1 by 2000. When observed regional climate changes are used to drive a glacier model and an allowance is included for an ongoing adjustment of the ice sheets, the modelled sea-level rise is about 2 mm yr−1 prior to 1950, similar to the observations. The model results encompass the observed rise and the model average is within 20% of the observations, about 10% when the observed ice sheet contributions since 1993 are added, increasing confidence in future projections for the 21st century. The increased rate of rise since 1990 is not part of a natural cycle but a direct response to increased radiative forcing (both anthropogenic and natural), which will continue to grow with ongoing greenhouse gas emissions

Information content and forecasting ability of sentiment indicators: case of real estate market

We evaluate a number of real estate sentiment indices to ascertain current and forward-looking information content that may be useful for forecasting demand and supply activities. Analyzing the dynamic relationships within a Vector Auto-Regression (VAR) framework and using the quarterly US data over 1988-2010, we test the efficacy of several sentiment measures by comparing them with other coincident economic indicators. Overall, our analysis suggests that the sentiment in real estate convey valuable information that can help predict changes in real estate returns. These findings have important implications for investment decisions, from consumers' as well as institutional investors' perspectives.

Assessing the ability of rural agrarian areas to provide Cultural Ecosystem Services (CES): a Multi Scale Social Indicator Framework (MSIF)

Assessing the ways in which rural agrarian areas provide Cultural Ecosystem Services (CES) is proving difficult to achieve. This research has developed an innovative methodological approach named as Multi Scale Indicator Framework (MSIF) for capturing the CES embedded into the rural agrarian areas. This framework reconciles a literature review with a trans-disciplinary participatory workshop. Both of these sources reveal that societal preferences diverge upon judgemental criteria which in turn relate to different visual concepts that can be drawn from analysing attributes, elements, features and characteristics of rural areas. We contend that it is now possible to list a group of possible multi scale indicators for stewardship, diversity and aesthetics. These results might also be of use for improving any existing European indicators frameworks by also including CES. This research carries major implications for policy at different levels of governance, as it makes possible to target and monitor policy instruments to the physical rural settings so that cultural dimensions are adequately considered. There is still work to be developed on regional specific values and thresholds for each criteria and its indicator set. In practical terms, by developing the conceptual design within a common framework as described in this paper, a considerable step forward towards the inclusion of the cultural dimension in European wide assessments can be made.

A variational approach to retrieve rain rate by combining information from rain gauges, radars, and microwave links

Accurate and reliable rain rate estimates are important for various hydrometeorological applications. Consequently, rain sensors of different types have been deployed in many regions. In this work, measurements from different instruments, namely, rain gauge, weather radar, and microwave link, are combined for the first time to estimate with greater accuracy the spatial distribution and intensity of rainfall. The objective is to retrieve the rain rate that is consistent with all these measurements while incorporating the uncertainty associated with the different sources of information. Assuming the problem is not strongly nonlinear, a variational approach is implemented and the Gauss–Newton method is used to minimize the cost function containing proper error estimates from all sensors. Furthermore, the method can be flexibly adapted to additional data sources. The proposed approach is tested using data from 14 rain gauges and 14 operational microwave links located in the Zürich area (Switzerland) to correct the prior rain rate provided by the operational radar rain product from the Swiss meteorological service (MeteoSwiss). A cross-validation approach demonstrates the improvement of rain rate estimates when assimilating rain gauge and microwave link information.

Volatile profile of Spanish Cistus plants as sources of antimicrobials for industrial applications

Cistus is a plant genus traditionally used in folk medicine as remedy for several microbial disorders and infections. The abundance of Cistus spp. in the Iberian Peninsula together with their ability to renew after wildfire contribute to their profitability as suppliers of functional ingredients. The aim of this study was to provide a comprehensive characterization of the volatile profile of different Cistus plants grown in Spain:Cistus ladanifer L., Cistus albidus L., Cistus salviifolius L., and Cistus clusii Dunal (the latter has not been studied before). A system combining headspace solid-phase microextraction and gas chromatography coupled to mass spectrometry (HS-SPME-GC–MS) was implemented; thereby, the volatile compounds were extracted and analyzed in a fast, reliable and environment-friendly way. A total of 111 volatile compounds were identified, 28 of which were reported in Cistus for the first time. The most abundant components of the samples (mono and sesquiterpenes) have been previously reported as potent antimicrobial agents. Therefore, this work reveals the potential use of the Cistus spp. studied as natural sources of antimicrobial compounds for industrial production of cosmeceuticals, among other applications.

