16 resultados para Robust estimates

em eResearch Archive - Queensland Department of Agriculture


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In this study, 120–144 commercial varieties and breeding lines were assessed for grain size attributes including plump grain (>2.8 mm) and retention (>2.5 mm+>2.8 mm). Grain samples were produced from replicated trials at 25 sites across four years. Climatic conditions varied between years as well as between sites. Several of the trial sites were irrigated while the remaining were produced under dryland conditions. A number of the dryland sites suffered severe drought stress. The grain size data was analysed for genetic (G), environmental (E) and genotype by environment (G×E) interactions. All analyses included maturity as a covariate. The genetic effect on grain size was greater than environmental or maturity effects despite some sites suffering terminal moisture stress. The model was used to calculate heritability values for each site used in the study. These values ranged from 89 to 98% for plump grain and 88 to 96% for retention. The results demonstrated that removing the sources of non-heritable variation, such as maturity and field effects, can improve genetic estimates of the retention and plump grain fractions. By partitioning all variance components, and thereby having more robust estimates of genetic differences, plant breeders can have greater confidence in selecting barley genotypes which maintain large, stable grain size across a range of environments.

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AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.

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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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Odour emission rates were measured for seven different anaerobic ponds treating piggery wastes at six to nine discrete locations across the surface of each pond on each sampling occasion over a thirteen month period. Significant variability in emission rates were observed for each pond. Measurement of a number of water quality variables in pond liquor samples collected at the same time and from the same locations as the odour samples indicated that the composition of the pond liquor was also variable. The results indicated that spatial variability was a real phenomenon and could have a significant impact on odour assessment practices. Considerably more odour samples would be required to characterise pond emissions than currently recommended by most practitioners, or regulatory agencies.

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The tropical abalone Haliotis asinina is a wild-caught and cultured species throughout the Indo-Pacific as well as being an emerging model species for the study of haliotids. H. asinina has the fastest recorded natural growth rate of any abalone and reaches sexual maturity within one year. As such, it is a suitable abalone species for selective breeding for commercially important traits such as rapid growth. Estimating the amount of variation in size that is attributable to heritable genetic differences can assist the development of such a selective breeding program. Here we estimated heritability for growth-related traits at 12 months of age by creating a single cohort of 84 families in a full-factorial mating design consisting of 14 sires and 6 dams. Of 500 progeny sampled, 465 were successfully assigned to their parents based on shared alleles at 5 polymorphic microsatellite loci. Using an animal model, heritability estimates were 0.48 ± 0.15 for shell length, 0.38 ± 0.13 for shell width and 0.36 ± 0.13 for weight. Genetic correlations were > 0.98 between shell parameters and weight, indicating that breeding for weight gains could be successfully achieved by selecting for shell length.

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Grass (monocots) and non-grass (dicots) proportions in ruminant diets are important nutritionally because the non-grasses are usually higher in nutritive value, particularly protein, than the grasses, especially in tropical pastures. For ruminants grazing tropical pastures where the grasses are C-4 species and most non-grasses are C-3 species, the ratio of C-13/C-12 in diet and faeces, measured as delta C-13 parts per thousand, is proportional to dietary non-grass%. This paper describes the development of a faecal near infrared (NIR) spectroscopy calibration equation for predicting faecal delta C-13 from which dietary grass and non-grass proportions can be calculated. Calibration development used cattle faeces derived from diets containing only C-3 non-grass and C-4 grass components, and a series of expansion and validation steps was employed to develop robustness and predictive reliability. The final calibration equation contained 1637 samples and faecal delta C-13 range (parts per thousand) of [12.27]-[27.65]. Calibration statistics were: standard error of calibration (SEC) of 0.78, standard error of cross-validation (SECV) of 0.80, standard deviation (SD) of reference values of 3.11 and R-2 of 0.94. Validation statistics for the final calibration equation applied to 60 samples were: standard error of prediction (SEP) of 0.87, bias of -0.15, R-2 of 0.92 and RPD of 3.16. The calibration equation was also tested on faeces from diets containing C-4 non-grass species or temperate C-3 grass species. Faecal delta C-13 predictions indicated that the spectral basis of the calibration was not related to C-13/C-12 ratios per se but to consistent differences between grasses and non-grasses in chemical composition and that the differences were modified by photosynthetic pathway. Thus, although the calibration equation could not be used to make valid faecal delta C-13 predictions when the diet contained either C-3 grass or C-4 non-grass, it could be used to make useful estimates of dietary non-grass proportions. It could also be ut :sed to make useful estimates of non-grass in mixed C-3 grass/non-grass diets by applying a modified formula to calculate non-grass from predicted faecal delta C-13. The development of a robust faecal-NIR calibration equation for estimating non-grass proportions in the diets of grazing cattle demonstrated a novel and useful application of NIR spectroscopy in agriculture.

