The Syntax of Pronominal Subjects in L2 Spanish: Comparing Two L2 Populations with Different Exposure

The purpose of this article is two-fold. First, via a critical review of available studies on the adult L2 resetting of the Null-Subject Parameter (NSP) and in light of a typologically wide sampling of languages, we conclude that the NSP cluster is much narrower in scope than is reflected in the design and discussion of most L2 studies. Secondly, we present original research on the L2 resetting of the NSP by two groups of adult English intermediate learners of L2 Spanish: a study-abroad group and a class-room only group. We seek to quantify the extent to which study-abroad experience, that is, increased exposure to native input, is beneficial specifically as it relates to the acquisition of new functional features needed for parameter re-setting (cf. Isabelli 2004). Despite the observable and clandestine linguistic benefits to study-abroad, our data suggest that for the resetting of the NSP, at least, such exposure to native input is not particularly gainful.

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).

Hydrocarbon biodegradation and soil microbial community response to repeated oil exposure

Bioremediation strategies continue to be developed to mitigate the environmental impact of petroleum hydrocarbon contamination. This study investigated the ability of soil microbiota, adapted by prior exposure, to biodegrade petroleum. Soils from Barrow Is. (W. Australia), a class A nature reserve and home to Australia’s largest onshore oil field, were exposed to Barrow production oil (50 ml/kg soil) and incubated (25 °C) for successive phases of 61 and 100 days. Controls in which oil was not added at Phase I or II were concurrently studied and all treatments were amended with the same levels of additional nutrient and water to promote microbial activity. Prior exposure resulted in accelerated biodegradation of most, but not all, hydrocarbon constituents in the production oil. Molecular biodegradation parameters measured using gas chromatography–mass spectrometry (GC–MS) showed that several aromatic constituents were degraded more slowly with increased oil history. The unique structural response of the soil microbial community was reflected by the response of different phospholipid fatty acid (PLFA) sub-classes (e.g. branched saturated fatty acids of odd or even carbon number) measured using a ratio termed Barrow PLFA ratio (B-PLFAr). The corresponding values of a previously proposed hydrocarbon degrading alteration index showed a negative correlation with hydrocarbon exposure, highlighting the site specificity of PLFA-based ratios and microbial community dynamics. B-PLFAr values increased with each Phase I and II addition of production oil. The different hydrocarbon biodegradation rates and responses of PLFA subclasses to the Barrow production oil probably relate to the relative bioavailability of production oil hydrocarbons. These different effects suggest preferred structural and functional microbial responses to anticipated contaminants may potentially be engineered by controlled pre-exposure to the same or closely related substrates. The bioremediation of soils freshly contaminated with petroleum could benefit from the addition of exhaustively bioremediated soils rich in biota primed for the impacting hydrocarbons.

Individualistic sensitivities and exposure to climate change explain variation in species' distribution and abundance changes

The responses of animals and plants to recent climate change vary greatly from species to species, but attempts to understand this variation have met with limited success. This has led to concerns that predictions of responses are inherently uncertain because of the complexity of interacting drivers and biotic interactions. However, we show for an exemplar group of 155 Lepidoptera species that about 60% of the variation among species in their abundance trends over the past four decades can be explained by species-specific exposure and sensitivity to climate change. Distribution changes were less well predicted, but nonetheless, up to 53% of the variation was explained. We found that species vary in their overall sensitivity to climate and respond to different components of the climate despite ostensibly experiencing the same climate changes. Hence, species have undergone different levels of population “forcing” (exposure), driving variation among species in their national-scale abundance and distribution trends. We conclude that variation in species’ responses to recent climate change may be more predictable than previously recognized.

Neonicotinoid pesticide exposure impairs crop pollination services provided by bumblebees

Recent concern over global pollinator declines has led to considerable research on the effects of pesticides on bees1, 2, 3, 4, 5. Although pesticides are typically not encountered at lethal levels in the field, there is growing evidence indicating that exposure to field-realistic levels can have sublethal effects on bees, affecting their foraging behaviour1, 6, 7, homing ability8, 9 and reproductive success2, 5. Bees are essential for the pollination of a wide variety of crops and the majority of wild flowering plants10, 11, 12, but until now research on pesticide effects has been limited to direct effects on bees themselves and not on the pollination services they provide. Here we show the first evidence to our knowledge that pesticide exposure can reduce the pollination services bumblebees deliver to apples, a crop of global economic importance. Bumblebee colonies exposed to a neonicotinoid pesticide provided lower visitation rates to apple trees and collected pollen less often. Most importantly, these pesticide-exposed colonies produced apples containing fewer seeds, demonstrating a reduced delivery of pollination services. Our results also indicate that reduced pollination service delivery is not due to pesticide-induced changes in individual bee behaviour, but most likely due to effects at the colony level. These findings show that pesticide exposure can impair the ability of bees to provide pollination services, with important implications for both the sustained delivery of stable crop yields and the functioning of natural ecosystems.

