6 resultados para predictive value of tests

em eResearch Archive - Queensland Department of Agriculture


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Understanding the effects of different types and quality of data on bioclimatic modeling predictions is vital to ascertaining the value of existing models, and to improving future models. Bioclimatic models were constructed using the CLIMEX program, using different data types – seasonal dynamics, geographic (overseas) distribution, and a combination of the two – for two biological control agents for the major weed Lantana camara L. in Australia. The models for one agent, Teleonemia scrupulosa Stål (Hemiptera:Tingidae) were based on a higher quality and quantity of data than the models for the other agent, Octotoma scabripennis Guérin-Méneville (Coleoptera: Chrysomelidae). Predictions of the geographic distribution for Australia showed that T. scrupulosa models exhibited greater accuracy with a progressive improvement from seasonal dynamics data, to the model based on overseas distribution, and finally the model combining the two data types. In contrast, O. scabripennis models were of low accuracy, and showed no clear trends across the various model types. These case studies demonstrate the importance of high quality data for developing models, and of supplementing distributional data with species seasonal dynamics data wherever possible. Seasonal dynamics data allows the modeller to focus on the species response to climatic trends, while distributional data enables easier fitting of stress parameters by restricting the species envelope to the described distribution. It is apparent that CLIMEX models based on low quality seasonal dynamics data, together with a small quantity of distributional data, are of minimal value in predicting the spatial extent of species distribution.

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Rabbits released in Australia in 1859 spread to most areas of suitable habitat by 1910 causing great damage to the environment and primary industries. Measurement of damage is essential to justify spending money and utilising resources to remove rabbits. Damage to pasture and biodiversity may be irreversible and therefore difficult to measure without comparison with an area that has never suffered such damage. A rabbit proof fence completed in 1906 protected a large part of south east Queensland from rabbits. The Darling Downs Moreton Rabbit Board (DDMRB) continues to maintain the fence and keep the area relatively free of rabbits. This area is unique because it is highly suitable for rabbits and yet it has never ‘experienced’ the damage caused by plagues of uncontrolled rabbits. A study site was established where the DDMRB fence separates an area heavily used by rabbits (‘dirty side’) from an area that has never been infested by rabbits (‘clean side’). The number and location of all rabbit warrens and log piles were recorded. The absence of warrens from the ‘clean side’ shows clearly that the rabbit proof fence has prevented rabbits from establishing warren systems. The ‘dirty side’ is characterised by a high number of warrens, a high density of rabbits, fewer pasture species and low macropod activity. Future work will determine whether the rabbit populations are viable in the absence of rabbit warrens. We plan to radio collar rabbits on both sides of the fence to measure their survival rate. In selected warrens and log piles of varying degrees of complexity and size, rabbits will be trapped and information on reproduction and age structure will be collected. This will allow better targeting of the source of rabbits during control operations. Once the initial comparative analysis of the site has been completed, all rabbit warrens will be destroyed on the dirty side of the fence. After rabbits are removed from this area, monitoring will continue to determine if pasture and biodiversity on opposite sides of the fence begin to mirror each other.

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The key outcome will be to identify a technology that is practical to use to scan logs identified by the modelling as suspect or marginal for sawing and to confirm their unsuitability for value adding sawing by internal scanning.

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We used an established seagrass monitoring programme to examine the short and longer-term impacts of an oil spill event on intertidal seagrass meadows. Results for potentially impacted seagrass areas were compared with existing monitoring data and with control seagrass meadows located outside of the oil spill area. Seagrass meadows were not significantly affected by the oil spill. Declines in seagrass biomass and area 1 month post-spill were consistent between control and impact meadows. Eight months post-spill, seagrass density and area increased to be within historical ranges. The declines in seagrass meadows were likely attributable to natural seasonal variation and a combination of climatic and anthropogenic impacts. The lack of impact from the oil spill was due to several mitigating factors rather than a lack of toxic effects to seagrasses. The study demonstrates the value of long-term monitoring of critical habitats in high risk areas to effectively assess impacts.

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Objective 1. Measure spatial and temporal trawl frequency of scallop grounds using VMS data. This will provide a relative measure of how often individual undersized scallops are caught and put through a tumbler 2. Estimate discard mortality and growth rates for saucer scallops using cage experiments. 3. Evaluate the current management measures, in particular the seasonal closure, rotational closure and seasonally varying minimum legal sizes using stock assessment and management modeling models. Recommend optimal range of management measures to ensure long-term viability and value of the Scallop fishery based on a formal management strategy evaluation. Outcomes acheived to date: 1. Improved understanding of the survival rates of discarded sub-legal scallops; 2. Preliminary von Bertalanffy growth parameters using data from tagged-and-released scallops; 3. Changing trends in vessels and fishing gear used in the Queensland scallop fishery and their effect on scallop catch rates over time using standardised catch rates quantified; 4. Increases in fishing power of vessels operating in the Queensland scallop fishery quantified; 5. Trawl intensity mapped and quantified for all Scallop Replenishment Areas; 6. Harvest Strategy Evaluations completed.

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Over the past two decades, the poultry sector in China went through a phase of tremendous growth as well as rapid intensification and concentration. Highly pathogenic avian influenza virus (HPAIV) subtype H5N1 was first detected in 1996 in Guangdong province, South China and started spreading throughout Asia in early 2004. Since then, control of the disease in China has relied heavily on wide-scale preventive vaccination combined with movement control, quarantine and stamping out. This strategy has been successful in drastically reducing the number of outbreaks during the past 5 years. However, HPAIV H5N1 is still circulating and is regularly isolated in traditional live bird markets (LBMs) where viral infection can persist, which represent a public health hazard for people visiting them. The use of social network analysis in combination with epidemiological surveillance in South China has identified areas where the success of current strategies for HPAI control in the poultry production sector may benefit from better knowledge of poultry trading patterns and the LBM network configuration as well as their capacity for maintaining HPAIV H5N1 infection. We produced a set of LBM network maps and estimated the associated risk of HPAIV H5N1 within LBMs and along poultry market chains, providing new insights into how live poultry trade and infection are intertwined. More specifically, our study provides evidence that several biosecurity factors such as daily cage cleaning, daily cage disinfection or manure processing contribute to a reduction in HPAIV H5N1 presence in LBMs. Of significant importance is that the results of our study also show the association between social network indicators and the presence of HPAIV H5N1 in specific network configurations such as the one represented by the counties of origin of the birds traded in LBMs. This new information could be used to develop more targeted and effective control interventions.