Assessing the potential economic benefits to farmers from various GM crops becoming available in the European Union by 2025: results from an expert survey

This paper reports on a study that identified a range of crop-trait combinations that are: agronomically suited to the EU; provide advantages to arable farmers and consumers; and are either already available in international markets, or advancing along the development pipeline and likely to become available by 2025. An expert stakeholder panel was recruited and asked for their views, using the Delphi approach, on the impact of these crop-traits on enterprise competitiveness, through changes to yields, production costs and product prices. In terms of input traits, there was consensus that traits such as herbicide tolerant/insect resistant (HT/IR) maize, HT sugar beet and HT soya bean would provide positive benefits for farmers. Output-side traits such as winter-sown rape with reduced saturated fats, were seen as offering benefits to consumers, but were either likely to be restricted to niche markets, or offer relatively modest price premia to farmers growing them. Our analysis of the financial impact of the adoption of GM crops more widely in the EU, showed that the competitiveness of the agricultural sector could well be improved by this. However, such improvements would be relatively small-scale in that large-scale national natural advantages from either economic or environmental conditions is unlikely to be overturned

The productivity and financial impacts of eight types of environmental enrichment for broiler chickens

Reduced mobility in broilers can contribute to leg health problems. Environmental enrichment has been suggested as one approach to combat this through stimulating increased physical activity. Past studies have tested the effect of environmental enrichments on bird behaviour, health and welfare, but few have estimated their financial impacts. This study tested the impact of eight types of environmental enrichment on enterprise net margin, accounting for direct intervention costs plus indirect effects via changes to bird mortality, weight, feed intake, feed conversion ratio, and foot pad dermatitis. The trial used 58 pens each containing approximately 500 broilers (Ross 308) at a stocking density of 40 kg/m2. The environmental enrichments were: roughage, vertical panels, straw bales, elevated platforms (5 and 30 cm), increased distances between feed and water (7 and 3.5 m) and stocking density reduced to 34 kg/m2, plus a control group. Mortality was recorded daily and feed intake and weight weekly. Footpad dermatitis was assessed on day 35. Only one intervention improved financial performance (3.5 m between feed and water) above the control, suggesting that most environmental enrichment would have a negative financial impact due to the additional intervention costs, unless consumers were willing to pay a price premium

Multi-Scale Entropy Analysis as a Method for Time-Series Analysis of Climate Data

Evidence is mounting that the temporal dynamics of the climate system are changing at the same time as the average global temperature is increasing due to multiple climate forcings. A large number of extreme weather events such as prolonged cold spells, heatwaves, droughts and floods have been recorded around the world in the past 10 years. Such changes in the temporal scaling behaviour of climate time-series data can be difficult to detect. While there are easy and direct ways of analysing climate data by calculating the means and variances for different levels of temporal aggregation, these methods can miss more subtle changes in their dynamics. This paper describes multi-scale entropy (MSE) analysis as a tool to study climate time-series data and to identify temporal scales of variability and their change over time in climate time-series. MSE estimates the sample entropy of the time-series after coarse-graining at different temporal scales. An application of MSE to Central European, variance-adjusted, mean monthly air temperature anomalies (CRUTEM4v) is provided. The results show that the temporal scales of the current climate (1960–2014) are different from the long-term average (1850–1960). For temporal scale factors longer than 12 months, the sample entropy increased markedly compared to the long-term record. Such an increase can be explained by systems theory with greater complexity in the regional temperature data. From 1961 the patterns of monthly air temperatures are less regular at time-scales greater than 12 months than in the earlier time period. This finding suggests that, at these inter-annual time scales, the temperature variability has become less predictable than in the past. It is possible that climate system feedbacks are expressed in altered temporal scales of the European temperature time-series data. A comparison with the variance and Shannon entropy shows that MSE analysis can provide additional information on the statistical properties of climate time-series data that can go undetected using traditional method

Derivation and analysis of a computationally efficient discrete Backus-Gilbert footprint-matching algorithm

Includes bibliographical references.A computationally efficient discrete Backus-Gilbert (BG) method is derived that is subject to minimization constraints appropriate for footprint-matching applications. The method is flexible, since computational cost can be traded for accuracy. A comparison of the discrete BG method with a non-discrete BG method shows that the new method can be 250% more efficient while maintaining the same accuracy as traditional approaches. In addition, optimization approaches are used to further enhance the computational performance of the discretized BG method. A singular value decomposition approximation is applied that increases the computational efficiencies 43% to 106% while maintaining similar accuracies to the original discretized algorithm. Accuracies of the optimization were found to be scene dependent. In addition, alternative quadrature methods were also tested for several idealized simulated scenes. The results suggest that accuracy improvements could be made using customized quadrature methods that would be employed along known physical data discontinuities (such as along coastlines in microwave imagery data). In addition, regularization behaviors are also discussed; with a particular emphasis on the extension of the method for use with unnormalized gain functions. This work demonstrates that for some gain function configurations local biases can be intrinsic to the system. The flexibility of the discrete BG method allowed for several of the optimizations to be performed in a straightforward manner. Many additional optimizations are likely possible. Due to the lower computational cost of the method, this work is applicable toward applications in which noise may vary dynamically (such as in RFI-contaminated environments). The computational flexibility of the method also makes it well suited to computationally constrained problems such as 4D data assimilation of remote sensing observations.Research supported by the DoD Center for Geosciences/Atmospheric Research at CSU under Cooperative Agreement #DAAL01-98-0078 with the Army Research Laboratory

Coronary heart disease risks associated with high levels of HDL cholesterol.

