# Cold adaptation does not handicap warm tolerance in the most abundant Arctic seabird

Julian Beaman, Craig White, Manon Clairbaux, Samuel Perret, Jérôme Fort, David Grémillet

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Julian Beaman, Craig White, Manon Clairbaux, Samuel Perret, Jérôme Fort, et al. Cold adaptation does not handicap warm tolerance in the most abundant Arctic seabird. Proceedings of the Royal Society B: Biological Sciences, 2024, 291 (2015), pp.20231887. 10.1098/rspb.2023.1887. hal-04410500

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**Cite this article:** Beaman JE, White CR, Clairbaux M, Perret S, Fort J, Grémillet D. 2024 Cold adaptation does not handicap warm tolerance in the most abundant Arctic seabird. *Proc. R. Soc. B* **291**: 20231887.

https://doi.org/10.1098/rspb.2023.1887

Received: 22 August 2023

Accepted: 8 December 2023

**Subject Category:**

Global change and conservation

**Subject Areas:**

ecology, physiology, evolution

**Keywords:**

Animal energetics, dovekie, ecophysiology,
evolutionary legacy, global warming,
phylogenic analyses

**Authors for correspondence:**

Julian E. Beaman

e-mail: julian.beaman@flinders.edu.au

David Grémillet

e-mail: david.gremillet@cefe.cnrs.fr

Cold adaptation does not handicap
warm tolerance in the most abundant
Arctic seabird

Julian E. Beaman<fnref n="1" />,<fnref n="2" />, Craig R. White<fnref n="1" />, Manon Clairbaux<fnref n="3" />,<fnref n="4" />,<fnref n="5" />, Samuel Perret<fnref n="3" />, Jérôme Fort<fnref n="6" /> and David Grémillet<fnref n="3" />,<fnref n="7" />

<figure><img src="image_4.png" /></figure>

JEB, 0000-0002-1618-5308; CRW, 0000-0002-0200-2187

Arctic birds and mammals are physiologically adapted to survive in cold environments but live in the fastest warming region on the planet. They should therefore be most threatened by climate change. We fitted a phylogenetic model of upper critical temperature (*T*<sub>LIC</sub>) in 255 bird species and determined that *T*<sub>LIC</sub> for dovekies (*Alle alle*; 22.4°C)—the most abundant seabird in the Arctic—is 8.8°C lower than predicted for a bird of its body mass (150 g) and habitat latitude. We combined our comparative analysis with *in situ* physiological measurements on 36 dovekies from East Greenland and forward-projections of dovekie energy and water expenditure under different climate scenarios. Based on our analyses, we demonstrate that cold adaptation in this small Arctic seabird does not handicap acute tolerance to air temperatures up to at least 15°C above their current maximum. We predict that climate warming will reduce the energetic costs of thermoregulation for dovekies, but their capacity to cope with rising temperatures will be constrained by water intake and salt balance. Dovekies evolved 15 million years ago, and their thermoregulatory physiology might also reflect adaptation to a wide range of palaeoclimates, both substantially warmer and colder than the present day.

1. Introduction

The Arctic is now warming three times as fast as the rest of the planet [1]. Yet, birds and mammals that live and breed in the Arctic exhibit physiological and morphological adaptation to survive low air and water temperatures [2,3]. Cold adaptation in endothermic animals involves mechanisms that increase heat production and reduce heat loss, which together maintain a high and stable body temperature against a strong thermal gradient [4]. According to the current paradigm, cold-adapted endotherms have limited tolerance to even moderately warming air temperatures [5,6]. Specifically, when air temperature exceeds the upper critical temperature of the thermoneutral zone, evaporative water loss must increase to dissipate excess body heat [7]. At the same time, metabolic heat production also increases as more active forms of evaporative water loss are employed to dissipate heat (e.g. gular fluttering) [8]. When air temperatures remain elevated above thermoneutrality, the cycle of increased water loss and increased heat production can lead to dehydration and hyperthermia. If this

© 2024 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution
License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original
author and source are credited.

