928 resultados para Bayesian forecasts


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Recent El Nino events have stimulated interest in the development of modeling techniques to forecast extremes of climate and related health events. Previous studies have documented associations between specific climate variables (particularly temperature and rainfall) and outbreaks of arboviral disease. In some countries, such diseases are sensitive to Fl Nino. Here we describe a climate-based model for the prediction of Ross River virus epidemics in Australia. From a literature search and data on case notifications, we determined in which years there were epidemics of Ross River virus in southern Australia between 1928 and 1998. Predictor variables were monthly Southern Oscillation index values for the year of an epidemic or lagged by 1 year. We found that in southeastern states, epidemic years were well predicted by monthly Southern Oscillation index values in January and September in the previous year. The model forecasts that there is a high probability of epidemic Ross River virus in the southern states of Australia in 1999. We conclude that epidemics of arboviral disease can, at least in principle, be predicted on the basis of climate relationships.

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Regression analyses of a long series of light-trap catches at Narrabri, Australia, were used to describe the seasonal dynamics of Helicoverpa armigera (Hubner). The size of the second generation was significantly related to the size of the first generation, to winter rainfall, which had a positive effect, and to spring rainfall which had a negative effect. These variables accounted for up to 96% of the variation in size of the second generation from year to year. Rainfall and crop hosts were also important for the size of the third generation. The area and tonnage of many potential host crops were significantly correlated with winter rain. When winter rain was omitted from the analysis, the sizes of both the second and third generations could be expressed as a function of the size of the previous generation and of the areas planted to lucerne, sorghum and maize. Lucerne and maize always had positive coefficients and sorghum a negative one. We extended our analysis to catches of H. punctigera (Wallengren), which declines in abundance after the second generation. Winter rain had a positive effect on the sizes of the second and third generations, and rain in spring or early summer had a negative effect. Only the area grown to lucerne had a positive effect on abundance. Forecasts of pest levels from a few months to a few weeks in advance are discussed, along with the improved understanding of the seasonal dynamics of both species and the significance of crops in the management of insecticide resistance for H. armigera.

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1. Although population viability analysis (PVA) is widely employed, forecasts from PVA models are rarely tested. This study in a fragmented forest in southern Australia contrasted field data on patch occupancy and abundance for the arboreal marsupial greater glider Petauroides volans with predictions from a generic spatially explicit PVA model. This work represents one of the first landscape-scale tests of its type. 2. Initially we contrasted field data from a set of eucalypt forest patches totalling 437 ha with a naive null model in which forecasts of patch occupancy were made, assuming no fragmentation effects and based simply on remnant area and measured densities derived from nearby unfragmented forest. The naive null model predicted an average total of approximately 170 greater gliders, considerably greater than the true count (n = 81). 3. Congruence was examined between field data and predictions from PVA under several metapopulation modelling scenarios. The metapopulation models performed better than the naive null model. Logistic regression showed highly significant positive relationships between predicted and actual patch occupancy for the four scenarios (P = 0.001-0.006). When the model-derived probability of patch occupancy was high (0.50-0.75, 0.75-1.00), there was greater congruence between actual patch occupancy and the predicted probability of occupancy. 4. For many patches, probability distribution functions indicated that model predictions for animal abundance in a given patch were not outside those expected by chance. However, for some patches the model either substantially over-predicted or under-predicted actual abundance. Some important processes, such as inter-patch dispersal, that influence the distribution and abundance of the greater glider may not have been adequately modelled. 5. Additional landscape-scale tests of PVA models, on a wider range of species, are required to assess further predictions made using these tools. This will help determine those taxa for which predictions are and are not accurate and give insights for improving models for applied conservation management.

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Item noise models of recognition assert that interference at retrieval is generated by the words from the study list. Context noise models of recognition assert that interference at retrieval is generated by the contexts in which the test word has appeared. The authors introduce the bind cue decide model of episodic memory, a Bayesian context noise model, and demonstrate how it can account for data from the item noise and dual-processing approaches to recognition memory. From the item noise perspective, list strength and list length effects, the mirror effect for word frequency and concreteness, and the effects of the similarity of other words in a list are considered. From the dual-processing perspective, process dissociation data on the effects of length, temporal separation of lists, strength, and diagnosticity of context are examined. The authors conclude that the context noise approach to recognition is a viable alternative to existing approaches.

