6 resultados para Women - Legal status, laws, etc - Victoria

em eResearch Archive - Queensland Department of Agriculture


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Urban encroachment on dense, coastal koala populations has ensured that their management has received increasing government and public attention. The recently developed National Koala Conservation Strategy calls for maintenance of viable populations in the wild. Yet the success of this, and other, conservation initiatives is hampered by lack of reliable and generally accepted national and regional population estimates. In this paper we address this problem in a potentially large, but poorly studied, regional population in the State that is likely to have the largest wild populations. We draw on findings from previous reports in this series and apply the faecal standing-crop method (FSCM) to derive a regional estimate of more than 59 000 individuals. Validation trials in riverine communities showed that estimates of animal density obtained from the FSCM and direct observation were in close agreement. Bootstrapping and Monte Carlo simulations were used to obtain variance estimates for our population estimates in different vegetation associations across the region. The most favoured habitat was riverine vegetation, which covered only 0.9% of the region but supported 45% of the koalas. We also estimated that between 1969 and 1995 -30% of the native vegetation associations that are considered as potential koala habitat were cleared, leading to a decline of perhaps 10% in koala numbers. Management of this large regional population has significant implications for the national conservation of the species: the continued viability of this population is critically dependent on the retention and management of riverine and residual vegetation communities, and future vegetation-management guidelines should be cognisant of the potential impacts of clearing even small areas of critical habitat. We also highlight eight management implications.

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Variable-rate technologies and site-specific crop nutrient management require real-time spatial information about the potential for response to in-season crop management interventions. Thermal and spectral properties of canopies can provide relevant information for non-destructive measurement of crop water and nitrogen stresses. In previous studies, foliage temperature was successfully estimated from canopy-scale (mixed foliage and soil) temperatures and the multispectral Canopy Chlorophyll Content Index (CCCI) was effective in measuring canopy-scale N status in rainfed wheat (Triticum aestivum L.) systems in Horsham, Victoria, Australia. In the present study, results showed that under irrigated wheat systems in Maricopa, Arizona, USA, the theoretical derivation of foliage temperature unmixing produced relationships similar to those in Horsham. Derivation of the CCCI led to an r2 relationship with chlorophyll a of 0.53 after Zadoks stage 43. This was later than the relationship (r2 = 0.68) developed for Horsham after Zadoks stage 33 but early enough to be used for potential mid-season N fertilizer recommendations. Additionally, ground-based hyperspectral data estimated plant N (g kg)1) in Horsham with an r2 = 0.86 but was confounded by water supply and N interactions. By combining canopy thermal and spectral properties, varying water and N status can potentially be identified eventually permitting targeted N applications to those parts of a field where N can be used most efficiently by the crop.

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Plant tissue culture has been used for a number of years to produce micropropagated strawberry plants for planting into runner growing beds in the Stanthorpe (Queensland) and Bothwell (Tasmania) regions. This process has allowed the rapid release of new cultivars from the LAWS (Late Autumn, Winter, Spring) breeding program into the current runner production system. Micro-propagation in vitro allows plants to be produced during the autumn and winter months, when mother plants would normally be in a fruit production phase in the field in Queensland. The plants produced are of a high health status when they are planted. The subsequent arrival and build up of various diseases in the runner fields are closely monitored. Using tissue culture for the first generation reduces the time the plants spend in the field by twelve months, reducing disease incidence. To date, any disease outbreak has been successfully managed using early detection and rapid response methods.

