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Combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable

BACKGROUND: All behaviour requires energy, and measuring energy expenditure in standard units (joules) is key to linking behaviour to ecological processes. Animal-borne accelerometers are commonly used to infer proxies of energy expenditure, termed ‘dynamic body acceleration’ (DBA). However, convert...

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Autores principales: Chakravarty, Pritish, Cozzi, Gabriele, Scantlebury, David Michael, Ozgul, Arpat, Aminian, Kamiar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10228015/
https://www.ncbi.nlm.nih.gov/pubmed/37254220
http://dx.doi.org/10.1186/s40462-023-00395-0
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author Chakravarty, Pritish
Cozzi, Gabriele
Scantlebury, David Michael
Ozgul, Arpat
Aminian, Kamiar
author_facet Chakravarty, Pritish
Cozzi, Gabriele
Scantlebury, David Michael
Ozgul, Arpat
Aminian, Kamiar
author_sort Chakravarty, Pritish
collection PubMed
description BACKGROUND: All behaviour requires energy, and measuring energy expenditure in standard units (joules) is key to linking behaviour to ecological processes. Animal-borne accelerometers are commonly used to infer proxies of energy expenditure, termed ‘dynamic body acceleration’ (DBA). However, converting acceleration proxies (m/s(2)) to standard units (watts) involves costly in-lab respirometry measurements, and there is a lack of viable substitutes for empirical calibration relationships when these are unavailable. METHODS: We used past allometric work quantifying energy expenditure during resting and locomotion as a function of body mass to calibrate DBA. We used the resulting ‘power calibration equation’ to estimate daily energy expenditure (DEE) using two models: (1) locomotion data-based linear calibration applied to the waking period, and Kleiber’s law applied to the sleeping period (ACTIWAKE), and (2) locomotion and resting data-based linear calibration applied to the 24-h period (ACTIREST24). Since both models require locomotion speed information, we developed an algorithm to estimate speed from accelerometer, gyroscope, and behavioural annotation data. We applied these methods to estimate DEE in free-ranging meerkats (Suricata suricatta), and compared model estimates with published DEE measurements made using doubly labelled water (DLW) on the same meerkat population. RESULTS: ACTIWAKE’s DEE estimates did not differ significantly from DLW (t(19) = − 1.25; P = 0.22), while ACTIREST24’s estimates did (t(19) = − 2.38; P = 0.028). Both models underestimated DEE compared to DLW: ACTIWAKE by 14% and ACTIREST by 26%. The inter-individual spread in model estimates of DEE (s.d. 1–2% of mean) was lower than that in DLW (s.d. 33% of mean). CONCLUSIONS: We found that linear locomotion-based calibration applied to the waking period, and a ‘flat’ resting metabolic rate applied to the sleeping period can provide realistic joule estimates of DEE in terrestrial mammals. The underestimation and lower spread in model estimates compared to DLW likely arise because the accelerometer only captures movement-related energy expenditure, whereas DLW is an integrated measure. Our study offers new tools to incorporate body mass (through allometry), and changes in behavioural time budgets and intra-behaviour changes in intensity (through DBA) in acceleration-based field assessments of daily energy expenditure. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40462-023-00395-0.
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spelling pubmed-102280152023-05-31 Combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable Chakravarty, Pritish Cozzi, Gabriele Scantlebury, David Michael Ozgul, Arpat Aminian, Kamiar Mov Ecol Methodology BACKGROUND: All behaviour requires energy, and measuring energy expenditure in standard units (joules) is key to linking behaviour to ecological processes. Animal-borne accelerometers are commonly used to infer proxies of energy expenditure, termed ‘dynamic body acceleration’ (DBA). However, converting acceleration proxies (m/s(2)) to standard units (watts) involves costly in-lab respirometry measurements, and there is a lack of viable substitutes for empirical calibration relationships when these are unavailable. METHODS: We used past allometric work quantifying energy expenditure during resting and locomotion as a function of body mass to calibrate DBA. We used the resulting ‘power calibration equation’ to estimate daily energy expenditure (DEE) using two models: (1) locomotion data-based linear calibration applied to the waking period, and Kleiber’s law applied to the sleeping period (ACTIWAKE), and (2) locomotion and resting data-based linear calibration applied to the 24-h period (ACTIREST24). Since both models require locomotion speed information, we developed an algorithm to estimate speed from accelerometer, gyroscope, and behavioural annotation data. We applied these methods to estimate DEE in free-ranging meerkats (Suricata suricatta), and compared model estimates with published DEE measurements made using doubly labelled water (DLW) on the same meerkat population. RESULTS: ACTIWAKE’s DEE estimates did not differ significantly from DLW (t(19) = − 1.25; P = 0.22), while ACTIREST24’s estimates did (t(19) = − 2.38; P = 0.028). Both models underestimated DEE compared to DLW: ACTIWAKE by 14% and ACTIREST by 26%. The inter-individual spread in model estimates of DEE (s.d. 1–2% of mean) was lower than that in DLW (s.d. 33% of mean). CONCLUSIONS: We found that linear locomotion-based calibration applied to the waking period, and a ‘flat’ resting metabolic rate applied to the sleeping period can provide realistic joule estimates of DEE in terrestrial mammals. The underestimation and lower spread in model estimates compared to DLW likely arise because the accelerometer only captures movement-related energy expenditure, whereas DLW is an integrated measure. Our study offers new tools to incorporate body mass (through allometry), and changes in behavioural time budgets and intra-behaviour changes in intensity (through DBA) in acceleration-based field assessments of daily energy expenditure. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40462-023-00395-0. BioMed Central 2023-05-30 /pmc/articles/PMC10228015/ /pubmed/37254220 http://dx.doi.org/10.1186/s40462-023-00395-0 Text en © The Author(s) 2023, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Methodology
Chakravarty, Pritish
Cozzi, Gabriele
Scantlebury, David Michael
Ozgul, Arpat
Aminian, Kamiar
Combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable
title Combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable
title_full Combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable
title_fullStr Combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable
title_full_unstemmed Combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable
title_short Combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable
title_sort combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10228015/
https://www.ncbi.nlm.nih.gov/pubmed/37254220
http://dx.doi.org/10.1186/s40462-023-00395-0
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