<footnote n="1">¹Centre for Geometric Biology, School of Biological Sciences, Monash University, Melbourne, Clayton, Victoria, Australia</footnote>

<footnote n="2">²Global Ecology, College of Science & Engineering, Flinders University, Adelaide, Australia</footnote>

<footnote n="3">³CEFE, Univ Montpellier, CNRS, EPHE, IRD, Montpellier, France</footnote>

<footnote n="4">⁴School of Biological, Environmental and Earth Sciences, University College Cork, Cork T23 N73K, Ireland</footnote>

<footnote n="5">⁵MaREI Centre for Energy, Climate and Marine, Environmental Research Institute, University College Cork, Cork P43 C573, Ireland</footnote>

<footnote n="6">⁶Littoral, Environnement et Sociétés, LIENSs, UMR 7266 CNRS-La Rochelle University, La Rochelle, France</footnote>

<footnote n="7">⁷FitzPatrick Institute of African Ornithology, Department of Biological Sciences, University of Cape Town, Rondebosch, South Africa</footnote>
current paradigm is accurate and Arctic endotherms have
limited tolerance to elevated temperatures, the physiological
costs of thermoregulation could render the Arctic region too
warm by the end of the century for many endemic species.

To explore how climate warming will affect Arctic endotherms, we studied the thermal physiology and bioenergetics of the dovekie (or little auk, *Alle alle*), the smallest (150 g) diving seabird in the North Atlantic, and most abundant Arctic seabird (40–80 million individuals, [9]), that plays a pivotal role in marine and terrestrial trophic flows [10]. We focused on the summer season, while dovekies are breeding in the high Arctic. During this phase, adults spend 54% of their time on land in underground nest cavities or perched on rocks at the surface of the colony, and 46% engaged in foraging trips at sea within *ca* 100 km from their nests, diving to catch zooplankton within the first 20 m of the water column [11,12]. The breeding season is the most energetically demanding period for dovekies [12,13].

Here, we combined physiological measurements with
modelling and phylogenetic analysis to assess whether
dovekies will be physiologically challenged by future pro-
jected climate scenarios in the Arctic. Dovekies live and
breed in cold conditions, with air temperatures frequently
around 0°C at summer breeding grounds, and as low as
-10.6°C during inter-breeding (winter) migration in the
North Atlantic [13]. The only other study to experimentally
examine the thermal physiology of dovekies [14] exposed
birds to air temperatures from -20°C up to a maximum of
20°C, which has since remained the only data from which to
estimate the upper critical temperature for the species [15].
Based on the idea that dovekies are putatively cold adapted,
combined with limited previous information on their physio-
logical tolerance at warmer temperatures, we expected that
dovekies would be poorly equipped to avoid overheating
when air temperatures exceed 20°C; a temperature regularly
overshot in summer at the breeding colony we studied in
East Greenland (D Grémillet et al. 2019, unpublished).

2. Methods

(a) Phylogenetic modelling

We fitted phylogenetic mixed models to existing data [15] for
upper critical temperature (T<sub>UC</sub>) in 255 bird species. We added
to the data one estimate for T<sub>UC</sub> for Wilson's storm petrel
(Oceanites oceanicus) based on data from the literature [16]. We
also updated the T<sub>UC</sub> for dovekies with the observation in the
present study, since the existing estimate was based on a single
previous study that had too few measurements above 20°C to
reliably estimate the inflection point at the T<sub>UC</sub> ([14]; see below
for a description of how we accounted for methodological differ-
ences in estimates of T<sub>UC</sub>). We used the consensus tree for bird
species [17] with Grafen's arbitrary branch lengths [18] to fit
phylogenetic least-squares models to the data for T<sub>UC</sub> using the
phytools package [19] in R version 4.1.2 [20]. In addition to
the random phylogenetic structure, we fitted fixed effects of
log mass and latitude. We also included information on potential
sources of variation in T<sub>UC</sub> estimates due to differences in meth-
odology among studies [21]. Specifically, different studies
estimated T<sub>UC</sub> from respirometric data obtained across different
temperature ranges, which potentially influences the precision
of estimates of T<sub>UC</sub>. To account for this potential source of
error in T<sub>UC</sub>, we used the 'data quality' categories proposed by
McKechnie et al. [21] in their examination of the primary data

from the Khaliq et al. [15] dataset. Their categories were 'Good'
(i.e. an increase in metabolic rate above thermoneutrality with
a clear inflection point defining T<sub>UC</sub>), 'Insufficient data'
(i.e. some evidence of an increase in metabolic rate above
thermoneutrality, but based on measurements at too few air
temperatures to reliably estimate T<sub>UC</sub>), 'No T<sub>UC</sub>' (i.e. no break-
point in the data, T<sub>UC</sub> taken as highest measurement
temperature), or '—' (i.e. not able to assess the data). Note
that McKechnie et al. categorized the previous estimate for
dovekies [14] as 'Good', but based on their description of the cat-
egories, we thought that it was best defined as 'Insufficient data'
due to there being too few measurements above the potential
inflection point to reliably estimate T<sub>UC</sub>. We left all other categor-
izations as they appear in McKechnie et al. [21]. We included
'data quality' (which we called 'methodology') as a fixed
factor (with the four levels described above) in our models.
Methodology explained 2.8% of the variance in T<sub>UC</sub> and the stan-
dardized effect sizes (Cohen's d) for each methodology category
varied between 0.03 and 0.07. In other words, differences in
methodology had little to negligible influence on the variance
in T<sub>UC</sub> relative to that associated with latitude and log mass.

