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Seasonally specific responses to wind patterns and ocean productivity facilitate the longest animal migration on Earth


Abstract and Figures

Migratory strategies of animals are broadly defined by species’ eco-evolutionary dynamics while behavioural plasticity according to the immediate environmental conditions en route is crucial for energy efficiency and survival. The Arctic tern Sterna paradisaea is known for its remarkable migration capacity as it performs the longest migration known by any animal. Yet, little is known about the ecology of this record-breaking journey. Here, we test how individual migration strategies of Arctic terns are adapted to wind conditions and fuelling opportunities along the way. To this end, we deployed geolocators on adult birds at their breeding sites in Svalbard, Norway. Our results confirm fundamental predictions of optimal migration theory: Arctic terns tailor their migration routes to profit from (1) tailwind support during the movement phase and (2) food-rich ocean areas during the stopover phase. We also found evidence for seasonally distinct migration strategies: terns prioritize fuelling in areas of high ocean productivity during the southbound autumn migration and rapid movement relying on strong tailwind support during the northbound spring migration. Travel speed in spring was 1.5 times higher compared to autumn corresponding to increase in experienced wind support. Furthermore, with their pole-to-pole migration, Arctic terns experience approx. 80% of all annual daylight on Earth (most by any animal) easing their strictly diurnal foraging behaviour. However, our results indicate that during migration daylight duration is not a limiting factor. These findings provide strong evidence for the importance of interaction between migrants and the environment in facilitating the longest animal migration on Earth.
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Mar Ecol Prog Ser
Vol. 638: 1–12, 2020 Published March 19
Bird migration usually comprises an interchange of
an active flying phase, when energy is consumed,
and a stationary stopover phase, when fuel is
restored by food intake (Alerstam & Lindström 1990,
Hedenström & Alerstam 1998). This is especially true
© The authors 2020. Open Access under Creative Commons by
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restricted. Authors and original publication must be credited.
Publisher: Inter-Research ·
*Corresponding author:
Seasonally specific responses to wind patterns and
ocean productivity facilitate the longest animal
migration on Earth
Tereza Hromádková1,2, Václav Pavel2, Jirˇí Flousek3, Martins Briedis4, 5, 6,*
1Department of Zoology, Faculty of Science, University of South Bohemia, 370 05 >eské Budeˇjovice, Czech Republic
2Centre for Polar Ecology, Faculty of Science, University of South Bohemia, 370 05 >eské Budeˇjovice, Czech Republic
3The Krkonoše Mountains National Park, Dobrovského 3, 543 01 Vrchlabí, Czech Republic
4Department of Zoology, Palacký University, 771 46 Olomouc, Czech Republic
5Swiss Ornithological Institute, 6204 Sempach, Switzerland
6Lab of Ornithology, Institute of Biology, University of Latvia, 2169 Salaspils, Latvia
ABSTRACT: Migratory strategies of animals are
broadly defined by species’ eco-evolutionary dynam-
ics, while behavioural plasticity according to the
immediate environmental conditions en route is cru-
cial for energy efficiency and survival. The Arctic tern
Sterna paradisaea is known for its remarkable migra-
tion capacity, as it performs the longest migration
known by any animal. Yet, little is known about the
ecology of this record-breaking journey. Here, we
tested how individual migration strategies of Arctic
terns are adapted to wind conditions and fuelling
opportunities along the way. To this end, we deployed
geolocators on adult birds at their breeding sites in
Svalbard, Norway. Our results confirm fundamental
predictions of optimal migration theory: Arctic terns
tailor their migration routes to profit from (1) tailwind
support during the movement phase and (2) food-rich
ocean areas during the stopover phase. We also found
evidence for seasonally distinct migration strategies:
terns prioritize fuelling in areas of high ocean produc-
tivity during the southbound autumn migration and
rapid movement relying on strong tailwind support
during the northbound spring migration. Travel speed
in spring was 1.5 times higher compared to autumn,
corresponding to an increase in experienced wind
support. Furthermore, with their pole-to-pole migra-
tion, Arctic terns experience approximately 80 % of all
annual daylight on Earth (the most by any animal),
easing their strictly diurnal foraging behaviour. How-
ever, our results indicate that during migration day-
light duration is not a limiting factor. These findings
provide strong evidence for the importance of interac-
tion between migrants and the environment in facili-
tating the longest animal migration on Earth.
