Do surface temperatures measure core temperature? No.

Working from home during the COVID19 pandemic has proven a challenge for many of us. Our students are not allowed to pursue their research, and yet most of us are working as hard from home as we would be on campus.

Anyhow, at the beginning of the lockdown, I gathered what equipment I could from the lab and set up to research at home. Hardly a serious pursuit, but I was designing some training material for an overseas student and needed the equipment at home anyway.

What kind of research can you do on yourself on lockdown you might ask? A little bit of thermal imaging!

Since COVID19 is/was on everyone’s mind, I knew it was only a matter of time before the fever scanning would start up again (remembering SARS 2003 and all the thermal cameras in airports).

But thermoregulatory physiologists know that surface temperature rarely, if ever, is equal to core temperature so then, how do we reconcile this with the return to use of superficial fever scanning?

Maybe it is because imaging is appealing to people and it is compelling that a region of the face or head close to the eye always appears warm, so naturally people assume it might represent or correlate to core measurements of body temperature. Indeed, even in animal thermal biology, this is one of more common questions people ask me: “Can eye temperature be an estimate of core temperature?”. To which I quip, “No”, with caveats.

I am not aware of systematic studies demonstrating that these warm eye/head surface temperatures are really good at estimating core temperature, but we previously measured core and surface temperatures in a previous study of ours in ducklings across different times of day and during a period of fasting:

Duckling thermal images – captures at two air temperatures and under different conditions.

Core temperature rises and falls quite substantially (ranging from ~39 to ~42C) across these different states and time periods:

Core (crop) temperature in ducklings measured over a course of 12 days, including a fasting period between days 5-8.

But the correlation between core temperature and the maximum eye region temperature is not that great. Indeed, you would expect the values to fall along or at least be parallel to the dotted line of equality below, but in the case of low air temperatures, the relationship is quite poor and the surface temperatures are much cooler than core.

Maximum eye region temperature correlates with core temperature, but not very strongly and is quite heavily dependent on surrounding air temperature.

So, it is easy to conclude that max eye temperature is not always a reliable indicator of core temperature in these ducks. Maybe we could derive an empirical calibration curve, taking into account air temperature, but the point is that this requires accurate temperature data and stable environmental conditions rarely present in the field.

So, what about the lockdown research mentioned earlier?

Having plenty of time to myself, I set up a thermal camera to capture a thermal image of my face at various times throughout the day to capture the natural variation in body temperature (no fever, per se, but my daily oral temperature measurements range from 35.6 to 36.9C). Here is a sample image, outlining the typical regions of skin surface measured:

Red arrow (inner canthus of the eye, typical hottest part of the face, ~35.2C here). Blue arrow (tongue, equivalent to measurement with oral thermomemeter, ~36.7C here). Green question mark (forehead, location of scanners seen on a lot of websites, ~32.4C here).

It got too scary the longer I was in lockdown as my hair grew too long and disheveled, so I ceased the experiment after only a short period.

But the results (next 3 graphs) below show how poorly forehead assesses normal oral temperature, and even how maximum eye temperature is ~1C cooler than oral temperature and influenced by nearby ambient conditions (my garage was cold back in April so I set up there for a few measurements).

Conclusions: Ignoring the N=1 subject (due to the pandemic this seems justified), forehead is a poor measure of oral temperature (3.85C too low), maximum eye temperature a bit better (but still 1C too low and affected by air temperature), while simply pointing the camera in your mouth and getting maximum temperature yields a temperature ~0.5C higher than an oral thermometer.

So, why if you look at any images of companies and airports doing fever scanning they point devices at people’s foreheads or relying on a single pixel value from possibly the eye region?

The simple answer is that it is easy to do, but from a target accuracy perspective, it is terrible, especially if low accuracy devices are being employed inappropriately. In the one image above, the device is pointing at someone’s hair, which shields the skin and thus produces a cooler value. Cooler values will not trigger a fever detection even if it is there!

