21 resultados para A1B scenario

em eResearch Archive - Queensland Department of Agriculture


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The emerging carbon economy will have a major impact on grazing businesses because of significant livestock methane and land-use change emissions. Livestock methane emissions alone account for similar to 11% of Australia's reported greenhouse gas emissions. Grazing businesses need to develop an understanding of their greenhouse gas impact and be able to assess the impact of alternative management options. This paper attempts to generate a greenhouse gas budget for two scenarios using a spread sheet model. The first scenario was based on one land-type '20-year-old brigalow regrowth' in the brigalow bioregion of southern-central Queensland. The 50 year analysis demonstrated the substantially different greenhouse gas outcomes and livestock carrying capacity for three alternative regrowth management options: retain regrowth (sequester 71.5 t carbon dioxide equivalents per hectare, CO2-e/ha), clear all regrowth (emit 42.8 t CO2-e/ha) and clear regrowth strips (emit 5.8 t CO2-e/ha). The second scenario was based on a 'remnant eucalypt savanna-woodland' land type in the Einasleigh Uplands bioregion of north Queensland. The four alternative vegetation management options were: retain current woodland structure (emit 7.4 t CO2-e/ha), allow woodland to thicken increasing tree basal area (sequester 20.7 t CO2-e/ha), thin trees less than 10 cm diameter (emit 8.9 t CO2-e/ha), and thin trees <20 cm diameter (emit 12.4 t CO2-e/ha). Significant assumptions were required to complete the budgets due to gaps in current knowledge on the response of woody vegetation, soil carbon and non-CO2 soil emissions to management options and land-type at the property scale. The analyses indicate that there is scope for grazing businesses to choose alternative management options to influence their greenhouse gas budget. However, a key assumption is that accumulation of carbon or avoidance of emissions somewhere on a grazing business (e.g. in woody vegetation or soil) will be recognised as an offset for emissions elsewhere in the business (e.g. livestock methane). This issue will be a challenge for livestock industries and policy makers to work through in the coming years.

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Pasture degradation, particularly that attributable to overgrazing, is a significant problem across the northern Australian rangelands. Although grazing studies have identified the scope for wet season resting strategies to be used to rehabilitate degraded pastures, the economic outcome of these strategies has not been extensively demonstrated. An exploratory study of the prospective economic value of wet season resting is presented using an economic simulation model of a 28000 ha beef enterprise located in the Charters Towers region of north-eastern Australia to explore seven hypothetical scenarios centred on the projected performance of a wet season resting strategy. A series of 20-year simulations for a range of pasture recovery profiles, stocking capacity, animal productivity responses, beef prices and agistment options are compared with a baseline scenario of taking no action. Estimates of the net present value of the 20-year difference in total enterprise gross margins between the various resting options and the 'do nothing' option identify that wet season resting can offer a positive economic return for the range of scenarios examined, although this is contingent on the assumptions that are made concerning the trajectories of change in carrying capacity and animal productivity. Some implications for management and policy making to support the practical implementation of wet season resting strategies are discussed.

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Aflatoxins are highly carcinogenic mycotoxins produced by two fungi, Aspergillus flavus and A. parasiticus, under specific moisture and temperature conditions before harvest and/or during storage of a wide range of crops including maize. Modelling of interactions between host plant and environment during the season can enable quantification of preharvest aflatoxin risk and its potential management. A model was developed to quantify climatic risks of aflatoxin contamination in maize using principles previously used for peanuts. The model outputs an aflatoxin risk index in response to seasonal temperature and soil moisture during the maize grain filling period using the APSIM's maize module. The model performed well in simulating climatic risk of aflatoxin contamination in maize as indicated by a significant R2 (P ≤ 0.01) between aflatoxin risk index and the measured aflatoxin B1 in crop samples, which was 0.69 for a range of rainfed Australian locations and 0.62 when irrigated locations were also included in the analysis. The model was further applied to determine probabilities of exceeding a given aflatoxin risk in four non-irrigated maize growing locations of Queensland using 106 years of historical climatic data. Locations with both dry and hot climates had a much higher probability of higher aflatoxin risk compared with locations having either dry or hot conditions alone. Scenario analysis suggested that under non-irrigated conditions the risk of aflatoxin contamination could be minimised by adjusting sowing time or selecting an appropriate hybrid to better match the grain filling period to coincide with lower temperature and water stress conditions.

