This statistic represents the average height of men and women in selected countries worldwide as of 2008. On average, men are ***** centimeters and women are ***** centimeters tall in Australia.

According to a survey conducted in 2019 by Ipsos on male beauty, ** percent of Australian respondents stated that they preferred men to be between * feet ** inches (about 178cm) to * feet * inch (about 185cm) tall. On the other end of the scale, only *** percent of respondents stated that the ideal height for men was less than * feet (about 152cm).

This dataset contains data derived from the GEOSAT satellite radar altimeter wave measuring program. Maps have been produced from processed data, showing attributes including mean significant wave height and the 100 year mean significant wave.

Format: shapefile.

Quality - Scope: Dataset. Absolute External Positional Accuracy: +/- one degree. Non Quantitative accuracy: Attributes are assumed to be correct.

Dataset measures wave height in metres, at 0.25m intervals:

Cover_Name, Item_Name, Description: mswaveheight, GRID-CODE, Numercial code to index the polygons mswaveheight, MSWAVE_HGT_(M), Mean significant wave height ranging 0-4.5m.

Conceptual consistency: Coverages are topologically consistent. No particular tests conducted by ERIN. Completeness omission: Complete for the Australian continent. Lineage: ERIN: Data was projected to Geographics using the WGS84 spheroid and datum to be compatible for viewing through the Australian Coastal Atlas. The data was attributed with the range of wave height in metres, at an interval of 0.25metres.

CSIRO: All CAMRIS data were stored in VAX files, MS-DOS R-base files and as a microcomputer dataset accessible under the LUPIS (Land Use Planning Information System) land allocation package. CAMRIS was established using SPANS Geographic Information System (GIS) software running under a UNIX operating system on an IBM RS 6000 platform. A summary follows of processing completed by the CSIRO: 1. r-BASE: Information imported into r-BASE from a number of different sources (ie Digitised, scanned, CD-ROM, NOAA World Ocean Atlas, Atlas of Australian Soils, NOAA GEODAS archive and The Complete Book of Australian Weather). 2. From the information held in r-BASE a BASE Table was generated incorporating specific fields. 3. SPANS environment: Works on creating a UNIVERSE with a geographic projection - Equidistant Conic (Simple Conic) and Lambert Conformal Conic, Spheroid: International Astronomical Union 1965 (Australia/Sth America); the Lower left corner and the longitude and latitude of the centre point. 4. BASE Table imported into SPANS and a BASE Map generated. 5. Categorise Maps - created from the BASE map and table by selecting out specified fields, a desired window size (ie continental or continent and oceans) and resolution level (ie the quad tree level). 6. Rasterise maps specifying key parameters such as: number of bits, resolution (quad tree level 8 lowest - 16 highest) and the window size (usually 00 or cn). 7. Gifs produced using categorised maps with a title, legend, scale and long/lat grid. 8. Supplied to ERIN with .bil; .hdr; .gif; Arc export files .e00; and text files .asc and .txt formats. 9. The reference coastline for CAMRIS was the mean high water mark (AUSLIG 1:100 000 topographic map series).

Map showing the annual mean wave height period using satellite derived wave height data generated from the Australian Bureau of Meteorology's Wave Model (WAM). This map has been produced by CSIRO for the National Oceans Office, as part of an ongoing commitment to natural resource planning and management through the 'National Marine Bioregionalisation' project. Variations in onscreen colour representation or printed reproduction may affect perception of the contained data.

An Australia-wide vegetation height was generated using Global Ecosystem Dynamics Investigation (GEDI) LiDAR Altimetry (from 2019) and used to train a random forest model to provide vegetation height from Landsat data available in Digital Earth Australia. The Landsat data used for extrapolating vegetation height images were the Annual Fractional Cover product and the Annual Geomedian product. The random forest model was used to generate annual vegetation height from 1988 to 2021. To reduce errors in irrigated agriculture, vegetation height below three metres was set to zero. Refer to the metadata for a description of the method and validation of this product and the Readme.txt for the data format (see Supporting files). This method was developed through the CSIRO Digiscape Future Science Platform and updated as part of the Regional Land and Ecosystem Accounts project, which is funded through the Australian Department of Climate Change, Energy the Environment and Water (DCCEEW). Lineage: GEDI data are available to download from the NASA EarthData Search website (https://search.earthdata.nasa.gov/search). The Landsat Annual Fractional Cover and Annual Geomedian products data are available through Digital Earth Australia as part of the Collection 3 data (Fractional Cover Percentiles – https://cmi.ga.gov.au/data-products/dea/630/dea-fractional-cover-percentiles-landsat and Geometric Median and Median Absolute Deviation – https://cmi.ga.gov.au/data-products/dea/645/dea-geometric-median-and-median-absolute-deviation-landsat ). Processing was performed on the Australian National Computational Infrastructure (NCI) and the CSIRO Earth Analytics Science and Innovation (EASI) platform, tested using Jupyter notebooks, and batch-processed as python scripts. Images were processed as tiles, then mosaicked to form annual Australia-wide layers.