Effects of agricultural management practices on earthworm populations and crop yield: validation and application of a mechanistic modelling approach

There is little consensus on how agriculture will meet future food demands sustainably. Soils and their biota play a crucial role by mediating ecosystem services that support agricultural productivity. However, a multitude of site-specific environmental factors and management practices interact to affect the ability of soil biota to perform vital functions, confounding the interpretation of results from experimental approaches. Insights can be gained through models, which integrate the physiological, biological and ecological mechanisms underpinning soil functions. We present a powerful modelling approach for predicting how agricultural management practices (pesticide applications and tillage) affect soil functioning through earthworm populations. By combining energy budgets and individual-based simulation models, and integrating key behavioural and ecological drivers, we accurately predict population responses to pesticide applications in different climatic conditions. We use the model to analyse the ecological consequences of different weed management practices. Our results demonstrate that an important link between agricultural management (herbicide applications and zero, reduced and conventional tillage) and earthworms is the maintenance of soil organic matter (SOM). We show how zero and reduced tillage practices can increase crop yields while preserving natural ecosystem functions. This demonstrates how management practices which aim to sustain agricultural productivity should account for their effects on earthworm populations, as their proliferation stimulates agricultural productivity. Synthesis and applications. Our results indicate that conventional tillage practices have longer term effects on soil biota than pesticide control, if the pesticide has a short dissipation time. The risk of earthworm populations becoming exposed to toxic pesticides will be reduced under dry soil conditions. Similarly, an increase in soil organic matter could increase the recovery rate of earthworm populations. However, effects are not necessarily additive and the impact of different management practices on earthworms depends on their timing and the prevailing environmental conditions. Our model can be used to determine which combinations of crop management practices and climatic conditions pose least overall risk to earthworm populations. Linking our model mechanistically to crop yield models would aid the optimization of crop management systems by exploring the trade-off between different ecosystem services.

A critical evaluation of the ability of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) thermal infrared red-green-blue rendering to identify dust events: theoretical analysis

Using a combination of idealized radiative transfer simulations and a case study from the first field campaign of the Saharan Mineral Dust Experiment (SAMUM) in southern Morocco, this paper provides a systematic assessment of the limitations of the widely used Spinning Enhanced Visible and Infrared Imager (SEVIRI) red-green-blue (RGB) thermal infrared dust product. Both analyses indicate that the ability of the product to identify dust, via its characteristic pink coloring, is strongly dependent on the column water vapor, the lower tropospheric lapse rate, and dust altitude. In particular, when column water vapor exceeds ∼20–25 mm, dust presence, even for visible optical depths of the order 0.8, is effectively masked. Variability in dust optical properties also has a marked impact on the imagery, primarily as a result of variability in dust composition. There is a moderate sensitivity to the satellite viewing geometry, particularly in moist conditions. The underlying surface can act to confound the signal seen through variations in spectral emissivity, which are predominantly manifested in the 8.7μm SEVIRI channel. In addition, if a temperature inversion is present, typical of early morning conditions over the Sahara and Sahel, an increased dust loading can actually reduce the pink coloring of the RGB image compared to pristine conditions. Attempts to match specific SEVIRI observations to simulations using SAMUM measurements are challenging because of high uncertainties in surface skin temperature and emissivity. Recommendations concerning the use and interpretation of the SEVIRI RGB imagery are provided on the basis of these findings.

Combining satellite observations and reanalysis energy transports to estimate global net surface energy fluxes 1985-2012

Two methods are developed to estimate net surface energy fluxes based upon satellite-based reconstructions of radiative fluxes at the top of atmosphere and the atmospheric energy tendencies and transports from the ERA-Interim reanalysis. Method 1 applies the mass adjusted energy divergence from ERA-Interim while method 2 estimates energy divergence based upon the net energy difference at the top of atmosphere and the surface from ERA-Interim. To optimise the surface flux and its variability over ocean, the divergences over land are constrained to match the monthly area mean surface net energy flux variability derived from a simple relationship between the surface net energy flux and the surface temperature change. The energy divergences over the oceans are then adjusted to remove an unphysical residual global mean atmospheric energy divergence. The estimated net surface energy fluxes are compared with other data sets from reanalysis and atmospheric model simulations. The spatial correlation coefficients of multi-annual means between the estimations made here and other data sets are all around 0.9. There are good agreements in area mean anomaly variability over the global ocean, but discrepancies in the trend over the eastern Pacific are apparent.

In vitro study on the cell adhesion ability of immobilized lactobacilli on natural supports

The aim of the present study was to investigate the effect of probiotic immobilization onto wheat grains, both wet and freeze dried, on the adhesion properties of the probiotic cells and make comparisons with wet and freeze dried free cells. Lactobacillus casei ATCC 393 and Lactobacillus plantarum NCIMB 8826 were used as model probiotic strains. The results showed satisfactory adhesion ability of free cells to a monolayer of Caco-2 cells (> 1000 CFU/100 Caco-2 cells for wet cells). Cell immobilization resulted in a significant decrease in adhesion, for both wet and freeze dried formulations, most likely because immobilized cells did not have direct access to the Caco-2 cells, but it still remained in adequate levels (> 100 CFU/100 Caco-2 cells for wet cells). No clear correlation could be observed between cell adhesion and the hydrophobicity of the bacterial cells, measured by the hexadecane adhesion assay. Most notably, immobilization enhanced the monolayer integrity of Caco-2 cells, demonstrated by a more than 2-fold increase in transepithelial electrical resistance (TEER) compared to free cells. SEM micrographs ascertained the adhesion of both immobilized and free cells to the brush border microvilli. Finally, the impact of the food matrix on the adhesion properties of probiotic bacteria and on the design of novel functional products is discussed.

