Modelling simultaneously water content and dry matter dynamics of wheat grains

A model was devised to describe simultaneously the grain masses of water and dry matter against thermal time during grain filling and maturation of winter wheat. The model accounted for a linear increase in water mass of duration anthesis-m(1) (end of rapid water assimilation phase) and rate a, followed by a more stable water mass until in,, after which water mass declined rapidly at rate e. Grain dry matter was described as a linear increase of rate bgf until a maximum size (maxgf) was attained at m(2).The model was fitted to plot data from weekly samples of grains taken from replicated field experiments investigating effects of grain position (apical or medial), fungicide (five contrasting treatments), sowing date (early or late), cultivar (Malacca or Shamrock) and season (2001/2002 and 2002/2003) on grain filling. The model accounted for between 83 and 99% of the variation ( 2) when fitted to data from individual plots, and between 97 and 99% when fitted to treatment means. Endosperm cell number of grains from early-sown plots in the first season were also counted. Differences in maxgf between grain positions and also between cultivars were mostly the result of effects on bgf and were empirically associated with water mass at nil. Fungicide application controlled S. tritici and powdery mildew infection, delayed flag leaf senescence, increased water mass at m(1) (wm(1)), and also increased m(2), bgf and maxgf. Fungicide effects on water mass were detected before fungicide effects on dry matter, but comparison of the effects of individual fungicide treatments showed no evidence that effects on wm(1), nor on endosperm cell numbers at about m(1), were required for fungicide effects on maxgf, (c) 2005 Elsevier B.V. All rights reserved.

Trophic interactions in a changing world: modelling aboveground-belowground interactions

The rate and scale of human-driven changes can exert profound impacts on ecosystems, the species that make them up and the services they provide that sustain humanity. Given the speed at which these changes are occurring, one of society's major challenges is to coexist within ecosystems and to manage ecosystem services in a sustainable way. The effect of possible scenarios of global change on ecosystem services can be explored using ecosystem models. Such models should adequately represent ecosystem processes above and below the soil surface (aboveground and belowground) and the interactions between them. We explore possibilities to include such interactions into ecosystem models at scales that range from global to local. At the regional to global scale we suggest to expand the plant functional type concept (aggregating plants into groups according to their physiological attributes) to include functional types of aboveground-belowground interactions. At the scale of discrete plant communities, process-based and organism-oriented models could be combined into "hybrid approaches" that include organism-oriented mechanistic representation of a limited number of trophic interactions in an otherwise process - oriented approach. Under global change the density and activity of organisms determining the processes may change non-linearly and therefore explicit knowledge of the organisms and their responses should ideally be included. At the individual plant scale a common organism-based conceptual model of aboveground-belowground interactions has emerged. This conceptual model facilitates the formulation of research questions to guide experiments aiming to identify patterns that are common within, but differ between, ecosystem types and biomes. Such experiments inform modelling approaches at larger scales. Future ecosystem models should better include this evolving knowledge of common patterns of aboveground-belowground interactions. Improved ecosystem models are necessary toots to reduce the uncertainty in the information that assists us in the sustainable management of our environment in a changing world. (C) 2004 Elsevier GmbH. All rights reserved.

World Health Organization dietary norms: a quantitative evaluation of potential consumption impacts in the United States, United Kingdom, and France

The member countries of the World Health Organization have endorsed its Global Strategy on Diet, Physical Activity, and Health. We assess the potential consumption impacts of these norms in the United States, France, and the United Kingdom using a mathematical programming approach. We find that adherence would involve large reductions in the consumption of fats and oils accompanying large rises in the consumption of fruits, vegetables, and cereal. Further, in the United Kingdom and the United States, but not France, sugar intakes would have to shrink considerably. Focusing on sub-populations within each country, we find that the least educated, not necessarily the poorest, would have to bear the highest burden of adjustment.

Food consumption impacts of adherence to dietary norms in the United States: a quantitative assessment

Promotion of adherence to healthy-eating norms has become an important element of nutrition policy in the United States and other developed countries. We assess the potential consumption impacts of adherence to a set of recommended dietary norms in the United States using a mathematical programming approach. We find that adherence to recommended dietary norms would involve significant changes in diets, with large reductions in the consumption of fats and oils along with large increases in the consumption of fruits, vegetables, and cereals. Compliance with norms recommended by the World Health Organization for energy derived from sugar would involve sharp reductions in sugar intakes. We also analyze how dietary adjustments required vary across demographic groups. Most socio-demographic characteristics appear to have relatively little influence on the pattern of adjustment required to comply with norms, Income levels have little effect on required dietary adjustments. Education is the only characteristic to have a significant influence on the magnitude of adjustments required. The least educated rather than the poorest have to bear the highest burden of adjustment. Out- analysis suggests that fiscal measures like nutrient-based taxes may not be as regressive as commonly believed. Dissemination of healthy-eating norms to the less educated will be a key challenge for nutrition policy.

