10 resultados para multi project environment

em eResearch Archive - Queensland Department of Agriculture


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Modeling of cultivar x trial effects for multienvironment trials (METs) within a mixed model framework is now common practice in many plant breeding programs. The factor analytic (FA) model is a parsimonious form used to approximate the fully unstructured form of the genetic variance-covariance matrix in the model for MET data. In this study, we demonstrate that the FA model is generally the model of best fit across a range of data sets taken from early generation trials in a breeding program. In addition, we demonstrate the superiority of the FA model in achieving the most common aim of METs, namely the selection of superior genotypes. Selection is achieved using best linear unbiased predictions (BLUPs) of cultivar effects at each environment, considered either individually or as a weighted average across environments. In practice, empirical BLUPs (E-BLUPs) of cultivar effects must be used instead of BLUPs since variance parameters in the model must be estimated rather than assumed known. While the optimal properties of minimum mean squared error of prediction (MSEP) and maximum correlation between true and predicted effects possessed by BLUPs do not hold for E-BLUPs, a simulation study shows that E-BLUPs perform well in terms of MSEP.

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Pratylenchus thornei is a root-lesion nematode (RLN) of economic significance in the grain growing regions of Australia. Chickpea (Cicer arietinum) is a significant legume crop grown throughout these regions, but previous testing found most cultivars were susceptible to P. thornei. Therefore, improved resistance to P. thornei is an important objective of the Australian chickpea breeding program. A glasshouse method was developed to assess resistance of chickpea lines to P. thornei, which requires relatively low labour and resource input, and hence is suited to routine adoption within a breeding program. Using this method, good differentiation of chickpea cultivars for P. thornei resistance was measured after 12 weeks. Nematode multiplication was higher for all genotypes than the unplanted control, but of the 47 cultivars and breeding lines tested, 17 exhibited partial resistance, allowing less than two fold multiplication. The relative differences in resistance identified using this method were highly heritable (0.69) and were validated against P. thornei data from seven field trials using a multi-environment trial analysis. Genetic correlations for cultivar resistance between the glasshouse and six of the field trials were high (>0.73). These results demonstrate that resistance to P. thornei in chickpea is highly heritable and can be effectively selected in a limited set of environments. The improved resistance found in a number of the newer chickpea cultivars tested shows that some advances have been made in the P. thornei resistance of Australian chickpea cultivars, and that further targeted breeding and selection should provide incremental improvements.

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Tillage is defined here in a broad sense, including disturbance of the soil and crop residues, wheel traffic and sowing opportunities. In sub-tropical, semi-arid cropping areas in Australia, tillage systems have evolved from intensively tilled bare fallow systems, with high soil losses, to reduced and no tillage systems. In recent years, the use of controlled traffic has also increased. These conservation tillage systems are successful in reducing water erosion of soil and sediment-bound chemicals. Control of runoff of dissolved nutrients and weakly sorbed chemicals is less certain. Adoption of new practices appears to have been related to practical and economic considerations, and proved to be more profitable after a considerable period of research and development. However there are still challenges. One challenge is to ensure that systems that reduce soil erosion, which may involve greater use of chemicals, do not degrade water quality in streams. Another challenge is to ensure that systems that improve water entry do not increase drainage below the crop root zone, which would increase the risk of salinity. Better understanding of how tillage practices influence soil hydrology, runoff and erosion processes should lead to better tillage systems and enable better management of risks to water quality and soil health. Finally, the need to determine the effectiveness of in-field management practices in achieving stream water quality targets in large, multi-land use catchments will challenge our current knowledge base and the tools available.

