13 resultados para Risk areas

em eResearch Archive - Queensland Department of Agriculture


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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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A recent report to the Australian Government identified concerns relating to Australia's capacity to respond to a medium to large outbreak of FMD. To assess the resources required, the AusSpread disease simulation model was used to develop a plausible outbreak scenario that included 62 infected premises in five different states at the time of detection, 28 days after the disease entered the first property in Victoria. Movements of infected animals and/or contaminated product/equipment led to smaller outbreaks in NSW, Queensland, South Australia and Tasmania. With unlimited staff resources, the outbreak was eradicated in 63 days with 54 infected premises and a 98% chance of eradication within 3 months. This unconstrained response was estimated to involve 2724 personnel. Unlimited personnel was considered unrealistic, and therefore, the course of the outbreak was modelled using three levels of staffing and the probability of achieving eradication within 3 or 6 months of introduction determined. Under the baseline staffing level, there was only a 16% probability that the outbreak would be eradicated within 3 months, and a 60% probability of eradication in 6 months. Deployment of an additional 60 personnel in the first 3 weeks of the response increased the likelihood of eradication in 3 months to 68%, and 100% in 6 months. Deployment of further personnel incrementally increased the likelihood of timely eradication and decreased the duration and size of the outbreak. Targeted use of vaccination in high-risk areas coupled with the baseline personnel resources increased the probability of eradication in 3 months to 74% and to 100% in 6 months. This required 25 vaccination teams commencing 12 days into the control program increasing to 50 vaccination teams 3 weeks later. Deploying an equal number of additional personnel to surveillance and infected premises operations was equally effective in reducing the outbreak size and duration.

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Decision-making in agriculture is carried out in an uncertain environment with farmers often seeking information to reduce risk. As a result of the extreme variability of rainfall and stream-flows in north-eastern Australia, water supplies for irrigated agriculture are a limiting factor and a source of risk. The present study examined the use of seasonal climate forecasting (SCF) when calculating planting areas for irrigated cotton in the northern Murray Darling Basin. Results show that minimising risk by adjusting plant areas in response to SCF can lead to significant gains in gross margin returns. However, how farmers respond to SCF is dependent on several other factors including irrigators’ attitude towards risk.

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Objective: To investigate the prevalence of Echinococcus granulosus in wild dogs (dingos and dingo-domestic dog hybrids) living in and around human habitation on Fraser Island and in townships of the Maroochy Shire, on Queensland's Sunshine Coast, Australia. Design: Wild dogs were humanely killed on Fraser Island and in the Maroochy Shire because they were deemed a potential danger to the public. Their intestines were collected and the contents examined for intestinal parasites. Procedure: Intestines were removed as soon after death as possible, packed in plastic bags and kept frozen until examination. The intestinal contents were washed, sieved and examined microscopically for the presence of helminths, which were identified and counted. Results: Intestines from 108 wild dogs, 7 foxes and 18 Fraser Island dingoes were examined. Echinococcus granulosus was only present in the wild dogs from Maroochy Shire (46.3%) with worm burdens of between 30 and 104,000. Other helminths included Spirometra erinacei, Dipylidium caninum, Taenia spp., Ancylostoma caninum and Toxocara canis. Two specimens of a trematode (Haplorchinae sp.) usually found infecting fish and seabirds were recovered from a Fraser Island dingo. Conclusion: Dingoes on Fraser Island are not infected with E. granulosus and do not pose a hydatid disease public health risk to residents or visitors. However, wild dogs examined from the Maroochy Shire do present a potential hydatid disease public health risk.

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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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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.

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Given the limited resources available for weed management, a strategic approach is required to give the best bang for your buck. The current study incorporates: (1) a model ensemble approach to identify areas of uncertainty and commonality regarding a species invasive potential, (2) current distribution of the invaded species, and (3) connectivity of systems to identify target regions and focus efforts for more effective management. Uncertainty in the prediction of suitable habitat for H. amplexicaulis (study species) in Australia was addressed in an ensemble-forecasting approach to compare distributional scenarios from four models (CLIMATCH; CLIMEX; boosted regression trees [BRT]; maximum entropy [Maxent]). Models were built using subsets of occurrence and environmental data. Catchment risk was determined through incorporating habitat suitability, the current abundance and distribution of H. amplexicaulis, and catchment connectivity. Our results indicate geographic differences between predictions of different approaches. Despite these differences a number of catchments in northern, central, and southern Australia were identified as high risk of invasion or further spread by all models suggesting they should be given priority for the management of H. amplexicaulis. The study also highlighted the utility of ensemble approaches in indentifying areas of uncertainty and commonality regarding the species invasive potential.

