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OZCAM (Online Zoo-log-i-cal Col-lec-tions of Aus-tralian Muse-ums) pro-vides access to an online data-base of records aggre-gated from fau-nal col-lec-tions data-bases in Aus-tralian museums.

Occurrence record: invertebrates:E14208

Preserved specimen of Ischnochiton (Ischnochiton) mawlei Iredale & May, 1916 recorded on 1983-03-24
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Dataset

Data partner OZCAM (Online Zoological Collections of Australian Museums) Provider
Data resource Tasmanian Museum and Art Gallery provider for OZCAM
Institution code Tasmanian Museum and Art Gallery
Supplied institution code "TMAG"
Collection Tasmanian Museum and Art Gallery Invertebrate Collection
Supplied collection code "invertebrates"
Catalog number E14208
Occurrence ID TMAG: E14208
Record type Preserved specimen
Supplied basis "PreservedSpecimen"
Identified by G.J. Edgar  
Collector G.J. Edgar
License CC-BY 4.0 (Int)
Presence/Absence PRESENT
Supplied as present
Sampling protocol [SCUBA]

Event

Occurrence date 1983-03-24
Supplied date "24/03/1983"
Sampling protocol SCUBA  
End day of year 83
Date precision DAY
Start day of year 83

Taxonomy

Scientific name Ischnochiton (Ischnochiton) mawlei
Original name usage Ischnochiton mawlei
Identified to rank species
Kingdom Animalia
Phylum Mollusca
Class Polyplacophora
Order Chitonida
Supplied as "Callochitonida"
Family Ischnochitonidae
Genus Ischnochiton
Species Ischnochiton mawlei
Name match metric exactMatch
Scientific name authorship Iredale & May, 1916
Name parse type SCIENTIFIC

Geospatial

Country Australia
State or Territory Tasmania
Locality Maatsuyker Island: offshore
Latitude -43.644
Supplied as: "-43.644"
Longitude 146.27
Supplied as: "146.27"
Datum EPSG:4326
Supplied datum: "GDA94"
Verbatim locality Maatsuyker Island, South Tasmania
Coordinate precision 1.0e-03
Coordinate uncertainty (in metres) 1000.0
Terrestrial true
Biome TERRESTRIAL
Marine false
Country Code AU

Additional properties

verbatim identification Ischnochiton mawlei

User flagged issues 

    Referenced in publications

    Publication: Curated Plant and Invertebrate Data for Bushfire Modelling

    DOI https://doi.org/10.25919/tm4m-5a46

    This data asset contains observations of individual plants and animals (“occurrences”) sourced from the Atlas of Living Australia. Data on vascular plants are based on the following paper: Godfree et al. (2021) Implications of the 2019-2020 Megafires for the Biogeography and Conservation of Australian Vegetation. Nature Communications 12: 1023 https://doi.org/10.1038/s41467-021-21266-5 Data on invertebrates are from the following report: Marsh et al. (2021) Threatened species hub report: Assessment of the impacts of the 2019-20 wildfires on southern and eastern Australia on invertebrate species. NESP Threatened Species Recovery Hub Project 8.3.1 Final report, Brisbane. Both studies were performed to understand the impacts of the Australian “Black Summer” (2019-20) fires on the taxonomic group in question. Consequently, this aggregated dataset is designed to support off-the-shelf bushfire impact modelling, and to provide useful context for associated biodiversity conservation work. A total of 896 species of vascular plants and 44,146 invertebrate species. The combined data asset was produced by the Science & Decision Support Team at the Atlas of living Australia (ALA) in collaboration with the authors of the original data sets. This was done as part of an Australian Research Data Commons (ARDC) bushfire data challenges project. The data contained in this deposition has been cleaned by researchers and taxonomists to ensure it is of high quality. Therefore, compared to data returned by the ALA, the unique record ID’s may return a different species or location than is denoted in this data set: these records have potentially been changed by the authors of the data to reflect what they believe is correct.

    Version of the data used in the publication
    Scientific nameIschnochiton (Ischnochiton) mawlei
    Decimal latitude-43.644
    Decimal longitude146.279
    Year1983

    View all data referenced by this publication

    Data quality tests

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