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Weedy Sporobolus grasses have low palatability for livestock, with infestations reducing land condition and pastoral productivity. Control and containment options are available, but the cost of weed control is high relative to the extra return from livestock, thus, limiting private investment. This paper outlines a process for analysing the economic consequences of alternative management options for weedy Sporobolus grasses. This process is applicable to other weeds and other pastoral degradation or development issues. Using a case study property, three scenarios were developed. Each scenario compared two alternative management options and was analysed using discounted cash flow analysis. Two of the scenarios were based on infested properties and one scenario was based on a currently uninfested property but highly likely to become infested without active containment measures preventing weed seed transport and seedling establishment. The analysis highlighted why particular weedy Sporobolus grass management options may not be financially feasible for the landholder with the infestation. However, at the regional scale, the management options may be highly worthwhile due to a reduction in weed seed movement and new weed invasions. Therefore, to encourage investment by landholders in weedy Sporobolus grass management the investment of public money on behalf of landholders with non-infested properties should be considered.

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Senna obtusifolia (sicklepod) is an invasive weed of northern Australia, where it significantly impacts agricultural productivity and alters natural ecosystem structure and function. Although currently restricted to northern regions, the potential for S. obtusifolia to spread south is not known. Using the eco-climatic model CLIMEX, this study simulated the potential geographic distribution of S. obtusifolia in Australia under two scenarios. Model parameters for both scenarios were derived from the distribution of S. obtusifolia throughout North and Central America. The first scenario used these base model parameters to predict the distribution of S. obtusifolia in Australia, whilst the second model predicted the distribution of a cold susceptible S. obtusifolia ecotype that is reported to occur in the USA. Both models predicted the potential for an extensive S. obtusifolia distribution, with the first model indicating suitable climatic conditions occurring predominantly in coastal regions from the Northern Territory, to far north Queensland and into northern Victoria. The cold susceptible ecotype displayed a comparatively reduced distribution in the southern parts of Australia, where inappropriate temperatures, a lack of thermal accumulation and cold stress restrict the invasion south to the coastal regions of central New South Wales. The extent of the predicted distribution of both ecotypes of S. obtusifolia reinforces the need for strategic management at a national scale.

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Climate change projections for Australia predict increasing temperatures, changes to rainfall patterns, and elevated atmospheric carbon dioxide (CO2) concentrations. The aims of this study were to predict plant production responses to elevated CO2 concentrations using the SGS Pasture Model and DairyMod, and then to quantify the effects of climate change scenarios for 2030 and 2070 on predicted pasture growth, species composition, and soil moisture conditions of 5 existing pasture systems in climates ranging from cool temperate to subtropical, relative to a historical baseline. Three future climate scenarios were created for each site by adjusting historical climate data according to temperature and rainfall change projections for 2030, 2070 mid-and 2070 high-emission scenarios, using output from the CSIRO Mark 3 global climate model. In the absence of other climate changes, mean annual pasture production at an elevated CO2 concentration of 550 ppm was predicted to be 24-29% higher than at 380 ppm CO2 in temperate (C-3) species-dominant pastures in southern Australia, with lower mean responses in a mixed C-3/C-4 pasture at Barraba in northern New South Wales (17%) and in a C-4 pasture at Mutdapilly in south-eastern Queensland (9%). In the future climate scenarios at the Barraba and Mutdapilly sites in subtropical and subhumid climates, respectively, where climate projections indicated warming of up to 4.4 degrees C, with little change in annual rainfall, modelling predicted increased pasture production and a shift towards C-4 species dominance. In Mediterranean, temperate, and cool temperate climates, climate change projections indicated warming of up to 3.3 degrees C, with annual rainfall reduced by up to 28%. Under future climate scenarios at Wagga Wagga, NSW, and Ellinbank, Victoria, our study predicted increased winter and early spring pasture growth rates, but this was counteracted by a predicted shorter spring growing season, with annual pasture production higher than the baseline under the 2030 climate scenario, but reduced by up to 19% under the 2070 high scenario. In a cool temperate environment at Elliott, Tasmania, annual production was higher than the baseline in all 3 future climate scenarios, but highest in the 2070 mid scenario. At the Wagga Wagga, Ellinbank, and Elliott sites the effect of rainfall declines on pasture production was moderated by a predicted reduction in drainage below the root zone and, at Ellinbank, the use of deeper rooted plant systems was shown to be an effective adaptation to mitigate some of the effect of lower rainfall.

