Youth Festival Music Performance : Deception Bay

Research Background - Young people with negative experiences of mainstream education often display low levels of traditional academic achievement. These young people tend to display considerable cultural and social resources developed through their repeated experiences of adversity. Education research has a duty to provide these young people with opportunities to showcase, assess and translate their social and cultural resources into symbolic forms of capital. This creative work addresses the following research question. How can educators develop disengaged teenager's social and cultural capital through live music performances? Research Contribution - These live music performances afford the young participants opportunities to display their artistic, technical, social and cultural resources through a popular cultural format. In doing so they require education institutions to provide venues that demonstrate the skills these young people acquire through flexible learning environments. The new knowledge derived from this research focuses on the academic and self confidence benefits for disengaged young people using festival performances as authentic learning activities. Research Significance - This research is significant because it aims to maximise the number of tangible outcomes related to a school-based arts project. The young participants gained technical, artistic, social and commercial skills during this project. This performance led to more recording and opportunities to perform at other youth festivals in SE QLD. Individual performances were distributed and downloaded via creative commons licences at the Australian Creative Resource Archive. It also contributed to their certified qualifications and acted as pilot research data for two competitively funded ARC grants (DP0209421 & LP0883643)

Enrichment, distribution and sources of heavy metals in the sediments of Deception Bay, Queensland, Australia

Sediment samples from 13 sampling sites in Deception Bay, Australia were analysed for the presence of heavy metals. Enrichment factors, modified contamination indices and Nemerow pollution indices were calculated for each sampling site to determine sediment quality. The results indicate significant pollution of most sites by lead (average enrichment factor (EF) of 13), but there is also enrichment of arsenic (average EF 2.3), zinc (average EF 2.7) and other heavy metals. The modified degree of contamination indices (average 1.0) suggests that there is little contamination. By contrast, the Nemerow pollution index (average 5.8) suggests that Deception Bay is heavily contaminated. Cluster analysis was undertaken to identify groups of elements. Strong correlation between some elements and two distinct clusters of sampling sites based on sediment type was evident. These results have implications for pollution in complex marine environments where there is significant influx of sand and sediment into an estuarine environment.

Temporal trends and bioavailability assessment of heavy metals in the sediments of Deception Bay, Queensland, Australia

Thirteen sites in Deception Bay, Queensland, Australia were sampled three times over a period of 7 months and assessed for contamination by a range of heavy metals, primarily As, Cd, Cr, Cu, Pb and Hg. Fraction analysis, enrichment factors and Principal Components Analysis-Absolute Principal Component Scores (PCA-APCS) analysis were conducted in order to identify the potential bioavailability of these elements of concern and their sources. Hg and Te were identified as the elements of highest enrichment in Deception Bay while marine sediments, shipping and antifouling agents were identified as the sources of the Weak acid Extractable Metals (WE-M), with antifouling agents showing long residence time for mercury contamination. This has significant implications for the future of monitoring and regulation of heavy metal contamination within Deception Bay.

Ecophysiology of the marine cyanobacterium, Lyngbya majuscula (Oscillatoriaceae) in Moreton Bay, Australia

Large blooms of the marine cyanobacterium Lyngbya majuscula in Moreton Bay, Australia (27 degrees 05'S, 153 degrees 08'E) have been re-occurring for several years. A bloom was studied in Deception Bay (Northern Moreton Bay) in detail over the period January-March 2000. In situ data loggers and field sampling characterised various environmental parameters before and during the L. majuscula bloom. Various ecophysiological experiments were conducted on L. majuscula collected in the field and transported to the laboratory, including short-term (2h) C-14 incorporation rates and long-term (7 days) pulse amplitude modulated (PAM) fluorometry assessments of photosynthetic capacity. The effects of L. majuscula on various seagrasses in the bloom region were also assessed with repeated biomass sampling. The bloom commenced in January 2000 following usual December rainfall events, water temperatures in excess of 24 degrees C and high light conditions. This bloom expanded rapidly from 0 to a maximum extent of 8 km(2) over 55 days with an average biomass of 210 g(dw)(-1) m(-2) in late February, followed by a rapid decline in early April. Seagrass biomass, especially Syringodium isoetifolium, was found to decline in areas of dense L. majuscula accumulation. Dissolved and total nutrient concentrations did not differ significantly (P > 0.05) preceding or during the bloom. However, water samples from creeks discharging into the study region indicated elevated concentrations of total iron (2.7-80.6 mu M) and dissolved organic carbon (2.5-24.7 mg L-1), associated with low pH values (3.8-6.7). C-14 incorporation rates by L. majuscula were significantly (P < 0.05) elevated by additions of iron (5 mu M Fe), an organic chelator, ethylenediaminetetra-acetic acid (5 mu M EDTA) and phosphorus (5 mu M PO4-3). Photosynthetic capacity measured with PAM fluorometry was also stimulated by various nutrient additions, but not significantly (P > 0.05). These results suggest that the L. majuscula bloom may have been stimulated by bioavailable iron, perhaps complexed by dissolved organic carbon. The rapid bloom expansion observed may then have been sustained by additional inputs of nutrients (N and P) and iron through sediment efflux, stimulated by redox changes due to decomposing L. majuscula mats. (c) 2004 Elsevier B.V. All rights reserved.

