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Heart-rate and the
energetic cost of
migration
Morgan Brown,
Willem Bouten,
Kees Camphuysen,
& Judy Shamoun-Baranes
Daily Energy
Expenditure
Productio
nActivity
Digestion
Thermo-
regulatio
n
Basal
Metabolic
Rate
Daily Energy
Expenditure
Productio
nActivity
Digestion
Thermo-
regulatio
n
Basal
Metabolic
Rate
Energy
demands by
migration
strategy
Energy
demands by
migration
strategy
Energy
demands by
migration
strategy
How do we measure
energy?
Measuring Energy: Acceleration (DBA)
• Activity costs
• Integrated into tracking devices
• Behavioural information
glidingflapping flight
Measuring Energy: Heart Rate
• Correlates with total energy
• Little behavioural information
• Responds to non-energy
related factors
• Surgical implantation
Methodology
Methodology
Methodology
Methodology
Methodology
• Breeding season:
• Acceleration: recorded every 2.5 minutes
• Heart rate: recorded every 5 minutes
• Winter settings:
• Heart Rate: every 40 minutes
How does acceleration compare to
the heart rate method?
5700: 7 june
13:00-22:00
Flapping Flight Floating
walking
Sit/Stand
Heart Rate vs DBA: Across behaviours
Heart Rate vs DBA: Across behaviours
Heart rate = 229 *DBA + 150
Heart Rate vs DBA: Within behaviours
Does DBA do a better job of predicting daily
mean heart rate than behaviour?
Heart rateFlap = 368 BPM
Heart rateManouver = 289 BPM
…
Heart rate = 229 *DBA + 150
Cost per activity predicts daily mean heart
rate as well as DBA
Cor = 0.45 Cor = 0.47
Heart Rate: Extra information or unexplained
variation?
Wind: 3 m/s
Wind: 6 m/s
Ground speed = 14 m/s
Air speed = 12.4 m/s
Heart rate = 298 BPM
DBA = 0.90 g (~ 356 BPM)
Ground speed = 10 m/s
Air speed = 15.9 m/s
Heart rate = 469 BPM
DBA = 0.93 g (~ 363 BPM)
Heart Rate: Extra information about resting
• Daily energy expenditure = Mean daily heart rate
• Resting metabolic rate = Minimum heart rate per day
• Time active = proportion of accelerometer measurements
classified as flying or walking
• Selected days with measurement covering > 75% of day
Resting contributes to DEE as much as time
active
Cor = 0.41 Cor = 0.43
Conclusions
• Heart rate and DBA are strongly correlated across behaviours,
but not within
• Heart rate could provide extra information regarding:
• Energy investment into ‘non-active’ processes
• Energy investments within an activity
Added value of Heart Rate
• What is the energetic cost of flight?
• How does the environment influence flight costs?
• How does activity (foraging, commuting, migrating) influence flight
costs?
Added value of Heart Rate
• How does migration strategy influence annual energy
expenditure?
• Does total energy expenditure change with migration distance?
• How is energy partitioned between resting and active behaviour?
• Energetic bottlenecks?
Special thanks to:
• Kees Camphuysen, Judy Shamoun-Baranes, Willem Bouten
• Roos Kentie, Suze van der Zwet, Thijs Lichtenbeld
• Gerrit Hardeman, Edwin Baaij
• David Tijssen
Heart rate changes rapidly
• Can change quickly!! Example with map, example with HR
chunk.
246 BPM
394 BPM
307 BPM
167 BPM
169 BPM
166 BPM
160 BPM
Methodology - 2018
• Pilot using captive birds to test quality of heart rate recordings
• Active (treadmill) and passive (cold challenge) calibration
Calibration Relationship
Energy (kj/gh) = 6.5e-5*Heart rateactive +
1.5e-2
Energy (kj/gh) = 2.9e-4*Heart rateresting +
1.1e-4
Energy (kj/gh) = 2.2e-2*DBA + 5.2e-2
Estimating Energy: Heart rate vs DBA
Energy estimated from heart rate (kJ/gh)
EnergyestimatedfromODBA(kJ/gh)
Heart rate in lab vs field
Walking Resting
Cost per activity predicts heart rate as well as
DBA
Marginal r2 = 0.55Marginal r2 = 0.59
Energetic cost of Migration
Flight among most costly behaviours
How do we measure energy?
• How does the acceleration method compare to the heart rate
method?
• Across behaviours?
• Within behaviours?
• How can heart rate be used to measure changes in the energy
invested into resting behavours?
Convert Acc to heart rate units
Heart rate = 229 *DBA + 150

