7 resultados para agent-based model

em eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry


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The eucalypt leaf beetle, Paropsis atomaria Olivier, is an increasingly important pest of eucalypt plantations in subtropical eastern Australia. A process-based model, ParopSys, was developed using DYMEXTM and was found to accurately predict the beetle populations. Climate change scenarios within the latest Australian climate model forecast range were run in ParopSys at three locations to predict changes in beetle performance. Relative population peaks of early generations did not change but shifted to earlier in the season. Temperature increases of 1.0 to 1.5 ºC or greater predicted an extra generation of adults at Gympie and Canberra, but not for Lowmead, where increased populations of late season adults were observed under all scenarios. Furthermore, an additional generation of late-larval stages was predicted at temperature increases of greater than 1.0 ºC at Lowmead. Management strategies to address these changes are discussed, as are requirements to improve the predictive capacity of the model.

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In this article, we describe and compare two individual-based models constructed to investigate how genetic factors influence the development of phosphine resistance in lesser grain borer (R. dominica). One model is based on the simplifying assumption that resistance is conferred by alleles at a single locus, while the other is based on the more realistic assumption that resistance is conferred by alleles at two separate loci. We simulated the population dynamic of R. dominica in the absence of phosphine fumigation, and under high and low dose phosphine treatments, and found important differences between the predictions of the two models in all three cases. In the absence of fumigation, starting from the same initial frequencies of genotypes, the two models tended to different stable frequencies, although both reached Hardy-Weinberg equilibrium. The one-locus model exaggerated the equilibrium proportion of strongly resistant beetles by 3.6 times, compared to the aggregated predictions of the two-locus model. Under a low dose treatment the one-locus model overestimated the proportion of strongly resistant individuals within the population and underestimated the total population numbers compared to the two-locus model. These results show the importance of basing resistance evolution models on realistic genetics and that using oversimplified one-locus models to develop pest control strategies runs the risk of not correctly identifying tactics to minimise the incidence of pest infestation.

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Prickly acacia (Vachellia nilotica subsp. indica), a native multipurpose tree in India, is a weed of National significance, and a target for biological control in Australia. Based on plant genetic and climatic similarities, native range surveys for identifying potential biological control agents for prickly acacia were conducted in India during 2008-2011. In the survey leaf-feeding geometrid, Isturgia disputaria Guenee (syn. Tephrina pulinda), widespread in Tamil Nadu and Karnataka States, was prioritized as a potential biological control agent based on field host range, damage potential and no choice test on non target plant species. Though the field host range study exhibited that V. nilotica ssp. indica and V. nilotica ssp. tomentosa were the primary hosts for successful development of the insect, I. disputaria, replicated no - choice larval feeding and development tests conducted on cut foliage and live plants of nine non-target acacia test plant species in India revealed the larval feeding and development on three of the nine non-target acacia species, V. tortilis, V. planiferons and V. leucophloea in addition to the V. nilotica ssp. indica and V. nilotica ssp. tomentosa. However, the proportion of larvae developing into adults was higher on V. nilotica subsp. indica and V. nilotica subsp. tomentosa, with 90% and 80% of the larvae completing development, respectively. In contrast, the larval mortality was higher on V. tortilis (70%), V. leucophloea (90%) and V. planiferons (70%). The no-choice test results support the earlier host specificity test results of I. disputaria from Pakistan, Kenya and under quarantine in Australia. Contrasting results between field host range and host use pattern under no-choice conditions are discussed.

