631 resultados para South-Eastern Australia
Resumo:
Accurate identification of viruses is critical for resistance breeding and for development of management strategies. To this end, we are developing PCR diagnostics for the luteoviruses / poleroviruses that commonly affect chickpea and pulse crops in Australia. This is helping to overcome the shortfalls in virus identifications that often result from cross reactions of viruses to some antibodies. We compared these PCR tests with antibody based Tissue blot immune-assay (TBIA) in virus surveys of chickpea and pulse crops from eastern Australia. We used a multiplex PCR for Beet western yellows virus (BWYV), Bean leaf roll virus (BLRV), Phasey bean virus (PhBV – a new polerovirus species) and Soybean dwarf virus (SbDV) to investigate the importance of each virus and their host range from different locations. Important alternative hosts included Malva parviflora which was commonly found to be infected with BWYV from many locations and Medicago polymorpha was a host for BLRV, PhBV and SbDV. Using the virus species-specific PCR, 49 virus affected plants (mostly crop plants) from surveys in 2013 were screened, revealing the following infections; 38 SbDV, 5 PhBV, 3 BWYV, 2 BLRV and 1 mixed SbDV/BWYV. From the 45 samples that were not BWYV by PCR, 33 were false-positives in the BWYV TBIA. This demonstrates the BWYV antibody used was not useful for identifying BWYV and PCR indicated that SbDV was the dominant virus from the samples tested from the 2013 season. Preliminary results from the 2014 season indicate a significant change, with SbDV being only a minor component of the total virus population. Further work to clarify the Australian luteovirus complex through molecular techniques is in progress.
Resumo:
Cat’s claw creeper, Macfadyena unguis-cati (L.) Gentry (Bignoniaceae) is a major environmental weed of riparian areas, rainforest communities and remnant natural vegetation in coastal Queensland and New South Wales, Australia. In densely infested areas, it smothers standing vegetation, including large trees, and causes canopy collapse. Quantitative data on the ecology of this invasive vine are generally lacking. The present study examines the underground tuber traits of M. unguis-cati and explores their links with aboveground parameters at five infested sites spanning both riparian and inland vegetation. Tubers were abundant in terms of density (~1000 per m2), although small in size and low in level of interconnectivity. M. unguis-cati also exhibits multiple stems per plant. Of all traits screened, the link between stand (stem density) and tuber density was the most significant and yielded a promising bivariate relationship for the purposes of estimation, prediction and management of what lies beneath the soil surface of a given M. unguis-cati infestation site. The study also suggests that new recruitment is primarily from seeds, not from vegetative propagation as previously thought. The results highlight the need for future biological-control efforts to focus on introducing specialist seed- and pod-feeding insects to reduce seed-output.
Resumo:
Abstract The enemy release hypothesis predicts that native herbivores will either prefer or cause more damage to native than introduced plant species. We tested this using preference and performance experiments in the laboratory and surveys of leaf damage caused by the magpie moth Nyctemera amica on a co-occuring native and introduced species of fireweed (Senecio) in eastern Australia. In the laboratory, ovipositing females and feeding larvae preferred the native S. pinnatifolius over the introduced S. madagascariensis. Larvae performed equally well on foliage of S. pinnatifolius and S. madagascariensis: pupal weights did not differ between insects reared on the two species, but growth rates were significantly faster on S. pinnatifolius. In the field, foliage damage was significantly greater on native S. pinnatifolius than introduced S. madagascariensis. These results support the enemy release hypothesis, and suggest that the failure of native consumers to switch to introduced species contributes to their invasive success. Both plant species experienced reduced, rather than increased, levels of herbivory when growing in mixed populations, as opposed to pure stands in the field; thus, there was no evidence that apparent competition occurred.
Resumo:
Research has shown that road lane width impacts on driver behaviour. This literature review provides guidelines to assist in the design, construction and retrofitting of urban roads to accommodate road users' safety requirements. It focuses on the impacts of lane widths on cyclists and motor vehicle safety behaviour. The literature review commenced with a search of library databases. Peer reviewed articles and road authority (local, state and national) reports were reviewed. The majority of studies investigating the effects of lane width on driver behaviour were simulator based, while research into cycling safety involved data collected from actual traffic environments. Results show that marked road lane width influences perceived task difficulty, risk perception and possibly speed choice. The positioning of cyclists in traffic lanes is influenced by the presence of on-road cycling facilities and the total roadway width. The lateral displacement between bicycle and vehicle is smallest when a bicycle facility is present. Lower, or reduced, vehicle speeds play a significant role in improving bicyclist and pedestrian safety. It is also shown that if road lane widths in urban areas were reduced, to a functional width that was less than the current guidelines of 3.5m, it could result in a safer road environment for all road users.