So, wherefore is the future of fever scanning? Intuitively, it seems it should work, but are we measuring the wrong thing? Why don’t we measure inside the mouth where normal oral thermometers do? At least this is better than crappy forehead measurements. Is this a privacy issue? Is it feasible to do in rapid scanning processes? Will it be feasible if we are all wearing masks?

I am not the first to write on this. This blog project was mostly a distraction in the early days of lockdown to keep my mind off the situation. I attach a few key articles and opinion pieces on the subject below that have commented more clearly on the connection (or lack) between fever and infection and why fever screening is not a panacea.

Links to further reading:

Scientific studies demonstrating reasonable predictive power for fever scanning:

Other articles discussing why using fever scanning does not equate to infection and misses asymptomatic cases of COVID19:

WHO Recommendations on temperature screening:

Idea for a Review Paper Anyone?

I think this situation really needs another look by the physiology community. My anecdote here is simply based on self reflection/measurement but also based on years of experience with thermal imaging.

The first rule of thermal imaging in biological systems: “Surface Temperature is not equal to Core Temperature.” We can’t forget that. If you want to use surface temperature, you have to do a lot of calibration checks or have very good control over your subject.

In case a grad student locked down at home wants a writing project, here are a few key points that I know should impact the predictive power of max surface temperature measurements in the context of rapid fever scanning in public places:

  • Air temperature near skin
  • Air flow (convective heat exchange) over skin
  • Blood flow relationship with the skin surface
  • Camera user skills and training
  • Quality and accuracy of the thermal scanner (some scanners I see people using have accuracies of +-2 to 4C).
  • Pre-symptomatic people lack fever
  • Masking of fever with antipyretic drugs undetected by scanning
  • What is the precise correspondence of eye canthus temperature with core temperature measurement?

Congratulations Anne Yagi, MSc!

Anne successfully defended her MSc research on “Flood Survival Strategies in Neonatal Snakes”. Congratulations!

Anne’s MSc research represents an amazing amount of research into overwintering snake behaviour and physiology, and what is in her thesis is still only a fraction of the research she has pursued while a Masters student in my lab!

Some highlights from her (online) defence:

With a teary eye for the closing of this particular chapter in our collaboration (as student and advisor), I am very proud for her achievement. I still expect many more years of conversations and collaborations!

We owe a lot of gratitude to many people, including the Yagi family, for their support of Anne while she pursued her MSc as full-time employee and for their help with data extraction from behaviour videos. Katharine Yagi in particular needs acknowledgement for her herculean efforts with statistical analyses and patiently working with us!

Thank you for the examining committee:

Dr. Cheryl McCormick, Chair (and microphone manager)
Dr. Bruce Kingsbury (external examiner)
Dr. Liette Vasseur (committee member)
Dr. Fiona Hunter (committee member)

Video based quantification of activity

Although not an inspiring or catchy title, our study has just been published, demonstrating that fixed-frame video capture can provide a quantitative assessment of energetics (citation below).

Summary of the study

Infrared thermal imaging is a passive imaging technique that captures the emitted radiation from an object to estimate surface temperature, often for inference of heat transfer.

Infrared thermal imaging offers the potential to detect movement without the challenges of glare, shadows, or changes in lighting associated with visual digital imaging or active infrared imaging.

In this paper, we employ a frame subtraction algorithm for extracting the pixel-by-pixel relative change in signal from a fixed focus video file, tailored for use with thermal imaging videos.  

A greyscale video of a metronome. Inanimate objects are still visible to the thermal camera due to slight differences in thermal equilibration, emissivity, and reflectivity across the different surfaces.
Same video as above, but as an “absolute difference image”, where each frame is subtracted from the previous frame and positized (i.e. the absolute value taken for each pixel difference). During zero motion, the image space is black with low variability based on sensor noise (sd number in upper left). After motion starts (~0:11), you clearly see the moving metronome as each frame difference depicts how pixels in a fixed frame differ.

By then cumulatively summing the sd for each frame across an entire video, we are able to assign quantitative activity assessments to thermal imaging data for comparison with simultaneous recordings of metabolic rates. We tested the accuracy and limits of this approach by analyzing movement of a metronome (see above) and provide an example of the approach to a study of Darwin’s finches.

