UTAS/a79ba0bb-eed7-4af6-9859-7cc1e9b9433fUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/a79ba0bb-eed7-4af6-9859-7cc1e9b9433fCharacterising people–species–place relationships

https://data.utas.edu.au/metadata/a79ba0bb-eed7-4af6-9859-7cc1e9b9433f

This dataset contains anonymised survey responses examining people’s connections to place and species at The Neck on Bruny Island, Tasmania using a novel extension of the Inclusion of Self Scale. The survey includes five scale measures to identify people-species-place relationships, with a focus on fairy penguins (Eudyptula minor) and short-tailed shearwaters (Ardenna tenuirostris). Data were collected from 93 participants. All data are de-identified and were collected with informed consent under approved ethical protocols (HREC29693).Attribution(BY)This dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0). Users are free to share and adapt the material for any purpose, provided appropriate credit is given to the original authors.https://data.utas.edu.au/metadata/a79ba0bb-eed7-4af6-9859-7cc1e9b9433f2026Edith ShumUniversity of Tasmania, Australia20252025https://orcid.org/0000-0003-2469-1355410401440604180206Place attachmentConnection to natureSpecies attachmentCultural keystone speciesPlacemakersHuman-nature relationshipsUTAS/6b5dbf03-98f2-4c40-b508-cdff00533b44University of Tasmania, Australiahttps://data.utas.edu.au/metadata/6b5dbf03-98f2-4c40-b508-cdff00533b44Exploring Online Learning at University and Its Impact on Students’ Approaches to Learning: Anonymised PhD questionnaire dataset (2022–2023)

https://data.utas.edu.au/metadata/6b5dbf03-98f2-4c40-b508-cdff00533b44

This dataset contains anonymised questionnaire responses collected for Paul Albinson’s PhD research on online learning at university and its impact on Students’ Approaches to Learning (SAL). Data were collected in two phases at one Australian university (University of Tasmania), with Phase 1 taking place during Semester 2, 2022, and Phase 2 during Semester 1, 2023. The PhD comprised a Phase 1 student study, a Phase 1 teacher study, and a Phase 2 student study. Each study included a questionnaire and follow-on interviews; this dataset contains questionnaire responses only, as interview data are excluded due to de-identification constraints. Phase 1 questionnaires covered students’ and teachers’ views and experiences of online learning and the online tools used for learning. The Phase 1 student questionnaire also explored Students’ Approaches to Learning (SAL) online. The Phase 2 student questionnaire examined the potential of a Personal Learning Resources Library to influence SAL online and students’ level of acceptance and willingness to use it. It also provided additional data on SAL online and their usage of student-directed tools. Both student questionnaires incorporated two Likert-type measures: a modified version of the Revised Two-Factor Study Process Questionnaire (R-SPQ-2F), which investigated SAL, and an Online Student Engagement Questionnaire (OSEQ), which investigated how students engaged with their studies in an online learning environment. For these measures, Phase 2 student responses supplemented Phase 1 student responses, which were combined into a single dataset within the PhD. To assist interpretation of the dataset, refer to Albinson, P. (2025). Exploring Online Learning at University and Its Impact on Students’ Approaches to Learning [PhD Thesis, University of Tasmania]. Hobart, Tasmania. https://doi.org/10.13140/RG.2.2.16749.86249Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/6b5dbf03-98f2-4c40-b508-cdff00533b442026Paul AlbinsonUniversity of Tasmania, Australia2022-072023-06northlimit=-8.66791800236311; southlimit=-44.840290651398; westlimit=830.1708984375; eastlimit=875.6982421875; projection=WGS84https://orcid.org/0000-0003-2270-7085390303390402390102160102160302160304Students’ Approaches to Learning (SAL)Deep and surface learningR-SPQ-2FOnline learningBlended learningHigher educationQuestionnaireEducation studentsUTAS/94843b52-b2a3-4c55-a325-9c7d95f1c8bcUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/94843b52-b2a3-4c55-a325-9c7d95f1c8bcGravimetric cup test mass measurements and calculations (wet-cup & dry-cup), Eucalyptus nitens, 23°C, 50% RH

https://data.utas.edu.au/metadata/94843b52-b2a3-4c55-a325-9c7d95f1c8bc

This dataset contains gravimetric cup-test measurements and derived vapour transport parameters for solid Eucalyptus nitens tested under controlled conditions of 23 °C and 50% relative humidity (RH) in a controlled test building. The dataset is provided as one consolidated Excel file and includes daily mass (weight) recordings for wet-cup (n = 5) and dry-cup (n = 5) configurations, along with the corresponding calculated outputs (e.g., vapour pressure difference Δpᵥ, vapour flux, permeance/permeability, vapour resistance, diffusion resistance factor µ, and equivalent air layer thickness Sᵈ). The data support reproduction, verification, and reanalysis of water vapour diffusion resistivity results under the stated condition.Attribution - No Derivatives(BY - ND)https://data.utas.edu.au/metadata/94843b52-b2a3-4c55-a325-9c7d95f1c8bc2026Zahraa AL-SHAMMAAUniversity of Tasmania, Australia2025-082025-10east=147.122257053852; north=-41.3992600760931; projection=WGS84https://orcid.org/0009-0000-9911-7425330305401699330110330105120202120205120203120403120306240601Eucalyptus nitenssolidwoodgravimetric cup methodiso 12572wet cupdry cupwater vapour diffusionvapour permeancevapour permeabilitydiffusion factorequivalent air layer thickness sdhygrothermal performanceUTAS/996a3ac9-3b2a-4aa9-8d0c-a7470197fcc6University of Tasmania, Australiahttps://data.utas.edu.au/metadata/996a3ac9-3b2a-4aa9-8d0c-a7470197fcc6Firebrand numerical simulation and radiant heat/firebrand house exposure models

https://data.utas.edu.au/metadata/996a3ac9-3b2a-4aa9-8d0c-a7470197fcc6

Dataset associated with the manuscript: "Wildfire house loss hazard mapping and fuel management scenario planning on a Tasmanian wildland-urban interface using radiant heat and firebrand exposure modelling" Data consists of statistical and transect-based summaries of firebrand spatial distribution from numerical simulations of firebrand transport under a range of fire weather and topographical scenarios, and the outputs of statistical firebrand model and radiant heat model on housing exposure across the Hobart and Glenorchy areas, indicating proportion of houses impacted by these hazards at a range of fire weather and interface structure scenarios.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/996a3ac9-3b2a-4aa9-8d0c-a7470197fcc62026Grant WilliamsonAmila WickramasingheOwen PriceStefania OndeiDavid BowmanUniversity of Tasmania, Australia20252026northlimit=-42.7621376340935; southlimit=-42.9091659251865; westlimit=147.193450927734; eastlimit=147.380218505859; projection=WGS84https://orcid.org/0000-0002-3469-7550https://orcid.org/0000-0002-0481-9166https://orcid.org/0000-0001-5327-568Xhttps://orcid.org/0000-0002-2515-3316https://orcid.org/0000-0001-8075-124X300706350703300707190401embersfirebrandsradiant heatwuifire behaviourhouse losshazardriskUTAS/5cc385cf-2953-4fd6-8ae6-45b04c0f0a70University of Tasmania, Australiahttps://data.utas.edu.au/metadata/5cc385cf-2953-4fd6-8ae6-45b04c0f0a70Code and deidentified data from Ondei et al., 2026. WF25218

https://data.utas.edu.au/metadata/5cc385cf-2953-4fd6-8ae6-45b04c0f0a70

Code and deidentified data used in: Ondei, S., Williamson, G. J., Foyster, S., & Bowman, D. M. (2026). Incorporating airborne LiDAR into reliable and scalable garden wildfire hazard assessments at the wildland–urban interface. International Journal of Wildland Fire, WF25218. The publication is available open access at https://doi.org/10.1071/WF25218. Please cite this publication when using scripts or data for your research. The code is also available on GitHub at https://github.com/StefOnd/LiDAR_garden_defensibleSpace.git. As research progresses, updated versions will be added to that GitHub repository.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/5cc385cf-2953-4fd6-8ae6-45b04c0f0a702026Stefania OndeiGrant WilliamsonDavid BowmanUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-2515-3316https://orcid.org/0000-0002-3469-7550https://orcid.org/0000-0001-8075-124X410205330308190101190401garden designdefensible spaceLiDARbushfirescommunity adaptationUTAS/8f391786-da55-4408-a16a-ef4ca4146ba2University of Tasmania, Australiahttps://data.utas.edu.au/metadata/8f391786-da55-4408-a16a-ef4ca4146ba2Mechanisms of species-people relationships in place attachment

https://data.utas.edu.au/metadata/8f391786-da55-4408-a16a-ef4ca4146ba2

This dataset contains anonymised survey responses examining people’s connections to place and species at The Neck on Bruny Island, Tasmania. The survey includes measures of place attachment and species-related person–process–place dimensions, with a focus on fairy penguins (Eudyptula minor) and short-tailed shearwaters (Ardenna tenuirostris). Data were collected from 95 participants and include composite and item-level responses used in quantitative analyses of species–place relationships. All data are de-identified and were collected with informed consent under approved ethical protocols (HREC29693).Attribution(BY)This dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0). Users are free to share and adapt the material for any purpose, provided appropriate credit is given to the original authors.https://data.utas.edu.au/metadata/8f391786-da55-4408-a16a-ef4ca4146ba22026Edith ShumUniversity of Tasmania, Australia20242025https://orcid.org/0000-0003-2469-1355410401440604180206Place attachmentConnection to natureperson-process-place frameworkspecies attachmentUTAS/72369222-751c-4454-ab72-129702742bafUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/72369222-751c-4454-ab72-129702742bafAssembly of Australia’s alpine seed plant flora

https://data.utas.edu.au/metadata/72369222-751c-4454-ab72-129702742baf

A total of 327 sequestration events were identified that led to the creation of 534 native Australian 534 native Australian alpine plant species in 62 families. Of these events 76% resulted in only one species, 13% were followed by minor radiations (144 species), and 10% were ambiguous (142 species) and may have involved multiple sequestrations. The latter and convergent evolution mean that the count of 327 events may be an underestimate. The alpine flora are dominated by groups that arrived in Australia long after the break-up of Gondwana (at least 62% of the species and 54% of the sequestration events), and mostly appear to have reached Australia by trans-oceanic dispersal. However, most of these recent events involved the intermediate step of occupying non-alpine habitats prior to colonising alpine habitats (at least 46% of these events and 53% of the species). Most of these latter groups mostly came from Africa, but Eurasia and the Americas also contributed. Groups that arrived directly from other regions mostly appear to have come from New Zealand. Alpine Tasmania, especially western Tasmania, has more old Australian groups, including remarkable palaeoendemics, and more woody species than alpine mainland Australia.Attribution - Share Alike(BY - SA)https://data.utas.edu.au/metadata/72369222-751c-4454-ab72-129702742baf2025Greg JordanUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-6033-2766https://orcid.org/0000-0001-5603-5024310402280102alpinebiogeographybiome assemblyevolutionniche conservatismphylogenyradiationUTAS/7bc61f5f-b811-4f14-8c24-dc5ad24fe8a2University of Tasmania, Australiahttps://data.utas.edu.au/metadata/7bc61f5f-b811-4f14-8c24-dc5ad24fe8a2Intermittently Controlled Temperature: A Hygrothermal and Bio-hygrothermal Assessment of Timber-framed Brick Veneer Wall Systems

https://data.utas.edu.au/metadata/7bc61f5f-b811-4f14-8c24-dc5ad24fe8a2

This study examines indoor temperature profiles in intermittently conditioned 7-Star homes in south-eastern Australia, focusing on two common external wall systems: brick veneer and compressed fibre cement sheet. Two scenarios are evaluated: (1) continuously controlled indoor temperature and relative humidity (RH), as prescribed by ASHRAE 160, and (2) uncontrolled indoor temperature with regulated RH. The study also assesses the effectiveness of mould mitigation strategies, including ventilated wall cavities and vapour control membranes, under both thermal conditions. The findings indicate frequent exceedances of the 21.1 °C threshold, particularly in kitchen–living spaces and bedrooms, leading to varying mould risks across climate zones. Mitigation effectiveness also varied: in several cases, an interior vapour control layer increased mould risk under uncontrolled temperature conditions, contrary to its performance in continuously conditioned settings.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/7bc61f5f-b811-4f14-8c24-dc5ad24fe8a22025Liqun (Antonia) GuanMark DewsburyUniversity of Tasmania, Australia2022-112032-11northlimit=-41.3980120407049; southlimit=-41.4022119878613; westlimit=147.117525689088; eastlimit=147.127785006743; projection=WGS84https://orcid.org/0000-0002-6994-6721https://orcid.org/0000-0002-3607-3637https://orcid.org/0000-0001-5603-5024330105400504510799170199200203200204CFCSBrick veneeruncontrolled temperaturesintermittent conditioninghygrothermal performanceindoor mould growthUTAS/cb328fe9-5793-4295-af6f-acc0bbf0e732University of Tasmania, Australiahttps://data.utas.edu.au/metadata/cb328fe9-5793-4295-af6f-acc0bbf0e732Uncontrolled Rh results of southeast 7-Star Australian housing (brick veneer)

https://data.utas.edu.au/metadata/cb328fe9-5793-4295-af6f-acc0bbf0e732

This study investigates the effects of uncontrolled indoor relative humidity on interstitial condensation and indoor mould risks in Australia's two most common low-rise timber framed external wall systems, brick veneer and compressed fibre cement sheet cladding of three temperate climate zones. Internationally, hygrothermal and bio-hygrothermal simulations are widely applied to design moisture-resilient building envelopes. In this research, ten-year transient hygrothermal and mould growth simulations are conducted. The result reveals that, without relative humidity control, interior conditions frequently exceed the international recommended 70% threshold, significantly increasing both surface and interstitial mould risks. The results are also compared with continuous control of indoor temperature below 21.1 °C with RH maintained below 70% (per ASHRAE 160) from previous research. Mitigation strategies, including ventilated wall cavities and interior vapour control membranes, are evaluated. Results show 1) frequent exceedances of the 70% RH benchmark in open living areas and bedrooms, with climate-specific variations in mould growth indices. 2) Importantly, vapour control membranes are effective under continuous conditioning, but proved inconsistent performance when under relative humidity was uncontrolled, intermittent conditioning.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/cb328fe9-5793-4295-af6f-acc0bbf0e7322025Liqun (Antonia) GuanMark DewsburyUniversity of Tasmania, Australia2023-112025-11https://orcid.org/0000-0002-6994-6721https://orcid.org/0000-0002-3607-3637330102330206330202120105120101energy efficientindoor healthhygrothermalbuilding performancemoisture in buildingsUTAS/0a48b3d3-5349-4d6f-831c-7b5e0ef8aa18University of Tasmania, Australiahttps://data.utas.edu.au/metadata/0a48b3d3-5349-4d6f-831c-7b5e0ef8aa18Hygrothermal Performance in Intermittently Conditioned 7-Star Housing, South-East Australia (Brick Veneer)

https://data.utas.edu.au/metadata/0a48b3d3-5349-4d6f-831c-7b5e0ef8aa18

This study examines the hygrothermal performance of 7-Star rated homes in South-East Australia when operated under intermittent air-conditioning schedules. It investigates how varying cooling and heating patterns influence indoor temperature, relative humidity, and overall comfort conditions throughout different climate zones. By analysing the interaction between building envelope performance and intermittent conditioning, the study highlights the risks and benefits related to moisture levels, thermal stability, and energy efficiency. The findings provide insights that support better design, operation, and occupant comfort strategies for high-performance Australian housing.Attribution - NonCommercial - No Derivatives(BY - NC - ND)All rights reserved to the related data creators.https://data.utas.edu.au/metadata/0a48b3d3-5349-4d6f-831c-7b5e0ef8aa182025Liqun (Antonia) GuanMark DewsburyUniversity of Tasmania, Australia2022-112025-11northlimit=-41.3976259525091; southlimit=-41.4043658973656; westlimit=147.114052113681; eastlimit=147.129742824323; projection=WGS84https://orcid.org/0000-0002-6994-6721https://orcid.org/0000-0002-3607-3637330107170199200204120105280110buildingphysicsbuildingarchitectural scienceUTAS/17937613-cccc-4c87-91a8-046f2d8efd3aUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/17937613-cccc-4c87-91a8-046f2d8efd3a𝘌𝘶𝘤𝘢𝘭𝘺𝘱𝘵𝘶𝘴 𝘨𝘭𝘰𝘣𝘶𝘭𝘶𝘴 chloroplast haplotype data for Potts 𝘦𝘵 𝘢𝘭 (2025)

https://data.utas.edu.au/metadata/17937613-cccc-4c87-91a8-046f2d8efd3a

This data record contains chloroplast DNA haplotype clade data used to construct pie diagrams in Figure 4 of Potts 𝘦𝘵 𝘢𝘭 (2025) Potts BM, Jones RC, Jordan GJ, Nicolle D, Vaillancourt RE, & Reid JB. (2025). Hybridisation and species boundaries in eucalypts. Austral Ecology [in press]. Specific Cc and Cg haplotypes in each race/subrace/locality are listed and the count indicates the number of trees with haplotypes corresponding to the central (Cc and Cg), southern, and other clades. The Strezlecki Ranges count does not include Phillip Island, which is plotted separately along with Rodondo Island. The three subraces from the northeastern race are plotted separately, and the southern Tasmania race includes five samples from Recherche Bay.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/17937613-cccc-4c87-91a8-046f2d8efd3a2025Rebecca JonesBrad PottsJames ReidRene VaillancourtDean NicolleGreg JordanUniversity of Tasmania, Australia19992025northlimit=-36.9937783887252; southlimit=-44.3945421921559; westlimit=140.108642578125; eastlimit=151.885986328125; projection=WGS84https://orcid.org/0000-0002-6491-1423https://orcid.org/0000-0001-6244-289Xhttps://orcid.org/0000-0003-4317-0977https://orcid.org/0000-0002-1159-9149https://orcid.org/0009-0005-7463-836Xhttps://orcid.org/0000-0002-6033-2766https://orcid.org/0000-0001-5603-5024410401310402260204chloroplasteucalyptushaplotypeJLAJLA+TasmaniaVictoriaUTAS/4c9917e2-77e0-476d-a9f2-6fd04fcf250fUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/4c9917e2-77e0-476d-a9f2-6fd04fcf250f𝘌𝘶𝘤𝘢𝘭𝘺𝘱𝘵𝘶𝘴 𝘨𝘭𝘰𝘣𝘶𝘭𝘶𝘴 flowering time data Potts 𝘦𝘵 𝘢𝘭 (2025)

https://data.utas.edu.au/metadata/4c9917e2-77e0-476d-a9f2-6fd04fcf250f

Variation in the flowering times of races of 𝘌𝘶𝘤𝘢𝘭𝘺𝘱𝘵𝘶𝘴 𝘨𝘭𝘰𝘣𝘶𝘭𝘶𝘴 races observed in natural stands in December 2004, as plotted in Figure 3 of Potts 𝘦𝘵 𝘢𝘭. (2025): Potts BM, Jones RC, Jordan GJ, Nicolle D, Vaillancourt RE, & Reid JB. (2025). Hybridisation and species boundaries in eucalypts. Austral Ecology [in press]. The race names follow Dutkowski and Potts (1999), with a change in the boundary between the southern Tasmanian and south-eastern Tasmanian races following information in López 𝘦𝘵 𝘢𝘭. (2001). Trees in each race were visually assessed from ground level for the percentage of the current seasons’ flower crop which were yet to open (white), and which were in flower (grey), and race averages are shown.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/4c9917e2-77e0-476d-a9f2-6fd04fcf250f2025Rebecca JonesBrad PottsJames ReidRene VaillancourtDean NicolleGreg JordanUniversity of Tasmania, Australia2004-122004-12northlimit=-36.9937783887252; southlimit=-44.3945421921559; westlimit=140.108642578125; eastlimit=151.885986328125; projection=WGS84https://orcid.org/0000-0002-6491-1423https://orcid.org/0000-0001-6244-289Xhttps://orcid.org/0000-0003-4317-0977https://orcid.org/0000-0002-1159-9149https://orcid.org/0009-0005-7463-836Xhttps://orcid.org/0000-0002-6033-2766https://orcid.org/0000-0001-5603-5024310804300703300707260204anthesiseucalyptusflowerfloweringTasmaniaVictoriaUTAS/c581456c-7e48-4c09-a683-504e318fd5f9University of Tasmania, Australiahttps://data.utas.edu.au/metadata/c581456c-7e48-4c09-a683-504e318fd5f9Appraisal-based emotion identification in urban search and rescue exercises using Roseman's model of emotion elicitation

https://data.utas.edu.au/metadata/c581456c-7e48-4c09-a683-504e318fd5f9

This dataset contains coded observational data collected from three Urban Search and Rescue (USAR) simulation exercises conducted in Australia and New Zealand between March and October 2024. Two of the exercises were official INSARAG External Reclassifications (IERs), and one was a full-scale mock exercise. Each exercise simulated an earthquake in a foreign country and involved continuous operations over a three-day period with approximately 100 participants, including commanders, rescue workers, and support staff. The dataset is comprised of 28 excerpts representing emotionally significant events observed during daylight operations (08:00–18:00), spanning approximately 90 hours of direct observation in total. Each excerpt is accompanied by a structured analysis applying five appraisal dimensions from Roseman’s model of emotion elicitation (goal consistency, motive consistency, agency, certainty, and control potential) culminating in the identification of a specific discrete emotion. The data are anonymised and adhere to UTAS Human Research Ethics Committee protocols.Attribution(BY)https://data.utas.edu.au/metadata/c581456c-7e48-4c09-a683-504e318fd5f92025Syed Adeel AkhtarSteven CurninBenjamin BrooksDarryl StellmachUniversity of Tasmania, Australia2024-032024-10https://orcid.org/0009-0005-9604-1548https://orcid.org/0000-0001-5248-7250https://orcid.org/0000-0002-0888-3288https://orcid.org/0000-0003-3845-6874https://orcid.org/0000-0001-5603-5024350703200406emotional intelligenceemotional elicitationUTAS/625a5c5f-ddc0-46fc-939d-36c033b9f8f6University of Tasmania, Australiahttps://data.utas.edu.au/metadata/625a5c5f-ddc0-46fc-939d-36c033b9f8f6Building parameter variation impacts on the energy efficiency performance and peak heating/cooling demand of low and high-performance lightweight detached dwellings in Australian cool temperate climates

https://data.utas.edu.au/metadata/625a5c5f-ddc0-46fc-939d-36c033b9f8f6

This dataset is comprised of the dwelling and material characteristics, simulation matrix, charts, and simulation results extracted, extrapolated and analysed from output files of the Australian Nationwide House Energy Rating Scheme (NatHERS) accredited software, AccuRate Sustainability (v2.4.3.21 SP1). The data were used to analyse the influence of key building parameter variations on the energy efficiency (expressed as NatHERS star ratings) and peak heating and cooling demands of lightweight detached dwellings. The scope includes unadapted, low-performance (<6-star) and adapted, high-performance (>6-star) dwellings within Australia's cool temperate climates. The simulation methodology is detailed in Chapters 3–7 of the associated PhD thesis '𝘉𝘶𝘪𝘭𝘥𝘪𝘯𝘨 𝘱𝘢𝘳𝘢𝘮𝘦𝘵𝘦𝘳 𝘷𝘢𝘳𝘪𝘢𝘵𝘪𝘰𝘯 𝘪𝘮𝘱𝘢𝘤𝘵𝘴 𝘰𝘯 𝘵𝘩𝘦 𝘦𝘯𝘦𝘳𝘨𝘺 𝘦𝘧𝘧𝘪𝘤𝘪𝘦𝘯𝘤𝘺 𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦 𝘢𝘯𝘥 𝘱𝘦𝘢𝘬 𝘩𝘦𝘢𝘵𝘪𝘯𝘨 𝘢𝘯𝘥 𝘤𝘰𝘰𝘭𝘪𝘯𝘨 𝘥𝘦𝘮𝘢𝘯𝘥 𝘰𝘧 𝘭𝘰𝘸 𝘢𝘯𝘥 𝘩𝘪𝘨𝘩-𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦 𝘭𝘪𝘨𝘩𝘵𝘸𝘦𝘪𝘨𝘩𝘵 𝘥𝘦𝘵𝘢𝘤𝘩𝘦𝘥 𝘥𝘸𝘦𝘭𝘭𝘪𝘯𝘨𝘴 𝘪𝘯 𝘈𝘶𝘴𝘵𝘳𝘢𝘭𝘪𝘢𝘯 𝘤𝘰𝘰𝘭 𝘵𝘦𝘮𝘱𝘦𝘳𝘢𝘵𝘦 𝘤𝘭𝘪𝘮𝘢𝘵𝘦𝘴' by Soo Kang Jack Tan, and the data files themselves support Chapters 4-7 of the thesis. The chapters are also supported by publications that are in the manuscript stage of production at the time of creation of this data record. The underlying AccuRate software models are not included in this dataset but can be requested by contacting the principal supervisor, Dr. Mark Dewsbury (mark.dewsbury@utas.edu.au), or the author (jack.tan@utas.edu.au).Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/625a5c5f-ddc0-46fc-939d-36c033b9f8f62025Jack Soo Kang TanUniversity of Tasmania, Australia20222025east=147.101440429688; north=-41.4015355828985; projection=WGS84https://orcid.org/0009-0005-8079-7754https://orcid.org/0000-0002-3607-3637https://orcid.org/0000-0001-5603-5024330102170199AccuRate SustainabilityNatHERSsimulationUTAS/7a130d09-42b2-4e67-bd45-22d1c557edb2University of Tasmania, Australiahttps://data.utas.edu.au/metadata/7a130d09-42b2-4e67-bd45-22d1c557edb2KoDeRR (Knowledge of Dementia Risk Reduction) instrument - October 2019

https://data.utas.edu.au/metadata/7a130d09-42b2-4e67-bd45-22d1c557edb2

This is the source data for the KoDeRR (Knowledge of Dementia Risk Reduction) instrument. This is the pilot data from the ISLAND survey wave - October 2019.Attribution(BY)https://data.utas.edu.au/metadata/7a130d09-42b2-4e67-bd45-22d1c557edb22025Alex KitsosKathleen DohertyClaire EcclestonUniversity of Tasmania, Australia2019-102019-12northlimit=-39.410733055085; southlimit=-44.1270280065; westlimit=143.470458984375; eastlimit=151.116943359375; projection=WGS84https://orcid.org/0000-0003-4319-1559https://orcid.org/0000-0002-0122-0123https://orcid.org/0000-0002-7913-6888420699200502200499Knowledge of Dementia Risk ReductionWicking Dementia Research and Education CentreUTAS/6aee06ab-1c21-4446-8fcd-ecb756b3dc4dUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/6aee06ab-1c21-4446-8fcd-ecb756b3dc4dPhenology and architecture associations generated from a chickpea diversity panel measured in natural and glasshouse environments

https://data.utas.edu.au/metadata/6aee06ab-1c21-4446-8fcd-ecb756b3dc4d

These data are outputs of the project: Improving The Adaptation And Profitability Of High Value Pulses (Chickpea And Lentil) Across Australian Agroecological Zones - GRDC Project Code UOT1909-002RTX. This dataset contains the genomic locations of SNP and haplotype associations detected for phenology traits measured across a chickpea diversity panel. The phenotypes were collected from the panel grown in three environments: in the field at Mount Barker, WA in 2008, a second planting in 2009, and in glasshouse conditions at Floreat, WA in 2021.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/6aee06ab-1c21-4446-8fcd-ecb756b3dc4d2025Jakob ButlerJames WellerRaul Ortega MartinezJacqueline Vander SchoorJens BergerUniversity of Tasmania, Australiahttps://orcid.org/0000-0003-1353-3765https://orcid.org/0000-0003-2423-8286https://orcid.org/0000-0001-5827-6630https://orcid.org/0000-0002-3813-5678https://orcid.org/0000-0002-8978-5099https://orcid.org/0000-0001-5603-5024310509260303280102chickpeaphenologyarchitectureGWASUTAS/6963f505-b744-4cb3-91a3-0a7a9935c186University of Tasmania, Australiahttps://data.utas.edu.au/metadata/6963f505-b744-4cb3-91a3-0a7a9935c186Phenology and architecture associations generated from a lentil diversity panel measured in long day, short day and field environments

https://data.utas.edu.au/metadata/6963f505-b744-4cb3-91a3-0a7a9935c186

These data are outputs of the project: Improving The Adaptation And Profitability Of High Value Pulses (Chickpea And Lentil) Across Australian Agroecological Zones - GRDC Project Code UOT1909-002RTX. This dataset contains the genomic locations of SNP and haplotype associations detected for architecture and phenology traits measured across a lentil diversity panel. The phenotypes were collected from the panel grown in three environments: in a short day photoperiod at the University of Tasmania, TAS in a natural long day photoperiod at a nearby nursery, and in the field at Horsham, VIC.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/6963f505-b744-4cb3-91a3-0a7a9935c1862025Jakob ButlerYang DaiJacqueline Vander SchoorRaul Ortega MartinezJames WellerArun Sivakumar ShunmugamUniversity of Tasmania, Australiahttps://orcid.org/0000-0003-1353-3765https://orcid.org/0000-0001-5954-6364https://orcid.org/0000-0002-3813-5678https://orcid.org/0000-0001-5827-6630https://orcid.org/0000-0003-2423-8286https://orcid.org/0000-0003-0282-3150https://orcid.org/0000-0001-5603-5024310509260303280102lentilphenologyarchitectureGWASUTAS/55ef7253-9bb8-4267-a63e-920f92657fd4University of Tasmania, Australiahttps://data.utas.edu.au/metadata/55ef7253-9bb8-4267-a63e-920f92657fd4Mapped Agricultural Land Capability Classification Data for Australia V.30

https://data.utas.edu.au/metadata/55ef7253-9bb8-4267-a63e-920f92657fd4

This data record contains a national agricultural land capability map for Australia, based on state agricultural land capability datasets reclassified to a single agricultural land capability classification (NSW method) and modeled grazing suitability. The data includes three raster layers (provided as GeoTIFF land_capability). The national scale agricultural land capability map is the primary data product available in the agricultural land capability data package (raster layer with 9 classes adhering to the NSW land capability mapping method definitions). The compiled state and territory land capability data on the unified rating class system is available as a sub product of the agricultural land capability data package (existing_capability GeoTIFF). Pastoral capability based upon modeled grazing suitability is available as a sub product of the agricultural land capability data package (pastoral_capability GeoTIFF). This data version now includes a zip file for those that wish to download the data as GeoTIFF layers and a geodatabase version for those that wish to access the layers as raster layers within an ArcGIS .gdb. It is recommended to select the appropriate file for download based on your intended usage.Attribution(BY)https://data.utas.edu.au/metadata/55ef7253-9bb8-4267-a63e-920f92657fd42025Vanessa AdamsJayden EngertUniversity of Tasmania, Australia2019 - presentnorthlimit=-10.6433329969502; southlimit=-44.5153100248151; westlimit=110.625000447035; eastlimit=154.394531697035; projection=WGS84UTAS/965ccbeb-6748-4c67-ad0e-56481e97780ahttps://orcid.org/0000-0002-3509-7901https://orcid.org/0000-0002-5558-2058https://orcid.org/0000-0001-5603-5024410401300203180603190207Agricultural land capabilityLand capacityLand suitabilitycroppinggrazinghorticultureforestryUTAS/119f5f11-30f3-47ed-ad0b-b07f4380b2e4University of Tasmania, Australiahttps://data.utas.edu.au/metadata/119f5f11-30f3-47ed-ad0b-b07f4380b2e4Phenology and architecture QTL for chickpea discovered in three F2 populations (CDC Frontier x ICCV96029, CDC Frontier x ICC5810, CDC Frontier x ICC16644) measured in long day and short day photoperiods

https://data.utas.edu.au/metadata/119f5f11-30f3-47ed-ad0b-b07f4380b2e4

These data are outputs of the project: Improving The Adaptation And Profitability Of High Value Pulses (Chickpea And Lentil) Across Australian Agroecological Zones - GRDC Project Code UOT1909-002RTX. This dataset contains the genomic position of QTLs in chickpea for phenology and architecture traits generated through three bi-parental F2 populations created by crossing CDC Frontier with ICCV96029, ICC5810 and ICC16644, grown in long day and short day photoperiods in a glasshouse.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/119f5f11-30f3-47ed-ad0b-b07f4380b2e42025Jakob ButlerJames WellerRaul Ortega MartinezJacqueline Vander SchoorEsmat SarafrazUniversity of Tasmania, Australiahttps://orcid.org/0000-0003-1353-3765https://orcid.org/0000-0003-2423-8286https://orcid.org/0000-0001-5827-6630https://orcid.org/0000-0002-3813-5678https://orcid.org/0009-0003-8067-0310https://orcid.org/0000-0001-5603-5024310509260303280102chickpeaphenologyQTLarchitectureUTAS/9c4fc660-802b-4a6d-84d7-9cba3d7ac560University of Tasmania, Australiahttps://data.utas.edu.au/metadata/9c4fc660-802b-4a6d-84d7-9cba3d7ac560Phenology and architecture QTL for lentil discovered in an Indianhead x ILL5888 F2 population measured in long day and short day photoperiods

https://data.utas.edu.au/metadata/9c4fc660-802b-4a6d-84d7-9cba3d7ac560

These data are outputs of the project: Improving The Adaptation And Profitability Of High Value Pulses (Chickpea And Lentil) Across Australian Agroecological Zones - GRDC Project Code UOT1909-002RTX. This dataset contains the genomic position of QTLs for phenology and architecture traits generated through a bi-parental F2 cross between lentil accessions Indianhead (late flowering) and ILL5888 (early flowering) grown in long day and short day photoperiods in a glasshouse.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/9c4fc660-802b-4a6d-84d7-9cba3d7ac5602025Jakob ButlerYang DaiJacqueline Vander SchoorRaul Ortega MartinezJames WellerUniversity of Tasmania, Australiahttps://orcid.org/0000-0003-1353-3765https://orcid.org/0000-0001-5954-6364https://orcid.org/0000-0002-3813-5678https://orcid.org/0000-0001-5827-6630https://orcid.org/0000-0003-2423-8286https://orcid.org/0000-0001-5603-5024310509260303280102lentilphenologyQTLarchitectureUTAS/67a5f750-0eee-4093-871b-48fe9c93caf0University of Tasmania, Australiahttps://data.utas.edu.au/metadata/67a5f750-0eee-4093-871b-48fe9c93caf0Balancing mould risk and energy efficient design of 6- and 7-Star southeastern Australian clay masonry external wall systems

https://data.utas.edu.au/metadata/67a5f750-0eee-4093-871b-48fe9c93caf0

This dataset presents the hygrothermal and bio-hygrothermal performance of brick veneer-clad external walls under the 6- and 7-Star energy efficiency standards, following ASHRAE-prescribed conditioning. The results focus on the risks of surface and interstitial moisture accumulation, as well as mould growth. Variations in Reference Meteorological Year (RMY) inputs—with and without rainfall—are also included.Attribution - NonCommercial - No Derivatives(BY - NC - ND)This data set is used for academic research and publication, all the rights reserved to data creators.https://data.utas.edu.au/metadata/67a5f750-0eee-4093-871b-48fe9c93caf02025Liqun (Antonia) GuanMark DewsburyFreya SuUniversity of Tasmania, Australia20222032northlimit=-41.4255423508487; southlimit=-41.4443643049873; westlimit=147.106338702219; eastlimit=147.170710884533; projection=WGS84https://orcid.org/0000-0002-6994-6721https://orcid.org/0000-0002-3607-3637https://orcid.org/0000-0002-7046-9416330206120105energy-efficientmoisture accumulationindoor mould growthphysicbuildingaustraliaUTAS/dc981c14-0466-4d2c-9085-0114ec0e5b58University of Tasmania, Australiahttps://data.utas.edu.au/metadata/dc981c14-0466-4d2c-9085-0114ec0e5b58Survey of Tasmanian benthic macroinvertebrate communities across an agricultural land-use gradient

https://data.utas.edu.au/metadata/dc981c14-0466-4d2c-9085-0114ec0e5b58

Macroinvertebrate community and environmental data from 18 cobble–pebble bedded streams across southern and north-west Tasmania across a gradient of upstream catchment conversion to agriculture, sampled in late summer 2021. Catchment land use was quantified in QGIS from state land-use surveys and aggregated into four categories (Uncleared, Forestry, Agriculture, Other). Field sampling included eight 30-second kick samples per site, with taxa identified to the finest feasible level (species/morphospecies for Ephemeroptera, Plecoptera and Trichoptera and others, genus/family/class as appropriate). The eight kick samples were pooled together for this data set. Environmental measurements included water quality (dissolved oxygen, temperature, conductivity, flow), stream morphology (depth, wetted/bankfull width), and substrate composition, with an interstitial sediment coefficient (ISC) calculated to estimate fine sediment levels.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/dc981c14-0466-4d2c-9085-0114ec0e5b582025Bridget WhiteLeon BarmutaUniversity of Tasmania, AustraliaLate summer 2021https://orcid.org/0000-0002-9040-5065https://orcid.org/0000-0002-8946-3727310304280120macroinvertebratesurveyagriculturediversityinvertebrateUTAS/ead9f51d-003d-4858-98e0-eaca79e9a2dcUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/ead9f51d-003d-4858-98e0-eaca79e9a2dcMacroinvertebrate and ecosystem function data from replicated in-stream experiments in Tasmanian streams (2021–2023)