(b) Physiological measurements

We performed respirometry on individual dovekies (*Alle alle*, *n* = 36) captured from a breeding colony at Ukaleqarteq, East Greenland (70° 43' N, 21° 33 W) between 11 July and 8 August 2019 (during the late incubation and chick-rearing period). On each day of measurement, four breeding birds (as indicated by the presence of a brood patch) were captured between 08.00 and 12.30 GMT and mass and morphometrics were recorded at time of capture. Each bird was then kept in a cotton bag in a quiet location for 2 to 3 h before being placed inside a 5 l plastic respirometry chamber and placed inside a temperature-controlled box. The temperature-controlled box was made from an insulated icebox fitted with a peltier-thermoelectric air cooler (TE Technology, model AC-027, Traverse City, MI, USA) and temperature controller (TE Technology, model TC-48-20, Traverse City, MI, USA). The temperature-controlled box provided a completely dark space in which to estimate resting metabolic rate and water loss rate in the dovekies exposed to a range of air temperatures. Measurements were completed between approximately 16.00 and 04.00 each day, which corresponds with the period of lowest activity on the colony from which the birds were collected.

The resting metabolic rate and water loss rate of each bird was estimated from the rate of carbon dioxide production (V̇CO₂, ml CO₂ h⁻¹) and rate of water vapour production (V̇H₂O, ml H₂O h⁻¹), respectively, during open-flow respirometry. Air was drawn from the outside air at the field lab using volumetric flow-controlled pumps (Sensidyne, model Gilian Gilair-5, St. Petersburg, FL, USA) at a flow rate set to 4.5 l min⁻¹ and calibrated with a wet-cell air flow calibrator (Sensidyne, Gilibrator-2, St. Petersburg, FL, USA). From the flow-controlled pump, air was delivered directly into the respirometry chambers (5 l plastic container). A subsample of the air leaving the respirometry chambers was passed through CO₂ / H₂O gas analysers (LI-COR, model LI-840A, Lincoln, NE, USA) interfaced with an analogue-to-digital converter (ADInstruments, model PowerLab 8/30 A/D convertor, Bella Vista, NSW, Australia) that was connected to a laptop computer. We were able to observe our measurements in real time via the LabChart software (ADInstruments, Bella Vista, NSW, Australia). We measured the excurrent air from chambers containing individual birds, as well as an empty reference chamber to obtain continuous measurements of atmospheric concentrations of CO₂ and H₂O during all measurements. The use of a reference chamber enabled us to mathematically compensate for fluctuations in atmospheric
concentrations of CO₂ and H₂O as well as compensate for the effects of fluctuations in atmospheric pressure.

The laptop computer was placed outside the room in which birds were being held, to minimize disturbance to the birds and so that respiration of the birds could be observed in real time to monitor welfare of the birds in each trial. We also monitored internal body temperature (T_b) in real time using data loggers (Animals Monitoring, model Anipill, Caen, France) with a data receiver to ensure the birds did not overheat at any point. The Anipill loggers were ingested by birds between capture and being put in the respirometry chambers and recorded body temperature continuously (1 sample min⁻¹). The Anipills are the same as those swallowed by human athletes to monitor their body temperature during activity (e.g. marathons). They are calibrated by the manufacturer, and a calibration certificate was provided. In seabirds, the devices reside in the stomach and do not enter the intestine, because the pylorus is extremely small and only lets liquid transfer from the stomach into the intestine. The device therefore remains in the stomach until regurgitated by the bird, usually after a few days. Regurgitation is a natural process in seabirds, to feed chicks and/or to evacuate undigested hard parts of prey, such as fish otoliths. All birds survived the respirometry trials and flew away upon release at the end of each trial. Several birds on which respirometry had been performed were re-sighted at the colony in the following days, and some of those were observed with full gular pouches, meaning they had returned to feeding behaviour and attending to their chicks at the nest. The period of time between when an individual was first caught and when it was released and had the opportunity to return to the nest was 17 h. Dovekies exhibit biparental care, with both male and female adults provisioning their chick with food, meaning that chicks would not have been without food during the time the other parent was in captivity.

