Use of airborne remote sensing to detect riverside Brassica rapa to aid in risk assessment of transgenic crops

High resolution descriptions of plant distribution have utility for many ecological applications but are especially useful for predictive modelling of gene flow from transgenic crops. Difficulty lies in the extrapolation errors that occur when limited ground survey data are scaled up to the landscape or national level. This problem is epitomized by the wide confidence limits generated in a previous attempt to describe the national abundance of riverside Brassica rapa (a wild relative of cultivated rapeseed) across the United Kingdom. Here, we assess the value of airborne remote sensing to locate B. rapa over large areas and so reduce the need for extrapolation. We describe results from flights over the river Nene in England acquired using Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) imagery, together with ground truth data. It proved possible to detect 97% of flowering B. rapa on the basis of spectral profiles. This included all stands of plants that occupied >2m square (>5 plants), which were detected using single-pixel classification. It also included very small populations (<5 flowering plants, 1-2m square) that generated mixed pixels, which were detected using spectral unmixing. The high detection accuracy for flowering B. rapa was coupled with a rather large false positive rate (43%). The latter could be reduced by using the image detections to target fieldwork to confirm species identity, or by acquiring additional remote sensing data such as laser altimetry or multitemporal imagery.

The CAP and EU enlargement: Prospects for an alternative strategy to avoid the lock-in of CAP support

The integration of the central and east European countries (CEECs) into the Common Agricultural Policy (CAP) could become a major problem. At the Copenhagen European summit in December 2002, the EU agreed a transitional period with a gradual phasing in of direct payments. However, this strategy will not solve the problems of the CAP: budgetary limits remain problematic, the policy ignores possible developments in the World Trade Organization (WTO), and the extension of direct payments to the CEECs will further capitalize, and hence lock-in, agricultural support. The latter makes future reform even more difficult and, to overcome these problems, we suggest an alternative strategy to integrate the CEECs into the CAP. The EU should phase out direct payments by applying a bond scheme. Finally, we consider whether this option is politically viable.

Consumer attitudes towards and willingness to pay for pesticide residue limit compliant 'safe' vegetables in Northeast Thailand

Pesticide residue in vegetables is a major food safety issue in Thailand. A range of vegetable products (organic/pesticide-free/ hydroponic) has emerged in Thai markets that guarantee compliance with maximum residue limits. The Government of Thailand is eager to extend the benefits of this suite of alternative vegetables to the entire population, particularly the semi-urban/rural segments that are often bypassed by such speciality products. However, little information is available to guide such an effort, particularly with regard to up-country consumer attitudes, shopping and consumption habits and willingness to pay premiums for such produce. This research aims to fill this gap in knowledge. It reports the results of a survey of vegetable consumption and shopping habits and attitudes of 608 consumers in northeast Thailand. Willingness to pay premiums for pesticide residue limit compliant vegetables is also assessed by using a contingent valuation method, and determinants of willingness to pay are examined using an ordered probit empirical model. Results indicate that, given adequate awareness of relative risks, even up-country consumers are willing to pay market premium levels for these products, and that inadequate availability, rather than lack of demand is the constraining factor. Willingness to pay is found to increase with income, age and supermarket sourcing of vegetables. We also discuss the challenge of improving availability at mainstream outlets.

