Fast dispersal simulation using bivariate quantiles

Spatial-temporal models of the spread of invasive species can require dispersal of large numbers of individuals from many locations at recurrent times, making them slow to execute. We present a fast algorithm for simulating dispersal of large numbers of individuals. The algorithm is stochastic and can be applied using any bivariate probability density function as the dispersal kernel. It achieves computational efficiency while still allowing the simulation of rare and important long-distance dispersals by combining different approaches for within and outside the tail of the dispersal kernel. The tail is specified by a given bivariate quantile, where the q-th bivariate quantile is defined to be the contour of equiprobability within which a proportion 0< q <1 of dispersing individuals will settle. We provide a method for finding bivariate quantiles that can be applied to any bivariate dispersal kernel derived from independent densities for distance and direction of dispersal. To illustrate this approach, we show how the Cauchy distribution can be used to produce isotropic and anisotropic bivariate dispersal kernels by assuming that the direction of dispersal is either random or takes a von Mises distribution. We show that the algorithm is considerably faster than generating individual random samples from a bivariate dispersal kernel. It also performs better for larger grid sizes, and when there are larger numbers of individuals to be spread, than an approach that generates samples from a Binomial distribution for each grid cell using the probability of dispersal to that cell. The degree of computational efficiency achieved by the algorithm compared to the Binomial approach depends upon the speed with which random sample scan be generated from the tail of the bivariate dispersal kernel used

A spatio-temporal modelling framework for assessing the impact of weed management technologies on the spread of herbicide resistance

This paper presents a spatio-temporal modelling framework for predicting the spread of herbicide resistance. It includes a model of the population dynamics of weeds growing in competition with crops, a polygenic model of the development of herbicide resistance, and gene transfer by means of pollen and seed movement. The framework is used to predict the long-term spread of resistant weeds given different integrated weed management choices combining tillage and herbicide treatments, and seed capture at harvest. The model’s predictions will be used to devise management options that minimise the spread of herbicide resistant weeds

Real-world recommendations: Do limits to validation constrain model usefulness?

This paper describes efforts to validate a model of glyphosate resistance in awnless barnyard grass (Echinochloa colona (L.) Link.) in the sub-tropical northern grains region of Australia. Possible constraints to the perceived usefulness of the model due to hidden or sparsely documented system factors are discussed. The evolution of herbicide resistance in real weed populations becomes apparent only after years or decades of selection. Modelling is therefore particularly useful in investigating and describing the change in the weed population and the relative importance of different factors pushing towards or mitigating against that change. A key role of modelling in farming systems research is to improve understanding of issues such as the evolution of herbicide resistance. However, model results are increasingly important for formulating or adjusting recommendations, including for resistance prevention, to be used by land managers. Importantly, the research projects under which models of agricultural systems are produced are likely to include the development or refinement of recommendations for change as part of their expected outcomes. The comprehensiveness of model validation can be thought to equate generally to the strength of an argument in favour of a model's hypotheses. By extension (and by convention), more comprehensive validation is often given to equate to a stronger argument in favour of practical recommendations that arise more or less directly from the model's outputs. That is, increasing confidence in the recommendations derived from a model is a result of the perceived validation of the model's predictions as much as of its hypotheses. Conversely, validation that is (by necessity or otherwise) partial or piecemeal, and which is structural rather than empirical, may not be seen as providing as secure an argument in favour of any recommendations for farmers that may be made. In the case of glyphosate resistance, hidden weed population variables and insufficiently detailed farming systems data make empirical, operational validation difficult. It is especially difficult to validate these models in time for them to be most useful in formulating practical recommendations for resistance prevention. A model of glyphosate resistance in awnless barnyard grass, a key northern Australian weed has been constructed, and attempts made to validate it in order to encourage trust in the model's predictions and the recommendations to industry that might be made from them. Empirical validation was performed through comparison with a population of the weed that was confirmed to be glyphosate resistant in 2007. Structural and behavioural pattern validation were performed during model development. In the historical dataset used for empirical validation, there are both hidden variables (in particular, the initial proportion of resistance-conferring alleles in the population before selection began) and sparsely documented variables (including the year in which glyphosate was first used, and the number and efficacy of glyphosate applications made to this weed population since then) that create difficulty in making direct comparisons between the real population and the model's predictions. The type of data that is available for use in empirical validation of the model is also a constraint. Herbicide resistance is identified as a point of failure in the agricultural system. Therefore, data from real fields is unlikely to contain information about whether or how the rate of evolution of resistance changes over time in response to the types of system actions that are included in the model. In this paper, potential validation methods and pitfalls are discussed, showing that recommendations can be made using the model's predictions with some confidence, but that herbicide model validation constraints may affect the credibility of the model's predictions particularly for non-scientist users