Morphometrics of seagrasses at species level, Moreton Bay, Australia determined from core samples collected in 2012-2013

Seagrass meadows are important marine carbon sinks, yet they are threatened and declining worldwide. Seagrass management and conservation requires adequate understanding of the physical and biological factors determining carbon content in seagrass sediments. Here, we identified key factors that influence carbon content in seagrass meadows across several environmental gradients in Moreton Bay, SE Queensland. Sampling was conducted in two regions: (1) Canopy Complexity, 98 sites on the Eastern Banks, where seagrass canopy structure and species composition varied while turbidity was consistently low; and (2) Turbidity Gradient, 11 locations across the entire bay, where turbidity varied among sampling locations. Sediment organic carbon content and seagrass structural complexity (shoot density, leaf area, and species specific characteristics) were measured from shallow sediment and seagrass biomass cores at each location, respectively. Environmental data were obtained from empirical measurements (water quality) and models (wave height). The key factors influencing carbon content in seagrass sediments were seagrass structural complexity, turbidity, water depth, and wave height. In the Canopy Complexity region, carbon content was higher for shallower sites and those with higher seagrass structural complexity. When turbidity varied along the Turbidity Gradient, carbon content was higher at sites with high turbidity. In both regions carbon content was consistently higher in sheltered areas with lower wave height. Seagrass canopy structure, water depth, turbidity, and hydrodynamic setting of seagrass meadows should therefore be considered in conservation and management strategies that aim to maximize sediment carbon content.

Bayesian model averaging for harmful algal bloom prediction

Harmful Algal Blooms (HABs) are a worldwide problem that have been increasing in frequency and extent over the past several decades. HABs severely damage aquatic ecosystems by destroying benthic habitat, reducing invertebrate and fish populations and affecting larger species such as dugong that rely on seagrasses for food. Few statistical models for predicting HAB occurrences have been developed, and in common with most predictive models in ecology, those that have been developed do not fully account for uncertainties in parameters and model structure. This makes management decisions based on these predictions more risky than might be supposed. We used a probit time series model and Bayesian Model Averaging (BMA) to predict occurrences of blooms of Lyngbya majuscula, a toxic cyanophyte, in Deception Bay, Queensland, Australia. We found a suite of useful predictors for HAB occurrence, with Temperature figuring prominently in models with the majority of posterior support, and a model consisting of the single covariate average monthly minimum temperature showed by far the greatest posterior support. A comparison of alternative model averaging strategies was made with one strategy using the full posterior distribution and a simpler approach that utilised the majority of the posterior distribution for predictions but with vastly fewer models. Both BMA approaches showed excellent predictive performance with little difference in their predictive capacity. Applications of BMA are still rare in ecology, particularly in management settings. This study demonstrates the power of BMA as an important management tool that is capable of high predictive performance while fully accounting for both parameter and model uncertainty.

