Find research datasets worth reusing

opencc-by-4.0Aug 2021View details →

The arrival and spread of the European firebug Pyrrhocoris apterus in Australia as documented by citizen scientists

Data and R script to reproduce analyses conducted in The arrival and spread of the European firebug Pyrrhocoris apterus in Australia as documented by citizen scientists Abstract We present evidence of the recent introduction and quick spread of the European firebug Pyrrhocoris apterus in Australia, as documented on the citizen science platform iNaturalist. The first public record of the species was reported in December 2018 in the City of Brimbank (Melbourne, Victoria). Since then, the species distribution has quickly expanded into 15 local government areas surrounding this first observation, including areas in both Metropolitan Melbourne and regional Victoria. The number of records of the European firebug in Victoria has also seen a substantial increase, with a current tally of almost 100 observations in iNaturalist as of July 31st, 2021. The case of the European firebug in Australia adds to the list of examples of citizen scientists playing a key role in not only early detection of newly introduced species but in documenting their expansion across their non-native range. Citizen science presents an exciting opportunity to complement biosecurity efforts carried out by government agencies, which often lack resources to sufficiently fund detection and monitoring programs given the overwhelming number of current and potential invasive species. Recognising and supporting the invaluable contribution of citizen scientists to science and society can help reduce this gap by: (1) increasing the number of introduced species that are quickly detected; (2) gathering evidence of the species’ early expansion stage; and (3) prompting adequate monitoring and rapid management plans for potentially harmful species. Given the range expansion patterns of the European firebug worldwide, their adaptation ability, and future climate scenarios, we suspect this species will continue expanding beyond Victoria, including other parts of Australia, New Zealand, and the South Pacific. We firmly believe that most of the knowledge about how this expansion process continues to happen will be provided by citizen scientists.

opencc-by-4.0Sep 2021View details →

PRISMA-derived water quality parameters for Lake Hume (Australia) (2020/04/22)

This dataset contains PRISMA-derived water quality (WQ) products of Lake Hume (Australia) for the 22 April 2020. Available parameters are: True-color image (RGB), Colored Dissolved Organic Matter (CDOM), Chlorophyll-a (CHL), and Suspended Particulate Matter (SPM). WQ parameters have been calculated using CNR’s bio-optical model BOMBER parameterized with the inherent optical properties specific of the case study. The data are available as GeoTiff files in WGS 84 / UTM zone 32N (EPSG: 32632). PRISMA data courtesy of the Italian Space Agency (ASI, 2020).

opencc-by-4.0Sep 2021View details →

DESIS-derived water quality parameters for Lake Hume (Australia) (2020/02/26)

This dataset contains DESIS-derived water quality (WQ) products of Lake Hume (Australia) for the 26 February 2020. Available parameters are: True-color image (RGB), Colored Dissolved Organic Matter (CDOM), Chlorophyll-a (CHL), and Suspended Particulate Matter (SPM). WQ parameters have been calculated using CNR’s bio-optical model BOMBER parameterized with the inherent optical properties specific of the case study. The data are available as GeoTiff files in WGS 84 / UTM zone 32N (EPSG: 32632). DESIS data courtesy of the German Aerospace Center (DLR, 2020).

opencc-by-4.0Sep 2021View details →

Daily temperature data at Adelaide, Australia taken in a Glaisher thermometer stand (1856–1952) and a homogenised daily temperature dataset for Adelaide (1856–2019)

23000_Adelaide_Glaisherstand_Tx_data.tsv and 23000_Adelaide_Glaisherstand_Tn_data.tsv: Daily maximum and minimum temperature observations for Adelaide,South Australia, taken in a Glaisher thermometer stand from November 1856 to July 1947. Data are given in Station Exchange Format (SEF, https://github.com/C3S-Data-Rescue-Lot1-WP3/SEF/wiki). 23000_combined_homogenised_data.tsv: A homogenised daily temperature dataset for Adelaide, South Australia, from January 1859 to December 2019. Data are provided in the format Year, Month, Day, Maximum temperature (degrees Celcius), Minimum temperature (degrees Celcius). Images of the data source for File 1 are available from the Australian Meteorological Association at https://www.met-acre.net/MERIT/AMETA.html.  The data are shared under Attribution-NonCommercial 4.0 International licence (CC BY-NC 4.0)