Mutational meltdown in primary endosymbionts: selection limits Muller's ratchet

Background Primary bacterial endosymbionts of insects (p-endosymbionts) are thought to be undergoing the process of Muller's ratchet where they accrue slightly deleterious mutations due to genetic drift in small populations with negligible recombination rates. If this process were to go unchecked over time, theory predicts mutational meltdown and eventual extinction. Although genome degradation is common among p-endosymbionts, we do not observe widespread p-endosymbiont extinction, suggesting that Muller's ratchet may be slowed or even stopped over time. For example, selection may act to slow the effects of Muller's ratchet by removing slightly deleterious mutations before they go to fixation thereby causing a decrease in nucleotide substitutions rates in older p-endosymbiont lineages. Methodology/Principal Findings To determine whether selection is slowing the effects of Muller's ratchet, we determined the age of the Candidatus Riesia/sucking louse assemblage and analyzed the nucleotide substitution rates of several p-endosymbiont lineages that differ in the length of time that they have been associated with their insect hosts. We find that Riesia is the youngest p-endosymbiont known to date, and has been associated with its louse hosts for only 13–25 My. Further, it is the fastest evolving p-endosymbiont with substitution rates of 19–34% per 50 My. When comparing Riesia to other insect p-endosymbionts, we find that nucleotide substitution rates decrease dramatically as the age of endosymbiosis increases. Conclusions/Significance A decrease in nucleotide substitution rates over time suggests that selection may be limiting the effects of Muller's ratchet by removing individuals with the highest mutational loads and decreasing the rate at which new mutations become fixed. This countering effect of selection could slow the overall rate of endosymbiont extinction.

Mutations in H5N1 influenza virus hemagglutinin that confer binding to human tracheal airway epithelium

The emergence in 2009 of a swine-origin H1N1 influenza virus as the first pandemic of the 21st Century is a timely reminder of the international public health impact of influenza viruses, even those associated with mild disease. The widespread distribution of highly pathogenic H5N1 influenza virus in the avian population has spawned concern that it may give rise to a human influenza pandemic. The mortality rate associated with occasional human infection by H5N1 virus approximates 60%, suggesting that an H5N1 pandemic would be devastating to global health and economy. To date, the H5N1 virus has not acquired the propensity to transmit efficiently between humans. The reasons behind this are unclear, especially given the high mutation rate associated with influenza virus replication. Here we used a panel of recombinant H5 hemagglutinin (HA) variants to demonstrate the potential for H5 HA to bind human airway epithelium, the predominant target tissue for influenza virus infection and spread. While parental H5 HA exhibited limited binding to human tracheal epithelium, introduction of selected mutations converted the binding profile to that of a current human influenza strain HA. Strikingly, these amino-acid changes required multiple simultaneous mutations in the genomes of naturally occurring H5 isolates. Moreover, H5 HAs bearing intermediate sequences failed to bind airway tissues and likely represent mutations that are an evolutionary "dead end." We conclude that, although genetic changes that adapt H5 to human airways can be demonstrated, they may not readily arise during natural virus replication. This genetic barrier limits the likelihood that current H5 viruses will originate a human pandemic.

Use of airborne remote sensing to detect riverside Brassica rapa to aid in risk assessment of transgenic crops

High resolution descriptions of plant distribution have utility for many ecological applications but are especially useful for predictive modeling of gene flow from transgenic crops. Difficulty lies in the extrapolation errors that occur when limited ground survey data are scaled up to the landscape or national level. This problem is epitomized by the wide confidence limits generated in a previous attempt to describe the national abundance of riverside Brassica rapa (a wild relative of cultivated rapeseed) across the United Kingdom. Here, we assess the value of airborne remote sensing to locate B. rapa over large areas and so reduce the need for extrapolation. We describe results from flights over the river Nene in England acquired using Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) imagery, together with ground truth data. It proved possible to detect 97% of flowering B. rapa on the basis of spectral profiles. This included all stands of plants that occupied >2m square (>5 plants), which were detected using single-pixel classification. It also included very small populations (<5 flowering plants, 1-2m square) that generated mixed pixels, which were detected using spectral unmixing. The high detection accuracy for flowering B. rapa was coupled with a rather large false positive rate (43%). The latter could be reduced by using the image detections to target fieldwork to confirm species identity, or by acquiring additional remote sensing data such as laser altimetry or multitemporal imagery.

