55 resultados para mathamatical modelling
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This project aims to use simulatiion modelling to improve our understanding of the genetics and physiology of complex traits with a view to increasing the rate of genetic gain in plant breeding programs.
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Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.
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Hierarchical Bayesian models can assimilate surveillance and ecological information to estimate both invasion extent and model parameters for invading plant pests spread by people. A reliability analysis framework that can accommodate multiple dispersal modes is developed to estimate human-mediated dispersal parameters for an invasive species. Uncertainty in the observation process is modelled by accounting for local natural spread and population growth within spatial units. Broad scale incursion dynamics are based on a mechanistic gravity model with a Weibull distribution modification to incorporate a local pest build-up phase. The model uses Markov chain Monte Carlo simulations to infer the probability of colonisation times for discrete spatial units and to estimate connectivity parameters between these units. The hierarchical Bayesian model with observational and ecological components is applied to a surveillance dataset for a spiralling whitefly (Aleurodicus dispersus) invasion in Queensland, Australia. The model structure provides a useful application that draws on surveillance data and ecological knowledge that can be used to manage the risk of pest movement.
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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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The Great Barrier Reef (GBR) is the largest reef system in the world; it covers an area of approximately 2,225,000 km² in the northern Queensland continental shelf. There are approximately 750 reefs that exist within 40 km of the Queensland coast. Recent research has identified that poor water quality is having negative impacts on the GBR (Haynes et al. 2007). The Fitzroy Basin covers 143,000 km² and is the largest catchment draining into the GBR as well as being one of the largest catchments in Australia (Karfs et al. 2009). The Burdekin Catchment is the second largest catchment entering into the GBR and covers 133,432 km².The prime determinant for the changes in water quality entering into the GBR have been attributed to grazing, with beef production the largest single land use industry comprising 90% of the land area (Karfs et al. 2009). Extensive beef production contributes over $1 billion dollars to the national economy annually and employs over 9000 people, many in rural communities (Gordon 2007). ‘Economic modelling of grazing systems in the Fitzroy and Burdekin catchments’ was a joint project with the Fitzroy Basin Association and the Queensland Department of Employment Economic Development and Innovation. The project was formed under the federally funded Caring For Our Country and the Reef Rescue programs. The project objectives were as follows; * Quantifying the costs of over-utilising available pasture and the resulting sediment leaving a representative farm for four of the major land systems in the Burdekin or Fitzroy catchments and identifying economically optimal pasture utilisation rates * Estimating the cost of reducing pasture utilisation rates below the determined optimal * Using this information, guide the selection of appropriate tools to achieve reduced utilisation rates e.g. extension process versus incentive payments or a combination of both * Model the biophysical and economic impacts of altering grazing systems to restore land condition e.g. from C condition to B condition for four land systems in the Burdekin or Fitzroy catchments.
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Crop models for herbaceous ornamental species typically include functions for temperature and photoperiod responses, but very few incorporate vernalization, which is a requirement of many traditional crops. This study investigated the development of floriculture crop models, which describe temperature responses, plus photoperiod or vernalization requirements, using Australian native ephemerals Brunonia australis and Calandrinia sp. A novel approach involved the use of a field crop modelling tool, DEVEL2. This optimization program estimates the parameters of selected functions within the development rate models using an iterative process that minimizes sum of squares residual between estimated and observed days for the phenological event. Parameter profiling and jack-knifing are included in DEVEL2 to remove bias from parameter estimates and introduce rigour into the parameter selection process. Development rate of B. australis from planting to first visible floral bud (VFB) was predicted using a multiplicative approach with a curvilinear function to describe temperature responses and a broken linear function to explain photoperiod responses. A similar model was used to describe the development rate of Calandrinia sp., except the photoperiod function was replaced with an exponential vernalization function, which explained a facultative cold requirement and included a coefficient for determining the vernalization ceiling temperature. Temperature was the main environmental factor influencing development rate for VFB to anthesis of both species and was predicted using a linear model. The phenology models for B. australis and Calandrinia sp. described development rate from planting to VFB and from VFB to anthesis in response to temperature and photoperiod or vernalization and may assist modelling efforts of other herbaceous ornamental plants. In addition to crop management, the vernalization function could be used to identify plant communities most at risk from predicted increases in temperature due to global warming.
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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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Increasing resistance to phosphine (PH 3) in insect pests, including lesser grain borer (Rhyzopertha dominica) has become a critical issue, and development of effective and sustainable strategies to manage resistance is crucial. In practice, the same grain store may be fumigated multiple times, but usually for the same exposure period and concentration. Simulating a single fumigation allows us to look more closely at the effects of this standard treatment.We used an individual-based, two-locus model to investigate three key questions about the use of phosphine fumigant in relation to the development of PH 3 resistance. First, which is more effective for insect control; long exposure time with a low concentration or short exposure period with a high concentration? Our results showed that extending exposure duration is a much more efficient control tactic than increasing the phosphine concentration. Second, how long should the fumigation period be extended to deal with higher frequencies of resistant insects in the grain? Our results indicated that if the original frequency of resistant insects is increased n times, then the fumigation needs to be extended, at most, n days to achieve the same level of insect control. The third question is how does the presence of varying numbers of insects inside grain storages impact the effectiveness of phosphine fumigation? We found that, for a given fumigation, as the initial population number was increased, the final survival of resistant insects increased proportionally. To control initial populations of insects that were n times larger, it was necessary to increase the fumigation time by about n days. Our results indicate that, in a 2-gene mediated resistance where dilution of resistance gene frequencies through immigration of susceptibles has greater effect, extending fumigation times to reduce survival of homozygous resistant insects will have a significant impact on delaying the development of resistance. © 2012 Elsevier Ltd.
