3 resultados para robust extended kalman filter

em eResearch Archive - Queensland Department of Agriculture


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The project has provided management and other stakeholders with information necessary to make informed decisions about the management of four of the key exploited shark species caught in the Queensland inshore net fishery and northern New South Wales line fishery. The project has determined that spatial management of milk sharks within Queensland, and scalloped hammerhead, common black tip and Australian black tip sharks within Queensland and New South Wales is appropriate. The project has determined that both black tip shark species are likely to require co-operative management arrangements between Queensland and New South Wales. For scalloped hammerheads separate stocks between the two jurisdictions were identified from the fisheriesdependent samples, however genetic exchange across borders is likely to be facilitated by movement of adult females and perhaps larger males to a lesser extent. This information will greatly assist compliance with the Commonwealth Environment Protection and Biodiversity Conservation Act (1999) for shark fisheries in north-eastern Australia by providing the necessary basis for robust assessment of the status of stocks of the study species, thereby helping to deliver their sustainable harvest. It also helps to achieve objectives of the Australian National Shark Plan. The project provides the appropriate spatial framework for future monitoring and assessment of the study species. This is at a time when shark fisheries are receiving close attention from all sectors and when monitoring programs are being implemented, aimed at better assessment of stock status. This project has provided the crucial information for developing an appropriate monitoring design as well as the necessary basis for making statements about stock status. The project has addressed research priorities identified by the Queensland Fisheries Research Advisory Board, Great Barrier Reef Marine Park Authority and Queensland Fisheries. Previously management has assumed a single stock for each species on the east coast of Queensland, and management of shark fisheries in New South Wales (NSW) and Queensland has been independent of one another. The project has been able to enhance and develop links between research, management and industry. Strong positive relationships with commercial fishers were crucial in the collection of samples throughout the study area and fisheries managers were part of the project team throughout the study period. During the project the study area was extended to include both Queensland and NSW waters, creating mutualistic and positive links between the States’ research and management agencies. Extension of project results included management representatives from NSW and Queensland, as well as the Northern Territory where similar shark fisheries operate and similar species are targeted. The project was able to provide significant human capital development opportunities providing considerable value to the project outcomes. Use of vertebral microchemistry and life history characteristics as stock determination methods provided material for two PhD students based at James Cook University: Ron Schroeder, vertebral chemistry; and Alastair Harry, life history characteristic. The project has developed novel research methods that have great capacity for future application, including: • Development of a simple and rapid genetic diagnostic tool (RT-HRM-PCR assay) for differentiating among the black tip shark species, for which no simple morphological identifier exists; and • Development of laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) methods for analysing and interpreting microchemical composition of shark vertebrae. The study has provided further confirmation of the effectiveness of using a holistic approach in stock structure studies and justifies investment into such studies.

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West Africa is highly vulnerable to climate hazards and better quantification and understanding of the impact of climate change on crop yields are urgently needed. Here we provide an assessment of near-term climate change impacts on sorghum yields in West Africa and account for uncertainties both in future climate scenarios and in crop models. Towards this goal, we use simulations of nine bias-corrected CMIP5 climate models and two crop models (SARRA-H and APSIM) to evaluate the robustness of projected crop yield impacts in this area. In broad agreement with the full CMIP5 ensemble, our subset of bias-corrected climate models projects a mean warming of +2.8 °C in the decades of 2031–2060 compared to a baseline of 1961–1990 and a robust change in rainfall in West Africa with less rain in the Western part of the Sahel (Senegal, South-West Mali) and more rain in Central Sahel (Burkina Faso, South-West Niger). Projected rainfall deficits are concentrated in early monsoon season in the Western part of the Sahel while positive rainfall changes are found in late monsoon season all over the Sahel, suggesting a shift in the seasonality of the monsoon. In response to such climate change, but without accounting for direct crop responses to CO2, mean crop yield decreases by about 16–20% and year-to-year variability increases in the Western part of the Sahel, while the eastern domain sees much milder impacts. Such differences in climate and impacts projections between the Western and Eastern parts of the Sahel are highly consistent across the climate and crop models used in this study. We investigate the robustness of impacts for different choices of cultivars, nutrient treatments, and crop responses to CO2. Adverse impacts on mean yield and yield variability are lowest for modern cultivars, as their short and nearly fixed growth cycle appears to be more resilient to the seasonality shift of the monsoon, thus suggesting shorter season varieties could be considered a potential adaptation to ongoing climate changes. Easing nitrogen stress via increasing fertilizer inputs would increase absolute yields, but also make the crops more responsive to climate stresses, thus enhancing the negative impacts of climate change in a relative sense. Finally, CO2 fertilization would significantly offset the negative climate

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This study aimed to define the frequency of resistance to critically important antimicrobials (CIAs) [i.e. extended-spectrum cephalosporins (ESCs), fluoroquinolones (FQs) and carbapenems] among Escherichia coli isolates causing clinical disease in Australian food-producing animals. Clinical E. coli isolates (n = 324) from Australian food-producing animals [cattle (n = 169), porcine (n = 114), poultry (n = 32) and sheep (n = 9)] were compiled from all veterinary diagnostic laboratories across Australia over a 1-year period. Isolates underwent antimicrobial susceptibility testing to 18 antimicrobials using the Clinical and Laboratory Standards Institute disc diffusion method. Isolates resistant to CIAs underwent minimum inhibitory concentration determination, multilocus sequence typing (MLST), phylogenetic analysis, plasmid replicon typing, plasmid identification, and virulence and antimicrobial resistance gene typing. The 324 E. coli isolates from different sources exhibited a variable frequency of resistance to tetracycline (29.0–88.6%), ampicillin (9.4–71.1%), trimethoprim/sulfamethoxazole (11.1–67.5%) and streptomycin (21.9–69.3%), whereas none were resistant to imipenem or amikacin. Resistance was detected, albeit at low frequency, to ESCs (bovine isolates, 1%; porcine isolates, 3%) and FQs (porcine isolates, 1%). Most ESC- and FQ-resistant isolates represented globally disseminated E. coli lineages (ST117, ST744, ST10 and ST1). Only a single porcine E. coli isolate (ST100) was identified as a classic porcine enterotoxigenic E. coli strain (non-zoonotic animal pathogen) that exhibited ESC resistance via acquisition of blaCMY-2. This study uniquely establishes the presence of resistance to CIAs among clinical E. coli isolates from Australian food-producing animals, largely attributed to globally disseminated FQ- and ESC-resistant E. coli lineages.