opencc-by-4.0Oct 2021View details →

Beach-face slope dataset for Australia

This repository contains a dataset of beach-face slopes for the Australian coastline. It includes more than 13,200 km of sandy coast with estimates of the beach-face slopes provided every 100 m. The methodology and dataset are described in: Vos, K., Deng, W., Harley, M. D., Turner, I. L., and Splinter, K. D. M.: Beach-face slope dataset for Australia, Earth Syst. Sci. Data, 14, 1345–1357, https://doi.org/10.5194/essd-14-1345-2022, 2022. The beach-face slope data is provided in 2 separate GEOJSON files: Australia_slopes_by_transect.geojson and Australia_slopes_by_beach.geojson. The first one presents the data along each transect (total of 132,132 beach transects) and the second one presents the data for each individual beach/embayment (total of 5,207 beaches).  Additionally, there are three layers that contain polygons for the Australian coastal regions, primary compartments and secondary compartments, respectively. The coordinate system for the geospatial layers is WGS84. 1. Australia_slope_by_transect.geojson: contains a geospatial layer with cross-shore transects along the Australian sandy coastline. Each feature in this layer is a transect (2 point linestring) with the following attributes:   - transect_id: Database id for each transect, e.g., aus0001-0000, aus0001-0001, …   - beach_id: Database id for each beach, e.g., aus0001, aus0002, …, aus5255   - beach_slope: estimate of the beach-face slope between Mean Sea Level (MSL) and Mean High Water Springs (MHWS), value between 0.01 and 0.2   - lower_conf_bound: Lower limit of the confidence band for the slope estimate   - upper_conf_bound: Upper limit of the confidence band for the slope estimate   - width_conf_band: Width of confidence band, value between 0 and 0.19)   - sl_points: Number of datapoints in the shoreline time-series used for beach-face slope estimation (minimum set to 100)   - quality_flag: Quality flag indicating the confidence in the slope estimate at this transect (High, Medium or Low)   - coastal_region: Database id corresponding to the 23 coastal regions as identified by Thom et al. (2018)   - primary_comp_id: Database id corresponding to the 100 primary sediment compartments as identified by Thom et al. (2018)   - secondary_comp_id: Database id corresponding  to the 361 secondary sediment Compartments as identified by Thom et al. (2018) 2. Australia_slope_by_beach.geojson: contains a geospatial layer with each individual beach/embayment (as a linestring) along the Australian sandy coastline. Each feature has the following attributes:   - beach_id: Database id for each beach, e.g., aus0001, aus0002, …, aus5255   - beach_slope_average: Average of the beach-face slope at the site, weighted by the width of the confidence bands, value between 0.01 and 0.2   - width_ci_average: Average width of confidence band over the comprised transects, value between 0 and 0.19   - quality_flag: Quality flag indicating the confidence in the slope estimate at this transect (High, Medium or Low)   - mstr: Mean Spring Tide Range at the beach calculated from the closest grid point in the FES2014 global tide model   - hsig_median: Median Significant Wave Height from the closest grid point in the CAWCR re-analysis dataset   - prc_msrt_obs: percentage of the Mean Spring Tide Range observed by the satellite-derived shorelines   - min_tide_obs: Lowest tide level observed by the satellite-derived shorelines   - max_tide_obs: Highest tide level observed by the satellite-derived shorelines   - sl_points_average: Average number of datapoints in the shoreline time-series over the comprised transects   - beach_length: Length of the beach or embayment, very long beaches (>50km) were split to optimise memory usage when downloading the satellite images   - coastal_region: Database id corresponding to the 23 coastal regions as identified by Thom et al. (2018)   - primary_comp_id: Database id corresponding to the 100 primary sediment compartments as identified by Thom et al. (2018)   - secondary_comp_id: Database id corresponding  to the 361 secondary sediment Compartments as identified by Thom et al. (2018) In addition to these two layers, the 3 different levels of the Sediment Compartments framework (Thom et al.. 2018) with their average beach-face slopes are also included here. 3. coastal_regions.geojson: contains a geospatial layer of each coastal region (as polygon) as defined by Thom et al. 2018. Each feature has the following attributes:   - name: name of the coastal region, e.g., Pilbara, Kimberley, etc   - beach_slope_average_by_beach: Beach-face slope in each coastal region averaged across all the individual beaches inside the polygon   - beach_slope_average_by_transect: Beach-face slope in each coastal region, averaged across all the individual 100-m spaced transects inside the polygon 4. primary_compartments.geojson: contains a geospatial layer of each primary sediment compartment (as polygon) as defined by Thom et al. 2018. Each feature has the following attributes:   - primary_comp_id: Database id corresponding to the 100 primary sediment compartments as identified by Thom et al. (2018)   - name: name of each primary sediment compartment   - beach_slope_average_by_beach: Beach-face slope in each coastal region averaged across all the individual beaches inside the polygon   - beach_slope_average_by_transect: Beach-face slope in each coastal region, averaged across all the individual 100-m spaced transects inside the polygon 5. secondary_compartments.geojson: contains a geospatial layer of each secondary sediment compartment (as polygon) as defined by Thom et al. 2018. Each feature has the following attributes:   - secondary_comp_id: Database id corresponding to the 361 secondary sediment compartments as identified by Thom et al. (2018)   - name: name of each secondary sediment compartment   - beach_slope_average_by_beach: Beach-face slope in each coastal region averaged across all the individual beaches inside the polygon   - beach_slope_average_by_transect: Beach-face slope in each coastal region, averaged across all the individual 100-m spaced transects inside the polygon

