Environmental factors driving the effectiveness of European agri-environmental measures in mitigating pollinator loss – a meta-analysis

In Europe, agri-environmental schemes (AES) have been introduced in response to concerns about farmland biodiversity declines. Yet, as AES have delivered variable results, a better understanding of what determines their success or failure is urgently needed. Focusing on pollinating insects, we quantitatively reviewed how environmental factors affect the effectiveness of AES. Our results suggest that the ecological contrast in floral resources created by schemes drives the response of pollinators to AES but that this response is moderated by landscape context and farmland type, with more positive responses in croplands (vs. grasslands) located in simple (vs. cleared or complex) landscapes. These findings inform us how to promote pollinators and associated pollination services in species-poor landscapes. They do not, however, present viable strategies to mitigate loss of threatened or endangered species. This indicates that the objectives and design of AES should distinguish more clearly between biodiversity conservation and delivery of ecosystem services.

Are superhumps good measures of the mass ratio for AM CVn systems?

We extend recent work that included the effect of pressure forces to derive the precession rate of eccentric accretion discs in cataclysmic variables to the case of double degenerate systems. We find that the logical scaling of the pressure force in such systems results in predictions of unrealistically high primary masses. Using the prototype AM CVn as a calibrator for the magnitude of the effect, we find that there is no scaling that applies consistently to all the systems in the class. We discuss the reasons for the lack of a superhump period to mass ratio relationship analogous to that known for SU UMa systems and suggest that this is because these secondaries do not have a single valued mass-radius relationship. We highlight the unreliability of mass-ratios derived by applying the SU UMa expression to the AM CVn binaries.

Cost effectiveness of mitigation measures for water security and water quality in the River Thames catchment: impacts of changing climate, land use and water scarcity

The catchment of the River Thames, the principal river system in southern England, provides the main water supply for London but is highly vulnerable to changes in climate, land use and population. The river is eutrophic with significant algal blooms with phosphorus assumed to be the primary chemical indicator of ecosystem health. In the Thames Basin, phosphorus is available from point sources such as wastewater treatment plants and from diffuse sources such as agriculture. In order to predict vulnerability to future change, the integrated catchments model for phosphorus (INCA-P) has been applied to the river basin and used to assess the cost-effectiveness of a range of mitigation and adaptation strategies. It is shown that scenarios of future climate and land-use change will exacerbate the water quality problems, but a range of mitigation measures can improve the situation. A cost-effectiveness study has been undertaken to compare the economic benefits of each mitigation measure and to assess the phosphorus reductions achieved. The most effective strategy is to reduce fertilizer use by 20% together with the treatment of effluent to a high standard. Such measures will reduce the instream phosphorus concentrations to close to the EU Water Framework Directive target for the Thames.

Problems with binary pattern measures for flood model evaluation

As the calibration and evaluation of flood inundation models are a prerequisite for their successful application, there is a clear need to ensure that the performance measures that quantify how well models match the available observations are fit for purpose. This paper evaluates the binary pattern performance measures that are frequently used to compare flood inundation models with observations of flood extent. This evaluation considers whether these measures are able to calibrate and evaluate model predictions in a credible and consistent way, i.e. identifying the underlying model behaviour for a number of different purposes such as comparing models of floods of different magnitudes or on different catchments. Through theoretical examples, it is shown that the binary pattern measures are not consistent for floods of different sizes, such that for the same vertical error in water level, a model of a flood of large magnitude appears to perform better than a model of a smaller magnitude flood. Further, the commonly used Critical Success Index (usually referred to as F<2 >) is biased in favour of overprediction of the flood extent, and is also biased towards correctly predicting areas of the domain with smaller topographic gradients. Consequently, it is recommended that future studies consider carefully the implications of reporting conclusions using these performance measures. Additionally, future research should consider whether a more robust and consistent analysis could be achieved by using elevation comparison methods instead.

Determinants and measures of export performance – comprehensive literature review

As one of the key indicators of the firm’s ability to leverage successfully its resources and capabilities in the international context, export performance has been one of the most extensively studied phenomena. A plethora of studies have been conducted pertaining to provide better understanding of the factors (firm- or environment-specific) and behaviours (e.g., export strategy) that make exporting a successful venture. Following a comprehensive literature review undertaking in this study the current state of the export performance literature could be summarisedas (i) methodologically fragmented in that there is a variety of analytical and methodological approaches, (ii) conceptually diverse, a large number of determinants have been identified as having direct or indirect influence on the firm’s export performance, and a large number of indicators have been used to conceptualise and operationalise the export performance measures, and (iii) inconclusive, the studies have produced inconsistent results of the impact of different determinants on export performance.