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Global trends in human population and agriculture dictate that future calls made on the resources (physical, human, financial) and systems involved in producing food will be increasingly more demanding and complex. Both plant breeding and improved agronomy lift the potential yield of crops, a key component in progressing farm yield, so society can reasonably expect both agronomy as a science and agronomists as practitioners to contribute to the successful delivery of necessary change. By reflecting on current trends in agricultural production (diversification, intensification, integration, industrialisation, automation) and deconstructing a futuristic scenario of attempting agricultural production on Mars, it seems the skills agronomists will require involve not only the mandatory elements of their discipline but also additional skills that enable engagement with, even leadership of, teams who integrate (in sum or part) engineering, (agri-)business, economics and operational management, and build the social capital required to create and maintain a diverse array of enhanced and new ethical production systems and achieve increasing efficiencies within them.

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This project will develop better understanding of resistance to glyphosate, paraquat and Group I herbicides to better inform weed management. The project will develop a range of tools for farm advisors to improve their confidence in decision making with respect to reducing the risk of glyphosate, Group I and paraquat resistance. These will include risk assessments, case studies and scenario exploring tools. The project will discuss with commercial providers the potential for new herbicide registrations. The project will establish farm advisor learning groups to work on the application of the research in local areas where resistance is already a major problem and to improve adoption of research outcomes from this and other projects.

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This paper examines the idea that plasticity in farm management introduces resilience to change and allows farm businesses to perform when operating in highly variable environments. We also argue for the need to develop and apply more integrative assessments of farm performance that combine the use of modelling tools with deliberative processes involving farmers and researchers in a co-learning process, to more effectively identify and implement more productive and resilient farm businesses. In a plastic farming system, farm management is highly contingent on environmental conditions. In plastic farming systems farm managers constantly vary crops and inputs based on the availability of limited and variable resources (e.g. land, water, finances, labour, machinery, etc.), and signals from its operating environment (e.g. climate, markets), with the objective of maximising a number of, often competing, objectives (e.g. maximise profits, minimise risks, etc.). In contrast in more rigid farming systems farm management is more calendar driven and relatively fixed sequences of crops are regularly followed over time and across the farm. Here we describe the application of a whole farm simulation model to (i) compare, in silico, the sensitivity of two farming systems designs of contrasting levels of plasticity, operating in two contrasting environments, when exposed to a stressor in the form of climate change scenarios;(ii) investigate the presence of interactions and feedbacks at the field and farm levels capable of modifying the intensity and direction of the responses to climate signals; and (iii) discuss the need for the development and application of more integrative assessments in the analysis of impacts and adaptation options to climate change. In both environments, the more plastic farm management strategy had higher median profits and was less risky for the baseline and less intensive climate change scenarios (2030). However, for the more severe climate change scenarios (2070), the benefit of plastic strategies tended to disappear. These results suggest that, to a point, farming systems having higher levels of plasticity would enable farmers to more effectively respond to climate shifts, thus ensuring the economic viability of the farm business. Though, as the intensity of the stress increases (e.g. 2070 climate change scenario) more significant changes in the farming system might be required to adapt. We also found that in the case studies analysed here, most of the impacts from the climate change scenarios on farm profit and economic risk originated from important reductions in cropping intensity and changes in crop mix rather than from changes in the yields of individual crops. Changes in cropping intensity and crop mix were explained by the combination of reductions in the number of sowing opportunities around critical times in the cropping calendar, and to operational constraints at the whole farm level i.e. limited work capacity in an environment having fewer and more concentrated sowing opportunities. This indicates that indirect impacts from shifts in climate on farm operations can be more important than direct impacts from climate on the yield of individual crops. The results suggest that due to the complexity of farm businesses, impact assessments and opportunities for adaptation to climate change might also need to be pursued at higher integration levels than the crop or the field. We conclude that plasticity can be a desirable characteristic in farming systems operating in highly variable environments, and that integrated whole farm systems analyses of impacts and adaptation to climate change are required to identify important interactions between farm management decision rules, availability of resources, and farmer's preference.