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Despite international protection of white sharks (Carcharodon carcharias), important conservation parameters such as abundance, population structure and genetic diversity are largely unknown. The tissue of 97 predominately juvenile white sharks sampled from spatially distant eastern and southwestern Australian coastlines was sequenced for the mitochondrial DNA (mtDNA) control region and genotyped with six nuclear-encoded microsatellite loci. MtDNA population structure was found between the eastern and southwestern coasts (FST = 0.142, p < 0.001), implying female natal philopatry. This concords with recent satellite and acoustic tracking findings which suggest the sustained presence of discrete east coast nursery areas. Furthermore, population subdivision was found between the same regions with biparentally inherited microsatellite markers (FST = 0.009, p <0.05), suggesting that males may also exhibit some degree of reproductive philopatry. Five sharks captured along the east coast had mtDNA haplotypes that resembled western Indian Ocean sharks more closely than Australian/New Zealand sharks, suggesting that transoceanic dispersal or migration resulting in breeding may occur sporadically. Our most robust estimate of contemporary genetic effective population size was low and below the threshold at which adaptive potential may be lost. For a variety of reasons, these contemporary estimates were at least one, possibly two orders of magnitude below our historical effective size estimates. Further population decline could expose these genetically isolated populations to detrimental genetic effects. Regional Australian white shark conservation management units should be implemented until genetic population structure, size and diversity can be investigated in more detail. Reference: Blower, D. C., Pandolfi, J. M., Gomez-Cabrera, M. del C., Bruce, B. D. & Ovenden, J. R. (In press - April 2012). Population genetics of Australian white sharks reveals fine-scale spatial structure, transoceanic dispersal events and low effective population sizes. Marine Ecology Progress Series.

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Reliable estimates of forest productivity are essential for improved predictions of timber yields for the private native spotted gum resource in southern Qld and northern NSW. The aim of this research was to estimate the potential productivity of native spotted gum forests on private land by making use of available inventory data collated from Qld and northern NSW for spotted gum forest on Crown land (i.e. state forests). We measured a range of site-related factors to determine their relative importance in predicting productivity of spotted gum forest. While measures such as stand height and height-diameter relationships are known to be useful predictors of productivity, we aimed to determine productivity for a site where this information was not available. Through estimation of stand growth rates we developed a spotted gum productivity assessment tool (SPAT) for use by landholders and extension officers. We aimed to develop a tool to allow private landholders to see the benefits of maintaining their timber resource. This paper summarises the information used to develop the SPAT with a particular focus on forest growth relationships.

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This report provides quantitative information on the effects of turtle excluder devices (TEDs) and bycatch reduction devices (BRDs) on the catch rates of bycatch, prawns, scallops and byproduct species, such as Moreton Bay bugs and Balmain bugs, in Queensland’s major trawl fishing sectors. It also provides biological information on, and management advice for several species referred to in the Fishery Management Plan as the permitted species. Several recommendations are included for reducing bycatch in the trawl fishery and for sustaining stocks of the permitted species.

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Remote detection of management-related trend in the presence of inter-annual climatic variability in the rangelands is difficult. Minimally disturbed reference areas provide a useful guide, but suitable benchmarks are usually difficult to identify. We describe a method that uses a unique conceptual framework to identify reference areas from multitemporal sequences of ground cover derived from Landsat TM and ETM+ imagery. The method does not require ground-based reference sites nor GIS layers about management. We calculate a minimum ground cover image across all years to identify locations of most persistent ground cover in years of lowest rainfall. We then use a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels. This difference estimates ground-cover change between successive below-average rainfall years, which provides a seasonally interpreted measure of management effects. We examine the approach's sensitivity to window size and to cover-index percentiles used to define persistence. The method successfully detected management-related change in ground cover in Queensland tropical savanna woodlands in two case studies: (1) a grazing trial where heavy stocking resulted in substantial decline in ground cover in small paddocks, and (2) commercial paddocks where wet-season spelling (destocking) resulted in increased ground cover. At a larger scale, there was broad agreement between our analysis of ground-cover change and ground-based land condition change for commercial beef properties with different a priori ratings of initial condition, but there was also some disagreement where changing condition reflected pasture composition rather than ground cover. We conclude that the method is suitably robust to analyse grazing effects on ground cover across the 1.3 x 10(6) km(2) of Queensland's rangelands. Crown Copyright (c) 2012 Published by Elsevier Inc. All rights reserved.