Integrated Bayesian network frameworks for modelling complex ecological issues

Ecological problems are typically multi faceted and need to be addressed from a scientific and a management perspective. There is a wealth of modelling and simulation software available, each designed to address a particular aspect of the issue of concern. Choosing the appropriate tool, making sense of the disparate outputs, and taking decisions when little or no empirical data is available, are everyday challenges facing the ecologist and environmental manager. Bayesian Networks provide a statistical modelling framework that enables analysis and integration of information in its own right as well as integration of a variety of models addressing different aspects of a common overall problem. There has been increased interest in the use of BNs to model environmental systems and issues of concern. However, the development of more sophisticated BNs, utilising dynamic and object oriented (OO) features, is still at the frontier of ecological research. Such features are particularly appealing in an ecological context, since the underlying facts are often spatial and temporal in nature. This thesis focuses on an integrated BN approach which facilitates OO modelling. Our research devises a new heuristic method, the Iterative Bayesian Network Development Cycle (IBNDC), for the development of BN models within a multi-field and multi-expert context. Expert elicitation is a popular method used to quantify BNs when data is sparse, but expert knowledge is abundant. The resulting BNs need to be substantiated and validated taking this uncertainty into account. Our research demonstrates the application of the IBNDC approach to support these aspects of BN modelling. The complex nature of environmental issues makes them ideal case studies for the proposed integrated approach to modelling. Moreover, they lend themselves to a series of integrated sub-networks describing different scientific components, combining scientific and management perspectives, or pooling similar contributions developed in different locations by different research groups. In southern Africa the two largest free-ranging cheetah (Acinonyx jubatus) populations are in Namibia and Botswana, where the majority of cheetahs are located outside protected areas. Consequently, cheetah conservation in these two countries is focussed primarily on the free-ranging populations as well as the mitigation of conflict between humans and cheetahs. In contrast, in neighbouring South Africa, the majority of cheetahs are found in fenced reserves. Nonetheless, conflict between humans and cheetahs remains an issue here. Conservation effort in South Africa is also focussed on managing the geographically isolated cheetah populations as one large meta-population. Relocation is one option among a suite of tools used to resolve human-cheetah conflict in southern Africa. Successfully relocating captured problem cheetahs, and maintaining a viable free-ranging cheetah population, are two environmental issues in cheetah conservation forming the first case study in this thesis. The second case study involves the initiation of blooms of Lyngbya majuscula, a blue-green algae, in Deception Bay, Australia. L. majuscula is a toxic algal bloom which has severe health, ecological and economic impacts on the community located in the vicinity of this algal bloom. Deception Bay is an important tourist destination with its proximity to Brisbane, Australia’s third largest city. Lyngbya is one of several algae considered to be a Harmful Algal Bloom (HAB). This group of algae includes other widespread blooms such as red tides. The occurrence of Lyngbya blooms is not a local phenomenon, but blooms of this toxic weed occur in coastal waters worldwide. With the increase in frequency and extent of these HAB blooms, it is important to gain a better understanding of the underlying factors contributing to the initiation and sustenance of these blooms. This knowledge will contribute to better management practices and the identification of those management actions which could prevent or diminish the severity of these blooms.

A Bayesian network approach to modelling temporal behaviour of Lyngbya majuscula bloom initiation

