A body composition model with multiple storage compartments for polar bears (Ursus maritimus)

Author:

Penk Stephanie R12ORCID,Sadana Pranav13,Archer Louise C1,Pagano Anthony M4,Cattet Marc R L5,Lunn Nicholas J6,Thiemann Gregory W7,Molnár Péter K12

Affiliation:

1. University of Toronto Scarborough Laboratory of Quantitative Global Change Ecology, Department of Biological Sciences, , 1265 Military Trail, Scarborough, Ontario M1C 1A4, Canada

2. University of Toronto Department of Ecology and Evolutionary Biology, , 25 Willcocks Street, Toronto, Ontario M5S 3B2 Canada

3. University of Winnipeg Department of Biology, , 515 Portage Ave, Winnipeg, Manitoba R3B 2E9, Canada

4. Alaska Science Center U.S. Geological Survey, , 4210 University Dr., Anchorage, AK 99508 USA

5. Government of Yukon Fish and Wildlife Branch, Department of Environment, , 10 Burns Road, Whitehorse, Yukon Y1A 4Y9, Canada

6. Environment Canada and Climate Change Canada Wildlife Research Division, Science and Technology Branch, , 11455 Saskatchewan Dr., Edmonton, Alberta T6G 2E9, Canada

7. York University Faculty of Environmental and Urban Change, , 4700 Keele St., Toronto, Ontario M3J 1P3, Canada

Abstract

Abstract Climate warming is rapidly altering Arctic ecosystems. Polar bears (Ursus maritimus) need sea ice as a platform from which to hunt seals, but increased sea-ice loss is lengthening periods when bears are without access to primary hunting habitat. During periods of food scarcity, survival depends on the energy that a bear has stored in body reserves, termed storage energy, making this a key metric in predictive models assessing climate change impacts on polar bears. Here, we developed a body composition model for polar bears that estimates storage energy while accounting for changes in storage tissue composition. We used data of dissected polar bears (n = 31) to link routinely collected field measures of total body mass and straight-line body length to the body composition of individual bears, described in terms of structural mass and two storage compartments, adipose and muscle. We then estimated the masses of metabolizable proteins and lipids within these storage compartments, giving total storage energy. We tested this multi-storage model by using it to predict changes in the lipid stores from an independent dataset of wild polar bears (n = 36) that were recaptured 8–200 days later. Using length and mass measurements, our model successfully predicted direct measurements of lipid changes via isotopic dilutions (root mean squared error of 14.5 kg). Separating storage into two compartments, and allowing the molecular composition of storage to vary, provides new avenues for quantifying energy stores of individuals across their life cycle. The multi-storage body composition model thus provides a basis for further exploring energetic costs of physiological processes that contribute to individual survival and reproductive success. Given bioenergetic models are increasingly used as a tool to predict individual fitness and population dynamics, our approach for estimating individual energy stores could be applicable to a wide range of species.

Publisher

Oxford University Press (OUP)

Subject

Management, Monitoring, Policy and Law,Nature and Landscape Conservation,Ecological Modeling,Physiology

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