https://data.utas.edu.au/metadata/ead9f51d-003d-4858-98e0-eaca79e9a2dc

This dataset is from an experiment testing stream community responses to catchment conversion to agriculture and short-term flow changes. We used a multiple before–after control–impact (mBACI) design across 8 Tasmanian streams (4 agricultural, 4 forested) during late summers of 2021–2023. Each stream contained three reaches (control, low flow, high flow). Flow was manipulated using temporary semi-porous weirs to create treatment conditions. Macroinvertebrate, physicochemical, and ecosystem function measurements were taken before, during, and after a disturbance (median 24.5 days, range 19–30), followed by a recovery (median 85 days, range 84–92). The sampling sequence was: Sample 1: pre-disturbance (baseline, all reaches), Samples 2–3: weekly during disturbance (weirs in place), Samples 4–6: monthly during recovery (post-weir removal). Macroinvertebrates were sampled with 0.25 m² box sampler; rocks scrubbed, fine material disturbed into 200 µm mesh net; preserved in 70% ethanol and identified to lowest practicable taxonomic level. Physicochemical variables were spot measures of temperature, pH, conductivity, dissolved oxygen (Hach HQ40d), and flow (Schiltknecht MiniAir 2); continuous temperature logging at controls using HOBO loggers and Derwent Estuary Program data. Ecosystem functions were leaf decomposition (mesh bags with ~5 g dried green Eucalyptus viminalis leaves, 45 per site (3 × 15 per treatment/control), retrieved at 5 intervals; leaves dried (40 °C, ~48 h) and weighed; negative controls corrected for transport/set-up loss); cellulose decomposition (45 unbleached cotton strips (65 × 35 mm; EMPA, Switzerland) per site, on submerged ropes, retrieved at 5 intervals; tensile strength loss measured with Salter ElectroSamson scales); algal accrual (45 unglazed ceramic tiles (25 × 25 mm) per site, retrieved at 5 intervals; chlorophyll a extracted with 90% ethanol and quantified spectrophotometrically).Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/ead9f51d-003d-4858-98e0-eaca79e9a2dc2025Bridget WhiteLeon BarmutaUniversity of Tasmania, AustraliaSummers of 2021-2022 and 2022-2023https://orcid.org/0000-0002-9040-5065https://orcid.org/0000-0002-8946-3727310304280120macroinvertebratetraitsriverfield experimentflowecosystem functionUTAS/1bbb0a03-ff2e-49a4-9a96-6b5805becb71University of Tasmania, Australiahttps://data.utas.edu.au/metadata/1bbb0a03-ff2e-49a4-9a96-6b5805becb71Supplementary Data File for Thesis - Chantelle J Beagley

https://data.utas.edu.au/metadata/1bbb0a03-ff2e-49a4-9a96-6b5805becb71

This file contains all supplementary data referenced in the PhD Thesis "A genetic dissection of domestication in the two legumes, pea and common bean, as a contribution towards a comparative understanding of crop evolution" by Chantelle J Beagley.Attribution(BY)https://data.utas.edu.au/metadata/1bbb0a03-ff2e-49a4-9a96-6b5805becb712025Chantelle BeagleyUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-4254-0510310599310510310509310506260303GeneticsCommon beanPhaseolus vulgarisPeaPisumMolecular geneticsCrop domesticationCrop evolutionLegumesUTAS/b942d40a-03d6-4c2a-9980-6c768888116eUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/b942d40a-03d6-4c2a-9980-6c768888116eThe Impact of Rain in Representative Climate Data in Hygrothermal Simulation

https://data.utas.edu.au/metadata/b942d40a-03d6-4c2a-9980-6c768888116e

The Impact of Rain in Representative Climate Data in Hygrothermal Simulation is a paper that analysises the effects of different types of rain input in jrepresentative climate datasets used in hygrothermal simulation. The dataset comprises the input representative climate datasets used in this paper and the results of hygrothermal simulations, water content and mould growth index, these data were then processed into a python script that generated graphs. The hygrothermal WUFI simulation files are included for completeness.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/b942d40a-03d6-4c2a-9980-6c768888116e2025Freya SuMark DewsburyUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7046-9416https://orcid.org/0000-0002-3607-3637330105120205rainhygrothermal simulationclimate databuilding performancedata sciencemouldUTAS/7abbe963-b243-487f-be3f-6ae94fdd161eUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/7abbe963-b243-487f-be3f-6ae94fdd161eMature tall wet Eucalyptus forests resist the spread of severe regrowth forest fires under moderate fire weather conditions

https://data.utas.edu.au/metadata/7abbe963-b243-487f-be3f-6ae94fdd161e

Using pre- and post-wildfire data of forest structure, surface fuel loads and understory temperature we investigated fire severity patterns in areas of mature and logged tall wet Eucalyptus forests in southeastern Tasmania that burned under moderate fire weather conditions. We found all regrowth forest patches in the study area were burned, at significantly higher severely than mature forests that comprised 98% of the fire perimeter. Regrowth forests were more flammable that mature forests with high consumption of live fuels, especially in the lower half of the 30 m regrowth profile, compared to the more modest effects across the burned and unburned mature forest 40 to 60 m profiles. Two years after the fire, fine fuel loads of regrowth and mature forest had returned to pre-fire levels, and resprouting enabled rapid recovery of vegetation structure. This archive contains code and source data for the statistical models of structure, fuels and microclimate associated with this study.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/7abbe963-b243-487f-be3f-6ae94fdd161e2025Grant WilliamsonDavid BowmanLynda PriorArko LucieerJames FurlaudLiu ZhaoUniversity of Tasmania, Australia20142021northlimit=-42.9091659251865; southlimit=-43.149594957605; westlimit=146.502685546875; eastlimit=146.992950439453; projection=WGS84https://orcid.org/0000-0002-3469-7550https://orcid.org/0000-0001-8075-124Xhttps://orcid.org/0000-0002-5511-2320https://orcid.org/0000-0002-9468-4516https://orcid.org/0000-0003-3925-0130https://orcid.org/0009-0006-8273-8042410205300706300703190401260204eucalyptuswet forestregrowthold growthwarratasmaniariveaux roadfirebushfireUTAS/eae8a7c6-a79d-4586-b983-4a8e08cf387eUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/eae8a7c6-a79d-4586-b983-4a8e08cf387eValidation of SWOT Satellite Observations in Bass Strait

https://data.utas.edu.au/metadata/eae8a7c6-a79d-4586-b983-4a8e08cf387e

Data and software supporting research presented in Earth and Space Science publication "In Situ Geometric Validation of SWOT Satellite Observations in Bass Strait, Australia", Hay et al., 2025. The analysis is conducted with data from the Bass Strait altimetry validation facility during the SWOT fast sampling phase (FSP) from 2023-03-30 to 2023-07-10. The zipped files "Bass_Strait_SWOT_calval_data.zip" and "Bass_Strait_SWOT_calval_software.zip" contain data and python jupyter notebooks, with further descriptions in the README.txtAttribution(BY)https://data.utas.edu.au/metadata/eae8a7c6-a79d-4586-b983-4a8e08cf387e2025Andrea HayChristopher Watsonbenoit legresyMatt KingBoye ZhouAlejandro BoheUniversity of Tasmania, Australia2023-03-302023-07-10northlimit=-39.973752789808; southlimit=-41.3669151508102; westlimit=144.610839814413; eastlimit=146.579589780886; projection=WGS84https://orcid.org/0000-0001-9556-0059https://orcid.org/0000-0002-7464-4592https://orcid.org/0000-0002-1909-1630https://orcid.org/0000-0001-5611-9498https://orcid.org/0000-0001-7281-3228https://orcid.org/0000-0001-6024-1330370603370803401305180506altimetryGNSSvalidationSWOTUTAS/b12b1dbb-f821-49ec-925d-bdb1372f4f78University of Tasmania, Australiahttps://data.utas.edu.au/metadata/b12b1dbb-f821-49ec-925d-bdb1372f4f78Exploring composition and within-population variation in the phloem exudate “manna” in Eucalyptus viminalis

https://data.utas.edu.au/metadata/b12b1dbb-f821-49ec-925d-bdb1372f4f78

Dataset of E.viminalis trees sampled for manna at Queens Domain reserve and associated R markdown code used for analysis.Attribution - NonCommercial - No Derivatives(BY - NC - ND)This dataset is shared under a CC BY-NC-ND 4.0 license. For reuse beyond non-commercial viewing or citation (e.g. in publications, analyses, or derivative work), please contact the author to request permission.https://data.utas.edu.au/metadata/b12b1dbb-f821-49ec-925d-bdb1372f4f782025Erin BokJulianne O'Reilly-WapstraUniversity of Tasmania, Australia2021-082023-02east=147.325834035873; north=-42.8669452754876; projection=WGS84https://orcid.org/0000-0003-4661-9151https://orcid.org/0000-0003-4801-4412310303310308180606eucalyptsapflowfoundation speciesecosystemUTAS/0646da89-1ba3-4bbb-8d54-934d26a8157cUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/0646da89-1ba3-4bbb-8d54-934d26a8157cWarming, Heatwave and Rain Manipulation Experimental Research

https://data.utas.edu.au/metadata/0646da89-1ba3-4bbb-8d54-934d26a8157c

A three-factor (Warming, Drought, Heatwave) climate manipulation experiment was conducted in the Tasmanian highlands in a subalpine plant community on Bucks Marsh, Silver Plains over three years. Plant community composition data was taken annually from each of 32 plots alongside soil volumetric water content and air temperature measurements taken every 30 minutes. The annual heatwave event was logged at a finer time resolution and following the event, plant fluorescence measurements were captured for common species. These data and some associated code are uploaded here.Attribution(BY)https://data.utas.edu.au/metadata/0646da89-1ba3-4bbb-8d54-934d26a8157c2025Melissa GerwinShane A. RichardsElizabeth WandragMark HovendenUniversity of Tasmania, Australia20212024east=147.087621688843; north=-42.0903885392301; projection=WGS84https://orcid.org/0000-0003-0072-2786https://orcid.org/0000-0002-9638-5827https://orcid.org/0000-0001-8140-539Xhttps://orcid.org/0000-0001-7208-9700310302190504Climate changePlant communitysubalpinewarmingdroughtheatwavediversitycompositionUTAS/f17d2767-dcb1-44eb-b3c4-3afda56df18cUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/f17d2767-dcb1-44eb-b3c4-3afda56df18cDecadal changes in California’s temperate mesophotic reef invertebrate community through the 2014-2016 Northeast Pacific marine heatwave

https://data.utas.edu.au/metadata/f17d2767-dcb1-44eb-b3c4-3afda56df18c

This repository contains R scripts and datasets used for the analysis presented in "Decadal changes in California’s temperate mesophotic reef invertebrate community through the 2014-2016 Northeast Pacific marine heatwave". The code includes workflows for data processing, interpolation, and visualisation of bottom temperature climatology and anomalies. All analyses were conducted in R (version 2.2.2) to ensure full reproducibility. Biological data are derived from remotely operated vehicle (ROV) surveys conducted by the California Department of Fish and Wildlife (CDFW) and Marine Applied Research and Exploration (MARE) between 2005 and 2021. Surveys targeted marine protected areas (MPAs) and adjacent reference sites, following a standardised protocol for long-term monitoring. Sites were selected based on survey coverage across three periods: pre-2014, during the 2014–2016 marine heatwave (MHW), and post-2016. Environmental data include NOAA OI SST V2 High Resolution Dataset (NOAA PSL) and monthly mean seawater potential temperature from the GLORYS12V1 product (Copernicus Marine Service).Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/f17d2767-dcb1-44eb-b3c4-3afda56df18c2025Rachel WongUniversity of Tasmania, Australia20052021northlimit=47.0044532974432; southlimit=30.812204720112; westlimit=-126.973266992454; eastlimit=-118.955236175516; projection=WGS84https://orcid.org/0000-0002-6550-5646310305180501MesophoticcaliforniaimageryMarine heatwavetemperateUTAS/c5aa3a46-b566-4b1d-8bea-4076ec93f659University of Tasmania, Australiahttps://data.utas.edu.au/metadata/c5aa3a46-b566-4b1d-8bea-4076ec93f659Global fire and lightning seasonality

https://data.utas.edu.au/metadata/c5aa3a46-b566-4b1d-8bea-4076ec93f659

Using a 0.25-degree resolution based on the ERA5 reanalysis product, these data present two interlinked products reflecting the seasonality of fire, lightning, and ignition patterns. The fire season product ('fire_season') reflects season definitions of potential ignitions based on a) localised fine fuel flammability thresholds (see DOI:10.25959/rbk3-5d65) and b) lightning stroke density. Season definitions are simplified to reflect the initiation and cessation day of the year (1-365). The global land use product ('global_land_use') reflects associated statistics, including the a) lengths of periods within each fire season where ignitions are driven predominantly by anthropogenic or mixed (i.e., anthropogenic and lightning) ignitions, b) total and proportional burned area (via MODIS burned area product, 2001-2024) occurring within each of the aforementioned ignition periods, c) mean MODIS-based vegetation productivity (2001-2023), and d) mean annual suppression intensity and fractional burned area attributed to human land management (1991-2014).Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/c5aa3a46-b566-4b1d-8bea-4076ec93f6592025Todd EllisGrant WilliamsonDavid BowmanUniversity of Tasmania, Australia19912020https://orcid.org/0000-0002-4410-8676https://orcid.org/0000-0002-3469-7550https://orcid.org/0000-0001-8075-124Xhttps://orcid.org/0000-0001-5603-5024300706370201370202310402410205190102190401190508climate changefire ecologyfire riskfire seasonalityignition patternslightningpyrogeographyUTAS/0bfb2557-6763-45fb-b5cc-0faaab4026f1University of Tasmania, Australiahttps://data.utas.edu.au/metadata/0bfb2557-6763-45fb-b5cc-0faaab4026f1Grm: deriving covariance kernels and simulating phenotypes

https://data.utas.edu.au/metadata/0bfb2557-6763-45fb-b5cc-0faaab4026f1

GRM is a C++ program designed to derive covariance kernels from genetic data and approximate the nearest positive-semidefinite kernel using Higham’s method. It also enables phenotype simulation by sampling from a multivariate normal distribution.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/0bfb2557-6763-45fb-b5cc-0faaab4026f12025Juan Manuel PeraltaUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-8811-5579https://orcid.org/0000-0002-9774-1539310207280102grmkernelpositive-semidefinite matrix approximationhighamUTAS/f785409a-f559-4d82-8b66-7a5000af937aUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/f785409a-f559-4d82-8b66-7a5000af937aBamstream and vcfconcat: tools for streamlining the joint-calling of genomic data

https://data.utas.edu.au/metadata/f785409a-f559-4d82-8b66-7a5000af937a

Bamstream and vcfconcat are specialized C++ tools designed to streamline genomic data processing. Bamstream consolidates short sequencing reads from multiple BAM files aligned to the same reference genome into a metadata-consistent multi-sample alignment stream, with a focus on efficient parallelization by operating on specific genomic regions. Vcfconcat resolves variation call conflicts in the overlapping ends of adjacent regions within gVCF files, prioritizing variants with higher quality scores to ensure accurate and consistent outputs for downstream analysis.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/f785409a-f559-4d82-8b66-7a5000af937a2025Juan Manuel PeraltaUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-8811-5579https://orcid.org/0000-0002-9774-1539310206280102bamstreamvcfconcatUTAS/427c31cd-d486-43c5-a077-9d5f936608c8University of Tasmania, Australiahttps://data.utas.edu.au/metadata/427c31cd-d486-43c5-a077-9d5f936608c8Data from "Mammalian Browsers Disrupt Eco‐Evolutionary Dynamics in a Forest Tree Restoration Planting"

https://data.utas.edu.au/metadata/427c31cd-d486-43c5-a077-9d5f936608c8

Estimated least-squares means for the 22 geographic regions (paired populations of E. ovata and E. pauciflora), the associated bioclimate variables and the derived principal components that summarises the bioclimatic data into three independent gradients. Multiple individuals of each species from each geographic region were planted in a common-garden field trial, inside and outside a herbivore exclusion zone. Height data is from age 3-year measurements and survival data is from age 8-year assessment.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/427c31cd-d486-43c5-a077-9d5f936608c82025Peter HarrisonJoao Costa e SilvaBrad PottsUniversity of Tasmania, AustraliaHeight data is off 3-year old individual plants; survival data is from 8-year old individual plantseast=147.132253646851; north=-41.8281303509222; projection=WGS84https://orcid.org/0000-0002-3502-0242https://orcid.org/0000-0003-1422-9554https://orcid.org/0000-0001-6244-289X310403310406319902410405180604190102assisted migrationherbivore-plant interactionstree survival and height growthdifferentiation of tree species and provenancesfamily varianceclimate adaptation and modellingUTAS/73b33c74-66da-492b-96bb-02c8f9ed15d5University of Tasmania, Australiahttps://data.utas.edu.au/metadata/73b33c74-66da-492b-96bb-02c8f9ed15d5Data from "An expert system to quantify wildfire hazards in gardens and create effective defensible space"

https://data.utas.edu.au/metadata/73b33c74-66da-492b-96bb-02c8f9ed15d5

This is the deidentified data used in: Ondei, S., Williamson, G. J., Foyster, S., & Bowman, D. M. (2025). An expert system to quantify wildfire hazards in gardens and create effective defensible space. International Journal of Disaster Risk Reduction, 121, 105424. The publication is available open access at https://www.sciencedirect.com/science/article/pii/S2212420925002481. Please cite this publication when using the data for your research.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/73b33c74-66da-492b-96bb-02c8f9ed15d52025Stefania OndeiUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-2515-3316410205330308190401Defensible spaceGarden designHouse lossRural-urban interfaceTasmaniaWildland-urban interfaceWildfiresUTAS/b7d4672a-0929-46e4-9aa2-d651ebc6561fUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/b7d4672a-0929-46e4-9aa2-d651ebc6561fMaterial from PhD thesis: Chapter 6 PRS Supplementary Files

https://data.utas.edu.au/metadata/b7d4672a-0929-46e4-9aa2-d651ebc6561f

This dataset contains supplemental material as part of a PhD thesis: Identification of Shared Genetic Risk Loci between Hypertensive Disorders of Pregnancy and Later-Life Cardiovascular Disease. The material supports Chapter 6: Genetic Dissection of Polygenic Risk Scores (PRS) for Cardiovascular Disease (CVD) Following Hypertensive Disorders of Pregnancy (HDP), which focuses on analysing existing PRS related to CVD from the PGS Catalog and examining whether they differ significantly between HDP-CAD (coronary artery disease) groups. It includes details of 1,022 CVD PRS from the PGS Catalog as of 3 January 2024, along with a subset of female-specific PRS. The dataset contains results comparing the number of PRS that matched with at least 75% of genetic variants in the BHS population. It also includes PRS that remained significant after bootstrapping 95% confidence intervals from Models 1 and 2 following ridge regression. ANOVA results assess PRS differences across HDP-CAD categories before and after adjustment for multiple testing, while logistic regression summary statistics are provided for models with and without HDP, analysing their association with CAD. These analyses contribute to understanding the genetic risk factors linking HDP and later-life CVD, emphasising PRS stratification, sex-specific effects, and statistical significance.Attribution(BY)https://data.utas.edu.au/metadata/b7d4672a-0929-46e4-9aa2-d651ebc6561f2025Gayathry KrishnamurthyPhillip MeltonUniversity of Tasmania, Australia20222025https://orcid.org/0000-0002-0819-9398https://orcid.org/0000-0003-4026-2964310506310509310505310207280103200509280102PRSPolygenic risk scoreGeneticsCardiovascular diseaseHypertensive disorders of pregnancyUTAS/9f49f0cc-d323-4d29-9aca-30192c28ae64University of Tasmania, Australiahttps://data.utas.edu.au/metadata/9f49f0cc-d323-4d29-9aca-30192c28ae64Material from PhD thesis: Chapter 5 GWAS Supplementary Files

https://data.utas.edu.au/metadata/9f49f0cc-d323-4d29-9aca-30192c28ae64

This dataset contains supplemental material as part of a PhD thesis: Identification of Shared Genetic Risk Loci between Hypertensive Disorders of Pregnancy and Later-Life Cardiovascular Disease. The material supports Chapter 5: Identifying Shared Genetic Risk Loci Between Hypertensive Disorders of Pregnancy and Later-Life Cardiovascular Disease: A Genome-Wide Association Study (GWAS). It includes GWAS summary statistics for Models 1-6, detailing genome-wide and suggestive genetic associations. In addition, it provides eQTL mapping results and chromatin interaction mapping summaries for Model 6. These analyses contribute to understanding the genetic links between hypertensive disorders of pregnancy and cardiovascular disease by identifying significant variants, gene expression associations, and potential regulatory mechanisms.Attribution(BY)https://data.utas.edu.au/metadata/9f49f0cc-d323-4d29-9aca-30192c28ae642025Gayathry KrishnamurthyPhillip MeltonUniversity of Tasmania, Australia20212025https://orcid.org/0000-0002-0819-9398https://orcid.org/0000-0003-4026-2964310506310509310508310505310207280103200509280102GWASGenome-wide association studyGeneticsCadiovascular diseaseHypertensive disorders of pregnancyUTAS/5ec73656-f69f-4820-b84b-e72cd26bd295University of Tasmania, Australiahttps://data.utas.edu.au/metadata/5ec73656-f69f-4820-b84b-e72cd26bd295Genotype, mapping and internode length phenotype data from an F2 population derived from a cross between a wild and domesticated common bean

https://data.utas.edu.au/metadata/5ec73656-f69f-4820-b84b-e72cd26bd295

This dataset contains the genotype locus file for MapQTL, raw internode length phenotype data and flowering loci genotyping, MapQTL traitfiles, and linkage mapping file generated from an F2 population derived from a cross between a wild (G12873) and domesticated (Midas) common bean. Genotype data was obtained through DArT, and the linkage map was generated using the JoinMap program. The F2 population was grown under long-day conditions.Attribution(BY)https://data.utas.edu.au/metadata/5ec73656-f69f-4820-b84b-e72cd26bd2952025Chantelle BeagleyJacqueline Vander SchoorJakob ButlerJames WellerUniversity of Tasmania, Australiaeast=147.323969900608; north=-42.9050716856641; projection=WGS84https://orcid.org/0000-0002-4254-0510https://orcid.org/0000-0002-3813-5678https://orcid.org/0000-0003-1353-3765https://orcid.org/0000-0003-2423-8286310510260303legumescommon beanQTL analysisInternode lengthelongationplant architecturelinkage mappingUTAS/7b4e48d3-9d2e-49ac-b781-a6715f411947University of Tasmania, Australiahttps://data.utas.edu.au/metadata/7b4e48d3-9d2e-49ac-b781-a6715f411947Material from PhD thesis: Appendix A-1 List of samples from live Tasmanian devils and spotted-tail quolls.

https://data.utas.edu.au/metadata/7b4e48d3-9d2e-49ac-b781-a6715f411947

This dataset contains supplemental material as part of a PhD thesis: Development of Novel Diagnostic Tools and Antigen Discovery for Devil Facial Tumour Disease. The material includes a list of samples collected from wild and live Tasmanian devils (Sarcophilus harrisii) and spotted-tail quolls (Dasyurus maculatus) which were taken as part of an annual monitoring field trapping trip in 2023 at Narawntapu National Park. The list also contains name, sex, net weight, estimated birth year, microchip number, and whether there was clinical signs of devil facial tumour disease.Attribution(BY)https://data.utas.edu.au/metadata/7b4e48d3-9d2e-49ac-b781-a6715f4119472025Anuk KruawanAndrew FliesUniversity of Tasmania, Australia2023-072023-07northlimit=-41.0604805387003; southlimit=-41.1882384959651; westlimit=146.535987854004; eastlimit=146.811332702637; projection=WGS84https://orcid.org/0000-0002-7974-6643https://orcid.org/0000-0002-4550-1859https://orcid.org/0000-0001-5603-5024310905320211300906241602280103280101diagnosticcancercrisprTasmanian devilDFTDdevil facial tumourUTAS/e3a0f870-5c40-4ad3-b2b8-17c8c22c368cUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/e3a0f870-5c40-4ad3-b2b8-17c8c22c368cElectric Vehicle Charger Test Data - Dynamic Grid Response

https://data.utas.edu.au/metadata/e3a0f870-5c40-4ad3-b2b8-17c8c22c368c

A number of electric vehicles and chargers, commercially available (in Australia), have been systematically tested, using state of the art laboratory test and measurement equipment, while being exposed to a range of well-defined electrical grid conditions (voltage and frequency). Tested conditions include disturbances typically experienced in power systems, both in Australia and other parts of the world, during normal operation and during short-term contingency conditions. These datasets contain electrical voltage and current data for a number of tests, which may then be used by other researchers or stakeholders for purposes of analysis and modelling. Datasets are .mat files, which may be easily loaded and read using Matlab, with data structures being clearly labelled. Each .mat file contains high res (0.1 ms) timeseries data for RMS voltage, current, active power, and reactive power; each .mat file is named with EV type (A, B, C, D...), tested fault voltage and fault duration. Any use of the data or for publication or otherwise sharing should acknowledge the School of Engineering at UTAS for testing and measurement and for providing data. For more information on test set-up, analysis of some test data and, from the data, the development of dynamic EV load models suitable for power system simulations can be found in the journal IEEE Transactions on Industry Applications: N. McKillop, C. Wembridge, S. Ransome, E. Franklin and J. Lord, "Practical Testing and Modelling of Electric Vehicle Charger Responses During Power System Faults," in IEEE Transactions on Industry Applications, vol. TBD, 2025, doi: TBD [Note: article is still under review at date of publication of this data, 3 Feb 2025. However, interested data users can simply search for the paper using the article title listed above, or may request a copy from the data authors].Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/e3a0f870-5c40-4ad3-b2b8-17c8c22c368c2025Evan FranklinNathan McKillopChristopher WembridgeUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-8146-2770https://orcid.org/0009-0001-9246-4093https://orcid.org/0000-0002-5863-9427400805170305Electric Vehicle Test DataFault Ride ThroughDynamic BehaviourElectricity GridsElectrical Fault ToleranceLoad ModellingUTAS/886c7d97-bbd3-448e-bdfa-52ef757aeb1cUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/886c7d97-bbd3-448e-bdfa-52ef757aeb1cRubicon estuary native saltmarsh spatial change data

https://data.utas.edu.au/metadata/886c7d97-bbd3-448e-bdfa-52ef757aeb1c

At the Rubicon estuary in North Tasmania, native marsh changes were evaluated at three sites 1946-2023 using two spatial methods, shoreline movement and marsh polygonal area.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/886c7d97-bbd3-448e-bdfa-52ef757aeb1c2025Nesyah SargisonJoanna EllisonUniversity of Tasmania, Australia19462023northlimit=-41.1519035540231; southlimit=-41.1808503813366; westlimit=146.545944213867; eastlimit=146.608772277832; projection=WGS84https://orcid.org/0009-0004-1849-5715https://orcid.org/0000-0003-0692-8347410402180202180203SaltmarshAustraliaspatial areaShoreline change rateTasmaniaRubicon estuaryUTAS/1c45a10b-eec9-4b05-982c-59d73cf7d999University of Tasmania, Australiahttps://data.utas.edu.au/metadata/1c45a10b-eec9-4b05-982c-59d73cf7d999Havre Volcano RR1506 Voyage Report

https://data.utas.edu.au/metadata/1c45a10b-eec9-4b05-982c-59d73cf7d999

This is the voyage report for RR1506 voyage to Havre volcano in 2015. Citation: Soule, S., and Carey, R. 2015. Mapping, Exploration and Sampling at Havre Volcano. RR1506. Voyage Report.Attribution(BY)https://data.utas.edu.au/metadata/1c45a10b-eec9-4b05-982c-59d73cf7d9992025Rebecca CareyUniversity of Tasmania, Australia2015-032015-04northlimit=-31.4973779366551; southlimit=-33.3156353646809; westlimit=179.456214308739; eastlimit=181.863652467728; projection=WGS84https://orcid.org/0000-0003-2015-6419370504370512370599280107HavreKermadecvolcanovoyage reportMESHRR1506UTAS/a67922b4-5a8e-4b7f-8716-5cc4aa126da6University of Tasmania, Australiahttps://data.utas.edu.au/metadata/a67922b4-5a8e-4b7f-8716-5cc4aa126da6Mixed-Mode Polymerizable Eutectics

https://data.utas.edu.au/metadata/a67922b4-5a8e-4b7f-8716-5cc4aa126da6

Data for mixed-mode polymerizable eutectic project December 2024Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/a67922b4-5a8e-4b7f-8716-5cc4aa126da62024Alexandra MutchStuart ThickettUniversity of Tasmania, AustraliaUTAS/80353798-0b98-4ab4-86c6-7fca1612e575https://orcid.org/0000-0002-9010-9047https://orcid.org/0000-0002-8168-3856340302340306401609120304240910240699polymerizable eutecticUTAS/ff900f05-a18a-44f5-8689-0cfefd7f6dd3University of Tasmania, Australiahttps://data.utas.edu.au/metadata/ff900f05-a18a-44f5-8689-0cfefd7f6dd3REVISED DEC 2024 Geospatial data for tectonic model development

https://data.utas.edu.au/metadata/ff900f05-a18a-44f5-8689-0cfefd7f6dd3

This dataset consists of various raster and gpkg feature classes which formed most of the data used to guide construction of tectonic elements and GPlates model discussed in chapters 3 and 4 of the thesis. Most of these datasets are from freely-available government sources. Those which were mentioned in the thesis but not included in this data package are predominantly sourced from supplementary data packages in other research studies. A README file is contained with more information.Attribution(BY)https://data.utas.edu.au/metadata/ff900f05-a18a-44f5-8689-0cfefd7f6dd32024Thomas SchaapUniversity of Tasmania, Australianorthlimit=-6.31529853833003; southlimit=-74.6832503005186; westlimit=108.6328125; eastlimit=206.71875; projection=WGS84UTAS/ae75e1f7-e2c6-4b7b-9440-33542dc79b2ehttps://orcid.org/0000-0002-4189-3760https://orcid.org/0000-0001-5603-5024370511370604250399tectonicgeochronologyUTAS/ce4e6035-6976-424a-ad8e-a4407e9fe1fbUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/ce4e6035-6976-424a-ad8e-a4407e9fe1fbREVISED Dec2024: Lachlan Orogen GPlates model

https://data.utas.edu.au/metadata/ce4e6035-6976-424a-ad8e-a4407e9fe1fb

REVISED as of Dec 2024. Model data and GPlates project file for Cambrian-Devonian reconstruction of the Lachlan Orogen integrated into a global model (Wright et al., 2013 - doi:10.5194/bg-10-1529-2013). All spatial datasets are provided in .gpml format and rotation files in .grot format.Attribution(BY)https://data.utas.edu.au/metadata/ce4e6035-6976-424a-ad8e-a4407e9fe1fb2024Thomas SchaapSebastien MeffreJoanne WhittakerMatthew CracknellUniversity of Tasmania, AustraliaPalaeozoicnorthlimit=-26.745610382199; southlimit=-75.4971573189308; westlimit=143.0859375; eastlimit=184.21875; projection=WGS84UTAS/6c85d9d6-0d8b-4629-a92a-bdea084cf890https://orcid.org/0000-0002-4189-3760https://orcid.org/0000-0003-2741-6076https://orcid.org/0000-0002-3170-3935https://orcid.org/0000-0001-9843-8251https://orcid.org/0000-0001-5603-5024370604370502370508370511250399plate tectonicsgplatesUTAS/2f215081-8607-4089-b321-f83cf3f217edUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/2f215081-8607-4089-b321-f83cf3f217edImpacts of small scale tropsophere variability on SWOT satellite

https://data.utas.edu.au/metadata/2f215081-8607-4089-b321-f83cf3f217ed

Data and software supporting the research presented in GRL publication "Small scale variability in the wet troposphere impacts the interpretation of SWOT satellite observations", Hay et al., 2025. The analysis covers Australian coastal regions during the SWOT fast sampling phase from 2023-03-30 to 2023-07-10. The zipped files "SWOT_troposphere_investigations_data.zip" and "SWOT_troposphere_investigations_software.zip" contain the relevant data and python jupyter notebooks, with further descriptions in the README.txt.Attribution(BY)https://data.utas.edu.au/metadata/2f215081-8607-4089-b321-f83cf3f217ed2024Andrea HayChristopher WatsonMatt Kingbenoit legresyJack BeardsleyUniversity of Tasmania, Australia2023-03-30 to 2023-07-10northlimit=-9.18887008447339; southlimit=-44.5278427984555; westlimit=109.951171875; eastlimit=156.357421875; projection=WGS84https://orcid.org/0000-0001-9556-0059https://orcid.org/0000-0002-7464-4592https://orcid.org/0000-0001-5611-9498https://orcid.org/0000-0002-1909-1630https://orcid.org/0000-0003-4486-0267370603370803401305180506altimetryGNSSvalidationtroposphereUTAS/445f346a-4f66-42af-8c36-90e9e3144196University of Tasmania, Australiahttps://data.utas.edu.au/metadata/445f346a-4f66-42af-8c36-90e9e3144196Material from PhD thesis: Appendix C-8 Mirror plots for likely misidentified LTR peptides

https://data.utas.edu.au/metadata/445f346a-4f66-42af-8c36-90e9e3144196

This dataset contains supplemental material as part of a PhD thesis: Development of Novel Diagnostic Tools and Antigen Discovery for Devil Facial Tumour Disease. The material contains a list of mirror plots comparing mass spectra between experimental (top) and synthetic (bottom) peptides. These plots show LTR candidates that were likely a result of misidentification. The raw data were generated as part of a published study (https://doi.org/10.1111/imm.13307). Peptides were identified via the database search pipeline using PEAKS® Studio (Bioinformatics Solutions Inc). Pearson correlation coefficient was then calculated for each comparison.Attribution(BY)https://data.utas.edu.au/metadata/445f346a-4f66-42af-8c36-90e9e31441962024Anuk KruawanAndrew FliesUniversity of Tasmania, Australia20212024northlimit=-40.0964579121214; southlimit=-44.4195592385336; westlimit=143.94287109375; eastlimit=149.17236328125; projection=WGS84https://orcid.org/0000-0002-7974-6643https://orcid.org/0000-0002-4550-1859https://orcid.org/0000-0001-5603-5024310905320211300906241601280103280101proteomicDFTDTasmania devilmass speccancerimmunologyvaccineUTAS/e86fd5c3-717c-4ab4-83a5-8905f9d53d8bUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/e86fd5c3-717c-4ab4-83a5-8905f9d53d8bMaterial from PhD thesis: Appendix C-7 List of identified peptides and synthetic peptides

https://data.utas.edu.au/metadata/e86fd5c3-717c-4ab4-83a5-8905f9d53d8b

This dataset contains supplemental material as part of a PhD thesis: Development of Novel Diagnostic Tools and Antigen Discovery for Devil Facial Tumour Disease. The material contains a full list of peptides identified in Tasmanian devil healthy tissue and DFT1 and DFT2 immunopeptidomes with a false discovery rate (FDR) of 5%. The raw data were generated as part of a published study (https://doi.org/10.1111/imm.13307). Peptides were identified via the database search pipeline using PEAKS® Studio (Bioinformatics Solutions Inc). The list consists of peptides identified from the Tasmanian devil's reference proteomes and the list of long-terminal repeats (LTRs) derived from endogenous retroviral elements (ERVs). The dataset also contains the peptide abundance.Attribution(BY)https://data.utas.edu.au/metadata/e86fd5c3-717c-4ab4-83a5-8905f9d53d8b2024Anuk KruawanAndrew FliesUniversity of Tasmania, Australia20212024northlimit=-40.2048370592182; southlimit=-44.2223218854529; westlimit=143.624267578125; eastlimit=149.117431640625; projection=WGS84https://orcid.org/0000-0002-7974-6643https://orcid.org/0000-0002-4550-1859https://orcid.org/0000-0001-5603-5024310905320211300906280103280101241601proteomicTasmanian devilimmunologyvaccineDFTDERVLTRcancerUTAS/a0dad5a8-119b-4973-9528-f9b5c8b73abbUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/a0dad5a8-119b-4973-9528-f9b5c8b73abbMaterial from PhD thesis: Appendix C-2 Repeat elements identified in Tasmanian devil's genome