Food consumption impacts of adherence to dietary norms in the United States: a quantitative assessment

Promotion of adherence to healthy-eating norms has become an important element of nutrition policy in the United States and other developed countries. We assess the potential consumption impacts of adherence to a set of recommended dietary norms in the United States using a mathematical programming approach. We find that adherence to recommended dietary norms would involve significant changes in diets, with large reductions in the consumption of fats and oils along with large increases in the consumption of fruits, vegetables, and cereals. Compliance with norms recommended by the World Health Organization for energy derived from sugar would involve sharp reductions in sugar intakes. We also analyze how dietary adjustments required vary across demographic groups. Most socio-demographic characteristics appear to have relatively little influence on the pattern of adjustment required to comply with norms, Income levels have little effect on required dietary adjustments. Education is the only characteristic to have a significant influence on the magnitude of adjustments required. The least educated rather than the poorest have to bear the highest burden of adjustment. Out- analysis suggests that fiscal measures like nutrient-based taxes may not be as regressive as commonly believed. Dissemination of healthy-eating norms to the less educated will be a key challenge for nutrition policy.

An assessment of the potential consumption impacts of WHO dietary norms in OECD countries

The member countries of the World Health Organization (WHO) have recently endorsed its global strategy on diet, physical activity and health. The strategy emphasises the need to limit the consumption of saturated fats and trans-fatty acids, salt and sugars, and to increase consumption of fruits and vegetables in order to combat the growing burden of non-communicable diseases. This paper attempts a broad quantitative assessment of the consumption impacts of these norms in OECD countries using a mathematical programming approach. We find that adherence to the WHO norms would involve a significant decrease in the consumption of vegetable oils (30%), dairy products (28%), sugar (24%), animal fats (30%) and meat (pig meat, 13.5%, mutton and goat 14.5%) and a significant increase in the human consumption of cereals (31%), fruits (25%) and vegetables (21%). (c) 2005 Elsevier Ltd. All rights reserved.

Modelling the partitioning of evapotranspiration in a maize-sunflower intercrop

The primary purpose of this study was to model the partitioning of evapotranspiration in a maize-sunflower intercrop at various canopy covers. The Shuttleworth-Wallace (SW) model was extended for intercropping systems to include both crop transpiration and soil evaporation and allowing interaction between the two. To test the accuracy of the extended SW model, two field experiments of maize-sunflower intercrop were conducted in 1998 and 1999. Plant transpiration and soil evaporation were measured using sap flow gauges and lysimeters, respectively. The mean prediction error (simulated minus measured values) for transpiration was zero (which indicated no overall bias in estimation error), and its accuracy was not affected by the plant growth stages, but simulated transpiration during high measured transpiration rates tended to be slightly underestimated. Overall, the predictions for daily soil evaporation were also accurate. Model estimation errors were probably due to the simplified modelling of soil water content, stomatal resistances and soil heat flux as well as due to the uncertainties in characterising the 2 micrometeorological conditions. The SW’s prediction of transpiration was most sensitive to parameters most directly related to the canopy characteristics such as the partitioning of captured solar radiation, canopy resistance, and bulk boundary layer resistance.

An illustration of the modelling of cost and efficacy data from a clinical trial

Health care providers, purchasers and policy makers need to make informed decisions regarding the provision of cost-effective care. When a new health care intervention is to be compared with the current standard, an economic evaluation alongside an evaluation of health benefits provides useful information for the decision making process. We consider the information on cost-effectiveness which arises from an individual clinical trial comparing the two interventions. Recent methods for conducting a cost-effectiveness analysis for a clinical trial have focused on the net benefit parameter. The net benefit parameter, a function of costs and health benefits, is positive if the new intervention is cost-effective compared with the standard. In this paper we describe frequentist and Bayesian approaches to cost-effectiveness analysis which have been suggested in the literature and apply them to data from a clinical trial comparing laparoscopic surgery with open mesh surgery for the repair of inguinal hernias. We extend the Bayesian model to allow the total cost to be divided into a number of different components. The advantages and disadvantages of the different approaches are discussed. In January 2001, NICE issued guidance on the type of surgery to be used for inguinal hernia repair. We discuss our example in the light of this information. Copyright © 2003 John Wiley & Sons, Ltd.

