[MARMAM] New publication: The blubber adipocyte index: A nondestructive biomarker of adiposity in humpback whales (Megaptera novaeangliae)

Juliana Castrillon Posada juliana.castrillonposada at griffithuni.edu.au
Mon Jun 19 16:40:23 PDT 2017


Dear all

We are very pleased to announce our most recent open access publication in
Ecology and Evolution

Castrillon, Juliana, Wilhelmina Huston, and Susan Bengtson Nash. "The
blubber adipocyte index: A nondestructive biomarker of adiposity in
humpback whales (Megaptera novaeangliae)." *Ecology and Evolution* (2017).

http://onlinelibrary.wiley.com/doi/10.1002/ece3.2913/full

Abstract:
The ability to accurately evaluate the energetic health of wildlife is of
critical importance,
particularly under conditions of environmental change. Despite the
relevance of this issue, currently there are no reliable, standardized,
nonlethal measures to assess
the energetic reserves of large, free-roaming marine mammals such as baleen
whales.
This study investigated the potential of adipocyte area analysis and
further, a standardized
adipocyte index (AI), to yield reliable information regarding humpback
whale (Megaptera novaeangliae) adiposity. Adipocyte area and AI, as
ascertained by image analysis, showed a direct correlation with each other
but only a weak correlation with the commonly used, but error prone,
blubber lipid-percent measure. The relative power of the three respective
measures was further evaluated by comparing humpback whale cohorts at
different stages of migration and fasting. Adipocyte area, AI, and blubber
lipid-percent were assessed by binary logistic regression revealing that
adipocyte area had the greatest probability to predict the migration cohort
with a high level of redundancy attributed to the AI given their strong
linear relationship (r = −.784). When only AI and lipid-percent were
assessed, the performance of both predictor variables was
significant but the power of AI far exceeded lipid-percent. The sensitivity
of adipocyte metrics and the rapid, nonlethal, and inexpensive nature of
the methodology and AI calculation validate the inclusion of the AI in
long-term monitoring of humpback whale population health, and further
raises its potential for broader wildlife applications.


-- 
*Juliana Castrillon *
PhD Candidate
*Southern Ocean Persistent Organic Pollutants Program (SOPOPP)*
Griffith School of Environment, Griffith University, Nathan Campus, 170
Kessels Road, Nathan QLD 4111 Australia
e: juliana.castrillonposada at griffithuni.edu.au
<marie.bigot at griffithuni.edu.au> / ph: +61 (0) 499 788 830
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