Lyngbya majuscula is a cyanobacterium (blue-green algae) occurring naturally in tropical and subtropical coastal areas worldwide. Deception Bay, in Northern Moreton Bay, Queensland, has a history of Lyngbya blooms, and forms a case study for this investigation. The South East Queensland (SEQ) Healthy Waterways Partnership, collaboration between government, industry, research and the community, was formed to address issues affecting the health of the river catchments and waterways of South East Queensland. The Partnership coordinated the Lyngbya Research and Management Program (2005-2007) which culminated in a Coastal Algal Blooms (CAB) Action Plan for harmful and nuisance algal blooms, such as Lyngbya majuscula. This first phase of the project was predominantly of a scientific nature and also facilitated the collection of additional data to better understand Lyngbya blooms. The second phase of this project, SEQ Healthy Waterways Strategy 2007-2012, is now underway to implement the CAB Action Plan and as such is more management focussed. As part of the first phase of the project, a Science model for the initiation of a Lyngbya bloom was built using Bayesian Networks (BN). The structure of the Science Bayesian Network was built by the Lyngbya Science Working Group (LSWG) which was drawn from diverse disciplines. The BN was then quantified with annual data and expert knowledge. Scenario testing confirmed the expected temporal nature of bloom initiation and it was recommended that the next version of the BN be extended to take this into account. Elicitation for this BN thus occurred at three levels: design, quantification and verification. The first level involved construction of the conceptual model itself, definition of the nodes within the model and identification of sources of information to quantify the nodes. The second level included elicitation of expert opinion and representation of this information in a form suitable for inclusion in the BN. The third and final level concerned the specification of scenarios used to verify the model. The second phase of the project provides the opportunity to update the network with the newly collected detailed data obtained during the previous phase of the project. Specifically the temporal nature of Lyngbya blooms is of interest. Management efforts need to be directed to the most vulnerable periods to bloom initiation in the Bay. To model the temporal aspects of Lyngbya we are using Object Oriented Bayesian networks (OOBN) to create ‘time slices’ for each of the periods of interest during the summer. OOBNs provide a framework to simplify knowledge representation and facilitate reuse of nodes and network fragments. An OOBN is more hierarchical than a traditional BN with any sub-network able to contain other sub-networks. Connectivity between OOBNs is an important feature and allows information flow between the time slices. This study demonstrates more sophisticated use of expert information within Bayesian networks, which combine expert knowledge with data (categorized using expert-defined thresholds) within an expert-defined model structure. Based on the results from the verification process the experts are able to target areas requiring greater precision and those exhibiting temporal behaviour. The time slices incorporate the data for that time period for each of the temporal nodes (instead of using the annual data from the previous static Science BN) and include lag effects to allow the effect from one time slice to flow to the next time slice. We demonstrate a concurrent steady increase in the probability of initiation of a Lyngbya bloom and conclude that the inclusion of temporal aspects in the BN model is consistent with the perceptions of Lyngbya behaviour held by the stakeholders. This extended model provides a more accurate representation of the increased risk of algal blooms in the summer months and show that the opinions elicited to inform a static BN can be readily extended to a dynamic OOBN, providing more comprehensive information for decision makers.

Stock assessment of the Queensland-New South Wales tailor fishery (Pomatomus saltatrix)

Data on catch sizes, catch rates, length-frequency and age composition from the Australian east coast tailor fishery are analysed by three different population dynamic models: a surplus production model, an age-structured model, and a model in which the population is structured by both age and length. The population is found to be very heavily exploited, with its ability to reproduce dependent on the fishery’s incomplete selectivity of one-year-old fish. Estimates of recent harvest rates (proportion of fish available to the fishery that are actually caught in a single year) are over 80%. It is estimated that only 30–50% of one-year-old fish are available to the fishery. Results from the age-length-structured model indicate that both exploitable biomass (total mass of fish selected by the fishery) and egg production have fallen to about half the levels that prevailed in the 1970s, and about 40% of virgin levels. Two-year-old fish appear to have become smaller over the history of the fishery. This is assumed to be due to increased fishing pressure combined with non-selectivity of small one-year-old fish, whereby the one-year-old fish that survive fishing are small and grow into small two-year-old fish the following year. An alternative hypothesis is that the stock has undergone a genetic change towards smaller fish; the true explanation is unknown. The instantaneous natural mortality rate of tailor is hypothesised to be higher than previously thought, with values between 0.8 and 1.3 yr–1 consistent with the models. These values apply only to tailor up to about three years of age, and it is possible that a lower value applies to fish older than three. The analysis finds no evidence that fishing pressure has yet affected recruitment. If a recruitment downturn were to occur, however, under current management and fishing pressure there is a strong chance that the fishery would need a complete closure for several years to recover, and even then recovery would be uncertain. Therefore it is highly desirable to better protect the spawning stock. The major recommendations are • An increase in the minimum size limit from 30cm to 40cm in order to allow most one-year-old fish to spawn, and • An experiment on discard mortality to gauge the proportion of fish between 30cm and 40cm that are likely to survive being caught and released by recreational line fishers (the dominant component of the fishery, currently harvesting roughly 1000t p.a. versus about 200t p.a. from the commercial fishery).

