14 resultados para Bayesian approaches

em eResearch Archive - Queensland Department of Agriculture


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The ecology of the uncultured, but large and morphologically conspicuous, rumen bacterium Oscillospira spp. was studied. Oscillospira-specific 16S rRNA gene sequences were detected in North American domestic cattle, sheep from Australia and Japan, and Norwegian reindeer. Phylogenetic analysis of the sequences obtained allowed definition of three operational taxonomic units within the Oscillospira clade. Consistent with this genetic diversity, we observed atypical smaller morphotypes by using an Oscillospira-specific fluorescence in situ hybridization probe. Despite the visual disappearance of typical large Oscillospira morphotypes, the presence of Oscillospira spp. was still detected by Oscillospira-specific PCR in the rumen of cattle and sheep. These observations suggest the broad presence of Oscillospira species in various rumen ecosystems with the level, and most likely the morphological form, dependent on diet. An ecological analysis based on enumeration of the morphologically conspicuous, large-septate form confirms that the highest counts are associated with the feeding of fresh forage diets to cattle and sheep and in two different subspecies of reindeer investigated.

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This paper describes the development of a model, based on Bayesian networks, to estimate the likelihood that sheep flocks are infested with lice at shearing and to assist farm managers or advisers to assess whether or not to apply a lousicide treatment. The risk of lice comes from three main sources: (i) lice may have been present at the previous shearing and not eradicated; (ii) lice may have been introduced with purchased sheep; and (iii) lice may have entered with strays. A Bayesian network is used to assess the probability of each of these events independently and combine them for an overall assessment. Rubbing is a common indicator of lice but there are other causes too. If rubbing has been observed, an additional Bayesian network is used to assess the probability that lice are the cause. The presence or absence of rubbing and its possible cause are combined with these networks to improve the overall risk assessment.

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Invasive plants are a serious threat to biodiversity. Yet, in some cases, they may play an important ecological role in heavily modified landscapes, such as where fleshy-fruited invasive plants support populations of native frugivores. How can such conservation conflicts be managed? We advocate an approach in which native fleshy-fruited plants are ranked on their ability to provide the fruit food resources for native frugivores currently being provided by invasive plants. If these native taxa are preferentially used, where ecologically appropriate, in plantings for restoration and in park and garden settings, they could help support native frugivore populations in the event of extensive invasive plant control. We develop and critically examine six approaches to selecting candidate native plant taxa: a multivariate approach based on the frugivore assemblage, a scoring model, and several multivariate approaches (including trait combinations having the greatest correlation with the diet of the native frugivore assemblage) based on the functional traits of fruit morphology, phenology, conspicuousness, and accessibility. To illustrate these approaches, we use a case study with Bitou bush (Chrysanthemoides monilifera subsp. rotundata) (Asteraceae), an Australian Weed of National Significance. The model using a dissimilarity value generated from all available traits identified a set of species used by the frugivores of C. monilifera more than null models. A replacement approach using species ranked by either all traits available or the frugivore community appears best suited to guide selection of plants in restoration practice.

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We review key issues, available approaches and analyses to encourage and assist practitioners to develop sound plans to evaluate the effectiveness of weed biological control agents at various phases throughout a program. Assessing the effectiveness of prospective agents before release assists the selection process, while post-release evaluation aims to determine the extent that agents are alleviating the ecological, social and economic impacts of the weeds. Information gathered on weed impacts prior to the initiation of a biological control program is necessary to provide baseline data and devise performance targets against which the program can subsequently be evaluated. Detailed data on weed populations, associated plant communities and, in some instances ecosystem processes collected at representative sites in the introduced range several years before the release of agents can be compared with similar data collected later to assess agent effectiveness. Laboratory, glasshouse and field studies are typically used to assess agent effectiveness. While some approaches used for field studies may be influenced by confounding factors, manipulative experiments where agents are excluded (or included) using chemicals or cages are more robust but time-consuming and expensive to implement. Demographic modeling and benefit–cost analyses are increasingly being used to complement other studies. There is an obvious need for more investment in long-term post-release evaluation of agent effectiveness to rigorously document outcomes of biological control programs.

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Improving the genetic base of cultivars that underpin commercial mango production is generally recognized as necessary for long term industry stability. Genetic improvement can take many approaches to improve cultivars, each with their own advantages and disadvantages. This paper will discuss several approaches used in the genetic improvement of mangoes in Australia, including varietal introductions, selection of monoembryonic progeny, selection within polyembryonic populations, assisted open pollination and controlled closed pollination. The current activities of the Australian National Mango Breeding Program will be outlined, and the analysis and use of hybrid phenotype data from the project for selection of next generation parents will be discussed. Some of the important traits that will enhance the competitiveness of future cultivars will be introduced and the challenges in achieving them discussed. The use of a genomics approach and its impact on future mango breeding is examined.