https://data.utas.edu.au/metadata/a0dad5a8-119b-4973-9528-f9b5c8b73abb

This dataset contains supplemental material as part of a PhD thesis: Development of Novel Diagnostic Tools and Antigen Discovery for Devil Facial Tumour Disease. The material contains a list of repeat elements identified from the Tasmanian devil's genome for the differential expression analysis and Tasmanian devil facial tumour disease antigen discovery for vaccine development. The RepeatMasker package was used to identify repeat elements on the Tasmanian devil's whole-genome sequence (mSarHar1.11). This was generated as part of a published study (https://doi.org/10.1126/science.abq6453).Attribution(BY)https://data.utas.edu.au/metadata/a0dad5a8-119b-4973-9528-f9b5c8b73abb2024Anuk KruawanMaximilian StammnitzAndrew FliesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7974-6643https://orcid.org/0000-0002-1704-9199https://orcid.org/0000-0002-4550-1859https://orcid.org/0000-0001-5603-5024310905320211300906280103280101241601vaccinecancerTasmanian devilDFTDimmunologyRNA-seqproteomicUTAS/c6531794-6877-4eb0-bfaa-9467a0b8bbb7University of Tasmania, Australiahttps://data.utas.edu.au/metadata/c6531794-6877-4eb0-bfaa-9467a0b8bbb7Material from PhD thesis: Appendix C-1 List of RNA-seq datasets

https://data.utas.edu.au/metadata/c6531794-6877-4eb0-bfaa-9467a0b8bbb7

This dataset contains supplemental material as part of a PhD thesis: Development of Novel Diagnostic Tools and Antigen Discovery for Devil Facial Tumour Disease. The material contains a list of RNA-seq datasets used for the differential expression analysis for Tasmanian devil facial tumour disease vaccine antigen discovery. RNA samples were sourced from wild/captive Tasmanian devils (as early as 2003) and from cell lines. The dataset includes paired-end and single-end RNA-seq datasets from 30 primary DFT1, 4 DFT1 cell line c5065, 5 primary DFT2 primary, 4 DFT2 cell line RV, and 2 DFT2 cell line JV, 8 whole blood, 2 ear fibroblast, 5 spleens, 5 hearts, 5 testis, 38 lips, 4 brains, 2 peripheral nerves, 2 blood vessels, 2 axillary nerves, 2 brachial plexus nerves, 2 brain stems, 2 cerebellums, 2 cerebrums, 2 optic nerves, 2 sciatic nerves, and 4 trigeminal nerves.Attribution(BY)https://data.utas.edu.au/metadata/c6531794-6877-4eb0-bfaa-9467a0b8bbb72024Anuk KruawanAndrew FliesUniversity of Tasmania, Australia20032024northlimit=-40.154474076012; southlimit=-44.1908205398717; westlimit=143.162841796875; eastlimit=149.293212890625; projection=WGS84https://orcid.org/0000-0002-7974-6643https://orcid.org/0000-0002-4550-1859https://orcid.org/0000-0001-5603-5024310905320211300906280103280101241601DFTDTasmanian devilRNA-seqvaccineERVLTRproteomicUTAS/d6890a79-70cd-4bd5-8a34-72b4b6cb577eUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/d6890a79-70cd-4bd5-8a34-72b4b6cb577eMaterial from PhD thesis: Appendix A-3 RPA primers and crRNA

https://data.utas.edu.au/metadata/d6890a79-70cd-4bd5-8a34-72b4b6cb577e

This dataset contains supplemental material as part of a PhD thesis: Development of Novel Diagnostic Tools and Antigen Discovery for Devil Facial Tumour Disease. The material contains a list of recombinase polymerase amplification (RPA) primers and LwCas13a CRISPR RNA (crRNA) for the amplification and detection of DFT1, DFT2, RPL13a, and ZIKV. The material also includes a list of primer combinations. The best-performing primer pair and crRNA for each target are indicated. These primers and crRNA were used in the development of CRISPR-based point-of-care diagnostic tools, termed specific high-sensitivity enzymatic reporter unlocking (SHERLOCK), to identify DFT1 and DFT2 in the field with limited instrumentation.Attribution(BY)https://data.utas.edu.au/metadata/d6890a79-70cd-4bd5-8a34-72b4b6cb577e2024Anuk KruawanAndrew FliesUniversity of Tasmania, Australia20222024northlimit=-40.4051304422217; southlimit=-44.2247334454171; westlimit=143.749512657523; eastlimit=149.444825425744; projection=WGS84https://orcid.org/0000-0002-7974-6643https://orcid.org/0000-0002-4550-1859https://orcid.org/0000-0001-5603-5024310905320211300906241602280103280101diagnosticcancercrisprTasmanian devilUTAS/d0e82753-51dc-4cf2-8505-ca1675fae937University of Tasmania, Australiahttps://data.utas.edu.au/metadata/d0e82753-51dc-4cf2-8505-ca1675fae937Assessing mechanisms of intrinsic vulnerability in sharks occupying different marine environments

https://data.utas.edu.au/metadata/d0e82753-51dc-4cf2-8505-ca1675fae937

Metadataset to assess the vulnerability of sharks occupying different marine environments. Dataset contains collated information on taxonomic classification, life history traits, maximum depth recorded, reproductive strategies and habitats occupied by 544 shark species.Attribution(BY)NAhttps://data.utas.edu.au/metadata/d0e82753-51dc-4cf2-8505-ca1675fae9372024Sushmita MukherjiNils KrueckUniversity of Tasmania, Australiahttps://orcid.org/0000-0003-4646-6538https://orcid.org/0000-0003-2090-1423300505310408180501sharklife-historyIUCNUTAS/313afa88-ea44-46d5-8114-f5adeb7cc53aUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/313afa88-ea44-46d5-8114-f5adeb7cc53aAre Australia’s volcanic-forests “biogeographic continental islands”? - Raw Downloaded Data

https://data.utas.edu.au/metadata/313afa88-ea44-46d5-8114-f5adeb7cc53a

Raw Data downloaded from Public Domains: Occurrence (presence-only) data of all vascular plant species were collated from state-based herbaria and databases of field surveys across eastern Australian to ensure a wide coverage of endemic species distributions. Data sources included Queensland WildNet (Department of Environment and Science, Queensland Government, 2022), NSW Bionet Atlas (including ACT observations) (Office of Environment and Heritage, 2024), Victorian Biodiversity Atlas (Department of Energy, Environment and Climate Action, 2024), Tasmanian Natural Values Atlas (Department of Natural Resources and Environment Tasmania, 2024), and the Australasian Virtual Herbarium (AVH) (Council of Heads of Australasian Herbaria, 2022a).Attribution(BY)https://data.utas.edu.au/metadata/313afa88-ea44-46d5-8114-f5adeb7cc53a2024Ngoc NguyenUniversity of Tasmania, Australianorthlimit=-9.71311790736767; southlimit=-44.5307798221068; westlimit=137.8564453125; eastlimit=155.2587890625; projection=WGS84https://orcid.org/0000-0002-4231-9170310308180606ecologybiogeographyendemismUTAS/f02df274-f80d-4a0a-86d0-b6f40af22be6University of Tasmania, Australiahttps://data.utas.edu.au/metadata/f02df274-f80d-4a0a-86d0-b6f40af22be6Elevated CO2 reduces leaf elongation rates and maximum leaf length in perennial ryegrass in Southern Tasmania

https://data.utas.edu.au/metadata/f02df274-f80d-4a0a-86d0-b6f40af22be6

In a Free-Air Carbon Enrichment site (FACE) in Tasmania, we investigated pasture grass (perennial ryegrass) responses to elevated CO2 and irrigation frequency and amount. We assessed the impacts of treatments on leaf growth traits such as leaf elongation rates and leaf size of perennial ryegrass over two years. These traits include leaf elongation rate of leaf one, two and three, maximum leaf lengths, total length of all leaves combined, total leaf elongation rates of all leaves combined, number of days to maximum length of leaf 1, 2 and 3, and internode (blade separation) length.Attribution(BY)https://data.utas.edu.au/metadata/f02df274-f80d-4a0a-86d0-b6f40af22be62024Mark HovendenUniversity of Tasmania, Australia20202022east=147.426030635834; north=-42.8017771730621; projection=WGS84https://orcid.org/0000-0001-7208-9700410102260699climate changepasturegrasslandcarbon dioxideplant growthUTAS/652c6c0c-6bf5-4017-86da-95dbe90ac2a1University of Tasmania, Australiahttps://data.utas.edu.au/metadata/652c6c0c-6bf5-4017-86da-95dbe90ac2a1Data from: Restoring landscape burning is compatible with conservation and livestock production in a southeast Australian grassland fragment

https://data.utas.edu.au/metadata/652c6c0c-6bf5-4017-86da-95dbe90ac2a1

These data are from a landscape burning experiment on private property in the Tasmanian Midlands, which was designed to explore the ecological effects of returning fire to a long unburnt grassland-woodland remnant. Three data files are included: i) camera trap data – recording the responses of vertebrate herbivores to burning; ii) scat transect data – recording the responses of vertebrate herbivores to burning, and; iii) vegetation quadrat data – recording the responses of broad vegetation composition and herbaceous biomass to burning and herbivore exclosure treatments.Attribution(BY)https://data.utas.edu.au/metadata/652c6c0c-6bf5-4017-86da-95dbe90ac2a12024Ben FrenchLynda PriorDavid BowmanUniversity of Tasmania, Australia20182020northlimit=-42.0308764727623; southlimit=-42.0610885301785; westlimit=147.520551681519; eastlimit=147.58303642273; projection=WGS84https://orcid.org/0000-0001-5046-4047https://orcid.org/0000-0002-5511-2320https://orcid.org/0000-0001-8075-124X410205180606eucalypt woodlandgrassland burningpyric herbivoryrangeland conservationrestoring fireTasmanian Midlandstemperate savannaUTAS/243b39c3-f63a-4179-afb5-8d7b0a5ab2e6University of Tasmania, Australiahttps://data.utas.edu.au/metadata/243b39c3-f63a-4179-afb5-8d7b0a5ab2e6Adaptive interventions for advancing in situ wildlife disease management

https://data.utas.edu.au/metadata/243b39c3-f63a-4179-afb5-8d7b0a5ab2e6

Observation dates, average (sarcoptic) mange scores, and fluralaner doses (mg/kg) for bare-nosed wombats (Vombatus ursinus) at Cape Portland, Tasmania, Australia.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/243b39c3-f63a-4179-afb5-8d7b0a5ab2e62024Vicky WilkinsonScott CarverShane RichardsChristina Naesborg-NielsenLeah BurgessKate MounseyUniversity of Tasmania, Australia2021-032022-07northlimit=-40.7417946379549; southlimit=-40.7919791181096; westlimit=147.957515716553; eastlimit=148.038883209229; projection=WGS84https://orcid.org/0000-0001-5620-2646https://orcid.org/0000-0002-3579-7588https://orcid.org/0000-0002-9638-5827https://orcid.org/0000-0001-9997-5593https://orcid.org/0000-0002-0786-654Xhttps://orcid.org/0000-0003-0579-9424410407410401300909180602130404Sarcoptic mangeBare-nosed wombatadaptivefluralanerinterventionSarcoptes scabieitreatmentUTAS/49c9eccd-de00-4a39-82a3-59fee49857dfUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/49c9eccd-de00-4a39-82a3-59fee49857dfLens images of AB and TL wildtype zebrafish strains

https://data.utas.edu.au/metadata/49c9eccd-de00-4a39-82a3-59fee49857df

The lenses of the 4dpf zebrafish larva were live imaged and photographed using Differential Interference Contrast (DIC) illumination, using an inverted microscope (Nikon Eclipse Ti-E) equipped with Zyla 4.2 PLUS sCMOS camera (Zyla 4.2, Andor) and NIS-Elements AR acquisition software (Nikon). AB, TL and mCherry zebrafish lines were used. Images were collected from multiple clutches. The broodstocks used in producing those clutches were obtained from multiple housing tanks in our facility. The images are in .tif file format. Images are named as Strain_TankNumber_ClutchNumber_ImageNumber. For each fish, a single lens image was captured. Images were evaluated for cataracts using the ImageJ program. The evaluation process adhered to the guidelines set forth by Zhao et al., 2021, which included an assessment of the severity of the cataracts. In addition to lens images, the cataract score sheet is provided. Clutch-wise and tank-wise statistics on cataract occurrences were computed, and the accompanying R scripts used for these calculations are included.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/49c9eccd-de00-4a39-82a3-59fee49857df2024Bibek KhatiwadaKathryn BurdonJohanna JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0001-9754-6525https://orcid.org/0000-0001-8217-1249https://orcid.org/0000-0002-6475-9134310903321201310599280102cataractzebrafishgeneticsstrainUTAS/ea77cd75-75a0-4a8d-9173-2003362fa3f8University of Tasmania, Australiahttps://data.utas.edu.au/metadata/ea77cd75-75a0-4a8d-9173-2003362fa3f8A Geological Imprint on Plant Biodiversity: Eastern Australia's Cenozoic Volcanic Flora - Field Data

https://data.utas.edu.au/metadata/ea77cd75-75a0-4a8d-9173-2003362fa3f8

- Field data collected from South-east Queensland and Tasmania as part of the study investigating biodiversity and species richness in eastern Australia.Attribution(BY)https://data.utas.edu.au/metadata/ea77cd75-75a0-4a8d-9173-2003362fa3f82024Ngoc NguyenUniversity of Tasmania, Australia2021-06-212022-02-13northlimit=-24.5271348225978; southlimit=-44.213709909702; westlimit=143.173828125; eastlimit=157.236328125; projection=WGS84https://orcid.org/0000-0002-4231-9170https://orcid.org/0000-0002-2491-1517https://orcid.org/0000-0001-6737-7468310308180601280111terrestrial vascular plantsbiodiversityspecies richnessUTAS/1d0dc779-6470-4a19-bc48-3ef9bc700002University of Tasmania, Australiahttps://data.utas.edu.au/metadata/1d0dc779-6470-4a19-bc48-3ef9bc700002PhD thesis - "Environmental and health associations with ectoparasite presence on a coastal sentinel, the little penguin"

https://data.utas.edu.au/metadata/1d0dc779-6470-4a19-bc48-3ef9bc700002

This data record presents raw and processed data for modelling input based on little penguin ectoparasite ecology. These data have been collected as part of a PhD project investigating the health of little penguins as sentinels of Tasmanian ecosystem health (UTAS Animal Ethics # 23764).Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/1d0dc779-6470-4a19-bc48-3ef9bc7000022024Melanie WellsScott CarverMary-Anne LeaUniversity of Tasmania, Australia20202023northlimit=-39.4446778393865; southlimit=-44.1837799920115; westlimit=143.041992858052; eastlimit=150.864258483052; projection=WGS84https://orcid.org/0000-0003-2817-8743https://orcid.org/0000-0002-3579-7588https://orcid.org/0000-0001-8318-9299https://orcid.org/0000-0001-5603-5024310303310305310909280108ectoparasiteseabird sentinelphysiologypenguinparasitismUTAS/d0b72b27-4102-4878-96fc-b7287b4a382aUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/d0b72b27-4102-4878-96fc-b7287b4a382aSupplementary document for 'Children's Questions on Climate Change Focus on Climate Action, Impacts, Existential Concerns, and Science'

https://data.utas.edu.au/metadata/d0b72b27-4102-4878-96fc-b7287b4a382a

This dataset is drawn from publicly available material on the Curious Climate Schools website www.curiousclimate.org.au/schools that is used in our research article 'Children's Questions on Climate Change Focus on Climate Action, Impacts, Existential Concerns, and Science' in One Earth.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/d0b72b27-4102-4878-96fc-b7287b4a382a2024Chloe LucasCharlotte JonesGabi MocattaKim BeasyRachel KellyGretta PeclUniversity of Tasmania, Australia20212022northlimit=-40.351365255679; southlimit=-43.7212650912207; westlimit=143.807119131088; eastlimit=148.988901525736; projection=WGS84https://orcid.org/0000-0002-0834-1622https://orcid.org/0000-0002-6322-1551https://orcid.org/0000-0001-6093-8330https://orcid.org/0000-0002-5998-1419https://orcid.org/0000-0002-8364-1836https://orcid.org/0000-0003-0192-4339440610390201190103childrenyoung peopleclimate changeclimate distressclimate anxietyeducationcitizenshipempowermentengagementUTAS/5bb3e49b-a5a1-402f-9e98-8bac1c39598aUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/5bb3e49b-a5a1-402f-9e98-8bac1c39598aWater market trading data

https://data.utas.edu.au/metadata/5bb3e49b-a5a1-402f-9e98-8bac1c39598a

Datasets to support "Water Market Development in Tasmania" study, by Kelvin Montanaro and Joanna EllisonAttribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/5bb3e49b-a5a1-402f-9e98-8bac1c39598a2023Kelvin MontanaroJoanna EllisonUniversity of Tasmania, Australiasee methodology section belowhttps://orcid.org/0009-0009-2746-1353https://orcid.org/0000-0003-0692-8347370901190211Water trading; Irrigation; Catchment; Victoria; Tasmania; Seasonal trends; Water policyUTAS/e3aacf7a-7708-402c-b98b-1e2fed66168aUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/e3aacf7a-7708-402c-b98b-1e2fed66168aForb germination data

https://data.utas.edu.au/metadata/e3aacf7a-7708-402c-b98b-1e2fed66168a

This dataset presents seed germination counts for three forb species (𝘈𝘳𝘵𝘩𝘳𝘰𝘱𝘰𝘥𝘪𝘶𝘮 𝘧𝘪𝘮𝘣𝘳𝘪𝘢𝘵𝘶𝘮, 𝘉𝘶𝘭𝘣𝘪𝘯𝘦 𝘣𝘶𝘭𝘣𝘰𝘴𝘢, 𝘔𝘪𝘤𝘳𝘰𝘴𝘦𝘳𝘪𝘴 𝘸𝘢𝘭𝘵𝘦𝘳𝘪) exposed to five temperature treatments, measured at four or five time points. Values represent the numbers of germinated seeds at a given time point for a given temperature treatment. Germination counts at 𝘵₄ (for 𝘔. 𝘸𝘢𝘭𝘵𝘦𝘳𝘪) and 𝘵₅ (𝘈. 𝘧𝘪𝘮𝘣𝘳𝘪𝘢𝘵𝘶𝘮, 𝘉. 𝘣𝘶𝘭𝘣𝘰𝘴𝘢) represent the number of seeds germinated after being placed into the putative optimal germination temperatures for these species. The dataset supports the publication '𝘐𝘯𝘵𝘳𝘢𝘴𝘱𝘦𝘤𝘪𝘧𝘪𝘤 𝘷𝘢𝘳𝘪𝘢𝘵𝘪𝘰𝘯 𝘢𝘯𝘥 𝘤𝘭𝘪𝘮𝘢𝘵𝘦 𝘥𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘵𝘪𝘢𝘭𝘭𝘺 𝘴𝘩𝘢𝘱𝘦 𝘵𝘩𝘦 𝘵𝘩𝘦𝘳𝘮𝘢𝘭 𝘨𝘦𝘳𝘮𝘪𝘯𝘢𝘵𝘪𝘰𝘯 𝘯𝘪𝘤𝘩𝘦𝘴 𝘰𝘧 𝘵𝘩𝘳𝘦𝘦 𝘤𝘰-𝘰𝘤𝘤𝘶𝘳𝘳𝘪𝘯𝘨 𝘸𝘰𝘰𝘥𝘭𝘢𝘯𝘥 𝘧𝘰𝘳𝘣𝘴' accepted for publication in Austral Ecology in 2024.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/e3aacf7a-7708-402c-b98b-1e2fed66168a2023Peter HarrisonUniversity of Tasmania, Australia20182018https://orcid.org/0000-0002-3502-0242https://orcid.org/0000-0001-5603-5024310406410102410401410405180604190102Bulbine bulbosaArthropodium fimbriatumMicrosersis walteriforbseed germinationthermal germination nicheclimate change vulnerabilityintraspecific variationUTAS/3a2d9dcf-f8fa-4514-aab0-b9d36f5a1983University of Tasmania, Australiahttps://data.utas.edu.au/metadata/3a2d9dcf-f8fa-4514-aab0-b9d36f5a1983Mega-Efficient Wildlife Classifier (MEWC) Case Study

https://data.utas.edu.au/metadata/3a2d9dcf-f8fa-4514-aab0-b9d36f5a1983

We provide training, test and inference data for the Mega-Efficient Wildlife Classifier (MEWC) workflow, using an example camera-trap dataset collected and curated by Barry Brook and Jessie Buettel, from Tasmania, Australia. These images are drawn from a variety of environmental contexts (dry and wet temperate eucalypt forest, woodland, and grasslands) using white-, infra-red (IR) and no-glow flash types from Cuddeback, Reconyx, Swift and Bushnell cameras. The following species or aggregated classes are represented in the dataset: Tasmanian Pademelon (Thylogale billardierii), Bennetts Wallaby (Notamacropus rufogriseus), Tasmanian Devil (Sarcophilus harrisii), Feral Cat (Felis catus), Bare-nosed Wombat (Vombatus ursinus), Brushtail Possum (Trichosurus vulpecula), Fallow Deer (Dama dama), Southern Brown Bandicoot (Isoodon obesulus), Currawong (Black: Strepera fuliginosa, Grey: S. versicolor) and Bronzewing (Brush: Phaps elegans, Common: P. chalcoptera). The latter two classes are birds, each of which consist of an aggregation of two species within a genus; the former eight are mammals. For implementing the classifier training, we provide 4,000 train and 1,000 test images for each of 10 different classes, for a total of 50,000 expert-labelled snips (each sized at 600- × 600-pixel, after being extracted from their original images using the MEWC-Snip tool). For demonstrating the detection, inference, and post-processing pipelines (EXIF writing and image sorting), we provide a sequence of 100 images for each of four field cameras that were not used in training, located on the lead author’s rural property in southern Tasmania: C3: IR flash, C7: white flash, C15: no-glow flash and C21: inbuilt IR flash. Other than the target wildlife, these images include some representations of blank images, humans (the lead author), and vehicles (trail-bike motorcycle), to demonstrate the four broad classes designated by the MegaDetector prior to classification on the animal images.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/3a2d9dcf-f8fa-4514-aab0-b9d36f5a19832023Barry BrookJessie BuettelUniversity of Tasmania, Australia20182023northlimit=-39.4581977454144; southlimit=-43.7599365319079; westlimit=143.668212890625; eastlimit=148.590087890625; projection=WGS84https://orcid.org/0000-0002-2491-1517https://orcid.org/0000-0001-6737-7468https://orcid.org/0009-0003-6198-0460https://orcid.org/0000-0002-9412-8288410407461103180601180606wildlifecamera trapTasmaniadetectionclassificationinferencefield siteecological communitymammalbirddeep learningartificial intelligenceVaughan PM, Buettel JC, Brook BW, 'Investigating avian behaviour using opportunistic camera-trap imagery reveals an untapped data source', Ornithological Science, 21, (1) pp. 3-12. ISSN 1347-0558 (2022) [Refereed Article]10.2326/osj.21.3Cunningham CX, Comte S, McCallum H, Hamilton DG, Hamede R, Storfer A, Hollings T, Ruiz-Aravena M, Kerlin DH, Brook BW, Hocking G, Jones Menna, 'Quantifying 25 years of disease-caused declines in Tasmanian devil populations: host density drives spatial pathogen spread', Ecology Letters, 24, (5) pp. 958-969. ISSN 1461-0248 (2021) [Refereed Article]10.1111/ele.13703Fielding MW, Cunningham CX, Buettel JC, Stojanovic D, Yates LA, Jones ME, Brook BW, 'Dominant carnivore loss benefits native avian and invasive mammalian scavengers', Royal Society of London Proceedings B Biological Sciences, 289, (1985) Article 20220521. ISSN 1471-2954 (2022) [Refereed Article]10.1098/rspb.2022.0521Paton AJ, Buettel JC, Brook BW, 'Evaluating scat surveys as a tool for population and community assessments', Wildlife Research ISSN 1035-3712 (2021) [Refereed Article]10.1071/WR21056Ringwaldt EM, Brook BW, Carver S, Buettel JC, 'The patterns and causes of dermatitis in terrestrial and semi-aquatic mammalian wildlife', Animals, 11, (6) Article 1691. ISSN 2076-2615 (2021) [Refereed Article]10.3390/ani11061691UTAS/b5f0f519-bea7-4a0d-84e7-95c9f38e11aaUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/b5f0f519-bea7-4a0d-84e7-95c9f38e11aaData from PhD thesis “Spatial variation in body condition of a coastal sentinel, the little penguin, reflects marine and terrestrial processes.”

https://data.utas.edu.au/metadata/b5f0f519-bea7-4a0d-84e7-95c9f38e11aa

This data record presents raw and processed data for modelling input based on little penguin body condition, with accompanying code. These data have been collected as part of a PhD project, investigating the health of little penguins, as sentinels of Tasmanian ecosystem health (UTAS Animal Ethics # 23764).Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/b5f0f519-bea7-4a0d-84e7-95c9f38e11aa2023Melanie WellsScott CarverMary-Anne LeaUniversity of Tasmania, Australia20202022northlimit=-39.317300373271; southlimit=-43.4305832263666; westlimit=143.191405981779; eastlimit=150.292970091105; projection=WGS84https://orcid.org/0000-0003-2817-8743https://orcid.org/0000-0002-3579-7588https://orcid.org/0000-0001-8318-9299https://orcid.org/0000-0001-5603-5024310303310305310907280102penguinseabirdphysiologyhealthconditionUTAS/b540bd4e-bd00-42ff-b779-a5b9402ddb98University of Tasmania, Australiahttps://data.utas.edu.au/metadata/b540bd4e-bd00-42ff-b779-a5b9402ddb98De-identified transcripts - Understanding the perspectives and needs of multiple stakeholders: Identifying key elements of a digital health intervention to protect against environmental hazards

https://data.utas.edu.au/metadata/b540bd4e-bd00-42ff-b779-a5b9402ddb98

This dataset holds the de-identified transcripts of interviews and focus groups with (a) health care professionals and (b) government agencies and non-government organisation representatives, regarding their perspectives on the smartphone app AirRater. AirRater is a smartphone environmental health app developed in Australia with the capability to collect individual health data and disseminate environmental hazard information to populations. Following on from evaluations involving app users, we wanted to understand key stakeholder knowledge and attitudes towards the app, as well as perceptions of its value, individual and/or organisational barriers to use, and opportunities to enhance the app. This study sought to explore these stakeholders' perspectives on the utility of environmental heath apps such as AirRater to support clinical and public health outcomes.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/b540bd4e-bd00-42ff-b779-a5b9402ddb982023Penelope JonesAnnabelle WorkmanFay Helena JohnstonSharon CampbellDavid BowmanChristopher LucaniUniversity of Tasmania, Australia20202020northlimit=-31.2034049509174; southlimit=-45.9511496866914; westlimit=140.141606926918; eastlimit=155.7861328125; projection=WGS84https://orcid.org/0000-0002-4880-6711https://orcid.org/0000-0002-4403-614Xhttps://orcid.org/0000-0002-5150-8678https://orcid.org/0000-0002-9788-5372https://orcid.org/0000-0001-8075-124Xhttps://orcid.org/0000-0001-8983-3575420699420302180101200499200406environmental healthallergiesasthmaAirRaterUTAS/fa1b6088-7031-4b0d-9bfe-b72147e5ea23University of Tasmania, Australiahttps://data.utas.edu.au/metadata/fa1b6088-7031-4b0d-9bfe-b72147e5ea23Tracking of serum lipid and lipoprotein levels from childhood and adolescence to adulthood: Systematic review and meta-analysis

https://data.utas.edu.au/metadata/fa1b6088-7031-4b0d-9bfe-b72147e5ea23

The dataset contains the data extracted from the studies included in the systematic review entitled "Tracking of serum lipid and lipoprotein levels from childhood and adolescence to adulthood: Systematic review and meta-analysis". Data was extracted from original empirical research journal articles published in MEDLINE, Embase, Web of Science (Core Collection), or Google Scholar databases before April 2022 that measured tracking of lipids from childhood or adolescence (defined as < 18 years of age) to adulthood (aged ≥ 18 years) using correlation coefficients or tracking coefficients. The dataset contains the following information extracted from each study: study name, study design, country where data were collected, type of lipid, effect estimate, tracking effect measure, variables used for adjustment (if any), sample size (total and by sex), sex, ethnicity (if stratified by ethnicity), age at baseline, length of follow-up, calendar years at baseline and follow-up, fasting status at baseline and follow-up as defined by the authors, number of measurements used to derive levels at baseline and follow-up, and measurement methods (e.g., assay, calculations). Analysis of the data is complete and the findings will be published in a scientific journal. The protocol of the systematic review is published in the International Prospective Register of Systematic Reviews, PROSPERO (protocol ID: CRD42020208859).Attribution - Share Alike(BY - SA)Requests for data may be directed to the custodians. Data may be used by researchers outside of the investigator team according to the terms of the license and provided that due ethics processes are adhered to and permission for use is granted by the custodians.https://data.utas.edu.au/metadata/fa1b6088-7031-4b0d-9bfe-b72147e5ea232023Oliver StanesbyCostan MagnussenUniversity of Tasmania, Australia19672018https://orcid.org/0000-0002-5996-5881https://orcid.org/0000-0002-6238-5730420207320101320504320202321301321302420605200104200101200201200206200407200105200412200506Lipidscholesteroltriglycerideschildadolescentsystematic reviewmeta-analysiscohort studiesUTAS/84cea31a-7dab-4038-acd7-de4c890cd50fUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/84cea31a-7dab-4038-acd7-de4c890cd50fData from Appendix B of "A systematic review of digital innovations in technology-enhanced learning designs in higher education"

https://data.utas.edu.au/metadata/84cea31a-7dab-4038-acd7-de4c890cd50f

These Excel (.xlsx) and .csv files contain summary information of the 130 publications included in 'A systematic review of digital innovations in technology-enhanced learning designs in higher education' by Choi-Lundberg et al., published in the Australasian Journal of Educational Technology (AJET), DOI: https://doi.org/10.14742/ajet.7615. Row 1 of the 'Appendix B' sheet contains the column headings, and these are also listed in Appendix B of the AJET article. Rows 2 to 131 contain the data for each of the 130 publications. Field of education codes (column I) are listed in cells I134 to I145, Kirkpatrick level codes (column O) are listed in cells O134 to O139, and Cook and Ellaway categories (column P) are listed in cells P134 to P141.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/84cea31a-7dab-4038-acd7-de4c890cd50f2023Derek Choi-LundbergKerryn Butler-HendersonKristyn HarmanJoseph CrawfordUniversity of Tasmania, Australia20142019https://orcid.org/0000-0002-3594-8585https://orcid.org/0000-0002-6082-2108https://orcid.org/0000-0002-0567-3736https://orcid.org/0000-0002-2191-6216https://orcid.org/0000-0001-5603-5024390405390303390199160102160304online learningblended learningtechnology-enhanced learningteaching and learning strategiescooperative and collaborative learninglearning communitiessystematic literature reviewUTAS/2e4f5e46-b472-47c0-bf18-3c266e1d6eacUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/2e4f5e46-b472-47c0-bf18-3c266e1d6eacIntegrated data for natural resource managers - V.2.0

https://data.utas.edu.au/metadata/2e4f5e46-b472-47c0-bf18-3c266e1d6eac

A compilation of Australian data that are (a) publicly available; and (b) use consistent measures across the continent. The compilation is deliberately broad - aiming to include variables that describe each of four 'capitals' (natural, human, social / institutional and financial/built). Our data set includes 6 unique files: 1) Metadata.xlsx: provides Data citations and license details for 37 unique data sources and all variable details as processed in this dataset 2) data_description_nrm_2023.html: Data description of variables and summary methods as output summary code 3) ibra_compile_2023.csv: tabular summary for IBRA regions 4) nrm_compile_2023.csv: tabular summary for NRM regions 5) NESP RL Hub IBRA subregions 2023.lpk: spatial layer package for IBRA regions 6) NESP RL Hub NRM regions 2023.lpk: spatial layer package for NRM regions The data presented here is provided under a Creative Commons CC-BY Attribution 3.0 Australia license. For the avoidance of doubt, this only applies to material as set out in this data record.Attribution(BY)The work undertaken to generate these data collections was funded by the Australian Government Department of Agriculture, Water and the Environment (DAWE) through the NESP Resilient Landscapes Hub. The data presented here is provided under a Creative Commons CC-BY Attribution 3.0 Australia license. For the avoidance of doubt, this only applies to material as set out in this data record. In regards to the Household Income and Labour Dynamics in Australia (HILDA) data summarised within the NRM dataset, the calculations are our own. The opinions, comments and analysis expressed in this document are those of the authors and do not necessarily represent the views of the Minister for Social Services or the Australian Government Department of Social Services and cannot be taken in any way as expressions of government policy.https://data.utas.edu.au/metadata/2e4f5e46-b472-47c0-bf18-3c266e1d6eac2023Natalie StoecklVanessa AdamsStuart AllenUniversity of Tasmania, AustraliaDifferent types of data have been collected by different agencies, at different points in time. This compilation includes the most recent; other temporal layers will be added over timenorthlimit=-10.6318144971726; southlimit=-44.0244234482847; westlimit=111.972652226686; eastlimit=154.511714726686; projection=WGS84UTAS/342fc527-7c1d-4a3c-ad3e-b06914010d01https://orcid.org/0000-0001-5899-4771https://orcid.org/0000-0002-3509-7901https://orcid.org/0000-0003-1640-6884380105380102410404180601180604190103Integrated dataNatural Resource ManagementSocioecological SystemsAustraliaUTAS/d598f6b9-9ed4-4f71-a66c-9bd8804bff5fUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/d598f6b9-9ed4-4f71-a66c-9bd8804bff5fThe Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 4.2 to Appendix 4.7.

https://data.utas.edu.au/metadata/d598f6b9-9ed4-4f71-a66c-9bd8804bff5f

The appendices 4.2 to 4.6 contain the data-sets of the stable O and radiogenic Lu-Hf isotope measurements made on zircon isolated from 12 Tasmanian Devonian granites, which had been dated using U-Pb sensitive high resolution ion microprobe. Appendix 4.7 provides simple mixing data between low and high delta 18O end members of the high and low εHf groups. Appendix 4.2. O-isotope standards and internal error Appendix 4.3. Lu-Hf isotope standards Appendix 4.4. Zircon and O isotope results for the Tasmanian Devonian granites Appendix 4.5: Expanded summary of zircon O and Lu-Hf isotope results for the Devonian Tasmanian plutons. Appendix 4.6. Comparison of magmatic results between the granite samples. Appendix 4.7. Simple mixing curvesAttribution(BY)https://data.utas.edu.au/metadata/d598f6b9-9ed4-4f71-a66c-9bd8804bff5f2023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107zircon O and Lu-Hf isotope dataTasmanian Devonian Graniteswhole rock Sr-Nd dataUTAS/e35ed3da-3e40-4277-811b-000a06055dd2University of Tasmania, Australiahttps://data.utas.edu.au/metadata/e35ed3da-3e40-4277-811b-000a06055dd2The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 5.1 Quartz O-isotopes SRM's and 5.3 Quartz Oxygen isotopes results.