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Commercial environments may receive only a fraction of expected genetic gains for growth rate as predicted from the selection environment. This fraction is result of undesirable genotype-by-environment interactions (GxE) and measured by the genetic correlation (rg) of growth between environments. Rapid estimates of genetic correlation achieved in one generation are notoriously difficult to estimate with precision. A new design is proposed where genetic correlations can be estimated by utilising artificial mating from cryopreserved semen and unfertilised eggs stripped from a single female. We compare a traditional phenotype analysis of growth to a threshold model where only the largest fish are genotyped for sire identification. The threshold model was robust to differences in family mortality differing up to 30%. The design is unique as it negates potential re-ranking of families caused by an interaction between common maternal environmental effects and growing environment. The design is suitable for rapid assessment of GxE over one generation with a true 0.70 genetic correlation yielding standard errors as low as 0.07. Different design scenarios were tested for bias and accuracy with a range of heritability values, number of half-sib families created, number of progeny within each full-sib family, number of fish genotyped, number of fish stocked, differing family survival rates and at various simulated genetic correlation levels.

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Despite international protection of white sharks Carcharodon carcharias, important conservation parameters such as abundance, population structure and genetic diversity are largely unknown. The tissue of 97 predominately juvenile white sharks sampled from spatially distant eastern and southwestern Australian coastlines was sequenced for the mitochondrial DNA (mtDNA) control region and genotyped with 6 nuclear-encoded microsatellite loci. MtDNA population structure was found between the eastern and southwestern coasts (F-ST = 0.142, p < 0.0001), implying female reproductive philopatry. This concurs with recent satellite and acoustic tracking findings which suggest the sustained presence of discrete east coast nursery areas. Furthermore, population subdivision was found between the same regions with biparentally inherited micro satellite markers (F-ST = 0.009, p < 0.05), suggesting that males may also exhibit some degree of reproductive philopatry; 5 sharks captured along the east coast had mtDNA haplotypes that resembled western Indian Ocean sharks more closely than Australian/New Zealand sharks, suggesting that transoceanic dispersal, or migration resulting in breeding, may occur sporadically. Our most robust estimate of contemporary genetic effective population size was low and close to thresholds at which adaptive potential may be lost. For a variety of reasons, these contemporary estimates were at least 1, possibly 2, orders of magnitude below our historical effective size estimates. Population decline could expose these genetically isolated populations to detrimental genetic effects. Regional Australian white shark conservation management units should be implemented until genetic population structure, size and diversity can be investigated in more detail.

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Key message Eucalyptus pellita demonstrated good growth and wood quality traits in this study, with young plantation grown timber being suitable for both solid and pulp wood products. All traits examined were under moderate levels of genetic control with little genotype by environment interaction when grown on two contrasting sites in Vietnam. Context Eucalyptus pellita currently has a significant role in reforestation in the tropics. Research to support expanded of use of this species is needed: particularly, research to better understand the genetic control of key traits will facilitate the development of genetically improved planting stock. Aims This study aimed to provide estimates of the heritability of diameter at breast height over bark, wood basic density, Kraft pulp yield, modulus of elasticity and microfibril angle, and the genetic correlations among these traits, and understand the importance of genotype by environment interactions in Vietnam. Methods Data for diameter and wood properties were collected from two 10-year-old, open-pollinated progeny trials of E. pellita in Vietnam that evaluated 104 families from six native range and three orchard sources. Wood properties were estimated from wood samples using near-infrared (NIR) spectroscopy. Data were analysed using mixed linear models to estimate genetic parameters (heritability, proportion of variance between seed sources and genetic correlations). Results Variation among the nine sources was small compared to additive variance. Narrow-sense heritability and genetic correlation estimates indicated that simultaneous improvements in most traits could be achieved from selection among and within families as the genetic correlations among traits were either favourable or close to zero. Type B genetic correlations approached one for all traits suggesting that genotype by environment interactions were of little importance. These results support a breeding strategy utilizing a single breeding population advanced by selecting the best individuals across all seed sources. Conclusion Both growth and wood properties have been evaluated. Multi-trait selection for growth and wood property traits will lead to more productive populations of E. pellita both with improved productivity and improved timber and pulp properties.

