Budgetary implications of, and motives for, converting to organic farming: Case study farm business evidence from Great Britain

This paper explores the financial implications of converting to organic farming in Great Britain through a case study of farmers considering conversion in 2002. Most study farmers were motivated to convert for financial, not ideological or life-style reasons; organic meat production was the most common planned enterprise, although those choosing to produce milk, vegetables and cereals were also studied in depth. At the time of study, organic beef and sheep meat production was particularly profitable. It was found that, in these product sectors, a large improvement in Family Farm Income would result if organic production was introduced on the case study farms. With few exceptions, a fall in Family Farm Income during the conversion period would not be an obstacle to farmers changing to organic methods. Fixed cost changes would also not deter conversion but expensive investment in new livestock and appropriate buildings would be required by some of those businesses studied. These findings are, however, dependent upon the price premia assumptions used and, whilst these premia have dropped slightly since the time of study, this would lessen the financial shortfall during the conversion period. There is also the possibility that reversion to conventional agricultural production might occur, perhaps at a faster rate than the original conversion process that was taking place around the turn of the century.

Estimating the hidden number of scrapie affected holdings in great Britain using a simple, truncated count model allowing for heterogeneity

None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture-recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture-recapture models. Alternative methods, still under the capture-recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture-recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao's lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates-in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.

Application of one-list capture-recapture models to scrapie surveillance data in Great Britain

In this paper, we apply one-list capture-recapture models to estimate the number of scrapie-affected holdings in Great Britain. We applied this technique to the Compulsory Scrapie Flocks Scheme dataset where cases from all the surveillance sources monitoring the presence of scrapie in Great Britain, the abattoir survey, the fallen stock survey and the statutory reporting of clinical cases, are gathered. Consequently, the estimates of prevalence obtained from this scheme should be comprehensive and cover all the different presentations of the disease captured individually by the surveillance sources. Two estimators were applied under the one-list approach: the Zelterman estimator and Chao's lower bound estimator. Our results could only inform with confidence the scrapie-affected holding population with clinical disease; this moved around the figure of 350 holdings in Great Britain for the period under study, April 2005-April 2006. Our models allowed the stratification by surveillance source and the input of covariate information, holding size and country of origin. None of the covariates appear to inform the model significantly. Crown Copyright (C) 2008 Published by Elsevier B.V. All rights reserved.

An investigation of the impact of time of generation on carbon savings from PV systems in Great Britain

PV only generates electricity during daylight hours and primarily generates over summer. In the UK, the carbon intensity of grid electricity is higher during the daytime and over winter. This work investigates whether the grid electricity displaced by PV is high or low carbon compared to the annual mean carbon intensity using carbon factors at higher temporal resolutions (half-hourly and daily). UK policy for carbon reporting requires savings to be calculated using the annual mean carbon intensity of grid electricity. This work offers an insight into whether this technique is appropriate. Using half hourly data on the generating plant supplying the grid from November 2008 to May 2010, carbon factors for grid electricity at half-hourly and daily resolution have been derived using technology specific generation emission factors. Applying these factors to generation data from PV systems installed on schools, it is possible to assess the variation in the carbon savings from displacing grid electricity with PV generation using carbon factors with different time resolutions. The data has been analyzed for a period of 363 to 370 days and so cannot account for inter-year variations in the relationship between PV generation and carbon intensity of the electricity grid. This analysis suggests that PV displaces more carbon intensive electricity using half-hourly carbon factors than using daily factors but less compared with annual ones. A similar methodology could provide useful insights on other variable renewable and demand-side technologies and in other countries where PV performance and grid behavior are different.