https://data.utas.edu.au/metadata/e35ed3da-3e40-4277-811b-000a06055dd2

These appendices contain magmatic quartz O isotope results for standard reference materials and for isolates from Tasmanian Devonian granites. The measurements were made by sensitive high resolution ion microprobe at Research School of Earth Sciences at Australian National University.Attribution(BY)https://data.utas.edu.au/metadata/e35ed3da-3e40-4277-811b-000a06055dd22023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107Quartz O isotopesshrimpUTAS/76901276-9584-4ed5-ad79-a2bdf64dd571University of Tasmania, Australiahttps://data.utas.edu.au/metadata/76901276-9584-4ed5-ad79-a2bdf64dd571The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendices 6.1 Methods, 6.3 Geochemistry results, Appendix 6.4Hbl and Pl EMPA, Appendix 6.5 Lu-Hf SRMs and data, Appendix 6.7 Zircon LA-ICP-MS U-Pb data

https://data.utas.edu.au/metadata/76901276-9584-4ed5-ad79-a2bdf64dd571

Appendix 6.1. Methods. The methods used in the study of the Hogans Road Diorite are detailed in this Appendix. The methods used were LA-ICP-MS U-Pb geochronology using zircon, apatite and monazite minerals, hornblende Ar/Ar geochronology, and methods used for whole rock Sr-Nd and zircon Lu-Hf isotope studies. Appendices 6.3, 6.4, 6.5: Hogans Road diorite major and trace element geochemistry, hornblende and plagioclase mineral chemistry, and zircon Lu and Hf data. Appendix 6.7. Zircon LA-ICP-MS U-Pb dataAttribution(BY)https://data.utas.edu.au/metadata/76901276-9584-4ed5-ad79-a2bdf64dd5712023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107MethodsGeochronologyIsotope studiesUTAS/0197b2f2-952a-4073-af90-2926c2aa51a0University of Tasmania, Australiahttps://data.utas.edu.au/metadata/0197b2f2-952a-4073-af90-2926c2aa51a0Ecoregion flammability thresholds: The global pyrogeography of dead fine fuel moisture content as a driver for wildfire activity

https://data.utas.edu.au/metadata/0197b2f2-952a-4073-af90-2926c2aa51a0

We identify the ecoregion flammability thresholds (EFTs) and the associated inflection point slope estimates (IPSEs) controlling landscapes' potential to burn for 791 distinct ecoregions. These thresholds were identified using a combination of: 1) the Terrestrial Ecosystems of the World regional classification system designating landscapes into hierarchical realms, biomes, and ecoregions; 2) ERA5 atmospheric reanalysis data to calculate dead fine fuel moisture content (DFFMC: %) using the Canadian Fire Weather Index (FWI) system; and 3) Moderate Resolution Imaging Spectroradiometer (MODIS) MCD64CMQ burnt area product. Nonlinear least squares regression formulae were fit to the association between an ecoregion's 25th percentile of DFFMC and the cumulative proportion of burnt area below a given value of DFFMC. Both the inflection point and reciprocal of the model scaling parameter were then extracted from the formulae and represent essential fuel moisture-fire threshold characteristics.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/0197b2f2-952a-4073-af90-2926c2aa51a02023Todd EllisGrant WilliamsonDavid BowmanUniversity of Tasmania, Australia1971-012019-12https://orcid.org/0000-0002-4410-8676https://orcid.org/0000-0002-3469-7550https://orcid.org/0000-0001-8075-124X310402410205300706370202370201190401190102190508climate changebiogeographyfire riskfuel moisturepyrogeographyUTAS/731feb6c-23a4-4363-a30d-d7e1859aa081University of Tasmania, Australiahttps://data.utas.edu.au/metadata/731feb6c-23a4-4363-a30d-d7e1859aa0812009-2019 data from Tasmania: grape botrytis bunch rot

https://data.utas.edu.au/metadata/731feb6c-23a4-4363-a30d-d7e1859aa081

Data files for field studies of botrytis bunch rot (BBR) in wine grapes, caused by Botrytis cinerea. Studies were conducted in Riesling or Sauvignon Blanc vines in commercial vineyards in Tasmania.Attribution(BY)This CC license requires that reusers give credit to the creator. It allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, even for commercial purposes.https://data.utas.edu.au/metadata/731feb6c-23a4-4363-a30d-d7e1859aa0812023Katherine EvansUniversity of Tasmania, Australia2009 to 2019https://orcid.org/0000-0003-2189-5870300409310805260608diseaseepidemiologysensorsenvironmental dataVitisgrey mouldgray moldweathermodelempiricaldecisionUTAS/f221d93b-dfc6-4203-a480-31e836a0a8efUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/f221d93b-dfc6-4203-a480-31e836a0a8efGlobal Savanna-Forest Classification with covariates

https://data.utas.edu.au/metadata/f221d93b-dfc6-4203-a480-31e836a0a8ef

Dataset containing classification of random tropical point into forest, savanna or urban, with associated climate covariates (precipitation, temperature, human influence, topography, fire).Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/f221d93b-dfc6-4203-a480-31e836a0a8ef2023Grant WilliamsonDavid TngUniversity of Tasmania, Australia20102021northlimit=49.8379824530848; southlimit=-29.5352295629485; westlimit=-155.390625; eastlimit=196.171875; projection=WGS84https://orcid.org/0000-0002-3469-7550https://orcid.org/0000-0001-5135-0922https://orcid.org/0000-0001-5603-5024310308310402370299190401firesavannaforestsatelliteUTAS/e8046fba-5317-4a88-b520-db3f6c397759University of Tasmania, Australiahttps://data.utas.edu.au/metadata/e8046fba-5317-4a88-b520-db3f6c397759Data from PhD thesis 'Investigating the health of little penguins as a sentinel for Tasmanian ecosystems' - Chapter 2: Body condition in little penguins

https://data.utas.edu.au/metadata/e8046fba-5317-4a88-b520-db3f6c397759

This data record presents the raw and processed data for modelling input, based on little penguin health [and] body condition information across 16 field sites in Tasmania, Australia. The .csv file contains three worksheets: the first sheet is the key to all columns in the following data worksheets, and the following two worksheets are the raw and the transformed data respectively. These data have been collected as part of a larger PhD project investigating spatial variability in little penguin health (UTAS Animal Ethics # 23764).Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/e8046fba-5317-4a88-b520-db3f6c3977592023Melanie WellsScott CarverMary-Anne LeaUniversity of Tasmania, Australia20202022northlimit=-39.4870849816875; southlimit=-43.8186748554532; westlimit=143.32763671875; eastlimit=150.79833984375; projection=WGS84https://orcid.org/0000-0003-2817-8743https://orcid.org/0000-0002-3579-7588https://orcid.org/0000-0001-8318-9299https://orcid.org/0000-0001-5603-5024310303310305310907280102penguinseabirdphysiologyhealthconditionUTAS/caddfd16-8133-49ab-a1fa-e6c15e3fdbedUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/caddfd16-8133-49ab-a1fa-e6c15e3fdbedAnimations for GPlates model of the Lachlan Orogen

https://data.utas.edu.au/metadata/caddfd16-8133-49ab-a1fa-e6c15e3fdbed

A series of videos showing animations captured directly from the GPlates visualisation interface, with annotations added at key times. Animations begin at the start-time indicated by the first number of the filename in Ma, and end at the second number in Ma. They start playing forwards in time and then play backwards in the second half. An additional animation is also provided, depicting the Tasmanian Orocline model with figures from Cayley (2015).Attribution(BY)https://data.utas.edu.au/metadata/caddfd16-8133-49ab-a1fa-e6c15e3fdbed2023Thomas SchaapUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-4189-3760https://orcid.org/0000-0001-5603-5024370511170699GPlatesTectonicsLachlan OrogenUTAS/6c85d9d6-0d8b-4629-a92a-bdea084cf890University of Tasmania, Australiahttps://data.utas.edu.au/metadata/6c85d9d6-0d8b-4629-a92a-bdea084cf890REVISED May 2023: Lachlan Orogen GPlates model August 2021

https://data.utas.edu.au/metadata/6c85d9d6-0d8b-4629-a92a-bdea084cf890

REVISED as of May 2023. Model data and GPlates project file for Cambrian-Devonian reconstruction of the Lachlan Orogen integrated into a global model (Wright et al., 2013 - doi:10.5194/bg-10-1529-2013). All spatial datasets are provided in .gpml format and rotation files in .grot format.Attribution(BY)https://data.utas.edu.au/metadata/6c85d9d6-0d8b-4629-a92a-bdea084cf8902023Thomas SchaapSebastien MeffreJoanne WhittakerMatthew CracknellUniversity of Tasmania, AustraliaPalaeozoicnorthlimit=-26.745610382199; southlimit=-75.4971573189308; westlimit=143.0859375; eastlimit=184.21875; projection=WGS84UTAS/6988aa01-5211-4b37-b339-9eb0e44aadbehttps://orcid.org/0000-0002-4189-3760https://orcid.org/0000-0003-2741-6076https://orcid.org/0000-0002-3170-3935https://orcid.org/0000-0001-9843-8251https://orcid.org/0000-0001-5603-5024370604370502370508370511250399plate tectonicsgplatesUTAS/ae75e1f7-e2c6-4b7b-9440-33542dc79b2eUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/ae75e1f7-e2c6-4b7b-9440-33542dc79b2eGeospatial data for tectonic model development

https://data.utas.edu.au/metadata/ae75e1f7-e2c6-4b7b-9440-33542dc79b2e

This dataset consists of various raster and gpkg feature classes which formed most of the data used to guide construction of tectonic elements and GPlates model discussed in chapters 3 and 4 of the thesis. Most of these datasets are from freely-available government sources. Those which were mentioned in the thesis but not included in this data package are predominantly sourced from supplementary data packages in other research studies. A README file is contained with more information.Attribution(BY)https://data.utas.edu.au/metadata/ae75e1f7-e2c6-4b7b-9440-33542dc79b2e2023Thomas SchaapUniversity of Tasmania, Australianorthlimit=-6.31529853833003; southlimit=-74.6832503005186; westlimit=108.6328125; eastlimit=206.71875; projection=WGS84https://orcid.org/0000-0002-4189-3760https://orcid.org/0000-0001-5603-5024370511370604250399tectonicgeochronologyUTAS/07c9dad2-cdbb-46f8-8c99-c8fc517bfdf5University of Tasmania, Australiahttps://data.utas.edu.au/metadata/07c9dad2-cdbb-46f8-8c99-c8fc517bfdf5𝘈𝘳𝘵𝘩𝘳𝘰𝘱𝘰𝘥𝘪𝘶𝘮 𝘧𝘪𝘮𝘣𝘳𝘪𝘢𝘵𝘶𝘮 genomics datasets

https://data.utas.edu.au/metadata/07c9dad2-cdbb-46f8-8c99-c8fc517bfdf5

Final filtered SNP datasets used in the study by Jordan 𝘦𝘵 𝘢𝘭. 2023 titled "Landscape genomics reveals signals of climate adaptation and a cryptic lineage in 𝘈𝘳𝘵𝘩𝘳𝘰𝘱𝘰𝘥𝘪𝘶𝘮 𝘧𝘪𝘮𝘣𝘳𝘪𝘢𝘵𝘶𝘮" (citation below). The dataset comprise SNP genotypes for 13 provenance and 10 provenances. Each file can be read into R using the 'readRDS()' function. This will read in a list object that contains 5 datasets used for analysis. This includes a (i) 'genlight' object of class adegenet, (ii) 'genmat' object of class matrix (row = sample, column = SNP) that was used to create the genind object, (iii) 'genind' object of class adegenet, (iv) 'genpop' object of class adegenet, and (v) 'allele_freq' object of class matrix comprising the population allele frequencies (row = sample, column = SNP).Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/07c9dad2-cdbb-46f8-8c99-c8fc517bfdf52023Dorothy SteanePeter HarrisonUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-8061-8454https://orcid.org/0000-0002-3502-0242https://orcid.org/0000-0001-5603-5024310403410102410401410405180604190102DArTSeqclimate adaptationrestorationSNPJordan R, Price M, Harrison PA, Prober S, Vaillancourt RE, Steane D, 'Landscape genomics reveals signals of climate adaptation and a cryptic lineage in Arthropodium fimbriatum', Conservation Genetics pp. 1-34. ISSN 1566-0621 (2023) [Refereed Article]UTAS/publications/155997UTAS/e4d80a03-3412-4ca5-a56f-5b7fb083b93cUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/e4d80a03-3412-4ca5-a56f-5b7fb083b93cThe Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 6.3 Geochemistry results, Appendix 6.4Hbl and Pl EMPA, Appendix 6.5 Lu-Hf SRMs and data.

https://data.utas.edu.au/metadata/e4d80a03-3412-4ca5-a56f-5b7fb083b93c

Hogans Road diorite major and trace element geochemistry, hornblende and plagioclase mineral chemistry, and zircon Lu and Hf data.Attribution(BY)https://data.utas.edu.au/metadata/e4d80a03-3412-4ca5-a56f-5b7fb083b93c2023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107mineral chemistrywhole rock chemistryLu and Hf isotopesHogans Road dioriteUTAS/86cbb4e2-30e1-4e13-931e-fbbf8ebaa029University of Tasmania, Australiahttps://data.utas.edu.au/metadata/86cbb4e2-30e1-4e13-931e-fbbf8ebaa029The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 5.1 Quartz O-isotopes SRM's and 5.3 Quartz Oxygen isotopes results

https://data.utas.edu.au/metadata/86cbb4e2-30e1-4e13-931e-fbbf8ebaa029

These appendices contain magmatic quartz O isotope results for standard reference materials and for isolates from Tasmanian Devonian granites. The measurements were made by sensitive high resolution ion microprobe at Research School of Earth Sciences at Australia National UniversityAttribution(BY)https://data.utas.edu.au/metadata/86cbb4e2-30e1-4e13-931e-fbbf8ebaa0292023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107quartz O isotopesshrimpUTAS/49bedaaf-1565-4055-a7ef-e058f5b9fd08University of Tasmania, Australiahttps://data.utas.edu.au/metadata/49bedaaf-1565-4055-a7ef-e058f5b9fd08The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 5.2 CL images of quartz mounts

https://data.utas.edu.au/metadata/49bedaaf-1565-4055-a7ef-e058f5b9fd08

The cathodoluminesence (CL) imaging of quartz mineral isolates in epoxy mounts from 12 Tasmanian Devonian granites are presented. These images were used to choose spots for analysis of O isotopes by ion microprobe and element concentrations by electron microprobe. The spots of the ion microprobe are arrowed and the electron microprobe spots were close to these spots. CL dark and light areas were selected in each magmatic grain studied.Attribution(BY)https://data.utas.edu.au/metadata/49bedaaf-1565-4055-a7ef-e058f5b9fd082023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107CL images of quartzTasmania Devonian graniteUTAS/8248a715-280f-4f5b-9564-33ac8d206b88University of Tasmania, Australiahttps://data.utas.edu.au/metadata/8248a715-280f-4f5b-9564-33ac8d206b88Data supporting assessment of variation in disease impacts for a multi-host pathogen

https://data.utas.edu.au/metadata/8248a715-280f-4f5b-9564-33ac8d206b88

This record presents an Excel file containing data frames used in data collection and analysis for Lewin 𝘦𝘵 𝘢𝘭., as well as updated host species database for 𝘚𝘢𝘳𝘤𝘰𝘱𝘵𝘦𝘴 𝘴𝘤𝘢𝘣𝘪𝘦𝘪.Attribution(BY)https://data.utas.edu.au/metadata/8248a715-280f-4f5b-9564-33ac8d206b882023Scott CarverZachary LewinUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-3579-7588https://orcid.org/0000-0002-5104-4818https://orcid.org/0000-0001-5603-5024300905109902Sarcoptic mangeSarcoptes scabieianimal welfaredisease impact assessmentEscobar LE, Carver S, Cross PC, Rossi L, Almberg ES, Yabsley MJ, Niedringhaus KD, Van Wick P, Dominguez-Villegas E, Gakuya F, Xie Y, Angelone S, Gortazar C, Astorga F, 'Sarcoptic mange: an emerging panzootic in wildlife', Transboundary and Emerging Diseases pp. 1-16. ISSN 1865-1674 (2021) [Refereed Article]10.1111/tbed.14082UTAS/c60272fb-7bf1-4a68-b141-0216f2e10246University of Tasmania, Australiahttps://data.utas.edu.au/metadata/c60272fb-7bf1-4a68-b141-0216f2e10246Dataset - Tracking of apolipoprotein B levels measured in childhood and adolescence: systematic review and meta-analysis

https://data.utas.edu.au/metadata/c60272fb-7bf1-4a68-b141-0216f2e10246

The dataset contains the data extracted from the studies included in the systematic review entitled "Tracking of apolipoprotein B levels measured in childhood and adolescence: systematic review and meta-analysis". Data was extracted from full-text original empirical research journal articles published in MEDLINE, Embase, Web of Science (Core Collection), or Google Scholar databases before February 2022 which reported the degree of tracking of apolipoprotein B (apoB) levels from childhood or adolescence (baseline; age <19 years) into later life (defined by a follow-up period ≥1 year). The dataset contains the following information extracted from each study: study name, study design, country where data were collected, type of apolipoprotein/lipid (apoB or LDL cholesterol), effect estimate, tracking effect measure, variables used for adjustment (if any), sample size (total and by sex), sex, ethnicity (if stratified by ethnicity), age at baseline, length of follow-up, fasting status at baseline and follow-up as defined by the authors, number of serum measurements used to derive levels at baseline and follow-up, measurement methods (e.g., assay, calculations). Analysis of the data is complete and the findings will be published in a scientific journal. The protocol of the systematic review is published in the International Prospective Register of Systematic Reviews, PROSPERO (protocol ID: CRD42022298663).Attribution - Share Alike(BY - SA)Requests for data may be directed to the custodians. Data may be used by researchers outside of the investigator team according to the terms of the license and provided that due ethics processes are adhered to and permission for use is granted by the custodians.https://data.utas.edu.au/metadata/c60272fb-7bf1-4a68-b141-0216f2e102462023Oliver StanesbyCostan MagnussenUniversity of Tasmania, Australia19742006https://orcid.org/0000-0002-5996-5881https://orcid.org/0000-0002-6238-5730420207320101320504320202321301321302420605200104200101200105200206200407200412200506Apolipoproteinschildrenadolescentsystematicreviewmeta-analysisUTAS/6be39802-105d-4d93-a22f-9f1ce833817bUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/6be39802-105d-4d93-a22f-9f1ce833817bThe Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 4.1. Zircon optical microscopy and cathodoluminescent imaging

https://data.utas.edu.au/metadata/6be39802-105d-4d93-a22f-9f1ce833817b

This dataset consists of reflected and transmitted light microscopy and cathodoluminescent images of zircons isolated from 11 East Tasmania Terrane and one West Tasmania Terrane granites.Attribution(BY)https://data.utas.edu.au/metadata/6be39802-105d-4d93-a22f-9f1ce833817b2023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107Zircon optical microscopyZircon cathodoluminescesce imagingTasmanian Devonian granitesUTAS/212c16aa-e166-44b8-8901-dfb3a123a1daUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/212c16aa-e166-44b8-8901-dfb3a123a1daThe Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 6.6 Cathodoluminescence imaging of zircon

https://data.utas.edu.au/metadata/212c16aa-e166-44b8-8901-dfb3a123a1da

The dataset consists of PDF images of cathodoluminescent imaging of zircons isolated from Hogans Road diorite samples SH19CJ-008, -011, -015, -020, -026 and -029, from granodiorite immediately adjacent the diorite suite in the Haleys New Country pluton SH19CJ-010 and -020 and regional granodiorites LP19CJ001 (Long Point) and SH19CJ005 (Beauty Point).Attribution(BY)https://data.utas.edu.au/metadata/212c16aa-e166-44b8-8901-dfb3a123a1da2023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107zircon cathodoluminescenceUTAS/319b25fe-e049-4dc1-9373-8876a46f5605University of Tasmania, Australiahttps://data.utas.edu.au/metadata/319b25fe-e049-4dc1-9373-8876a46f5605Tasmanian Wilderness World Heritage Area (TWWHA) Bushfire Recovery: Lake Mackenzie Rehabilitation Trials Data - Pencil Pine mortality

https://data.utas.edu.au/metadata/319b25fe-e049-4dc1-9373-8876a46f5605

The aim of this study was to evaluate the reliability of assessments of fire impacts on pencil pine populations made one year post-fire. In particular, we quantified delayed mortality occurring between one and four years post-fire, and attempted to determine whether the ultimate fate of stems could be predicted from measurements of canopy damage made one year post-fire. In addition, we quantified resprouting and juvenile presence four years after the fire. For full details, refer to Bliss 𝘦𝘵 𝘢𝘭 (2021).Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/319b25fe-e049-4dc1-9373-8876a46f56052023David BowmanLynda PriorAimee BlissUniversity of Tasmania, Australia20172020northlimit=-41.655727656181; southlimit=-41.7013710118883; westlimit=146.354026794434; eastlimit=146.421318054199; projection=WGS84https://orcid.org/0000-0001-8075-124Xhttps://orcid.org/0000-0002-5511-2320https://orcid.org/0000-0001-5573-0543https://orcid.org/0000-0002-5808-509Xhttps://orcid.org/0000-0001-5603-5024410206410205410405180604Pencil PinePencil Pine mortalitypost-fire recoveryAthrotaxis cupressoidesTWWHATasmanian Wilderness World Heritage AreaEucalyptus cocciferaBliss A, Prior LD, Bowman DMJS, 'Lack of reliable post-fire recovery mechanisms makes the iconic Tasmanian conifer Athrotaxis cupressoides susceptible to population decline', Australian Journal of Botany, 69, (3) Article BT20117. ISSN 0067-1924 (2021) [Refereed Article]10.1071/BT20117Bowman DMJS, Bliss A, Bowman CJW, Prior LD, 'Fire caused demographic attrition of the Tasmanian palaeoendemic conifer Athrotaxis cupressoides', Austral Ecology, 44, (8) pp. 1322-1339. ISSN 1442-9985 (2019) [Refereed Article]10.1111/aec.12789UTAS/b639e9cb-ce93-4a80-bcc3-caefbce7bac7University of Tasmania, Australiahttps://data.utas.edu.au/metadata/b639e9cb-ce93-4a80-bcc3-caefbce7bac7Tasmanian Wilderness World Heritage Area (TWWHA) Bushfire Recovery: Lake Mackenzie Rehabilitation Trials Data - Post-fire restoration of Pencil Pines

https://data.utas.edu.au/metadata/b639e9cb-ce93-4a80-bcc3-caefbce7bac7

The primary goal of this trial was to identify best-practice methods (interventions) for restoring burnt pencil pine (𝘈𝘵𝘩𝘳𝘰𝘵𝘢𝘹𝘪𝘴 𝘤𝘶𝘱𝘳𝘦𝘴𝘴𝘰𝘪𝘥𝘦𝘴) stands. We selected five study sites in the Lake Mackenzie area. We sought to develop methods to rehabilitate burnt Pencil Pine stands (not create new stands) and hence targeted areas with fire-killed Pencil Pines. We selected three sites burnt in the 2016 fires (Burnt sites henceforth) and two which were not burnt in 2016, but contained dead Pencil Pines from the 1960’s fires (Unburnt sites henceforth). We chose sites which were relatively accessible and which captured environmental variability. Sites did not have formal boundaries or fixed size; they were simply a tool to achieve geographic spread.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/b639e9cb-ce93-4a80-bcc3-caefbce7bac72023David BowmanBen FrenchLynda PriorUniversity of Tasmania, Australia20182022northlimit=-41.6600882512475; southlimit=-41.7026526611747; westlimit=146.354713439941; eastlimit=146.439170837402; projection=WGS84https://orcid.org/0000-0001-8075-124Xhttps://orcid.org/0000-0001-5046-4047https://orcid.org/0000-0002-5511-2320https://orcid.org/0000-0002-5808-509Xhttps://orcid.org/0000-0001-5603-5024410206410205410405180604Athrotaxis cupressoidespencil pinepost-fire restorationpencil pine rehabilitationTasmanian Wilderness World Heritage AreaTWWHAUTAS/636f2469-3b75-4ca6-95cf-9f2a3845fde4University of Tasmania, Australiahttps://data.utas.edu.au/metadata/636f2469-3b75-4ca6-95cf-9f2a3845fde4Data from: 'Molecular insights into the dynamics of species invasion by hybridisation in Tasmanian eucalypts'

https://data.utas.edu.au/metadata/636f2469-3b75-4ca6-95cf-9f2a3845fde4

Dataset includes geographic coordinates, phenotypes, and genotype data for all the 259 individuals analysed in the manuscript. The genotyping datasets contained here include both the raw file with the 63,795 SNP markers generated by the Diversity Arrays Technology (DArTseq) platform and the file with only the 3,362 high-quality filtered SNPs that were used in the analyses. The full methodology is available in the publication: http://ecite.utas.edu.au/155252Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/636f2469-3b75-4ca6-95cf-9f2a3845fde42023Thais Ribeiro PfeilstickerRebecca JonesDorothy SteaneRene VaillancourtBrad PottsUniversity of Tasmania, AustraliaLeaf samples for DNA extraction were obtained between October 2019 and March 2020northlimit=-42.8221461442699; southlimit=-42.8348615431966; westlimit=147.3220038414; eastlimit=147.338569164276; projection=WGS84https://orcid.org/0000-0003-4690-4593https://orcid.org/0000-0002-6491-1423https://orcid.org/0000-0002-8061-8454https://orcid.org/0000-0002-1159-9149https://orcid.org/0000-0001-6244-289Xhttps://orcid.org/0000-0001-5603-5024310510310509310899310499190199Eucalyptus amygdalinaEucalyptus risdoniigeneticsspecies expansionclimate changeadmixturedispersal mechanismPfeilsticker TR, Jones RC, Steane DA, Vaillancourt RE, Potts BM, 'Molecular insights into the dynamics of species invasion by hybridisation in Tasmanian eucalypts', Molecular Ecology pp. 1-17. ISSN 1365-294X (2023) [Refereed Article]10.1111/mec.16892UTAS/ef903ce8-7a37-4dab-8d40-9a67442739baUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/ef903ce8-7a37-4dab-8d40-9a67442739baTasmanian Wilderness World Heritage Area (TWWHA) Bushfire Recovery: Lake Mackenzie Rehabilitation Trials Data - Sphagnum Restoration Trial

https://data.utas.edu.au/metadata/ef903ce8-7a37-4dab-8d40-9a67442739ba

This record presents data from the 𝘚𝘱𝘩𝘢𝘨𝘯𝘶𝘮 rehabilitation trial, designed to test whether various combinations of fertiliser, shadecloth and 𝘚𝘱𝘩𝘢𝘨𝘯𝘶𝘮 transplants can promote recovery of the 𝘚𝘱𝘩𝘢𝘨𝘯𝘶𝘮 communities burnt in the 2016 fire. There were two facets to the 𝘚𝘱𝘩𝘢𝘨𝘯𝘶𝘮 restoration trials at Lake Mackenzie: (1) investigating the use of small unoccupied aerial systems (UAS) to identify moderately and severely damaged 𝘚𝘱𝘩𝘢𝘨𝘯𝘶𝘮, and (2) testing whether recovery of fire-damaged 𝘚𝘱𝘩𝘢𝘨𝘯𝘶𝘮 could be improved by applying shadecloth, fertiliser or transplanting healthy 𝘚𝘱𝘩𝘢𝘨𝘯𝘶𝘮. This dataset represents component (2) of this project.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/ef903ce8-7a37-4dab-8d40-9a67442739ba2023David BowmanScott NicholsLynda PriorUniversity of Tasmania, Australia20182022northlimit=-41.6424115858262; southlimit=-41.6993443518217; westlimit=146.344413757324; eastlimit=146.435050964356; projection=WGS84https://orcid.org/0000-0001-8075-124Xhttps://orcid.org/0000-0002-1478-1579https://orcid.org/0000-0002-5511-2320https://orcid.org/0000-0002-5808-509Xhttps://orcid.org/0000-0001-5603-5024410206410205410405180604Sphagnum restorationpost-fire restoration of sphagnum mirestasmaniaTWWHATasmanian Wilderness World Heritage AreaPrior LD, Nichols SC, Williamson GJ, Bowman DMJS, 'Post-fire restoration of Sphagnum bogs in the Tasmanian Wilderness World Heritage Area, Australia', Restoration Ecology, 31, (3) Article 13797. ISSN 1526-100X (2022) [Refereed Article]10.1111/rec.13797UTAS/8628529b-49cf-42d4-9459-3c1e97f70d98University of Tasmania, Australiahttps://data.utas.edu.au/metadata/8628529b-49cf-42d4-9459-3c1e97f70d98Revision of Totten Glacier ocean & sediment DNA (IN2017_V01)

https://data.utas.edu.au/metadata/8628529b-49cf-42d4-9459-3c1e97f70d98

Genetic data underlying the paper 'From the Surface Ocean to the Seafloor: Linking Modern and Paleo-genetics at the Sabrina Coast, East Antarctica (IN2017_V01)' by Armbrecht et al. In this study, we provide the first taxonomic overview of the modern and ancient marine bacterial and eukaryotic communities of the Totten Glacier region, East Antarctica, using a combination of 16S and 18S rRNA amplicon sequencing (modern DNA) and shotgun metagenomic (sedimentary ancient DNA, sedaDNA) analyses, respectively. We explore environmental and geochemical variables that drive these biodiversity patterns. Our data show considerable differences between eukaryote and bacterial signals detected via DNA analyses in the water column vs. the sediments. Organisms that are well represented in deeper waters appear are to have a higher likelihood of becoming preserved in the sediments. The study provides the first assessment of DNA transfer from ocean waters to sediments, while also providing a broad overview of the biological communities occurring in the climatically important Totten Glacier region. (Please note that this record supersedes the metadata and the data files from the version, here: https://dx.doi.org/10.25959/hwk8-cc81.)Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/8628529b-49cf-42d4-9459-3c1e97f70d982023Linda ArmbrechtAmaranta FocardiUniversity of Tasmania, Australia2017-012017-03UTAS/a47db45c-4895-42c2-82de-b5e0b959a725https://orcid.org/0000-0002-1213-1257https://orcid.org/0000-0002-0340-4225https://orcid.org/0000-0001-5603-5024310306370801410102180404190102Totten GlacierSabrina Coastancient DNAmodern DNAmarineAntarcticaSouthern OceandiatomsradiolariansbacteriaUTAS/bd74979c-db1b-4b71-934a-0908b2fa049dUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/bd74979c-db1b-4b71-934a-0908b2fa049dThe Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 7A.1 Monazite U-Th-Pb CHIME.

https://data.utas.edu.au/metadata/bd74979c-db1b-4b71-934a-0908b2fa049d

Monazite chemical dating of the Hogans Road dioriteAttribution(BY)https://data.utas.edu.au/metadata/bd74979c-db1b-4b71-934a-0908b2fa049d2023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107CHIMEMonazite datingChemical U-Th-Pb datingUTAS/8f1dcb31-1015-41e8-b26a-70ab6e304ecbUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/8f1dcb31-1015-41e8-b26a-70ab6e304ecbThe Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 6.11 Sr-Nd results.

https://data.utas.edu.au/metadata/8f1dcb31-1015-41e8-b26a-70ab6e304ecb

Whole rock Sr-Nd isotope analysis on the Hogans Road diorite.Attribution(BY)https://data.utas.edu.au/metadata/8f1dcb31-1015-41e8-b26a-70ab6e304ecb2023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107Sr-Nd isotopesHogans Road dioriteWhole rock Sr-Nd isotopesUTAS/a14d8877-3b74-4329-90ec-58f43df52a5cUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/a14d8877-3b74-4329-90ec-58f43df52a5cThe Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 6.10 Ar/Ar_results

https://data.utas.edu.au/metadata/a14d8877-3b74-4329-90ec-58f43df52a5c

Geochronology of the HRD using hornblende mineral and Ar isotopesAttribution(BY)https://data.utas.edu.au/metadata/a14d8877-3b74-4329-90ec-58f43df52a5c2023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107Hornblende Ar/Ar datingHornblende geochronologyUTAS/469eefac-f9a2-49b5-a1c6-8fb544765ff1University of Tasmania, Australiahttps://data.utas.edu.au/metadata/469eefac-f9a2-49b5-a1c6-8fb544765ff1The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 6.9 Monazite LA-ICP-MS U-Pb.

https://data.utas.edu.au/metadata/469eefac-f9a2-49b5-a1c6-8fb544765ff1

Geochronological dating of monazite in a syenogranite dike crosscutting the HRD outcrop.Attribution(BY)https://data.utas.edu.au/metadata/469eefac-f9a2-49b5-a1c6-8fb544765ff12023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107geochronologymineral datingmonaziteUTAS/b21f9565-29db-4e21-9c57-08b7d1ce684dUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/b21f9565-29db-4e21-9c57-08b7d1ce684dThe Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 6.8 Apatite LA-ICP-MS U-Pb .

https://data.utas.edu.au/metadata/b21f9565-29db-4e21-9c57-08b7d1ce684d

Hogans Road diorite geochronology using apatite: U-Pb isotope data.Attribution(BY)https://data.utas.edu.au/metadata/b21f9565-29db-4e21-9c57-08b7d1ce684d2023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107Apatitemineral datingU-Pb isotope datingUTAS/00fbb3e2-28fa-4638-ac6b-c084bad51db6University of Tasmania, Australiahttps://data.utas.edu.au/metadata/00fbb3e2-28fa-4638-ac6b-c084bad51db6The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 6.7 Zircon LA-ICP-MS U-Pb.

https://data.utas.edu.au/metadata/00fbb3e2-28fa-4638-ac6b-c084bad51db6

Results of zircon U-Pb isotope studies using LA-ICP-MS on Hogans Road diorite samplesAttribution(BY)https://data.utas.edu.au/metadata/00fbb3e2-28fa-4638-ac6b-c084bad51db62023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107Laser ablationzirconUTAS/fcbf262c-986b-4148-a183-cd6f937bd56fUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/fcbf262c-986b-4148-a183-cd6f937bd56fThe Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 6.6 CL images of zircons

https://data.utas.edu.au/metadata/fcbf262c-986b-4148-a183-cd6f937bd56f

Scanning electron microprobe (cathodoluminescence) images of zircons.Attribution(BY)https://data.utas.edu.au/metadata/fcbf262c-986b-4148-a183-cd6f937bd56f2023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107CathodoluminescenceUTAS/a0399ab1-2869-4436-8df9-3a62ca4f66b3University of Tasmania, Australiahttps://data.utas.edu.au/metadata/a0399ab1-2869-4436-8df9-3a62ca4f66b3The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 6.2 Locations of samples.eps

https://data.utas.edu.au/metadata/a0399ab1-2869-4436-8df9-3a62ca4f66b3

Map of where the Hogans Road diorite samples were located.Attribution(BY)https://data.utas.edu.au/metadata/a0399ab1-2869-4436-8df9-3a62ca4f66b32023Colin JonesUniversity of Tasmania, Australianorthlimit=-41.3355759731239; southlimit=-41.5579215778042; westlimit=147.54638671875; eastlimit=148.1396484375; projection=WGS84https://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107Map of sample locationsUTAS/976cf944-c2b2-42fd-a62d-01d1ada68bb6University of Tasmania, Australiahttps://data.utas.edu.au/metadata/976cf944-c2b2-42fd-a62d-01d1ada68bb6The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 6.1 Methods

https://data.utas.edu.au/metadata/976cf944-c2b2-42fd-a62d-01d1ada68bb6

The methods used in the study of the Hogans Road Diorite are detailed in this Appendix. The methods used were LA-ICP-MS U-Pb geochronology using zircon, apatite and monazite minerals, hornblende Ar/Ar geochronology, and methods used for whole rock Sr-Nd and zircon Lu-Hf isotope studies.Attribution(BY)https://data.utas.edu.au/metadata/976cf944-c2b2-42fd-a62d-01d1ada68bb62023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107MethodologyGeochronologySr-Nd isotope studiesZircon apatite monazite U-Pb isotopesUTAS/d556e774-083b-478e-8f40-51685fdca2f1University of Tasmania, Australiahttps://data.utas.edu.au/metadata/d556e774-083b-478e-8f40-51685fdca2f1The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 6.3 Geochemistry results, Appendix 6.4Hbl and Pl EMPA, Appendix 6.5 Lu-Hf SRM's and data.

https://data.utas.edu.au/metadata/d556e774-083b-478e-8f40-51685fdca2f1

Hogans Road diorite major and trace element geochemistry, hornblende and plagioclase mineral chemistry, and zircon Lu and Hf isotope data.Attribution(BY)https://data.utas.edu.au/metadata/d556e774-083b-478e-8f40-51685fdca2f12023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107Mineral chemistryWhole rock chemistryLu and Hf isotope dataUTAS/87dbf27b-e6ae-4856-b42b-e00dbff33f61University of Tasmania, Australiahttps://data.utas.edu.au/metadata/87dbf27b-e6ae-4856-b42b-e00dbff33f61The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 5.5 WR δ18O calculated from δ18Ozir and δ18Oqz

https://data.utas.edu.au/metadata/87dbf27b-e6ae-4856-b42b-e00dbff33f61

The estimation of late plutonic crustal assimilation was calculated by comparing estimated whole rock δ18O values from measured zircon and quartz mineral δ18O values. Calculations of whole rock δ18O at 650, 750, and 900 Celsius using measured zircon δ18O concentrations and at 470 Celsius using measured δ18O quartz concentrations are presented in this appendix.Attribution(BY)https://data.utas.edu.au/metadata/87dbf27b-e6ae-4856-b42b-e00dbff33f612023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107whole rock δ18Ozircon and quartz δ18OUTAS/4dd8f609-3f9f-4b11-9d98-f247c48d19daUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/4dd8f609-3f9f-4b11-9d98-f247c48d19daThe Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 5.4 Zircon U–Pb LA-ICP-MS ages and Ti data

https://data.utas.edu.au/metadata/4dd8f609-3f9f-4b11-9d98-f247c48d19da

This appendix describes the methodology used for magmatic zircon U-Pb LA-ICP-MS geochronology and Ti concentration measurement and presents the results datasets for 12 Tasmanian Devonian granites.Attribution(BY)https://data.utas.edu.au/metadata/4dd8f609-3f9f-4b11-9d98-f247c48d19da2023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107U-Pb geochronologyTasmanian Devonian graniteszircon U-Pb isotope and Ti concentrationsUTAS/368c3153-f1a4-4dcb-83dc-98c6588589cdUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/368c3153-f1a4-4dcb-83dc-98c6588589cdThe Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 5.2 CL images of quartz mounts

https://data.utas.edu.au/metadata/368c3153-f1a4-4dcb-83dc-98c6588589cd

The cathodoluminesence imaging of quartz mineral isolates in epoxy mounts from 12 Tasmanian Devonian granites are presented using .jpeg format.Attribution(BY)https://data.utas.edu.au/metadata/368c3153-f1a4-4dcb-83dc-98c6588589cd2023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107CL images of quartzUTAS/a1dd6fca-5e1d-49c3-8bfb-abe2603b3689University of Tasmania, Australiahttps://data.utas.edu.au/metadata/a1dd6fca-5e1d-49c3-8bfb-abe2603b3689The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 5.1 Quartz O-isotopes SRM's and 5.3 Quartz Oxygen isotopes results.xlsx

https://data.utas.edu.au/metadata/a1dd6fca-5e1d-49c3-8bfb-abe2603b3689

These appendices contain magmatic quartz O isotope results for standard reference materials and for isolates from Tasmanian Devonian granites. The measurements were made by sensitive high resolution ion microprobe at Research School of Earth Sciences at Australian National University.Attribution(BY)https://data.utas.edu.au/metadata/a1dd6fca-5e1d-49c3-8bfb-abe2603b36892023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107Quartz O isotopesshrimpUTAS/ebda5c0b-c2bb-498a-a116-da81fbf54bd7University of Tasmania, Australiahttps://data.utas.edu.au/metadata/ebda5c0b-c2bb-498a-a116-da81fbf54bd7The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 4.8. Statistical modeling of results.

