54 resultados para Other Economics


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The economic analysis is based on the A, B, C and D management practice framework for water quality improvement developed in 2007/2008 by the respective natural resource management region. This document focuses on the economic implications of these management practices in the Burdekin Delta region. A review of the management practices is currently being undertaken to clarify some issues and incorporate new knowledge since the earlier version of the framework. However, this updated version is not yet complete and so the Paddock to Reef project has used the most current available version of the framework for the modelling and economics.

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The economic analysis is based on the A, B, C and D management practice framework for water quality improvement developed in 2007/2008 by the respective natural resource management region. This document focuses on the economic implications of these management practices in the Burdekin River Irrigation Area (BRIA). A review of the management practices is currently being undertaken to clarify some issues and incorporate new knowledge since the earlier version of the framework. However, this updated version is not yet complete and so the Paddock to Reef project has used the most current available version of the framework for the modelling and economics.

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In Queensland the subtropical strawberry ( Fragaria * ananassa) breeding program aims to combine traits into novel genotypes that increase production efficiency. The contribution of individual plant traits to cost and income under subtropical Queensland conditions was investigated, with the overall goal of improving the profitability of the industry through the release of new strawberry cultivars. The study involved specifying the production and marketing system using three cultivars of strawberry that are currently widely grown annually in southeast Queensland, developing methods to assess the economic impact of changes to the system, and identifying plant traits that influence outcomes from the system. From May through September P (price; $ punnet -1), V (monthly mass; tonne of fruit on the market) and M (calendar month; i.e. May=5) were found to be related ( r2=0.92) by the function (SE) P=4.741(0.469)-0.001630(0.0005) V-0.226(0.102) M using data from 2006 to 2010 for the Brisbane central market. Both income and cost elements in the gross margin were subject to sensitivity analysis. 'Harvesting' and 'Handling/Packing' 'Groups' of 'Activities' were the major contributors to variable costs (each >20%) in the gross margin analysis. Within the 'Harvesting Group', the 'Picking Activity' contributed most (>80%) with the trait 'display of fruit' having the greatest (33%) influence on the cost of the 'Picking Activity'. Within the 'Handling/Packing Group', the 'Packing Activity' contributed 50% of costs with the traits 'fruit shape', 'fruit size variation' and 'resistance to bruising' having the greatest (12-62%) influence on the cost of the 'Packing Activity'. Non-plant items (e.g. carton purchases) made up the other 50% of the costs within the 'Handling/Packing Group'. When any of the individual traits in the 'Harvesting' and 'Handling/Packing' groups were changed by one unit (on a 1-9 scale) the gross margin changed by up to 1%. Increasing yield increased the gross margin to a maximum (15% above present) at 1320 g plant -1 (94% above present). A 10% redistribution of total yield from September to May increased the gross margin by 23%. Increasing fruit size increased gross margin: a 75% increase in fruit size (to ~30 g) produced a 22% increase in the gross margin. The modified gross margin analysis developed in this study allowed simultaneous estimation of the gross margin for the producer and gross value of the industry. These parameters sometimes move in opposite directions.

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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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The research undertaken here was in response to a decision by a major food producer in about 2009 to consider establishing processing tomato production in northern Australia. This was in response to a lack of water availability in the Goulburn Valley region following the extensive drought that continued until 2011. The high price of water and the uncertainty that went with it was important in making the decision to look at sites within Queensland. This presented an opportunity to develop a tomato production model for the varieties used in the processing industry and to use this as a case study along with rice and cotton production. Following some unsuccessful early trials and difficulties associated with the Global Financial Crisis, large scale studies by the food producer were abandoned. This report uses the data that was collected prior to this decision and contrasts the use of crop modelling with simpler climatic analyses that can be undertaken to investigate the impact of climate change on production systems. Crop modelling can make a significant contribution to our understanding of the impacts of climate variability and climate change because it harnesses the detailed understanding of physiology of the crop in a way that statistical or other analytical approaches cannot do. There is a high overhead, but given that trials are being conducted for a wide range of crops for a variety of purposes, breeding, fertiliser trials etc., it would appear to be profitable to link researchers with modelling expertise with those undertaking field trials. There are few more cost-effective approaches than modelling that can provide a pathway to understanding future climates and their impact on food production.

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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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Microfungi that cause disease or are associated with diseased plants in the wet tropics of northern Queensland are listed. A total of 206 host-pathogen combinations on 148 host species has been compiled from the results of plant disease surveys in the Wet Tropics World Heritage Area in 1992 and 1993, from herbarium records and from previously published host-pathogen combinations.