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Targets for improvements in water quality entering the Great Barrier Reef (GBR) have been set through the Reef Water Quality Protection Plan (Reef Plan). To measure and report on progress towards the targets set a program has been established that combines monitoring and modelling at paddock through to catchment and reef scales; the Paddock to Reef Integrated Monitoring, Modelling and Reporting Program (Paddock to Reef Program). This program aims to provide evidence of links between land management activities, water quality and reef health. Five lines of evidence are used: the effectiveness of management practices to improve water quality; the prevalence of management practice adoption and change in catchment indicators; long-term monitoring of catchment water quality; paddock & catchment modelling to provide a relative assessment of progress towards meeting targets; and finally marine monitoring of GBR water quality and reef ecosystem health. This paper outlines the first four lines of evidence. (C) 2011 Elsevier Ltd. All rights reserved.
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Glyphosate resistance is a rapidly developing threat to profitability in Australian cotton farming. Resistance causes an immediate reduction in the effectiveness of in-crop weed control in glyphosate-resistant transgenic cotton and summer fallows. Although strategies for delaying glyphosate resistance and those for managing resistant populations are qualitatively similar, the longer resistance can be delayed, the longer cotton growers will have choice over which tactics to apply and when to apply them. Effective strategies to avoid, delay, and manage resistance are thus of substantial value. We used a model of glyphosate resistance dynamics to perform simulations of resistance evolution in Sonchus oleraceus (common sowthistle) and Echinochloa colona (awnless barnyard grass) under a range of resistance prevention, delaying, and management strategies. From these simulations, we identified several elements that could contribute to effective glyphosate resistance prevention and management strategies. (i) Controlling glyphosate survivors is the most robust approach to delaying or preventing resistance. High-efficacy, high-frequency survivor control almost doubled the useful lifespan of glyphosate from 13 to 25 years even with glyphosate alone used in summer fallows. (ii) Two non-glyphosate tactics in-crop plus two in-summer fallows is the minimum intervention required for long-term delays in resistance evolution. (iii) Pre-emergence herbicides are important, but should be backed up with non-glyphosate knockdowns and strategic tillage; replacing a late-season, pre-emergence herbicide with inter-row tillage was predicted to delay glyphosate resistance by 4 years in awnless barnyard grass. (iv) Weed species' ecological characteristics, particularly seed bank dynamics, have an impact on the effectiveness of resistance strategies; S. oleraceus, because of its propensity to emerge year-round, was less exposed to selection with glyphosate than E. colona, resulting in an extra 5 years of glyphosate usefulness (18 v. 13 years) even in the most rapid cases of resistance evolution. Delaying tactics are thus available that can provide some or many years of continued glyphosate efficacy. If glyphosate-resistant cotton cropping is to remain profitable in Australian farming systems in the long-term, however, growers must adapt to the probability that they will have to deal with summer weeds that are no longer susceptible to glyphosate. Robust resistance management systems will need to include a diversity of weed control options, used appropriately.
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Concepts of agricultural sustainability and possible roles of simulation modelling for characterising sustainability were explored by conducting, and reflecting on, a sustainability assessment of rain-fed wheat-based systems in the Middle East and North Africa region. We designed a goal-oriented, model-based framework using the cropping systems model Agricultural Production Systems sIMulator (APSIM). For the assessment, valid (rather than true or false) sustainability goals and indicators were identified for the target system. System-specific vagueness was depicted in sustainability polygons-a system property derived from highly quantitative data-and denoted using descriptive quantifiers. Diagnostic evaluations of alternative tillage practices demonstrated the utility of the framework to quantify key bio-physical and chemical constraints to sustainability. Here, we argue that sustainability is a vague, emergent system property of often wicked complexity that arises out of more fundamental elements and processes. A 'wicked concept of sustainability' acknowledges the breadth of the human experience of sustainability, which cannot be internalised in a model. To achieve socially desirable sustainability goals, our model-based approach can inform reflective evaluation processes that connect with the needs and values of agricultural decision-makers. Hence, it can help to frame meaningful discussions, from which actions might emerge.
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Climate change and on-going water policy reforms will likely contribute to on-farm and regional structural adjustment in Australia. This paper gathers empirical evidence of farm-level structural adjustments and integrates these with a regional equilibrium model to investigate sectoral and regional impacts of climate change and recent water use policy on rice industry. We find strong evidence of adjustments to the farming system, enabled by existing diversity in on-farm production. A further loss of water with additional pressures to adopt less intensive and larger-scale farming, will however reduce the net number of farm businesses, which may affect regional rice production. The results from a regional CGE model show impacts on the regional economy over and above the direct cost of the environmental water, although a net reduction in real economic output and real income is partially offset by gains in rest of the Australia through the reallocation or resources. There is some interest within the industry and from potential new corporate entrants in the relocation of some rice production to the north. However, strong government support would be crucial to implement such relocation.
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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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* Plant response to drought is complex, so that traits adapted to a specific drought type can confer disadvantage in another drought type. Understanding which type(s) of drought to target is of prime importance for crop improvement. * Modelling was used to quantify seasonal drought patterns for a check variety across the Australian wheatbelt, using 123 yr of weather data for representative locations and managements. Two other genotypes were used to simulate the impact of maturity on drought pattern. * Four major environment types summarized the variability in drought pattern over time and space. Severe stress beginning before flowering was common (44% of occurrences), with (24%) or without (20%) relief during grain filling. High variability occurred from year to year, differing with geographical region. With few exceptions, all four environment types occurred in most seasons, for each location, management system and genotype. * Applications of such environment characterization are proposed to assist breeding and research to focus on germplasm, traits and genes of interest for target environments. The method was applied at a continental scale to highly variable environments and could be extended to other crops, to other drought-prone regions around the world, and to quantify potential changes in drought patterns under future climates.