opencc-by-4.0Jan 2023View details →

New insights into crustal deformation of the Indonesia-Australia-New Guinea collision zone from a broad-scale kinematic model: Supplementary Model Files

Supplementary kinematic model input for the JGR: Solid Earth publication "New insights into crustal deformation of the Indonesia-Australia-New Guinea collision zone from a broad-scale kinematic model".

opencc-by-4.0Aug 2022View details →

Supplementary data for: "The influence of reef isostasy, dynamic topography, and glacial isostatic adjustment on the Last Interglacial sea-level record of Northeastern Australia"

This repository contains supplementary information and data for the paper: ""The influence of reef isostasy, dynamic topography, and glacial isostatic adjustment on the Last Interglacial sea-level record of Northeastern Australia", submitted to Communications Earth & Environment. This version (1.1) was produced to answer comments from reviewers.

openmit-licenseMay 2023View details →

WTF Climate dataset: 4 years of weather data from tropical Queensland, Australia

This repository contains the code for constructing a 4-year climate dataset for the WTF project. Time series were constructed for 6 field sites in Queensland, Australia at 1 hour resolution.

opencc-by-4.0Feb 2023View details →

Seafood mislabelling in Australia

Input data for the Cundy et al. paper: Seafood label quality and mislabelling rates hamper consumer choices for sustainability in Australia. Includes .fasta files used to create a forward and reverse sequence consensus as well as .xlsx files with the various inputs into the processing script.

opencc-by-4.0Apr 2020View details →

Beach-face slopes from satellite-derived shorelines along SE Australia and California

This repository contains the data described in Vos, K., Harley, M. D., Splinter, K. D., Walker, A., & Turner, I. L. (2020). Beach Slopes From Satellite‐Derived Shorelines. Geophysical Research Letters, 47(14), e2020GL088365. There are 2 GEOJSON files in this repository. The coordinate system for both geospatial layers is WGS84 (epsg:4326). 1. slopes_along_transects.geojson: contains a geospatial layer with cross-shore transects for sandy coastlines along SE Australia and California. Each feature in this layer is a transect (2 point linestring) with the following attributes:   - site_id: id of the beach in which the transect is located   - id: id of the individual transect   - orientation: orientation of the transect in degrees from North (positive clockwise)   - beach slope: beach-face slope from Mean Sea Level (MSL) to Mean High Water Springs (MHWS) 2.  slopes_along_beaches.geojson: this layer contains sandy beaches instead of transects. For each beach the median slope has been calculated from all the available transects. The following attributes are available:     - id: id of the beach     - name: name of the beach in the OpenStreetMap database (if not available 'noname')     - beach_length: length of the beach in metres     - median_orientation: beach orientation calculated as the median of the orientations of each transect     - Tide range: average tidal range (mean high water - mean low water) at each beach based on FES2014 global tide model     - median_slope: median beach-face slope along the beach based on the estimated beach-face slope along the transects

Figs 40-42. Macvicaria kingscotensis n in Eight new species of Macvicaria Gibson and Bray, 1982 (Digenea: Opecoelidae) from temperate marine fishes of Australia

Figs 40-42. Macvicaria kingscotensis n. sp. ex Haletta semifasciata. 40. Whole-mount ventral view. 41. Terminal genitalia. 42. Dorsal distribution of vitelline follicles. Scale bars: 40, 42, 250 µm; 41, 100 µm.