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Reduced economic circumstances have moved management goals towards higher profit, rather than maximum sustainable yields in several Australian fisheries. The eastern king prawn is one such fishery, for which we have developed new methodology for stock dynamics, calculation of model-based and data-based reference points and management strategy evaluation. The fishery is notable for the northward movement of prawns in eastern Australian waters, from the State jurisdiction of New South Wales to that of Queensland, as they grow to spawning size, so that vessels fishing in the northern deeper waters harvest more large prawns. Bio-economic fishing data were standardized for calibrating a length-structured spatial operating model. Model simulations identified that reduced boat numbers and fishing effort could improve profitability while retaining viable fishing in each jurisdiction. Simulations also identified catch-rate levels that were effective for monitoring in simple within-year effort-control rules. However, favourable performance of catch-rate indicators was achieved only when a meaningful upper limit was placed on total allowed fishing effort. The methods and findings will allow improved measures for monitoring fisheries and inform decision makers on the uncertainty and assumptions affecting economic indicators.

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The global importance of grasslands is indicated by their extent; they comprise some 26% of total land area and 80% of agriculturally productive land. The majority of grasslands are located in tropical developing countries where they are particularly important to the livelihoods of some one billion poor peoples. Grasslands clearly provide the feed base for grazing livestock and thus numerous high-quality foods, but such livestock also provide products such as fertilizer, transport, traction, fibre and leather. In addition, grasslands provide important services and roles including as water catchments, biodiversity reserves, for cultural and recreational needs, and potentially a carbon sink to alleviate greenhouse gas emissions. Inevitably, such functions may conflict with management for production of livestock products. Much of the increasing global demand for meat and milk, particularly from developing countries, will have to be supplied from grassland ecosystems, and this will provide difficult challenges. Increased production of meat and milk generally requires increased intake of metabolizable energy, and thus increased voluntary intake and/or digestibility of diets selected by grazing animals. These will require more widespread and effective application of improved management. Strategies to improve productivity include fertilizer application, grazing management, greater use of crop by-products, legumes and supplements and manipulation of stocking rate and herbage allowance. However, it is often difficult to predict the efficiency and cost-effectiveness of such strategies, particularly in tropical developing country production systems. Evaluation and on-going adjustment of grazing systems require appropriate and reliable assessment criteria, but these are often lacking. A number of emerging technologies may contribute to timely low-cost acquisition of quantitative information to better understand the soil-pasture-animal interactions and animal management in grassland systems. Development of remote imaging of vegetation, global positioning technology, improved diet markers, near IR spectroscopy and modelling provide improved tools for knowledge-based decisions on the productivity constraints of grazing animals. Individual electronic identification of animals offers opportunities for precision management on an individual animal basis for improved productivity. Improved outcomes in the form of livestock products, services and/or other outcomes from grasslands should be possible, but clearly a diversity of solutions are needed for the vast range of environments and social circumstances of global grasslands.

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Ninety-three giant Queensland grouper, Epinephelus lanceolatus (Bloch), were found dead in Queensland, Australia, from 2007 to 2011. Most dead fish occurred in northern Queensland, with a peak of mortalities in Cairns in June 2008. In 2009, sick wild fish including giant sea catfish, Arius thalassinus (Ruppell), and javelin grunter, Pomadasys kaakan (Cuvier), also occurred in Cairns. In 2009 and 2010, two disease epizootics involving wild stingrays occurred at Sea World marine aquarium. Necropsy, histopathology, bacteriology and PCR determined that the cause of deaths of 12 giant Queensland grouper, three wild fish, six estuary rays, Dasyatis fluviorum (Ogilby), one mangrove whipray, Himantura granulata (Macleay), and one eastern shovelnose ray, Aptychotrema rostrata (Shaw), was Streptococcus agalactiae septicaemia. Biochemical testing of 34 S.agalactiae isolates from giant Queensland grouper, wild fish and stingrays showed all had identical biochemical profiles. The 16S rRNA gene sequences of isolates confirmed all isolates were S.agalactiae; genotyping of selected S.agalactiae isolates showed the isolates from giant Queensland grouper were serotype Ib, whereas isolates from wild fish and stingrays closely resembled serotype II. This is the first report of S.agalactiae from wild giant Queensland grouper and other wild tropical fish and stingray species in Queensland, Australia.

