This data set in excel sheet format presents results of the mail survey of 1565 residents of the GBRWHA. The dataset is accompanied by a set of 58 maps that illustrate key findings.

Project 10.2 explored how visitors and residents feel towards and perceive Great Barrier Reef World Heritage Area, as well as their willingness to pay to protect the reef and their satisfaction with current and future developments in and around the GBRWHA.

Data were collected from the residents of the GBRWHA using a mail-out survey to a geographically stratified random sample of resident households in postcodes that lay partially or entirely within the study area. The pilot stage included 230 randomly selected households (2 from each of the postcodes identified), while the main mailing included about 40 households in each postcode. Following the Dilman (2007) methodology, we sent a reminder letter with replacement questionnaire to those who had not responded four weeks later, with a third reminder after that. We estimate that just under 4,000 questionnaires reached their intended recipients, and we received 902 completed questionnaires.

We were cognizant that some demographic groups are more likely to respond to mail-out surveys than others in these regions (e.g. young males, Indigenous people). Therefore we conducted supplementary face-to-face data-collection using the same questionnaire, across various public locations such as ferry terminals, airports and beaches. These extra activities generated an additional 663 responses, bringing the total number of completed resident questionnaires to 1565.

Data Format:

Excel data sheet with each row representing a postcode within the Great Barrier Reef Catchment Area and each column providing summary information about one variable (e.g. % or respondents who have never been to the GBRWHA). The GIS maps represent the data visually (one variable per map, showing responses for each postcode).

The original raw data cannot be published for privacy reasons. Data available here is a public form of the data, aggregated by postcode.

Further details of the project, including data collection and analysis methods, can be found in:

Stoeckl, N., Farr, M. and Sakata H. (2013) What do residents and tourists ¿value¿ most in the GBRWHA? Project 10.2 interim report on residential and tourist data collection activities including descriptive data summaries. Report to the National Environmental research program. Reef and Rainforest Research Centre Limited, Cairn (pp112)

Dispersal is critical for successful pest control measures as it determines the rate of movement across target control areas and influences the risk of human exposure. We used a fine-scale spatial population genomic approach to investigate the dispersal ecology and population structure of Aedes notoscriptus, an important disease-transmitting mosquito at the Mornington Peninsula, Australia. We sampled and reared Ae. notoscriptus eggs at two time points from 170 traps up to 5 km apart and generated genomic data from 240 individuals. We also produced a draft genome assembly from a laboratory colony established from mosquitoes sampled near the study area. We found low genetic structure (Fst) and high coancestry throughout the study region. Using genetic data to identify close kin dyads, we found that mosquitoes had moved distances of >1 km within a generation, which is further than previously described. A spatial autocorrelation analysis of genetic distances indicated genetic similarity at >1 km separation, a tenfold higher distance than for a comparable population of Ae. aegypti, from Cairns, Australia. These findings point to high mobility of Ae. notoscriptus, highlighting challenges of localized intervention strategies. Further sampling within the same area 6 and 12 months after initial sampling showed that egg-counts were relatively consistent across time, and that spatial variation in egg-counts covaried with spatial variation in Wright’s neighbourhood size (NS). As NS increases linearly with population density, egg-counts may be useful for estimating relative density in Ae. notoscriptus. The results highlight the importance of acquiring species-specific data when planning control measures.

Births that occurred by hospital name. Birth events of 5 or more per hospital location are displayed

Census employment and income data for persons working in creative industries and creative occupations.

This dataset consists of 14 individual datasets that underpin the interactive dashboards on the project's Data Tables webpage.

Project background:

Australian cultural and creative activity: A population and hotspot analysis is an Australian Research Council Linkage project (LP160101724) being undertaken by QUT and the University of Newcastle, in partnership with Arts Queensland, Create NSW, Creative Victoria, Arts South Australia and the Western Australian Department of Local Government, Sport and Cultural Industries.

This comprehensive project aims to grasp the contemporary dynamics of cultural and creative activity in Australia. It brings together population-level and comparative quantitative and qualitative analyses of local cultural and creative activity. The project will paint a complete national picture, while also exploring the factors that are producing local and regional creative hotspots.

Creative hotspots for study were selected in consultation with state research partners:

Queensland – Cairns, Sunshine Coast + Noosa, Gold Coast, Central West Queensland
New South Wales – Coffs Harbour, Marrickville, Wollongong, Albury
Victoria – Geelong + Surf Coast, Ballarat, Bendigo, Wodonga
Western Australia – Geraldton, Fremantle, Busselton, Albany + Denmark
South Australia – to be confirmed shortly

Statistical summaries drawn from a diverse range of data sources including the Australian Census, the Australian Business Register, IP Australia registration data, infrastructure availability lists and creative grants and rights payments as well as our fieldwork, inform hotspot reports.

Adjusting for population levels, Queensland households generated an average of 556kg of waste per capita in 2016 2017, ranging from 390kg in the Cairns region to 680kg in Remote Queensland. Adjusting for population levels, Queensland households generated an average of 556kg of waste per capita in 2016 2017, ranging from 390kg in the Cairns region to 680kg in Remote Queensland.

