Response of farmland biodiversity to the introduction of bioenergy crops: effects of local factors and surrounding landscape context

The recent growth in bioenergy crop cultivation, stimulated by the need to implement measures to reduce net CO emissions, is driving major land-use changes with consequences for biodiversity and ecosystem service provision. Although the type of bioenergy crop and its associated management is likely to affect biodiversity at the local (field) scale, landscape context and its interaction with crop type may also influence biodiversity on farms. In this study, we assessed the impact of replacing conventional agricultural crops with two model bioenergy crops (either oilseed rape Brassica napus or Miscanthus × giganteus) on vascular plant, bumblebee, solitary bee, hoverfly and carabid beetle richness, diversity and abundance in 50 sites in Ireland. We assessed whether within-field biodiversity was also related to surrounding landscape structure. We found that local- and landscape-scale variables correlated with biodiversity in these agricultural landscapes. Overall, the differences between the bioenergy crops and the conventional crops on farmland biodiversity were mostly positive (e.g. higher vascular plant richness in Miscanthus planted on former conventional tillage, higher solitary bee abundance and richness in Miscanthus and oilseed rape compared with conventional crops) or neutral (e.g. no differences between crop types for hoverflies and bumblebees). We showed that these crop type effects were independent of (i.e. no interactions with) the surrounding landscape composition and configuration. However, surrounding landscape context did relate to biodiversity in these farms, negatively for carabid beetles and positively for hoverflies. Although we conclude that the bioenergy crops compared favourably with conventional crops in terms of biodiversity of the taxa studied at the field scale, the effects of large-scale planting in these landscapes could result in very different impacts. Maintaining ecosystem functioning and the delivery of ecosystem services will require a greater understanding of impacts at the landscape scale to ensure the sustainable development of climate change mitigation measures.

Taxonomic and functional diversity of farmland bird communities across Europe:Effects of biogeography and agricultural intensification

In eight European study sites (in Spain, Ireland, Netherlands, Germany, Poland, Estonia and Sweden), abundance of breeding farmland bird territories was obtained from 500 × 500 m survey plots (30 per area, N = 240) using the mapping method. Two analyses were performed: (I) a Canonical Correspondence Analysis of species abundance in relation to geographical location and variables measuring agricultural intensification at field and farm level to identify significant intensification variables and to estimate the fractions of total variance in bird abundance explained by geography and agricultural intensification; (II) several taxonomic and functional community indices were built and analysed using GLM in relation to the intensification variables found significant in the CCA. The geographical location of study sites alone explains nearly one fifth (19. 5%) of total variation in species abundance. The fraction of variance explained by agricultural intensification alone is much smaller (4. 3%), although significant. The intersection explains nearly two fifths (37. 8%) of variance in species abundance. Community indices are negatively affected by correlates of intensification like farm size and yield, whereas correlates of habitat availability and quality have positive effects on taxonomic and functional diversity of assemblages. Most of the purely geographical variation in farmland bird assemblage composition is associated to Mediterranean steppe species, reflecting the bio-geographical singularity of that assemblage and reinforcing the need to preserve this community. Taxonomic and functional diversity of farmland bird communities are negatively affected by agricultural intensification and positively affected by increasing farmland habitat availability and quality. © 2011 Springer Science+Business Media B.V.

Rigorous Specification and Low-Latency Implementation of Technical Market Indicators

Technical market indicators are tools used by technical an- alysts to understand trends in trading markets. Technical (market) indicators are often calculated in real-time, as trading progresses. This paper presents a mathematically- founded framework for calculating technical indicators. Our framework consists of a domain specific language for the un- ambiguous specification of technical indicators, and a run- time system based on Click, for computing the indicators. We argue that our solution enhances the ease of program- ming due to aligning our domain-specific language to the mathematical description of technical indicators, and that it enables executing programs in kernel space for decreased latency, without exposing the system to users’ programming errors.

The influence of market deregulation on fast food consumption and body mass index:A cross-national time series analysis

Objective
To investigate the effect of fast food consumption on mean population body mass index (BMI) and explore the possible influence of market deregulation on fast food consumption and BMI.

Methods
The within-country association between fast food consumption and BMI in 25 high-income member countries of the Organisation for Economic Co-operation and Development between 1999 and 2008 was explored through multivariate panel regression models, after adjustment for per capita gross domestic product, urbanization, trade openness, lifestyle indicators and other covariates. The possible mediating effect of annual per capita intake of soft drinks, animal fats and total calories on the association between fast food consumption and BMI was also analysed. Two-stage least squares regression models were conducted, using economic freedom as an instrumental variable, to study the causal effect of fast food consumption on BMI.

Findings
After adjustment for covariates, each 1-unit increase in annual fast food transactions per capita was associated with an increase of 0.033 kg/m2 in age-standardized BMI (95% confidence interval, CI: 0.013–0.052). Only the intake of soft drinks – not animal fat or total calories – mediated the observed association (β: 0.030; 95% CI: 0.010–0.050). Economic freedom was an independent predictor of fast food consumption (β: 0.27; 95% CI: 0.16–0.37). When economic freedom was used as an instrumental variable, the association between fast food and BMI weakened but remained significant (β: 0.023; 95% CI: 0.001–0.045).