Geolocator tagged Arctic term Sterna paradisaea at a breed-
ing site in Svalbard, Norway.
Photo: Martins Briedis
KEY WORDS: Arctic tern · Sterna paradisaea ·
Daylength · Geolocator · Global wind systems · Long-
distance migration · Migration phenology · Migration
strategy · Ocean productivity
Mar Ecol Prog Ser 638: 1–12, 2020
for flapping migrants (e.g. waders and songbirds)
that fuel their flight by burning energy, as opposed to
soaring migrants (e.g. raptors and albatrosses) that
often take advantage of thermals or topography-
induced air uplifts, to cover large distances with min-
imal energy expenditure. For flapping flyers, this
means that, while on migration, extended time needs
to be spent at stopover sites refuelling and storing
energy reserves to power the upcoming flight bouts
(Hedenström & Alerstam 1997). Because the rate of
energy expenditure during the flight phase is usually
much higher than the rate of fuel deposition on
stopovers, visiting high-quality stopover areas en
route is of high importance for efficient and success-
ful migration (Alerstam 2011). One of the main ways
to reduce the expenditure of stored energy during
flapping flight is to exploit prevailing wind regimes
and adjust migration routes to take a full advantage
of wind assistance for covering large distances rap-
idly (Kranstauber et al. 2015). Thus, maximizing
fuelling rates on stopovers and minimizing energy
expenditure during the flight bouts are the 2 key
aspects of migration energetics for species that use
powered flight for their migration (Alerstam 2003).
The overall migration duration of birds is largely de-
pendent on fuelling rates (Lindström 2003), while tail-
wind support can significantly facilitate faster travel-
ling during the movement phase (Green 2004).
Daylength regime (day:night ratio) has also been sug-
gested to have considerable effect on the total migra-
tion duration of diurnally foraging species because
of limited daylight hours available for fuelling
(Bauchinger & Klaassen 2005). As the season pro-
gresses and migrants move across latitudes, they ex-
perience changes in the daylength regime, which can
slow down or speed up their migration depending on
the time of the year, latitude and species’ activity
cycle (nocturnal vs. diurnal migrants and nocturnal
vs. diurnal foragers). For most species, migration
should be shorter (and faster) when daylength is
longer and there is more time for fuelling (Kvist &
Lindström 2000, Bauchinger & Klaassen 2005).
All these aspects should be especially important for
trans-equatorial migrants that cover long distances be-
tween their breeding and non-breeding areas. On the
extreme range of the migration distance spectrum is
the Arctic tern Sterna paradisaea that annually mi-
grates over 50 000 km between the breeding areas in
the Arctic and the non-breeding areas in Antarctica
(Storr 1958, Egevang et al. 2010). Despite a recent
surge in tracking studies on Arctic terns (Egevang et al.
2010, Fijn et al. 2013, McKnight et al. 2013, Volkov et
al. 2017, Alerstam et al. 2019), significant gaps remain
in our understanding about the ecology of this record-
breaking migration. To travel such vast distances
across all climatic zones, exploitation of environmental
settings for efficient travel may be crucial, as the seem-
ingly favourable shortest route may not be optimal. By
arching migration corridors according to the tailwind
support and further fine-tuning the routes to pass
through areas of high ocean productivity, migrants can
sustain the energy-demanding flight phase by stopping
over and refuelling at sites where food resources are
abundant. Furthermore, while residing at the breeding
and non-breeding sites, Arctic terns are exposed to
24 h daylight, enabling flexible interchange between
foraging and resting time. In contrast, during migration
terns are exposed to shifts between day and night as
they pass through intermediate latitudes. Because Arc-
tic terns are strictly diurnal foragers (McKnight et al.