https://data.utas.edu.au/metadata/ebda5c0b-c2bb-498a-a116-da81fbf54bd7

Statistical evidence of distinct subgroups in the O-Hf isotope data were determined by quadratic regression and exponential decay modeling of all data, modeling the separate subgroups interactions and using ANOVA to assess the interaction against the all-data model using R Version 3.6.2, 2019-12-12.Attribution(BY)https://data.utas.edu.au/metadata/ebda5c0b-c2bb-498a-a116-da81fbf54bd72023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107Statistical modeling of O and Lu-Hf dataUTAS/d086e965-965c-4c72-af61-5b1da96e2fa8University of Tasmania, Australiahttps://data.utas.edu.au/metadata/d086e965-965c-4c72-af61-5b1da96e2fa8The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 4.2 to Appendix 4.7.xlsx

https://data.utas.edu.au/metadata/d086e965-965c-4c72-af61-5b1da96e2fa8

The appendices 4.2 to 4.6 contain the data-sets of the stable O and radiogenic Lu-Hf isotope measurements made on zircon isolated from 12 Tasmanian Devonian granites, which had been dated using U-Pb sensitive high resolution ion microprobe. Appendix 4.7 provides simple mixing data between low and high delta 18O end members of the high and low εHf groups. Appendix 4.2. O-isotope standards and internal error Appendix 4.3. Lu-Hf isotope standards Appendix 4.4. Zircon and O isotope results for the Tasmanian Devonian granites Appendix 4.5: Expanded summary of zircon O and Lu-Hf isotope results for the Devonian Tasmanian plutons. Appendix 4.6. Comparison of magmatic results between the granite samples. Appendix 4.7 Simple mixing curvesAttribution(BY)https://data.utas.edu.au/metadata/d086e965-965c-4c72-af61-5b1da96e2fa82023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107O and Lu-Hf isotopeTasmanian Devonian Graniteszircon O and Lu-Hf isotope datasimple mixingUTAS/2ebc850d-31f8-4643-8815-9fd4036a7c51University of Tasmania, Australiahttps://data.utas.edu.au/metadata/2ebc850d-31f8-4643-8815-9fd4036a7c51The Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 4.1 Zircon imaging.

https://data.utas.edu.au/metadata/2ebc850d-31f8-4643-8815-9fd4036a7c51

Zircon imaging by reflected and transmitted optical microscopy and cathodoluminescent electro microprobe.Attribution(BY)https://data.utas.edu.au/metadata/2ebc850d-31f8-4643-8815-9fd4036a7c512023Colin JonesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024379901280107Cathodoluminescent imagingzircon microscopyUTAS/07e0a441-2cb9-4e6e-b119-6b5671d0feadUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/07e0a441-2cb9-4e6e-b119-6b5671d0feadThe Petrogenesis of the East Tasmania Terrane Devonian Granites. Appendix 3.1 Geological data for ETT granites.

https://data.utas.edu.au/metadata/07e0a441-2cb9-4e6e-b119-6b5671d0fead

Sample location, major and trace element geochemistry.Attribution(BY)https://data.utas.edu.au/metadata/07e0a441-2cb9-4e6e-b119-6b5671d0fead2023Colin JonesUniversity of Tasmania, Australianorthlimit=-40.6806380252146; southlimit=-42.2610491621138; westlimit=147.1728515625; eastlimit=149.501953125; projection=WGS84https://orcid.org/0000-0002-7453-2857https://orcid.org/0000-0001-5603-5024370603280107databasemajor and trace element chemistryUTAS/5397be1d-aed7-4c30-9040-3d9887a4f374University of Tasmania, Australiahttps://data.utas.edu.au/metadata/5397be1d-aed7-4c30-9040-3d9887a4f374Dataset for study: Double-Differenced dNBR: Combining MODIS and Landsat Imagery to Map Fine-Grained Fire MOSAICS in Lowland Eucalyptus Savanna in Kakadu National Park, Northern Australia

https://data.utas.edu.au/metadata/5397be1d-aed7-4c30-9040-3d9887a4f374

Dataset containing landscape metrics, summary statistics and burnt area data for inter-satellite comparison of MODIS, Landsat, and new combined double-dNBR methodology, applied to savannas in Kakadu National Park. Paper DOI: https://doi.org/10.3390/fire5050160Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/5397be1d-aed7-4c30-9040-3d9887a4f3742022Grant WilliamsonDavid BowmanTodd EllisUniversity of Tasmania, Australia19892021northlimit=-11.9748447529318; southlimit=-13.7740664080548; westlimit=131.676635742188; eastlimit=133.390502929688; projection=WGS84https://orcid.org/0000-0002-3469-7550https://orcid.org/0000-0001-8075-124Xhttps://orcid.org/0000-0002-4410-8676https://orcid.org/0000-0001-5603-5024410205300706300703401304190401fireforestsavannaburnt areasatellitemodislandsatUTAS/8dc20722-4706-4413-99fe-18686b47c6afUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/8dc20722-4706-4413-99fe-18686b47c6afDataset: Fire recovery and other fire-related traits in 𝘌𝘶𝘤𝘢𝘭𝘺𝘱𝘵𝘶𝘴 𝘨𝘭𝘰𝘣𝘶𝘭𝘶𝘴 (2022-09-27)

https://data.utas.edu.au/metadata/8dc20722-4706-4413-99fe-18686b47c6af

Fire-related traits were assessed in a large outcrossed F2 𝘌𝘶𝘤𝘢𝘭𝘺𝘱𝘵𝘶𝘴 𝘨𝘭𝘰𝘣𝘶𝘭𝘶𝘴 population in a field trial in Tasmania, Australia, which was uniformly burnt by a wildfire 14 years after planting. The trial also included open-pollinated families of the grandparental dwarf and tall ecotypes used to produce the F2 population. The data was used to compare ecotypes, study correlations within the F2 population and perform QTL analyses using a linkage map comprised of 472 markers.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/8dc20722-4706-4413-99fe-18686b47c6af2022Mariano HernándezJakob ButlerHans AmmitzbollJulianne O'Reilly-WapstraJules FreemanRene VaillancourtBrad PottsUniversity of Tasmania, Australia2016-06-292020-02-19east=146.902570724487; north=-43.2167487949353; projection=WGS84https://orcid.org/0000-0003-2557-3342https://orcid.org/0000-0003-1353-3765https://orcid.org/0000-0002-8115-0267https://orcid.org/0000-0003-4801-4412https://orcid.org/0000-0003-1166-9976https://orcid.org/0000-0002-1159-9149https://orcid.org/0000-0001-6244-289Xhttps://orcid.org/0000-0001-5603-5024310899410205310509260299bark thicknessepicormic resproutingEucalyptus globulusherbivorypost-fire recoveryQTL analysiswildfireUTAS/a47db45c-4895-42c2-82de-b5e0b959a725University of Tasmania, Australiahttps://data.utas.edu.au/metadata/a47db45c-4895-42c2-82de-b5e0b959a725Totten Glacier ocean & sediment DNA (IN2017_V01)

https://data.utas.edu.au/metadata/a47db45c-4895-42c2-82de-b5e0b959a725

Genetic data underlying the paper 'From the Surface Ocean to the Seafloor: Linking Modern and Paleo-genetics at the Sabrina Coast, East Antarctica (IN2017_V01)' by Armbrecht et al. In this study, we provide the first taxonomic overview of the modern and ancient marine bacterial and eukaryotic communities of the Totten Glacier region, East Antarctica, using a combination of 16S and 18S rRNA amplicon sequencing (modern DNA) and shotgun metagenomic (sedimentary ancient DNA, sedaDNA) analyses, respectively. We explore environmental and geochemical variables that drive these biodiversity patterns. Our data show considerable differences between eukaryote and bacterial signals detected via DNA analyses in the water column vs. the sediments. Organisms that are well represented in deeper waters appear are to have a higher likelihood of becoming preserved in the sediments. The study provides the first assessment of DNA transfer from ocean waters to sediments, while also providing a broad overview of the biological communities occurring in the climatically important Totten Glacier region.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/a47db45c-4895-42c2-82de-b5e0b959a7252022Linda ArmbrechtUniversity of Tasmania, Australia2017-012017-03https://orcid.org/0000-0002-1213-1257310306370801410102180404190102Totten GlacierSabrina Coastancient DNAmodern DNAmarineAntarcticaSouthern OceandiatomsradiolariansbacteriaUTAS/5d3ec4b8-9c23-44c2-b1ff-316e5919b5d7University of Tasmania, Australiahttps://data.utas.edu.au/metadata/5d3ec4b8-9c23-44c2-b1ff-316e5919b5d7Making the Most of Plain Packaging (MMoPP) - Data Files

https://data.utas.edu.au/metadata/5d3ec4b8-9c23-44c2-b1ff-316e5919b5d7

Background: Smokers can respond defensively to health risk communication such as on-pack warning labels, potentially reducing their effectiveness. Theory suggests that risk perception together with self-efficacy reduces defensive responses and predicts target behaviours. Currently, tobacco warning labels globally predominantly target risk and do not explicitly consider efficacy. This study explores the effectiveness of combining Australian tobacco warning labels with efficacy content to increase quitting intentions. Methods: RCT in 83 smokers over three weeks. After a seven-day baseline phase (smoking from usual tobacco packaging), participants were randomised to one of two adhesive labels groups for the remaining 14 days: standard health warning labels (HWLs) featuring enhanced efficacy messages (experimental group) or unmodified standard HWLs (control group). Participants attached these labels to their tobacco packaging and recorded their cognitions and smoking behaviour once daily using smartphones. Multi-level structural equation modelling was used to test theorised effects of the labels on self-efficacy, risk perception and intentions to quit.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/5d3ec4b8-9c23-44c2-b1ff-316e5919b5d72022Stuart FergusonNatalie SchüzBenjamin SchüzLillian BrinkenUniversity of Tasmania, Australiahttps://orcid.org/0000-0001-7378-3497https://orcid.org/0000-0001-9010-5487https://orcid.org/0000-0002-0801-498Xhttps://orcid.org/0000-0002-5383-3597https://orcid.org/0000-0001-5603-5024520304200412warning labelssmokingpsychologytobaccoUTAS/342fc527-7c1d-4a3c-ad3e-b06914010d01University of Tasmania, Australiahttps://data.utas.edu.au/metadata/342fc527-7c1d-4a3c-ad3e-b06914010d01Integrated data for natural resource managers

https://data.utas.edu.au/metadata/342fc527-7c1d-4a3c-ad3e-b06914010d01

A compilation of Australian data that are (a) publicly available; and (b) use consistent measures across the continent. The compilation is deliberately broad - aiming to include variables that describe each of four 'capitals' (natural, human, social / institutional and financial/built). The file 'integrated data description_nrm.pdf' lists the current data sets within the compilation. Further work is underway to expand the data set, including more variables.Attribution(BY)The data collections described in this record are funded by the Australian Government Department of Agriculture, Water and the Environment (DAWE) through the NESP Resilient Landscapes Hubhttps://data.utas.edu.au/metadata/342fc527-7c1d-4a3c-ad3e-b06914010d012022Natalie StoecklVanessa AdamsStuart AllenUniversity of Tasmania, AustraliaDifferent types of data have been collected by different agencies, at different points in time. This compilation includes the most recent; other temporal layers will be added over timenorthlimit=-10.6318144971726; southlimit=-44.0244234482847; westlimit=111.972652226686; eastlimit=154.511714726686; projection=WGS84https://orcid.org/0000-0001-5899-4771https://orcid.org/0000-0002-3509-7901https://orcid.org/0000-0003-1640-6884380105380102410404180601180604190103Integrated dataNatural Resource ManagementSocioecological SystemsAustraliaUTAS/8fc48769-b74e-48cd-98c0-83df9459b828University of Tasmania, Australiahttps://data.utas.edu.au/metadata/8fc48769-b74e-48cd-98c0-83df9459b828Dataset - Trips4Health: An incentives-based trial to increase transport-related physical activity

https://data.utas.edu.au/metadata/8fc48769-b74e-48cd-98c0-83df9459b828

The trips4health study was a single-blinded parallel design randomised controlled trial (RCT) to assess the impact of a bus trips incentives intervention on physical activity and transport behaviours. The trips4health RCT planned to assess participants at three timepoints (T1: 0 months, T2: 4 months, T3: 10 months), with an intervention group receiving a four-month incentive-based program to increase public transport use between T1 and T2 and a control group that did not. When RCT was abandoned because of the broadscale social changes imposed by COVID-19, uncertainty about the progress of COVID-19, participant safety concerns, and the impact of COVID-19 on study validity, 110 participants had completed the T1 assessment, 64 of whom had completed the T2 assessment, and none had completed the T3 assessment. Participants of the abandoned trips4health RCT who had completed the T1 assessment were invited to complete two additional assessments (T2v2, then T3 three months later). At each timepoint, participants completed a one-week assessment period in which they wore an accelerometer, completed a seven-day transport diary, and completed an online survey of physical activity, transport behaviours, health, economics, and demographics. Transport smartcard boardings were passively tracked during the 16-week trial period and the 10 weeks pre- and post-trial periods. For a full decription of the data, please refer to the Codebook in the Related Information.Attribution - NonCommercial - No Derivatives(BY - NC - ND)The data that support the findings are stored at the University of Tasmania, Hobart, Australia. Requests for data may be directed to the custodians. Data may be used by researchers outside of the investigator team provided that due ethics processes are adhered to and permission for use is granted by the custodians.https://data.utas.edu.au/metadata/8fc48769-b74e-48cd-98c0-83df9459b8282022Oliver StanesbyVerity ClelandUniversity of Tasmania, Australia2019-092021-03northlimit=-42.6862715084771; southlimit=-43.0903531994036; westlimit=147.006957856938; eastlimit=147.622192231938; projection=WGS84https://orcid.org/0000-0002-5996-5881https://orcid.org/0000-0001-8358-3237https://orcid.org/0000-0001-5603-5024420201200401Translational Medical ResearchDisease OutbreaksTransportation FacilitiesBehaviour and Behaviour MechanismsPublic-Private Sector PartnershipsExercisephysical activitypublic transportcommutingbus useSedentary BehaviourwalkingSharman MJ, Ball K, Greaves S, Jose KA, Morse M, Blizzard CL, Wells G, Venn AJ, Palmer AJ, Lester D, Williams J, Harpur S, Cleland VJ, 'trips4health: Protocol of a single-blinded randomised controlled trial incentivising adults to use public transport for physical activity gain', Contemporary Clinical Trials Communications, 19 Article 100619. ISSN 2451-8654 (2020) [Contribution to Refereed Journal]10.1016/j.conctc.2020.100619UTAS/965ccbeb-6748-4c67-ad0e-56481e97780aUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/965ccbeb-6748-4c67-ad0e-56481e97780aMapped Agricultural Land Capability Classification Data for Australia V.20

https://data.utas.edu.au/metadata/965ccbeb-6748-4c67-ad0e-56481e97780a

This data record contains a national agricultural land capability map for Australia, based on state agricultural land capability datasets reclassified to a single agricultural land capability classification (NSW method) and modeled grazing suitability. The data includes three raster layers (provided as GeoTIFF land_capability). The national scale agricultural land capability map is the primary data product available in the agricultural land capability data package (raster layer with 9 classes adhering to the NSW land capability mapping method definitions). The compiled state and territory land capability data on the unified rating class system is available as a sub product of the agricultural land capability data package (existing_capability GeoTIFF). Pastoral capability based upon modeled grazing suitability is available as a sub product of the agricultural land capability data package (pastoral_capability GeoTIFF).Attribution(BY)https://data.utas.edu.au/metadata/965ccbeb-6748-4c67-ad0e-56481e97780a2022Vanessa AdamsJayden EngertUniversity of Tasmania, Australia2019 - presentnorthlimit=-10.6433329969502; southlimit=-44.5153100248151; westlimit=110.625000447035; eastlimit=154.394531697035; projection=WGS84UTAS/c17b3704-c620-4411-b538-ba76c0b583b4https://orcid.org/0000-0002-3509-7901https://orcid.org/0000-0002-5558-2058https://orcid.org/0000-0001-5603-5024410401300203180603190207Agricultural land capabilityLand capacityLand suitabilitycroppinggrazinghorticultureforestryUTAS/bcc70827-ca48-407e-bc76-941bcaaccf26University of Tasmania, Australiahttps://data.utas.edu.au/metadata/bcc70827-ca48-407e-bc76-941bcaaccf26Dataset Fire recovery and other fire-related traits in 𝘌𝘶𝘤𝘢𝘭𝘺𝘱𝘵𝘶𝘴 𝘨𝘭𝘰𝘣𝘶𝘭𝘶𝘴 (2022-07-01)

https://data.utas.edu.au/metadata/bcc70827-ca48-407e-bc76-941bcaaccf26

Fire-related traits were assessed in a large outcrossed F2 𝘌𝘶𝘤𝘢𝘭𝘺𝘱𝘵𝘶𝘴 𝘨𝘭𝘰𝘣𝘶𝘭𝘶𝘴 population in a field trial in Tasmania, Australia, which was uniformly burnt by a wildfire 14 years after planting. The trial also included open-pollinated families of the grandparental dwarf and tall ecotypes used to produce the F2 population. The data was used to compare ecotypes, study correlations within the F2 population and perform QTL analyses using a linkage map comprised of 480 markers (the list of markers used is included in the Excel file attached).Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/bcc70827-ca48-407e-bc76-941bcaaccf262022Mariano HernándezJakob ButlerHans AmmitzbollJulianne O'Reilly-WapstraJules FreemanRene VaillancourtBrad PottsUniversity of Tasmania, Australia2016-06-292020-02-19east=146.902570724487; north=-43.2167487949353; projection=WGS84https://orcid.org/0000-0003-2557-3342https://orcid.org/0000-0003-1353-3765https://orcid.org/0000-0002-8115-0267https://orcid.org/0000-0003-4801-4412https://orcid.org/0000-0003-1166-9976https://orcid.org/0000-0002-1159-9149https://orcid.org/0000-0001-6244-289Xhttps://orcid.org/0000-0001-5603-5024310899410205310509260299bark thicknessepicormic resproutingEucalyptus globulusherbivorypost-fire recoveryQTL analysiswildfireUTAS/f58bcdf6-b3ed-460a-b3a3-23c9cd53dc59University of Tasmania, Australiahttps://data.utas.edu.au/metadata/f58bcdf6-b3ed-460a-b3a3-23c9cd53dc59Dataset: Fire recovery and other fire-related traits in 𝘌𝘶𝘤𝘢𝘭𝘺𝘱𝘵𝘶𝘴 𝘨𝘭𝘰𝘣𝘶𝘭𝘶𝘴 (2022-07-01)

https://data.utas.edu.au/metadata/f58bcdf6-b3ed-460a-b3a3-23c9cd53dc59

Fire-related traits were assessed in a large outcrossed F2 𝘌𝘶𝘤𝘢𝘭𝘺𝘱𝘵𝘶𝘴 𝘨𝘭𝘰𝘣𝘶𝘭𝘶𝘴 population in a field trial in Tasmania, Australia, which was uniformly burnt by a wildfire 14 years after planting. The trial also included open-pollinated families of the grandparental dwarf and tall ecotypes used to produce the F2 population. The data was used to compare ecotypes, study correlations within the F2 population and perform QTL analyses using a linkage map comprised of 480 markers (the list of markers used is included in the Excel file attached).Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/f58bcdf6-b3ed-460a-b3a3-23c9cd53dc592022Mariano HernándezJakob ButlerHans AmmitzbollJulianne O'Reilly-WapstraJules FreemanRene VaillancourtBrad PottsUniversity of Tasmania, Australia2016-06-292020-02-19east=146.902570724487; north=-43.2167487949353; projection=WGS84https://orcid.org/0000-0003-2557-3342https://orcid.org/0000-0003-1353-3765https://orcid.org/0000-0002-8115-0267https://orcid.org/0000-0003-4801-4412https://orcid.org/0000-0003-1166-9976https://orcid.org/0000-0002-1159-9149https://orcid.org/0000-0001-6244-289Xhttps://orcid.org/0000-0001-5603-5024310899410205310509260299bark thicknessepicormic resproutingEucalyptus globulusherbivorypost-fire recoveryQTL analysiswildfireUTAS/38b4bb8b-919b-47ec-9249-70081c8b0cc7University of Tasmania, Australiahttps://data.utas.edu.au/metadata/38b4bb8b-919b-47ec-9249-70081c8b0cc7Dataset - Free Bus Fares: Exploring impacts on physical activity (Trips4Free)

https://data.utas.edu.au/metadata/38b4bb8b-919b-47ec-9249-70081c8b0cc7

A cross-sectional online survey (using Qualtrics software) collected largely quantitative and some qualitative data. Participants Participants were adult Tasmanian bus users who made use of the free bus fares initiative between 28 March and 1 May 2022. The study explored the impact of the Tasmanian Government’s initiative to provide free public transport over five weeks (Monday 28 March – Sunday 1 May 2022) on physical activity and bus use. The datasets are raw research data, provided in CSV format. Versions of the datasets are indicated by date (with the most-recent being the latest and final version). A copy of the questionaire and description of branching logic are attached in the Related Information.Attribution - NonCommercial - No Derivatives(BY - NC - ND)The data that support the findings are stored at the University of Tasmania, Hobart, Australia. Requests for data may be directed to the custodians. Data may be used by researchers outside of the investigator team provided that due ethics processes are adhered to and permission for use is granted by the custodians.https://data.utas.edu.au/metadata/38b4bb8b-919b-47ec-9249-70081c8b0cc72022Oliver StanesbyVerity ClelandUniversity of Tasmania, Australia2022-05-042022-06-14northlimit=-40.2912586478968; southlimit=-43.877305908411; westlimit=144.276856407523; eastlimit=149.00537095964; projection=WGS84https://orcid.org/0000-0002-5996-5881https://orcid.org/0000-0001-8358-3237https://orcid.org/0000-0001-5603-5024420201200401public transportphysical activitybus usefree faresUTAS/786c658e-777c-49ac-b8c5-ecf64a149935University of Tasmania, Australiahttps://data.utas.edu.au/metadata/786c658e-777c-49ac-b8c5-ecf64a149935Ocean Tide Loading Provider modelling parameter dataset for Australian GNSS sites

https://data.utas.edu.au/metadata/786c658e-777c-49ac-b8c5-ecf64a149935

This record provides a set of blq files that contain harmonic parameters for 11 major tidal constituents modelled at 360 Australian GNSS sites' locations using a variety of ocean tide models and Greens functions (Earth models). The blq files were generated with CARGA software at the Free Ocean Tide Loading Provider (http://holt.oso.chalmers.se/loading). The ocean tide loading displacements timeseries could be reconstructed using HARDISP software utility from IERS software package. Files naming conventions were design to contain all the important parameters: 1) dataset key [GA | None], convenient when working with multiple datasets; 2) ocean tide model [FES2004 | FES2012 | FES2014b | GOT4.10c | GOT4.8 | TPXO8_atl | TPXO9_atl | TPXO9v2a_atl]; 3) Greens function [GBe | PREM | STW105 | S362ANI]; 4) dissipation correction applied [d | None]; 5) spatially varying water density and compressibility corrections [c | s | None]. Both applied [c] or only spatially varying water density correction applied [s]; 7) No water conservation correction is applied to conserve water mass [w | None]; 6) Centre of Mass correction [CM | CE] present [CM] or not [CE]. Note that CM blq files should only be used with JPL native orbit and clock products solutions, CE in all other cases (CODE, ESA, IGS etc. products solutions).Attribution(BY)https://data.utas.edu.au/metadata/786c658e-777c-49ac-b8c5-ecf64a1499352022Bogdan MatviichukMachiel BosUniversity of Tasmania, Australianorthlimit=-10.351169859592; southlimit=-43.9292408613355; westlimit=108.389353752136; eastlimit=160.407364368439; projection=WGS84https://orcid.org/0000-0001-9695-3823https://orcid.org/0000-0002-1946-8637https://orcid.org/0000-0001-5611-9498https://orcid.org/0000-0001-5603-5024401303370899280107OTL displacementsOTLDOcean Tide Loading DisplacementsUTAS/99d8603b-ab7f-4ebf-9a6d-3627e3114d41University of Tasmania, Australiahttps://data.utas.edu.au/metadata/99d8603b-ab7f-4ebf-9a6d-3627e3114d41Copy of Data for geochronology, geochemistry, and zircon Hf-isotopic systematics of the middle Cambrian igneous suites and metasedimentary rocks in western Tasmania and central Victoria

https://data.utas.edu.au/metadata/99d8603b-ab7f-4ebf-9a6d-3627e3114d41

This database contains all the data used in Chapter 2 of Umer Habib's PhD thesis. The location of samples, U-Pb ages, U-Pb acquisition methodology, zircon geochemistry and Hafnium isotope data is contained in separate tabs of the excel file. The supplementary CL images and sample geochemistry is contained in the PDF file. The data can also be requested by contacting Umer Habib at umerhabib990@gmail.com.Attribution(BY)https://data.utas.edu.au/metadata/99d8603b-ab7f-4ebf-9a6d-3627e3114d412022Umer HabibSebastien MeffreUniversity of Tasmania, Australia20212041https://orcid.org/0000-0002-1830-9511https://orcid.org/0000-0003-2741-6076https://orcid.org/0000-0001-5603-5024370502370303370511250307PaleozoicresearchVictoriaTasmaniaU-Pb zircon ageUTAS/7d271e63-54bb-4764-8c5f-16ce4931de57University of Tasmania, Australiahttps://data.utas.edu.au/metadata/7d271e63-54bb-4764-8c5f-16ce4931de57Revision of Data for Provenance of the Palaeozoic sedimentary rocks in TasmaProvenance of the Paleozoic sedimentary rocks in Tasmania and Waratah Bay, south Victoria: Constraints from hafnium isotope and zircon trace element geochemistry

https://data.utas.edu.au/metadata/7d271e63-54bb-4764-8c5f-16ce4931de57

This database contains all the data used in Chapter 5 of Umer Habib's PhD thesis. The data file contains the acquired Hafnium isotope data, previously published hafnium data and zircon geochemistry. The data can also be requested by emailing Umer Habib at umerhabib990@gmail.com.Attribution(BY)https://data.utas.edu.au/metadata/7d271e63-54bb-4764-8c5f-16ce4931de572022Umer HabibSebastien MeffreRon BerryUniversity of Tasmania, Australia20212041UTAS/cf705d34-52d8-4c49-a59f-028cdfd7aafdhttps://orcid.org/0000-0002-1830-9511https://orcid.org/0000-0003-2741-6076https://orcid.org/0000-0002-5547-3396https://orcid.org/0000-0001-5603-5024370303370502370511250307PaleozoicWaratah BayVictoriaTasmaniaHafnium isotopesUTAS/eeeb9e17-3f90-4f5b-9d9b-524b3dab32c0University of Tasmania, Australiahttps://data.utas.edu.au/metadata/eeeb9e17-3f90-4f5b-9d9b-524b3dab32c0Training systems for sweet cherry

https://data.utas.edu.au/metadata/eeeb9e17-3f90-4f5b-9d9b-524b3dab32c0

This dataset contains observational data collected over two seasons between 2019 and 2021. All data was collected in Jericho, Tasmania with analysis conducted at the University of Tasmania, Sandy Bay. Analysis of the data was conducted using various statistical software programs. The cherry tree training systems studied in this data set were the Upright Fruiting Offshoot (UFO), Bibaum (BB), Super Spindle Axe (SSA), Tall Spindle Axe (TSA) and Steep Leader (SL). The cherry industry is increasingly looking for are optimal use of light interception and space within an orchard particularly under protected cropping systems. This studied addressed the question of which training system is most suitable for a lateral bearing fruiting cultivar in a high density planting setting. Training system light interception, fruit quality, flowering and crop load analysis derived from this data.Attribution(BY)https://data.utas.edu.au/metadata/eeeb9e17-3f90-4f5b-9d9b-524b3dab32c02022Cameron StoneUniversity of Tasmania, Australia2019-10-102021-25-01northlimit=-41.9476175018023; southlimit=-43.1614915129406; westlimit=146.409301757813; eastlimit=148.309936523438; projection=WGS84https://orcid.org/0000-0003-4589-6341https://orcid.org/0000-0001-5603-5024300802260511Lighttraining systemcherryUTAS/0f9d9776-f858-421b-b92c-de0ab350d4a3University of Tasmania, Australiahttps://data.utas.edu.au/metadata/0f9d9776-f858-421b-b92c-de0ab350d4a3CaDaGIA GPS and surface loading displacement data AAS4318

https://data.utas.edu.au/metadata/0f9d9776-f858-421b-b92c-de0ab350d4a3

This data supports the 2022 publication: by Matt King, Christopher Watson, and Duanne White of "GPS rates of vertical bedrock motion suggest late Holocene ice-sheet readvance in a critical sector of East Antarctica " paper ID 2021GL097232 submitted to Geophysical Research Letters. The dataset includes bedrock GPS time series, surface loading data, surface loading displacements, common mode error, GPS and GIA model velocities. A README.txt file fully describes the dataset.Attribution - Share Alike(BY - SA)https://data.utas.edu.au/metadata/0f9d9776-f858-421b-b92c-de0ab350d4a32022Matt KingChristopher WatsonUniversity of Tasmania, Australia19792020northlimit=-64.5484401442252; southlimit=-71.8562288818553; westlimit=79.013671875; eastlimit=123.57421875; projection=WGS84https://orcid.org/0000-0001-5611-9498https://orcid.org/0000-0002-7464-4592370603401305280107glacial isostatic adjustmentsurface mass balanceloading displacementGPSbedrock velocitiestotten glacierdenman glacierUTAS/cf612cc9-9f3c-45e7-9eba-19c29758aa1eUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/cf612cc9-9f3c-45e7-9eba-19c29758aa1eThe Tasmania Project - Wellbeing (PESRAC) Survey

https://data.utas.edu.au/metadata/cf612cc9-9f3c-45e7-9eba-19c29758aa1e

The Tasmania Project was established by the Institute for Social Change at the University of Tasmania to understand how Tasmanians are experiencing and adjusting to the social, political and economic responses to COVID-19. The project aims to support immediate and longer term social and economic decisions by providing useful, evidence-based and timely information, and share Tasmanian residents' experiences and ideas through this critical period and beyond. This dataset is for the Wellbeing (PESRAC) Survey, which was open from 19 October - 22 November 2020 and had a final sample size of 2354 respondents. The survey consisted of three sections: 1. Wellbeing (adapting indicators from the OECD Better Life Index), 2. Tasmania’s recovery from COVID-19, 3. Demographic information. This survey was part of Phase 2 of the consultation process conducted by the Premier's Economic and Social Advisory Council (PESRAC) and was designed to support PESRAC in developing advice to the Government on COVID-19 recovery strategies.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/cf612cc9-9f3c-45e7-9eba-19c29758aa1e2021Elizabeth LesterElla HortonNyree PisanuBruce TranterRebecca BanhamAriel RemundUniversity of Tasmania, Australia2020-10-192020-11-22https://orcid.org/0000-0003-1046-2412https://orcid.org/0000-0003-3600-4604https://orcid.org/0000-0003-3495-1114https://orcid.org/0000-0002-0649-6065https://orcid.org/0000-0001-8182-4017https://orcid.org/0000-0003-1326-8244https://orcid.org/0000-0001-5603-5024441004230113communitycommunity involvementCOVID-19educationemploymentenvironmenteveryday lifefood shortagesgovernmenthealthhousehold budgetshousingincomepandemicpublic healthregulationssafetysocial and economic developmentsocial changeTasmaniawellbeingUTAS/efda4156-e49b-4102-908f-4543ee9246e7University of Tasmania, Australiahttps://data.utas.edu.au/metadata/efda4156-e49b-4102-908f-4543ee9246e7The Tasmania Project - Borders and Community Health Survey

https://data.utas.edu.au/metadata/efda4156-e49b-4102-908f-4543ee9246e7

The Tasmania Project was established by the Institute for Social Change at the University of Tasmania to understand how Tasmanians are experiencing and adjusting to the social, political and economic responses to COVID-19. The project aims to support immediate and longer term social and economic decisions by providing useful, evidence-based and timely information, and share Tasmanian residents' experiences and ideas through this critical period and beyond. This dataset is for the Borders and Community Health Survey, which was open from 28 September - 12 October 2020 and had a final sample size of 1377 respondents. The survey consisted of six sections: 1. Border restrictions, 2. Compliance and responsibility, 3. Staying informed, 4. Employment, 5. Wellbeing, 6. Demographic information. This survey was supported by the State Control Centre to inform the Tasmanian Government’s response to COVID-19 and help to develop public communications strategies and policy decisions as borders started to reopen.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/efda4156-e49b-4102-908f-4543ee9246e72021Elizabeth LesterElla HortonNyree PisanuUniversity of Tasmania, Australia2020-09-282020-10-12https://orcid.org/0000-0003-1046-2412https://orcid.org/0000-0003-3600-4604https://orcid.org/0000-0003-3495-1114https://orcid.org/0000-0001-5603-5024441004230113agriculturebehaviourborderscommunitycommunity involvementCOVID-19economicsemploymentenvironmenteventsgovernmenthealthhousingincomeincome supportinformationmediapandemicpublic healthsafetysocial changeTasmaniawellbeingUTAS/211efa28-8957-46de-b54d-6eaa6719827bUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/211efa28-8957-46de-b54d-6eaa6719827bThe Tasmania Project - Creative and Cultural Industries Survey

https://data.utas.edu.au/metadata/211efa28-8957-46de-b54d-6eaa6719827b

The Tasmania Project was established by the Institute for Social Change at the University of Tasmania to understand how Tasmanians are experiencing and adjusting to the social, political and economic responses to COVID-19. The project aims to support immediate and longer term social and economic decisions by providing useful, evidence-based and timely information, and share Tasmanian residents' experiences and ideas through this critical period and beyond. This dataset is for the Creative and Cultural Industries (CCI) Survey, which was open from 6 - 31 August 2020 and had a final sample size of 291 individuals who were working (or had worked), either paid or unpaid, in the creative and cultural industries in Tasmania. The survey consisted of six sections: 1. Involvement in the sector, 2. Work in the sector, 3. Income, 4. COVID-19 recovery for the sector in Tasmania, 5. Concerns and wellbeing, 6. Demographic information. For this survey, we partnered with the Tasmanian Government’s Department of State Growth to understand the impact of the pandemic on Tasmania’s creative and cultural industries and individuals who work in the sector.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/211efa28-8957-46de-b54d-6eaa6719827b2021Elizabeth LesterElla HortonNyree PisanuKathleen WilliamsUniversity of Tasmania, Australia2020-08-062020-08-31https://orcid.org/0000-0003-1046-2412https://orcid.org/0000-0003-3600-4604https://orcid.org/0000-0003-3495-1114https://orcid.org/0000-0001-8530-5361https://orcid.org/0000-0001-5603-5024441004230113artsborderscommunitycommunity involvementCOVID-19cultureeducationemploymentenvironmenteveryday lifegovernmenthealthincomeincome supportlearningpandemicpublic healthregulationssafetysmall businessessocial and economic developmentsocial changeTasmaniatourismwellbeingUTAS/09ad91ac-34ef-4940-9bc8-115b15726139University of Tasmania, Australiahttps://data.utas.edu.au/metadata/09ad91ac-34ef-4940-9bc8-115b15726139The Tasmania Project - Housing Survey