Upon being introduced to the respirometry chambers, birds were given 3.5 h to settle at a temperature between 4 and 10°C (mean air temperature at the colony during our study was 7.5°C) before the temperature in the temperature-controlled box was changed. It took approximately 1.5 h for air temperature to stabilize at each new test temperature, after which birds were held at that temperature for approximately 1 h. Hence, the first measurement period occurred at 5 h after birds were introduced to the respirometry chamber, and birds were kept in respirometry chambers for approximately 14 h and exposed to 4–5 acute test temperatures (in total 184 measurements from 36 individual birds). Estimates for resting metabolic rate, water loss rate and internal body temperature were obtained from measurements taken during the 1 h test period when air temperature was stable. We used a custom algorithm that searched for a 30 min period corresponding to the lowest mean value of metabolic rate within the 1 h measurement period. While each individual was exposed to 4–5 test temperatures, we randomized the test temperatures that individuals were exposed to between 5°C and 35°C. We randomized test temperatures to maximize the spread of samples across the continuous range of ambient temperatures rather than arbitrarily ‘binning’ all individuals to a subset of 4–5 temperatures, which would reduce the precision of the fit of the regression model to the data. We also randomized the order in which individuals were exposed to test temperatures so that any potential changes in the contribution of stress over the 14 h measurement period were randomly distributed across the range and order of test temperatures in our study. Temperature was recorded separately inside each respirometry chamber with a temperature data logger (OneTemp, model Hobo MX2201, Adelaide, South Australia, Australia), which was connected via Bluetooth to a smart phone (Apple, model iPhone 6, Cupertino, CA, USA) and temperatures could be tracked in real time.

No birds that were used for respirometry were observed with full gular pouches when captured prior to respirometry. This does not rule out that the birds might have fed recently prior to the trial but at least birds had not fed immediately prior to capture. Even if birds had fed immediately prior to capture, the initial phase of the specific dynamic action response (during which time metabolic rate is elevated due to the energetic cost of digestion) would have passed prior to measurement of metabolic rate, which occurred at least 7 h after capture. To the extent that it is possible in wild birds, our measurement protocols sought to minimize inter-individual variation in metabolic rate associated with energy expenditure on activities other than that required for thermoregulation, including digestion and stress.

### (c) Statistical modelling for physiological measurements

We fitted nonlinear least-squares regression models to our data for $\dot{V}_{CO_2}$ and $\dot{V}_{H_2O}$ using the minpack.lm package [22] in R. Our goal was to estimate nonlinear function relating $\dot{V}_{CO_2}$ and $\dot{V}_{H_2O}$ to temperature, but we also need to account for the effect of body mass on each response variable. We were unable to achieve convergence for models fitted with parameters describing the effects of both temperature and body mass, so we had to mass-adjust the data prior to fitting models for temperature. We did this by fitting linear models relating log $\dot{V}_{CO_2}$ or log $\dot{V}_{H_2O}$ to log body mass to estimate the allometric scaling exponent. We then divided $\dot{V}_{CO_2}$ and $\dot{V}_{H_2O}$ by mass raised to the allometric exponent to calculate mass-specific rates. We also adjusted our estimates of $\dot{V}_{CO_2}$ and $\dot{V}_{H_2O}$ to account for potential measurement time (order) effects. To do this, we fitted a segmented regression model to $\dot{V}_{CO_2}$ estimates, with air temperature and measurement order (1–5) fitted as fixed effects. We estimated the difference between the mean of the final test period (at which point the birds had the longest time to settle since the beginning of the trial) and the mean of each test period preceding it. We then subtracted that difference in means from each individual trait value according to the order of the test period. The biggest difference was between the first measurement and the final measurement, with the difference between subsequent measurements and the final measurement declining until there was no difference between the last and second last measurement periods. We calculated the respiratory exchange ratio (RER) for each individual as a way to identify and exclude any estimates with clearly unrealistic RER values outside the range of 0.45–1.2 (a RER near 0.65 indicates fat as the predominant metabolic fuel source and a RER near 1 indicates carbohydrate as the predominant fuel source).