Epidemiological risk assessment using linked network and grid based modelling: Phytophthora ramorum and Phytophthora kernoviae in the UK

We developed a stochastic simulation model incorporating most processes likely to be important in the spread of Phytophthora ramorum and similar diseases across the British landscape (covering Rhododendron ponticum in woodland and nurseries, and Vaccinium myrtillus in heathland). The simulation allows for movements of diseased plants within a realistically modelled trade network and long-distance natural dispersal. A series of simulation experiments were run with the model, representing an experiment varying the epidemic pressure and linkage between natural vegetation and horticultural trade, with or without disease spread in commercial trade, and with or without inspections-with-eradication, to give a 2 x 2 x 2 x 2 factorial started at 10 arbitrary locations spread across England. Fifty replicate simulations were made at each set of parameter values. Individual epidemics varied dramatically in size due to stochastic effects throughout the model. Across a range of epidemic pressures, the size of the epidemic was 5-13 times larger when commercial movement of plants was included. A key unknown factor in the system is the area of susceptible habitat outside the nursery system. Inspections, with a probability of detection and efficiency of infected-plant removal of 80% and made at 90-day intervals, reduced the size of epidemics by about 60% across the three sectors with a density of 1% susceptible plants in broadleaf woodland and heathland. Reducing this density to 0.1% largely isolated the trade network, so that inspections reduced the final epidemic size by over 90%, and most epidemics ended without escape into nature. Even in this case, however, major wild epidemics developed in a few percent of cases. Provided the number of new introductions remains low, the current inspection policy will control most epidemics. However, as the rate of introduction increases, it can overwhelm any reasonable inspection regime, largely due to spread prior to detection. (C) 2009 Elsevier B.V. All rights reserved.

Spatiotemporal modelling of CheY complexes in Escherichia coli chemotaxis

The chemotaxis pathway of Escherichia coli is one of the best studied and modelled biological signalling pathways. Here we extend existing modelling approaches by explicitly including a description of the formation and subcellular localization of intermediary complexes in the phosphotransfer pathway. The inclusion of these complexes shows that only about 60% of the total output response regulator (CheY) is uncomplexed at any moment and hence free to interact with its target, the flagellar motor. A clear strength of this model is its ability to predict the experimentally observable subcellular localization of CheY throughout a chemotactic response. We have found good agreement between the model output and experimentally determined CheY localization patterns. (C) 2009 Elsevier Ltd. All rights reserved.

Monthly average temperature modelling

This research is associated with the goal of the horticultural sector of the Colombian southwest, which is to obtain climatic information, specifically, to predict the monthly average temperature in sites where it has not been measured. The data correspond to monthly average temperature, and were recorded in meteorological stations at Valle del Cauca, Colombia, South America. Two components are identified in the data of this research: (1) a component due to the temporal aspects, determined by characteristics of the time series, distribution of the monthly average temperature through the months and the temporal phenomena, which increased (El Nino) and decreased (La Nina) the temperature values, and (2) a component due to the sites, which is determined for the clear differentiation of two populations, the valley and the mountains, which are associated with the pattern of monthly average temperature and with the altitude. Finally, due to the closeness between meteorological stations it is possible to find spatial correlation between data from nearby sites. In the first instance a random coefficient model without spatial covariance structure in the errors is obtained by month and geographical location (mountains and valley, respectively). Models for wet periods in mountains show a normal distribution in the errors; models for the valley and dry periods in mountains do not exhibit a normal pattern in the errors. In models of mountains and wet periods, omni-directional weighted variograms for residuals show spatial continuity. The random coefficient model without spatial covariance structure in the errors and the random coefficient model with spatial covariance structure in the errors are capturing the influence of the El Nino and La Nina phenomena, which indicates that the inclusion of the random part in the model is appropriate. The altitude variable contributes significantly in the models for mountains. In general, the cross-validation process indicates that the random coefficient model with spatial spherical and the random coefficient model with spatial Gaussian are the best models for the wet periods in mountains, and the worst model is the model used by the Colombian Institute for Meteorology, Hydrology and Environmental Studies (IDEAM) to predict temperature.

Modelling heterotachy in phylogenetic inference by reversible-jump Markov chain Monte Carlo

The rate at which a given site in a gene sequence alignment evolves over time may vary. This phenomenon-known as heterotachy-can bias or distort phylogenetic trees inferred from models of sequence evolution that assume rates of evolution are constant. Here, we describe a phylogenetic mixture model designed to accommodate heterotachy. The method sums the likelihood of the data at each site over more than one set of branch lengths on the same tree topology. A branch-length set that is best for one site may differ from the branch-length set that is best for some other site, thereby allowing different sites to have different rates of change throughout the tree. Because rate variation may not be present in all branches, we use a reversible-jump Markov chain Monte Carlo algorithm to identify those branches in which reliable amounts of heterotachy occur. We implement the method in combination with our 'pattern-heterogeneity' mixture model, applying it to simulated data and five published datasets. We find that complex evolutionary signals of heterotachy are routinely present over and above variation in the rate or pattern of evolution across sites, that the reversible-jump method requires far fewer parameters than conventional mixture models to describe it, and serves to identify the regions of the tree in which heterotachy is most pronounced. The reversible-jump procedure also removes the need for a posteriori tests of 'significance' such as the Akaike or Bayesian information criterion tests, or Bayes factors. Heterotachy has important consequences for the correct reconstruction of phylogenies as well as for tests of hypotheses that rely on accurate branch-length information. These include molecular clocks, analyses of tempo and mode of evolution, comparative studies and ancestral state reconstruction. The model is available from the authors' website, and can be used for the analysis of both nucleotide and morphological data.