From a discrete to a continuum model of cell dynamics in one dimension

Multiscale modeling is emerging as one of the key challenges in mathematical biology. However, the recent rapid increase in the number of modeling methodologies being used to describe cell populations has raised a number of interesting questions. For example, at the cellular scale, how can the appropriate discrete cell-level model be identified in a given context? Additionally, how can the many phenomenological assumptions used in the derivation of models at the continuum scale be related to individual cell behavior? In order to begin to address such questions, we consider a discrete one-dimensional cell-based model in which cells are assumed to interact via linear springs. From the discrete equations of motion, the continuous Rouse [P. E. Rouse, J. Chem. Phys. 21, 1272 (1953)] model is obtained. This formalism readily allows the definition of a cell number density for which a nonlinear "fast" diffusion equation is derived. Excellent agreement is demonstrated between the continuum and discrete models. Subsequently, via the incorporation of cell division, we demonstrate that the derived nonlinear diffusion model is robust to the inclusion of more realistic biological detail. In the limit of stiff springs, where cells can be considered to be incompressible, we show that cell velocity can be directly related to cell production. This assumption is frequently made in the literature but our derivation places limits on its validity. Finally, the model is compared with a model of a similar form recently derived for a different discrete cell-based model and it is shown how the different diffusion coefficients can be understood in terms of the underlying assumptions about cell behavior in the respective discrete models.

ONeSAMP: a program to estimate effective population size using approximate Bayesian computation

The estimation of effective population size from one sample of genotypes has been problematic because most estimators have been proven imprecise or biased. We developed a web-based program, ONeSAMP that uses approximate Bayesian computation to estimate effective population size from a sample of microsatellite genotypes. ONeSAMP requires an input file of sampled individuals' microsatellite genotypes along with information about several sampling and biological parameters. ONeSAMP provides an estimate of effective population size, along with 95% credible limits. We illustrate the use of ONeSAMP with an example data set from a re-introduced population of ibex Capra ibex.

Assessing the date of the global oil peak: the need to use 2P reserves

Combining geological knowledge with proved plus probable ('2P') oil discovery data indicates that over 60 countries are now past their resource-limited peak of conventional oil production. The data show that the global peak of conventional oil production is close. Many analysts who rely only on proved ('1P') oil reserves data draw a very different conclusion. But proved oil reserves contain no information about the true size of discoveries, being variously under-reported, over-reported and not reported. Reliance on 1P data has led to a number of misconceptions, including the notion that past oil forecasts were incorrect, that oil reserves grow very significantly due to technology gain, and that the global supply of oil is ensured provided sufficient investment is forthcoming to 'turn resources into reserves'. These misconceptions have been widely held, including within academia, governments, some oil companies, and organisations such as the IEA. In addition to conventional oil, the world contains large quantities of non-conventional oil. Most current detailed models show that past the conventional oil peak the non-conventional oils are unlikely to come on-stream fast enough to offset conventional's decline. To determine the extent of future oil supply constraints calculations are required to determine fundamental rate limits for the production of non-conventional oils, as well as oil from gas, coal and biomass, and of oil substitution. Such assessments will need to examine technological readiness and lead-times, as well as rate constraints on investment, pollution, and net-energy return. (C) 2007 Elsevier Ltd. All rights reserved.

Joint modelling of obstacle induced and mesoscale changes: current limits and challenges

Obstacles considerably influence boundary layer processes. Their influences have been included in mesoscale models (MeM) for a long time. Methods used to parameterise obstacle effects in a MeM are summarised in this paper using results of the mesoscale model METRAS as examples. Besides the parameterisation of obstacle influences it is also possible to use a joint modelling approach to describe obstacle induced and mesoscale changes. Three different methods may be used for joint modelling approaches: The first method is a time-slice approach, where steady basic state profiles are used in an obstacle resolving microscale model (MiM, example model MITRAS) and diurnal cycles are derived by joining steady-state MITRAS results. The second joint modelling approach is one-way nesting, where the MeM results are used to initialise the MiM and to drive the boundary values of the MiM dependent on time. The third joint modelling approach is to apply multi-scale models or two-way nesting approaches, which include feedbacks from the MiM to the MeM. The advantages and disadvantages of the different approaches and remaining problems with joint Reynolds-averaged Navier–Stokes modelling approaches are summarised in the paper.