The best fitting model of the thermal dependence of $\dot{V}_{CO_2}$, $\dot{V}_{H_2O}$ and $T_b$ was a four-parameter function relating mass-adjusted $\dot{V}_{CO_2}$ (or $\dot{V}_{H_2O}$, or $T_b$) to temperature according to the following equation:

$$ \frac{\dot{V}_{CO_2}}{\text{mass}^b} = \text{BMR} + \text{C}_{\text{min}} \times (T_{\text{crit}} - \text{temp}_{<T_{\text{crit}}}) + H \times (\text{temp}_{>T_{\text{crit}}} - T_{\text{crit}}), \quad (2.1) $$

where b is the allometric scaling exponent for the relationship between log $\dot{V}_{CO_2}$ and log mass, BMR is the minimum rate of $\dot{V}_{CO_2}$, $C_{\text{min}}$ is the slope estimate for the thermal dependence of $\dot{V}_{CO_2}$ at temperatures below the critical temperature ($T_{\text{crit}}$) and H is the slope estimate for the thermal dependence of $\dot{V}_{CO_2}$ at temperatures above the critical temperature ($T_{\text{crit}}$). Typically, BMR falls within a thermoneutral zone bounded by an upper ($T_{\text{UC}}$) and lower critical temperature ($T_{\text{LC}}$) as estimated using Scholander-Irving models [3]. However, our data exhibited only a single critical temperature when $\dot{V}_{CO_2}$ was lowest, and below that temperature $\dot{V}_{CO_2}$ increased with decreasing temperature and above that temperature $\dot{V}_{CO_2}$ increased with increasing temperature. The same was true for the data for $\dot{V}_{H_2O}$ and $T_b$.
<figure><img src="image_5.png" /><figcaption>**Figure 1.** Dovekies exhibit lower *T*<sub>UC</sub> than predicted for a bird of its size and habitat latitude. (a) (Map inset) dovekies (*Alle alle*) are the most abundant seabird in the Arctic. The geographic distribution of dovekies in winter, summer and breeding locations are shown in light green, medium green and dark green shades, respectively [25]. The light blue and dark blue lines show the present-day maximum and minimum sea-ice extent, respectively [26]. (b) Bird species that live at higher latitudes (blue branches on phylogenetic tree) show reduced upper critical temperature (*T*<sub>UC</sub>) after accounting for the effects of body mass and phylogeny. Residual *T*<sub>UC</sub> is shown by the bars at the tree tips, with bar length (see axis) and colour (green, orange) corresponding to deviation from model predictions. Dovekies have a *T*<sub>UC</sub> 14.8°C less than predicted for a bird of its body mass and taxonomy (and 8.8°C lower than predicted by a model that also includes habitat latitude; see main text for full statistical results).</figcaption></figure>

We were not able to account for repeated measures on
individual birds by fitting nonlinear mixed effects models as
these models did not converge, likely due to an issue with
overparameterization. We decided to continue with nonlinear
least-squares regression to obtain confidence intervals on our par-
ameter estimates for the future scenarios modelling (see below),
which we obtained using the *confint2* function in the *nlstools* pack-
age [23]. We also modelled the data using linear mixed effects
models for the data above and below *T*<sub>UC</sub> (i.e. the breakpoint in
the data) and obtained the same results as those obtained from
nonlinear least-squares (nls) models described above.

(d) Modelling dovekie physiology under future climate scenarios

We used one of the best performing climate models for the
Arctic climate (HadGEM2-ES; [24]) to extract land surface air
temperatures every 3 h for the summer months (June – August)
at our study site at Ukaleqarteq, East Greenland (70° 43′ N,
21° 33 W). We extracted 3 hourly summer air temperatures each
year for a decade during a historical baseline (1996–2005),
as well as mid-century (2036–2045) and a late-century (2090–
2099). In the mid- and late-century decades, summer air tempera-
tures were considered under both low (RCP2.6) and high (RCP8.5)
radiative forcing scenarios, creating a total of five climatic con-
ditions (one baseline, mid-century low and high global
greenhouse gas emissions, and late century low and high global
greenhouse gas emissions). Combining those air temperature
data and empirical physiological data, we calculated the total
amount of energy expended (CO₂ total) and water lost (H₂O total)
by an average individual over the summer breeding season. To
examine how CO₂ total and H₂O total might also be sensitive to
changes in the TUC parameter of the thermoregulatory function
(either via evolution or plasticity), we modelled energy and

water costs across a range of TUC values from 5 to 35°C. We
then calculated the factorial change in CO2 total and H2O total
under future climate scenarios relative to the baseline scenario.