Resumo:
Research has highlighted the relationship between vehicle speed and increased crash risk and severity. Evidence suggests that police speed enforcement, in particular speed camera operations, can be an effective tool for reducing traffic crashes. A quantitative survey of Queensland drivers (n = 852) was conducted to investigate the impact of police speed enforcement methods on self-reported speeding behaviour. Results indicate that visible enforcement was associated with significantly greater self-reported compliance than covert operations irrespective of the mobility of the approach, and the effects on behaviour were longer lasting. The mobility of operations appeared to be moderated the visibility of the approach. Specifically, increased mobility was associated with increase reported compliant behaviour, but only for covert operations, and increased longevity of reported compliant behaviour, but only for overt operations. The perceived effectiveness of various speed enforcement approaches are also analysed across a range of driving scenarios. Results are discussed in light of the small effect sizes. Recommendations for policy and future research are presented.
Resumo:
Traffic law enforcement is based on deterrence principles, whereby drivers control their behaviour in order to avoid an undesirable sanction. For “hooning”-related driving behaviours in Queensland, the driver’s vehicle can be impounded for 48 hours, 3 months, or permanently depending on the number of previous hooning offences. It is assumed that the threat of losing something of value, their vehicle, will discourage drivers from hooning. While official data shows that the rate of repeat offending is low, an in-depth understanding of the deterrent effects of these laws should involve qualitative research with targeted drivers. A sample of 22 drivers who reported engaging in hooning behaviours participated in focus group discussions about the vehicle impoundment laws as applied to hooning offences in Queensland. The findings suggested that deterrence theory alone cannot fully explain hooning behaviour, as participants reported hooning frequently, and intended to continue doing so, despite reporting that it is likely that they will be caught, and perceiving the vehicle impoundment laws to be extremely severe. The punishment avoidance aspect of deterrence theory appears important, as well as factors over and above legal issues, particularly social influences. A concerning finding was drivers’ willingness to flee from police in order to avoid losing their vehicle permanently for a third offence, despite acknowledging risks to their own safety and that of others. This paper discusses the study findings in terms of the implications for future research directions, enforcement practices and policy development for hooning and other traffic offences for which vehicle impoundment is applied.
Resumo:
The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.
Resumo:
The Wet Tropics bioregion of north-eastern Australia has been subject to extensive fluctuations in climate throughout the late Pliocene and Pleistocene. Cycles of rainforest contraction and expansion of dry sclerophyll forest associated with such climatic fluctuations are postulated to have played a major role in driving geographical endemism in terrestrial rainforest taxa. Consequences for the distributions of aquatic organisms, however, are poorly understood.The Australian non-biting midge species Echinocladius martini Cranston (Diptera: Chironomidae), although restricted to cool, well-forested freshwater streams, has been considered to be able to disperse among populations located in isolated rainforest pockets during periods of sclerophyllous forest expansion, potentially limiting the effect of climatic fluctuations on patterns of endemism. In this study, mitochondrial COI and 16S data were analysed for E. martini collected from eight sites spanning theWet Tropics bioregion to assess the scale and extent of phylogeographic structure. Analyses of genetic structure showed several highly divergent cryptic lineages with restricted geographical distributions. Within one of the identified lineages, strong genetic structure implied that dispersal among proximate (<1 km apart) streams was extremely restricted. The results suggest that vicariant processes, most likely due to the systemic drying of the Australian continent during the Plio-Pleistocene, might have fragmented historical E. martini populations and, hence, promoted divergence in allopatry.
Resumo:
Within the Australian wet tropics bioregion, only 900 000 hectares of once continuous rainforest habitat between Townsville and Cooktown now remains. While on the Atherton Tableland, only 4% of the rainforest that once occurred there remains today with remnant vegetation now forming a matrix of rainforest dispersed within agricultural land (sugarcane, banana, orchard crops, townships and pastoral land). Some biologists have suggested that remnants often support both faunal and floral communities that differ significantly from remaining continuous forest. Australian tropical forests possess a relatively high diversity of native small mammal species particularly rodents, which unlike larger mammalian and avian frugivores elsewhere, have been shown to be resilient to the effects of fragmentation, patch isolation and reduction in patch size. While small mammals often become the dominant mammalian frugivores, in terms of their relative abundance, the relationship that exists between habitat diversity and structure, and the impacts of small mammal foraging within fragmented habitat patches in Australia, is still poorly understood. The relationship between foraging behaviour and demography of two small mammal species, Rattus fuscipes and Melomys cervinipes, and food resources in fragmented rainforest sites, were investigated in the current study. Population densities of both species were strongly related with overall density of seed resources in all rainforest fragments. The distribution of both mammal species however, was found to be independent of the distribution of seed resources. Seed utilisation trials indicated that M.cervinipes and R.fuscipes had less impact on seed resources (extent of seed harvesting) than did other rainforest frugivores. Experimental feeding trials demonstrated that in 85% of fruit species tested, rodent feeding increased seed germination by a factor of 3.5 suggesting that in Australian tropical rainforest remnants, small mammals may play a significant role in enhancing germination of large seeded fruits. This study has emphasised the role of small mammals in tropical rainforest systems in north eastern Australia, in particular, the role that they play within isolated forest fragments where larger frugivorous species may be absent.