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Blackwood (Acacia melanoxylon R. Br.) is a valuable leguminous cabinetwood species which is commonly found as a canopy or subcanopy tree in a broad range of mixed-species moist forests on tablelands and coastal escarpments in eastern Australia. This paper reports on the competitive light environment of a commercially valuable multi-species regrowth forest in NW Tasmania, in order to define some of the functional interactions and competitive dynamics of these stands. Comparative observations were made of the internal forest light environment in response to small-gap silvicultural treatments, in a young regenerative mix of three codominant tree species. Light measurements were made during periods of maximum external irradiance of the regrowth Eucalyptus obliqua/A. melanoxylon forest canopy at age 10.5 years. This was at a time of vigourous stand development, 4.5 years following the application of three experimental silvicultural treatments whose effects were observed in comparison with an untreated canopy sample designed as a control. Minimal irradiance was observed within and beneath the dense subcanopy of the native nurse species (Pomaderris apetala) which closely surrounds young blackwood regeneration. Unlike current plantation nurse systems, the dense foliage of the native broadleaved Pomaderris all but eliminated direct side-light and low-angle illumination of the young blackwood, from the beginning of tree establishment. The results demonstrated that retention of these densely stocked native codominants effectively suppressed both size and frequency of blackwood branches on the lower bole, through effective and persistent interception of sunlight. Vigorous young blackwood crowns later overtopped the codominant nurse species, achieving a predictable height of branch-free bole. This competitive outcome offers a valuable tool for management of blackwood crown dynamics, stem form and branch habit through manipulation of light environment in young native regrowth systems. Results demonstrate that effective self-pruning in the lower bole of blackwood is achieved through a marked reduction in direct and diffuse sunlight incident on the lower crown, notably to less than 10-15% of full sunlight intensity during conditions of maximum insolation. The results also contain insights for the improved design of mixed-species plantation nurse systems using these or functionally similar species' combinations. Based on evidence presented here for native regrowth forest, plantation nurse systems for blackwood will need to achieve 85-90% interception of external side-light during early years of tree development if self-pruning is to emulate the results achieved in the native nurse system.

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The Cape York Peninsula Land Use Strategy (CYPLUS) is a joint Queensland/Commonwealth initiative to provide a framework for making decisions about how to use and manage the natural resources of Cape York Peninsula in ways that will be ecologically sustainable. As part of the Natural Resources Analysis Program (NRAP) of CYPLUS, the Fisheries Division of the Queensland Department of Primary Industries has mapped the marine vegetation (mangroves and seagrasses) for Cape York Peninsula. The project ran from July 1992 to June 1994. Field work was undertaken in November 1992, May 1993, and April 1994. Final report on project: NRO6 – Marine Plan (Seagrass/Mangrove) Distribution. Dataset URL Link: Queensland Coastal Wetlands Resources Mapping data. [Dataset]