An interdisciplinary modelling approach asessing the cost-effectiveness of agri-environmental measures on reducing nutrient concentration to WFD thresholds under climate change: the case of the Louros catchment

The application of the Water Framework Directive (WFD) in the European Union (EU) targets certain threshold levels for the concentration of various nutrients, nitrogen and phosphorous being the most important. In the EU, agri-environmental measures constitute a significant component of Pillar 2—Rural Development Policies in both financial and regulatory terms. Environmental measures also are linked to Pillar 1 payments through cross-compliance and the greening proposals. This paper drawing from work carried out in the REFRESH FP7 project aims to show how an INtegrated CAtchment model of plant/soil system dynamics and instream biogeochemical and hydrological dynamics can be used to assess the cost-effectiveness of agri-environmental measures in relation to nutrient concentration targets set by the WFD, especially in the presence of important habitats. We present the procedures (methodological steps, challenges and problems) for assessing the cost-effectiveness of agri-environmental measures at the baseline situation, and climate and land use change scenarios. Furthermore, we present results of an application of this methodology to the Louros watershed in Greece and discuss the likely uses and future extensions of the modelling approach. Finally, we attempt to reveal the importance of this methodology for designing and incorporating alternative environmental practices in Pillar 1 and 2 measures.

The measurement of self-complexity: A comparison of H and SC measures

Greater self-complexity has been suggested as a protective factor for people under stress (Linville, 1985). Two different measures have been proposed to assess individual self-complexity: Attneave’s H statistic (1959) and a composite index of two components of self-complexity (SC; Rafaeli-Mor et al., 1999). Using mood-incongruent recall, i.e., recalling positive events while in negative mood, the present study compared validity of the two measures through reanalysis of Sakaki’s (2004) data. Results indicated that H statistic did not predict performance of mood-incongruent recall. In contrast, greater SC was associated with better mood-incongruent recall even when the effect of H statistic was controlled.

Using lexical diversity measures to operationalise language dominance in bilinguals

Treffers-Daller and Korybski propose to operationalize language dominance on the basis of measures of lexical diversity, as computed, in this particular study, on transcripts of stories told by Polish-English bilinguals in each of their languages They compute four different Indices of Language Dominance (ILD) on the basis of two different measures of lexical diversity, the Index of Guiraud (Guiraud, 1954) and HD-D (McCarthy & Jarvis, 2007). They compare simple indices, which are based on subtracting scores from one language from scores for another language, to more complex indices based on the formula Birdsong borrowed from the field of handedness, namely the ratio of (Difference in Scores) / (Sum of Scores). Positive scores on each of these Indices of Language Dominance mean that informants are more English-dominant and negative scores that they are more Polish-dominant. The authors address the difficulty of comparing scores across languages by carefully lemmatizing the data. Following Flege, Mackay and Piske (2002) they also look into the validity of these indices by investigating to what extent they can predict scores on other, independently measured variables. They use correlations and regression analysis for this, which has the advantage that the dominance indices are used as continuous variables and arbitrary cut-off points between balanced and dominant bilinguals need not be chosen. However, they also show how the computation of z-scores can help facilitate a discussion about the appropriateness of different cut-off points across different data sets and measurement scales in those cases where researchers consider it necessary to make categorial distinctions between balanced and dominant bilinguals. Treffers-Daller and Korybski correlate the ILD scores with four other variables, namely Length of Residence in the UK, attitudes towards English and life in the UK, frequency of usage of English at home and frequency of code-switching. They found that the indices correlated significantly with most of these variables, but there were clear differences between the Guiraud-based indices and the HDD-based indices. In a regression analysis three of the measures were also found to be a significant predictor of English language usage at home. They conclude that the correlations and the regression analyses lend strong support to the validity of their approach to language dominance.

