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The Relationship Between White Nose Syndrome and Dietary PUFA Levels in Bats

  • Craig L. Frank
  • Patricia M. Diaz
  • Thomas H. Kunz
Chapter

Abstract

Six bat species in northeastern North America spend winter hibernating in caves/mines. Hibernation is characterized by multi-day periods of torpor, when metabolic rates are reduced. Body fat levels increase from 7 to 27% in the fall, just prior to the onset of hibernation by bats. Some groups of hibernating bats in northeastern North America display abnormal behaviors and increased overwinter mortality called white nose syndrome (WNS). Large numbers of dead bats are found in hibernation sites affected by WNS. Previous research has demonstrated that the increased over-mortality is due to the depletion of depot fat reserves by February, which is in turn caused by greatly shortened torpor bouts. Published studies on hibernating mammals have revealed that moderately high levels of polyunsaturated fatty acids (PUFAs) are required in the diet during the fall for torpor. We thus predicted that bats suffering from WNS have lower levels of PUFAs in their fall diets than those that do not suffer from WNS. We tested this hypothesis by analyzing white adipose tissue (WAT) samples from: (a) little brown bats (Myotis lucifugus) collected from different hibernation sites and (b) big brown bats (Eptesicus fuscus), a species not greatly affected by WNS. Our analyses reveal that M. lucifugus populations prone to WNS have significantly less of the PUFA α-linolenic acid in their fall diets than those where WNS does not occur. The fall diets of E. fuscus contain significantly more of the PUFA linoleic acid than those of M. lucifugus from the same site. Our findings thus support the hypothesis that bats suffering from WNS have lower levels of PUFAs in their fall diets.

Keywords

White Adipose Tissue Ground Squirrel PUFA Content Torpor Bout PUFA Ratio 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

We thank Alan Hicks and Carl Hertzog for their generous assistance. This study was supported by NSF grants IOS-0818222 awarded to C.L.F., and IOS- 0840762 awarded to T.H.K. and C.L.F.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Craig L. Frank
    • 1
  • Patricia M. Diaz
    • 1
  • Thomas H. Kunz
    • 2
  1. 1.Department of Biological SciencesFordham UniversityArmonkUSA
  2. 2.Department of BiologyBoston UniversityBostonUSA

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