Simulating human and environmental exposure from hand-held knapsack pesticide application: Be-WetSpa-Pest, an integrative, spatially explicit modeling approach

This paper presents an integrative and spatially explicit modeling approach for analyzing human and environmental exposure from pesticide application of smallholders in the potato producing Andean region in Colombia. The modeling approach fulfills the following criteria: (i) it includes environmental and human compartments; (ii) it contains a behavioral decision-making model for estimating the effect of policies on pesticide flows to humans and the environment; (iii) it is spatially explicit; and (iv) it is modular and easily expandable to include additional modules, crops or technologies. The model was calibrated and validated for the Vereda La Hoya and was used to explore the effect of different policy measures in the region. The model has moderate data requirements and can be adapted relatively easy to other regions in developing countries with similar conditions.

Assessment and improvement of biotransfer models to cow’s milk and beef used in exposure assessment tools for organic pollutants

The aim of this study was to assess and improve the accuracy of biotransfer models for the organic pollutants (PCBs, PCDD/Fs, PBDEs, PFCAs, and pesticides) into cow’s milk and beef used in human exposure assessment. Metabolic rate in cattle is known as a key parameter for this biotransfer, however few experimental data and no simulation methods are currently available. In this research, metabolic rate was estimated using existing QSAR biodegradation models of microorganisms (BioWIN) and fish (EPI-HL and IFS-HL). This simulated metabolic rate was then incorporated into the mechanistic cattle biotransfer models (RAIDAR, ACC-HUMAN, OMEGA, and CKow). The goodness of fit tests showed that RAIDAR, ACC-HUMAN, OMEGA model performances were significantly improved using either of the QSARs when comparing the new model outputs to observed data. The CKow model is the only one that separates the processes in the gut and liver. This model showed the lowest residual error of all the models tested when the BioWIN model was used to represent the ruminant metabolic process in the gut and the two fish QSARs were used to represent the metabolic process in the liver. Our testing included EUSES and CalTOX which are KOW-regression models that are widely used in regulatory assessment. New regressions based on the simulated rate of the two metabolic processes are also proposed as an alternative to KOW-regression models for a screening risk assessment. The modified CKow model is more physiologically realistic, but has equivalent usability to existing KOW-regression models for estimating cattle biotransfer of organic pollutants.

Modelling the bioaccumulation of persistent organic pollutants in agricultural food chains for regulatory exposure assessment

New models for estimating bioaccumulation of persistent organic pollutants in the agricultural food chain were developed using recent improvements to plant uptake and cattle transfer models. One model named AgriSim was based on K OW regressions of bioaccumulation in plants and cattle, while the other was a steady-state mechanistic model, AgriCom. The two developed models and European Union System for the Evaluation of Substances (EUSES), as a benchmark, were applied to four reported food chain (soil/air-grass-cow-milk) scenarios to evaluate the performance of each model simulation against the observed data. The four scenarios considered were as follows: (1) polluted soil and air, (2) polluted soil, (3) highly polluted soil surface and polluted subsurface and (4) polluted soil and air at different mountain elevations. AgriCom reproduced observed milk bioaccumulation well for all four scenarios, as did AgriSim for scenarios 1 and 2, but EUSES only did this for scenario 1. The main causes of the deviation for EUSES and AgriSim were the lack of the soil-air-plant pathway and the ambient air-plant pathway, respectively. Based on the results, it is recommended that soil-air-plant and ambient air-plant pathway should be calculated separately and the K OW regression of transfer factor to milk used in EUSES be avoided. AgriCom satisfied the recommendations that led to the low residual errors between the simulated and the observed bioaccumulation in agricultural food chain for the four scenarios considered. It is therefore recommended that this model should be incorporated into regulatory exposure assessment tools. The model uncertainty of the three models should be noted since the simulated concentration in milk from 5th to 95th percentile of the uncertainty analysis often varied over two orders of magnitude. Using a measured value of soil organic carbon content was effective to reduce this uncertainty by one order of magnitude.