916 resultados para farm heterogeneity


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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.

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The 2003 reform of the European Union's (EU) Common Agricultural Policy introduced a decoupled income support for farmers called the Single Farm Payment (SFP). Concerns were raised about possible future land use and production changes and their impact on rural communities. Here, such concerns are considered against the workings of the SFP in three EU Member States. Various quantitative studies that have determined the likely impact of the SFP within the EU and the study countries are reviewed. We present the results of a farm survey conducted in the study countries in which farmers' responses to a decoupling scenario similar to the SFP were sought. We found that little short-term change was proposed in the three, rather different, study countries with only 30% of the farmers stating that they would alter their mix of farm activities. Furthermore, less than 30% of all respondents in each country would idle any land under decoupling. Of those who would adopt a new activity, the most popular choices were forestry, woodland and non-food crops. (c) 2007 Elsevier Ltd. All rights reserved.

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The low proportion of forested land and continuing degradation of existing forest cover are serious threats to the sustainability of forestry in Pakistan. Farm forestry has been identified as a feasible solution, particularly in the plain areas. Applying the Theory of Planned Behaviour in a survey of 124 farmers in Dera Ismail Khan district of Pakistan's North West Frontier Province showed that farmers' willingness to grow trees on their farms is a function of their attitudes towards the advantages and disadvantages of growing trees, their perception of the opinions of salient referents and factors that encourage and discourage farm level tree planting. Farmers viewed farm forestry as economically beneficial and environmentally friendly. Tree planting was perceived as increasing income, providing wood for fuel and furniture, controlling erosion and pollution and providing shade for humans and animals. Farmers saw hindrance in agricultural operations and the harbouring of insects, pests and diseases as negative impacts of tree planting; however, these were outweighed by their perceptions of positive impacts. Tree growing decisions of farmers were influenced by the opinions of family members, owners/tenants, fellow farmers and village elders. The factors that significantly predicted farm level tree planting were availability of barren land, lack of markets, lack of nurseries and damage caused by animals and humans. Farm forestry programmes are more likely to be successful if they acknowledge and address the factors which underlie farmers' reasons for planting or not planting trees.

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OBJECTIVES: This contribution provides a unifying concept for meta-analysis integrating the handling of unobserved heterogeneity, study covariates, publication bias and study quality. It is important to consider these issues simultaneously to avoid the occurrence of artifacts, and a method for doing so is suggested here. METHODS: The approach is based upon the meta-likelihood in combination with a general linear nonparametric mixed model, which lays the ground for all inferential conclusions suggested here. RESULTS: The concept is illustrated at hand of a meta-analysis investigating the relationship of hormone replacement therapy and breast cancer. The phenomenon of interest has been investigated in many studies for a considerable time and different results were reported. In 1992 a meta-analysis by Sillero-Arenas et al. concluded a small, but significant overall effect of 1.06 on the relative risk scale. Using the meta-likelihood approach it is demonstrated here that this meta-analysis is due to considerable unobserved heterogeneity. Furthermore, it is shown that new methods are available to model this heterogeneity successfully. It is argued further to include available study covariates to explain this heterogeneity in the meta-analysis at hand. CONCLUSIONS: The topic of HRT and breast cancer has again very recently become an issue of public debate, when results of a large trial investigating the health effects of hormone replacement therapy were published indicating an increased risk for breast cancer (risk ratio of 1.26). Using an adequate regression model in the previously published meta-analysis an adjusted estimate of effect of 1.14 can be given which is considerably higher than the one published in the meta-analysis of Sillero-Arenas et al. In summary, it is hoped that the method suggested here contributes further to a good meta-analytic practice in public health and clinical disciplines.

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Background: Variation in carrying capacity and population return rates is generally ignored in traditional studies of population dynamics. Variation is hard to study in the field because of difficulties controlling the environment in order to obtain statistical replicates, and because of the scale and expense of experimenting on populations. There may also be ethical issues. To circumvent these problems we used detailed simulations of the simultaneous behaviours of interacting animals in an accurate facsimile of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of skylarks Alauda arvensis, voles Microtus agrestis, a ground beetle Bembidion lampros and a linyphiid spider Erigone atra. This allows us to quantify and evaluate the importance of spatial and temporal heterogeneity on the population dynamics of the four species. Results: Both spatial and temporal heterogeneity affected the relationship between population growth rate and population density in all four species. Spatial heterogeneity accounted for 23–30% of the variance in population growth rate after accounting for the effects of density, reflecting big differences in local carrying capacity associated with the landscape features important to individual species. Temporal heterogeneity accounted for 3–13% of the variance in vole, skylark and spider, but 43% in beetles. The associated temporal variation in carrying capacity would be problematic in traditional analyses of density dependence. Return rates were less than one in all species and essentially invariant in skylarks, spiders and beetles. Return rates varied over the landscape in voles, being slower where there were larger fluctuations in local population sizes. Conclusion: Our analyses estimated the traditional parameters of carrying capacities and return rates, but these are now seen as varying continuously over the landscape depending on habitat quality and the mechanisms of density dependence. The importance of our results lies in our demonstration that the effects of spatial and temporal heterogeneity must be accounted for if we are to have accurate predictive models for use in management and conservation. This is an area which until now has lacked an adequate theoretical framework and methodology.