A model for exchange rates with crawling bands: an application to the Colombian peso

This paper builds upon previous research on currency bands, and provides a model for the Colombian peso. Stochastic differential equations are combined with information related to the Colombian currency band to estimate competing models of the behaviour of the Colombian peso within the limits of the currency band. The resulting moments of the density function for the simulated returns describe adequately most of the characteristics of the sample returns data. The factor included to account for the intra-marginal intervention performed to drive the rate towards the Central Parity accounts only for 6.5% of the daily change, which supports the argument that intervention, if performed by the Central Bank, it is not directed to push the currency towards the limits. Moreover, the credibility of the Colombian Central Bank, Banco de la República’s ability to defend the band seems low.

Exploring social barriers to adaptation: insights from Western Nepal

As the challenges and opportunities posed by climate change become increasingly apparent, the need for facilitating successful adaptation and enhancing adaptive capacity within the context of sustainable development is clear. With adaptation high on the agenda, the notion of limits and barriers to adaptation has recently received much attention within both academic and policymaking spheres. While emerging literature has been quick to depict limits and barriers in terms of natural, financial, or technologic processes, there is a clear shortfall in acknowledging social barriers to adaptation. It is against such a backdrop that this paper sets out to expose and explore some of the underlying features of social barriers to adaptation, drawing on insights from two case studies in the Western Nepal. This paper exposes the significant role of cognitive, normative and institutional factors in both influencing and prescribing adaptation. It explores how restrictive social environments can limit adaptation actions and influence adaptive capacity at the local level, particularly for the marginalised and socially excluded. The findings suggest a need for greater recognition of the diversity and complexity of social barriers, strategic planning and incorporation at national and local levels, as well as an emphasis on tackling the underlying drivers of vulnerability and social exclusion.

Bistable systems with stochastic noise: virtues and limits of effective one-dimensional Langevin equations

The understanding of the statistical properties and of the dynamics of multistable systems is gaining more and more importance in a vast variety of scientific fields. This is especially relevant for the investigation of the tipping points of complex systems. Sometimes, in order to understand the time series of given observables exhibiting bimodal distributions, simple one-dimensional Langevin models are fitted to reproduce the observed statistical properties, and used to investing-ate the projected dynamics of the observable. This is of great relevance for studying potential catastrophic changes in the properties of the underlying system or resonant behaviours like those related to stochastic resonance-like mechanisms. In this paper, we propose a framework for encasing this kind of studies, using simple box models of the oceanic circulation and choosing as observable the strength of the thermohaline circulation. We study the statistical properties of the transitions between the two modes of operation of the thermohaline circulation under symmetric boundary forcings and test their agreement with simplified one-dimensional phenomenological theories. We extend our analysis to include stochastic resonance-like amplification processes. We conclude that fitted one-dimensional Langevin models, when closely scrutinised, may result to be more ad-hoc than they seem, lacking robustness and/or well-posedness. They should be treated with care, more as an empiric descriptive tool than as methodology with predictive power.

Valuation and arbitrage

The use of discounted cash flow (DCF) methods in investment valuation and appraisal is argued by many academics as being rational and more rigorous than the traditional capitalisation model. However those advocates of DCF should be cautious in their claims for rationality. The various DCF models all rely upon an all-encompassing equated yield (IRR) within the calculation. This paper will argue that this is a simplification of the risk perception which the investor places on the income profile from property. In determining the long term capital value of a property an 'average' DCF method will produce the 'correct' price, however, the individual short term values of each cash-flow may differ significantly. In the UK property market today, where we are facing a period in which prices are not expected to rise generally at the same rate or with such persistence as hitherto, investors and tenants are increasingly concerned with the down side implications of rental growth and investors may indeed be interested in trading property over a shorter investment horizon than they had originally planned. The purpose of this paper is therefore to bring to the analysis a rigorous framework which can be used to analyse the constituent cash flows within the freehold valuation. We show that the arbitrage analysis lends itself to segregating the capital value of the cash flows in a way which is more appropriate for financial investors