Voltammetric investigation of the kinetics of alkali metal cation reduction in N,N-dimethylformamide

The standard electron-transfer heterogeneous rate constant of lithium, potassium, sodium and caesium amalgams in N,N-dimethylformamide was ascertained employing cyclic voltammetry in an effort to relate the presence of a non-equilibrium electrode reaction at the dropping lithium amalgam electrode to the variation of the lithium amalgam electrode potential with amalgam electrode con- figuration, i.e. whether streaming, dropping or stationary. Such variations are not observed at other alkali metal amalgam electrodes. In the dipolar aprotic solvents the standard electron-transfer heterogeneous rate constant for the Li(Hg) electrode increases as the solvating power for Li+ decreases, i.e. dimethyl sulphoxide < di- methylformamide < propylene carbonate. Water is a much stronger solvator of Li+ than is propylene carbonate, but the electron transfer is faster in water than in propylene carbonate; the important role of entropic contributions in ion solvation is discussed as an explanation

Modelling the effects of farm management on the spread of herbicide resistance

Herbicide resistance is an increasing problem in Australian cropping systems, but little is known about how resistance spreads and how farmers can manage their paddocks to minimise its spread. This paper presents a modelling framework for predicting biological processes in agriculture, with particular emphasis on the spatial and temporal spread of herbicide resistance. It includes a model of the population dynamics of weeds growing in competition with crops, a polygenic model of the development of herbicide resistance and gene transfer by means of seed and pollen movement. The modelling framework is used to predict the long-term spread of resistant weeds given different integrated weed management choices combining tillage and herbicide treatments, as well as new technologies such as seed capture at harvest and precision planting systems that allow different treatments for inter and intra-rows. The model's predictions are used to devise management options that minimise the spread of herbicide resistant weeds

Automated pneumococcal MLST using liquid-handling robotics and a capillary DNA sequencer

Multilocus sequence typing (MLST) is used by the Scottish Meningococcus and Pneumococcus Reference Laboratory (SMPRL) as a routine method for the characterization of certain bacterial pathogens. The SMPRL recently started performing MLST on strains of Streptococcus pneumoniae, and here we describe a fully automated method for MLST using a 96-well-format liquid-handling robot and a 96-capillary automated DNA sequencer

Virtual Visualization System for Growth of Tobacco Root

International audienceVisualization study on the growth of virtual plant roots is of great significance to enhance the overall level of research on virtual plant growth. In this study, with the tobacco root as the object, its growth was divided by systematic analysis into three stages: root emergence, root growth, and root branching. Through the quantitative analysis of the morphological data of the tobacco root and in combination with results of previous studies, the tobacco root growth, branching and other models were established, and parameter values of the models were extracted. On this basis, computer graphics technology was applied to establish a virtual visualization system for tobacco root growth that should be capable of simulating root growth and computing indicators of roots including the number, length, density, etc. Results indicated that this system can do a better job of simulating the morphological features for the tobacco root and virtually displaying the process of tobacco root growth in a more realistic way

Methodological issues in economic evaluations of emergency transport systems in low-income and middle-income countries

A recent systematic review identified few papers on the economic evaluation of systems for emergency transport of acutely ill or injured patients. In addition, we found no articles dealing with the methodological challenges posed by such studies in low-income or middle-income countries. We therefore carried out an analysis of issues that are of particular salience to this important topic. This is an intellectual study in which we develop models, identify their limitations, suggest potential extensions to the models and discuss priorities for empirical studies to populate models. First, we develop a general model to calculate changes in survival contingent on the reduced time to treatment that an emergency transport system is designed to achieve. Second, we develop a model to estimate transfer times over an area that will be served by a proposed transfer system. Third, we discuss difficulties in obtaining parameters with which to populate the models. Fourth, we discuss costs, both direct and indirect, of an emergency transfer service. Fifth, we discuss the issue that outcomes other than survival should be considered and that the effects of a service are a weighted sum over all the conditions and severities for which the service caters. Lastly, based on the above work, we identify priorities for research. To our knowledge, this is the first study to identify and frame issues in the health economics of acute transfer systems and to develop models to calculate survival rates from basic parameters, such as time delay/survival relationships, that vary by intervention type and context. © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