Fixed frame Different Image Thermography video of a bird filmed over a long period of time within a viewing chamber. The cumulative difference image provides a slope value that corresponds to an indication of movement. Scale is relative to the degree of motion.

Simultaneous measurements of oxygen consumption (dark black lines) match up well with smoothed estimates (blue lines) of the activity score (grey lines) derived from the difference image thermography videos. Resolving fast respirometry data is difficult and best left to the experts at Sable Systems, but the average trends are informative for energy expenditure.
Correlations between 5 minute average oxygen consumption measurements and the activity values line up well at the individual level.

In principle, this “Difference Imaging Thermography” (DIT) would allow for activity data to be standardized to energetic measurements and could be applied to any radiometric imaging system.


Fixed frame is required. Changing the reference frame or using a camera without a tripod would not work unless you do a lot of motion correction. Also, we used infrared thermal imaging because we were collecting data for a different purpose (still writing those up!), but we think that any sort of imaging should work, provided it produces a simple, ratiometric or radiometric image. Usually monochrome cameras or near infrared cameras produce a signal that is a simple greyscale image. Reflected light might interfere with the approach, so this is why we argued this might be an addition use of thermal imaging videos.

Behind the scenes

This paper took a long time to put together, but was the beginning of my lab’s journey into R, ImageJ, and open source coding. A lot has changed since I started the data analysis. Combing through 500 Gb of video files, extracting, processing, converting them into something manageable took the better part of 2 weeks on a supercomputer, until I realised that there were more efficient routes!

We have since created routines in ImageJ that help facilitate the conversions and have placed those routines in a github repository, where we will write them up as a methods paper in the future. The principles outlined in the paper are not themselves novel. Sliding average and frame subtraction routines are common in video processing software. Assessing whether the motion captured is correlated with meaningful biological information is what we hoped to capture with the study.


Tattersall, GJ, Danner, RM, Chaves, JA, and Levesque, DL. 2020. Activity analysis of thermal imaging videos using a difference imaging approach. Journal of Thermal Biology.  91 102611

Link to the full text here (first 50 clicks can access the paper).

Congratulations, Nick Sakich, MSc!

In a first for the lab, we just held a completely online MSc defence. Valiantly, Nick defended his MSc with grace, precision, insight, humour, and interesting anecdotes.

His thesis is entitled: “The Physiological and Behavioural Consequences of Reduced Scalation in Captive-bred Phenotypes of the Bearded Dragon (Pogona vitticeps Ahl 1926)“.

Here he is giving his presentation (sorry for the screen cap, Nick)

speaking about one of our favourite study animals:

The 3 phenotypes of captive-bred Pogona vitticeps studied in Nick’s thesis. a) wildtype, b) leatherback, and c) silkback.

Many thanks to the examining committee:

External Examiner, Dr. Chris Oufiero, Towson University
Chair, Dr. Cheryl McCormick
Committee Member, Dr. Jeff Stuart
Committee Member, Dr. Robert Carlone
Supervisor, Dr. Glenn Tattersall

Virtual congratulations to Nick are insufficient expression of gratitude for his hard work and devotion to his research. When and if we can safely congregate in small groups, we will celebrate appropriately! I really owe Nick my thanks for joining my lab. He has helped educate me through his efforts. It cannot be fun wrapping up one’s MSc during a pandemic, and Nick did a brilliant job.

A few highlights from Nick’s presentation below.

Thanks as well to A&A Dragons for their support over the years.

Massassauga Rattlesnake Overwintering Lifezone

Congratulations to lab member, Anne Yagi on publishing a life’s work of research on the overwintering lifezone of the Eastern Massassauga rattlesnake! The final proofs have been sent back to the publisher and we are anxiously awaiting it to make it to press:

Summary of the study here, with links to the paper below.

Temperate snakes occupy overwintering sites for most of their annual life cycle. Microhabitat characteristics of the hibernaculum are largely undescribed yet are paramount in ensuring snake overwintering survival.

