9 resultados para Transition matrix

em eResearch Archive - Queensland Department of Agriculture


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Movement rates of eastern king prawns, Melicertus plebejus (Hess), were estimated from historical and recent conventional tag-recapture information collected across eastern Australia. Data from three studies and 2,656 tag recaptures were used. Recaptured males and females both moved east–north-east in central Queensland and north–north-east in southern Queensland and New South Wales. Over a period of one year, the estimated transition matrix reflected the species strong northerly movement and the more complex longitudinal movement, showing a very high probability of eastern movement in central Queensland and almost negligible eastern or western movement in northern New South Wales. The high exchange probability between New South Wales and Queensland waters indicated that spatial assessment models with movement rates between state jurisdictions would improve the management of this single-unit stock.

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Stochastic growth models were fitted to length-increment data of eastern king prawns, Melicertus plebejus (Hess, 1865), tagged across eastern Australia. The estimated growth parameters and growth transition matrix are for each sex representative of the species' geographical distribution. Our study explicitly displays the stochastic nature of prawn growth. Capturing length-increment growth heterogeneity for short-lived exploited species such as prawns that cannot be readily aged is essential for length-based modelling and improved management.

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Movement rates of eastern king prawns, Melicertus plebejus (Hess), were estimated from historical and recent conventional tag-recapture information collected across eastern Australia. Data from three studies and 2,656 tag recaptures were used. Recaptured males and females both moved east-north-east in central Queensland and north-north-east in southern Queensland and New South Wales. Over a period of one year, the estimated transition matrix reflected the species strong northerly movement and the more complex longitudinal movement, showing a very high probability of eastern movement in central Queensland and almost negligible eastern or western movement in northern New South Wales. The high exchange probability between New South Wales and Queensland waters indicated that spatial assessment models with movement rates between state jurisdictions would improve the management of this single-unit stock.

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Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

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The complexity, variability and vastness of the northern Australian rangelands make it difficult to assess the risks associated with climate change. In this paper we present a methodology to help industry and primary producers assess risks associated with climate change and to assess the effectiveness of adaptation options in managing those risks. Our assessment involved three steps. Initially, the impacts and adaptation responses were documented in matrices by ‘experts’ (rangeland and climate scientists). Then, a modified risk management framework was used to develop risk management matrices that identified important impacts, areas of greatest vulnerability (combination of potential impact and adaptive capacity) and priority areas for action at the industry level. The process was easy to implement and useful for arranging and analysing large amounts of information (both complex and interacting). Lastly, regional extension officers (after minimal ‘climate literacy’ training) could build on existing knowledge provided here and implement the risk management process in workshops with rangeland land managers. Their participation is likely to identify relevant and robust adaptive responses that are most likely to be included in regional and property management decisions. The process developed here for the grazing industry could be modified and used in other industries and sectors. By 2030, some areas of northern Australia will experience more droughts and lower summer rainfall. This poses a serious threat to the rangelands. Although the impacts and adaptive responses will vary between ecological and geographic systems, climate change is expected to have noticeable detrimental effects: reduced pasture growth and surface water availability; increased competition from woody vegetation; decreased production per head (beef and wool) and gross margin; and adverse impacts on biodiversity. Further research and development is needed to identify the most vulnerable regions, and to inform policy in time to facilitate transitional change and enable land managers to implement those changes.

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Transition of EGA wheat breeding activities to Australian Grain Technologies.

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Understanding the ontogenetic habitat linkages of sharks is important for conservation and managing human interactions. We used acoustic telemetry, catch data, elemental and stable isotope signatures and dietary analyses to investigate ontogenetic habitat use in south-east Queensland, Australia, by the bull shark Carcharhinus leucas, a IUCN 'near-threatened' species that is implicated in many shark attacks on humans in urban estuaries. Sequential analyses for delta(15)N and delta(13)C of vertebrae from five adult C. leucas and laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) for elemental composition from 23 C. leucas, including a pregnant female, were also used to trace ontogenetic habitat dependence. Acoustic telemetry indicated large juvenile and subadult C. leucas remained in estuarine habitats. delta(15)N values across shark vertebrae showed an ontogenetic shift in diet with total length (TL), confirmed by stomach contents. LA-ICPMS data reflected the ontogenetic movements of C. leucas from natal habitats. Differences among adults were gender related. Shifts in habitat use by subadults were correlated with a sigmoidal delta(13)C relationship with TL. C. leucas have a multipartite, stage-specific dependency in their transition between habitats along the freshwater-estuarine-marine continuum, making them particularly susceptible to the habitat alteration that is occurring globally.

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We derive a new method for determining size-transition matrices (STMs) that eliminates probabilities of negative growth and accounts for individual variability. STMs are an important part of size-structured models, which are used in the stock assessment of aquatic species. The elements of STMs represent the probability of growth from one size class to another, given a time step. The growth increment over this time step can be modelled with a variety of methods, but when a population construct is assumed for the underlying growth model, the resulting STM may contain entries that predict negative growth. To solve this problem, we use a maximum likelihood method that incorporates individual variability in the asymptotic length, relative age at tagging, and measurement error to obtain von Bertalanffy growth model parameter estimates. The statistical moments for the future length given an individual’s previous length measurement and time at liberty are then derived. We moment match the true conditional distributions with skewed-normal distributions and use these to accurately estimate the elements of the STMs. The method is investigated with simulated tag–recapture data and tag–recapture data gathered from the Australian eastern king prawn (Melicertus plebejus).

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Variation in strontium (Sr) and barium (Ba) within otoliths is invaluable to studies of fish diadromy. Typically, otolith Sr : Ca is positively related to salinity, and the ratios of Ba and Sr to calcium (Ca) vary in opposite directions in relation to salinity. In this study of jungle perch, Kuhlia rupestris, otolith Sr : Ca and Ba : Ca, however, showed the same rapid increase as late-larval stages transitioned directly from a marine to freshwater environment. This transition was indicated by a microstructural check mark on otoliths at 35–45 days age. As expected ambient Sr was lower in the fresh than the marine water, however, low Ca levels (0.4 mg L–1) of the freshwater resulted in the Sr : Ca being substantially higher than the marine water. Importantly, the otolith Sr : Ba ratio showed the expected pattern of a decrease from the marine to freshwater stage, illustrating that Sr : Ba provided a more reliable inference of diadromous behaviour based on prior expectations of their relationship to salinity, than did Sr : Ca. The results demonstrate that Ca variation in freshwaters can potentially be an important influence on otolith element : Ca ratios and that inferences of marine–freshwater habitat use from otolith Sr : Ca alone can be problematic without an understanding of water chemistry.