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Executive summary. In this report we analyse implementation costs and benefits for agricultural management practices, grouped into farming systems. In order to do so, we compare plot scale gross margins for the dominant agricultural production systems (sugarcane, grazing and banana cultivation) in the NRM regions Wet Tropics, Burdekin Dry Tropics and Mackay Whitsundays. Furthermore, where available, we present investment requirements for changing to improved farming systems. It must be noted that transaction costs are not captured within this project. For sugarcane, this economic analysis shows that there are expected benefits to sugarcane growers in the different regions through transitions to C and B class farming systems. Further transition to A-class farming systems can come at a cost, depending on the capital investment required and the length of the investment period. Obviously, the costs and benefits will vary for each individual grower and will depend on their starting point and individual property scenario therefore each circumstance needs to be carefully considered before making a change in management practice. In grazing, overall, reducing stocking rates comes at a cost (reduced benefits). However, when operating at low utilisation rates in wetter country, lowering stocking rates can potentially come at a benefit. With win-win potential, extension is preferred to assist farmer in changing management practices to improve their land condition. When reducing stocking rates comes at a cost, incentives may be applicable to support change among farmers. For banana cultivation, the results indicate that the transition to C and B class management practices is a worthwhile proposition from an economic perspective. For a change from B to A class farming systems however, it is not worthwhile from a financial perspective. This is largely due to the large capital investment associated with the change in irrigation system and negative impact in whole of farm gross margin. Overall, benefits will vary for each individual grower depending on their starting point and their individual property scenario. The results presented in this report are one possible set of figures to show the changes in profitability of a grower operating in different management classes. The results in this report are not prescriptive of every landholder. Landholders will have different costs and benefits from transitioning to improved practices, even if similar operations are practiced, hence it is recommended that landholders that are willing to change management undertake their own research and analysis into the expected costs and benefits for their own soil types and property circumstances.