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Preputial prolapse is an obvious condition affecting bulls from many breeds. Unfortunately, the losses in production and welfare concerns associated with preputial prolapse can remain undetected for long periods of time in the extensive beef areas of northern Australia where the bulls are not inspected regularly. Thus, there is a critical need to identify the structural factors predisposing to preputial prolapse in young bulls so that they can be culled early. Despite there being no firm scientific evidence of an association between preputial eversion and preputial prolapse, it seems logical that the increased exposure of the sensitive prepuce as a consequence of preputial eversion may increase the risk of bulls developing preputial pathology, in particular preputial prolapse. This may be particularly relevant in Bos indicus bulls as they have a more pendulous sheath and thus eversion of the prepuce may be associated with a greater risk of injury to the prepuce compared to that in Bos taurus bulls. Further, studies of preputial eversion in Bos taurus bulls have concluded that there is an association between polledness and increased prevalence and severity (length of everted prepuce and duration of eversion) of preputial eversion due primarily to the absence or poor development of the caudal preputial muscles. No similar definitive work in Bos indicus bulls has been conducted and thus anatomical studies reported in this thesis were conducted to determine if a similar association occurred in Bos indicus bulls. A survey of a sample of large beef breeding herds in northern Australia found that preputial prolapse is a significant problem in Bos indicus and Bos indicus derived bulls and affected both young and older bulls. The importance of preputial prolapse confirmed the value of further research into the causes of this problem. A series of anatomical studies confirmed that preputial eversion in Bos indicus derived bulls was not more prevalent in polled bulls than horned bulls and was not associated with deficiency of the caudal preputial muscles as was established in Bos taurus bulls. An anatomical study of Bos indicus derived bulls with preputial prolapse found that preputial prolapse occurred in horned bulls of varying ages and these bulls did not have any evidence of deficiency in the caudal preputial muscles. However, preputial prolapse was observed in young polled bulls that had poorly developed or absent caudal preputial muscles. It was concluded that deficiency of the caudal preputial muscles in polled Bos indicus derived bulls may predispose to preputial prolapse at an early age, but no predisposing anatomical factors were found for horned Bos indicus derived bulls. In these studies, preputial eversion and preputial prolapse were found in horned Bos indicus derived bulls that did not have any preputial muscle deficiency and it was noted that preputial eversion was not related to the length of the prepuce. Further studies confirmed that preputial eversion was linearly and consistently associated with position of the glans penis within the sheath in Bos indicus derived bulls, and movement of the glans penis towards the preputial orifice consistently resulted in preputial eversion in these bulls. A method to objectively measure the relationship between movement of the glans penis within the sheath and preputial eversion was developed. Studies in humans have linked function of some abdominal muscles to function of the pelvic organs. This relationship was investigated in Bos indicus derived bulls to determine whether the function of specific abdominal muscles affected position of the penis in the sheath. Using the method developed to objectively measure the relationship between penis movement and preputial eversion, the abdominal muscles that potentially were associated with movement of the glans penis or preputial eversion were examined but no significant relationships were observed. In the anatomical study of Bos indicus derived bulls not affected with preputial prolapse a more pendulous sheath was associated with increased prevalence of preputial eversion. This relationship was confirmed for horned and polled bulls in the penis movement studies. Bos indicus derived bulls with more pendulous sheaths evert their prepuces more than bulls with less pendulous sheaths thus increasing the risk of damage to the prepuce either from the environment, other bulls, or from them inadvertently stepping on the everted prepuce when they get to their feet. Culling Bos indicus derived bulls with more pendulous sheaths should reduce the incidence of preputial eversion and possibly preputial prolapse. The anatomical study of Bos indicus derived bulls that did not have preputial prolapse demonstrates that there are herds of bulls where the polled bulls do not have any evidence of deficiency of the caudal preputial iv muscles. There is a need to develop a practical and cost effective test to identify polled Bos indicus bulls that have a deficiency in their caudal preputial muscles.