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The requirement for Queensland, Northern Territory and Western Australian jurisdictions to ensure sustainable harvest of fish resources and their optimal use relies on robust information on the resource status. For grey mackerel (Scomberomorus semifasciatus) fisheries, each of these jurisdictions has their own management regime in their corresponding waters. The lack of information on stock structure of grey mackerel, however, means that the appropriate spatial scale of management is not known. As well, fishers require assurance of future sustainability to encourage investment and long-term involvement in a fishery that supplies lucrative overseas markets. These management and fisher-unfriendly circumstances must be viewed in the context of recent 3-fold increases in catches of grey mackerel along the Queensland east coast, combined with significant and increasing catches in other parts of the species' northern Australian range. Establishing the stock structure of grey mackerel would also immensely improve the relevance of resource assessments for fishery management of grey mackerel across northern Australia. This highlighted the urgent need for stock structure information for this species. The impetus for this project came from the strategic recommendations of the FRDC review by Ward and Rogers (2003), "Northern mackerel (Scombridae: Scomberomorus): current and future research needs" (Project No. 2002/096), which promoted the urgency for information on the stock structure of grey mackerel. In following these recommendations this project adopted a multi-technique and phased sampling approach as carried out by Buckworth et al (2007), who examined the stock structure of Spanish mackerel, Scomberomorus commerson, across northern Australia. The project objectives were to determine the stock structure of grey mackerel across their northern Australian range, and use this information to define management units and their appropriate spatial scales. We used multiple techniques concurrently to determine the stock structure of grey mackerel. These techniques were: genetic analyses (mitochondrial DNA and microsatellite DNA), otolith (ear bones) isotope ratios, parasite abundances, and growth parameters. The advantage of using this type of multi-technique approach was that each of the different methods is informative about the fish’s life history at different spatial and temporal scales. Genetics can inform about the evolutionary patterns as well as rates of mixing of fish from adjacent areas, while parasites and otolith microchemistry are directly influenced by the environment and so will inform about the patterns of movement during the fishes lifetime. Growth patterns are influenced by both genetic and environmental factors. Due to these differences the use of these techniques concurrently increases the likelihood of detecting different stocks where they exist. We adopted a phased sampling approach whereby sampling was carried out at broad spatial scales in the first year: east coast, eastern Gulf of Carpentaria (GoC), western GoC, and the NW Northern Territory (NW NT). By comparing the fish samples from each of these locations, and using each of the techniques, we tested the null hypothesis that grey mackerel were comprised of a single homogeneous population across northern Australia. Having rejected the null hypothesis we re-sampled the 1st year locations to test for temporal stability in stock structure, and to assess stock structure at finer spatial scales. This included increased spatial coverage on the east coast, the GoC, and WA. From genetic approaches we determined that there at least four genetic stocks of grey mackerel across northern Australia: WA, NW NT (Timor/Arafura), the GoC and the east Grey mackerel management units in northern Australia ix coast. All markers revealed concordant patterns showing WA and NW NT to be clearly divergent stocks. The mtDNA D-loop fragment appeared to have more power to resolve stock boundaries because it was able to show that the GoC and east coast QLD stocks were genetically differentiated. Patterns of stock structure on a finer scale, or where stock boundaries are located, were less clear. From otolith stable isotope analyses four major groups of S. semifasciatus were identified: WA, NT/GoC, northern east coast and central east coast. Differences in the isotopic composition of whole otoliths indicate that these groups must have spent their life history in different locations. The magnitude of the difference between the groups suggests a prolonged separation period at least equal to the fish’s life span. The parasite abundance analyses, although did not include samples from WA, suggest the existence of at least four stocks of grey mackerel in northern Australia: NW NT, the GoC, northern east coast and central east coast. Grey mackerel parasite fauna on the east coast suggests a separation somewhere between Townsville and Mackay. The NW NT region also appears to comprise a separate stock while within the GoC there exists a high degree of variability in parasite faunas among the regions sampled. This may be due to 1. natural variation within the GoC and there is one grey mackerel stock, or 2. the existence of multiple localised adult sub-stocks (metapopulations) within the GoC. Growth parameter comparisons were only possible from four major locations and identified the NW NT, the GoC, and the east coast as having different population growth characteristics. Through the use of multiple techniques, and by integrating the results from each, we were able to determine that there exist at least five stocks of grey mackerel across northern Australia, with some likelihood of additional stock structuring within the GoC. The major management units determined from this study therefore were Western Australia, NW Northern Territory (Timor/Arafura), the Gulf of Carpentaria, northern east Queensland coast and central east Queensland coast. The management implications of these results indicate the possible need for management of grey mackerel fisheries in Australia to be carried out on regional scales finer than are currently in place. In some regions the spatial scales of management might continue as is currently (e.g. WA), while in other regions, such as the GoC and the east coast, managers should at least monitor fisheries on a more local scale dictated by fishing effort and assess accordingly. Stock assessments should also consider the stock divisions identified, particularly on the east coast and for the GoC, and use life history parameters particular to each stock. We also emphasise that where we have not identified different stocks does not preclude the possibility of the occurrence of further stock division. Further, this study did not, nor did it set out to, assess the status of each of the stocks identified. This we identify as a high priority action for research and development of grey mackerel fisheries, as well as a management strategy evaluation that incorporates the conclusions of this work. Until such time that these priorities are addressed, management of grey mackerel fisheries should be cognisant of these uncertainties, particularly for the GoC and the Queensland east coast.