We hypothesized that snakes survive hibernation within a vertical subterranean space that we termed a “life zone”, that is aerobic, flood, and frost-free throughout winter and did this by studying an isolated, endangered population of Massasaugas (Sistrurus catenatus) inhabiting an anthropogenically-altered peatland and monitored the subterranean habitat during a period of environmental stochasticity.

Lifezone concept (Credit: A Yagi)

Initial radio telemetry confirmed that snakes moved between altered and natural habitats during the active season and showed hibernation site fidelity to either habitat. We used a grid of groundwater wells, and frost tubes installed in each hibernation area to measure lifezone characteristics over 11 consecutive winters.

The lifezone within the impacted area was periodically reduced to zero during a flood-freeze cycle, while the lifezone in the natural area was maintained.

Sample figure from the paper showing year by year changes in the winter lifezone size (cm = depth or size underground that remains frost and flood free). Mined sites refer to an anthropogenically disturbed site where surface peat extraction had historically occurred. Unmined site is a peat bog. Flood events refer to a period of time when large regions of the site experienced sustained surface flooding.

Soil-depth and flood status best predicted lifezone size. Thermal buffering and groundwater dissolved oxygen increased with lifezone size, and annual Massasauga encounters were significantly correlated with lifezone size.

This analysis suggests a population decline occurred when lifezone size was reduced by flooding. Our data give support to the importance and maintenance of a lifezone for successful snake hibernation.

Our methods apply to subterranean hibernation habitats that are at risk of environmental stochasticity, causing flooding, freezing, or hypoxia, and speak to the issues regarding management of sensitive watersheds inhabitated by species-at-risk.

Snake well installation in the field to test the overwintering lifezone.


Yagi, A, Planck, RJ, Yagi, KT, and Tattersall GJ. 2020. A long-term study on Massasaugas (Sistrurus catenatus) inhabiting a partially-mined peatland: presenting a standardized method to characterize snake overwintering habitat. Journal of Herpetology. 54: 235-244.

For further information, please see

Avian Thermal Biology Visitor

The lab will be hosting a PhD student from Spain for the next 3 months.

Núria Playà Montmany from the University of Extremadura has just arrived (I’m a few days late, she arrived in late January!). I met Núria last summer defending her poster at the SEB meeting in Sevilla. She will be becoming a thermal imaging expert while she is here!

With overlapping interests in avian physiology and the lab’s interests in thermal biology and studying animal responses to climate change, we hope to have a productive visit. Here is a link to Núria’s blog:

Welcome to the lab, Núria! Let’s hope you have a good few months working with us.

Visitor to the Lab

It has been a busy January, and so my updates are out of date! From Jan 10th to the 24th, I hosted Dr. Agnes Jullian Vinet in the lab, mostly to learn thermal imaging for future human thermogenesis research.

Dr. Vinet was a welcome visitor, enduring the dark, but not so cold, Canadian winter with us! Thanks to Stephen Cheung’s lab, Gary Hodges and Leed McNab for helping to host Agnes.

Hopefully we can return the favour and visit her lab next summer!

Problems with assumptions in macroecology

Thanks to some very kind and smart colleagues, we have an editorial published in Ecology and Evolution!

Here is the citation:

Justin G. Boyles, Danielle L. Levesque, Julia Nowack, Michał S. Wojciechowski, Clare Stawski, Andrea Fuller, Ben Smit, and Glenn J. Tattersall 2019. An oversimplification of physiological principles leads to flawed macroecological analyses.

Take home message? Few endotherms are homeothermic, so they do not conform to assumptions of the Scholander-Irving model. Taking predictions from the SI model based on a broad range of lab studies can lead to huge errors in predictions. A re-assessment of macroecological predictions using this approach is warranted.

Demonstration of the inherent limitations of using body temperature (Tb) and the lower critical temperature (Tlc) of the thermal neutral zone to calculate thermal conductance (C) when Tb and Tlc are poorly defined.

Congratulations Anne Yagi!

Congratulations to Anne Yagi for her Blue Racer Award from the Canadian Herpetological Society. The Blue Racer award is presented to an individual in recognition of cumulative contributions to the conservation of amphibians and reptiles in Canada. 

For full details on the announcement: