Blue Whale Study aerial surveys, southern Australia 2002-2007
Citation
Gill, P. 2015. Blue Whale Study aerial surveys, southern Australia 2002-2007. Data downloaded from OBIS-SEAMAP (http://seamap.env.duke.edu/dataset/971) on yyyy-mm-dd. https://doi.org/10.15468/rfz6xk accessed via GBIF.org on 2024-12-12.Description
Original provider: Blue Whale Study Inc. Dataset credits: Blue Whale Study Inc. Abstract: Blue whales Balaenoptera musculus aggregate to feed in a regional upwelling system during November–May between the Great Australian Bight (GAB) and Bass Strait. We analyzed sightings from aerial surveys over 6 upwelling seasons (2001–02 to 2006–07) to assess within-season patterns of blue whale habitat selection, distribution, and relative abundance. Habitat variables were modelled using a general linear model (GLM) that ranked sea surface temperature (SST) and sea surface chlorophyll (SSC) of equal importance, followed by depth, distance to shore, SSC gradient, distance to shelf break, and SST gradient. Further discrimination by hierarchical partitioning indicated that SST accounted for 84.4% of variation in blue whale presence explained by the model, and that probability of sightings increased with increasing SST. The large study area was resolved into 3 zones showing diversity of habitat from the shallow narrow shelf and associated surface upwelling of the central zone, to the relatively deep upper slope waters, broad shelf and variable upwelling of the western zone, and the intermediate features of the eastern zone. Density kernel estimation showed a trend in distribution from the west during November–December, spreading south-eastward along the shelf throughout the central and eastern zones during January–April, with the central zone most consistently utilized. Encounter rates in central and eastern zones peaked in February, coinciding with peak upwelling intensity and primary productivity. Blue whales avoided inshore upwelling centers, selecting SST ~1°C cooler than remotely sensed ambient SST. Whales selected significantly higher SSC in the central and eastern zones than the western zone, where relative abundance was extremely variable. Most animals departed from the feeding ground by late April. Purpose: A primary objective of the present study was to use modelling (i.e., general linear model [GLM]) to assess the relative importance of a range of biophysical habitat variables in explaining whale distribution (see Redfern et al. 2006 for a review of cetacean habitat modelling). To do this we used blue whale sighting data from aerial surveys over 6 upwelling seasons, in combination with bathymetric, remote sensing, and temperature logger data. Another objective was to explain within-season patterns of distribution and relative abundance of foraging blue whales in this upwelling system using density kernel estimation and monthly variabililty in encounter rates. Furthermore, the present study presented an opportunity to assess whether the Bonney Upwelling surface plume, representing a shoaling of the thermocline rarely observed in blue whale feeding grounds elsewhere, provided insights into relationships between whales and upwelling in this region.Reference: Redfern, J.V., M.C. Ferguson, E.A. Becker, K.D. Hyrenbach et al. 2006. Techniques for cetacean-habitat modelling. Marine Ecological Progress Series 310:271–295. Supplemental information: [2015-06-04] The identification of the species is updated from Balaenoptera musculus to Balaenoptera musculus brevicauda.
Purpose
A primary objective of the present study was to use modelling (i.e., general linear model [GLM]) to assess the relative importance of a range of biophysical habitat variables in explaining whale distribution (see
Redfern et al. 2006 for a review of cetacean habitat modelling). To do this we used blue whale sighting data from aerial surveys over 6 upwelling seasons, in combination with bathymetric, remote sensing, and temperature logger data. Another objective was to explain within-season patterns of distribution and
relative abundance of foraging blue whales in this upwelling system using density kernel estimation and monthly variabililty in encounter rates. Furthermore, the present study presented an opportunity to assess whether the Bonney Upwelling surface plume, representing a shoaling of the thermocline rarely observed in blue whale feeding grounds elsewhere, provided insights into relationships between whales and upwelling in this region.
Reference: Redfern, J.V., M.C. Ferguson, E.A. Becker, K.D. Hyrenbach et al. 2006. Techniques for cetacean-habitat modelling.
Marine Ecological Progress Series 310:271–295.
Sampling Description
Study Extent
NASampling
NAMethod steps
- NA
Additional info
marine, harvested by iOBISTaxonomic Coverages
Scientific names are based on the Integrated Taxonomic Information System (ITIS).
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Balaenoptera musculus brevicaudacommon name: Pygmy blue whale rank: subspecies
Geographic Coverages
Australia
Bibliographic Citations
Contacts
Peter Gilloriginator
position: Primary contact
Blue Whale Study Inc.
email: pete@bluewhalestudy.org
homepage: http://www.bluewhalestudy.org
OBIS-SEAMAP
metadata author
Marine Geospatial Ecology Lab, Duke University
A328 LSRC building
Durham
27708
NC
US
email: seamap-contact@duke.edu
homepage: http://seamap.env.duke.edu
OBIS-SEAMAP
distributor
Marine Geospatial Ecology Lab, Duke University
A328 LSRC building
Durham
27708
NC
US
email: seamap-contact@duke.edu
homepage: http://seamap.env.duke.edu
Peter Gill
owner
position: Primary contact
Blue Whale Study Inc.
email: pete@bluewhalestudy.org
homepage: http://www.bluewhalestudy.org
Peter Gill
administrative point of contact
position: Primary contact
Blue Whale Study Inc.
email: pete@bluewhalestudy.org
homepage: http://www.bluewhalestudy.org