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Common coral trout Plectropomus leopardus is an iconic fish of the Great Barrier Reef (GBR) and is the most important fish for the commercial fishery there. Most of the catch is exported live to Asia. This stock assessment was undertaken in response to falls in catch sizes and catch rates in recent years, in order to gauge the status of the stock. It is the first stock assessment ever conducted of coral trout on the GBR, and brings together a multitude of different data sources for the first time. The GBR is very large and was divided into a regional structure based on the Bioregions defined by expert committees appointed by the Great Barrier Reef Marine Park Authority (GBRMPA) as part of the 2004 rezoning of the GBR. The regional structure consists of six Regions, from the Far Northern Region in the north to the Swains and Capricorn–Bunker Regions in the south. Regions also closely follow the boundaries between Bioregions. Two of the northern Regions are split into Subregions on the basis of potential changes in fishing intensity between the Subregions; there are nine Subregions altogether, which include four Regions that are not split. Bioregions are split into Subbioregions along the Subregion boundaries. Finally, each Subbioregion is split into a “blue” population which is open to fishing and a “green” population which is closed to fishing. The fishery is unusual in that catch rates as an indicator of abundance of coral trout are heavily influenced by tropical cyclones. After a major cyclone, catch rates fall for two to three years, and rebound after that. This effect is well correlated with the times of occurrence of cyclones, and usually occurs in the same month that the cyclone strikes. However, statistical analyses correlating catch rates with cyclone wind energy did not provide significantly different catch rate trends. Alternative indicators of cyclone strength may explain more of the catch rate decline, and future work should investigate this. Another feature of catch rates is the phenomenon of social learning in coral trout populations, whereby when a population of coral trout is fished, individuals quickly learn not to take bait. Then the catch rate falls sharply even when the population size is still high. The social learning may take place by fish directly observing their fellows being hooked, or perhaps heeding a chemo-sensory cue emitted by fish that are hooked. As part of the assessment, analysis of data from replenishment closures of Boult Reef in the Capricorn–Bunker Region (closed 1983–86) and Bramble Reef in the Townsville Subregion (closed 1992–95) estimated a strong social learning effect. A major data source for the stock assessment was the large collection of underwater visual survey (UVS) data collected by divers who counted the coral trout that they sighted. This allowed estimation of the density of coral trout in the different Bioregions (expressed as a number of fish per hectare). Combined with mapping data of all the 3000 or so reefs making up the GBR, the UVS results provided direct estimates of the population size in each Subbioregion. A regional population dynamic model was developed to account for the intricacies of coral trout population dynamics and catch rates. Because the statistical analysis of catch rates did not attribute much of the decline to tropical cyclones, (and thereby implied “real” declines in biomass), and because in contrast the UVS data indicate relatively stable population sizes, model outputs were unduly influenced by the unlikely hypothesis that falling catch rates are real. The alternative hypothesis that UVS data are closer to the mark and declining catch rates are an artefact of spurious (e.g., cyclone impact) effects is much more probable. Judging by the population size estimates provided by the UVS data, there is no biological problem with the status of coral trout stocks. The estimate of the total number of Plectropomus leopardus on blue zones on the GBR in the mid-1980s (the time of the major UVS series) was 5.34 million legal-sized fish, or about 8400 t exploitable biomass, with an 2 additional 3350 t in green zones (using the current zoning which was introduced on 1 July 2004). For the offshore regions favoured by commercial fishers, the figure was about 4.90 million legal-sized fish in blue zones, or about 7700 t exploitable biomass. There is, however, an economic problem, as indicated by relatively low catch rates and anecdotal information provided by commercial fishers. The costs of fishing the GBR by hook and line (the only method compatible with the GBR’s high conservation status) are high, and commercial fishers are unable to operate profitably when catch rates are depressed (e.g., from a tropical cyclone). The economic problem is compounded by the effect of social learning in coral trout, whereby catch rates fall rapidly if fishers keep returning to the same fishing locations. In response, commercial fishers tend to spread out over the GBR, including the Far Northern and Swains Regions which are far from port and incur higher travel costs. The economic problem provides some logic to a reduction in the TACC. Such a reduction during good times, such as when the fishery is rebounding after a major tropical cyclone, could provide a net benefit to the fishery, as it would provide a margin of stock safety and make the fishery more economically robust by providing higher catch rates during subsequent periods of depressed catches. During hard times when catch rates are low (e.g., shortly after a major tropical cyclone), a change to the TACC would have little effect as even a reduced TACC would not come close to being filled. Quota adjustments based on catch rates should take account of long-term trends in order to mitigate variability and cyclone effects in data.