https://data.utas.edu.au/metadata/09ad91ac-34ef-4940-9bc8-115b15726139

The Tasmania Project was established by the Institute for Social Change at the University of Tasmania to understand how Tasmanians are experiencing and adjusting to the social, political and economic responses to COVID-19. The project aims to support immediate and longer term social and economic decisions by providing useful, evidence-based and timely information, and share Tasmanian residents' experiences and ideas through this critical period and beyond. This dataset is for the Housing Survey, which was open from 23 June - 2 July 2020 and had a final sample size of 821 respondents. The survey consisted of four sections: 1. Living arrangements and housing circumstances, 2. Appropriateness of housing, 3. Property as a source of income, 4. Demographic information. For this survey, we partnered with the Australian Housing and Urban Research Institute (AHURI) to generate data on regional housing and household experiences arising from the pandemic to manage the emerging housing needs of the community and support recovery.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/09ad91ac-34ef-4940-9bc8-115b157261392021Elizabeth LesterElla HortonNyree PisanuJulia VerdouwKathleen FlanaganUniversity of Tasmania, Australia2020-06-232020-07-02https://orcid.org/0000-0003-1046-2412https://orcid.org/0000-0003-3600-4604https://orcid.org/0000-0003-3495-1114https://orcid.org/0000-0002-0009-5914https://orcid.org/0000-0002-5585-2871https://orcid.org/0000-0001-5603-5024441004230113communityCOVID-19governmenthome ownershiphousinghousing financeincomeincome supportinvestmentliving standardspandemicpropertypublic healthsocial changeTasmaniaUTAS/52fd6bb6-ca50-4842-a087-36f1e5becd83University of Tasmania, Australiahttps://data.utas.edu.au/metadata/52fd6bb6-ca50-4842-a087-36f1e5becd83The Tasmania Project - Food Survey

https://data.utas.edu.au/metadata/52fd6bb6-ca50-4842-a087-36f1e5becd83

The Tasmania Project was established by the Institute for Social Change at the University of Tasmania to understand how Tasmanians are experiencing and adjusting to the social, political and economic responses to COVID-19. The project aims to support immediate and longer term social and economic decisions by providing useful, evidence-based and timely information, and share Tasmanian residents' experiences and ideas through this critical period and beyond. This dataset is for the Food Survey, which was open from 20 May - 6 June 2020 and had a final sample size of 1170 respondents. The survey consisted of five sections: 1. Access to food, 2. Tasmanian produce, 3. Seafood consumption, 4. Food supply, 5. Demographic information.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/52fd6bb6-ca50-4842-a087-36f1e5becd832021Elizabeth LesterElla HortonNyree PisanuKatherine KentSandra MurrayUniversity of Tasmania, Australia2020-05-202020-06-06https://orcid.org/0000-0003-1046-2412https://orcid.org/0000-0003-3600-4604https://orcid.org/0000-0003-3495-1114https://orcid.org/0000-0002-5330-7044https://orcid.org/0000-0002-2261-7840https://orcid.org/0000-0001-5603-5024441004230113communitycookingCOVID-19fisheriesfood preparationfood productionfood shortagesfood storagefood surplusesgovernmenthousehold budgetspandemicpublic healthseafoodsocial changeTasmaniaTasmanian produceUTAS/b2094df6-f0b1-417b-b1e0-c82c29bf3c24University of Tasmania, Australiahttps://data.utas.edu.au/metadata/b2094df6-f0b1-417b-b1e0-c82c29bf3c24The Tasmania Project - General Survey #5 (TTP5)

https://data.utas.edu.au/metadata/b2094df6-f0b1-417b-b1e0-c82c29bf3c24

The Tasmania Project was established by the Institute for Social Change at the University of Tasmania to understand how Tasmanians are experiencing and adjusting to the social, political and economic responses to COVID-19. The project aims to support immediate and longer term social and economic decisions by providing useful, evidence-based and timely information, and share Tasmanian residents' experiences and ideas through this critical period and beyond. This dataset is for General Survey #5 (TTP5), which was open from 24 September - 3 October 2021 and had a final sample size of 1200 respondents. The survey consisted of five sections: 1. Restrictions and safety, 2. Life in the second year of COVID, 3. Work and employment, 4. Volunteering, 5. Demographic information.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/b2094df6-f0b1-417b-b1e0-c82c29bf3c242021Elizabeth LesterElla HortonNyree PisanuAmi SeivwrightUniversity of Tasmania, Australia2021-09-242021-10-03https://orcid.org/0000-0003-1046-2412https://orcid.org/0000-0003-3600-4604https://orcid.org/0000-0003-3495-1114https://orcid.org/0000-0002-6226-0719https://orcid.org/0000-0001-5603-5024441004230113access to health servicesborderscommunityCOVID-19digital accesseducationemploymentenvironmenteventseveryday lifefood shortagesfood storagegovernmenthealthincomeinformationpandemicpublic healthregulationssafetysocial and economic developmentsocial changeTasmania. vaccinationvolunteeringwellbeingUTAS/bb4b93ad-6d32-41e8-94c0-01af59893991University of Tasmania, Australiahttps://data.utas.edu.au/metadata/bb4b93ad-6d32-41e8-94c0-01af59893991The Tasmania Project - General Survey #4 (TTP4)

https://data.utas.edu.au/metadata/bb4b93ad-6d32-41e8-94c0-01af59893991

The Tasmania Project was established by the Institute for Social Change at the University of Tasmania to understand how Tasmanians are experiencing and adjusting to the social, political and economic responses to COVID-19. The project aims to support immediate and longer term social and economic decisions by providing useful, evidence-based and timely information, and share Tasmanian residents' experiences and ideas through this critical period and beyond. This dataset is for General Survey #4 (TTP4), which was open from 29 April - 12 May 2021 and had a final sample size of 1176 respondents. The survey consisted of seven sections: 1. Restrictions and safety, 2. Vaccinations, 3. Wellbeing and concerns, 4. Employment and financial wellbeing, 5. Travel and events, 6. Food access and supply, 7. Demographic information.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/bb4b93ad-6d32-41e8-94c0-01af598939912021Elizabeth LesterElla HortonNyree PisanuUniversity of Tasmania, Australia2021-04-292021-05-12https://orcid.org/0000-0003-1046-2412https://orcid.org/0000-0003-3600-4604https://orcid.org/0000-0003-3495-1114https://orcid.org/0000-0001-5603-5024441004230113access to health servicesborderscommunitycommunity involvementCOVID-19dairy productsdigital accessemploymentenvironmenteventseveryday lifefarmingfisheriesfood productionfood shortagesfood storagegovernmenthealthhousehold budgetshousingincomeincome supportinformationinternational relationsmediapandemicpublic healthred meatregulationssafetyseafoodsmall businessessocial changeTasmaniatourismtravelvaccinationwellbeingUTAS/8e77b955-b858-41dd-9858-328519b7c962University of Tasmania, Australiahttps://data.utas.edu.au/metadata/8e77b955-b858-41dd-9858-328519b7c962The Tasmania Project - General Survey #3 (TTP3)

https://data.utas.edu.au/metadata/8e77b955-b858-41dd-9858-328519b7c962

The Tasmania Project was established by the Institute for Social Change at the University of Tasmania to understand how Tasmanians are experiencing and adjusting to the social, political and economic responses to COVID-19. The project aims to support immediate and longer term social and economic decisions by providing useful, evidence-based and timely information, and share Tasmanian residents' experiences and ideas through this critical period and beyond. This dataset is for General Survey #3 (TTP3), which was open from 26 August – 6 September 2020 and had a final sample size of 1133 respondents. The survey consisted of seven sections: 1. Restrictions and measures, 2. Wellbeing and concerns, 3. Food access and supply, 4. Tasmania’s connections to the world, 5. Where you live, 6. Work and employment, 7. Demographic information.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/8e77b955-b858-41dd-9858-328519b7c9622021Elizabeth LesterElla HortonNyree PisanuKatherine KentSandra MurrayUniversity of Tasmania, Australia2020-08-262020-09-06https://orcid.org/0000-0003-1046-2412https://orcid.org/0000-0003-3600-4604https://orcid.org/0000-0003-3495-1114https://orcid.org/0000-0002-5330-7044https://orcid.org/0000-0002-2261-7840https://orcid.org/0000-0001-5603-5024441004230113borderscommunitycommunity involvementCOVID-19digital accessdiscriminationeducationemploymentenvironmenteventseveryday lifefoodfood shortagesfood storagegovernmenthealthhousehold budgetshousinghousing financeincomeincome supportinformal careinformationinternational relationslearningpandemicpublic healthregulationssafetysocial and economic developmentsocial changeTasmaniatourismtravelvaccinationwellbeingUTAS/fbee4d33-9a59-4439-9c36-9b73f1815a42University of Tasmania, Australiahttps://data.utas.edu.au/metadata/fbee4d33-9a59-4439-9c36-9b73f1815a42The Tasmania Project - General Survey #2 (TTP2)

https://data.utas.edu.au/metadata/fbee4d33-9a59-4439-9c36-9b73f1815a42

The Tasmania Project was established by the Institute for Social Change at the University of Tasmania to understand how Tasmanians are experiencing and adjusting to the social, political and economic responses to COVID-19. The project aims to support immediate and longer term social and economic decisions by providing useful, evidence-based and timely information, and share Tasmanian residents' experiences and ideas through this critical period and beyond. This dataset is for General Survey #2 (TTP2), which was open from from 9 – 17 June 2020 and had a final sample size of 1258 respondents. The survey consisted of eight sections: 1. Official COVID-19 measures, 2. The future in Tasmania, 3. Wellbeing and concerns, 4. Arts and culture, 5. Work and employment, 6. Financial wellbeing, 7. Use of communications technologies, 8. Demographic information.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/fbee4d33-9a59-4439-9c36-9b73f1815a422021Elizabeth LesterElla HortonNyree PisanuMatthew AllenKathleen WilliamsUniversity of Tasmania, Australia2020-06-092020-06-17https://orcid.org/0000-0003-1046-2412https://orcid.org/0000-0003-3600-4604https://orcid.org/0000-0003-3495-1114https://orcid.org/0000-0002-8882-8763https://orcid.org/0000-0001-8530-5361https://orcid.org/0000-0001-5603-5024441004230113artsborderscommunitycommunity involvementCOVID-19creativitycultural tourismculturedigital accesseconomic and social developmentemploymentenvironmenteventseveryday lifegovernmenthealthhealth serviceshousehold budgetshousingincomeincome supportinformationinternet usemediapandemicpublic healthregulationssafetysocial changeTasmaniawellbeingUTAS/d0bf782a-70de-46c6-93e4-14cc85915e62University of Tasmania, Australiahttps://data.utas.edu.au/metadata/d0bf782a-70de-46c6-93e4-14cc85915e62The Tasmania Project - General Survey #1 (TTP1)

https://data.utas.edu.au/metadata/d0bf782a-70de-46c6-93e4-14cc85915e62

The Tasmania Project was established by the Institute for Social Change at the University of Tasmania to understand how Tasmanians are experiencing and adjusting to the social, political and economic responses to COVID-19. The project aims to support immediate and longer term social and economic decisions by providing useful, evidence-based and timely information, and share Tasmanian residents' experiences and ideas through this critical period and beyond. This dataset is for General Survey #1 (TTP1), which was open from 20 April - 10 May 2020 and had a final sample size of 1159 respondents. The survey consisted of ten sections: 1. Adjusting to life in the time of COVID-19, 2. Connections and support, 3. Staying informed, 4. Official responses to COVID-19, 5. Concerns, 6. The future in Tasmania, 7. Housing, 8. Work and employment, 9. School and learning, 10. Demographic information.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/d0bf782a-70de-46c6-93e4-14cc85915e622021Elizabeth LesterElla HortonNyree PisanuBruce TranterRebecca BanhamLisa DennyUniversity of Tasmania, Australia2020-04-202020-05-10https://orcid.org/0000-0003-1046-2412https://orcid.org/0000-0003-3600-4604https://orcid.org/0000-0003-3495-1114https://orcid.org/0000-0002-0649-6065https://orcid.org/0000-0001-8182-4017https://orcid.org/0000-0001-9842-1556https://orcid.org/0000-0001-5603-5024441004230113access to health servicesborderscommunityCOVID-19digital accesseconomic and social developmenteducationemotional statesemploymentenvironmenteveryday lifefoodgovernmenthealthhousehold budgetshousinginformal careinformationinternet uselearningmediapandemicpublic healthregulationssafetysocial changeTasmaniawellbeingUTAS/c17b3704-c620-4411-b538-ba76c0b583b4University of Tasmania, Australiahttps://data.utas.edu.au/metadata/c17b3704-c620-4411-b538-ba76c0b583b4Mapped Agricultural Land Capability Classification Data for Australia

https://data.utas.edu.au/metadata/c17b3704-c620-4411-b538-ba76c0b583b4

This data record contains a national agricultural land capability map for Australia, based on modeled grazing suitability mosaiced with harmonized state agricultural land capability datasets. The data is a single raster layer (provided as GeoTIFF) with 9 classes adhering to the NSW land capability mapping method definitions. Access to this data collection is by request to the owner (Vanessa Adams) via the contact email address (vm.adams@utas.edu.au).Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/c17b3704-c620-4411-b538-ba76c0b583b42021Vanessa AdamsJayden EngertUniversity of Tasmania, Australia2019 - presentnorthlimit=-10.6433329969502; southlimit=-44.5153100248151; westlimit=110.625000447035; eastlimit=154.394531697035; projection=WGS84https://orcid.org/0000-0002-3509-7901https://orcid.org/0000-0002-5558-2058https://orcid.org/0000-0001-5603-5024410401300203180603190207Agricultural land capabilityLand capacityLand suitabilitycroppinggrazinghorticultureforestryUTAS/592df23a-08d1-4493-844e-cd25b4dcd8e3University of Tasmania, Australiahttps://data.utas.edu.au/metadata/592df23a-08d1-4493-844e-cd25b4dcd8e3Post-fire responses of the Tasmanian conifer Athrotaxis cupressoides

https://data.utas.edu.au/metadata/592df23a-08d1-4493-844e-cd25b4dcd8e3

Athrotaxis cupressoides is an iconic Tasmanian palaeoendemic conifer that is vulnerable to fire. A survey of three populations burnt by severe fire in 2016, conducted 1 year post-fire, found 33% of stems were still alive, with many surviving stems suffering some canopy scorch. We re-surveyed these populations to quantify delayed mortality, resprouting, and presence of juveniles, and to determine whether fire impacts can be reliably assessed after 1 year. We applied three measures of fire severity: canopy scorched, canopy consumed, and the minimum burnt twig diameter of neighbouring shrubs.Attribution(BY)https://data.utas.edu.au/metadata/592df23a-08d1-4493-844e-cd25b4dcd8e32021Aimee BlissLynda PriorDavid BowmanUniversity of Tasmania, Australiahttps://orcid.org/0000-0001-5573-0543https://orcid.org/0000-0002-5511-2320https://orcid.org/0000-0001-8075-124X300703190401Athrotaxis cupressoidesburnt twig diametercrown volume scorchedcrown volume consumeddelayed mortalityfire-caused mortalitypalaeoendemicregeneration failureresproutTasmaniapencil pineBowman DMJS, Bliss A, Bowman CJW, Prior LD, 'Fire caused demographic attrition of the Tasmanian palaeoendemic conifer Athrotaxis cupressoides', Austral Ecology, 44, (8) pp. 1322-1339. ISSN 1442-9985 (2019) [Refereed Article]10.1111/aec.12789Bliss A, Prior LD, Bowman DMJS, 'Lack of reliable post-fire recovery mechanisms makes the iconic Tasmanian conifer Athrotaxis cupressoides susceptible to population decline', Australian Journal of Botany, 69, (3) Article BT20117. ISSN 0067-1924 (2021) [Refereed Article]10.1071/BT20117UTAS/c773ac73-5545-4361-bfe9-2d2518c9b056University of Tasmania, Australiahttps://data.utas.edu.au/metadata/c773ac73-5545-4361-bfe9-2d2518c9b056Author publications per year

https://data.utas.edu.au/metadata/c773ac73-5545-4361-bfe9-2d2518c9b056

This dataset contains two samples - one for authors publishing in multidisciplinary journals in 2020 (Nature, Science, PNAS) and one publishing in a list of disciplinary journals in 2020Attribution(BY)https://data.utas.edu.au/metadata/c773ac73-5545-4361-bfe9-2d2518c9b0562021dave kendalUniversity of Tasmania, Australia1970-2020https://orcid.org/0000-0003-2816-1722440710280109publication metricsresearchearly career rearchersUTAS/e7558680-aab6-4429-ad5b-1921440470adUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/e7558680-aab6-4429-ad5b-1921440470adPacBio HiFi DNA sequence data from male Carinascincus ocellatus

https://data.utas.edu.au/metadata/e7558680-aab6-4429-ad5b-1921440470ad

PacBio HiFi DNA sequence data from male Carinascincus ocellatusAttribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/e7558680-aab6-4429-ad5b-1921440470ad2021Christopher BurridgeUniversity of Tasmania, Australia20212021east=146.721038818359; north=-41.9880773830916; projection=WGS84https://orcid.org/0000-0002-8185-6091310509280102PacBio HiFiCarinascincus ocellatusUTAS/8ea4a33b-4646-4a15-9a41-d5f11d7a7c69University of Tasmania, Australiahttps://data.utas.edu.au/metadata/8ea4a33b-4646-4a15-9a41-d5f11d7a7c69Data for detrital zircon ages, provenance and tectonic evolution in the early Paleozoic of Tasmania and Waratah Bay, Victoria

https://data.utas.edu.au/metadata/8ea4a33b-4646-4a15-9a41-d5f11d7a7c69

This database contains all the data used in Chapter 3 of Umer Habib's PhD thesis which is published in Australian Journal of Earth Sciences. The U-Pb ages, U-Pb acquisition methodology, 2-D statistics and published U-Pb data is contained in separate tabs of the excel file. The data can also be requested by contacting Umer Habib at umerhabib990@gmail.com.Attribution(BY)https://data.utas.edu.au/metadata/8ea4a33b-4646-4a15-9a41-d5f11d7a7c692021Umer HabibSebastien MeffreRon BerryUniversity of Tasmania, Australia20212041northlimit=-40.7672295937329; southlimit=-44.1222961906634; westlimit=144.94042955339; eastlimit=148.67578111589; projection=WGS84https://orcid.org/0000-0002-1830-9511https://orcid.org/0000-0003-2741-6076https://orcid.org/0000-0002-5547-3396https://orcid.org/0000-0001-5603-5024370502370511370301250307detrital zircon U-Pb agesTasmaniaWaratah BayVictoriaresearchPaleozoicpaleozoicHabib U, Meffre S, Berry R, Kultaksayos S, 'Detrital zircon ages, provenance and tectonic evolution in the early Paleozoic of Tasmania and Waratah Bay, Victoria', Australian Journal of Earth Sciences pp. 1-16. ISSN 0812-0099 (2021) [Refereed Article]10.1080/08120099.2022.2000493UTAS/cf705d34-52d8-4c49-a59f-028cdfd7aafdUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/cf705d34-52d8-4c49-a59f-028cdfd7aafdData for Provenance of the Palaeozoic sedimentary rocks in TasmaProvenance of the Paleozoic sedimentary rocks in Tasmania and Waratah Bay, south Victoria: Constraints from hafnium isotope and zircon trace element geochemistry

https://data.utas.edu.au/metadata/cf705d34-52d8-4c49-a59f-028cdfd7aafd

This database contains all the data used in Chapter 5 of Umer Habib's PhD thesis. The data file contains the acquired Hafnium isotope data, previously published hafnium data and zircon geochemistry. The data can also be requested by emailing Umer Habib at umerhabib990@gmail.com.Attribution(BY)https://data.utas.edu.au/metadata/cf705d34-52d8-4c49-a59f-028cdfd7aafd2021Umer HabibSebastien MeffreRon BerryUniversity of Tasmania, Australia20212041https://orcid.org/0000-0002-1830-9511https://orcid.org/0000-0003-2741-6076https://orcid.org/0000-0002-5547-3396https://orcid.org/0000-0001-5603-5024370303370502370511250307PaleozoicWaratah BayVictoriaTasmaniaHafnium isotopesUTAS/7786cc93-85eb-45e2-a94c-cd28cddc4d37University of Tasmania, Australiahttps://data.utas.edu.au/metadata/7786cc93-85eb-45e2-a94c-cd28cddc4d37Data for geochronology, geochemistry, and zircon Hf-isotopic systematics of the middle Cambrian igneous suites and metasedimentary rocks in western Tasmania and central Victoria

https://data.utas.edu.au/metadata/7786cc93-85eb-45e2-a94c-cd28cddc4d37

This database contains all the data used in Chapter 2 of Umer Habib's PhD thesis. The location of samples, U-Pb ages, U-Pb acquisition methodology, zircon geochemistry and Hafnium isotope data is contained in separate tabs of the excel file. The supplementary CL images and sample geochemistry is contained in the PDF file. The data can also be requested by contacting Umer Habib at umerhabib990@gmail.com.Attribution(BY)https://data.utas.edu.au/metadata/7786cc93-85eb-45e2-a94c-cd28cddc4d372021Umer HabibSebastien MeffreUniversity of Tasmania, Australia20212041https://orcid.org/0000-0002-1830-9511https://orcid.org/0000-0003-2741-6076https://orcid.org/0000-0001-5603-5024370502370303370511250307PaleozoicresearchVictoriaTasmaniaU-Pb zircon ageUTAS/9497e63a-22a0-424c-a7ca-c20006e2fe3dUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/9497e63a-22a0-424c-a7ca-c20006e2fe3dAuScope Geodetic VLBI: AUSTRAL observing program data

https://data.utas.edu.au/metadata/9497e63a-22a0-424c-a7ca-c20006e2fe3d

The AUSTRAL observing program was started in 2011, performing geodetic and astrometric very long baseline interferometry (VLBI) sessions using the new Australian AuScope VLBI antennas at Hobart, Katherine, and Yarragadee. These sessions are organised and performed by the operations centre in Hobart and support innovative research on the observations and operations at the University of Tasmania, in the fields of geodesy, astrometry and astronomy. The telescopes regularly participate in global-scale VLBI experiments organised through the international VLBI service (IVS). Access to these data is via the email address (jamie.mccallum@utas.edu.au) in the contact field above, or via tiegem@utas.edu.au.Attribution(BY)https://data.utas.edu.au/metadata/9497e63a-22a0-424c-a7ca-c20006e2fe3d2021Jamie McCallumJames LovellLucia McCallumTiege McCarthyChin Chuan LimAhmad JaradatUniversity of Tasmania, Australia2011 to presentnorthlimit=-10.7037917116807; southlimit=-44.0560116957853; westlimit=112.7197265625; eastlimit=154.0283203125; projection=WGS84https://orcid.org/0000-0002-0233-6937https://orcid.org/0000-0001-5273-9817https://orcid.org/0000-0002-7563-9488https://orcid.org/0000-0001-9525-7981https://orcid.org/0000-0003-0612-8921https://orcid.org/0000-0003-3221-1008https://orcid.org/0000-0001-5603-5024370603510102510104280107280120geodesyVLBIastrometryradioastronomygeodetic VLBIPlank L, Shabala SS, McCallum JN, Krasna H, Petrachenko B, Rastorgueva-Foi E, Lovell JEJ, 'On the estimation of a celestial reference frame in the presence of source structure', Monthly Notices of the Royal Astronomical Society, 455, (1) pp. 343-356. ISSN 0035-8711 (2016) [Refereed Article]10.1093/mnras/stv2080Shu F, Petrov L, Jiang W, Xia B, Jiang T, Cui Y, Takefuji K, McCallum J, Lovell J, Yi S-O, Hao L, Yang W, Zhang H, Chen Z, Li J, 'VLBI ecliptic plane survey: VEPS-1', Astrophysical Journal, Supplement Series, 230, (2) Article 13. ISSN 0067-0049 (2017) [Refereed Article]10.3847/1538-4365/aa71a3McCallum L, Mayer D, Le Bail K, Schartner M, McCallum J, Lovell J, Titov O, Shu F, Gulyaev S, 'Star scheduling mode - a new observing strategy for monitoring weak southern radio sources with the AuScope VLBI Array', Publications of the Astronomical Society of Australia, 34 Article e063. ISSN 1448-6083 (2017) [Refereed Article]10.1017/pasa.2017.58Plank L, Lovell JEJ, Shabala SS, Bohm J, Titov O, 'Challenges for geodetic VLBI in the southern hemisphere', Advances in Space Research, 56, (2) pp. 304-313. ISSN 0273-1177 (2015) [Refereed Article]10.1016/j.asr.2015.04.022Iles EJ, McCallum L, Lovell JEJ, McCallum JN, 'Automated and dynamic scheduling for geodetic VLBI - a simulation study for AuScope and global networks', Advances in Space Research, 61, (3) pp. 962-973. ISSN 0273-1177 (2018) [Refereed Article]10.1016/j.asr.2017.11.012Sun J, Tang G, Shu F, Li X, Liu S, Cao J, Hellerschmeid A, Bohm J, McCallum L, McCallum J, Lovell J, Haas R, Neidhardt A, Lu W, Han S, Ren T, Chen L, Wang M, Ping J, 'VLBI observations to the APOD satellite', Advances in Space Research, 61, (3) pp. 823-829. ISSN 0273-1177 (2018) [Refereed Article]10.1016/j.asr.2017.10.046Litvinov DA, Rudenko VN, Alakoz AV, Bach U, Bartel N, Belonenko AV, Belousov KG, Bietenholz M, Biriukov AV, Carman R, Cimo G, Courde C, Dirkx D, Duev DA, Filetkin AI, Granato G, Gurvits LI, Gusev AV, Haas R, Herold G, Kahlon A, Kanevsky BZ, Kauts VL, Kopelyansky GD, Kovalenko AV, Kronschnabl G, Kulagin VV, Kutkin AM, Lindqvist M, Lovell JEJ, Mariey H, McCallum J, Molera Calves G, Moore C, Moore K, Neidhardt A, Plotz C, Pogrebenko SV, Pollard A, Porayko NK, Quick J, Smirnov AI, Sokolovsky KV, Stepanyants VA, Torre JM, de Vicente P, Yang J, Zakhvatkin MV, 'Probing the gravitational redshift with an Earth-orbiting satellite', Physics Letters, Section A: General, Atomic and Solid State Physics, 382, (33) pp. 2192-2198. ISSN 0375-9601 (2018) [Refereed Article]10.1016/j.physleta.2017.09.014Md Said N, Ellingsen SP, Bignall HE, Shabala S, McCallum JN, Reynolds C, 'Interstellar scintillation of an extreme scintillator: PKS B1144-379', Monthly Notices of the Royal Astronomical Society, 498, (4) pp. 4615-4634. ISSN 0035-8711 (2020) [Refereed Article]10.1093/mnras/staa2642Plank L, Lovell JEJ, McCallum JN, Mayer D, Reynolds C, Quick J, Weston S, Titov O, Shabala SS, Bohm J, Natusch T, Nickola M, Gulyaev S, 'The AUSTRAL VLBI observing program', Journal of Geodesy, 91, (7) pp. 803-817. ISSN 0949-7714 (2017) [Refereed Article]10.1007/s00190-016-0949-yDuev DA, Pogrebenko SV, Cimo G, Molera Calves G, Bocanegra Bahamon TM, Gurvits LI, Kettenis MM, Kania J, Tudose V, Rosenblatt P, Marty J-C, Lainey V, de Vicente P, Quick J, Nickola M, Neidhardt A, Kronschnabl G, Ploetz C, Haas R, Lindqvist M, Orlati A, Ipatov AV, Kharinov MA, Mikhailov AG, Lovell JEJ, McCallum JN, Stevens J, Gulyaev SA, Natush T, Weston S, Wang WH, Xia B, Yang WJ, Hao L-F, Kallunki J, Witasse O, 'Planetary Radio Interferometry and Doppler Experiment (PRIDE) technique: A test case of the Mars Express Phobos fly-by', Astronomy & Astrophysics, 593 Article A34. ISSN 1432-0746 (2016) [Refereed Article]10.1051/0004-6361/201628869Lovell JEJ, McCallum JN, Reid PB, McCulloch PM, Baynes BE, Dickey JM, Shabala SS, Watson CS, Titov O, Ruddick R, Twilley R, Reynolds C, Tingay SJ, Shield P, Adada R, Ellingsen SP, Morgan JS, Bignall HE, 'The AuScope geodetic VLBI array', Journal of Geodesy, 87, (6) pp. 527-538. ISSN 0949-7714 (2013) [Refereed Article]10.1007/s00190-013-0626-3Titov O, Girdiuk A, Lambert SB, Lovell J, McCallum J, Shabala S, McCallum L, Mayer D, Schartner M, de Witt A, Shu F, Melnikov A, Ivanov D, Mikhailov A, Yi S, Soja B, Xia B, Jiang T, 'Testing general relativity with geodetic VLBI. What a single, specially designed experiment can teach us', Astronomy and Astrophysics, 168 Article A8. ISSN 1432-0746 (2018) [Refereed Article]10.1051/0004-6361/201833459Hellerschmied A, McCallum L, McCallum J, Sun J, Bohm J, Cao J, 'Observing APOD with the AuScope VLBI array', Sensors, 18, (5) Article 1587. ISSN 1424-8220 (2018) [Refereed Article]10.3390/s18051587UTAS/7a2b5896-0a8a-42c7-bcad-3f66bb62e952University of Tasmania, Australiahttps://data.utas.edu.au/metadata/7a2b5896-0a8a-42c7-bcad-3f66bb62e952Carinascincus ocellatus HiC DNA sequence data

https://data.utas.edu.au/metadata/7a2b5896-0a8a-42c7-bcad-3f66bb62e952

HiC DNA sequence data from a male Carinascincus ocellatus from Miena, TasmaniaAttribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/7a2b5896-0a8a-42c7-bcad-3f66bb62e9522021Christopher BurridgeUniversity of Tasmania, Australia20212021east=146.732782367617; north=-41.9852007090533; projection=WGS84https://orcid.org/0000-0002-8185-6091310509280102HiCDNA sequenceUTAS/f4db03a9-f500-45da-aa3b-f675f503e82dUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/f4db03a9-f500-45da-aa3b-f675f503e82dCarinascinus ocellatus transcriptome - liver

https://data.utas.edu.au/metadata/f4db03a9-f500-45da-aa3b-f675f503e82d

Transcriptomes from high elevation population of Carinascincus ocellatus. 3 males and 3 females at each population. Liver tissue.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/f4db03a9-f500-45da-aa3b-f675f503e82d2021Christopher BurridgeUniversity of Tasmania, Australia20212021east=146.732288987841; north=-41.9831421851238; projection=WGS84https://orcid.org/0000-0002-8185-6091310509280102TransciptomeCarinascincus ocellatusLiverUTAS/c2f81258-628e-46b3-8e67-d191d8520eaaUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/c2f81258-628e-46b3-8e67-d191d8520eaaHans Ammitzboll PhD Thesis Appendices

https://data.utas.edu.au/metadata/c2f81258-628e-46b3-8e67-d191d8520eaa

Supporting data for Chapters 3 and 5Attribution(BY)https://data.utas.edu.au/metadata/c2f81258-628e-46b3-8e67-d191d8520eaa2021Hans AmmitzbollUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-8115-0267310409310703180601silviculturebacteriafungisoilfireUTAS/15ffe371-b2e4-4c33-9bdc-5bdf9eb25951University of Tasmania, Australiahttps://data.utas.edu.au/metadata/15ffe371-b2e4-4c33-9bdc-5bdf9eb25951Vela Pulsar Single Pulse Data Archive

https://data.utas.edu.au/metadata/15ffe371-b2e4-4c33-9bdc-5bdf9eb25951

This dataset contains approximately 1 PB of single-pulse observations of the Vela pulsar (J0835-4510). The data was collected mainly from the Mt Pleasant 26 metre radio telescope, but also includes some data from the Ceduna 30 metre radio telescope. The date range is from 2007 to present, however observations were sporadic prior to 2013. The data has been folded using DSPSR with (in most cases) 16 frequency channels, 8192 timing bins, and includes full Stokes (uncalibrated). The centre frequency is mostly 1376 MHz and a bandwidth of 64 MHz. There are approximately 800 million single pulses from Vela observed at Mt Pleasant alone. The single pulse observation of the 2016 Vela glitch that was published in Nature is included in this dataset. Access to this data collection is by request to the owner via the contact email address above, or via jim77742@gmail.com.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/15ffe371-b2e4-4c33-9bdc-5bdf9eb259512021Jim PalfreymanUniversity of Tasmania, Australia2007 to presentnorthlimit=-31.5935092069905; southlimit=-44.1002094522514; westlimit=132.73681640625; eastlimit=148.86474609375; projection=WGS84https://orcid.org/0000-0001-8691-8039https://orcid.org/0000-0001-5603-5024510104510106280120Vela pulsarJ0835-4510neutron starsnon-thermal radiation mechanismsgravitational wavesgamma raysx-rayspulsar wind nebulaepulsarsPalfreyman J, 'A long-term single-pulse study of the Vela pulsar' (2018) [PhD]10.25959/100.00030030Pellizzoni A, Trois A, Tavani M, Pilia M, Giuliani A, Pucella G, Esposito P, Sabatini S, Piano G, Argan A, Barbiellini G, Bulgarelli A, Burgay M, Caraveo P, Cattaneo PW, Chen AW, Cocco V, Contessi T, Costa E, D'Ammando F, Del Monte E, De Paris G, Di Cocco G, Di Persio G, Donnarumma I, Evangelista Y, Feroci M, Ferrari A, Fiorini M, Fuschino F, Galli M, Gianotti F, Hotan A, Labanti C, Lapshov I, Lazzarotto F, Lipari P, Longo F, Marisaldi M, Mastropietro M, Mereghetti S, Moretti E, Morselli A, Pacciani L, Palfreyman J, Perotti F, Picozza F, Pittori C, Possenti A, Prest M, Rapisarda M, 'Detection of gamma-ray emission from the Vela pulsar wind nebula with AGILE', Science, 327, (5966) pp. 663-665. ISSN 0036-8075 (2010) [Refereed Article]10.1126/science.1183844Palfreyman J, Dickey JM, Hotan A, Ellingsen S, van Straten W, 'Alteration of the magnetosphere of the Vela pulsar during a glitch', Nature, 556, (7700) pp. 219-222. ISSN 0028-0836 (2018) [Refereed Article]10.1038/s41586-018-0001-xPalfreyman JL, Dickey JM, Ellingsen SP, Jones IR, Hotan AW, 'Temporal evolution of the Vela pulsar's pulse profile', The Astrophysical Journal, 820, (1) Article 64. ISSN 0004-637X (2016) [Refereed Article]10.3847/0004-637X/820/1/64Buchner S, Hotan A, Palfreyman J, 'Beating the spin-down limit on gravitational wave emission from the Vela pulsar', The Astrophysical Journal, 737, (2) Article 93. ISSN 0004-637X (2011) [Refereed Article]10.1088/0004-637X/737/2/93Palfreyman JL, Hotan AW, Dickey JM, Young TG, Trenham C, 'Consecutive bright pulses in the vela pulsar', The Astrophysical Journal Letters, 735, (1) Article L17. ISSN 2041-8205 (2011) [Refereed Article]10.1088/2041-8205/735/1/L17Pellizzoni A, Pilia M, Possenti A, Fornari F, Caraveo P, Del Monte E, Mereghetti S, Tavani M, Argan A, Trois A, Burgay M, Chen A, Cognard I, Costa E, D'Amico N, Esposito P, Evangelista Y, Feroci M, Fuschino F, Giuliani A, Halpern J, Hobbs G, Hotan A, Johnston S, Kramer M, Longo F, Manchester RN, Marisaldi M, Palfreyman J, Weltevrede P, Barbiellini G, Boffelli F, Bulgarelli A, Cattaneo PW, Cocco V, D'Ammando F, De Paris G, Di Cocco G, Donnarumma I, Fiorini M, Froysland T, Galli M, Gianotti F, Harding A, Labanti C, Lapshov I, Lazzarotto F, Lipari P, Mauri F, Morselli A, Pacciani L, Perotti F, Picozza P, Prest M, Pucella G, Rapisarda M, Rappoldi A, Soffitta P, Trifoglio M, Vallazza E, Vercellone S, Vittorini V, Zambra A, Zanello D, Pittori C, Verrecchia F, Preger B, Santolamazza P, Giommi P, Salotti L, 'High-resolution timing observations of spin-powered pulsars with the AGILE gamma-ray telescope', The Astrophysical Journal, 691, (2) pp. 1618-1633. ISSN 0004-637X (2009) [Refereed Article]10.1088/0004-637X/691/2/1618UTAS/8e445cde-99b8-4514-a621-54befb94dc29University of Tasmania, Australiahttps://data.utas.edu.au/metadata/8e445cde-99b8-4514-a621-54befb94dc29Data for paleomagnetic testing of the Lachlan Orocline hypothesis: Overprinting of remanence in Paleozoic rocks of the Lachlan Orogen in southeast Australia