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Identifying species boundaries within morphologically indistinguishable cryptic species complexes is often contentious. For the whitefly Bemisia tabaci (Gennadius) (Hemiptera: Sternorrhyncha: Aleyrodoidea: Aleyrodidae), the lack of a clear understanding about the genetic limits of the numerous genetic groups and biotypes so far identified has resulted in a lack of consistency in the application of the terms, the approaches use to apply them and in our understanding of what genetic structure within B. tabaci means. Our response has been to use mitochondrial gene cytochrome oxidase one to consider how to clearly and consistently define genetic separation. Using Bayesian phylogenetic analysis and analysis of sequence pairwise divergence we found a considerably higher to number of genetic groups than had been previously determined with two breaks in the distribution, one at 11% and another at 3.5%. At >11% divergence, 11 distinct groups were resolved, whereas at >3.5% divergence 24 groups were identified. Consensus sequences for each of these groups were determined and were shown to be useful in the correct assignment of sequences of unknown origin. The 3.5% divergence bound is consistent with species level separations in other insect taxa and Suggests that B. tabaci is it cryptic species composed of at least 24 distinct species. We further show that the placement of Bemesia atriplex (Froggatt) within the B. tabaci in, group adds further weight to the argument for species level separation within B. tabaci. This new analysis, which constructs consensus sequences and uses these its a standard against which unknown sequences call be compared, provides for the first time it consistent means of identifying the genetic hounds of each species with it high degree of certainty.

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Genetic approaches to resistance of bread wheat to crown rot and common root rot.

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This project provided information on the genetics of crown rot (CR) resistance to help breeding work, located new parent lines in wheat and barley, and provided an insight into yield losses that occur in commercial varieties with increasing levels of CR for risk management. Genetic experiments found some highly resistant lines were poor parents, and CR resistance was complex. Best parent lines and many specific crosses were identified for further work. New potential parent lines were identified in wheat and barley, some now used in breeding programs. Yield loss can be severe even with low levels of CR when combined with drought stress. CR can reduce yield even with a wet finish.

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Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

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Hierarchical Bayesian models can assimilate surveillance and ecological information to estimate both invasion extent and model parameters for invading plant pests spread by people. A reliability analysis framework that can accommodate multiple dispersal modes is developed to estimate human-mediated dispersal parameters for an invasive species. Uncertainty in the observation process is modelled by accounting for local natural spread and population growth within spatial units. Broad scale incursion dynamics are based on a mechanistic gravity model with a Weibull distribution modification to incorporate a local pest build-up phase. The model uses Markov chain Monte Carlo simulations to infer the probability of colonisation times for discrete spatial units and to estimate connectivity parameters between these units. The hierarchical Bayesian model with observational and ecological components is applied to a surveillance dataset for a spiralling whitefly (Aleurodicus dispersus) invasion in Queensland, Australia. The model structure provides a useful application that draws on surveillance data and ecological knowledge that can be used to manage the risk of pest movement.

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Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of absence observations and the hurdle model is a two step approach that is useful when analyzing such a binary response dataset. The proposed hurdle model utilizes Bayesian classification trees to firstly identify covariates and covariate levels pertaining to possible presence or absence of strong resistance. Secondly, generalized additive models (GAMs) with spike and slab priors for variable selection are fitted to the subset of the dataset identified from the Bayesian classification tree indicating possibility of presence of strong resistance. From the GAM we assess trends, biosecurity issues and site specific variables influencing the presence of strong resistance using a variable selection approach. The proposed Bayesian hurdle model is compared to its frequentist counterpart, and also to a naive Bayesian approach which fits a GAM to the entire dataset. The Bayesian hurdle model has the benefit of providing a set of good trees for use in the first step and appears to provide enough flexibility to represent the influence of variables on strong resistance compared to the frequentist model, but also captures the subtle changes in the trend that are missed by the frequentist and naive Bayesian models. © 2014 Springer Science+Business Media New York.

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Henipaviruses cause fatal infection in humans and domestic animals. Transmission from fruit bats, the wildlife reservoirs of henipaviruses, is putatively driven (at least in part) by anthropogenic changes that alter host ecology. Human and domestic animal fatalities occur regularly in Asia and Australia, but recent findings suggest henipaviruses are present in bats across the Old World tropics. We review the application of the One Health approach to henipavirus research in three locations: Australia, Malaysia and Bangladesh. We propose that by recognising and addressing the complex interaction among human, domestic animal and wildlife systems, research within the One Health paradigm will be more successful in mitigating future human and domestic animal deaths from henipavirus infection than alternative single-discipline approaches. © Springer-Verlag Berlin Heidelberg 2013.

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A holistic approach to stock structure studies utilises multiple different techniques on the same individuals sampled from selected populations and combines results across spatial and temporal scales to produce a weight of evidence conclusion. It is the most powerful and reliable source of information to use in formulating resource management and monitoring plans. Few examples of the use of a holistic approach in stock structure studies exist, although more recently this is changing. Using such an approach makes integration of results from each technique challenging. An integrated stock definition (ISD) approach for holistic stock structure studies was developed in this study to aid in the appropriate interpretation of stock structure results to guide the determination of fishery management units. The ISD approach is applied herein to a study of the northern Australian endemic grey mackerel, Scomberomorus semifasciatus (Scombridae). Analyses of genetic (mitochondrial DNA and microsatellites), parasite, otolith stable isotope, and growth data are synthesised to determine the stock structure of S. semifasciatus across northern Australia. Integration of the results from all techniques identified at least six S. semifasciatus stocks for management purposes. Further, the use of the ISD approach provided a simple basis for integrating multiple techniques and for their interpretation. The use of this holistic approach was a powerful tool in providing greater certainty about the appropriate management units for S. semifasciatus. Future stock structure studies investigating spatial management questions in the fisheries context should adopt a holistic approach and apply the ISD approach for a more accurate definition of biological stocks to improve fisheries management.