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The development of innovative methods of stock assessment is a priority for State and Commonwealth fisheries agencies. It is driven by the need to facilitate sustainable exploitation of naturally occurring fisheries resources for the current and future economic, social and environmental well being of Australia. This project was initiated in this context and took advantage of considerable recent achievements in genomics that are shaping our comprehension of the DNA of humans and animals. The basic idea behind this project was that genetic estimates of effective population size, which can be made from empirical measurements of genetic drift, were equivalent to estimates of the successful number of spawners that is an important parameter in process of fisheries stock assessment. The broad objectives of this study were to 1. Critically evaluate a variety of mathematical methods of calculating effective spawner numbers (Ne) by a. conducting comprehensive computer simulations, and by b. analysis of empirical data collected from the Moreton Bay population of tiger prawns (P. esculentus). 2. Lay the groundwork for the application of the technology in the northern prawn fishery (NPF). 3. Produce software for the calculation of Ne, and to make it widely available. The project pulled together a range of mathematical models for estimating current effective population size from diverse sources. Some of them had been recently implemented with the latest statistical methods (eg. Bayesian framework Berthier, Beaumont et al. 2002), while others had lower profiles (eg. Pudovkin, Zaykin et al. 1996; Rousset and Raymond 1995). Computer code and later software with a user-friendly interface (NeEstimator) was produced to implement the methods. This was used as a basis for simulation experiments to evaluate the performance of the methods with an individual-based model of a prawn population. Following the guidelines suggested by computer simulations, the tiger prawn population in Moreton Bay (south-east Queensland) was sampled for genetic analysis with eight microsatellite loci in three successive spring spawning seasons in 2001, 2002 and 2003. As predicted by the simulations, the estimates had non-infinite upper confidence limits, which is a major achievement for the application of the method to a naturally-occurring, short generation, highly fecund invertebrate species. The genetic estimate of the number of successful spawners was around 1000 individuals in two consecutive years. This contrasts with about 500,000 prawns participating in spawning. It is not possible to distinguish successful from non-successful spawners so we suggest a high level of protection for the entire spawning population. We interpret the difference in numbers between successful and non-successful spawners as a large variation in the number of offspring per family that survive – a large number of families have no surviving offspring, while a few have a large number. We explored various ways in which Ne can be useful in fisheries management. It can be a surrogate for spawning population size, assuming the ratio between Ne and spawning population size has been previously calculated for that species. Alternatively, it can be a surrogate for recruitment, again assuming that the ratio between Ne and recruitment has been previously determined. The number of species that can be analysed in this way, however, is likely to be small because of species-specific life history requirements that need to be satisfied for accuracy. The most universal approach would be to integrate Ne with spawning stock-recruitment models, so that these models are more accurate when applied to fisheries populations. A pathway to achieve this was established in this project, which we predict will significantly improve fisheries sustainability in the future. Regardless of the success of integrating Ne into spawning stock-recruitment models, Ne could be used as a fisheries monitoring tool. Declines in spawning stock size or increases in natural or harvest mortality would be reflected by a decline in Ne. This would be good for data-poor fisheries and provides fishery independent information, however, we suggest a species-by-species approach. Some species may be too numerous or experiencing too much migration for the method to work. During the project two important theoretical studies of the simultaneous estimation of effective population size and migration were published (Vitalis and Couvet 2001b; Wang and Whitlock 2003). These methods, combined with collection of preliminary genetic data from the tiger prawn population in southern Gulf of Carpentaria population and a computer simulation study that evaluated the effect of differing reproductive strategies on genetic estimates, suggest that this technology could make an important contribution to the stock assessment process in the northern prawn fishery (NPF). Advances in the genomics world are rapid and already a cheaper, more reliable substitute for microsatellite loci in this technology is available. Digital data from single nucleotide polymorphisms (SNPs) are likely to super cede ‘analogue’ microsatellite data, making it cheaper and easier to apply the method to species with large population sizes.