2013), feeding and refuelling during migration are lim-
ited to the available daylight hours. This may force
terns to feed during the day and travel at night if rapid
and short-duration migration is advantageous.
In this study, we used geolocator tracking to, first,
describe migration patterns and non-breeding areas
of the Arctic terns breeding in the high Arctic (Sval-
bard, Norway) at the northern limits of the species’
distribution range (BirdLife International 2018). Sec-
ond, we tested how individual migration routes and
stopover sites are adapted to take advantage of wind
support and food availability en route. We hypothe-
sized that the longest animal migration on Earth is
facilitated by wind assistance during the flight phase
and abundance of food resources during the refu-
elling stopover phase, which is further eased by
extended daylength hours throughout the journey.
Hence, we predicted that (1) the chosen migration
routes of the tracked Arctic terns will be adapted so
that the birds benefit from tailwind support during
both southbound and northbound migrations; (2) the
stopover sites of the terns will be located in areas of
higher ocean productivity compared to passage
areas (McKnight et al. 2013); (3) the terns will time
their migration to cross the Equator near the
equinoxes, enabling longer foraging hours in both
hemispheres (Alerstam 2003).
2.1. Field work
Our study site was located in Longyearbyen on
the island of Spitsbergen, Svalbard archipelago
(78° 14’ N, 15° 39’ E). We captured 30 breeding indi-
Hromádková et al.: Environmental effects on the longest animal migration
viduals during late stages of egg incubation between
8 and 14 July 2017, using tent spring traps placed on
their nests. All captured birds were marked with
unique colour ring combinations and equipped with
multi-sensor archival data loggers (geolocators;
model Intigeo-W65A9-SEA, Migrate Technology)
that were fixed to the colour rings. Geolocators were
set to sample ambient light intensity every minute
and store maximal values at 5 min intervals. Temper-
ature was sampled every 5 min, storing maximal and
minimal values at 4 h intervals; immersion and con-
ductivity measures were sampled every 30 s, storing
the sum of samples scored as wet and maximal con-
ductivity every 4 h.
The geolocators including colour rings weighed
1.06 ± 0.05 g (SD), which never exceeded 1.2% of the
body mass of the tagged birds (106.2 ± 7.6 g, n = 30).
Sex of all tagged individuals was determined molecu-
larly using a droplet of blood taken from the brachial
vein (Griffiths et al. 1998, Fridolfsson & Ellegren 1999,
Ležalová-Piálková 2011), as the accuracy of sexing
Arctic terns in the field is typically lower than 74%
(Fletcher & Hamer 2003, Devlin et al. 2004).
In the following season between 27 June and 12
July 2018, we managed to recapture 16 birds with
geolocators (53%) at the same breeding colony. At
least 7 more of the previously tagged birds were
sighted in the breeding colony (total return rate =
77%), but we failed to recapture them. This was
mainly due to high predation rate of the nests in this
season by Arctic fox Vulpes lagopus leading to fre-
quent relocation or disappearance of the individuals
whose nests were depredated.
Body mass of the tagged individuals was higher
upon recapture and removal of the geolocators com-
pared to the time of deployment a year earlier (2017:
104.6 ± 8 g [n = 16], mean capture date = 10 July;
2018: 110.9 ± 7.6 g, mean capture date = 4 July;
paired t-test: t14 = 2.691, p = 0.018; data met the
assumption of normality and homogeneity of vari-
ances based on a Shapiro-Wilk normality test and an
F-test, respectively). Thus, geolocators apparently
did not have a negative effect on the body condition
of the tagged individuals (Brlík et al. 2020).
