Hydrocarbon-degrading bacteria in SRE4 experiment by most probable number count

• Other Authors: BOWMAN, JOHN (hasPrincipalInvestigator), POWELL, SHANE (hasPrincipalInvestigator), POWELL, SHANE (processor), Australian Antarctic Data Centre (publisher)
• Format: Dataset
• Language: unknown
• Published: Australian Antarctic Data Centre
• Subjects: environment; CONTAMINANT LEVELS/SPILLS; EARTH SCIENCE; HUMAN DIMENSIONS; ENVIRONMENTAL IMPACTS; OIL SPILLS; PETROLEUM; SOLID EARTH; EARTH GASES/LIQUIDS; SEDIMENT CHEMISTRY; OCEANS; MARINE SEDIMENTS; BACTERIA/ARCHAEA; BIOLOGICAL CLASSIFICATION; EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > BENTHIC; bacteria; most probable number; hydrocarbon biodegradation; used synthetic lubricant; synthetic lubricant; biodegradable lubricant; diesel; sediment; special antarctic blend; SEDIMENT CORERS; FIELD SURVEYS; CONTINENT > ANTARCTICA > Casey; GEOGRAPHIC REGION > POLAR; Antarctic; Antarc*; Antarctica
• Online Access: https://researchdata.ands.org.au/hydrocarbon-degrading-bacteria-number-count/701816; https://doi.org/10.26179/5d3f9c8252954; https://data.aad.gov.au/metadata/records/SRE4_hydrocarbondegrading_MPN_2001; http://nla.gov.au/nla.party-617536

Most probable number counts of bacteria in sediment samples from the Sediment Recruitment Experiment 4. Samples were taken immediately after the collection of sediment, after the addition of the oils to the sediment and after five weeks in-situ incubation. Sediment was treated by the addition of oil (four different types: synthetic lubricant, used synthetic lubricant, biodegradable lubricant and special Antarctic blend diesel) and the number of bacteria able to degrade components of Special Antarctic Blend diesel (SAB) was determined using an MPN method on a marine mineral medium with Special Antarctic Blend diesel as sole carbon source. Data are presented as the most-probable-number of bacteria per gram of wet sediment. See also the metadata record 'SRE4_hydrocarbondegrading_MPN_2006'. This work was completed as part of ASAC project 1228. The download file contains a readme which provides further information about the dataset, as well as an excel and csv copy of the data.