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The availability and quality of irrigation water has become an issue limiting productivity in many Australian vegetable regions. Production is also under competitive pressure from supply chain forces. Producers look to new technologies, including changing irrigation infrastructure, exploring new water sources, and more complex irrigation management, to survive these stresses. Often there is little objective information investigating which improvements could improve outcomes for vegetable producers, and external communities (e.g. meeting NRM targets). This has led to investment in inappropriate technologies, and costly repetition of errors, as business independently discover the worth of technologies by personal experience. In our project, we investigated technology improvements for vegetable irrigation. Through engagement with industry and other researchers, we identified technologies most applicable to growers, particularly those that addressed priority issues. We developed analytical tools for ‘what if’ scenario testing of technologies. We conducted nine detailed experiments in the Lockyer Valley and Riverina vegetable growing districts, as well as case studies on grower properties in southern Queensland. We investigated root zone monitoring tools (FullStop™ wetting front detectors and Soil Solution Extraction Tubes - SSET), drip system layout, fertigation equipment, and altering planting arrangements. Our project team developed and validated models for broccoli, sweet corn, green beans and lettuce, and spreadsheets for evaluating economic risks associated with new technologies. We presented project outcomes at over 100 extension events, including irrigation showcases, conferences, field days, farm walks and workshops. The FullStops™ were excellent for monitoring root zone conditions (EC, nitrate levels), and managing irrigation with poor quality water. They were easier to interpret than the SSET. The SSET were simpler to install, but required wet soil to be reliable. SSET were an option for monitoring deeper soil zones, unsuitable for FullStop™ installations. Because these root zone tools require expertise, and are labour intensive, we recommend they be used to address specific problems, or as a periodic auditing strategy, not for routine monitoring. In our research, we routinely found high residual N in horticultural soils, with subsequently little crop yield response to additional nitrogen fertiliser. With improved irrigation efficiency (and less leaching), it may be timely to re-examine nitrogen budgets and recommendations for vegetable crops. Where the drip irrigation tube was located close to the crop row (i.e. within 5-8 cm), management of irrigation was easier. It improved nitrogen uptake, water use efficiency, and reduced the risk of poor crop performance through moisture stress, particularly in the early crop establishment phases. Close proximity of the drip tube to the crop row gives the producer more options for managing salty water, and more flexibility in taking risks with forecast rain. In many vegetable crops, proximate drip systems may not be cost-effective. The next best alternative is to push crop rows closer to the drip tube (leading to an asymmetric row structure). The vegetable crop models are good at predicting crop phenology (development stages, time to harvest), input use (water, fertiliser), environmental impacts (nutrient, salt movement) and total yields. The two immediate applications for the models are understanding/predicting/manipulating harvest dates and nitrogen movements in vegetable cropping systems. From the economic tools, the major influences on accumulated profit are price and yield. In doing ‘what if’ analyses, it is very important to be as accurate as possible in ascertaining what the assumed yield and price ranges are. In most vegetable production systems, lowering the required inputs (e.g. irrigation requirement, fertiliser requirement) is unlikely to have a major influence on accumulated profit. However, if a resource is constraining (e.g. available irrigation water), it is usually most profitable to maximise return per unit of that resource.

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Development of new agricultural industries in northern Australia is seen as a way to provide food security in the face of reduced water availability in existing regions in the south. This report aims to identify some of the possible economic consequences of developing a rice industry in the Burdekin region, while there is a reduction of output in the Riverina. Annual rice production in the Riverina peaked at 1.7 M tonnes, but the long-term outlook, given climate change impacts on that region and government water buy-backs, is more likely to be less than 800,000 tonnes. Growers are highly efficient water users by international standards, but the ability to offset an anticipated reduction in water availability through further efficiency gains is limited. In recent years growers in the Riverina have diversified their farms to a greater extent and secondary production systems include beef, sheep and wheat. Production in north Queensland is in its infancy, but a potentially suitable farming system has been developed by including rice within the sugarcane system without competition and in fact contributing to the production of sugar by increasing yields and controlling weeds. The economic outcomes are estimated a large scale, dynamic, computable general equilibrium (CGE) model of the world economy (Tasman Global), scaled down to regional level. CGE models mimic the workings of the economy through a system of interdependent behavioural and accounting equations which are linked to an input-output database. When an economic shock or change is applied to a model, each of the markets adjusts according to the set of behavioural parameters which are underpinned by economic theory. In this study the model is driven by reducing production in the Riverina in accordance with relationships found between water availability and the production of rice and replacement by other crops and by increasing ride production in the Burdekin. Three scenarios were considered: • Scenario 1: Rice is grown using the fallow period between the last ratoon crop of sugarcane and the new planting. In this scenario there is no competition between rice and sugarcane • Scenario 2: Rice displaces sugarcane production • Scenario 3: Rice is grown on additional land and does not compete with sugarcane. Two time periods were used, 2030 and 2070, which are the conventional time points to consider climate change impacts. Under scenario 1, real economic output declines in the Riverina by $45 million in 2030 and by $139 million in 2070. This is only partially offset by the increased real economic output in the Burdekin of $35 million and $131 million respectively.

