Data

Blue Whale Study aerial surveys, southern Australia, 2007-2012

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/dr15884&rft.title=Blue Whale Study aerial surveys, southern Australia, 2007-2012&rft.identifier=ala.org.au/dr15884&rft.publisher=Atlas of Living Australia&rft.description=Original provider: Blue Whale Study Inc. Dataset credits: Blue Whale Study Inc. Abstract: Wind-forced cold water upwelling occurs seasonally along the continental shelf of south-east Australia, where pygmy blue whales aggregate to forage. Seasonality and variability are apparent for both blue whale encounter rates and upwelling, within and between seasons. Here we quantify upwelling variability over 11 seasons (2001/02 to 2011/12) and relate it to blue whale encounter rates. Two indices, cumulative wind stress (Intensity) quantifying physical forcing, and surface chlorophyll-a (chl-a) quantifying the ocean’s biological response, revealed variability in upwelling at a variety of temporal scales. Within seasons, upwelling Intensity peaked during February, and chl-a during February–March. Blue whale encounter rate from 52 aerial surveys was modelled against upwelling indices and the climate signal SAM (Southern Annular Mode), at individual survey- and aggregated season-levels, using General Additive Models (GAMs). Survey-level GAMs showed that encounter rate increased with increasing chl-a, and with increasing upwelling Intensity to a point beyond which further increases in Intensity resulted in declining encounter rates. This indicated the importance of productivity, as well as relaxation of upwelling, in producing optimal blue whale foraging conditions. In exploratory season-level models, a strong influence of SAM was apparent, with higher encounter rates associated with positive SAM during the preceding 12 months. Including chl-a improved the model, indicating that both broad-scale climatic signals inherently incorporating environmental variability and uncertainty, as well as more proximal regional factors may influence blue whale occurrence in the study area. Measuring the complex relationships between whale occurrence and upwelling is complicated by the fact that the population of blue whales using the Bonney Upwelling is open, and moves between alternate foraging areas. The findings were interpreted in the context of blue whale foraging ecology in this system. Purpose: Relate variability in blue whale relative abundance to variability in upwelling off southern Australia&rft.creator=Anonymous&rft.date=2020&rft_rights=&rft_rights=This work is licensed under a Creative Commons Attribution (CC-BY) 4.0 License.&rft.type=dataset&rft.language=English Access the data

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Brief description

Original provider:
Blue Whale Study Inc.

Dataset credits:
Blue Whale Study Inc.

Abstract:
Wind-forced cold water upwelling occurs seasonally along the continental shelf of south-east Australia, where pygmy blue whales aggregate to forage. Seasonality and variability are apparent for both blue whale encounter rates and upwelling, within and between seasons. Here we quantify upwelling variability over 11 seasons (2001/02 to 2011/12) and relate it to blue whale encounter rates. Two indices, cumulative wind stress (Intensity) quantifying physical forcing, and surface chlorophyll-a (chl-a) quantifying the ocean’s biological response, revealed variability in upwelling at a variety of temporal scales. Within seasons, upwelling Intensity peaked during February, and chl-a during February–March. Blue whale encounter rate from 52 aerial surveys was modelled against upwelling indices and the climate signal SAM (Southern Annular Mode), at individual survey- and aggregated season-levels, using General Additive Models (GAMs). Survey-level GAMs showed that encounter rate increased with increasing chl-a, and with increasing upwelling Intensity to a point beyond which further increases in Intensity resulted in declining encounter rates. This indicated the importance of productivity, as well as relaxation of upwelling, in producing optimal blue whale foraging conditions. In exploratory season-level models, a strong influence of SAM was apparent, with higher encounter rates associated with positive SAM during the preceding 12 months. Including chl-a improved the model, indicating that both broad-scale climatic signals inherently incorporating environmental variability and uncertainty, as well as more proximal regional factors may influence blue whale occurrence in the study area. Measuring the complex relationships between whale occurrence and upwelling is complicated by the fact that the population of blue whales using the Bonney Upwelling is open, and moves between alternate foraging areas. The findings were interpreted in the context of blue whale foraging ecology in this system.

Purpose:
Relate variability in blue whale relative abundance to variability in upwelling off southern Australia

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Identifiers
  • Local : ala.org.au/dr15884