A body composition model to estimate mammalian energy stores and metabolic rates from body mass and body length, with application to polar bears

Many species experience large fluctuations in food availability and depend on energy from fat and protein stores for survival, reproduction and growth. Body condition and, more specifically, energy stores thus constitute key variables in the life history of many species. Several indices exist to qua...

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Bibliographic Details
Main Authors: Derocher, Andrew E., Klanjscek, Tin, Molnár, Péter K., Lewis, Mark A., Obbard, Martyn E.
Format: Article in Journal/Newspaper
Language:English
Published: 2009
Subjects:
Online Access:https://era.library.ualberta.ca/items/00da503a-9069-42cf-85d2-31237cbe8057
https://doi.org/10.7939/R3MS3K18V
Description
Summary:Many species experience large fluctuations in food availability and depend on energy from fat and protein stores for survival, reproduction and growth. Body condition and, more specifically, energy stores thus constitute key variables in the life history of many species. Several indices exist to quantify body condition but none can provide the amount of stored energy. To estimate energy stores in mammals, we propose a body composition model that differentiates between structure and storage of an animal. We develop and parameterize the model specifically for polar bears (Ursus maritimus Phipps) but all concepts are general and the model could be easily adapted to other mammals. The model provides predictive equations to estimate structural mass, storage mass and storage energy from an appropriately chosen measure of body length and total body mass. The model also provides a means to estimate basal metabolic rates from body length and consecutive measurements of total body mass. Model estimates of body composition, structural mass, storage mass and energy density of 970 polar bears from Hudson Bay were consistent with the life history and physiology of polar bears. Metabolic rate estimates of fasting adult males derived from the body composition model corresponded closely to theoretically expected and experimentally measured metabolic rates. Our method is simple, noninvasive and provides considerably more information on the energetic status of individuals than currently available methods.