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Intelligent design theorist William Dembski has proposed an explanatory filter for distinguishing between events due to chance, lawful regularity or design. We show that if Dembski's filter were adopted as a scientific heuristic, some classical developments in science would not be rational, and that Dembski's assertion that the filter reliably identifies rarefied design requires ignoring the state of background knowledge. If background information changes even slightly, the filter's conclusion will vary wildly. Dembski fails to overcome Hume's objections to arguments from design.

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The phylogeny of the Australian legume genus Daviesia was estimated using sequences of the internal transcribed spacers of nuclear ribosomal DNA. Partial congruence was found with previous analyses using morphology, including strong support for monophyly of the genus and for a sister group relationship between the clade D. pachyloma and the rest of the genus. A previously unplaced bird-pollinated species, anceps + D. D. epiphyllum, was well supported as sister to the only other bird-pollinated species in the genus, D. speciosa, indicating a single origin of bird pollination in their common ancestor. Other morphological groups within Daviesia were not supported and require reassessment. A strong and previously unreported sister clade of Daviesia consists of the two monotypic genera Erichsenia and Viminaria. These share phyllode-like leaves and indehiscent fruits. The evolutionary history of cord roots, which have anomalous secondary thickening, was explored using parsimony. Cord roots are limited to three separate clades but have a complex history involving a small number of gains (most likely 0-3) and losses (0-5). The anomalous structure of cord roots ( adventitious vascular strands embedded in a parenchymatous matrix) may facilitate nutrient storage, and the roots may be contractile. Both functions may be related to a postfire resprouting adaptation. Alternatively, cord roots may be an adaptation to the low-nutrient lateritic soils of Western Australia. However, tests for association between root type, soil type, and growth habit were equivocal, depending on whether the variables were treated as phylogenetically dependent (insignificant) or independent ( significant).

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Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.

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Butterflyfish are colourful, pan-tropical coastal fish that are important and distinctive members of coral reef communities. A successful systematic scheme and a robust phylogeny is considered essential in understanding further their biogeography and ecology, although recent cladistic treatments of butterflyfish phylogeny, based on soft tissue and bone morphology and coded at the generic and subgeneric levels, differ in character coding and subsequently tree topology. This study provides an independent test of the morphologically based hypotheses, using molecular systematic data from two partial mitochondrial gene fragments, cytochrome b (cytb) and small subunit rRNA (rrnS), for 52 ingroup chaetodontids and seven pomacanthids used to root the molecular trees. Individual gene trees were largely compatible and a combined molecular phylogeny, inferred from Bayesian analysis, was used to test alternative hypotheses suggested by morphological analyses. The tree was also used to map the latest morphological matrix in order to evaluate potential synapomorphies for various nodes defining butterflyfish interrelationships. A clade comprised of Chelmon and Coradion was sister group to other chaetodontids. Heniochus and Hemitaurichthys were each resolved as monophyletic groups, and as sister taxa Of the taxa sampled, Prognothodes was resolved as the sister genus to Chaeotodon. Of the ten Chaetodon subgenera sampled, all were monophyletic but their interrelationships differed significantly from that inferred from morphological characters. Lepidochaetodon was the most basal subgenus followed by Exornator and the remaining subgenera. Molecular data support the sister group relationship between Corallochaetodon and Citharoedus suggested by morphology, but major differences occur among the remaining more derived taxa. Chaetodon trifascialis and C. oligacanthus were resolved as sister taxa adding weight to the inclusion of the latter in C. Megaprotodon. Of those pairs of taxa known to hybridize and sampled with molecular data, all were closely related phylogenetically, except those hybrids known to occur in the Rabdophorus subgenus. Two base changes separated C. pelewensis from C. paucifasciatus which have been regarded previously as a single species. Cytb provided greater resolution than rrnS and will likely provide additional resolution with greater taxon sampling.