https://data.utas.edu.au/metadata/8e445cde-99b8-4514-a621-54befb94dc29

This data set contains supplementary data for Umer Habib's PhD thesis chapter 4. Chapter 4 appendices contains the description for the locations of the samples acquired along with recent and previously published paleo pole data, thermal and alternating field demagnetisation and specific gravity for each sample.. The SEM images and spectrum of the analyzed magnetic grains is also included in separate docx and excel files. The data can also be requested by contacting Umer Habib at umerhabib990@gmail.com.Attribution(BY)https://data.utas.edu.au/metadata/8e445cde-99b8-4514-a621-54befb94dc292021Umer HabibSebastien MeffreRobert MusgraveUniversity of Tasmania, Australia20212041northlimit=-34.2926227986861; southlimit=-38.9457390802466; westlimit=144.351561963558; eastlimit=150.679686963558; projection=WGS84https://orcid.org/0000-0002-1830-9511https://orcid.org/0000-0003-2741-6076https://orcid.org/0000-0003-0485-4081https://orcid.org/0000-0001-5603-5024370607370604280107PaleomagnetismVictoriaNew South WalesPaleozoic eraHabib U, Musgrave R, Meffre S, 'Paleomagnetic testing of the Lachlan Orocline hypothesis: overprinting of remanence in Paleozoic rocks of the Lachlan Orogen in southeast Australia', Australian Journal of Earth Sciences pp. 1-22. ISSN 0812-0099 (2021) [Refereed Article]10.1080/08120099.2021.1918246UTAS/39660933-1616-4ad6-8157-4ad12a8d7a02University of Tasmania, Australiahttps://data.utas.edu.au/metadata/39660933-1616-4ad6-8157-4ad12a8d7a02Native for whom: a mixed-methods literature review and synthesis to conceptualise biotic nativeness for social research in the urban context [Study 2 data]

https://data.utas.edu.au/metadata/39660933-1616-4ad6-8157-4ad12a8d7a02

Dataset of all papers (n=37) included in a systematic literature review of quantitative social research on perceptions of nativeness in urban contexts (Study 2). The purpose of the study was to assess the extent to which the literature measuring public perceptions of native and non-native plants addresses the dimensions of nativeness identified in Study 1 in urban contexts. Papers were identified from a search of the Scopus database in January 2021. Data extracted from each paper for the analysis includes: year of publication; authors and their affiliations; study location; urban context; study objectives; methods used; topics of the study; concepts that were examined (e.g., attitudes, values, etc.); and dimensions of nativeness measured.Attribution(BY)https://data.utas.edu.au/metadata/39660933-1616-4ad6-8157-4ad12a8d7a022021Haylee Kaplandave kendalVishnu PrahaladUniversity of Tasmania, Australiahttps://orcid.org/0000-0003-1269-3492https://orcid.org/0000-0003-2816-1722https://orcid.org/0000-0002-3547-616X440612410401180604180602nativenon-nativeperceptionssocial researchsystematic reviewUTAS/6988aa01-5211-4b37-b339-9eb0e44aadbeUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/6988aa01-5211-4b37-b339-9eb0e44aadbeLachlan Orogen GPlates model Aug2021

https://data.utas.edu.au/metadata/6988aa01-5211-4b37-b339-9eb0e44aadbe

Model data and GPlates project file for Cambrian-Devonian reconstruction of the Lachlan Orogen integrated into a global model (Wright et al., 2013 - doi:10.5194/bg-10-1529-2013). All spatial datasets are provided in .gpml format and rotation files in .grot format.Attribution(BY)https://data.utas.edu.au/metadata/6988aa01-5211-4b37-b339-9eb0e44aadbe2021Thomas SchaapSebastien MeffreJoanne WhittakerMatthew CracknellUniversity of Tasmania, AustraliaPalaeozoicnorthlimit=-26.745610382199; southlimit=-75.4971573189308; westlimit=143.0859375; eastlimit=184.21875; projection=WGS84https://orcid.org/0000-0002-4189-3760https://orcid.org/0000-0003-2741-6076https://orcid.org/0000-0002-3170-3935https://orcid.org/0000-0001-9843-8251370604370502370508370511250399plate tectonicsgplatesUTAS/14e31776-6466-4aa3-9dc6-3283ebf36286University of Tasmania, Australiahttps://data.utas.edu.au/metadata/14e31776-6466-4aa3-9dc6-3283ebf36286SSR data from Yost et al (2021) Forests paper on Californian landrace of 𝘌𝘶𝘤𝘢𝘭𝘺𝘱𝘵𝘶𝘴 𝘨𝘭𝘰𝘣𝘶𝘭𝘶𝘴

https://data.utas.edu.au/metadata/14e31776-6466-4aa3-9dc6-3283ebf36286

SSR data for native and Californian landrace samples of 𝘌𝘶𝘤𝘢𝘭𝘺𝘱𝘵𝘶𝘴 𝘨𝘭𝘰𝘣𝘶𝘭𝘶𝘴 used for the STRUCTURE analysis reported in Table 1 and Supplementary material Table S1 of: Yost JM, Wise SL, Love NLR, Steane DA, Jones RC, Ritter MK and Potts BM (2021) Origins, diversity and naturalization of 𝘌𝘶𝘤𝘢𝘭𝘺𝘱𝘵𝘶𝘴 𝘨𝘭𝘰𝘣𝘶𝘭𝘶𝘴 (Myrtaceae) in California. Forests. Data is in the format of a STRUCTURE input file with six SSR loci - EMB19 EMB30 CRC2 CRC7 CRC10 CRC11. The tree grouping (second column) corresponds to Victoria (1), Furneaux (2), King Is./W Tas (3), Eastern Tasmania (4) and Californian Landrace (0). The third column identifies the native stand (1) and Californian landrace samples (0). The Californian landrace sample codes follow Table S1 in the above paper and the provenance of the Australian samples is listed in the attached supplementary file.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/14e31776-6466-4aa3-9dc6-3283ebf362862021Brad PottsSascha WiseNatalie LoveRebecca JonesDorothy SteaneUniversity of Tasmania, Australiahttps://orcid.org/0000-0001-6244-289Xhttps://orcid.org/0000-0003-2026-4532https://orcid.org/0000-0002-5013-5478https://orcid.org/0000-0002-6491-1423https://orcid.org/0000-0002-8061-8454https://orcid.org/0000-0001-5603-5024310308300707410202260201180602blue gumgenetic diversitySSRsmicrosatellitesmolecular markerslandraceeucalyptUTAS/e4a78c27-7dd0-4338-b4e0-f7f6ae3910a0University of Tasmania, Australiahttps://data.utas.edu.au/metadata/e4a78c27-7dd0-4338-b4e0-f7f6ae3910a0Carinascincus ocellatus transcriptome

https://data.utas.edu.au/metadata/e4a78c27-7dd0-4338-b4e0-f7f6ae3910a0

Transcriptomes from high (MIena) and low (Orford) populations of Carinascincus ocellatus. 3 males and 3 females at each population. Tissues analysed include brain and gonad.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/e4a78c27-7dd0-4338-b4e0-f7f6ae3910a02021Christopher BurridgeUniversity of Tasmania, Australia20212021https://orcid.org/0000-0002-8185-6091310509280102Carinascincus ocellatusUTAS/6c5dd3ac-529a-42cb-94a8-44bc39d47aa0University of Tasmania, Australiahttps://data.utas.edu.au/metadata/6c5dd3ac-529a-42cb-94a8-44bc39d47aa0Upper mantle viscosity underneath northern Marguerite Bay, Antarctic Peninsula constrained by bedrock uplift and ice mass variability

https://data.utas.edu.au/metadata/6c5dd3ac-529a-42cb-94a8-44bc39d47aa0

GPS dataset: Folder “GPS” GPS data are in *.mat format from ROTH, BSA1, SMRT and SMR5 stations. “up_roth.mat” : this file contains uplift (up_roth = [uplift in mm]), time. “up_bsa1.mat” : this file contains uplift (up_bsa1 = [uplift in mm]), time. “up_smrt.mat” : this file contains uplift (up_smrt = [uplift in mm]), time. “up_smr5.mat” : this file contains uplift (up_smr5 = [uplift in mm]), time. Surface Elevation Change: Folder “Elevation_Change” Surface elevation change data are in *.mat format for western and eastern parts from 2002-2017. “E_dhdt_2k2_2k9.mat.mat” [For Eastern Part for 2002-2009], “W_dhdt_2k4_2k12.mat” [For Western Part for 2004-2012], “E_dhdt_2k9_2k15.mat” [For Eastern Part for 2009-2015], and “W_dhdt_2k12_2k17.mat” [For Western Part for 2012-2017]: all of these file contain there component name “lon” [in degree], “lat” [in degree] and elevation chnage [in m/year]. We use an ice density of 900 kg/m3 to convert to equivalent water height. Viscoelastic Models: Folder “VE_Model” have two subfolder name “Elastic” and “Viscous”. Elastic folder contain two files of elastic model predictions fro ROTH and SMRT. “Elastic_roth.mat” and “Elastic_smrt.mat” both file contains two components name “time” and “elastic” uplift in “mm” “Viscous” folder contain two folder for ROTH and SMRT where a range of viscous models outputs placed. Both of these folders contains viscous models outputs files name “viscous_roth_L*M_*e*.mat” [for ROTH] and “viscous_smrt_L*M_*e*.mat” [for SMRT], respectively. Each viscous “*mat” file contains two components name “time” and “viscous” uplift in “mm”.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/6c5dd3ac-529a-42cb-94a8-44bc39d47aa02021NAHIDUL HOQUE SAMRATUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-4796-7257370603190501geodesyUTAS/86c4a68b-6d30-41b8-b0f2-fb407d041dc3University of Tasmania, Australiahttps://data.utas.edu.au/metadata/86c4a68b-6d30-41b8-b0f2-fb407d041dc3Detecting and Preventing Cheating in a Fully Online Professional Education Program

https://data.utas.edu.au/metadata/86c4a68b-6d30-41b8-b0f2-fb407d041dc3

Data used in an evaluation of a method for preventing cheating in a fully online courseAttribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/86c4a68b-6d30-41b8-b0f2-fb407d041dc32021Tristan LingPeter GeeIvan BindoffCorinna DwanUniversity of Tasmania, Australia2020-012020-11https://orcid.org/0000-0003-4361-5294https://orcid.org/0000-0002-9193-7813https://orcid.org/0000-0002-8170-8339https://orcid.org/0000-0001-8437-0743321402390405160104200199online learningacademic misconductcheatingpreventing cheatingCOVID-19UTAS/59410fa6-f07e-4982-a6ab-04f50dfb63fcUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/59410fa6-f07e-4982-a6ab-04f50dfb63fcRevision of Design of financial incentive programmes: A discrete choice experiment

https://data.utas.edu.au/metadata/59410fa6-f07e-4982-a6ab-04f50dfb63fc

Financial incentive programmes promote smoking cessation. However, the incentive amount which should be provided – and how this may interact with other programme characteristics – is unknown. The objective of this study was to evaluate the influence of the design of incentive programmes for smoking cessation on current smokers’ perceptions of programmes and willingness to enrol. An online discrete choice experiment was conducted amongst adult current smokers residing in the United Kingdom (N = 430). Hypothetical incentive programmes were described using five attributes (incentive amount, incentive type, frequency of sessions, reward schedule, programme location). Participants responded to a series of choice sets comprised of two hypothetical programmes. For each set, participants selected their preferred programme. They then specified whether they would enrol in their preferred programme if it were available. Analyses also considered the effect of participant income on preferences.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/59410fa6-f07e-4982-a6ab-04f50dfb63fc2021Stuart FergusonRachel BreenMatthew PalmerMai FrandsenUniversity of Tasmania, AustraliaUTAS/5a7d7263-44b6-4147-ab8e-a88b5246974ehttps://orcid.org/0000-0001-7378-3497https://orcid.org/0000-0002-2727-5763https://orcid.org/0000-0002-3467-3364https://orcid.org/0000-0001-7027-1445420605200412smoking cessationtobaccofinancial incentivesUTAS/5a7d7263-44b6-4147-ab8e-a88b5246974eUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/5a7d7263-44b6-4147-ab8e-a88b5246974eDesign of financial incentive programmes: A discrete choice experiment

https://data.utas.edu.au/metadata/5a7d7263-44b6-4147-ab8e-a88b5246974e

Financial incentive programmes promote smoking cessation. However, the incentive amount which should be provided – and how this may interact with other programme characteristics – is unknown. The objective of this study was to evaluate the influence of the design of incentive programmes for smoking cessation on current smokers’ perceptions of programmes and willingness to enrol. An online discrete choice experiment was conducted amongst adult current smokers residing in the United Kingdom (N = 430). Hypothetical incentive programmes were described using five attributes (incentive amount, incentive type, frequency of sessions, reward schedule, programme location). Participants responded to a series of choice sets comprised of two hypothetical programmes. For each set, participants selected their preferred programme. They then specified whether they would enrol in their preferred programme if it were available. Analyses also considered the effect of participant income on preferences.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/5a7d7263-44b6-4147-ab8e-a88b5246974e2021Stuart FergusonRachel BreenUniversity of Tasmania, Australiahttps://orcid.org/0000-0001-7378-3497https://orcid.org/0000-0002-2727-5763420605200412smoking cessationtobaccofinancial incentivesUTAS/484c2b53-776b-41da-8bb7-49ded4e96ea2University of Tasmania, Australiahttps://data.utas.edu.au/metadata/484c2b53-776b-41da-8bb7-49ded4e96ea2Clements Compendium: PDF database of attacks on and by Aborigines in southeast Tasmania

https://data.utas.edu.au/metadata/484c2b53-776b-41da-8bb7-49ded4e96ea2

Compendiums of all known violent incidents that occurred on the southeast Tasmanian frontier compiled by Nicholas Clements to accompany the book 'Tongerlongeter: First Nations Leader and Tasmanian War Hero', co-authored with Henry Reynolds (NewSouth, 2021). There are three PDF files: 1. Compendium of violent against colonists in Oyster Bay & Big River territories, 1823-1831 2. Compendium of violent acts against Aborigines in Oyster Bay and Big River territories, 1804-1831 3. A document containing the protocols and sources for the two compendiumsAttribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/484c2b53-776b-41da-8bb7-49ded4e96ea22021Nicholas ClementsUniversity of Tasmania, Australia18041831northlimit=-41.3681776535685; southlimit=-43.2578932655187; westlimit=146.113014221191; eastlimit=148.591289520264; projection=WGS84UTAS/54c64783-f712-4f97-958f-eddb6cc19d6chttps://orcid.org/0000-0003-0261-7779https://orcid.org/0000-0001-5603-5024430313451901430304450103450410210407aboriginaltasmaniahistoryIndigenousFrontier warVan Diemen's LandTongerlongeterwybalennaFlinders IslandBlack WarOyster BaytribeBig RiverMusquitoMannalargennaGeorge Augustus RobinsonGeorge ArthurMontpelliattaKickertopollerBlack TomGilbert RobinsonresistancewarfarewarCompendiumDatabasedatasetattacksincidentswindschuttleplomleycommemorationmemorialisationroving partiesTongerlongeter: First Nations Leader and Tasmanian War HeroWindschuttleLyndall RyanBarry BrimfieldClements NP, 'The Vandemonian War: the secret history of Britain's Tasmanian invasion', Papers and Proceedings of the Tasmanian Historical Research Association, 64, (3) pp. 68-71. ISSN 0039-9809 (2017) [Review Single Work]UTAS/publications/126751Clements NP, 'The Black War: Fear, Sex and Resistance in Tasmania', University of Queensland Press, Australia, pp. 268. ISBN 9780702250064 (2014) [Authored Research Book]UTAS/publications/90908Clements N, Gregg A, ''I am frightened out of my life': Black War, white fear', Settler Colonial Studies, 7, (2) pp. 221-240. ISSN 2201-473X (2017) [Refereed Article]10.1080/2201473X.2015.1096878Clements Nick, 'Army of Sufferers: The Experience of Tasmania's Black Line', Journal of Australian Studies, 37, (1) pp. 19-33. ISSN 1444-3058 (2013) [Refereed Article]10.1080/14443058.2012.754782UTAS/54c64783-f712-4f97-958f-eddb6cc19d6cUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/54c64783-f712-4f97-958f-eddb6cc19d6cClements Compendiums: PDF database of attacks on and by Aborigines in southeast Tasmania

https://data.utas.edu.au/metadata/54c64783-f712-4f97-958f-eddb6cc19d6c

Compendiums of all known violent incidents that occurred on the southeast Tasmanian frontier compiled by Nicholas Clements to accompany the book 'Tongerlongeter: First Nations Leader and Tasmanian War Hero', co-authored with Henry Reynolds (NewSouth, 2021). There are three PDF files: 1. Compendium of violent against colonists in Oyster Bay & Big River territories, 1823-1831 2. Compendium of violent acts against Aborigines in Oyster Bay and Big River territories, 1804-1831 3. A document containing the protocols and sources for the two compendiumsAttribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/54c64783-f712-4f97-958f-eddb6cc19d6c2021Nicholas ClementsUniversity of Tasmania, Australia18041831northlimit=-41.3681776535685; southlimit=-43.2578932655187; westlimit=146.113014221191; eastlimit=148.591289520264; projection=WGS84https://orcid.org/0000-0003-0261-7779https://orcid.org/0000-0001-5603-5024430313451901430304450103450410210407aboriginaltasmaniahistoryIndigenousFrontier warVan Diemen's LandTongerlongeterwybalennaFlinders IslandBlack WarOyster BaytribeBig RiverMusquitoMannalargennaGeorge Augustus RobinsonGeorge ArthurMontpelliattaKickertopollerBlack TomGilbert RobinsonresistancewarfarewarCompendiumDatabasedatasetattacksincidentswindschuttleplomleycommemorationmemorialisationroving partiesTongerlongeter: First Nations Leader and Tasmanian War HeroWindschuttleLyndall RyanBarry BrimfieldClements NP, 'The Vandemonian War: the secret history of Britain's Tasmanian invasion', Papers and Proceedings of the Tasmanian Historical Research Association, 64, (3) pp. 68-71. ISSN 0039-9809 (2017) [Review Single Work]UTAS/publications/126751Clements Nick, 'Army of Sufferers: The Experience of Tasmania's Black Line', Journal of Australian Studies, 37, (1) pp. 19-33. ISSN 1444-3058 (2013) [Refereed Article]10.1080/14443058.2012.754782Clements N, Gregg A, ''I am frightened out of my life': Black War, white fear', Settler Colonial Studies, 7, (2) pp. 221-240. ISSN 2201-473X (2017) [Refereed Article]10.1080/2201473X.2015.1096878Clements NP, 'The Black War: Fear, Sex and Resistance in Tasmania', University of Queensland Press, Australia, pp. 268. ISBN 9780702250064 (2014) [Authored Research Book]UTAS/publications/90908UTAS/024f7bdd-c272-49af-bfc2-1317c243a408University of Tasmania, Australiahttps://data.utas.edu.au/metadata/024f7bdd-c272-49af-bfc2-1317c243a408AU GNSS 2015.0-2020.5

https://data.utas.edu.au/metadata/024f7bdd-c272-49af-bfc2-1317c243a408

A filtered and preprocessed dataset of GPS, GLONASS and GPS+GLONASS coordinate timeseries used in the study of the Ocean Tide Loading Displacements (OTLD) over Australia. The dataset includes timeseries computed with JPL (GPS-only, both free and resolved ambiguities), ESA and CODE (GPS-only, GLONASS-only and GPS+GLONASS, all ambiguity free) satellite products. The removed OTLD based on FES2004-GBe during processing was restored using hardisp software.Attribution(BY)https://data.utas.edu.au/metadata/024f7bdd-c272-49af-bfc2-1317c243a4082021Bogdan MatviichukMatt KingChristopher WatsonMachiel BosUniversity of Tasmania, Australia2015-012020-06northlimit=-10.141931686131; southlimit=-44.3395652480971; westlimit=110.654296875; eastlimit=156.708984375; projection=WGS84https://orcid.org/0000-0001-9695-3823https://orcid.org/0000-0001-5611-9498https://orcid.org/0000-0002-7464-4592https://orcid.org/0000-0002-1946-8637401399370603280107Ocean Tide LoadingGPSGNSSAsthenosphereGipsyXUTAS/f9041839-cd71-4648-9b64-7cefc61f1576University of Tasmania, Australiahttps://data.utas.edu.au/metadata/f9041839-cd71-4648-9b64-7cefc61f1576Restoration monitoring with ZEB

https://data.utas.edu.au/metadata/f9041839-cd71-4648-9b64-7cefc61f1576

Dataset of crown architecture and performance traits derived from ZEB-borne LiDAR, used to detect species and provenance variation across time and space.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/f9041839-cd71-4648-9b64-7cefc61f15762021Peter HarrisonNicolò CamarrettaUniversity of Tasmania, Australia20172020east=146.912355422974; north=-42.299151023366; projection=WGS84https://orcid.org/0000-0002-3502-0242https://orcid.org/0000-0001-7520-126X410405310599190310LiDAREucalyptusZEB1Structural attributestree architectureUTAS/ed349d22-e126-4c48-b956-c769a09080e0University of Tasmania, Australiahttps://data.utas.edu.au/metadata/ed349d22-e126-4c48-b956-c769a09080e0Iron-binding organic ligands in Antarctic sea ice

https://data.utas.edu.au/metadata/ed349d22-e126-4c48-b956-c769a09080e0

This work collates iron-binding organic ligands data, detected in sea-ice samples collected around Antarctica. Ice cores were collected during different voyages, namely AWECS (2013), SIPEX-2 (2012), Davis (2015), and V2 (2016-2017). The determination of concentration and binding strength of the natural organic ligand occurred through voltammetric analysis (Competitive Ligand Equilibration - Adsorptive Stripping Voltammetry, CLE-AdCSV) at the University of Genoa (Italy) and at the Institute for Marine and Antarctic Studies (Hobart, TAS).Attribution(BY)https://data.utas.edu.au/metadata/ed349d22-e126-4c48-b956-c769a09080e02021Cristina GenoveseUniversity of Tasmania, Australiadata collates results from four different Southern Ocean voyages, from 2012 to 2017.northlimit=-62.9152330394761; southlimit=-79.1713346408195; westlimit=-74.8828125; eastlimit=188.7890625; projection=WGS84https://orcid.org/0000-0002-9015-020X370802180401biogeochemical cyclesUTAS/a1b0bfd3-ecdd-4d7c-8adb-caae9631e94fUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/a1b0bfd3-ecdd-4d7c-8adb-caae9631e94fAUS_Coastal_Litter_2013-19

https://data.utas.edu.au/metadata/a1b0bfd3-ecdd-4d7c-8adb-caae9631e94f

Litter observed along the coastline of Australia in 32 different local government areas (LGAs). Data recorded using methodology and data sheets found at https://research.csiro.au/marinedebris/resources/ Dataset also contains the waste management strategy changes at each LGA, and environmental and social factors that potential effect the distribution and accumulation of litter along the Australian coastline. Details of each variable contained in the dataset are found in the metadata file.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/a1b0bfd3-ecdd-4d7c-8adb-caae9631e94f2021Kathryn WillisUniversity of Tasmania, Australia20132019east=134.542967677116; north=-25.6098261997886; projection=WGS84https://orcid.org/0000-0001-7614-1027410404190299plastic pollutionwaste managementcoastal litteraustralialocal governmentUTAS/e580a176-10d7-4bf3-9f7b-3697f8d50a2dUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/e580a176-10d7-4bf3-9f7b-3697f8d50a2dDissolved and particulate metal concentration in East-Antarctica sea ice (2012-2017)

https://data.utas.edu.au/metadata/e580a176-10d7-4bf3-9f7b-3697f8d50a2d

This dataset shows dissolved and particulate metal concentrations (Cadmium, Manganese, Cobalt, Nickel, Copper and Zinc) for sea ice, brine and seawater below sea ice obtained from three voyages around East-Antarctica (SIPEX-2, Davis and AAV2) during 2012-2017Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/e580a176-10d7-4bf3-9f7b-3697f8d50a2d2021Luis Paulo DupratUniversity of Tasmania, Australia20122017northlimit=-60.7591595022699; southlimit=-76.1849954609472; westlimit=42.890625; eastlimit=175.4296875; projection=WGS84https://orcid.org/0000-0003-1536-9559370802180402metalssea iceAntarcticaUTAS/0286a71c-8e3c-445e-8f50-948380ae595aUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/0286a71c-8e3c-445e-8f50-948380ae595aVolatile scent chemicals in urine of the red fox - Data

https://data.utas.edu.au/metadata/0286a71c-8e3c-445e-8f50-948380ae595a

The red fox is a highly adaptable mammal that has established itself world-wide in many different environments. Contributing to its success is a social structure based on chemical signalling between individuals. Urine scent marking behaviour has long been known in foxes, but there has not been a recent study of the chemical composition of fox urine. We have used solid-phase microextraction and gas chromatography-mass spectrometry to analyze the urinary volatiles in 15 free-ranging wild foxes (2 female) living in farmlands and bush in Victoria, Australia. Foxes here are routinely culled as feral pests, and the urine was collected by bladder puncture soon after death. Compounds were identified from their mass spectra and Kovats retention indices. There were 53 possible endogenous scent compounds, 10 plant-derived compounds and 5 anthropogenic xenobiotics. Among the plant chemicals were several aromatic apocarotenoids previously found in greater abundance in the fox tail gland. They reflect the dietary consumption of carotenoids, essential for optimal health. One third of all the endogenous volatiles were sulfur compounds, a highly odiferous group which included thiols, methylsulfides and polysulfides. Five of the sulfur compounds (3-isopentenyl thiol, 1- and 2-phenylethyl methyl sulfide, octanethiol and benzyl methyl sulfide) have only been found in foxes, and four others (isopentyl methyl sulfide, 3-isopentenyl methyl sulfide, and 1- and 2-phenylethane thiol) only in some canid, mink and skunk species. The urinary scent chemistry may represent a highly evolved system of semiochemicals for communication between foxes. The data files attached to this record support the paper "Volatile Scent Chemicals in the Urine of the Red Fox, 𝘝𝘶𝘭𝘱𝘦𝘴 𝘷𝘶𝘭𝘱𝘦𝘴".Attribution - Share Alike(BY - SA)https://data.utas.edu.au/metadata/0286a71c-8e3c-445e-8f50-948380ae595a2021Stuart McLeanNoel DaviesDavid NicholsUniversity of Tasmania, Australia20152020northlimit=-36.9586711315303; southlimit=-38.7969083034843; westlimit=143.739624023438; eastlimit=148.485717773438; projection=WGS84UTAS/31c142d4-d8a3-4e4b-82e3-847b6047bf82https://orcid.org/0000-0003-1041-6563https://orcid.org/0000-0002-9624-0935https://orcid.org/0000-0002-8066-3132https://orcid.org/0000-0001-5603-5024310308410202340109280111foxscentssemiochemicalsgas chromatographyurineAustraliaVulpes vulpesUTAS/82845a9c-9b00-46a7-bb1c-1577087dbffcUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/82845a9c-9b00-46a7-bb1c-1577087dbffcChange in modifiable dementia risk factors during COVID-19 lockdown: the experience of over 50s in Tasmania, Australia

https://data.utas.edu.au/metadata/82845a9c-9b00-46a7-bb1c-1577087dbffc

R scripts for analysis of Wicking Dementia Research & Education Centre project's Change in modifiable dementia risk factors during COVID-19 lockdown: the experience of over 50s in Tasmania, Australia publicationAttribution - Share Alike(BY - SA)https://data.utas.edu.au/metadata/82845a9c-9b00-46a7-bb1c-1577087dbffc2021Larissa BartlettAidan BindoffJames BradyDuncan SinclairHannah FairMaree FarrowSarang KimJames VickersUniversity of Tasmania, Australia20192020east=147.32961273141; north=-42.8787693408526; projection=WGS84https://orcid.org/0000-0003-0474-8107https://orcid.org/0000-0002-0943-2702https://orcid.org/0000-0002-3959-1325https://orcid.org/0000-0001-5961-1007https://orcid.org/0000-0002-4409-9132https://orcid.org/0000-0003-0302-9426https://orcid.org/0000-0003-4869-9255https://orcid.org/0000-0001-5671-4879420201200401dementiacovid-19modifiable risk-factorslockdownlongitudinalUTAS/ff80025e-0019-4cbb-aa8a-2fb289915b51University of Tasmania, Australiahttps://data.utas.edu.au/metadata/ff80025e-0019-4cbb-aa8a-2fb289915b51NZ GPS 2013.0-2020.5

https://data.utas.edu.au/metadata/ff80025e-0019-4cbb-aa8a-2fb289915b51

A dataset used for the analysis of the ocean tide loading with initial FES2004-based correctionAttribution(BY)https://data.utas.edu.au/metadata/ff80025e-0019-4cbb-aa8a-2fb289915b512021Bogdan MatviichukMatt KingUniversity of Tasmania, Australia2013-012020-06https://orcid.org/0000-0001-9695-3823https://orcid.org/0000-0001-5611-9498401399370603280107Ocean Tide LoadingGPSGNSSAsthenosphereGipsyXUTAS/2c3122be-fc62-48d0-a42d-41875d21e71bUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/2c3122be-fc62-48d0-a42d-41875d21e71bFoodChoices4

https://data.utas.edu.au/metadata/2c3122be-fc62-48d0-a42d-41875d21e71b

One of a series of real-world studies designed to explore the impact of social, emotional and environmental factors on eating. This study was designed to investigate the relationship between attentional bias, impulsivity, and real-world eating patterns. In addition to completing laboratory tasks, participants were required to log every instance of food or drink consumed into a smartphone during a two-week real-world monitoring period. For a subset of these reports, participants answered questions about their affect, activities and social setting at the time of consumption. Participants also completed to randomly-timed non-eating assessments throughout each day.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/2c3122be-fc62-48d0-a42d-41875d21e71b2020Stuart FergusonUniversity of Tasmania, Australiahttps://orcid.org/0000-0001-7378-3497520304200412obesityresearchEMAecological momentary assessmentattentional biasUTAS/da3965b1-2f7c-4179-8fc2-a6cc1ff5da82University of Tasmania, Australiahttps://data.utas.edu.au/metadata/da3965b1-2f7c-4179-8fc2-a6cc1ff5da82Incentive Amounts-Prolific

https://data.utas.edu.au/metadata/da3965b1-2f7c-4179-8fc2-a6cc1ff5da82

Studies demonstrate that financial incentive programmes increase smoking cessation. However, there is little guidance on which incentive magnitudes will ensure optimal enrolment and motivation levels. This study investigates current smokers’ perceptions of varying incentive magnitudes to identify whether there is evidence for optimal amount(s), and whether perceptions differ by income group. Studies 1 (N = 56) and 2 (N = 147) were conducted online via Prolific.co. Current smokers were randomly shown multiple hypothetical incentive programmes which differed only in the incentive amount offered. For each programme, smokers rated its appeal, their likelihood of enrolling, and predicted their motivation to quit if enrolled.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/da3965b1-2f7c-4179-8fc2-a6cc1ff5da822020Stuart FergusonRachel BreenMatthew PalmerUniversity of Tasmania, Australia2019-092019-12east=-3.17436218261719; north=55.4621173584655; projection=WGS84https://orcid.org/0000-0001-7378-3497https://orcid.org/0000-0002-2727-5763https://orcid.org/0000-0002-3467-3364520402200412smokingcessationincentivebehaviour changefinancial incentivesUTAS/905348ea-19d3-4ac5-b345-06f4f42732e2University of Tasmania, Australiahttps://data.utas.edu.au/metadata/905348ea-19d3-4ac5-b345-06f4f42732e2Metabarcoding reveals landscape drivers of beetle community composition approximately 50 years after timber harvesting

https://data.utas.edu.au/metadata/905348ea-19d3-4ac5-b345-06f4f42732e2

This dataset includes raw Miseq sequencing data, bioinformatic pipeline and R codes that were used in the study "Metabarcoding reveals landscape drivers of beetle community composition approximately 50 years after timber harvesting". This manuscript has not been published yet when this dataset was deposited on this portal.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/905348ea-19d3-4ac5-b345-06f4f42732e22020Mingxin LiuGreg JordanChristopher BurridgeLaurence ClarkeSusan BakerUniversity of Tasmania, Australiahttps://orcid.org/0000-0003-0436-4058https://orcid.org/0000-0002-6033-2766https://orcid.org/0000-0002-8185-6091https://orcid.org/0000-0002-0844-4453https://orcid.org/0000-0002-7593-0267310206410401310913180606180604beetle diversityclearcuttingforest successionlandscape configurationmetabarcodingreserve designUTAS/d5969fc2-0eea-4a53-9b2c-f8ff1a7d00adUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/d5969fc2-0eea-4a53-9b2c-f8ff1a7d00adDNA metabarcoding captures subtle differences in forest beetle communities following disturbance

https://data.utas.edu.au/metadata/d5969fc2-0eea-4a53-9b2c-f8ff1a7d00ad

This dataset includes all raw Miseq high-throughput sequencing data, bioinformatic pipeline and R codes that were used in the publication "Liu M, Baker SC, Burridge CP, Jordan GJ, Clarke LJ (2020) DNA metabarcoding captures subtle differences in forest beetle communities following disturbance. Restoration Ecology. 28:1475-1484. DOI:10.1111/rec.13236." Miseq_16S.zip - Miseq sequencing dataset for gene marker 16S, including 48 fastq files for 24 beetle bulk samples; Miseq_CO1.zip -Miseq sequencing dataset for gene marker CO1, including 46 fastq files for 23 beetle bulk samples (one sample failed to be sequenced); nfp4MBC.nf - A nextflow bioinformatic script to process Miseq datasets; nextflow.config - A configuratioin file needed when using nfp4MBC.nf; adapters_16S.zip - Adapters used to tag each of 24 beetle bulk samples for 16S, also used to process 16S Miseq dataset when using nfp4MBC.nf; adapters_CO1.zip - Adapters used to tag each of 24 beetle bulk samples for CO1, also used to process CO1 Miseq dataset when using nfp4MBC.nf; rMBC.Rmd - R markdown codes for community analyses; rMBC.zip - Datasets used in rMBC.Rmd. COI_ZOTUs_176.fasta - DNA sequences of 176 COI ZOTUs. 16S_ZOTUs_156 -DNA sequences of 156 16S ZOTUs.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/d5969fc2-0eea-4a53-9b2c-f8ff1a7d00ad2020Mingxin LiuGreg JordanChristopher BurridgeLaurence ClarkeSusan BakerUniversity of Tasmania, Australiahttps://orcid.org/0000-0003-0436-4058https://orcid.org/0000-0002-6033-2766https://orcid.org/0000-0002-8185-6091https://orcid.org/0000-0002-0844-4453https://orcid.org/0000-0002-7593-0267310206310913180606biodiversity monitoringColeopteracytochrome c oxidase subunit I (COI)forest restorationhigh-throughput sequencingmetabarcodingUTAS/bfb77e30-1f1a-478b-bdf0-cbf2cf1a0268University of Tasmania, Australiahttps://data.utas.edu.au/metadata/bfb77e30-1f1a-478b-bdf0-cbf2cf1a0268A practical guide to DNA metabarcoding for entomological ecologists

https://data.utas.edu.au/metadata/bfb77e30-1f1a-478b-bdf0-cbf2cf1a0268

This dataset includes an input data for generating the Sankey diagram (Dataset S1.txt), a spreadsheet of surveyed studies (Appendix S1.xlsx) and two fasta formatted files (Dataset S2.fas and Dataset S3.fas) that were used in the publication "Liu M, Clarke LJ, Baker SC, Jordan GJ, Burridge CP (2020) A practical guide to DNA metabarcoding for entomological ecologists. Ecological Entomology 45:373-385. DOI:10.1111/een.12831".Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/bfb77e30-1f1a-478b-bdf0-cbf2cf1a02682020Mingxin LiuUniversity of Tasmania, Australiahttps://orcid.org/0000-0003-0436-4058310913180606Biodiversity monitoringDNA preservationecological inferencesenvironmental DNAhigh-throughput sequencinginvertebratesmetabarcodingUTAS/66ca8b8d-67ec-4fbd-8a3d-8ca9ad750fc6University of Tasmania, Australiahttps://data.utas.edu.au/metadata/66ca8b8d-67ec-4fbd-8a3d-8ca9ad750fc6Supplementary data for Geology and geochronology of the Two-Thirty Prospect, Northparkes district, NSW

