Book reviews

Teaching/Communication/Extension/Profession,

Focus rural land policies on ecosystem services, not agriculture.

Land policies around the world are weighted towards agricultural output. We argue that this leads to ineffective public expenditure, environmental harm and missed opportunities for use of rural resources. Applying ecosystems services thinking to the governance of rural land would secure greater social value

Genetic risk factors for the development of allergic disease identified by genome-wide association

An increasing proportion of the worldwide population is affected by allergic diseases such as allergic rhinitis (AR), atopic dermatitis (AD) and allergic asthma and improved treatment options are needed particularly for severe, refractory disease. Allergic diseases are complex and development involves both environmental and genetic factors. Although the existence of a genetic component for allergy was first described almost 100 years ago, progress in gene identification has been hindered by lack of high throughput technologies to investigate genetic variation in large numbers of subjects. The development of Genome-Wide Association Studies (GWAS), a hypothesis-free method of interrogating large numbers of common variants spanning the entire genome in disease and non-disease subjects has revolutionised our understanding of the genetics of allergic disease. Susceptibility genes for asthma, AR and AD have now been identified with confidence, suggesting there are common and distinct genetic loci associated with these diseases, providing novel insights into potential disease pathways and mechanisms. Genes involved in both adaptive and innate immune mechanisms have been identified, notably including multiple genes involved in epithelial function/secretion, suggesting that the airway epithelium may be particularly important in asthma. Interestingly, concordance/discordance between the genetic factors driving allergic traits such as IgE levels and disease states such as asthma have further supported the accumulating evidence for heterogeneity in these diseases. While GWAS have been useful and continue to identify novel genes for allergic diseases through increased sample sizes and phenotype refinement, future approaches will integrate analyses of rare variants, epigenetic mechanisms and eQTL approaches, leading to greater insight into the genetic basis of these diseases. Gene identification will improve our understanding of disease mechanisms and generate potential therapeutic opportunities

Stolen wages, corruption, and selective application of the law : is APUNCAC a solution?

APUNCAC is a draft international convention designed to address systemic corruption, strengthening UNCAC’s provisions and adding mechanisms to make it more effective. ‘Corruption’ includes public officials abusing their powers. This article addresses an especially insidious form: when laws are created and applied to deny equal protection under the law. Ruling elites control the executive and parliament, to pass laws that selectively target and disadvantage a segment of the population. Our empirical data comes from a historical case, massive government-sanctioned wage theft from Western Australian Aboriginal workers between 1901 and 1972. We use these data to analyse how this kind of corruption works in practice, to evaluate APUNCAC’s measures and strategies, to see what specific measures might be used or modified, and where APUNCAC might need supplementing. We argue that Article 4(3) could have a major impact, especially supported by other Articles and processes, such as dedicated independent courts and strategic engagement with local courts. We evaluate two scenarios: The first scenario is prospective, assuming that APUNCAC is adopted. We evaluate the possible impact of APUNCAC in deterring future corruption involving selective application of the law. The second scenario is retrospective. We evaluate the possible support that APUNCAC might provide regarding court actions that seek redress for potential litigants, such as WA Aboriginal people who were injured in the past

Building livelihood resilience: a case study of factors affecting farm households’ adoption of coping and adaptive strategies in rural Nigeria

Recent research on social and ecological resilience has recognised the importance of identifying opportunities in adversities, providing a wealth of theoretical knowledge; but empirical evidence remains a major gap not only for sustainability debates but also for focusing development objectives. The aim of this paper is to identify aspect of rural livelihoods that assists in sustaining households’ coping and adaptive capacities during a crisis, thus attempting to diagnose which element of a livelihood has potential for maximising livelihood resilience and minimising vulnerabilities. This paper takes an example of how a society reorganises under a process of novel change by examining households’ coping and risk management strategies in response to shock and stress created by avian influenza (H5N1) outbreaks in rural Nigeria. Using a multivariate probit model accounting for complementarities and substitution effects, the paper shows the significance of social capital, market access, communal insurance and ex ante biosecurity investment in influencing responses and in strengthening coping capacities; and argues that these elements may also have potential for maintaining livelihood resilience in the rural area

Models of Rural Development and Approaches To Analysis Evaluation And Decision-Making