2.2. Data analyses
2.2.1. Geolocator tracking
All data analyses were done in R version 3.5.1 (R
Core Team 2018). To calculate the geographic posi-
tions of the terns, we first log-transformed light inten-
sity recordings from the retrieved geolocators to
derive sunrise and sunset times (twilight events)
using the ‘preprocessLight’ function in the R-pack-
age ‘TwGeos’. Further, we used the R-package
‘FLightR’ to estimate geographic locations of the
tracked individuals (Rakhimberdiev et al. 2017). Dur-
ing both breeding and non-breeding periods,
tracked Arctic terns were exposed to 24 h daylight,
thus making it problematic to use these stationary
periods for calibrating the light data. Sunsets and
sunrises were recorded only during migration peri-
ods and during an approximately 2 mo long period
before the spring migration when the birds were at
an unknown location at the non-breeding sites.
Within the latter period, we identified extended peri-
ods when birds were stationary before the spring
migration by visually inspecting recorded sunrise
and sunset times. We then used the ‘find. stationary.
location’ function to estimate the geographic location
of this unknown site and used it for calibration.
Further, we followed standard analysis procedures
in ‘FLightR’ as outlined by Lisovski et al. (2020).
‘FLightR’ uses a template fit method to compute a
spatial likelihood surface for each twilight event. A
posterior distribution of the likeliest migration path
and its credible intervals are then derived via particle
filtering. Because the conductivity (salinity) record-
ing on all of our geolocators indicated that whenever
geolocators were immersed, birds were in saltwater,
we set 0 probability for birds occurring in areas that
were further than 50 km away from the shoreline. For
1 track (BH004, see Fig. S1e in the Supplement at
www. int-res. com/ articles/ suppl/ m638 p001 _ supp. pdf),
the imposed spatial mask led to a failure of the parti-
cle filter; therefore, the analyses for this geolocator
were run without a spatial mask. Finally, we used the
‘stationary.migration.summary’ function to deter-
mine stationary periods that were longer than 6 twi-
light events (3 d) and arrival/departure dates from
them. For this, we defined 20% as the minimum
probability of movement.
Using high-frequency data, McKnight et al. (2013)
showed that Arctic terns typically do not rest on
water, as only a small fraction of time (0.5 ± 0.22 h d−1
at most in August) is spent floating. Thus, immersion
recordings should approximately reflect the daily
rate of feeding dives. Based on this, we used the
cumulative daily count of the number of times the
geolocator was immersed in water as a proxy for esti-
mating the feeding rate across the annual cycle.
We used ANOVA to test if there were differences in
migration parameters (migration timing, speed, dis-
tance, feeding rate, etc.) between males and females.
Mar Ecol Prog Ser 638: 1–12, 2020
We used Bartlett’s test of homogeneity of variances
and a Shapiro-Wilk normality test to test homogeneity
of variance and assumption of normality, respectively.
In 3 migration parameters (onset of spring migration,
migration distance in autumn and migration speed in
autumn), homogeneity of variances and assumption
of normality were not met, and in 1 migration parame-
ter (total migration distance), only the assumption of
normality was not met. Thus, we filtered outlying val-
ues from these 4 migration parameters. After exclud-
ing outlying values, total migration distance and mi-
gration speed in autumn met both assumptions. For
onset of spring migration and migration distance in
autumn, we used the nonparametric Wilcoxon rank
sum test. Since no differences were found in any of
the tested migration parameters, we pooled data of
both sexes for all further analyses. Travel speed (km
d−1) is defined here as the total distance travelled di-
vided by the total number of days spent on migration
in each migration season.
2.2.2. Ocean productivity
We used ocean productivity data to compare if
stopover sites of terns were located in areas with
potentially higher food resource abundance as com-
pared to passage areas (migration corridors). We
defined polygons for stationary sites in a radius of 2°
around the median location of the stationary sites
earlier established by the ‘stationary.migration.sum-
mary’ function. Migration corridors were defined as
lines connecting twice-daily positions within the
migration periods with 1° wide buffer around them
and excluding stationary sites.