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The Fitzroy Basin is the second largest catchment area in Australia covering 143,00 km² and is the largest catchment for the Great Barrier Reef lagoon (Karfs et al., 2009). The Great Barrier Reef is the largest reef system in the world; it covers an area of approximately 225,000 km² in the northern Queensland continental shelf. There are approximately 750 reefs that exist within 40 km of the Queensland Coast (Haynes et al., 2007). The prime determinant for the changes in water quality have been attributed to grazing, with beef production the largest single land use industry comprising 90% of the land area (Karfs et al., 2009). In response to the depletion of water quality in the reef, in 2003 a Reef Water Quality plan was developed by the Australian and Queensland governments. The plan targets as a priority sediment contributions from grazing cattle in high risk catchments (The State of Queensland and Commonwealth of Australia, 2003). The economic incentive strategy designed includes analysing the costs and benefits of best management practice that will lead to improved water quality (The State of Queensland and Commonwealth of Australia, 2003).

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A novel methodology for describing genotype by environment interactions estimated from multi-environment field trials is described and an empirical example using an extensive trial network of eucalypts is presented. The network of experiments containing 65 eucalypts was established in 38 replicated field trials across the tropics and subtropics of eastern Australia, with a selection of well-tested species used to provide a more detailed examination of productivity differentials across environmental gradients. By focusing on changes in species’ productivity across environmental gradients, the results are applicable for all species established across the range of environments evaluated in the trial network and simultaneously classify species and environments so that results may be applied across the landscape. The methodology developed was able to explain most (93 %) of the variation in the selected species relative changes in productivity across the various environmental variables examined. Responses were primarily regulated by changes in variables related to water availability and secondarily by temperature related variables. Clustering and ordination can identify groups of species with similar physiological responses to environment and may also guide the parameterisation and calibration of process based models of plant growth. Ordination was particularly useful in the identification of species with distinct environmental response patterns that would be useful as probes for extracting more information from future trials.

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Retrospective identification of fire severity can improve our understanding of fire behaviour and ecological responses. However, burnt area records for many ecosystems are non-existent or incomplete, and those that are documented rarely include fire severity data. Retrospective analysis using satellite remote sensing data captured over extended periods can provide better estimates of fire history. This study aimed to assess the relationship between the Landsat differenced normalised burn ratio (dNBR) and field measured geometrically structured composite burn index (GeoCBI) for retrospective analysis of fire severity over a 23 year period in sclerophyll woodland and heath ecosystems. Further, we assessed for reduced dNBR fire severity classification accuracies associated with vegetation regrowth at increasing time between ignition and image capture. This was achieved by assessing four Landsat images captured at increasing time since ignition of the most recent burnt area. We found significant linear GeoCBI–dNBR relationships (R2 = 0.81 and 0.71) for data collected across ecosystems and for Eucalyptus racemosa ecosystems, respectively. Non-significant and weak linear relationships were observed for heath and Melaleuca quinquenervia ecosystems, suggesting that GeoCBI–dNBR was not appropriate for fire severity classification in specific ecosystems. Therefore, retrospective fire severity was classified across ecosystems. Landsat images captured within ~ 30 days after fire events were minimally affected by post burn vegetation regrowth.

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In Maize, as with most cereals, grain yield is mostly determined by the total grain number per unit area, which is highly related to the rate of crop growth during the critical period around silking. Management practices such as plant density or nitrogen fertilization can affect the growth of the crop during this period, and consequently the final grain yield. Across the Northern Region maize is grown under a large range of plant populations under high year-to-year rainfall variability. Clear guidelines on how to match hybrids and management across environments and expected seasonal condition, would allow growers to increase yields and profits while managing risks. The objective of this research was to screen the response of commercial maize hybrids differing in maturity and prolificity (i.e. multi or single cobbing) types for their efficiency in the allocation of biomass into grain.