**3. Results and discussion**

We performed a phylogenetic analysis of existing data [15]
for upper critical temperature (T<sub>UC</sub>) in 256 bird species span-
ning in body sizes from 3 g to 11 kg, from the tropics to the
Arctic, to examine the evidence for cold adaption in dovekies.
We found that T<sub>UC</sub> decreases towards the poles (F<sub>1,249</sub> = 29.49,
p < 0.001) and decreases with log body mass (F<sub>1,249</sub> = 12.34,
p < 0.001), which is consistent with the long-standing
assumption that polar species are potentially heat-stressed
under warming conditions [2–6]. Dovekies thereby appear
to be putatively adapted to cold conditions, with an observed
T<sub>UC</sub> (22.4°C, this study) that is 8.8°C lower than predicted
(31.2°C) by our statistical model that included the effects of
phylogeny, body mass and habitat latitude (figure 1). To
account for potential methodological sources of error in T<sub>UC</sub>
estimates we included a fixed factor in our models based
on the ‘data quality’ categories proposed by McKechnie
et al. [21] in their examination of the primary data from the
Khaliq et al. [15] dataset. Their categories were ‘Good’, ‘No
T<sub>UC</sub>’ (i.e. no breakpoint in the data, T<sub>UC</sub> taken as highest
measurement temperature), ‘Insufficient data’, or ‘—’
(meaning they were not able to assess the data). Data quality
explained only 2.8% of the variance in T<sub>UC</sub>. We included
‘data quality’, which we called ‘methodology’, as a fixed
factor (with the four levels described above) in our models.
Methodology explained 2.8% of the variance in T<sub>UC</sub> and the
<figure><img src="image_6.png" /><figcaption>**Figure 2.** Thermoregulatory physiology of dovekies (*Alle alle*). Basal metabolic rate in our study population coincided with an air temperature of 22.4°C, and energy expenditure increased less with increasing air temperature than it did with decreasing air temperature (a). Rates of evaporative water loss increased passively and gradually from 5 to 31.6°C, beyond which active mechanisms of evaporative cooling led to a rapid increase in rate of water loss (b). Dovekies showed signs of facultative hyperthermia, with increases in body temperature (*T*<sub>b</sub>) at air temperatures above 24.3°C (c) that were controlled, since the rate of increase in *T*<sub>b</sub> (Δ*T*<sub>b</sub>) during high temperature exposure was insensitive to ambient temperature (d).</figcaption></figure>

standardized effect sizes (Cohen's *d*) for each methodology
category varied between 0.03 and 0.07 (very little effect).
In other words, variation associated with methodological
error (2.8%) was much smaller than that associated with lati-
tude and body mass, and thus does not obfuscate the large-
scale signals of latitude and body mass—an argument that
has been previously discussed in the physiological and
macro-ecological literature [27–29].

The presumed cold adaptation of dovekies is consistent
with the only previous experimental study of physiological
cold adaptation in this species [14], which estimated that the
basal rate of heat production (177.9 kJ day⁻¹) was more than
twice that predicted (84.2 kJ day⁻¹) for a non-passerine bird
of the same size (153 g) [30]. That same study also found
that dovekies have low thermal conductance, meaning that –
at cold temperatures below thermoneutrality – they retain
heat more effectively than other temperate-zone seabirds of
similar size, such as the Georgian diving petrel (*Pelecanoides
georgicus*) [14,31,32]. Given the phylogenetic and physiological
evidence in support of cold adaptation in dovekies, we
expected that they would be prone to acute hyperthermia
when exposed to warmer temperatures above thermoneutral-
ity. This is coherent with dovekie morphology, notably with an
extremely dense plumage which provides highly efficient
thermal insulation both in air and water [13].

In this context, we estimated resting metabolic rate (V̇CO₂), rate of water loss (V̇H₂O) and internal body temperature (T_b) in dovekies from a breeding colony at Ukaleqarteq, East Greenland (70° 43′ N, 21° 33 W). Contrary to our