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One major benefit of land application of biosolids is to supply nitrogen (N) for agricultural crops, and understanding mineralisation processes is the key for better N-management strategies. Field studies were conducted to investigate the process of mineralisation of three biosolids products (aerobic, anaerobic, and thermally dried biosolids) incorporated into four different soils at rates of 7-90 wet t/ha in subtropical Queensland. Two of these studies also examined mineralisation rates of commonly used organic amendments (composts, manures, and sugarcane mill muds). Organic N in all biosolids products mineralised very rapidly under ambient conditions in subtropical Queensland, with rates much faster than from other common amendments. Biosolids mineralisation rates ranged from 30 to 80% of applied N during periods ranging from 3.5 to 18 months after biosolids application; these rates were much higher than those suggested in the biosolids land application guidelines established by the NSW EPA (15% for anaerobic and 25% for aerobic biosolids). There was no consistently significant difference in mineralisation rate between aerobic and anaerobic biosolids in our studies. When applied at similar rates of N addition, other organic amendments supplied much less N to the soil mineral N and plant N pools during the crop season. A significant proportion of the applied biosolids total N (up to 60%) was unaccounted for at the end of the observation period. High rates of N addition in calculated Nitrogen Limited Biosolids Application Rates (850-1250 kg N/ha) resulted in excessive accumulation of mineral N in the soil profile, which increases the environmental risks due to leaching, runoff, or gaseous N losses. Moreover, the rapid mineralisation of the biosolids organic N in these subtropical environments suggests that biosolids should be applied at lower rates than in temperate areas, and that care must be taken with the timing to maximise plant uptake and minimise possible leaching, runoff, or denitrification losses of mineralised N.

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Marine species generally have large population sizes, continuous distributions and high dispersal capacity. Despite this, they are often subdivided into separate populations, which are the basic units of fisheries management. For example, populations of some fisheries species across the deep water of the Timor Trench are genetically different, inferring minimal movement and interbreeding. When connectivity is higher than the Timor Trench example, but not so high that the populations become one, connectivity between populations is crinkled. Crinkled connectivity occurs when migration is above the threshold required to link populations genetically, but below the threshold for demographic links. In future, genetic estimates of connectivity over crinkled links could be uniquely combined with other data, such as estimates of population size and tagging and tracking data, to quantify demographic connectedness between these types of populations. Elasmobranch species may be ideal targets for this research because connectivity between populations is more likely to be crinkled than for finfish species. Fisheries stock-assessment models could be strengthened with estimates of connectivity to improve the strategic and sustainable harvesting of biological resources.

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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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Computer simulation modelling is an essential aid in building an integrated understanding of how different factors interact to affect the evolutionary and population dynamics of herbicide resistance, and thus in helping to predict and manage how agricultural systems will be affected. In this review, we first discuss why computer simulation modelling is such an important tool and framework for dealing with herbicide resistance. We then explain what questions related to herbicide resistance have been addressed to date using simulation modelling, and discuss the modelling approaches that have been used, focusing first on the earlier, more general approaches, and then on some newer, more innovative approaches. We then consider how these approaches could be further developed in the future, by drawing on modelling techniques that are already employed in other areas, such as individual-based and spatially explicit modelling approaches, as well as the possibility of better representing genetics, competition and economics, and finally the questions and issues of importance to herbicide resistance research and management that could be addressed using these new approaches are discussed. We conclude that it is necessary to proceed with caution when increasing the complexity of models by adding new details, but, with appropriate care, more detailed models will make it possible to integrate more current knowledge in order better to understand, predict and ultimately manage the evolution of herbicide resistance. © 2014 Society of Chemical Industry.

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Cotton bunchy top virus (CBTV) and the related Cotton leafroll dwarf virus (CLRDV) have caused sporadic disease outbreaks in most cotton regions of the world. Until recently, little was known about the diversity of CBTV or its natural host range. Seven natural field hosts and one experimental host of CBTV have now been identified. These include cotton, Malva parviflora (Marshmallow weed), Abutilon theophrasti (Velvetleaf), Anoda cristata (Spurred anoda), Hibiscus sabdariffa (Rosella), Sida rhombifolia (Paddy’s lucerne), Chamaesyce hirta (Asthma plant) and Gossypium australe. These are currently the only eight known hosts of CBTV. However the virus may have a wider host range than originally thought and include further non-Malvaceae species like asthma plant (family Euphorbiaceae). There are two distinct strains of CBTV in Australia, -A and -B, which have been detected in cotton from numerous locations across almost all growing regions. From 105 samples of cotton that have been positive for CBTV, 6 were infections of strain A only, 60 were strain B only and 64 were a mixed infection of strains A and B. These results indicate the symptoms of cotton bunchy top disease are closely associated with the presence of strain CBTV-B. A diagnostic assay for Cotton leafroll dwarf virus (CLRDV - cotton blue disease) is being developed and applied successfully for the detection of CLRDV samples from Brazil and Thailand. This is the first confirmation of CLRDV from SE-Asia, which may pose an increased biosecurity threat to the Australian industry.