Working memory, reading ability and the effects of distance and typicality on anaphor resolution in children

We investigated the time course of anaphor resolution in children and whether this is modulated by individual differences in working memory and reading skill. The eye movements of 30 children (10-11 years) were monitored as they read short paragraphs in which (i) the semantic typicality of an antecedent and (ii) its distance in relation to an anaphor, were orthogonally manipulated. Children showed effects of distance and typicality on the anaphor itself, and also on the word to the right of the anaphor, suggesting that anaphoric processing begins immediately but continues after the eyes have left the anaphor. Furthermore, children showed no evidence of resolving anaphors in the most difficult condition (distant atypical antecedent), suggesting that anaphoric processing that is demanding may not occur online in children of this age. Finally, working memory capacity and reading comprehension skill affect the magnitude and time course of typicality and distance effects during anaphoric processing.

A thermoreversible supramolecular polyurethane with excellent healing ability at 45 °C

We report the synthesis and characterization of a healable, elastomeric shape recovery supramolecular polyurethane whose properties result from self-complementary π−π stacking and hydrogen bonding interactions plus phase separation. ESEM analysis and photographic images have revealed that this material can heal at 45 °C in 15 min to recover the mechanical properties of the pristine material with healing efficiencies >99%. This supramolecular polyurethane is also able to recover an applied strain of 25% within 5 min of release of the load.

The blended approach to real estate allocations: performance implications of combining an exposure to German Spezialfonds with Global Listed Real Estate Securities

This paper seeks to increase the understanding of the performance implications for investors who choose to combine an unlisted real estate portfolio (in this case German Spezialfonds) with a (global) listed real estate element. We call this a “blended” approach to real estate allocations. For the avoidance of doubt, in this paper we are dealing purely with real estate equity (listed and unlisted) allocations, and do not incorporate real estate debt (listed or unlisted) or direct property into the process. A previous paper (Moss and Farrelly 2014) showed the benefits of the blended approach as it applied to UK Defined Contribution Pension Schemes. The catalyst for this paper has been the recent attention focused on German pension fund allocations, which have a relatively low (real estate) equity content, and a high bond content. We have used the MSCI Spezialfonds Index as a proxy for domestic German institutional real estate allocations, and the EPRA Global Developed Index as a proxy for a global listed real estate allocation. We also examine whether a rules based trading strategy, in this case Trend Following, can improve the risk adjusted returns above those of a simple buy and hold strategy for our sample period 2004-2015. Our findings are that by blending a 30% global listed portfolio with a 70% allocation (as opposed to a typical 100% weighting) to Spezialfonds, the real estate allocation returns increase from 2.88% p.a. to 5.42% pa. Volatility increases, but only to 6.53%., but there is a noticeable impact on maximum drawdown which increases to 19.4%. By using a Trend Following strategy raw returns are improved from 2.88% to 6.94% p.a. , The Sharpe Ratio increases from 1.05 to 1.49 and the Maximum Drawdown ratio is now only 1.83% compared to 19.4% using a buy and hold strategy . Finally, adding this (9%) real estate allocation to a mixed asset portfolio allocation typical for German pension funds there is an improvement in both the raw return (from 7.66% to 8.28%) and the Sharpe Ratio (from 0.91 to 0.98).

Young Children's Ability to Engage in Cognitive Therapy Tasks: Associations With Age and Educational Experience

Abstract. In two linked studies we examined children’s performance on tasks required for participation in cognitive therapy. In Study 1 we piloted some new tasks with children aged 5 to 11 years. In study 2 the effects of IQ, age and educational experience were examined in children aged 5 to 7 years. In study 1, 14 children aged 5 to 11 completed three tasks related to cognitive therapy; generating post-event attributions, naming emotions, and linking thoughts and feelings. Study 2 used a between-subjects design in which 72 children aged 5, 6, or 7 years from two primary schools completed the three tasks and the Block Design and Vocabulary sub-tests from the WISC III or WPPSI-R. Children were tested individually during the school day. All measures were administered on the same occasion. In study 2 administration order of the cognitive therapy task and the WISC III/WPPSI-R were randomized. The majority of children demonstrated some ability on each of the three tasks. In study 2, performance was associated with school and with IQ but not with age. There were no gender differences. Children attending a school with an integrated thinking skills programme and those with a higher 1Q were more successful on the cognitive therapy tasks. These results suggest that many young children could engage in cognitive therapy given age-appropriate materials. The effects of training in relevant meta-cognitive skills on children’s ability to use concepts in CBT may warrant further research. Keywords: Cognitive behaviour therapy, young children, cognitive development