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Paropsis atomaria is a recently emerged pest of eucalypt plantations in subtropical Australia. Its broad host range of at least 20 eucalypt species and wide geographical distribution provides it the potential to become a serious forestry pest both within Australia and, if accidentally introduced, overseas. Although populations of P. atomaria are genetically similar throughout its range, population dynamics differ between regions. Here, we determine temperature-dependent developmental requirements using beetles sourced from temperate and subtropical zones by calculating lower temperature thresholds, temperature-induced mortality, and day-degree requirements. We combine these data with field mortality estimates of immature life stages to produce a cohort-based model, ParopSys, using DYMEX™ that accurately predicts the timing, duration, and relative abundance of life stages in the field and number of generations in a spring–autumn (September–May) field season. Voltinism was identified as a seasonally plastic trait dependent upon environmental conditions, with two generations observed and predicted in the Australian Capital Territory, and up to four in Queensland. Lower temperature thresholds for development ranged between 4 and 9 °C, and overall development rates did not differ according to beetle origin. Total immature development time (egg–adult) was approximately 769.2 ± S.E. 127.8 DD above a lower temperature threshold of 6.4 ± S.E. 2.6 °C. ParopSys provides a basic tool enabling forest managers to use the number of generations and seasonal fluctuations in abundance of damaging life stages to estimate the pest risk of P. atomaria prior to plantation establishment, and predict the occurrence and duration of damaging life stages in the field. Additionally, by using local climatic data the pest potential of P. atomaria can be estimated to predict the risk of it establishing if accidentally introduced overseas. Improvements to ParopSys’ capability and complexity can be made as more biological data become available.

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Miconia calvescens (Melastomataceae) is a serious invader in the tropical Pacific, including the Hawaiian and Tahitian Islands, and currently poses a major threat to native biodiversity in the Wet Tropics of Australia. The species is fleshy-fruited, small-seeded and shade tolerant, and thus has the potential to be dispersed widely and recruit in relatively intact rainforest habitats, displacing native species. Understanding and predicting the rate of spread is critical for the design and implementation of effective management actions. We used an individual-based model incorporating a dispersal function derived from dispersal curves for similar berry-fruited native species, and life-history parameters of fecundity and mortality to predict the spatial structure of a Miconia population after a 30 year time period. We compared the modelled population spatial structure to that of an actual infestation in the rainforests of north Queensland. Our goal was to assess how well the model predicts actual dispersion and to identify potential barriers and conduits to seed movement and seedling establishment. The model overpredicts overall population size and the spatial extent of the actual infestation, predicting individuals to occur at a maximum 1,750 m from the source compared with the maximum distance of any detected individual in the actual infestation of 1,191 m. We identify several characteristic features of managed invasive populations that make comparisons between modelled outcomes and actual infestations difficult. Our results suggest that the model’s ability to predict both spatial structure and spread of the population will be improved by incorporating a spatially explicit element, with dispersal and recruitment probabilities that reflect the relative suitability of different parts of the landscape for these processes.

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New efforts at biological control of Miconia calvescens (Melastomataceae) is a serious invader in the tropical Pacific, including the Hawaiian and Tahitian Islands, and currently poses a major threat to native biodiversity in the Wet Tropics of Australia. The species is fleshy-fruited, small-seeded and shade tolerant, and thus has the potential to be dispersed widely and recruit in relatively intact rainforest habitats, displacing native species. Understanding and predicting the rate of spread is critical for the design and implementation of effective management actions. We used an individual-based model incorporating a dispersal function derived from dispersal curves for similar berry-fruited native species, and life-history parameters of fecundity and mortality to predict the spatial structure of a Miconia population after a 30 year time period. We compared the modelled population spatial structure to that of an actual infestation in the rainforests of north Queensland. Our goal was to assess how well the model predicts actual dispersion and to identify potential barriers and conduits to seed movement and seedling establishment. The model overpredicts overall population size and the spatial extent of the actual infestation, predicting individuals to occur at a maximum 1,750 m from the source compared with the maximum distance of any detected individual in the actual infestation of 1,191 m. We identify several characteristic features of managed invasive populations that make comparisons between modelled outcomes and actual infestations difficult. Our results suggest that the model’s ability to predict both spatial structure and spread of the population will be improved by incorporating a spatially explicit element, with dispersal and recruitment probabilities that reflect the relative suitability of different parts of the landscape for these processes. Mikania micrantha H.B.K. (Asteraceae) in Papua New Guinea and Fiji.