An investigation of migration and possible stock structuring by the stout whiting, Sillago robusta, in southern Queensland waters, and its impact on managing the fishery. Final Report on the Pilot Program

A highly polymorphic genetic locus of Stout Whiting was examined for evidence of geographical subdivision amongst samples collected from three locales in southern Queensland waters. Statistical indicators of subdivision were not significantly different from zero, suggesting that it is unlikely that the Stout Whiting resource in southern Queensland is genetically subdivided into separate stocks. It is recommended that the full-scale genetic program not proceed and that the resource be managed as a single stock.

Understanding city fringe gentrification: The role of a potential investment gap

Discussion of gentrification has become ‘balkanised’ into a series of competing and intensely-held positions. The dichotomies are between economic and cultural explanations, supply-side and demand-side explanations and structural Marxist and liberal humanist views. Despite the long academic and policy interest in gentrification there is still no clear definition of what it is and why it occurs. However, almost all previous analyses see gentrification as an inner-city phenomenon and so deal with it within framework of inner-city theory and causation. This paper approaches the debate from a somewhat different position. It argues that gentrification, seen as the replacement of lower status and income households by higher status and income households, can occur outside the inner city. It uses clear cases of gentrification on the urban fringe of metropolitan Brisbane in South East Queensland, to explore mechanisms and explanations. The key to this ‘gentrification by the sea’ is a ‘potential investment gap’ between current and potential future property values, based on increasing demand for a limited locational resource – but instead of this being inner-city properties it is waterside land in a regional facing rapid population increase. The paper also draws attention to the inadequate recognition of the roles of the state and the media in previous analyses of gentrification.

Integrating science through Bayesian Belief Networks : case study of Lyngbya in Moreton Bay

Bayesian Belief Networks (BBNs) are emerging as valuable tools for investigating complex ecological problems. In a BBN, the important variables in a problem are identified and causal relationships are represented graphically. Underpinning this is the probabilistic framework in which variables can take on a finite range of mutually exclusive states. Associated with each variable is a conditional probability table (CPT), showing the probability of a variable attaining each of its possible states conditioned on all possible combinations of it parents. Whilst the variables (nodes) are connected, the CPT attached to each node can be quantified independently. This allows each variable to be populated with the best data available, including expert opinion, simulation results or observed data. It also allows the information to be easily updated as better data become available ----- ----- This paper reports on the process of developing a BBN to better understand the initial rapid growth phase (initiation) of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay, Queensland. Anecdotal evidence suggests that Lyngbya blooms in this region have increased in severity and extent over the past decade. Lyngbya has been associated with acute dermatitis and a range of other health problems in humans. Blooms have been linked to ecosystem degradation and have also damaged commercial and recreational fisheries. However, the causes of blooms are as yet poorly understood.

Jack's Bay (the architecturalisation of memory)

Jack's Bay (the architecturalisation of memory) is a key work of the author's exhibition Lightsite, which toured Western Australian galleries from February 2006 to November 2007. It is a five-minute-long exposure photographic image captured inside a purpose-built, room-sized pinhole camera which is demountable and does not have a floor. The work depicts octogenarian Jack Morris, who for forty years held the professional salmon fishing license in the hamlet of Bremer Bay, on the SE coast of Western Australia. The pinhole camera-room is sited within sand dunes new Jack's now demolished beachside camp. Three generations of Jack's descendents stand outside the room - from his daughter to his great grand children. The light from this exterior landscape is 'projected' inside the camera-room and illuminates the interior scene which includes that part of the sand dune upon which the floorless room is erected, along with Jack who is sitting inside. The image evokes the temporality of light. Here, light itself is portrayed as the primary medium through which we both perceive and describe landscape. In this way it is through the agency of light that we construct our connectivity to landscape.

Jack's Bay

Jack's Bay expands understandings of the role of photographic media in the representation of landscapes. It does so by combining architectural construction with B&W photographic processing techniques. A purpose-built room-sized camera obscura is first constructed over a portion of the landscape to be recorded. Photosensitive paper is applied to the interior wall surfaces and is exposed to the inverted light entering a small aperture. These photographs are subsequently developed within the camera itself and consequently 'suffer' embellishments and aberrations from the makeshift darkroom conditions. In this way the specificity of both the landscape and the event of its recording are registered in the final image. Many images were destroyed in the process. The idea of the work is to help the viewer reflect on the role media plays in our understanding of landscape and to thus question the means by which they themselves record and interpret landscape representations.