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In irrigated cropping, as with any other industry, profit and risk are inter-dependent. An increase in profit would normally coincide with an increase in risk, and this means that risk can be traded for profit. It is desirable to manage a farm so that it achieves the maximum possible profit for the desired level of risk. This paper identifies risk-efficient cropping strategies that allocate land and water between crop enterprises for a case study of an irrigated farm in Southern Queensland, Australia. This is achieved by applying stochastic frontier analysis to the output of a simulation experiment. The simulation experiment involved changes to the levels of business risk by systematically varying the crop sowing rules in a bioeconomic model of the case study farm. This model utilises the multi-field capability of the process based Agricultural Production System Simulator (APSIM) and is parameterised using data collected from interviews with a collaborating farmer. We found sowing rules that increased the farm area sown to cotton caused the greatest increase in risk-efficiency. Increasing maize area also improved risk-efficiency but to a lesser extent than cotton. Sowing rules that increased the areas sown to wheat reduced the risk-efficiency of the farm business. Sowing rules were identified that had the potential to improve the expected farm profit by ca. $50,000 Annually, without significantly increasing risk. The concept of the shadow price of risk is discussed and an expression is derived from the estimated frontier equation that quantifies the trade-off between profit and risk.

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For many years Australian forest pathologists and other scientists have dreaded the arrival of the rust fungus, Puccinia psidii, commonly known as Myrtle Rust, in Australia. This pathogen eventually did arrive in that country and was first detected in New South Wales in 2010 on Willow Myrtle (Agonis flexuosa). It is generally accepted that it entered the country on an ornamental Myrtales* host brought in by a private nursery. Despite efforts to eradicate the invasive rust, it has already spread widely, now occurring along the east coast of Australia, from temperate areas in Victoria and southern North South Wales to tropical areas in north Queensland.

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Puccinia psidii, the causal agent of myrtle rust, was first recorded from Latin America more than 100 years ago. It occurs on many native species of Myrtaceae in Latin America and also infects non-native plantation-grown Eucalyptus species in the region. The pathogen has gradually spread to new areas including Australia and most recently South Africa. The aim of this study was to consider the susceptibility of selected Eucalyptus genotypes, particularly those of interest to South African forestry, to infection by P. psidii. In addition, risk maps were compiled based on suitable climatic conditions and the occurrence of potential susceptible tree species. This made it possible to identify the season when P. psidii would be most likely to infect and to define the geographic areas where the rust disease would be most likely to establish in South Africa. As expected, variation in susceptibility was observed between eucalypt genotypes tested. Importantly, species commonly planted in South Africa show good potential for yielding disease-tolerant material for future planting. Myrtle rust is predicted to be more common in spring and summer. Coastal areas, as well as areas in South Africa with subtropical climates, are more conducive to outbreaks of the pathogen.

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Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.

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Aflatoxin is a potent carcinogen produced by Aspergillus flavus, which frequently contaminates maize (Zea mays L.) in the field between 40° north and 40° south latitudes. A mechanistic model to predict risk of pre-harvest contamination could assist in management of this very harmful mycotoxin. In this study we describe an aflatoxin risk prediction model which is integrated with the Agricultural Production Systems Simulator (APSIM) modelling framework. The model computes a temperature function for A. flavus growth and aflatoxin production using a set of three cardinal temperatures determined in the laboratory using culture medium and intact grains. These cardinal temperatures were 11.5 °C as base, 32.5 °C as optimum and 42.5 °C as maximum. The model used a low (≤0.2) crop water supply to demand ratio—an index of drought during the grain filling stage to simulate maize crop's susceptibility to A. flavus growth and aflatoxin production. When this low threshold of the index was reached the model converted the temperature function into an aflatoxin risk index (ARI) to represent the risk of aflatoxin contamination. The model was applied to simulate ARI for two commercial maize hybrids, H513 and H614D, grown in five multi-location field trials in Kenya using site specific agronomy, weather and soil parameters. The observed mean aflatoxin contamination in these trials varied from <1 to 7143 ppb. ARI simulated by the model explained 99% of the variation (p ≤ 0.001) in a linear relationship with the mean observed aflatoxin contamination. The strong relationship between ARI and aflatoxin contamination suggests that the model could be applied to map risk prone areas and to monitor in-season risk for genotypes and soils parameterized for APSIM.