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An analysis of the relationships of the major arthropod groups Was undertaken using mitochondrial genome data to examine the hypotheses that Hexapoda is polyphyletic and that Collembola is more closely related to branchiopod crustaceans than insects. We sought to examine the sensitivity of this relationship to outgroup choice, data treatment. gene choice and optimality criteria used in the phylogenetic analysis of mitochondrial genome data. Additionally we sequenced the mitochondrial genome of ail archaeognathan, Nesomachilis australica. to improve taxon selection in the apterygote insects, a group poorly represented in previous mitochondrial phylogenies. The sister group of the Collembola was rarely resolved in our analyses with a significant level of support. The use of different outgroups (myriapods, nematodes, or annelids + mollusks) resulted in many different placements of Collembola. The way in which the dataset was coded for analysis (DNA, DNA with the exclusion of third codon position and as amino acids) also had marked affects on tree topology. We found that nodal Support was spread evenly throughout the 13 mitochondrial genes and the exclusion of genes resulted in significantly less resolution in the inferred trees. Optimality criteria had a much lesser effect on topology than the preceding factors; parsimony and Bayesian trees for a given data set and treatment were quite similar. We therefore conclude that the relationships of the extant arthropod groups as inferred by mitochondrial genomes are highly vulnerable to outgroup choice, data treatment and gene choice, and no consistent alternative hypothesis of Collembola's relationships is supported. Pending the resolution of these identified problems with the application of mitogenomic data to basal arthropod relationships, it is difficult to justify the rejection of hexapod monophyly, which is well supported on morphological grounds. (c) The Willi Hennig Society 2004.

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We discuss the expectation propagation (EP) algorithm for approximate Bayesian inference using a factorizing posterior approximation. For neural network models, we use a central limit theorem argument to make EP tractable when the number of parameters is large. For two types of models, we show that EP can achieve optimal generalization performance when data are drawn from a simple distribution.

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Background/Aims: Approximately four million Africans were taken as slaves to Brazil, where they interbred extensively with Amerindians and Europeans. We have previously shown that while most White Brazilians carry Y chromosomes of European origin, they display high proportions of African and Amerindian mtDNA lineages, because of sex-biased genetic admixture. Methods: We studied the Y chromosome and mtDNA haplogroup structure of 120 Black males from Sao Paulo, Brazil. Results: Only 48% of the Y chromosomes, but 85% of the mtDNA haplogroups were characteristic of sub-Saharan Africa, confirming our previous observation of sexually biased mating. We mined literature data for mtDNA and Y chromosome haplogroup frequencies for African native populations from regions involved in Atlantic Slave Trade. Principal Components Analysis and Bayesian analysis of population structure revealed no genetic differentiation of Y chromosome marker frequencies between the African regions. However, mtDNA examination unraveled considerable genetic structure, with three clusters at Central-West Africa, West Africa and Southeast Africa. A hypothesis is proposed to explain this structure. Conclusion: Using these mtDNA data we could obtain for the first time an estimate of the relative ancestral contribution of Central-West (0.445), West (0.431) and Southeast Africa (0.123) to African Brazilians from Sao Paulo. These estimates are consistent with historical information. Copyright (c) 2008 S. Karger AG, Basel.

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For the purpose of developing a longitudinal model to predict hand-and-foot syndrome (HFS) dynamics in patients receiving capecitabine, data from two large phase III studies were used. Of 595 patients in the capecitabine arms, 400 patients were randomly selected to build the model, and the other 195 were assigned for model validation. A score for risk of developing HFS was modeled using the proportional odds model, a sigmoidal maximum effect model driven by capecitabine accumulation as estimated through a kinetic-pharmacodynamic model and a Markov process. The lower the calculated creatinine clearance value at inclusion, the higher was the risk of HFS. Model validation was performed by visual and statistical predictive checks. The predictive dynamic model of HFS in patients receiving capecitabine allows the prediction of toxicity risk based on cumulative capecitabine dose and previous HFS grade. This dose-toxicity model will be useful in developing Bayesian individual treatment adaptations and may be of use in the clinic.

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Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing bodies. The industry could profitably use forecasts of likely production to adjust their operations strategically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.