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This study presents the use of a whole farm model in a participatory modelling research approach to examine the sensitivity of four contrasting case study farms to a likely climate change scenario. The newly generated information was used to support discussions with the participating farmers in the search for options to design more profitable and sustainable farming systems in Queensland Australia. The four case studies contrasted in key systems characteristics: opportunism in decision making, i.e. flexible versus rigid crop rotations; function, i.e. production of livestock or crops; and level of intensification, i.e. dryland versus irrigated agriculture. Tested tactical and strategic changes under a baseline and climate change scenario (CCS) involved changes in the allocation of land between cropping and grazing enterprises, alternative allocations of limited irrigation water across cropping enterprises, and different management rules for planting wheat and sorghum in rainfed cropping. The results show that expected impacts from a likely climate change scenario were evident in the following increasing order: the irrigated cropping farm case study, the cropping and grazing farm, the more opportunistic rainfed cropping farm and the least opportunistic rainfed cropping farm. We concluded that in most cases the participating farmers were operating close to the efficiency frontier (i.e. in the relationship between profits and risks). This indicated that options to adapt to climate change might need to evolve from investments in the development of more innovative cropping and grazing systems and/or transformational changes on existing farming systems. We expect that even though assimilating expected changes in climate seems to be rather intangible and premature for these farmers, as innovations are developed, adaptation is likely to follow quickly. The multiple interactions among farm management components in complex and dynamic farm businesses operating in a variable and changing climate, make the use of whole farm participatory modelling approaches valuable tools to quantify benefits and trade-offs from alternative farming systems designs in the search for improved profitability and resilience.

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The off-site transport of agricultural chemicals, such as herbicides, into freshwater and marine ecosystems is a world-wide concern. The adoption of farm management practices that minimise herbicide transport in rainfall-runoff is a priority for the Australian sugarcane industry, particularly in the coastal catchments draining into the World Heritage listed Great Barrier Reef (GBR) lagoon. In this study, residual herbicide runoff and infiltration were measured using a rainfall simulator in a replicated trial on a brown Chromosol with 90–100% cane trash blanket cover in the Mackay Whitsunday region, Queensland. Management treatments included conventional 1.5 m spaced sugarcane beds with a single row of sugarcane (CONV) and 2 m spaced, controlled traffic sugarcane beds with dual sugarcane rows (0.8 m apart) (2mCT). The aim was to simulate the first rainfall event after the application of the photosynthesis inhibiting (PSII) herbicides ametryn, atrazine, diuron and hexazinone, by broadcast (100% coverage, on bed and furrow) and banding (50–60% coverage, on bed only) methods. These events included heavy rainfall 1 day after herbicide application, considered a worst case scenario, or rainfall 21 days after application. The 2mCT rows had significantly (P < 0.05) less runoff (38%) and lower peak runoff rates (43%) than CONV rows for a rainfall average of 93 mm at 100 mm h−1 (1:20 yr Average Return Interval). Additionally, final infiltration rates were higher in 2mCT rows than CONV rows, with 72 and 52 mm h−1 respectively. This resulted in load reductions of 60, 55, 47, and 48% for ametryn, atrazine, diuron and hexazinone from 2mCT rows, respectively. Herbicide losses in runoff were also reduced by 32–42% when applications were banded rather than broadcast. When rainfall was experienced 1 day after application, a large percentage of herbicides were washed off the cane trash. However, by day 21, concentrations of herbicide residues on cane trash were lower and more resistant to washoff, resulting in lower losses in runoff. Consequently, ametryn and atrazine event mean concentrations in runoff were approximately 8 fold lower at day 21 compared with day 1, whilst diuron and hexazinone were only 1.6–1.9 fold lower, suggesting longer persistence of these chemicals. Runoff collected at the end of the paddock in natural rainfall events indicated consistent though smaller treatment differences to the rainfall simulation study. Overall, it was the combination of early application, banding and controlled traffic that was most effective in reducing herbicide losses in runoff. Crown copyright © 2012

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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.