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Wake respirometry allows breath-by-breath assessment of ventilation and CO2 production in unrestrained animals
,
Rory Wilson ,
Claudia Ramenda,
Hermina Robotka,
Martin Wikelski,
Emily Shepard
iScience, Volume: 25, Issue: 9, Start page: 104878
Swansea University Authors:
Kayleigh Rose , Rory Wilson , Emily Shepard
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Copyright: 2022 The Authors. This is an open access article under the CC BY license
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DOI (Published version): 10.1016/j.isci.2022.104878
Abstract
Quantifying stress and energetic responses in animals are major challenges, as existing methods lack temporal resolution and elevate animal stress. We propose‘‘wake respirometry,’’ a new method of quantifying fine-scale changes in CO2 production in unrestrained animals, using a nondispersive infrare...
| Published in: | iScience |
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| ISSN: | 2589-0042 |
| Published: |
Elsevier BV
2022
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa60973 |
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| Abstract: |
Quantifying stress and energetic responses in animals are major challenges, as existing methods lack temporal resolution and elevate animal stress. We propose‘‘wake respirometry,’’ a new method of quantifying fine-scale changes in CO2 production in unrestrained animals, using a nondispersive infrared CO2 sensor positioned downwind of the animal, i.e., in its wake. We parameterize the dispersionof CO2 in wakes using known CO2 flow rates and wind speeds. Tests with threebird species in a wind tunnel demonstrated that the system can resolve breathby-breath changes in CO2 concentration, with clear exhalation signaturesincreasing in period and integral with body size. Changes in physiological statewere detectable following handling, flight, and exposure to a perceived threat.We discuss the potential of wake respirometry to quantify stress and respiratorypatterns in wild animals and provide suggestions for estimating behavior-specificmetabolic rates via full integration of CO2 production across the wake. |
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| Keywords: |
Wildlife behavior, Physiology, Animal physiology, Methodology in biological sciences |
| College: |
Faculty of Science and Engineering |
| Funders: |
This work was supported by the European Research Council under the European Union’s Horizon 2020 research and innovation program (starting grant 715874 to ELCS) and a Max Planck Sabbatical Fellowship (to ELCS). |
| Issue: |
9 |
| Start Page: |
104878 |