A 2m by 2m canopy height model (CHM) grid developed from the 2011 aerial LiDAR survey of Christmas Island. As with the 2011 DEM, the CHM was provided to Geoscience Australia in 1km by 1km ESRI grid tiles, which were then joined together using ESRI ArcMap. Each grid cell (2m x 2m) contains the maximum vegetation height in metres. Canopy height was generated by subtracting the ground height from the first laser return classified as vegetation. As a guide, the data is vertically accurate to 15cm and horizontally accurate to 30cm. For a detailed description of the survey accuracy see the AAM Survey Report. The CHM grid file was provided in GDA94 MGA zone 48 and has been left in this projection. The CHM data can be used to find the average vegetation canopy height for defined areas. LiDAR vegetation heights, along with vegetation density values have been used in other organisations to create vegetation maps, estimate carbon content, characterise species habitats and assist in decision making. Disclaimer

Dynamic height of sea surface height and currents referenced to 2000m, computed from CARS2000 3-dimensional seasonal temperature and salinity fields. Monthly values derived from annual and semi-annual temperature and salinity cycles. CARS is a set of seasonal maps of temperature, salinity, dissolved oxygen, nitrate, phosphate and silicate, generated using Loess mapping from all available oceanographic data in the region. It covers the region 100-200E, 50-0S, on a 0.5 degree grid, and on 56 standard depth levels. Higher resolution versions are also available for the Australian continental shelf. The data was obtained from the World Ocean Atlas 98 and CSIRO Marine and NIWA archives. It was designed to improve on the Levitus WOA98 Atlas, in the Australian region. All known reliable published data is used, but this is still very sparse in the SW, at depth, and especially for some nutrients. In many places strong interannual signals (which in many cases we do not attempt to resolve nor compensate for) may be aliased into spatial or seasonal signals.

Remotely sensed topographic (elevation) and bathymetric (depth) information were acquired for the NSW coast (Point Danger to Cape Howe) and southern Queensland (Palm Beach to Point Danger) using Airborne LiDAR Bathymetry (ALB - a combination of Light Detection And Ranging (LiDAR) and Laser Airborne Depth Sounding (LADS) sensors) during July – December 2018. Data were acquired by Fugro Pty Ltd on behalf of NSW Office of Environment and Heritage using a Riegl VQ-820-G ALB (LiDAR) and Fugro LADS High-Definition sensors aboard sub-contracted Corporate Air Cessna C441 (VH-VEH). Funding was provided through the NSW Coastal Reforms package. The objective of the project was to provide high-resolution data better than 3-5 m spaced soundings (0.5 m spot spacing terrestrial; 3.4 m spot spacing marine) from the mean high-water mark to ~200m inland, and from the shore, seaward (LADS - bathymetry) to the point of laser extinction (~20-40m water depth depending on in-water conditions). Positioning data were collected on the ellipsoid ITRF 2014 GRS80 in UTM Z56 and post-processed using local base stations (CORSnet NSW) to provide a Post Processed Kinematic GNSS solution for final aircraft trajectory before being applied to all data. The final data Geotif products are provided on the Geosciences Australia ELVIS website .They are combined gridded terrestrial (elevation) and subtidal marine (bathymetry) data at 5 x 5 m (horizontal resolution) Geotifs exported using ESRI ArcMap from rasters (weighted average of clean soundings) in GDA 2020 (horizontal datum) to Australian Height Datum (vertical datum) and vertical precision to International Hydrographic Order (IHO) 1B. Data covers an area of 6862 km2 provided in 48 sub-datasets the extents of which are generally defined in their alongshore extent by the boundaries of NSW Secondary Sediment Compartments (Geosciences Australia). Other data outputs will include raw and classified LAS format files, aerial imagery and raw seabed reflectance data to be made available shortly on the ELVIS website. Data packages containing Arc Grids (topo-bathy, contours), XYZ, KMZ, tif, pdf maps and Fledermaus SD files will be made publicly available via the AODN (Australian Ocean Data network). Metadata, data quality statements and a geographical data coverage ArcGIS shapefile are available via SEED. The data are intended to inform coastal and marine management and should not be used for navigation without additional processing.