Conclusion
Fast food consumption is an independent predictor of mean BMI in high-income countries. Market deregulation policies may contribute to the obesity epidemic by facilitating the spread of fast food.

Offshore wind power forecasting error and electricity market implications

Wind energy has been identified as key to the European Union’s 2050 low carbon economy. However, as wind is a variable resource and stochastic by nature, it is difficult to plan and schedule the power system under varying wind power generation. This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact of the magnitude and variance of the offshore wind power forecast error on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price is analysed. The main findings of this research are that the magnitude of the offshore wind power forecast error has the largest impact on system generation costs and dispatch-down of wind, but the variance of the offshore wind power forecast error has the biggest impact on emissions costs and system marginal price. Overall offshore wind power forecast error variance results in a system marginal price increase of 9.6% in 2050.

Disinflation with labor market frictions

This paper studies disinflationary shocks in a non-linear New Keynesian model with search and matching frictions and moral hazard in the labor markets. Our focus is on understanding the wage formation process as well as welfare costs of disinflations in the presence of such labor market frictions.

The presence of imperfect information in labor markets imposes a lower bound on worker surplus that varies endogenously. Consequently equilibrium can take two forms depending on whether the no shirking condition is binding or not. We also evaluate both regimes from a welfare perspective when the economy is subject to a perfectly credible disinflationary shock.

Impacts of compressed air energy storage plant on an electricity market with a large renewable energy portfolio

Renewable energy generation is expected to continue to increase globally due to renewable energy targets and obligations to reduce greenhouse gas emissions. Some renewable energy sources are variable power sources, for example wind, wave and solar. Energy storage technologies can manage the issues associated with variable renewable generation and align non-dispatchable renewable energy generation with load demands. Energy storage technologies can play different roles in each of the step of the electric power supply chain. Moreover, large scale energy storage systems can act as renewable energy integrators by smoothing the variability. Compressed air energy storage is one such technology. This paper examines the impacts of a compressed air energy storage facility in a pool based wholesale electricity market in a power system with a large renewable energy portfolio.

Impact of offshore wind power forecast error in a carbon constraint electricity market

This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact from offshore wind power forecast errors of up to 2000 MW on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price are analysed. The main findings of this research are an increase in system marginal prices of approximately 1% for every percentage point rise in the offshore wind power forecast error regardless of the average forecast error sign. If offshore wind power generates less than forecasted (−13%) generation costs and system marginal prices increases by 10%. However, if offshore wind power generates more than forecasted (4%) the generation costs decrease yet the system marginal prices increase by 3%. The dispatch down of large quantities of wind power highlights the need for flexible interconnector capacity. From a system operator's perspective it is more beneficial when scheduling wind ahead of the trading period to forecast less wind than will be generated.

Lead in rice: Analysis of baseline lead levels in market and field collected rice grains

In a large scale survey of rice grains from markets (13 countries) and fields (6 countries), a total of 1578 rice grain samples were analysed for lead. From the market collected samples, only 0.6% of the samples exceeded the Chinese and EU limit of 0.2 μg g− 1 lead in rice (when excluding samples collected from known contaminated/mine impacted regions). When evaluating the rice grain samples against the Food and Drug Administration's (FDA) provisional total tolerable intake (PTTI) values for children and pregnant women, it was found that only people consuming large quantities of rice were at risk of exceeding the PTTI from rice alone. Furthermore, 6 field experiments were conducted to evaluate the proportion of the variation in lead concentration in rice grains due to genetics. A total of 4 of the 6 field experiments had significant differences between genotypes, but when the genotypes common across all six field sites were assessed, only 4% of the variation was explained by genotype, with 9.5% and 11% of the variation explained by the environment and genotype by environment interaction respectively. Further work is needed to identify the sources of lead contamination in rice, with detailed information obtained on the locations and environments where the rice is sampled, so that specific risk assessments can be performed.

Testing of a Market Fraction Model and Power-law Behaviour in the DAX 30

This paper tests a simple market fraction asset pricing model with heterogeneous
agents. By selecting a set of structural parameters of the model through a systematic procedure, we show that the autocorrelations (of returns, absolute returns and squared returns) of the market fraction model share the same pattern as those of the DAX 30. By conducting econometric analysis via Monte Carlo simulations, we characterize these power-law behaviours and find that estimates of the power-law decay indices, the (FI)GARCH parameters, and the tail index of the selected market fraction model closely match those of the DAX 30. The results strongly support the explanatory power of the heterogeneous agent models.

The cross-section of stock returns in an early stock market

Using a new dataset which contains monthly data on 1015 stocks traded on the London Stock Exchange between 1825 and 1870, we investigate the cross section of stock returns in this early capital market. Unique features of this market allow us to evaluate the veracity of several popular explanations of asset pricing behavior. Using portfolio analysis and Fama–MacBeth regressions, we find that stock characteristics such as beta, illiquidity, dividend yield, and past-year return performance are all positively correlated with stock returns. However, market capitalization and past-three-year return performance have no significant correlation with stock returns.