Juvenile shark occurrence inferred from baited remote underwater video surveys Northwest Australia (2003-2013)
This dataset describes the predicted occurrence of juvenile sharks around Northwest Australia, mapped over a 0.01 degree spatial grid. Juvenile sharks were mapped at two taxonomic levels: order by including all juvenile sharks sampled (all juveniles) and species by considering the three most abundant species sampled separately (grey reef (Carcharhinus amblyrhynchos), sandbar (Carcharhinus plumbeus), and whitetip reef (Triaenodon obesus) sharks). The data cover the period 2003-2013 and are derived from an analysis of count data derived from baited remote underwater videos deployed through various sampling programs. Further detail can be found in the following peer-reviewed publication: Oh, BZL, Sequeira, AMM, Meekan, MG, Ruppert, JLW and Meeuwig, JJ (2017), Predicting occurrence of juvenile shark habitat to improve conservation planning. Conservation Biology, 31: 635–645. doi:10.1111/cobi.12868
Below is a full list of species, with contributions to the total counted (%):
--------------------------------------------------
Silvertip shark / Carcharhinus albimarginatus – 4.14%
Grey reef shark / Carcharhinus amblyrhynchos – 28.06%
Bronze whaler / Carcharhinus brachyurus – 0.18%
Galapagos shark / Carcharhinus galapagensis – 0.09%
Bull shark / Carcharhinus leucas – 0.18%
Common-Australian blacktip shark / Carcharhinus limbatus-C.tilstoni – 1.38%
Blacktip reef shark / Carcharhinus melanopterus – 1.56%
Sandbar shark / Carcharhinus plumbeus – 4.78%
Spot-tail shark / Carcharhinus sorrah – 0.18%
Tiger shark / Galeocerdo cuvier – 2.39%
Sliteye-Sharpnose shark / Loxodon macrorhinus-Rhizoprionodon spp. – 6.35%
Lemon shark / Negaprion acutidens – 1.01%
Whitetip reef shark / Triaenodon obesus – 18.95%
Tawny shark / Nebrius ferrugineus – 0.83%
Grey carpetshark / Chiloscyllium punctatum – 1.38%
Taselled wobbegong / Eucrossorhinus dasypogon – 0.09%
Scalloped hammerhead / Sphyrna lewini – 0.46%
Great hammerhead / Sphyrna mokarran – 3.86%
Zebra shark / Stegostoma fasciatum – 0.83%
Sicklefin houndshark / Hemitriakis falcata – 1.01%
Grey gummy shark / Mustelus ravidus – 0.28%
Archived BRUVS video files used in this study are the intellectual property of multiple institutions and industry partners and are not published in this record. See credits for further information.
Simple
Identification info
- Date (Creation)
- 2016-09-27
Principal investigator
- Credit
- Australian Institute of Marine Science for access to BRUVS data, PTTEP Australasia Ltd for BRUVS data generated from a study, Roland Pitcher (Geoscience Australia) for access to environmental data collated by Geoscience Australia.
- Credit
- National Environmental Science Program (NESP) Marine Biodiversity Hub
- Status
- Completed
Point of contact
Principal investigator
- Topic category
-
- Biota
Extent
Temporal extent
- Time period
- 2003-06-06 2013-04-22
- Maintenance and update frequency
- Not planned
- Keywords (Theme)
-
- marine protected areas
- baited remote underwater video stations (BRUVS)
- occurrence
- wildlife distribution
- Keywords (Taxon)
-
- Sharks (Order Selachii)
- Global Change Master Directory (GCMD) Earth Science Keywords Version 8.0
- Keywords (Theme)
-
- Predicted occurrence of all juvenile sharks
- Predicted ocurrence of grey reef shark
- Predicted occurrence of whitetip reef shark
- Predicted occurrence of sandbar shark
Resource constraints
- Classification
- Unclassified
Resource constraints
- Use limitation
- The data described in this record are the intellectual property of the University of Western Australia and the Australian Institute of Marine Science.
- Use limitation
- This record is hosted by the Institute of Marine Science (IMAS), University of Tasmania (UTAS) on behalf of UWA and AIMS.