Median canopy height was greatest in areas with a remnant canopy or with advanced revegetation or regeneration. River She-oak riparian forest within the Lower Cotter management zone had the greatest median canopy height out of all the management zones. For Ribbon Gum riparian woodland, the Cotter tributaries management zone had the largest proportion of tall trees, followed by Cotter midsection. The impact of restoration efforts in the Murrumbidgee, Lower Molonglo and Small streams management zones on medium canopy height are difficult to assess at this stage because plantings are still relatively young. It is hoped that median canopy height will improve in these management zones as restoration plantings mature into detectable height-classes over time.

Diversification in sexual signals is often taken as evidence for the importance of sexual selection in speciation. However, in order for sexual selection to generate reproductive isolation between populations, both signals and mate preferences must diverge together. Furthermore, assortative mating may result from multiple behavioural mechanisms, including female mate preferences, male mate preferences and male-male competition; yet their relative contributions are rarely evaluated. Here, we explored the role of mate preferences and male competitive ability as potential barriers to gene flow between two divergent lineages of the tawny dragon lizard, Ctenophorus decresii, which differ in male throat coloration. We found stronger behavioural barriers to pairings between southern lineage males and northern lineage females than between northern males and southern females, indicating incomplete and asymmetric behavioural isolating barriers. These results were driven by both male and female mate preferences rather than lineage differences in male competitive ability. Intrasexual selection is therefore unlikely to drive the outcome of secondary contact in C. decresii, despite its widely acknowledged importance in lizards. Our results are consistent with the emerging view that although both male and female mate preferences can diverge alongside sexual signals, speciation is rarely driven by divergent sexual selection alone.

Methods Study species and husbandry

We used 90 adult lizards (>65mm snout-vent length; SVL) comprising 21 male and 24 female northern lineage C. decresii from Caroona Creek Conservation Park, South Australia (-33.4114°S, 139.0945°E), and 21 male and 24 female southern lineage C. decresii from private properties around Palmer, South Australia (-34.8223°S, 139.1621°E). Lizards were collected in September in 2015 and 2016, and subsequently kept in captivity at The University of Melbourne, Victoria, Australia, where they were housed individually in 55 × 34 × 38cm (length × width × height) opaque plastic enclosures containing a layer of sand and a crevice between two ceramic tiles for shelter. Housing was maintained at temperatures and lighting cycles that mimicked natural seasonal variation, with UV lights (ZooMed T8 ReptiSun® 10.0 UVB) above each enclosure (30cm), emitting both UVA and UVB radiation. A heat lamp was provided to generate a thermal gradient and allow the lizards to attain their preferred body temperatures (approx. 36°C). Lizards were misted with water for hydration and fed live crickets dusted with multi-vitamins three times per week. All behavioural trials were conducted during the breeding seasons (August–December) in 2016 and 2017. Research methods used in this study were reviewed and approved by the Animal Ethics Committee of The University of Melbourne (1413220.3) and the South Australian Wildlife Ethics Committee (25/2015).

Female-male behavioural trials

Females are receptive to mating approximately 2–3 weeks after emergence from hibernation, and after laying their first or second clutch. We conducted mate preference trials during these known receptive periods, when females were in good body condition (average mass of 16.7g ± 2.9g), though receptivity cannot be determined with certainty a priori. Each female was paired with both a southern and a northern lineage male, with half of the females paired with a southern male first and the other half with a northern male first. Females were placed into the first male’s enclosure for a period of 24 hours, and then into the second male’s enclosure for the subsequent 24 hours. Both encounters were monitored and recorded using a Swann DVR8-1525 8 channel 960H digital video recorder with a PRO-615 camera attached. We conducted a total of 147 trials, with individual females paired with one southern and one northern male per reproductive cycle, in up to 2 reproductive cycles (average of 3.34 trials, with a range of 2–4 trials, per female).

Videos were analysed using Behavioural Observation Research Interactive Software (BORIS) version 4.1.5 and both female and male behaviour was scored. For females, we recorded the number of head-bobs (pronounced nodding movement of the head), and combined the number of aggressive behaviours (biting and chasing) and times the female fled from the male as a measure of “rejection”. For males, we also recorded the number of head-bobs (courtship behaviour) as well as the number of attempts to copulate, and whether or not copulation was successful. We did not analyse the number of successful copulations as copulation was observed in only 7 of the 147 trials (although more may have taken place under the tile). Lizards were not paired for long enough to ensure mating; rather, we were interested in behaviour during initial contact as an indicator of mate preference.