expectations based on previous investigations [14], we
found that dovekies exhibited a remarkable capacity for ther-
moregulation at high temperatures. Energy expenditure
while resting was lowest at 22.4°C (95% CI 19.8–25.0, t₁₃₃ =
16.37, *p* < 0.0001; figure 2a) and there was only a marginal
increase in energy expenditure as ambient temperature
increased from 22 up to 35°C (4.93 ml CO₂ h⁻¹°C⁻¹, 95% CI
1.70–8.16, t₁₃₃ = 3.02, *p* < 0.05; figure 2a). Heat dissipation
mechanisms allowed mean body temperatures to remain
stable at temperatures up to 24.3°C (95% CI 22.3–26.2, t₉₄ =
24.8, *p* < 0.0001; figure 2c), above which mean body tempera-
ture rose by 0.16°C with every 1°C increase in ambient
temperature (95% CI 0.11–0.21, t₉₄ = 6.1, *p* < 0.0001;
figure 2c). Yet these increases in body temperature were not
uncontrolled, since the rate of increase in T_b (ΔT_b) during
high temperature exposure was essentially insensitive to
ambient temperature variation (the slope of ΔT_b ~ T_a was
0.048°C h⁻¹, figure 2d). This suggests that dovekies engage
in facultative hyperthermia to reduce the thermal gradient
between their body and the air, and to reduce water loss at
higher temperatures. Indeed, rates of water loss show only
a gradual and largely passive increase between 5 and 31.6°
C, at which point there is a distinct increase in rates of
water loss above 31.6°C (95% CI 30.1–33.1, t₁₃₁ = 42.2, *p* <
0.0001; figure 2b).

We used our physiological measurements and future
climate projections for our study site to model how the ener-
getic and water costs of thermoregulation are expected to
change under future climate warming. Our modelling
<figure><img src="image_7.png" /><figcaption>**Figure 3.** Modelling the energetic and water costs of thermoregulation in dovekies under warming Arctic climates. We used one of the best performing climate models for the Arctic climate (HadGEM2-ES; [24]) to extract land surface air temperatures every 3 h for the summer months (June to August) at our study site at Ukaleqarteq, East Greenland (a). We calculated air temperature data for a historical baseline decade (1996–2005) as well as mid-century (2036–2045) and late-century (2090–2099) decades, each under low (RCP2.6) and high (RCP8.5) global greenhouse gas emissions scenarios (b). Using our physiological data, we modelled total energy expenditure and water loss for the whole of summer in each year of our climate scenarios (c) and (d). Energy and water costs were calculated for the whole summer for *T*<sub>UC</sub> values ranging from 1 to 36 to capture possible effects of variation in *T*<sub>UC</sub> (caused by plasticity or adaptation). Lines in plots (c) and (d) show the mean total energy cost and mean total water cost for each of the five climate scenarios (see inset legend for colour and line type). To show how energy and water costs are predicted to change into the future, plots (e) and (f) show the factorial change in total energy and water costs relative to the baseline estimations. Arrows in plots (c)–(e) indicate the *T*<sub>UC</sub> of dovekies (22.4°C).</figcaption></figure>

predicts that the energetic costs of thermoregulation (while at rest) will be reduced in dovekies under future climate warming scenarios (figure 3). While initially surprising, this result is consistent with the fact that, in dovekies at least, the energetic cost of heat production is greater than the energetic cost of heat dissipation. In other words, it is more energetically costly to maintain a high and stable body temperature at cold air temperatures than it is to dissipate excess body

heat at warmer temperatures. Rather than being constrained by energy expenditure, the challenge faced at air temperatures above $T_{\text{UC}}$ is water conservation: active mechanisms of evaporative water loss become increasingly important for maintaining core body temperature and preventing lethal hyperthermia. Indeed, our modelling predicts that the water cost of thermoregulation will increase under all future climate scenarios. Across a wide range of plausible
values of *T*<sub>UC</sub> (current estimate of 22.4 ± 7°C), our modelling predicts that water costs of thermoregulation will increase by a factor between 1.1 and 2 by 2100.

Dovekies, being seabirds, have an abundance of water available in their habitat, and because they possess salt glands in the frontal part of their skulls, they can (and do) drink saltwater and excrete excess salt [33,34]. Hence, increased water costs to support thermoregulation may not necessarily impose an immediate constraint. Taken together, our bioenergetic and water loss data suggest that dovekies have an unexpectedly high thermoregulatory capacity to survive acute heat exposures at least five times their current habitat average air temperature and approximately 15°C above maximum air temperatures. In the 2019 breeding summer season, average air temperature was 7.6°C ± 5.9 (s.d.) and maximum recorded air temperature was 20.8°C (2019, unpublished data, gathered by a weather station at the breeding colony, recording temperature each minute).

Our results and their implications primarily concern the resting phase of dovekies, which represents 54% of their time budget during the summer breeding season [12], and 64% during the inter-breeding winter period [35]. During the remaining time, birds engage in energetically demanding activities such as flying and diving (flying: 7.24 × basal metabolic rate; diving: 9.37 × basal metabolic rate [36]), which may lead to overheating. Yet, recent field measurements [37] demonstrated that dovekies efficiently alternate periods spent flying and diving, with resting at sea or at the colony enabling the rapid dissipation of muscular heat and body temperature decline.