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Heart-rate and the energetic cost of migration (Morgan Brown)

Editor's Notes

  1. Symposium on tracking – tracking a physiological characteristic, metabolic rate. MR is an individuals energy consumption over time, and it is an interesting attribute to measure because it is needed for all biological processes. Important fitness attribute as an individuals energy budget determines how much it can invest into self-maintenance and reproduction. Energy is therefore a unifying currency. Quantifying how energy is allocated/partitioned between processes of the course of the year allows us To compare different morphological, physiological or behavior features.
  2. An individual’s energy demand consists of the sum of a range of active and resting behaviours. These include their basal metabolic rate, fluctuating resting costs such as production (or growth, body repair, feather moult). digestion, thermoregulation (the energy used to maintain a constant body temperature, which increases as the environment gets colder), as well as energetic costs of activity.
  3. However, bird often spend a relatively low proportion of time in flight. As such, small changes in the energy invested into resting behaviours, such as thermoregulatory costs, could contribute substantially towards the total energy budget.
  4. How do and individuals’ energy demands change with migration strategy?
  5. Low travel, high thermos regulation?
  6. High travel, low thermoregulation?
  7. Currently there are two different techniques that could potentially be used to help predict annual energy expenditure in migratory birds. The first is acceleration, which has already been introduced today. The theory behind accelerometry is that the body must perform work inorder to accelerate. Therefore, if we sum the body acceleration along the three main axes of movement (called Dynamic Body Acceleration, or DBA), it should correlate with the energy invested into activity. The downside to this methodology is that it only addresses one portion of the daily energy budget, ignoring changes in investment into resting components of the daily energy budget. However, accelerometer as incredibly small and light weight, and can be integrated into existing tracking devices with little to no extra impact on the individual. Patterns of acceleration can also be used to determine what behaviours an individual is performing.
  8. The heart rate method, which I imagine most people are more familiar with, is more established, however has been limited by our ability to use over long periods of time. Technology has now caught up and a few different implantable, long-term heart rate monitors are now on the market. Currently these devices are more invasive as they need to be surgically implanted – this is far safer for indivdiuals over a long-term tracking study than externally attached electrodes. Heart rate has the advantage of correlating with the total energy expenditure by an individual (activity, and resting costs). On its own, however, it provides little information about how energy is distributed between active and resting behaviours, and it can be influences by non-energy related factors, such as stress.
  9. Separate system so don’t perfectly sync!
  10. How does HR compare to ACC? - Strong correlation between heart rate and ODBA. - Reasonably stable within prolonged activity
  11. How does HR compare to ACC? - Strong correlation between heart rate and ODBA. - Reasonably stable within prolonged activity
  12. How does HR compare to ACC? Greater range in HR than ODBA Soaring vs walking similar Floating vs Standing -
  13. How does HR compare to ACC? Greater range in HR than ODBA Soaring vs walking similar Floating vs Standing -
  14. How does HR compare to ACC?
  15. How does HR compare to ACC? How well can we predict daily mean heart rate from 1. ODBA and 2. mean heart rate per activity
  16. How does HR compare to ACC? ODBA perfroms similarly to using a mean value per activity. So time budget approach (if we have a good idea of activity costs) is just as good as ODBA. The caveat of this is it assumes heart rate is truth.
  17. How does HR compare to ACC? Greater range in HR than ODBA -
  18. Heart rate changes with airspeed, ODBA doesn’t
  19. Both minimum heart rate and proportion of time active contribute toward daily energy budget. These is even during the breeding season when resting costs should we relatively stable! This will become increasingly important over longer time spans when there will be more fluctuation in thermoregulation and production costs. -Could also explain why HR ranges more than ODBA within behaviours.
  20. most studies that have attempted to relate environmental variables to FMR have been unable to establish a clear relationship -’extra noise’ can also be useful e.g. is resting in the colony more stressful than resting on the beach/floating on water?
  21. Thank you all for listening, if you have any feedback or advise on my PhD proposal I would love to talk about it, as I said it is still very much in its formative stages. Likewise I’d be happy to answer any questions you might have about my work with the blackpoll warblers and motus.
  22. Heart rate changes very quickly!! - High potential for fine-scale changes, if acceleration and heart rate can be well synchronized.
  23. Heart rate predicts energy ~ 50% lower than ODBA
  24. Heart rate in field is lower than in the lab – stress effect?