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Bemisia tabaci, biotype B, commonly known as the silverleaf whitefly (SLW) is an alien species that invaded Australia in the mid-90s. This paper reports on the invasion ecology of SLW and the factors that are likely to have contributed to the first outbreak of this major pest in an Australian cotton cropping system, population dynamics of SLW within whitefly-susceptible crop (cotton and cucurbit) and non-crop vegetation (sowthistle, Sonchus spp.) components of the cropping system were investigated over four consecutive growing seasons (September-June) 2001/02-2004/05 in the Emerald Irrigation Area (EIA) of Queensland, Australia. Based on fixed geo-referenced sampling sites, variation in spatial and temporal abundance of SLW within each system component was quantified to provide baseline data for the development of ecologically sustainable pest management strategies. Parasitism of large (3rd and 4th instars) SLW nymphs by native aphelinid wasps was quantified to determine the potential for natural control of SLW populations. Following the initial outbreak in 2001/02, SLW abundance declined and stabilised over the next three seasons. The population dynamics of SLW is characterised by inter-seasonal population cycling between the non-crop (weed) and cotton components of the EIA cropping system. Cotton was the largest sink for and source of SLW during the study period. Over-wintering populations dispersed from weed host plant sources to cotton in spring followed by a reverse dispersal in late summer and autumn to broad-leaved crops and weeds. A basic spatial source-sink analysis showed that SLW adult and nymph densities were higher in cotton fields that were closer to over-wintering weed sources throughout spring than in fields that were further away. Cucurbit fields were not significant sources of SLW and did not appear to contribute significantly to the regional population dynamics of the pest. Substantial parasitism of nymphal stages throughout the study period indicates that native parasitoid species and other natural enemies are important sources of SLW mortality in Australian cotton production systems. Weather conditions and use of broad-spectrum insecticides for pest control are implicated in the initial outbreak and on-going pest status of SLW in the region.

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The strategic objectives of Turf Australia (formerly the Turf Producers Association (TPA)) relating to water use in turf are to: • Source and collate information to support the case for adequate access to water for the Turf production and maintenance sectors and • Compile information generated into a convincing communication package that can be readily used by the industry in its advocacy programs (to government, regulators, media etc) More specifically, the turfgrass industry needs unbiased scientific evidence of the value of healthy grass in our environment. It needs to promote the use of adequate water even during drought periods to maintain quality turfgrass, which provides many benefits to the broader community including cooling the environment, saving energy and encouraging healthy lifestyles. The many environmental, social and health benefits of living turfgrass have been the subject of numerous investigations beyond the scope of this review. However further research is needed to fully understand the economic returns achievable by the judicious use of water for the maintenance of healthy turfgrass. Consumer education, backed by scientific evidence will highlight the “false economy” in allowing turfgrass to wither and die during conditions which require high level water restrictions. This report presents a review of the literature pertaining to research in the field of turf water use. The purpose of the review was to better understand the scope and nature of existing research results on turf water relations so that knowledge gaps could be identified in achieving the above strategic objectives of the TPA. Research to date has been found to be insufficient to compile a convincing communication package as described. However, identified knowledge gaps can now be addressed through targeted research. Information derived from targeted research will provide valuable material for education of the end user of turfgrass. Recommendations have been developed, based on the results of this desktop review. It was determined that future research in the field of turf irrigation needs to focus on a number of key factors which directly or indirectly affect the relationship between turfgrass and water use. These factors are: • Climate • Cultivar • Quality • Site use requirements • Establishment and management The overarching recommendation is to develop a strategic plan for turfgrass water relations research based around the five determinants of turf water use listed above. This plan should ensure research under these five categories is integrated into a holistic approach by which the consumer can be guided in species and/or cultivar choices as well as best management practices with respect to turfgrass water relations. Worsening drought cycles and limited supply of water for irrigation were the key factors driving every research project reviewed in this report. Subsidence of the most recent (or current) drought conditions in Australia should not be viewed by the turf industry as a reason to withdraw support or funding for research in this area. Drought conditions, limited domestic water availability and urban water restrictions will return in Australia albeit in 5, 10 or 20 years time and the turf industry has an opportunity to prepare for that time.

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Report on evidence of shrinkage of live coral trout during professional fishing operations on the Great Barrier Reef in 2000. Excel data includes the following fields: Column A. Fish (fish number from 1 -24) Column B. Bin (1-8, container the fish was held in during the experiment) Column C. Measure (1-7, number of the measurement of each fish) Column D. Observer (1 or 2, making the measurement) Column E. Time 2 Column F. Time (time of the day the measurement was made) Column G. FL (Fork Length) Column H. TL (Total Length) Column I. Difference (difference in length between measures) Column J. Order Column K. Temperature (surface water temp under the boat)