We tested whether female lineage, male lineage, or their interaction predicted: 1) number of copulation attempts, 2) number of male head-bobs, 3) number of female head-bobs and 4) number of female rejection behaviours using generalised linear mixed models (lme4 package, R). Female ID, male ID and pairing number (female’s first or second trial) were included as random factors in all models to account for repeated use of individuals, and response variables were log transformed to meet model assumptions of normality. We performed pairwise comparisons by calculating least squares means and confidence intervals using the Satterthwaite’s approximation for degrees of freedom (lmerTest package, R).

Male-male behavioural trials

A previous study investigating aggression levels among morphs of the northern lineage found that orange-throated males were significantly more aggressive towards territory intruders than yellow, orange-yellow or grey-throated males. Therefore, we categorised males into three behavioural groups based on lineage and throat colour morph: southern, northern high aggression (orange), or northern low aggression (yellow, orange-yellow, grey). We designed trials such that each focal male was matched with three others, representing each of the behavioural groups, in random order. Pairs were size-matched to minimize the effect of body size on contest outcome, with an average difference of 1.59mm ± 1.16mm snout vent length (SVL) between competing males.

Contest trials were conducted in a neutral 120 × 30 × 60cm (length × width × height) enclosure (i.e. not the home enclosure of either male). An opaque divider initially separated the enclosure into two equally sized holding areas, each containing a layer of sand, ceramic tile and heat lamp. Just prior to the trial, males were weighed to obtain a measure of body condition as the residuals of a linear model of mass and SVL. The designated “focal” and “opponent” males were then placed into the separate holding areas and allowed to acclimatise for 48 hours to establish residency. At the commencement of the trial, the divider was removed and the interaction was recorded from two different angles using Panasonic HC-V770M video cameras. Trials were conducted for a maximum of 25 minutes and monitored to ensure there was no risk of injury to animals (as required under the Animal Ethics permit). Consequently, we did not record contest outcome (i.e. winner, loser) as some trials were stopped before a winner was established. To minimize stress and the potential influence of previous contest outcomes, males were not used in a subsequent trial for at least 48 hours. We conducted a total of 120 trials (involving 42 males), 26 of which were excluded due to no interaction, resulting in 94 trials which were used in the statistical analysis.

We scored focal male behaviour from the video footage using BORIS. C. decresii males perform energetic displays during territory defence prior to engaging in physical aggression. Therefore, we recorded the number of head-bobs, tail flicks and push-ups performed by the focal male as a measure of “display behaviour”, and combined the duration of chasing and wrestling (involving biting) as a measure of “physical aggression”. We also recorded the time between the start of the trial and the focal male’s emergence from beneath the tile (“latency”), as this is an indicator of individual boldness. Display behaviour and physical aggression were divided by the total trial duration (minus latency) to account for differences in trial lengths.

We tested whether behavioural group or body condition predicted: 1) focal male latency to emerge, 2) focal male display behaviour and 3) focal male physical aggression using generalised linear mixed models. We included focal male behavioural group, opponent male behavioural group and their interaction, as well as focal male body condition and opponent male body condition as predictor variables in the models. Additionally, focal male ID and focal male trial number were included as random factors in all models to account for repeated use of individuals. For models 2 (display behaviour) and 3 (physical aggression), the response variables were log transformed to meet model assumptions of normality, and we performed post hoc pairwise comparisons as detailed above.

Dynamic height of sea surface height and currents referenced to 2000m, computed from CARS2000 3-dimensional seasonal temperature and salinity fields. Monthly values derived from annual and semi-annual temperature and salinity cycles. CARS is a set of seasonal maps of temperature, salinity, dissolved oxygen, nitrate, phosphate and silicate, generated using Loess mapping from all available oceanographic data in the region. It covers the region 100-200E, 50-0S, on a 0.5 degree grid, and on 56 standard depth levels. Higher resolution versions are also available for the Australian continental shelf. The data was obtained from the World Ocean Atlas 98 and CSIRO Marine and NIWA archives. It was designed to improve on the Levitus WOA98 Atlas, in the Australian region. All known reliable published data is used, but this is still very sparse in the SW, at depth, and especially for some nutrients. In many places strong interannual signals (which in many cases we do not attempt to resolve nor compensate for) may be aliased into spatial or seasonal signals.