Novel application of CO2 sensor technology for breath-by-breath assessment of stress and energetics in unrestrained free-living animals
Novel application of CO2 sensor technology for breath-by-breath assessment of stress and energetics in unrestrained free-living animals
批准号:
NE/X013308/1
负责人:
Kayleigh Ann Rose
金额:
$10.17万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
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英文摘要
How animals manage their time and energy has implications for their reproductive success and, therefore, evolution. Measuring animal stress and energy costs specific to different behaviours and in relation to the environment is, therefore, important to be able to predict how animals will respond to human-induced disturbance and environmental change. However, methods available to do this each come with ethical issues and technical drawbacks.In standard respirometry (measuring O2 consumption and/or CO2 production), animals are confined to chambers or fitted with a mask which can limit expression of movement behaviour as it would be in the wild. In the field, loggers can be either attached to, or implanted in, animals to measure variables that correlate with metabolic rate, such as heart rate or dynamic body acceleration (first needing calibration with respirometry in the lab). Another field option is to inject isotopes into the blood of animals and later sample blood to quantify CO2 production. Stress levels can also be assessed by sampling blood for hormone analysis. All of these field methods require animal capture (and often recapture), known to cause a stress response, and some are invasive. Temporal resolution is low for the isotope method, and while it is high for acceleration, acceleration is due to movement, and cannot account for periods when animals are still and therefore basal costs, or the costs of thermoregulation, incubation or stress. Technology for measuring CO2 concentration has advanced incredibly, with non-dispersive infrared CO2 spectroscopy (NoDIS) sensors now able to resolve concentrations as 0.1 ppm and record at high frequency (e.g., 20 Hz). In our recent proof-of-concept work for 'wake respirometry' in wind tunnels, we demonstrated that it is possible to monitor animal stress and ventilation rates by positioning an open path NoDIS (Li7500 from LICOR https://www.licor.com/env/products/eddy_covariance/LI-7500DS) downwind of animals. The wake of exhaled CO2, or plume, over time, gives a signal response of peaks, providing breath-by-breath resolution. We demonstrated that rapid responses to stressors and recovery from exercise in birds could be measured, and that, in theory, this could be developed to calculate metabolic rate by integrating the full CO2 wake.Our principal aim is of this research is to take the high temporal resolution of wake respirometry to the field and explore the potential to quantity stress and energetics of free living animals that are stationary, e.g., incubating, hibernating, roosting, basking. If this works, many doors will be opened to investigate metabolic rhythms of animals and any factors that change those rhythms e.g., anthropogenic disturbance, urbanisation, ecotourism, resource availability, temperature (with links to global warming) and even disease (e.g., white noise syndrome in bats).Our specific objectives are to: 1) conduct gas simulation experiments to optimise field set up conditions for breath-by-breath resolution in nest boxes. 2) Under optimised nest box set up conditions, trial the method for measuring ventilation and metabolic rates of captive pigeons and measure their responses to a perceived threat and novel object. 3) Take the method to field to quantify stress and energetics in incubating barn owls Tyto alba in relation to livestock proximity (known to cause stress), noise, light and temperature. 4) Trial measuring metabolic rates in open air using dogs of different body size and the eddy covariance technique to measure CO2 flux and metabolic rate. This will involve using a LiCOR sonic anemometer and smart flux system to combine wind speed and direction data with CO2 data.
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