Resource constraints
- Linkage
-
http://i.creativecommons.org/l/by/4.0/88x31.png
License Graphic
- Title
- Creative Commons Attribution 4.0 International License
- Website
-
http://creativecommons.org/licenses/by/4.0/
License Text
- Other constraints
- The citation in a list of references is: citation author name/s (year metadata published), metadata title. Citation author organisation/s. File identifier and Data accessed at (add http link).
- Other constraints
- Data was sourced from the NESP Marine Biodiversity Hub – the Marine Biodiversity Hub is supported through funding from the Australian Government’s National Environmental Science Program (NESP), administered by the Department of the Environment (DOE).
- Language
- English
- Character encoding
- UTF8
- Supplemental Information
- Oh, BZL, Sequeira, AMM, Meekan, MG, Ruppert, JLW and Meeuwig, JJ (2017), Predicting occurrence of juvenile shark habitat to improve conservation planning. Conservation Biology, 31: 635–645. doi:10.1111/cobi.12868
Content Information
- Content type
- Physical measurement
- Description
- 0.01 degree spatial grid
- Name
-
Predicted occurrence of all juvenile sharks
- Name
-
pred.Alljuv
- Name
- proportion
- Description
- 0.01 degree spatial grid
- Name
-
Predicted ocurrence of grey reef shark
- Name
-
pred.Camb
- Name
- proportion
- Description
- 0.01 degree spatial grid
- Name
-
Predicted occurrence of whitetip reef shark
- Name
-
pred.Tobe
- Name
- proportion
- Description
- 0.01 degree spatial grid
- Name
-
Predicted occurrence of sandbar shark
- Name
-
pred.Cplu
- Name
- proportion
Distribution Information
- Distribution format
-
-
ESRI Shapefile
-
ESRI Shapefile
- OnLine resource
-
DATA ACCESS - predicted occurrence of juvenile sharks in NW Australia [zipped Shapefiles, direct download]
- OnLine resource
-
ASSOCIATED PUBLICATION - Predicting occurrence of juvenile shark habitat to improve conservation planning [doi:10.1111/cobi.12868]
- OnLine resource
-
NESP Project D1 [ANDS RDA record]
Resource lineage
- Statement
- The following information were extracted from 2,262 BRUVS deployments: shark species, number of sharks, shark fork length, sampling date, location (longitude and latitude at 0.01° precision), and soak time (number of hours the BRUVS were deployed). Sharks were classified as juveniles or adults based on published lengths at which 50% of the individuals were mature (i.e., juvenile < L50 ≤ adult; Last & Stevens 2009; Harry et al. 2011). Because sex could not be reliably determined from the video imagery, for species with sex-specific L50, we used an average of the lengths at male and female maturity. Presence-absence records were pooled at the taxonomic level of order for 21 species (hereafter “all juveniles”), and also for the three most abundant juvenile species sampled: grey reef, sandbar and whitetip reef sharks. Raw data were filtered and pooled for each grid cell with a resolution of 0.01° (284 presence and 441 absence records). For further details, see Oh, BZL, Sequeira, AMM, Meekan, MG, Ruppert, JLW and Meeuwig, JJ (2017), Predicting occurrence of juvenile shark habitat to improve conservation planning. Conservation Biology, 31: 635–645. doi:10.1111/cobi.12868
- Hierarchy level
- Dataset
Metadata
- Metadata identifier
-
5af57072-c4c2-4a5a-bc72-62486dc6d73e
- Language
- English
- Character encoding
- UTF8
Point of contact
Type of resource
- Resource scope
- Dataset
- Metadata linkage
-
https://metadata.imas.utas.edu.au/geonetwork/srv/eng/catalog.search#/metadata/5af57072-c4c2-4a5a-bc72-62486dc6d73e
Point of truth URL of this metadata record
- Date info (Creation)
- 2018-12-14T17:00:00
- Date info (Revision)
- 2018-12-14T17:00:00
Metadata standard
- Title
- ISO 19115-3:2018