Titel
Morphometric parameters predict body fat proportions in common hamsters
Autor*in
Thomas Ruf
Research Institute of Wildlife Ecology, Department of Interdisciplinary Life Sciences, University of Veterinary Medicine
Autor*in
Stefanie Monecke
Institut des Neurosciences Cellulaires et Intégratives (INCI), Neurobiologie des Rythmes, CNRS UPR-3212, Université de Strasbourg
... show all
Abstract
Common hamsters (Cricetus cricetus) are hibernators that rely both on body fat reserves and food stores for the winter period. They face an ongoing population decline in most parts of their distribution and recently were classified as critically endangered. Knowledge on individual body fat proportions in this species is of particular interest for conservation, because it could contribute to better understand the high plasticity in overwintering strategies, overwinter mortality rates, individual variations in reproductive output, and give information on the animals’ health state. To calculate body fat proportions, we validated a method that can be applied in the field without the use of anesthesia. To develop this method, we first analyzed the body fat in carcasses of common hamsters using Soxhlet extractions and measured four morphometric parameters (body mass, head length, tibia length, foot length). The morphometric measurements were then integrated in a linear regression model to predict body fat proportions based on the measured values. The morphometric variables yielded an explained variance (adjusted R2) of 96.42% and body fat proportions were predicted with a mean absolute error of 1.27 ± 0.11% from measured values. We applied the model to predict body fat for available field data, which consistently produced reliable values. By measuring the four morphometric parameters and following the provided instructions, body fat proportions can be reliably and noninvasively estimated in captive or free-ranging common hamsters. Furthermore, the method could be applicable to other rodents after species-specific validation.
Stichwort
body fatcommon hamstermorphometricsmultiple regressionnoninvasivevalidation
Objekt-Typ
Sprache
Englisch [eng]
Persistent identifier
Erschienen in
Titel
Journal of Mammalogy
Band
103
Ausgabe
2
ISSN
0022-2372
Erscheinungsdatum
2021
Seitenanfang
471
Seitenende
480
Publication
Oxford University Press (OUP)
Erscheinungsdatum
2021
Zugänglichkeit
Rechteangabe
© The Author(s) 2021

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