Literature DB >> 27264988

Measurement of flying and diving metabolic rate in wild animals: Review and recommendations.

Kyle H Elliott1.   

Abstract

Animals' abilities to fly long distances and dive to profound depths fascinate earthbound researchers. Due to the difficulty of making direct measurements during flying and diving, many researchers resort to modeling so as to estimate metabolic rate during each of those activities in the wild, but those models can be inaccurate. Fortunately, the miniaturization, customization and commercialization of biologgers has allowed researchers to increasingly follow animals on their journeys, unravel some of their mysteries and test the accuracy of biomechanical models. I provide a review of the measurement of flying and diving metabolic rate in the wild, paying particular attention to mass loss, doubly-labelled water, heart rate and accelerometry. Biologgers can impact animal behavior and influence the very measurements they are designed to make, and I provide seven guidelines for the ethical use of biologgers. If biologgers are properly applied, quantification of metabolic rate across a range of species could produce robust allometric relationships that could then be generally applied. As measuring flying and diving metabolic rate in captivity is difficult, and often not directly translatable to field conditions, I suggest that applying multiple techniques in the field to reinforce one another may be a viable alternative. The coupling of multi-sensor biologgers with biomechanical modeling promises to improve precision in the measurement of flying and diving metabolic rate in wild animals.
Copyright © 2016 Elsevier Inc. All rights reserved.

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Year:  2016        PMID: 27264988     DOI: 10.1016/j.cbpa.2016.05.025

Source DB:  PubMed          Journal:  Comp Biochem Physiol A Mol Integr Physiol        ISSN: 1095-6433            Impact factor:   2.320


  9 in total

1.  The current use of wearable sensors to enhance safety and performance in breath-hold diving: A systematic review.

Authors:  Giovanni Vinetti; Nicola F Lopomo; Anna Taboni; Nazzareno Fagoni; Guido Ferretti
Journal:  Diving Hyperb Med       Date:  2020-03-31       Impact factor: 0.887

2.  How animals distribute themselves in space: variable energy landscapes.

Authors:  Juan F Masello; Akiko Kato; Julia Sommerfeld; Thomas Mattern; Petra Quillfeldt
Journal:  Front Zool       Date:  2017-07-05       Impact factor: 3.172

3.  Validating accelerometry estimates of energy expenditure across behaviours using heart rate data in a free-living seabird.

Authors:  Olivia Hicks; Sarah Burthe; Francis Daunt; Adam Butler; Charles Bishop; Jonathan A Green
Journal:  J Exp Biol       Date:  2017-03-03       Impact factor: 3.312

4.  The energetic cost of parasitism in a wild population.

Authors:  Olivia Hicks; Sarah J Burthe; Francis Daunt; Mark Newell; Adam Butler; Motohiro Ito; Katsufumi Sato; Jonathan A Green
Journal:  Proc Biol Sci       Date:  2018-05-30       Impact factor: 5.349

5.  Cyclic bouts of extreme bradycardia counteract the high metabolism of frugivorous bats.

Authors:  M Teague O'Mara; Martin Wikelski; Christian C Voigt; Andries Ter Maat; Henry S Pollock; Gary Burness; Lanna M Desantis; Dina Kn Dechmann
Journal:  Elife       Date:  2017-09-19       Impact factor: 8.140

6.  Effects of age, sex, and ENSO phase on foraging and flight performance in Nazca boobies.

Authors:  Jennifer L Howard; Emily M Tompkins; David J Anderson
Journal:  Ecol Evol       Date:  2021-03-10       Impact factor: 2.912

7.  Acceleration predicts energy expenditure in a fat, flightless, diving bird.

Authors:  Olivia Hicks; Akiko Kato; Frederic Angelier; Danuta M Wisniewska; Catherine Hambly; John R Speakman; Coline Marciau; Yan Ropert-Coudert
Journal:  Sci Rep       Date:  2020-12-09       Impact factor: 4.379

8.  Vocalization-associated respiration patterns: thermography-based monitoring and detection of preparation for calling.

Authors:  Vlad Demartsev; Marta B Manser; Glenn J Tattersall
Journal:  J Exp Biol       Date:  2022-03-10       Impact factor: 3.312

9.  Ecological inference using data from accelerometers needs careful protocols.

Authors:  Baptiste Garde; Rory P Wilson; Adam Fell; Nik Cole; Vikash Tatayah; Mark D Holton; Kayleigh A R Rose; Richard S Metcalfe; Hermina Robotka; Martin Wikelski; Fred Tremblay; Shannon Whelan; Kyle H Elliott; Emily L C Shepard
Journal:  Methods Ecol Evol       Date:  2022-02-07       Impact factor: 8.335

  9 in total

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