PMI: Post-mortem interval; CDR: Clinical dementia rating.

Dingoes play a strong role in Australia's ecological framework as the apex predator but are under threat from hybridization and agricultural control programs. Government legislation lists the conservation of the dingo as an important aim, yet little is known about the biogeography of this enigmatic canine, making conservation difficult. Mitochondrial and Y chromosome DNA studies show evidence of population structure within the dingo. Here, we present the data from Illumina HD canine chip genotyping for 23 dingoes from five regional populations, and five New Guinea Singing Dogs to further explore patterns of biogeography using genome-wide data. Whole genome single nucleotide polymorphism (SNP) data supported the presence of three distinct dingo populations (or ESUs) subject to geographical subdivision: southeastern (SE), Fraser Island (FI) and northwestern (NW). These ESUs should be managed discretely. The FI dingoes are a known reservoir of pure, genetically distinct dingoes. Elevated inbreeding coefficients identified here suggest this population may be genetically compromised and in need of rescue; current lethal management strategies that do not consider genetic information should be suspended until further data can be gathered. D statistics identify evidence of historical admixture or ancestry sharing between southeastern dingoes and South East Asian village dogs. Conservation efforts on mainland Australia should focus on the SE dingo population that is under pressure from domestic dog hybridization and high levels of lethal control. Further data concerning the genetic health, demographics and prevalence of hybridization in the SE and FI dingo populations is urgently needed to develop evidence based conservation and management strategies.

Admixture between species is a cause for concern in wildlife management. Canids are particularly vulnerable to inter-specific hybridisation, and genetic admixture has shaped their evolutionary history. Microsatellite DNA testing, relying on a small number of genetic markers and geographically restricted reference populations, has identified extensive domestic dog admixture in Australian dingoes and driven conservation management policy. There has been concern that geographic variation in dingo genotypes could confound ancestry analyses that use a small number of genetic markers. Here we apply genome-wide single nucleotide polymorphism (SNP) genotyping to a set of 385 wild and captive dingoes from across Australia and then carry out comparisons to domestic dogs, and perform ancestry modelling and biogeographic analyses to characterize population structure in dingoes and investigate the extent of admixture between dingoes and dogs in different regions of the continent. We show that there are at least five distinct dingo populations across Australia. We observed limited evidence of dog admixture in wild dingoes, challenging previous reports regarding the occurrence and extent of dog admixture in dingoes, as our ancestry analyses show that previous assessments severely overestimate the degree of domestic dog admixture in dingo populations, particularly in southeastern Australia. These findings strongly support the use of genome-wide SNP genotyping as a refined method for wildlife managers and policy makers to assess and inform dingo management policy and legislation moving forwards. Methods This data was collected by microarray SNP genotyping using Axiom Canine Set A, Axiom Canine Set B and Axiom CanineHD arrays (Thermo Fischer Scientific Inc). Microarrays were processed at either the Ramaciotti Centre for Genomics (Sydney, Australia) or Thermo Scientific Microarray Research Services Laboratory (Santa Clara, CA, USA). Both the raw CEL files off the GeneTitan microarray scanner and Plink SNP datasets are provided.

The final Australian National Liveability Study 2018 datasets comprise a suite of policy relevant spatial indicators of local neighbourhood liveability and amenity access estimated for residential address points across Australia's 21 largest cities, and summarised at range of larger area scales (Mesh Block, Statistical Areas 1-4, Suburb, LGA, and overall city summaries). The indicators and measures included encompass topics including community and health services, employment, food, housing, public open space, transportation, walkability and overall liveability. The datasets were produced through analysis of built environment and social data from multiple sources including OpenStreetMap the Australian Bureau of Statistics, and public transport agency GTFS feed data. These are provided in CSV format under an Open Data Commons Open Database licence. The 2018 Australian National Liveability data will be of interest to planners, population health and urban researchers with an interest in the spatial distribution of built environment exposures and outcomes for data linkage, modelling and mapping purposes. Area level summaries for the data were used to create the indicators for the Australian Urban Observatory at its launch in 2020. A detailed description of the datasets and the study has been published in Nature Scientific Data, and notes and code illustrating usage of the data are located on GitHub. The spatial data were developed by the Healthy Liveable Cities Lab, Centre for Urban Research with funding support provided from the Australian Prevention Partnership Centre #9100003, NESP Clean Air and Urban Landscapes Hub, NHMRC Centre of Research Excellence in Healthy, Liveable Communities #1061404 and an NHMRC Senior Principal Research Fellowship GNT1107672; with interactive spatial indicator maps accessible via the Australian Urban Observatory. Any publications utilising the data are not necessarily the view of or endorsed by RMIT University or the Centre of Urban Research. RMIT excludes all liability for any reliance on the data.

Adjusted dengue incidence rates per age class for the city of Cairns during January–August 2003.

Description of each space-time cluster identified for the dengue epidemic that affected the city of Cairns during January–August 2003.