Data

Blue Whale Study aerial surveys, southern Australia 2002-2007

Atlas of Living Australia
Ocean Biodiversity Information System (Managed by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://collections.ala.org.au/public/show/dr15883&rft.title=Blue Whale Study aerial surveys, southern Australia 2002-2007&rft.identifier=ala.org.au/dr15883&rft.publisher=Atlas of Living Australia&rft.description=Original provider: Blue Whale Study Inc. Dataset credits: Blue Whale Study Inc. Abstract: Blue whales <i>Balaenoptera musculus</i> 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.<br><br> 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.&rft.creator=Anonymous&rft.date=2020&rft_rights=&rft_rights=This work is licensed under a Creative Commons Attribution Non Commercial (CC-BY-NC) 4.0 License.&rft.type=dataset&rft.language=English Access the data

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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.

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  • Local : ala.org.au/dr15883