Carpogenic germination of Sclerotinia minor and potential distribution in Australia

This study confirms that Australian isolates of Sclerotinia minor can produce fertile apothecia and further demonstrates that ascospores collected from these apothecia are pathogenic to sunflower (Helianthus annuus). Sunflower is a known host of the related fungus Sclerotinia sclerotiorum and is grown in some regions where S. minor is known to occur. Head rot symptoms were produced following inoculation with S. minor ascospores. Predictive modeling using CLIMEX software suggested that conditions suitable for carpogenic germination of S. minor probably occur in Australia particularly in southern regions. Carpogenic germination is probably a rare event in northern regions and, if it does occur, probably does not coincide with anthesis in sunflower crops, therefore allowing disease escape.

Modelling pre-clearing vegetation distribution using GIS-integrated statistical, ecological and data models: A case study from the wet tropics of Northeastern Australia

Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.

Climate change and biotic invasions: a case history of a tropical woody vine

The impacts of climate change in the potential distribution and relative abundance of a C3 shrubby vine, Cryptostegia grandiflora, were investigated using the CLIMEX modelling package. Based upon its current naturalised distribution, C. grandiflora appears to occupy only a small fraction of its potential distribution in Australia under current climatic conditions; mostly in apparently sub-optimal habitat. The potential distribution of C. grandiflora is sensitive towards changes in climate and atmospheric chemistry in the expected range of this century, particularly those that result in increased temperature and water use efficiency. Climate change is likely to increase the potential distribution and abundance of the plant, further increasing the area at risk of invasion, and threatening the viability of current control strategies markedly. By identifying areas at risk of invasion, and vulnerabilities of control strategies, this analysis demonstrates the utility of climate models for providing information suitable to help formulate large-scale, long-term strategic plans for controlling biotic invasions. The effects of climate change upon the potential distribution of C. grandiflora are sufficiently great that strategic control plans for biotic invasions should routinely include their consideration. Whilst the effect of climate change upon the efficacy of introduced biological control agents remain unknown, their possible effect in the potential distribution of C. grandiflora will likely depend not only upon their effects on the population dynamics of C. grandiflora, but also on the gradient of climatic suitability adjacent to each segment of the range boundary.

Characterisation of pore structure of carbon adsorbents using regularisation procedure

The constrained regularisation procedure was applied to compute the pore size distributions (PSDs, f(x)) for a variety of activated carbons using overall adsorption equation based on the combination of the Kelvin equation and the statistical adsorbed film thickness. The impact of the boundary values of relative nitrogen pressure p/p(0) was analysed on the basis of the corresponding alterations in the PSDs. Changes in microporosity and mesoporosity of activated carbons can be described adequately only when the range of p/p(0) is as wide as possible, as at a high initial p/p(0) value, the f(x) curves can be broadened with shifted maxima especially for micropores and narrow mesopores. Comparative analysis of the PSDs and the adsorption potential, adsorption energy and fractal dimension distributions gives useful information on the complete description of the adsorbent characteristics. (C) 2001 Elsevier Science B.V. All rights reserved.

Robust Mixture Modelling Using the t Distribution

Normal mixture models are being increasingly used to model the distributions of a wide variety of random phenomena and to cluster sets of continuous multivariate data. However, for a set of data containing a group or groups of observations with longer than normal tails or atypical observations, the use of normal components may unduly affect the fit of the mixture model. In this paper, we consider a more robust approach by modelling the data by a mixture of t distributions. The use of the ECM algorithm to fit this t mixture model is described and examples of its use are given in the context of clustering multivariate data in the presence of atypical observations in the form of background noise.

Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment

A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.

Modelling the distribution of stamp paper thickness via finite normal mixtures: The 1872 Hidalgo stamp issue of Mexico revisited

Izenman and Sommer (1988) used a non-parametric Kernel density estimation technique to fit a seven-component model to the paper thickness of the 1872 Hidalgo stamp issue of Mexico. They observed an apparent conflict when fitting a normal mixture model with three components with unequal variances. This conflict is examined further by investigating the most appropriate number of components when fitting a normal mixture of components with equal variances.

Distribution of a nematocyst-bearing sponge in relation to potential coral donors

Haliclona sp. 628 (Demospongiae, Haplosclerida, Chalinidae), a sponge found on the reef slope below 5 in depth on the Great Barrier Reef, has two unusual characteristics. It contains a symbiotic dinoflagellate, Symbiodinium sp., similar in structure to the dinoflagellate found within Acropora nobilis (S. microadriaticum), and it contains coral nematocysts randomly distributed between the ectosome and endosome and usually undischarged in intact sponge tissue. Given the unusual occurrence of nematocysts in Haliclona sp. 628, the focus of this study was to determine the distribution of this species of sponge on the reef slope at Heron Island Reef in relation to the distribution of potential coral donors. A combination of line and belt transects was used to estimate the abundance of Halielona sp. 628 and a co-occurring congener, Haliclona sp. 1031, which does not contain nematocysts, at three widely separated sites on the reef slope at Heron Island Reef. The abundance of different types of substratum (sand, sand-covered coral rubble, dead A. nobilis, live A. nobilis, other live coral, and other dead coral) along the transects and the substratum to which each sponge colony was attached were also recorded. Despite the predominance of live A. nobilis and sand-covered rubble at all sites, between 30 and 55% of Haliclona sp. 628 colonies were attached to dead A. nobilis which comprised less than 8% of the available substratum along any transect. In contrast, Haliclona sp. 1031 was found significantly more frequently on other dead corals and less frequently on live A. nobilis than would be expected based on the availability of the different substrata in the sites. Potential explanations to account for the distribution of Haliclona sp. 628 in relation to potential coral donors are discussed.

Influence of charge size distribution on net-power draw of tumbling mill based on DEM modelling

Modelling and optimization of the power draw of large SAG/AG mills is important due to the large power draw which modern mills require (5-10 MW). The cost of grinding is the single biggest cost within the entire process of mineral extraction. Traditionally, modelling of the mill power draw has been done using empirical models. Although these models are reliable, they cannot model mills and operating conditions which are not within the model database boundaries. Also, due to its static nature, the impact of the changing conditions within the mill on the power draw cannot be determined using such models. Despite advances in computing power, discrete element method (DEM) modelling of large mills with many thousands of particles could be a time consuming task. The speed of computation is determined principally by two parameters: number of particles involved and material properties. The computational time step is determined by the size of the smallest particle present in the model and material properties (stiffness). In the case of small particles, the computational time step will be short, whilst in the case of large particles; the computation time step will be larger. Hence, from the point of view of time required for modelling (which usually corresponds to time required for 3-4 mill revolutions), it will be advantageous that the smallest particles in the model are not unnecessarily too small. The objective of this work is to compare the net power draw of the mill whose charge is characterised by different size distributions, while preserving the constant mass of the charge and mill speed. (C) 2004 Elsevier Ltd. All rights reserved.

The application of numerical modelling to the assessment of the potential for, and the detection of, spontaneous combustion in coal mines

Numerical modelling has been used to examine the relationship between the results of two commonly used methods of assessing the propensity of coal to spontaneous combustion, the R70 and Relative Ignition Temperature tests, and the likely behaviour in situ. The criticality of various parameters has been examined and a method of utilising critical self-heating parameters has been developed. This study shows that on their own, the laboratory test results do not provide a reliable guide to in situ behaviour but can be used in combination to considerably increase the ability to predict spontaneous combustion behaviour.