https://data.utas.edu.au/metadata/66ca8b8d-67ec-4fbd-8a3d-8ca9ad750fc6

Supplementary tables (7) for the AJES manuscript Geology and geochronology of the Two-Thirty Prospect, Northparkes district, NSW (Wells et al., 2020). Table 1 contains details of selected mineral deposits of the Macquarie Arc. Table 2 details the breccia components and properties used to define breccia facies. Tables 3 to 7 provide detailed descriptions the breccia facies present at the Two-Thirty prospect, Northparkes, NSW.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/66ca8b8d-67ec-4fbd-8a3d-8ca9ad750fc62020Tristan WellsSebastien MeffreUniversity of Tasmania, Australia2016-02-102020-12-04northlimit=-32.8230570660097; southlimit=-33.0995949757848; westlimit=147.941207885742; eastlimit=148.125228881836; projection=WGS84https://orcid.org/0000-0001-5229-4619https://orcid.org/0000-0003-2741-6076370599370502370508250302250305Magmatic-hydrothermalNorthparkesNew South WalesGoldOrdovicianBrecciaRe-Os datingzirconGeochronologyUTAS/ea3ac424-c75d-4222-8519-9e14efec1a35University of Tasmania, Australiahttps://data.utas.edu.au/metadata/ea3ac424-c75d-4222-8519-9e14efec1a35Diversity and abundance of soil microbial communities decline and community compositions change, with severity of post-logging fire

https://data.utas.edu.au/metadata/ea3ac424-c75d-4222-8519-9e14efec1a35

16S and ITS zotu sequences, qPCR outputs and environmental data for Ammitzboll et al 2021Attribution(BY)https://data.utas.edu.au/metadata/ea3ac424-c75d-4222-8519-9e14efec1a352020Hans AmmitzbollUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-8115-0267310799310399180601Microbial EcologyMolecularMetagenomeSoilCommunityMicrobesBacteriaFungiUTAS/e2258544-b1f8-4ea1-b278-4fce0de0bdfcUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/e2258544-b1f8-4ea1-b278-4fce0de0bdfcAustralian waste management changes

https://data.utas.edu.au/metadata/e2258544-b1f8-4ea1-b278-4fce0de0bdfc

weighted regression data on waste management changes from 2013 to 2019 in Australia.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/e2258544-b1f8-4ea1-b278-4fce0de0bdfc2020Kathryn WillisUniversity of Tasmania, Australia20132019east=138.796870708466; north=-24.1427396029187; projection=WGS84https://orcid.org/0000-0001-7614-1027441007180201plastic pollutionwaste managementpolicy changescomplianceUTAS/31c142d4-d8a3-4e4b-82e3-847b6047bf82University of Tasmania, Australiahttps://data.utas.edu.au/metadata/31c142d4-d8a3-4e4b-82e3-847b6047bf82Fox urine scent data

https://data.utas.edu.au/metadata/31c142d4-d8a3-4e4b-82e3-847b6047bf82

The red fox is a highly adaptable mammal that has established itself world-wide in many different environments. Contributing to its success is a social structure based on chemical signalling between individuals. Urine scent marking behaviour has long been known in foxes, but there has not been a recent study of the chemical composition of fox urine. We have used solid-phase microextraction and gas chromatography-mass spectrometry to analyze the urinary volatiles in 15 free-ranging wild foxes (2 female) living in farmlands and bush in Victoria, Australia. Foxes here are routinely culled as feral pests, and the urine was collected by bladder puncture soon after death. Compounds were identified from their mass spectra and Kovats retention indices. There were 53 possible endogenous scent compounds, 10 plant-derived compounds and 5 anthropogenic xenobiotics. Among the plant chemicals were several aromatic apocarotenoids previously found in greater abundance in the fox tail gland. They reflect the dietary consumption of carotenoids, essential for optimal health. One third of all the endogenous volatiles were sulfur compounds, a highly odiferous group which included thiols, methylsulfides and polysulfides. Five of the sulfur compounds (3-isopentenyl thiol, 1- and 2-phenylethyl methyl sulfide, octanethiol and benzyl methyl sulfide) have only been found in foxes, and four others (isopentyl methyl sulfide, 3-isopentenyl methyl sulfide, and 1- and 2-phenylethane thiol) only in some canid, mink and skunk species. The urinary scent chemistry may represent a highly evolved system of semiochemicals for communication between foxes. The data files attached to this record support the paper "Volatile Scent Chemicals in the Urine of the Red Fox, 𝘝𝘶𝘭𝘱𝘦𝘴 𝘷𝘶𝘭𝘱𝘦𝘴".Attribution - Share Alike(BY - SA)https://data.utas.edu.au/metadata/31c142d4-d8a3-4e4b-82e3-847b6047bf822020Stuart McLeanNoel DaviesDavid NicholsUniversity of Tasmania, Australia20152020northlimit=-36.9586711315303; southlimit=-38.7969083034843; westlimit=143.739624023438; eastlimit=148.485717773438; projection=WGS84https://orcid.org/0000-0003-1041-6563https://orcid.org/0000-0002-9624-0935https://orcid.org/0000-0002-8066-3132https://orcid.org/0000-0001-5603-5024310308410202340109280111foxscentssemiochemicalsgas chromatographyurineAustraliaVulpes vulpesUTAS/bdbc5570-252e-403b-bad0-1b983ccd3628University of Tasmania, Australiahttps://data.utas.edu.au/metadata/bdbc5570-252e-403b-bad0-1b983ccd3628Global Fishing Effort by Country, sector LME and FAO Area 1950 - 2015

https://data.utas.edu.au/metadata/bdbc5570-252e-403b-bad0-1b983ccd3628

Nominal and effective (creep of 2.6% per year) fishing effort (in kW-days by year) by fishing entity (country), Sector (Industrial / Artisanal and unmotorised), reporting status and FAO Area. Only marine, wild catch fisheries included, recreational excluded. Existing and disbanded supranational entities (e.g. ex-USSR, ex-Yugoslavia, European Union) are given as their components as off 2015. Sectors (Artisanal/Industrial) are based on National definitions, all non-motorised fleet was considered artisanal. FAO Area given as number. Based on the effort data by country and Sector (Rousseau et al., 2019. doi.org/10.1073/pnas.1820344116) and the global fisheries landings by country and sector (Watson, 2019. doi.org/10.25959/5c522cadbea37). The effort data was geared following interpolation and extrapolation methods adapted from Rousseau et al. (2019), and the total effort by country, year, sector and gear was associated to a corresponding catch. Incompatibilities between effort and catch were resolved by comparing broader families of gears (e.g. lines instead of longlines or manual lines, bottom nets instead of bottom trawl or dredge, etc.). The effort was mapped in 0.5 degree cells using a ratio to the total catch, and limiting artisanal boats to the EEZ of the country, and unmotorised boats to 12nm. The data was then aggregated by Large Marine Ecosystem (using NOAA denomination) and FAO area. Full methodology can be found in Rousseau, Y. (2020) Mapping global fisheries: balancing gaps and overconfidence in data. Chapter 5, in 'Predicting the future of global seafood production'. Ph.D. thesis, University of Tasmania, Australia.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/bdbc5570-252e-403b-bad0-1b983ccd36282020Yannick RousseauUniversity of Tasmania, Australia19502015https://orcid.org/0000-0003-0765-7518300505100399FisheriesEffortsectorRousseau Y, Watson RA, Blanchard JL, Fulton EA, 'Evolution of global marine fishing fleets and the response of fished resources', Proceedings of the National Academy of Sciences of The United States of America, 116, (25) pp. 12238-12243. ISSN 0027-8424 (2019) [Refereed Article]10.1073/pnas.1820344116UTAS/b3ad825d-0382-48a1-82bf-95038a366c72University of Tasmania, Australiahttps://data.utas.edu.au/metadata/b3ad825d-0382-48a1-82bf-95038a366c72IODP-L183-U1138 Scientific Drilling Kerguelen Plateau

https://data.utas.edu.au/metadata/b3ad825d-0382-48a1-82bf-95038a366c72

These are ICPMS laser geochemical data on IODP Leg 183 U1138 core samples. The ICPMS data was collected at the CODES Analytical Laboratories in 2016.Attribution - Share Alike(BY - SA)https://data.utas.edu.au/metadata/b3ad825d-0382-48a1-82bf-95038a366c722020Rebecca CareyTrevor FalloonUniversity of Tasmania, Australiaeast=74.292254447937; north=-53.3583893754556; projection=WGS84https://orcid.org/0000-0002-7173-3119https://orcid.org/0000-0001-6528-9739370504280107Kerguelen Plateaularge igneous provinceresearchheard islandUTAS/5d9ee4e6-99e8-46f0-b6c2-cc869a5e3d06University of Tasmania, Australiahttps://data.utas.edu.au/metadata/5d9ee4e6-99e8-46f0-b6c2-cc869a5e3d06PhD Thesis Supplemental Data

https://data.utas.edu.au/metadata/5d9ee4e6-99e8-46f0-b6c2-cc869a5e3d06

Supplemental material for PhD Thesis "Modelling Antarctic Ice Shelf-Ocean Interaction at High Resolution" by Ole RichterAttribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/5d9ee4e6-99e8-46f0-b6c2-cc869a5e3d062020Ole RichterUniversity of Tasmania, Australia20072007https://orcid.org/0000-0002-5857-8361401399180402ice shelf basal meltingUTAS/8e042cea-2379-4d5a-9e28-c92238ab4f61University of Tasmania, Australiahttps://data.utas.edu.au/metadata/8e042cea-2379-4d5a-9e28-c92238ab4f61The nature and formation of oceanic crust at fast spreading ridges: geochemical results from scientific ocean drilling at Hess Deep

https://data.utas.edu.au/metadata/8e042cea-2379-4d5a-9e28-c92238ab4f61

This data set comprises mineral and whole-rock geochemical data on basalts, gabbros and peridotites from IODP Expedition 345 and ODP Leg 147 at Hess Deep, eastern equatorial Pacific. The excel file ‘Data File Inventory’ outlines the contents of all 48 files in the repository. The acquisition of analytical data was made possible by funding from the Australian IODP Office.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/8e042cea-2379-4d5a-9e28-c92238ab4f612020Trevor FalloonUniversity of Tasmania, Australia20132018east=147.301940917969; north=-42.888039560563; projection=WGS84https://orcid.org/0000-0001-6528-9739340299140199basaltgabbroperidotiteolivineorthopyroxenecinopyroxeneplagioclasespineltroctolitescientific ocean drillingUTAS/d34f18f9-a878-49cb-9ad5-b4d27e0c7b77University of Tasmania, Australiahttps://data.utas.edu.au/metadata/d34f18f9-a878-49cb-9ad5-b4d27e0c7b77Data from: Tidal Modulation of Antarctic Ice Shelf Melting

https://data.utas.edu.au/metadata/d34f18f9-a878-49cb-9ad5-b4d27e0c7b77

Data underlying the figures of the manuscript "Tidal Modulation of Antarctic Ice Shelf Melting" submitted to The Cryosphere. For more information see README.txt.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/d34f18f9-a878-49cb-9ad5-b4d27e0c7b772020Ole RichterUniversity of Tasmania, Australia20072007https://orcid.org/0000-0002-5857-8361370201190501190502tidesice shelf meltingUTAS/ee816dd3-379a-489a-b78f-3dc1b16e0befUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/ee816dd3-379a-489a-b78f-3dc1b16e0befData from: Antarctic Ice Shelves Lose Most of Their Mass From Shallow Depths

https://data.utas.edu.au/metadata/ee816dd3-379a-489a-b78f-3dc1b16e0bef

Data underlying the figures of the article "Antarctic Ice Shelves Lose Most of Their Mass From Shallow Depths" submitted to Geophysical Research Letters. See README for figure references and more information.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/ee816dd3-379a-489a-b78f-3dc1b16e0bef2020Ole RichterUniversity of Tasmania, Australia20072007https://orcid.org/0000-0002-5857-8361370803190501ice shelf basal meltingUTAS/bae6e09e-ab11-4d01-8b1a-9bbaf0e6ff73University of Tasmania, Australiahttps://data.utas.edu.au/metadata/bae6e09e-ab11-4d01-8b1a-9bbaf0e6ff73Foodchoices3

https://data.utas.edu.au/metadata/bae6e09e-ab11-4d01-8b1a-9bbaf0e6ff73

One of a series of real-world studies designed to explore the impact of social, emotional and environmental factors on eating. This study was designed to investigate the relationship between attentional bias, impulsivity, and real-world eating patterns. In addition to completing laboratory tasks, participants were required to log every instance of food or drink consumed into a smartphone during a two-week real-world monitoring period. For a subset of these reports, participants answered questions about their affect, activities and social setting at the time of consumption. Participants also completed to randomly-timed non-eating assessments throughout each day.Attribution - NonCommercial - No Derivatives(BY - NC - ND)https://data.utas.edu.au/metadata/bae6e09e-ab11-4d01-8b1a-9bbaf0e6ff732020Stuart FergusonUniversity of Tasmania, Australiaeast=147.329129129648; north=-42.8833071430881; projection=WGS84https://orcid.org/0000-0001-7378-3497520304200412obesityresearchEMAUTAS/5bbd960b-5db7-4cbc-a969-97b233857176University of Tasmania, Australiahttps://data.utas.edu.au/metadata/5bbd960b-5db7-4cbc-a969-97b233857176GRL_shallow_melting

https://data.utas.edu.au/metadata/5bbd960b-5db7-4cbc-a969-97b233857176

Data underlying the figures in "Antarctic Ice Shelves Lose Most of Their Mass From Shallow Depths" published in Geophysical Research Letters. Richter_depth.csv Rignot_depth.csv - Data underlying Fig. 2 - zice_bins is ice draft depth in m m.nc temp_surf.nc - Data underlying Fig. 1 - temp is potential temperature in degC of the uppermost sigma layer - m is ice shelf melt rate in m/s (negative denotes refreezing) - both are maps of 2007 mean ts_vals2_sec_cavity.npy salt_centres.csv temp_centres.csv - Data underlying Fig. 3 - the numpy file contains an archive of numpy arrays - each array represents the cavity conditions of one sector - these arrays are 2d with salt in x and temp in y direction - the values represent the mean depth of each T/S combination in m - the csv files are 1D arrays containing the axis values; potential temperature in degC; practical salinity depth_melt_evo.npy shallow_temp_evo.npy - Data underlying Fig. 4 - the numpy files contain archives of xarray arrays - each array representing a certain depth range in m - the ocean_time attribute is faulty, stating year 2014 - all values are for 2007 and the arrays start with May - ice shelf melt rate in m/yr; potential temperature in degCAttribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/5bbd960b-5db7-4cbc-a969-97b2338571762020Ole RichterUniversity of Tasmania, Australia20072007https://orcid.org/0000-0002-5857-8361370803190501ice shelf basal meltingUTAS/9f7cc90a-bebb-4f9b-b851-bfbb702cc875University of Tasmania, Australiahttps://data.utas.edu.au/metadata/9f7cc90a-bebb-4f9b-b851-bfbb702cc875Revision of HECTOR input, output and control files for Antarctic Surface Mass Balance (RACMO2.3p2 and ice core composites)

https://data.utas.edu.au/metadata/9f7cc90a-bebb-4f9b-b851-bfbb702cc875

The dataset creation is described in a submitted paper of King and Watson "Antarctic Surface Mass Balance: natural variability, noise and detecting new trends". It includes the input, output and control files requires to run HECTOR software with various parameterisations and noise models. The format of the data is given in the HECTOR software manual.Attribution(BY)https://data.utas.edu.au/metadata/9f7cc90a-bebb-4f9b-b851-bfbb702cc8752020Matt KingUniversity of Tasmania, Australia18002017northlimit=-61.7731228645315; southlimit=-81.923186326022; westlimit=-70.13671875; eastlimit=327.83203125; projection=WGS84UTAS/e10e199d-c7dd-43cc-80fa-e32cc121e044https://orcid.org/0000-0001-5611-9498370904370902280107Antarctic surface mass balancenoisetrendsuncertaintiesUTAS/1068adf9-9124-45c6-af79-40ee47e00c48University of Tasmania, Australiahttps://data.utas.edu.au/metadata/1068adf9-9124-45c6-af79-40ee47e00c48A novel system to map protein interactions reveals evolutionarily conserved immune evasion pathways on transmissible cancers

https://data.utas.edu.au/metadata/1068adf9-9124-45c6-af79-40ee47e00c48

Readme file for: Flies et al., 2020. Science Advances. “A novel system to map protein interactions reveals evolutionarily conserved immune evasion pathways on transmissible cancers” Data for each figure in the Flies 2020 FAST protein manuscript is linked to the figures below. An experimental protocol spreadsheet with a unique ID is provided for each figure. The next page in this document links the figures to the data.Attribution(BY)https://data.utas.edu.au/metadata/1068adf9-9124-45c6-af79-40ee47e00c482020Andrew FliesUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-4550-1859310905320409300906280112200199200199immunologyflow cytometrywild immunologyFAST proteinimmune checkpointtransmissible cancerUTAS/5a30e193-1f35-4b04-805f-683fcd38d3d0University of Tasmania, Australiahttps://data.utas.edu.au/metadata/5a30e193-1f35-4b04-805f-683fcd38d3d0Satellite Altimetry derived Southern Ocean temperature and salinity fields

https://data.utas.edu.au/metadata/5a30e193-1f35-4b04-805f-683fcd38d3d0

A gravest empirical mode (GEM) projection of temperature and salinity fields over the circumpolar Southern Ocean is presented and is used in combination with satellite altimetry to produce gridded, full-depth, time-evolving temperature, salinity, and velocity fields. Meijers, A.J., N.L. Bindoff, and S.R. Rintoul, 2011: Estimating the Four-Dimensional Structure of the Southern Ocean Using Satellite Altimetry. J. Atmos. Oceanic Technol., 28, 548–568, https://doi.org/10.1175/2010JTECHO790.1Attribution(BY)https://data.utas.edu.au/metadata/5a30e193-1f35-4b04-805f-683fcd38d3d02020Andrew MeijersNathaniel BindoffStephen RintoulUniversity of Tasmania, Australia19922010northlimit=-27.0591257843741; southlimit=-79.5605462637637; westlimit=-8.0859375; eastlimit=352.6171875; projection=WGS84https://orcid.org/0000-0003-3876-7736https://orcid.org/0000-0001-5662-9519https://orcid.org/0000-0002-7055-9876https://orcid.org/0000-0002-1656-4535https://orcid.org/0000-0001-5603-5024370202370803280107salinitysouthern oceantemperatureMeijers AJS, Bindoff NL, Rintoul SR, 'Estimating the Four-Dimensional Structure of the Southern Ocean Using Satellite Altimetry', Journal of Atmospheric and Oceanic Technology, 28, (4) pp. 548-568. ISSN 0739-0572 (2011) [Refereed Article]10.1175/2010JTECHO790.1UTAS/e10e199d-c7dd-43cc-80fa-e32cc121e044University of Tasmania, Australiahttps://data.utas.edu.au/metadata/e10e199d-c7dd-43cc-80fa-e32cc121e044HECTOR input, output and control files for Antarctic Surface Mass Balance (RACMO2.3p2 and ice core composites)

https://data.utas.edu.au/metadata/e10e199d-c7dd-43cc-80fa-e32cc121e044

The dataset creation is described in a submitted paper of King and Watson "Antarctic Surface Mass Balance: natural variability, noise and detecting new trends". It includes the input, output and control files requires to run HECTOR software with various parameterisations and noise models. The format of the data is given in the HECTOR software manual.Attribution(BY)https://data.utas.edu.au/metadata/e10e199d-c7dd-43cc-80fa-e32cc121e0442020Matt KingUniversity of Tasmania, Australia18002017northlimit=-61.7731228645315; southlimit=-81.923186326022; westlimit=-70.13671875; eastlimit=327.83203125; projection=WGS84https://orcid.org/0000-0001-5611-9498370904370902280107Antarctic surface mass balancenoisetrendsuncertaintiesUTAS/f627138c-b243-44ca-83cc-00fb63d42f4cUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/f627138c-b243-44ca-83cc-00fb63d42f4cClimate Futures Interim Archive

https://data.utas.edu.au/metadata/f627138c-b243-44ca-83cc-00fb63d42f4c

An archive of technical reports and the summary reports authored by the Climate Futures for Tasmania Program.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/f627138c-b243-44ca-83cc-00fb63d42f4c2020Tomas RemenyiUniversity of Tasmania, Australia2010northlimit=-8.94476650635172; southlimit=-44.7954799845647; westlimit=108.550415039063; eastlimit=156.393814086914; projection=WGS84UTAS/c65c29c9-1b13-448a-9916-399e9d5a4c79https://orcid.org/0000-0002-4145-9323370202190503Climate ChangeRegional Climate Model AssessmentClimate Research translationUTAS/c65c29c9-1b13-448a-9916-399e9d5a4c79University of Tasmania, Australiahttps://data.utas.edu.au/metadata/c65c29c9-1b13-448a-9916-399e9d5a4c79Climate Futures Technical Reports

https://data.utas.edu.au/metadata/c65c29c9-1b13-448a-9916-399e9d5a4c79

An archive of technical reports authored by the Climate Futures Program.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/c65c29c9-1b13-448a-9916-399e9d5a4c792020Tomas RemenyiUniversity of Tasmania, Australia2010northlimit=-39.1982053488948; southlimit=-44.3709869629717; westlimit=143.15185546875; eastlimit=149.4580078125; projection=WGS84https://orcid.org/0000-0002-4145-9323370202190503Climate ChangeRegional Climate Model AssessmentClimate Research translationUTAS/9f982f11-f508-415d-bf0f-dcfee919a11aUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/9f982f11-f508-415d-bf0f-dcfee919a11aAssessment of magmatic fertility using pXRF on altered rocks from the Ordovician Macquarie Arc, New South Wales

https://data.utas.edu.au/metadata/9f982f11-f508-415d-bf0f-dcfee919a11a

Whole rock geochemical data pertaining to the Australian Journal of Earth Sciences publication "Assessment of magmatic fertility using pXRF on altered rocks from the Ordovician Macquarie Arc, New South Wales". These data include the data source, unique sample ID, sample type and location in 3 dimensions (where applicable) as well as major and trace element geochemistry from the Ordovician intrusive rocks in the Northparkes district as well as a global geochemical reference suite and selected samples from across the Lachlan Fold Belt of eastern Australia. The ratios used in the magmatic fertility study are included in these data. Samples were collected from the Northparkes core library and from the broader district. Geochemical analyses were conducted at various labs and research facilities. All portable X-ray Fluorescence analyses were conducted at CODES - University of Tasmania using an Olympus Vanta M series pXRF with a Rh tube. Data generated by this study were compiled with data from numerous thesis and publications in order to provide a robust data set. Four data files (.xslx) in this set include the Northparkes geochemical data, Geological Survey of New South Wales data compilation, a selected compilation of global porphyry geochemical data compilation from fertile and barren intrusive suites across the globe, and NSW regional pXRF analyses.Attribution(BY)https://data.utas.edu.au/metadata/9f982f11-f508-415d-bf0f-dcfee919a11a2019Tristan WellsUniversity of Tasmania, AustraliaOrdovician to Devoniannorthlimit=-29.382175659442; southlimit=-37.2069981434602; westlimit=145.224609263241; eastlimit=149.501954801381; projection=WGS84https://orcid.org/0000-0001-5229-4619370301250399portable XRFporphyryMacquarie ArcLachlcan OrogenNorthparkesMagmatic FertilityUTAS/eacaf2d6-d20a-42f9-a47d-dc93296f6f56University of Tasmania, Australiahttps://data.utas.edu.au/metadata/eacaf2d6-d20a-42f9-a47d-dc93296f6f56Compiled Geochemical data from the Northparkes porphyry district (1990-2019)

https://data.utas.edu.au/metadata/eacaf2d6-d20a-42f9-a47d-dc93296f6f56

Whole rock geochemical data pertaining to the Australian Journal of Earth Sciences publication "Porphyry Fertility in the Northparkes district: Indicators from whole-rock geochemistry". These data include the data source, unique sample ID, sample type and location in 3 dimensions (where applicable) as well as major and trace element geochemistry from the Ordovician intrusive rocks in the Northparkes district. The ratios used in the magmatic fertility study are included in these data. Samples were collected from the Northparkes core library and from the broader district. All geochemical analyses were performed by ALS Brisbane. Data generated by this study were compiled with data from numerous thesis and publications in order to provide a robust data set. Two data files (.xslx) in this set include the Northparkes geochemical data and a selected compilation of Zirconium and Yttrium geochemical data from fertile and barren intrusive suites across the globe.Attribution - NonCommercial(BY - NC)https://data.utas.edu.au/metadata/eacaf2d6-d20a-42f9-a47d-dc93296f6f562019Tristan WellsSebastien MeffreUniversity of Tasmania, AustraliaOrdovician to Devoniannorthlimit=-32.9180224141736; southlimit=-33.175874124278; westlimit=147.791748043383; eastlimit=148.139648322249; projection=WGS84https://orcid.org/0000-0001-5229-4619https://orcid.org/0000-0003-2741-6076370301250302PorphyryMagmatic fertilityMacquarie ArcNorthparkesUTAS/4ee202f9-c2f6-48a1-82c7-459949113b68University of Tasmania, Australiahttps://data.utas.edu.au/metadata/4ee202f9-c2f6-48a1-82c7-459949113b68Integrating Continuous Differential Evolution with Discrete Local Search for Meander Line RFID Antenna Design

https://data.utas.edu.au/metadata/4ee202f9-c2f6-48a1-82c7-459949113b68

Result sets produced in the application of Differential Evolution to the problem of meander line RFID antenna design, as reported in the in prep. paper "Integrating Continuous Differential Evolution with Discrete Local Search for Meander Line RFID Antenna Design". Two files of generated solutions are included: the eight local search variants applied to the 7x7 instance (7x7_ls_study.txt.zip); and all other results for variants of DE applied to 5x5 to 10x10 problems, plus the results of the prior ACO (de_w_ls_for_RFID_results.txt.zip). Results are grouped by the algorithm composition used to generated them. Also included is C++ source code for a version of the NEC++ antenna evaluator, a Linux executable for the NEC evaluator (mynec), and a Python script for transforming node paths into input files for NEC++ (evaluate.py). The two data files are tab-delimited with the following columns: alg: the algorithm combination used size: grid size (5-10) trial: for DE this is the random seed, for ACO this is the value of the q0 parameter f0: solution's resonant frequency e: solution's efficiency (%) length: number of nodes in the antenna path path: node path as a space-delimited list Values for alg include: DE: the multiobjective DE 'control' DE + bias: DE with solution archive selection bias DE + bias + ls x/y/n: DE with bias and backbite local search, using the x/y/n solution reintegration strategy (see paper for details) DE + bias + (uncounted) ls, regen/det/3: DE with best-performing local search strategy run under similar conditions to prior ACO ACO: the prior Ant Colony System algorithm; due to the way solutions were represented in that work some duplicate solutions were produced The Python evaluation script can be used interactively to generate the input used by NEC or, at the command line, it will also attempt to run the NEC simulator and report the objective values for the given solution.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/4ee202f9-c2f6-48a1-82c7-459949113b682019James MontgomeryUniversity of Tasmania, Australiahttps://orcid.org/0000-0002-5360-7514461104490108280115RFID antennadifferential evolutionant colony optimisationlocal searchevolutionary computationMontgomery J, Randall M, Lewis A, 'Integrating continuous differential evolution with discrete local search for meander line RFID antenna design', PLoS ONE, 14, (10) Article e0223194. ISSN 1932-6203 (2019) [Refereed Article]10.1371/journal.pone.0223194UTAS/42f086a8-bbd2-4ca1-ba32-6a900a397417University of Tasmania, Australiahttps://data.utas.edu.au/metadata/42f086a8-bbd2-4ca1-ba32-6a900a397417Usage Statistics for University of Tasmania EPrints Repository

https://data.utas.edu.au/metadata/42f086a8-bbd2-4ca1-ba32-6a900a397417

The dataset is an active collection of access data to information items in the University of Tasmania's EPrints repository. Each night a task is scheduled to run, and this picks up in the Apache access logs from where it left off the previous night. Each download of an open access full-text item causes the generation of a database record in the MySQL database, together with a timestamp, and an approximate location of the computer system generating the download. This is achieved by looking up the IP address against the GeoIP database, with one significant difference. Downloads originating from a University of Tasmania IP address are separately identified, and removed from the Australia category. This eliminates vanity searches from achieving high significance. Countries are coded using the ISO3166 two-letter code. The dataset has been used to analyse the usage made of the repository and to tune it to achieve maximal visibility for the University of Tasmania. Researchers with items in the repository have used it to identify the types of use being made of their work, and to find potential collaborators. The citation of a work in a journal or conference article, for example, causes a typical step in usage, and the citing article can be searched in Google or Google Scholar to identify the authors. This enhances the dissemination experience and its value. The software was written in the University of Tasmania by Professor Arthur Sale (in php) based on earlier work by the University of Melbourne (with permission). Mr Christian McGee wrote some critical sections of the code in perl, and set up the cron scheduling. The dataset is generated by a computer program written by Professor Arthur Sale. The software was a test bed for ideas, and subsequently resulted in an official software set included in the EPrints distribution. This set expanded on the concepts significantlyAttribution(BY)Copyright is held by the University of Tasmania.https://data.utas.edu.au/metadata/42f086a8-bbd2-4ca1-ba32-6a900a3974172019Arthur SaleUniversity of Tasmania, Australiahttps://orcid.org/0000-0001-7261-8035469999461299220303open source softwarestatistical packageeprintsUTAS/8fbadcd7-6d62-4449-8c97-e2259ad0c06bUniversity of Tasmania, Australiahttps://data.utas.edu.au/metadata/8fbadcd7-6d62-4449-8c97-e2259ad0c06bAquatic Refuge MCAS‐S Datapack for identifying river refuges in the Tasmanian Midlands

https://data.utas.edu.au/metadata/8fbadcd7-6d62-4449-8c97-e2259ad0c06b

The Aquatic Refuge MCAS‐S Datapack the Tasmanian Midlands is made up of spatial data in a form that can be readily opened, displayed and interpreted using MCAS‐S software and a worked example of an MCAS‐S query (known as an MCAS‐S ‘project’). The datapack was designed for the purpose of identifying river locations that could act as climate refuges for aquatic biota. The types of input data/layers considered for the analysis included topographical features, groundwater inflows, tree cover, solar radiation and enhanced flows associated with climate change or shandying for irrigation (transport of irrigation water along natural waterways). Data on land tenure/protection and biological condition are also included for the purpose of prioritising refuges. The worked example includes a functional model that can be opened with MCAS‐S and a user's guide to describe the spatial data in the datapack and provide detailed instructions on how these data can be integrated and analysed within MCAS‐S and also how the model structure can be modified for decision support. We provide all available and relevant input data. We also provide information to help users to add their own or new data to the datapack. For more information see: Magierowski RH, Carter O, Gilfedder L, Gaynor S, Lefroy, EC and Davies PE 2014 Aquatic Refuge MCAS‐S Datapack for the Tasmanian Midlands: A worked example of using the MCAS‐S tool for addressing aquatic questions in the Tasmanian Midlands. Landscapes and Policy Hub. The Multi‐Criteria Analysis Shell for Spatial Decision Support (MCAS‐S), developed by the Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) is a decision support tool designed specifically for non‐GIS users to integrate spatial data. The tool is free to download from www.abares.gov.au/mcass. The Landscapes and Policy Hub developed tools, techniques and policy pathways that enable managers and policy makers to integrate biodiversity conservation into regional–scale pAttribution(BY)https://data.utas.edu.au/metadata/8fbadcd7-6d62-4449-8c97-e2259ad0c06b2019Regina MagierowskiUniversity of Tasmania, Australia2014northlimit=-41.4427263776721; southlimit=-42.5287962932037; westlimit=146.49169921875; eastlimit=147.930908203125; projection=WGS84https://orcid.org/0000-0002-7547-8549410102410206410404190301190504180403rivershydrologyclimate changeecosystemUTAS/f45ef310-4387-4016-a5c3-7c608399a496University of Tasmania, Australiahttps://data.utas.edu.au/metadata/f45ef310-4387-4016-a5c3-7c608399a496MCAS-S Datapack for Alpine Bogs of the Australian Alps Bioregion

https://data.utas.edu.au/metadata/f45ef310-4387-4016-a5c3-7c608399a496

The MCAS-S Datapack for Alpine Bogs of the Australian Alps Bioregion is made up of spatial data in a form that can be readily opened, displayed and interpreted using MCAS-S software and a worked example of an MCAS-S query (known as an MCAS-S ‘project’). The datapack was designed for the purpose of identifying examples of the EPBC Act listed Alpine Sphagnum Bogs and Associated Fens community within the Australian Alps bioregion that are currently, or in the future, likely to be exposed or vulnerable to multiple threats under climate change and range expansion of pest species. The input layers are grouped into two types: 1) Threat – Variables that have the potential to directly impact the ecological condition of alpine bogs and 2) Vulnerability – Variables that have the potential to increase the vulnerability of alpine bogs to impacts from threats. The worked example includes a functional model that can be opened with MCAS-S and a user's guide to describe the spatial data in the datapack and provide detailed instructions on how these data can be integrated and analysed within MCAS-S and also how the model structure can be modified for decision support. We provide relevant input data on a number of threats including fine-scale climate projections from the Climate Futures project, distribution of exotic species, and past & future fire regimes. We also provide information to help users to add their own or new data to the datapack. The Multi-Criteria Analysis Shell for Spatial Decision Support (MCAS-S), developed by the Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) is a decision support tool designed specifically for non-GIS users to integrate spatial data. The tool is free to download from www.abares.gov.au/mcass. The Landscapes and Policy Hub was supported through funding from the Australian Government’s National Environmental Research Programme.Attribution(BY)https://data.utas.edu.au/metadata/f45ef310-4387-4016-a5c3-7c608399a4962019Regina MagierowskiAnita WildUniversity of Tasmania, Australia2014northlimit=-35.9424357525543; southlimit=-37.6229335949009; westlimit=146.348876953125; eastlimit=148.77685546875; projection=WGS84https://orcid.org/0000-0002-7547-8549https://orcid.org/0000-0001-5019-1907410102410404410407190504180601180606wetlandswaterclimate changeexotic faunaexotic floraUTAS/7d1ead3b-7317-4846-b570-cbc688e744e2University of Tasmania, Australiahttps://data.utas.edu.au/metadata/7d1ead3b-7317-4846-b570-cbc688e744e2PIV for Benchmarking - Towing tank flat plate experiment

https://data.utas.edu.au/metadata/7d1ead3b-7317-4846-b570-cbc688e744e2

Benchmarking of Particle Image Velocimetry (PIV) on the moving carriage of the Australian Maritime College towing tank to ITTC Guideline 7.5-01-03-04 using a vertical surface piercing flat plate at angle of incidence 20°.Attribution(BY)https://data.utas.edu.au/metadata/7d1ead3b-7317-4846-b570-cbc688e744e22019Alexander Ashworth BriggsJonathan BinnsUniversity of Tasmania, Australiahttps://orcid.org/0000-0001-7225-6513https://orcid.org/0000-0001-6892-0063401502401299140108researchAshworth Briggs A, Fleming A, Ojeda R, Binns JR, 'Tracking the vortex core from a surface-piercing foil by particle image velocimetry (PIV) using fluorescing particles', Proceedings of the 19th Australasian Fluid Mechanics Conference, 8-11 December, Melbourne, Australia, pp. 1-4. ISBN 978-0-646-59695-2 (2014) [Refereed Conference Paper]UTAS/publications/97463Ashworth Briggs A, Fleming A, Duffy J, Binns JR, 'Tracking the vortex core from a surface-piercing flat plate by particle image velocimetry and numerical simulation', Institution of Mechanical Engineers. Proceedings. Part M: Journal of Engineering for the Maritime Environment, 233, (3) pp. 793-808. ISSN 1475-0902 (2019) [Refereed Article]10.1177/1475090218776202UTAS/dbc8eefe-42b5-4093-bb4f-ce4a4a1d7665University of Tasmania, Australiahttps://data.utas.edu.au/metadata/dbc8eefe-42b5-4093-bb4f-ce4a4a1d7665PQT EMA Data

https://data.utas.edu.au/metadata/dbc8eefe-42b5-4093-bb4f-ce4a4a1d7665

The objective of the current study was to test the effects of the pre-quit use of varenicline and nicotine patch on smoking rate and satisfaction with smoking. Methods: All participants were required to attend up to five study visit sections. Participants (n = 213) who were interested in quitting were randomised (open-label) to receive either prequit patch or varenicline (both treatments started 2 weeks prior to an assigned quit day, followed by 10 weeks post-quit) or standard patch (10 weeks starting from an assigned quit day). Participants used modified smartphones to monitor their smoking in real time for 4 weeks.Attribution - NonCommercial - Share Alike(BY - NC - SA)https://data.utas.edu.au/metadata/dbc8eefe-42b5-4093-bb4f-ce4a4a1d76652018Stuart FergusonUniversity of Tasmania, Australiahttps://orcid.org/0000-0001-7378-3497420605200412smokingcessationnicotinedependenceLu W, Chappell KJ, Walters JAE, Jacobson GA, Patel R, Schuz N, Ferguson SG, 'The effect of varenicline and nicotine patch on smoking rate and satisfaction with smoking: an examination of the mechanism of action of two pre-quit pharmacotherapies', Psychopharmacology, 234, (13) pp. 1969-1976. ISSN 0033-3158 (2017) [Refereed Article]10.1007/s00213-017-4604-y