Identifying antimicrobial resistance genes of human clinical relevance within Salmonella isolated from food animals in Great Britain

To investigate the occurrence of antimicrobial resistance genes of human clinical relevance in Salmonella isolated from livestock in Great Britain. Two hundred and twenty-five Salmonella enterica isolates were characterized using an antimicrobial resistance gene chip and disc diffusion assays. Plasmid profiling, conjugation experiments and identification of Salmonella genomic island 1 (SGI1) were performed for selected isolates. Approximately 43% of Salmonella harboured single or multiple antimicrobial resistance genes with pig isolates showing the highest numbers where 96% of Salmonella Typhimurium harboured one or more resistance genes. Isolates harbouring multiple resistances divided into three groups. Group 1 isolates harboured ampicillin/streptomycin/sulphonamide/tetracycline resistance and similar phenotypes. This group contained isolates from pigs, cattle and poultry that were from several serovars including Typhimurium, 4,[5],12:i:-, Derby, Ohio and Indiana. All Group 2 isolates were from pigs and were Salmonella Typhimurium. They contained a non-sul-type class 1 integron and up to 13 transferrable resistances. All Group 3 isolates harboured a class 1 integron and were isolated from all animal species included in the study. Most isolates were Salmonella Typhimurium and harboured SGI1. Salmonella isolated from livestock was shown to harbour antimicrobial resistance genes although no or little resistance to third-generation cephalosporins or ciprofloxacin, respectively, was detected. The preponderance in pigs of multidrug-resistant Salmonella Typhimurium makes it important to introduce control measures such as improved biosecurity to ensure that they do not pass through the food chain and limit human therapeutic options.

A high prevalence of antimicrobial resistant Escherichia coli isolated from pigs and a low prevalence of antimicrobial resistant E-coli from cattle and sheep in Great Britain at slaughter

The incidence of antimicrobial resistance and expressed and unexpressed resistance genes among commensal Escherichia coli isolated from healthy farm animals at slaughter in Great Britain was investigated. The prevalence of antimicrobial resistance among the isolates varied according to the animal species; of 836 isolates from cattle tested only 5.7% were resistant to one or more antimicrobials, while only 3.0% of 836 isolates from sheep were resistant to one or more agents. However, 92.1% of 2480 isolates from pigs were resistant to at least one antimicrobial. Among isolates from pigs, resistance to some antimicrobials such as tetracycline (78.7%), sulphonamide (66.9%) and streptomycin (37.5%) was found to be common, but relatively rare to other agents such as amikacin (0.1%), ceftazidime ( 0.1%) and coamoxiclav (0.2%). The isolates had a diverse range of resistance gene profiles, with tet(B), sul2 and strAB identified most frequently. Seven out of 615 isolates investigated carried unexpressed resistance genes. One trimethoprim-susceptible isolate carried a complete dfrA17 gene but lacked a promoter for it. However, in the remaining six streptomycin-susceptible isolates, one of which carried strAB while the others carried aadA, no mutations or deletions in gene or promoter sequences were identified to account for susceptibility. The data indicate that antimicrobial resistance in E. coli of animal origin is due to a broad range of acquired genes.

Species distribution models for crop pollination: a modelling framework applied to Great Britain

Insect pollination benefits over three quarters of the world's major crops. There is growing concern that observed declines in pollinators may impact on production and revenues from animal pollinated crops. Knowing the distribution of pollinators is therefore crucial for estimating their availability to pollinate crops; however, in general, we have an incomplete knowledge of where these pollinators occur. We propose a method to predict geographical patterns of pollination service to crops, novel in two elements: the use of pollinator records rather than expert knowledge to predict pollinator occurrence, and the inclusion of the managed pollinator supply. We integrated a maximum entropy species distribution model (SDM) with an existing pollination service model (PSM) to derive the availability of pollinators for crop pollination. We used nation-wide records of wild and managed pollinators (honey bees) as well as agricultural data from Great Britain. We first calibrated the SDM on a representative sample of bee and hoverfly crop pollinator species, evaluating the effects of different settings on model performance and on its capacity to identify the most important predictors. The importance of the different predictors was better resolved by SDM derived from simpler functions, with consistent results for bees and hoverflies. We then used the species distributions from the calibrated model to predict pollination service of wild and managed pollinators, using field beans as a test case. The PSM allowed us to spatially characterize the contribution of wild and managed pollinators and also identify areas potentially vulnerable to low pollination service provision, which can help direct local scale interventions. This approach can be extended to investigate geographical mismatches between crop pollination demand and the availability of pollinators, resulting from environmental change or policy scenarios.