Accounting for body mass effects in the estimation of field metabolic rates from body acceleration

Author:

Byrnes Evan E.123ORCID,Lear Karissa O.1ORCID,Brewster Lauran R.34ORCID,Whitney Nicholas M.5,Smukall Matthew J.36ORCID,Armstrong Nicola J.17ORCID,Gleiss Adrian C.12ORCID

Affiliation:

1. Centre for Sustainable Aquatic Ecosystems, Harry Butler Institute, Murdoch University, 90 South St., Murdoch, WA 6150, Australia

2. College of Science, Health, Engineering and Education, Murdoch University, 90 South Street, Murdoch, WA 6150, Australia

3. Bimini Biological Field Station Foundation, South Bimini, Bahamas

4. Harbor Branch Oceanographic Institute, Florida Atlantic University, 5600 N US Highway 1, Fort Pierce, FL 34946, USA

5. Anderson Cabot Center for Ocean Life, New England Aquarium, 1 Central Wharf, Boston, MA 02110, USA

6. College of Fisheries and Ocean Sciences, University of Alaska Fairbanks, 2150 Koyukuk Drive, Fairbanks, AK 99775, USA

7. Department of Mathematics and Statistics, Curtin University, Kent Street, Bentley, Perth, WA 6102, Australia

Abstract

ABSTRACT Dynamic body acceleration (DBA), measured through animal-attached tags, has emerged as a powerful method for estimating field metabolic rates of free-ranging individuals. Following respirometry to calibrate oxygen consumption rate (ṀO2) with DBA under controlled conditions, predictive models can be applied to DBA data collected from free-ranging individuals. However, laboratory calibrations are generally performed on a relatively narrow size range of animals, which may introduce biases if predictive models are applied to differently sized individuals in the field. Here, we tested the mass dependence of the ṀO2–DBA relationship to develop an experimental framework for the estimation of field metabolic rates when organisms differ in size. We performed respirometry experiments with individuals spanning one order of magnitude in body mass (1.74–17.15 kg) and used a two-stage modelling process to assess the intraspecific scale dependence of the ṀO2–DBA relationship and incorporate such dependencies into the coefficients of ṀO2 predictive models. The final predictive model showed scale dependence; the slope of the ṀO2–DBA relationship was strongly allometric (M1.55), whereas the intercept term scaled closer to isometry (M1.08). Using bootstrapping and simulations, we evaluated the performance of this coefficient-corrected model against commonly used methods of accounting for mass effects on the ṀO2–DBA relationship and found the lowest error and bias in the coefficient-corrected approach. The strong scale dependence of the ṀO2–DBA relationship indicates that caution must be exercised when models developed using one size class are applied to individuals of different sizes.

Funder

Save Our Seas Foundation

National Science Foundation

Publisher

The Company of Biologists

Subject

Insect Science,Molecular Biology,Animal Science and Zoology,Aquatic Science,Physiology,Ecology, Evolution, Behavior and Systematics

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