Figs 1-3. Macvicaria shotteri n in Eight new species of Macvicaria Gibson and Bray, 1982 (Digenea: Opecoelidae) from temperate marine fishes of Australia

Figs 1-3. Macvicaria shotteri n. sp. ex Apogon fasciatus. 1. Whole-mount ventral view. 2. Terminal genitalia. 3. Dorsal distribution of vitelline follicles. Scale bars: 1, 3, 250 µm; 2, 100 µm.

Figs 30-32 in Eight new species of Macvicaria Gibson and Bray, 1982 (Digenea: Opecoelidae) from temperate marine fishes of Australia

Figs 30-32. Macvicaria heronensis Bray & Cribb, 1989 ex Trachinotus coppingeri. 30. Whole-mount ventral view. 31. Terminal genitalia. 32. Dorsal distribution of vitelline follicles. Scale bars: 30, 32, 250 µm; 31, 100 µm.

Figs 7-9. Macvicaria mekistomorphe n in Eight new species of Macvicaria Gibson and Bray, 1982 (Digenea: Opecoelidae) from temperate marine fishes of Australia

Figs 7-9. Macvicaria mekistomorphe n. sp. ex Sillago maculata. 7. Whole-mount ventral view. 8. Terminal genitalia. 9. Dorsal distribution of vitelline follicles. Scale bars: 7, 9, 250 µm; 8, 100 µm.

Figs 19-20. Macvicaria flexuomeatus n in Eight new species of Macvicaria Gibson and Bray, 1982 (Digenea: Opecoelidae) from temperate marine fishes of Australia

Figs 19-20. Macvicaria flexuomeatus n. sp. ex Cheilodactylus rubrolabiatus. 19. Whole-mount ventral view. 20. Dorsal distribution of vitelline follicles. Scale bars: 19, 20, 250 µm.

Figs 4-6. Macvicaria shotteri n in Eight new species of Macvicaria Gibson and Bray, 1982 (Digenea: Opecoelidae) from temperate marine fishes of Australia

Figs 4-6. Macvicaria shotteri n. sp. ex Sillaginodes punctatus. 4. Whole-mount ventral view. 5. Terminal genitalia. 6. Dorsal distribution of vitelline follicles. Scale bars: 4, 6, 250 µm; 5, 100 µm.

opencc-by-4.0Mar 2010View details →

Figure 24. A in The millipede genus Tasmaniosoma Verhoeff, 1936 (Diplopoda, Polydesmida, Dalodesmidae) from Tasmania, Australia, with descriptions of 18 new species

Figure 24. A Localities as of 31 January 2010 for Tasmaniosoma alces sp. n. (filled triangles), T. aureorivum sp. n. (crosses), T. australe sp. n. (filled squares), T. bruniense sp. n. (stars), T. hesperium sp. n. (open circles), T. laccobium sp. n. (open triangle), T. maria sp. n. (filled circles) and T. warra sp. n. (open squares). See also Fig. 23. Scale bar = 50 km. (B) Map of Tasmania showing location of main map (rectangle).

opencc-by-4.0Mar 2010View details →

Figure 23. A in The millipede genus Tasmaniosoma Verhoeff, 1936 (Diplopoda, Polydesmida, Dalodesmidae) from Tasmania, Australia, with descriptions of 18 new species

Figure 23. A Localities as of 31 January 2010 for Tasmaniosoma hickmanorum sp. n. (squares), T. compitale sp. n. (stars) and T. armatum Verhoeff, 1936 (crosses). Scale bar = 100 km. B Preliminary mapping of eastern parapatric boundary between T. compitale sp. n. (stars) and T. hickmanorum sp. n. (squares). Bounding rectangle as in map (A); scale bar = 20 km.

opencc-by-4.0Apr 2009View details →

Figure 3 in A new millipede genus and a new species of Asphalidesmus Silvestri, 1910 (Diplopoda, Polydesmida, Dalodesmidea) from southern Tasmania, Australia

Figure 3. Dorsal view of ring 12 and left lateral view of ring 13 of paratype males. (A), (B) Noteremus summus sp. n., QVM 23:46556; (C), (D) N. infimus sp. n., QVM 23:12969. Scale bars = 0.5 mm.