Estimation of Gaussian process regression model using probability distance measures

A new class of parameter estimation algorithms is introduced for Gaussian process regression (GPR) models. It is shown that the integration of the GPR model with probability distance measures of (i) the integrated square error and (ii) Kullback–Leibler (K–L) divergence are analytically tractable. An efficient coordinate descent algorithm is proposed to iteratively estimate the kernel width using golden section search which includes a fast gradient descent algorithm as an inner loop to estimate the noise variance. Numerical examples are included to demonstrate the effectiveness of the new identification approaches.

How reliable is internet-based self-reported identity, socio-demographic and obesity measures in European adults?

In e-health intervention studies, there are concerns about the reliability of internet-based, self-reported (SR) data and about the potential for identity fraud. This study introduced and tested a novel procedure for assessing the validity of internet-based, SR identity and validated anthropometric and demographic data via measurements performed face-to-face in a validation study (VS). Participants (n = 140) from seven European countries, participating in the Food4Me intervention study which aimed to test the efficacy of personalised nutrition approaches delivered via the internet, were invited to take part in the VS. Participants visited a research centre in each country within 2 weeks of providing SR data via the internet. Participants received detailed instructions on how to perform each measurement. Individual’s identity was checked visually and by repeated collection and analysis of buccal cell DNA for 33 genetic variants. Validation of identity using genomic information showed perfect concordance between SR and VS. Similar results were found for demographic data (age and sex verification). We observed strong intra-class correlation coefficients between SR and VS for anthropometric data (height 0.990, weight 0.994 and BMI 0.983). However, internet-based SR weight was under-reported (Δ −0.70 kg [−3.6 to 2.1], p < 0.0001) and, therefore, BMI was lower for SR data (Δ −0.29 kg m−2 [−1.5 to 1.0], p < 0.0001). BMI classification was correct in 93 % of cases. We demonstrate the utility of genotype information for detection of possible identity fraud in e-health studies and confirm the reliability of internet-based, SR anthropometric and demographic data collected in the Food4Me study.

A moment problem for random discrete measures

Let X be a locally compact Polish space. A random measure on X is a probability measure on the space of all (nonnegative) Radon measures on X. Denote by K(X) the cone of all Radon measures η on X which are of the form η =

Simple measures of climate, soil properties and plant traits predict national scale grassland soil carbon stocks

1. Soil carbon (C) storage is a key ecosystem service. Soil C stocks play a vital role in soil fertility and climate regulation, but the factors that control these stocks at regional and national scales are unknown, particularly when their composition and stability are considered. As a result, their mapping relies on either unreliable proxy measures or laborious direct measurements. 2. Using data from an extensive national survey of English grasslands we show that surface soil (0-7cm) C stocks in size fractions of varying stability can be predicted at both regional and national scales from plant traits and simple measures of soil and climatic conditions. 3. Soil C stocks in the largest pool, of intermediate particle size (50-250 µm), were best explained by mean annual temperature (MAT), soil pH and soil moisture content. The second largest C pool, highly stable physically and biochemically protected particles (0.45-50 µm), was explained by soil pH and the community abundance weighted mean (CWM) leaf nitrogen (N) content, with the highest soil C stocks under N rich vegetation. The C stock in the small active fraction (250-4000 µm) was explained by a wide range of variables: MAT, mean annual precipitation, mean growing season length, soil pH and CWM specific leaf area; stocks were higher under vegetation with thick and/or dense leaves. 4. Testing the models describing these fractions against data from an independent English region indicated moderately strong correlation between predicted and actual values and no systematic bias, with the exception of the active fraction, for which predictions were inaccurate. 5. Synthesis and Applications: Validation indicates that readily available climate, soils and plant survey data can be effective in making local- to landscape-scale (1-100,000 km2) soil C stock predictions. Such predictions are a crucial component of effective management strategies to protect C stocks and enhance soil C sequestration.

Neurolinguistic measures of typological effects in multilingual transfer: introducing an ERP methodology

This article has two main objectives. First, we offer an introduction to the subfield of generative third language (L3) acquisition. Concerned primarily with modeling initial stages transfer of morphosyntax, one goal of this program is to show how initial stages L3 data make significant contributions toward a better understanding of how the mind represents language and how (cognitive) economy constrains acquisition processes more generally. Our second objective is to argue for and demonstrate how this subfield will benefit from a neuro/psycholinguistic methodological approach, such as event-related potential experiments, to complement the claims currently made on the basis of exclusively behavioral experiments.