Les changements récents du cadre général du soutien public à l’agriculture, notamment l’importance croissante du second pilier de la PAC ont accru significativement l’intérêt porté à la politique de développement rural, et en conséquence le besoin d’une meilleure compréhension des processus qu’elle est supposée influencer. La diversité spatiale de l’activité économique rurale et la forte dépendance des espaces ruraux par rapport à l’activité urbaine a pour conséquence que les modèles basés sur un seul secteur, centrés sur une seule activité économique ou bien sur des hypothèses de simple différenciation entre espaces urbains et ruraux sont sujets à de nombreuses interrogations. En partant de l’expérience du Royaume-Uni, l’article repère un ensemble de modèles alternatifs : sectoriel, multisectoriel, territorial et local, qui représentent les différentes approches adoptées par les politiques de développement rural. Il avance que la nature du développement rural a connu des changements fondamentaux qui ont des implications profondes sur l’analyse et l’évaluation de la politique publique. Cela demande de trouver un équilibre entre l’évaluation quantitative aux implications limitées et la compréhension de la sociologie des espaces ruraux aux bases empiriques relativement ténues. L’article conclut en suggérant de nouvelles directions pour améliorer l’analyse des interventions conçues pour stimuler le développement rural.Recent changes to the framework of agricultural support, particularly the rising prominence of the ‘Second Pillar’ of the CAP, have stimulated an increasing interest in rural development policy, and consequently a need for better understanding of the processes it is designed to influence. The spatial diversity of rural economic activity, and a high level of dependence of the countryside on urban economic activity, implies that models based on a single sector, that focus only on economic activity or that assume a simple differentiation between urban and rural are problematic. Drawing particularly on experience within the United Kingdom, the paper identifies a series of alternative models: sectoral, multisectoral, territorial and local that represent the different approaches that have been taken to rural development policy, and argues that the nature of rural development has undergone fundamental changes that have profound implications for analysis and evaluation of policy. This involves balancing the reductionist implications of quantitative evaluation against the relatively slender empirical base of rural sociological understanding. The paper concludes by suggesting new directions for improved approaches towards interventions designed to promote rural development

Creating restoration landscapes: partnerships in large-scale conservation in the UK

It is increasingly recognized that ecological restoration demands conservation action beyond the borders of existing protected areas. This requires the coordination of land uses and management over a larger area, usually with a range of partners, which presents novel institutional challenges for conservation planners. Interviews were undertaken with managers of a purposive sample of large-scale conservation areas in the UK. Interviews were open-ended and analyzed using standard qualitative methods. Results show a wide variety of organizations are involved in large-scale conservation projects, and that partnerships take time to create and demand resilience in the face of different organizational practices, staff turnover, and short-term funding. Successful partnerships with local communities depend on the establishment of trust and the availability of external funds to support conservation land uses. We conclude that there is no single institutional model for large-scale conservation: success depends on finding institutional strategies that secure long-term conservation outcomes, and ensure that conservation gains are not reversed when funding runs out, private owners change priorities, or land changes hands

Farmers’ spending on variable inputs tends to maximise crop yields, not profit

We estimate the marginal returns to spending on Crop Variable Inputs (CVI) (such as fertilizers and crop protection), to explore whether observed spending maximises physical or economic returns to farmers. Data are taken from the Farm Business Survey for 2004-2013, where gross margins and input spending are available, in over 10,300 crops of conventional winter wheat or oilseed rape in England and Wales. Marginal spending on CVIs generate financial returns significantly less than £1 per marginal pound spent. This suggests that expenditure on CVIs exceeds an economic optimum that would maximise profit. However marginal physical products (crop yields) are positive, but small and significantly different from zero. This suggests that, on average, farmers approximately maximise yields. These results hold across a wide range of alternative economic models and two crop species. Similar results have been reported in estimations for Indian grain production and for maize in China. In practice, farmers are making decisions on input use in advance of having information on a variety of factors, including future yield, product quality and price, making it difficult to optimise input levels according to expected profit. Farmers may be consistently optimistic, prefer to avoid risk, or deliberately seek to maximise yields. Some farmers may put on the standard recommended application irrespective of input or expected output price. It is also possible that advice may sometimes aim to maximise yield, influenced by an incentive to encourage greater sales. Excessive input use both reduces private profits and is a cause of environmental damage. There are thus potential private as well as social benefits to be gained from optimising levels of input use

Application of Artificial Neural Network to Search for Gravitational-Wave Signals Associated with Short Gamma-Ray Bursts

We apply a machine learning algorithm, the artificial neural network, to the search for gravitational-wave signals associated with short gamma-ray bursts. The multi-dimensional samples consisting of data corresponding to the statistical and physical quantities from the coherent search pipeline are fed into the artificial neural network to distinguish simulated gravitational-wave signals from background noise artifacts. Our result shows that the data classification efficiency at a fixed false alarm probability is improved by the artificial neural network in comparison to the conventional detection statistic. Therefore, this algorithm increases the distance at which a gravitational-wave signal could be observed in coincidence with a gamma-ray burst. In order to demonstrate the performance, we also evaluate a few seconds of gravitational-wave data segment using the trained networks and obtain the false alarm probability. We suggest that the artificial neural network can be a complementary method to the conventional detection statistic for identifying gravitational-wave signals related to the short gamma-ray bursts.Comment: 30 pages, 10 figure

Journeys in big data statistics

The realm of big data is a very wide and varied one. We discuss old, new, small and big data, with some of the important challenges including dealing with highly-structured and object-oriented data. In many applications the objective is to discern patterns and learn from large datasets of historical data. We shall discuss such issues in some transportation network applications in non-academic settings, which are naturally applicable to other situations. Vital aspects include dealing with logistics, coding and choosing appropriate statistical methodology, and we provide a summary and checklist for wider implementation