Overall, the implication of our study is that the longer-
term impacts of climate warming on Arctic endotherms are
unlikely to be dictated by direct (i.e. lethal) susceptibility
to acute hyperthermia, even during the highly energetically
demanding breeding season. Instead, the climate vulner-
ability of species is more likely to be modulated by indirect
climate change impacts. Notably, previous studies pointed
to climate-induced shifts in North Atlantic zooplankton com-
munities, with smaller, less profitable prey invading dovekie
foraging areas [38]. Dovekies buffered this indirect conse-
quence of Arctic warming by increasing their foraging
effort, and their breeding performance remained unchanged
[39]. Yet, they reached an energetic ceiling [40] and are
more sensitive to contaminant exposure [41]. As a conse-
quence, dovekie adult survival declined in Arctic areas
most affected by climate warming [42], but overall population
consequences of these changes remain unclear.

It is at first surprising that cold adaptation does not pre-
clude warm tolerance in dovekies. It is important to recall,
however, that dovekies diversified from ancestral Alcid
species 15 million years ago (Ma) [43] during the Middle-
Miocene Climatic Optimum (MMCO). The MMCO was a
global warming event that occurred 16–14 Ma, when global
mean surface temperature was 3–4°C warmer than today
[44,45], and is associated with major shifts in the global

distribution of faunal and floral assemblages [46]. Further,
during the Pliocene (2.6–5 Ma), global mean annual tempera-
ture was 2–3°C warmer than today, and the Arctic was
estimated to be 19°C warmer [47]. Following palaeoclimatic
warm periods, dovekies persisted through ice ages when
global temperatures were much colder than the present. For
instance, during the Last Glacial Maximum (23–19 thousand
years ago), global average temperature was about 6°C colder
compared with modern-day (pre-industrial) temperatures,
and up to 15°C colder at high northern latitudes [48].
During the inter-breeding winter period today, migrating
dovekies experience a range of air temperatures between
6.4°C and –10.7°C and sea temperatures between 6.3°C and
–1.3°C (see table 1 in [13]). Hence, throughout their evol-
utionary history, dovekies may have been exposed to
climates that were both markedly warmer and colder than
in the present time. We speculate that the ecophysiology of
dovekies has been shaped by a complex climatic legacy,
with a resulting blend of cold- and warm-adaptive traits.
Overall, our study suggests that we may suffer from evol-
utionary short-sightedness when assessing the impact of
current global warming on endemic Arctic birds and
mammals.

Ethics. All protocols were validated with respect to ethics, and research permits issued by the Ministry of Fisheries and Hunting, Government of Greenland (Permit number: 2019-88).

Data accessibility. Data and code are available from the Dryad Digital Repository: https://doi.org/10.5061/dryad.2280gb5zp [49].

Declaration of AI use. We have not used AI-assisted technologies in creating this article.

**Authors' Contributions.** J.E.B.: conceptualization, data curation, formal analysis, investigation, methodology, project administration, validation, visualization, writing—original draft, writing—review and editing; C.R.W.: conceptualization, formal analysis, funding acquisition, methodology, project administration, resources, supervision, validation, writing—review and editing; M.C.: investigation, validation, writing—review and editing; S.P.: investigation, methodology, resources, writing—review and editing; J.F.: data curation, funding acquisition, investigation, project administration, resources, validation, writing—review and editing; D.G.: conceptualization, data curation, funding acquisition, investigation, methodology, project administration, resources, supervision, validation, writing—original draft, writing—review and editing.

All authors gave final approval for publication and agreed to be
held accountable for the work performed therein.

Conflict of interest declaration. We declare we have no competing interests.

**Funding.** This study and long-term monitoring programme on dovekies have been funded by the French Polar Institute (grant 388 to D.G. and J.F.) and by various grants from the Australian Research Council to C.R.W. We also thank CNRS Ecology and Environment for support through its long-term monitoring programmes scheme.

**Acknowledgements.** The authors would like to acknowledge that the field work was conducted on the land of First Nations Tunumiit people of east Greenland. We thank NANU Travel for logistic support. We would also like to acknowledge Dr Carmen da Silva, Dr Hugh Win-wood-Smith and Dr Lesley Alton for logistical support prior to field work and for helpful discussions during manuscript preparation, as well as two anonymous reviewers whose feedback and suggestions were greatly appreciated and improved the manuscript.

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