Resumo:
Abstract Neopolycystus sp. is the only primary egg parasitoid associated with the pest beetle Paropsis atomaria in subtropical eucalypt plantations, but its impact on its host populations is unknown. The simplified ecosystem represented by the plantation habitat, lack of interspecific competition for host and parasitoid, and the multivoltinism of the host population makes this an ideal system for quantifying the direct and indirect effects of egg parasitism, and hence, effects on host population dynamics. Within-, between- and overall-egg-batch parasitism rates were determined at three field sites over two field seasons, and up to seven host generations. The effect of exposure time (egg batch age), host density proximity to native forest and water sources on egg parasitism rates was also tested. Neopolycystus sp. exerts a significant influence on P. atomaria populations in Eucalyptus cloeziana. plantations in south-eastern Queensland, causing the direct (13%) and indirect (15%) mortality of almost one-third of all eggs in the field. Across seasons and generations, 45% of egg batches were parasitised, with a within-batch parasitism rate of around 30%. Between-batch parasitism increased up to 5–6 days after oviposition in the field, although within-batch parasitism rates generally did not. However, there were few apparent patterns to egg parasitism, with rates often varying significantly between sites and seasons.
Resumo:
Determining the ecologically relevant spatial scales for predicting species occurrences is an important concept when determining species–environment relationships. Therefore species distribution modelling should consider all ecologically relevant spatial scales. While several recent studies have addressed this problem in artificially fragmented landscapes, few studies have researched relevant ecological scales for organisms that also live in naturally fragmented landscapes. This situation is exemplified by the Australian rock-wallabies’ preference for rugged terrain and we addressed the issue of scale using the threatened brush-tailed rock-wallaby (Petrogale penicillata) in eastern Australia. We surveyed for brush-tailed rock-wallabies at 200 sites in southeast Queensland, collecting potentially influential site level and landscape level variables. We applied classification trees at either scale to capture a hierarchy of relationships between the explanatory variables and brush-tailed rock-wallaby presence/absence. Habitat complexity at the site level and geology at the landscape level were the best predictors of where we observed brush-tailed rock-wallabies. Our study showed that the distribution of the species is affected by both site scale and landscape scale factors, reinforcing the need for a multi-scale approach to understanding the relationship between a species and its environment. We demonstrate that careful design of data collection, using coarse scale spatial datasets and finer scale field data, can provide useful information for identifying the ecologically relevant scales for studying species–environment relationships. Our study highlights the need to determine patterns of environmental influence at multiple scales to conserve specialist species such as the brush-tailed rock-wallaby in naturally fragmented landscapes.
Resumo:
The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.
Resumo:
The annual income return for rural property is based on two major factors being commodity prices and production yields. Commodity prices paid to rural producers can vary depending on the agricultural policies of their respective countries. Free trade countries, such as Australia and New Zealand are subject to the volatility of the world commodity markets to a greater extent than those farmers in protected or subsidised markets. In countries where rural production is protected or subsidised the annual income received by rural producers has been relatively stable. However, the high cost of agricultural protection is now being questioned, particularly in relation to the increasing economic costs of government services such as health, education and housing. When combined with the agricultural production limitations of climate, topography, chemical residues and disease issues, the impact of commodity prices on rural property income is crucial in the ability of rural producers to enter into or expand their holdings in agricultural land. These problems are then reflected in the volatility of the rural land capital returns and the investment performance of this property class. This paper will address the total and capital return performance of a major agricultural area and compare these returns on the basis of both location of land and land use. The comparison will be used to determine if location or actual land use has a greater influence on rural property capital returns. This performance analysis is based on over 35,000 rural sales transactions. These transactions cover all market based rural property transactions in New South Wales, Australia for the period January 1990 to December 2008. Correlation analysis and investment performance analysis has also been carried out to determine the possible relationships between location and land use and subsequent changes in rural land capital values.
Resumo:
Robust image hashing seeks to transform a given input image into a shorter hashed version using a key-dependent non-invertible transform. These image hashes can be used for watermarking, image integrity authentication or image indexing for fast retrieval. This paper introduces a new method of generating image hashes based on extracting Higher Order Spectral features from the Radon projection of an input image. The feature extraction process is non-invertible, non-linear and different hashes can be produced from the same image through the use of random permutations of the input. We show that the transform is robust to typical image transformations such as JPEG compression, noise, scaling, rotation, smoothing and cropping. We evaluate our system using a verification-style framework based on calculating false match, false non-match likelihoods using the publicly available Uncompressed Colour Image database (UCID) of 1320 images. We also compare our results to Swaminathan’s Fourier-Mellin based hashing method with at least 1% EER improvement under noise, scaling and sharpening.