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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.

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We focus on the comparison of three statistical models used to estimate the treatment effect in metaanalysis when individually pooled data are available. The models are two conventional models, namely a multi-level and a model based upon an approximate likelihood, and a newly developed model, the profile likelihood model which might be viewed as an extension of the Mantel-Haenszel approach. To exemplify these methods, we use results from a meta-analysis of 22 trials to prevent respiratory tract infections. We show that by using the multi-level approach, in the case of baseline heterogeneity, the number of clusters or components is considerably over-estimated. The approximate and profile likelihood method showed nearly the same pattern for the treatment effect distribution. To provide more evidence two simulation studies are accomplished. The profile likelihood can be considered as a clear alternative to the approximate likelihood model. In the case of strong baseline heterogeneity, the profile likelihood method shows superior behaviour when compared with the multi-level model. Copyright (C) 2006 John Wiley & Sons, Ltd.

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We describe a general likelihood-based 'mixture model' for inferring phylogenetic trees from gene-sequence or other character-state data. The model accommodates cases in which different sites in the alignment evolve in qualitatively distinct ways, but does not require prior knowledge of these patterns or partitioning of the data. We call this qualitative variability in the pattern of evolution across sites "pattern-heterogeneity" to distinguish it from both a homogenous process of evolution and from one characterized principally by differences in rates of evolution. We present studies to show that the model correctly retrieves the signals of pattern-heterogeneity from simulated gene-sequence data, and we apply the method to protein-coding genes and to a ribosomal 12S data set. The mixture model outperforms conventional partitioning in both these data sets. We implement the mixture model such that it can simultaneously detect rate- and pattern-heterogeneity. The model simplifies to a homogeneous model or a rate- variability model as special cases, and therefore always performs at least as well as these two approaches, and often considerably improves upon them. We make the model available within a Bayesian Markov-chain Monte Carlo framework for phylogenetic inference, as an easy-to-use computer program.

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A critical analysis of single crystal X-ray diffraction studies on a series of terminally protected tripeptides containing a centrally positioned Aib (alpha-aminoisobutyric acid) residue has been reported. For the tripeptide series containing Boc-Ala-Aib as corner residues, all the reported peptides formed distorted type II beta-turn structures. Moreover, a series of Phe substituted analogues ( tripeptides with Boc-Phe-Aib) have also shown different beta-turn conformations. However, the Leu-modified analogues (tripeptides with Boc-Leu-Aib) disrupt the concept of beta-turn formation and adopt various conformations in the solid state. X-ray crystallography sheds some light on the conformational heterogeneity at atomic resolution. (c) 2007 Elsevier Ltd. All rights reserved.

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Williams syndrome (WS) is a rare genetic disorder resulting from a deletion on chromosome 7. A number of studies have shown that individuals with WS have a superior linguistic profile compared to their non-verbal abilities, however the evidence has been inconclusive, as many studies have disputed such a profile. The vast majority of studies on WS have assumed a single, homogeneous WS linguistic profile in order to support various theoretical viewpoints. The present study investigated the linguistic profiles of 5 individuals with WS on a number of standardized verbal measures and in conversational settings. The results indicated substantially variable performance in all aspects of the verbal domain, which supports the view that WS, linguistically, is a rather heterogeneous condition and this should be taken into consideration when referring to it in theoretical accounts of language acquisition and debates on modularity.

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The performance benefit when using Grid systems comes from different strategies, among which partitioning the applications into parallel tasks is the most important. However, in most cases the enhancement coming from partitioning is smoothed by the effect of the synchronization overhead, mainly due to the high variability of completion times of the different tasks, which, in turn, is due to the large heterogeneity of Grid nodes. For this reason, it is important to have models which capture the performance of such systems. In this paper we describe a queueing-network-based performance model able to accurately analyze Grid architectures, and we use the model to study a real parallel application executed in a Grid. The proposed model improves the classical modelling techniques and highlights the impact of resource heterogeneity and network latency on the application performance.