BackgroundThe association between high-density lipoprotein cholesterol (HDL-C) and coronary heart disease (CHD) events is not well described in individuals with very high levels of HDL-C (>80 mg/dL).Methods and resultsUsing pooled data from 6 community-based cohorts we examined CHD and total mortality risks across a broad range of HDL-C, including values in excess of 80 mg/dL. We used Cox proportional hazards models with penalized splines to assess multivariable, adjusted, sex-stratified associations of HDL-C with the hazard for CHD events and total mortality, using HDL-C 45 mg/dL and 55 mg/dL as the referent in men and women, respectively. Analyses included 11 515 men and 12 925 women yielding 307 245 person-years of follow-up. In men, the association between HDL-C and CHD events was inverse and linear across most HDL-C values; however at HDL-C values >90 mg/dL there was a plateau effect in the pattern of association. In women, the association between HDL-C and CHD events was inverse and linear across lower values of HDL-C, however at HDL-C values >75 mg/dL there were no further reductions in the hazard ratio point estimates for CHD. In unadjusted models there were increased total mortality risks in men with very high HDL-C, however mortality risks observed in participants with very high HDL-C were attenuated after adjustment for traditional risk factors.ConclusionsWe did not observe further reductions in CHD risk with HDL-C values higher than 90 mg/dL in men and 75 mg/dL in women

In Memoriam: Keith R. Briffa, 1952–2017

Keith R. Briffa was one of the most influential palaeoclimatologists of the last 30 years. His primary research interests lay in Late-Holocene climate change with a geographical emphasis on northern Eurasia. His greatest impact was in the field of dendroclimatology, a field that he helped to shape. His contributions have been seminal to the development of sound methods for tree-ring analysis and in their proper application to allow the interpretation of climate variability from tree rings. This led to the development of many important records that allow us to understand natural climate variability on timescales from years to millennia and to set recent climatic trends in their historical context

Measuring sustainable intensification: combining composite indicators and efficiency analysis to account for positive externalities in cereal production

We combine the use of a stochastic frontier analysis framework and composite indicators for farm provision of environmental goods to obtain a farm level composite indicator reflecting sustainable intensification. The novel sustainable intensification composite indicator that is developed accounts for multidimensional market and non-market outputs, namely the economic performance of cereal farms (i.e. market production value) and the associated positive environmental impacts of production (e.g. positive environmental externalities). The composite indicator integrates three different indicators for the provision of environmental goods into a stochastic frontier analysis: a) agri-environmental payments; b) the ratio of rough grassland and permanent pasture area to total utilised agricultural area; and c) land use diversity, as measured by the Shannon Index. We apply this approach to a panel of data for 106 cereal farms in England and Wales during the period 2010–2012. Results indicate that farm rankings on the indicator vary substantially depending on the weight given to the different environmental aspects/indicators, suggesting that single indicators of the provision of environmental goods may not provide a true reflection of the environmental performance of farms. We illustrate a simple approach that captures the aspects of sustainable intensification of farms in a much more holistic way, i.e. by producing a distribution of sustainable intensification scores for each farm reflecting different weightings of evaluation criteria. To reduce the dimensionality of this distribution farms are classified into four distinct groups according to the shape of this distribution, with some farms found to perform well under all combinations of weights for evaluation criteria, while others always perform poorly. This distribution-based analysis provides a greater depth of information than traditional approaches based on the generation of a single sustainable intensification score

Improving animal health on organic dairy farms: stakeholder views on policy options

Although ensuring good animal health is a stated aim of organic livestock farming and an important reason why consumers purchase organic products, the health states actually achieved are comparable to those in conventional farming. Unfortunately, there have been no studies to date that have assessed stakeholder views on different policy options for improving animal health on organic dairy farms. To address this deficit, stakeholder consultations were conducted in four European countries, involving 39 supply-chain stakeholders (farmers, advisors, veterinarians, inspectors, processors, and retailers). Stakeholders were encouraged to discuss different ways, including policy change, of improving organic health states. Acknowledging the need for further health improvements in organic dairy herds, stakeholders generally favoured establishing outcome-oriented animal health requirements as a way of achieving this. However, as a result of differing priorities for animal health improvement, there was disagreement on questions such as: who should be responsible for assessing animal health status on organic farms; and how to define and implement minimum health requirements. The results of the study suggest that future research must fully explore the opportunities and risks of different policy options and also suggest ways to overcome the divergence of stakeholders’ interests in public debates

ISOKINETIC STRENGTH PROFILE OF FEMALE SOCCER PLAYERS: BETWEEN LIMB COMPARISONS.

The purpose of this study was to provide an isokinetic strength profile of female soccer players and examine whether limb preference influences bilateral and reciprocal knee joint muscle balance. Gravity corrected isokinetic (60°·s-1) concentric and eccentric moment-angle profiles of both limbs were collected from 25 female soccer players from the 2nd tier of English women’s soccer. Bilateral muscle imbalances were present, but limb preference only had small effects on muscle strength asymmetry and reciprocal muscle balance ratios. Trivial to small non-significant differences between preferred and non-preferred limbs were observed throughout isokinetic range for each muscle group in each mode, suggesting that injury mitigation strategies for female soccer players should focus on developing global knee extensor and flexor strength, rather than on regional strength deficits