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Population genetics of dugongs in SBMP
No full textMaintenance and Update Frequency: unknownStatement: Original record compiled for the Western Australian Marine Science Institution (WAMSI), Project 3.8, 2008. Originally sourced from several databases compiled by WA DEC Marine Science Branch of projects relevant to the marine parks of WA. Variable metadata information was available.<b>Credit</b><br/>Adrian McMahan: James Cook University (JCU)Collection of skin samples from Dugongs for describing population structure of Dugongs using genetic analyses
Percentage of variance in radiolarian correspondence analysis scores explained by various oceanic parameters
No full textMaintenance and Update Frequency: irregularStatement: Parameters: Variable, depth (m), percentage of the variance in correspondence scores for radiolarian abundance counts explained by environmental variable (%).<b>Credit</b><br/>Funded by The Australian Research Council (ARC)<b>Credit</b><br/>The Australian National University (ANU)<b>Credit</b><br/>National Oceanographic and Atmospheric Administration (NOAA)<b>Purpose</b><br/>Investigation of quaternary palaeo-environmental oceanographic parametersPercentage of the variance in correspondence scores for radiolarian abundance counts for sites in the eastern & southern Indian Ocean explained by environmental variables for those sites. <br/><br/>The abundance counts were derived from ~100 surface sediment gravity cores from the Southern and Eastern Indian Ocean collected between 1988 and 2004. <br/><br/>The environmental variables (annual, austral spring, summer, autumn and winter.for depths between the surface and 500m) were obtained from NOAA World Ocean Atlas 2001
Disturbance effects on fish assemblages at large scales of space and time (Ningaloo, Rowley Shoals, Scott Reef)
No full textMaintenance and Update Frequency: unknownStatement: Original record compiled for the Western Australian Marine Science Institution (WAMSI), Project 3.8, 2008. Originally sourced from several databases compiled by WA DEC Marine Science Branch of projects relevant to the marine parks of WA. Variable metadata information was available.<b>Credit</b><br/>A. Halford: Australian Institute of Marine Science (AIMS), Fremantle<b>Credit</b><br/>James Cook University (JCU)Baseline data collection from 1990's to presen
Ningaloo Historical Collections
No full textMaintenance and Update Frequency: unknownStatement: Original record compiled for the Western Australian Marine Science Institution (WAMSI), Project 3.8, 2008. Originally sourced from several databases compiled by WA DEC Marine Science Branch of projects relevant to the marine parks of WA. Variable metadata information was available.<b>Credit</b><br/>Jane Fromont: Western Australian Museum (WAM)Uploading historical invertebrate data from the Ningaloo region to OBIS
Mean grainsize of surface samples collected from the Reef rim physiographic zone of Wistari Reef
No full textStatement: Surface samples were collected on reef walks or on boat transects across Wistari Reef. Deeper samples were obtained by diving. Samples were collected using a hand-held scoop and 600ml plastic bottles. Sediment samples were sieved in order to determine modal particle diameters, and sorting data. Samples were first dry sieved. Sieves of sizes -1.0phi to 2.5phi were stacked and installed on a sieving shaker. Samples were weighed out to approximately 250g, and each sample was sieved for 15minutes to ensure correct separation of size fractions. Each fraction was then removed from the sieve and weighed. The size fractions 2.5phi, 3.0phi, 3.5phi and 4.0phi were pre-weighed, and wet sieved separately using a low pressure water hose, through smaller micropalaeontological sieves. Sediment textures are expressed in terms of mean grainsize, and sorting coefficient, represented by standard deviation.Statement: Although the data represents the average, the sediments on the reef edge vary greatly in grainsize and sorting. In general, the reef edge supports a very low proportion of sediments due to the high energy conditions. The only sediments seen here exist in protected pools and other slightly lower energy environments. Scanned histograms are used to highlight the percentage of sediments within each grainsize bracket. The exact percentage figures are not available.
Parameters: Average mean grainsize (phi), average sorting coefficient (phi), dominant coarse biota, dominant fine biota.<b>Credit</b><br/>Funded by The Australian Research Council (ARC)<b>Credit</b><br/>The Australian National University (ANU)<b>Purpose</b><br/>To provide an overview of the sedimentary zones of Wistari Reef. Conducted as part of a broader study looking at Holocene production and accumulation of sediments on Wistari Reef.Wistari Reef is a lagoonal platform reef, situated on the Tropic of Capricorn, within the Capricorn and Bunker region of the southern Great Barrier Reef (GBR). Surface samples were taken from the reef-rim to determine the mean grainsize and the sorting coefficient and also the proportion of aragonite to calcite within the samples. In this area the average mean grainsize is ~0.21phi, with an average sorting coefficient of 0.62phi. It should be noted that the sediments of the reef edge vary greatly in grainsize and sorting; ranging from moderately well-sorted to poorly sorted coarse sand
The relative abundance (%) of planktonic foraminifera over time in core BAR 9403, located off the coast of Sumatra
No full textStatement: Foraminifera were identified accurately to a species level, with an average of 437 individuals picked and identified per sample. Relative species abundances are calculated as a percentage of the total count.
Parameters: Age of core (yrs BP), relative abundance of planktonic foraminifera assemblages (%).Statement: Counts of planktonic foraminifera were made on splits of the >150µm fractions to provide a base level for ecological counts, removing small juvenile and possibly unidentifiable foraminifera. Each sample was split by an Otto-micro splitter until ~400 species were present in the final split.<b>Credit</b><br/>The Australian National University (ANU)<b>Credit</b><br/>Funded by The National Oceans Office (NOO)<b>Credit</b><br/>Funded by The French Polar Institute<b>Credit</b><br/>Funded by The Australian Institute of Nuclear Science Engineering (AINSE)<b>Credit</b><br/>Funded by The Australian Research Council (ARC)<b>Credit</b><br/>Funded by The Murray Darling Basin Commission<b>Purpose</b><br/>To reconstruct the faunal assemblages of planktonic foraminifera through time and give insight into palaeoceanography of core location.The advent of deep-sea drilling in the 1950's prompted the use of planktonic foraminifera (unicellular protozans) as palaeoceanographic indicators. They provide a natural archive of past environmental changes due to their global distribution, their prolific productivity and sensitivity to environmental variations. <br/><br/>The most obvious change in relative abundance in core BAR9403 (off the coast of Sumatra) is shown by sub-polar to transitional 'upwelling' species Ga. bulloides with abundances of 26% at approximately 14,000yrs BP and 22.7% during the Holocene. This is compared to the periods from Marine Isotope Stage (MIS) 3 to the Last Glacial Maximum (LGM) where the relative abundance of Ga. bulloides is generally <10%. Gr. menardii, a tropical 'upwelling' species, also increases its relative abundance during MIS 2 from <8% during MIS 3 to a peak abundance of 16% at ~17,000yrs BP
***Draft***The Effect of Industrial Development on Mangroves in North Western Australia
No full textStatement: Original record compiled for the Western Australian Marine Science Institution (WAMSI) Node 3.8 project (North West Marine Research Inventory) with Michelle Vardy - Environmental Graduate from BHP Billiton providing the original information.In 2000, the consultant Halpern Glick and Maunsell completed a study on the effect of industrial development on mangroves in North Western Australi
Carbon isotope (13-C) values for 5 different foraminiferal species down the core of GC12, collected from the Capricorn Channel
No full textMaintenance and Update Frequency: notPlannedStatement: Samples for foraminifera picking were dried in the oven at 60oC before being re-soaked in distilled water. Samples were then wet sieved through a series of four mesh sizes before the size fractions were transferred to drying trays. After drying foraminifera were picked from under microscope for the large size fractions of >300 µm and >400µm. 10-15 individuals of each species were hand picked for isotope analysis. The samples were washed in methanol and ultrasonicated for 30 secs to remove any surface and internal particles. The samples were analysed at the Research School of Earth Science, Australian National University, using an automated individual carbonate reaction (Kiel) device coupled with a Finnigan MAT-251 mass spectrometer.Statement: 13-C values are normalised to TIC (total inorganic carbon) for 3 of the 5 foraminifera species analysed. The 13-C of the Cibicidoides genus is considered to reflect the 13-C of bottom water with relatively little fractionation relative to equilibrium calcite, while no correction is available for Gr. truncatulinoides. The noramlisation accounts for interspecies variability in fractionating carbon isotopes. The record of G. ruber, G. sacculifer and Gr. menardii is provided consistently every 5-10 cm of the core, down to a depth of 510cm. The results for Gr. menardii and Gr. truncatulinoides are more sporadic due to the absence of these species within some intervals of the core, generally in the top 150cm. From 150cm (~16340 yrs BP) down, results are provided for every 5-10cm.<b>Credit</b><br/>Funded by The Australian Research Council (ARC)<b>Credit</b><br/>Funded by The Australian National University (ANU) Faculties Research Grant Scheme<b>Purpose</b><br/>The analysis of stable isotopes in multiple species of planktonic foraminifera provides an insight into changes in the gradients of physical and biological properties in the water column. Carbon isotopes ratios are used to track changes in biological productivity and have been the traditional tool with which palaeoceanographers trace water masses.A gravity core (GC12) was collected from a depth of 990.5 mbsl within the Capricorn Channel, southern Great Barrier Reef (GBR). 13-C values were recorded for 5 foraminiferal species through the core, with results varying considerably throughout the last 30kyr. The 13-C values of the benthic Cibicidoides spp. are the lowest, whilst those for the planktonic species are comparable, once correlated for their vital effects (except Globorotalia truncatulinoides because no correction for vital effects is available). It is apparent from the 13-C values that there are 3 main 13-C phases during the glacial/interglacial transition: Glacial, Deglaciation and Holocene phases
Analogue site survey report for Apache Energy Ltd. Stag- 8.
No full textMaintenance and Update Frequency: unknownStatement: Original record compiled for the Western Australian Marine Science Institution (WAMSI), Project 3.8, 2008. Originally sourced from DEWHA EPBC Referrals online (April, 2008). Metadata information generated from citations in referrals. Date range from citation date. Abstract derived from citation title only. Spatial extent derived from referral area of interest.<b>Credit</b><br/>Racal Survey Australia Ltd<b>Credit</b><br/>Apache Energy LtdAnalogue site survey report for Apache Energy Ltd. Stag- 8
Hyperspectral mapping - bathymetry
No full textMaintenance and Update Frequency: unknownStatement: Original record compiled for the Western Australian Marine Science Institution (WAMSI), Project 3.8, 2008. Originally sourced from several databases compiled by WA DEC Marine Science Branch of projects relevant to the marine parks of WA. Variable metadata information was available.<b>Credit</b><br/>Merv Lynch - Curtin University<b>Credit</b><br/>Wojciech Klonowski (Curtin)<b>Credit</b><br/>Peter Feans (murdoch)<b>Credit</b><br/>Mark Grey (Murdoch)To use the hyperspectral data to create a bathymetry data set and board scale classification of the lagoon habitats over the extent of the NMP. Develop a radiation transfer model and optimisation code that can be used by researchers on a a number of different systems to reprocess atmospherically corrected reflectance data