We downloaded gridded (0.167° grid) weekly
ocean productivity data from the Ocean Productivity
website of the Oregon State University (www.sci-
ence.oregon state. edu/ ocean.productivity/; Behren-
feld & Falkow ski 1997) and extracted productivity
values for all grid cells within the defined stationary
areas and migration corridors corresponding to the
specific weeks. Grid cells that did not contain pro-
ductivity data were omitted from the analyses.
Because ocean productivity data were positively
skewed, we transformed the values using the natural
2.2.3. Wind support
To evaluate the role of wind assistance in facilitat-
ing the migration, we obtained wind data from the
European Centre for Midrange Weather Forecast
(ECMWF; Wind data were
averaged across the full migration period of the
tracked terns (autumn 2017: 24 Aug−27 Nov, spring
2018: 31 Mar−6 Jun) for each 4×4° grid across the
area between 85° N−85°S and 80° W−35°E. Because
Arctic terns typically migrate at low altitudes near
the water surface (Gudmundsson et al. 1992, Heden-
ström & Åkesson 2016) we used wind measurements
at the surface level. We then used the ‘NCEP.Air-
speed’ function from the R-package ‘RNCEP’ (Kemp
et al. 2012) to calculate wind support for each move-
ment segment (twice-daily positions and movement
direction between them) along the migration routes
of the tracked individuals.
2.2.4. Daylength
We used the light recording data from the geoloca-
tors to estimate the total amount of daylight hours
experienced by individual terns throughout the
annual cycle. Further, we calculated daylight dura-
tion at various latitudes across the year using the R-
package ‘suncalc’ (Thieurmel & Elmarhraoui 2019).
Daylight duration was calculated as the time
between civil dawn and civil dusk when the geomet-
ric centre of the Sun is 6° below the horizon, which
approximately matches light recording sensitivity of
the geolocators’ light sensor.
3.1. Migration and non-breeding areas
Terns departed their breeding site in Svalbard in
late August−early September (Box 1) and migrated to
a stopover area in the north Atlantic. Further, 9 indi-
viduals followed the west coast of Africa with later
stopovers in the southeast Atlantic, while 7 individu-
als followed the east coast of South America with
stopover sites in the southwest Atlantic (Fig. 1a).
Interestingly, 2 individuals (BH011 and BH024, both
females) made a loop at the beginning of the south-
bound migration and returned to Svalbard in early
October before continuing their southward move-
ment into tropical latitudes (Fig. S1i,p). Migration
parameters are summarized in Box 1.
At the end of the southbound migration, all tracked
individuals crossed the Antarctic Circle, entering the
24 h daylight zone; thus, location data from late
November until early to mid-February are not avail-
Hromádková et al.: Environmental effects on the longest animal migration
able. Between February and April, non-breeding
sites of all but 1 bird were located in the Weddell Sea
(Box 1, Fig. 2). The outlier individual travelled to
the Indian Ocean, residing at ca. 100° E longitude.
Another individual crossed the Drake Passage be -
tween Antarctica and South America in late March,
thus entering the Pacific Ocean before commencing
the northbound migration. Overall, the terns were
highly mobile during the non-breeding period cover-
ing several thousand km and residing at multiple
sites during their 4−5 mo long non-breeding period
in Antarctica (Box 1). Throughout the non-breeding
period, all birds were exposed daily to sub-zero tem-
peratures (Figs. S1 & S2).
Terns started the northbound migration in early
April (Box 1), following an S-shaped migration
pattern through the Atlantic (Fig. 1b). Longer
stopover periods were scarce until the end of the
migration period, when the birds arrived in the
northern Atlantic residing at the same stopover
region as at the beginning of the southbound
migration. During this stopover period, the terns
increased their feeding rate more than 2-fold (as
implied by the number of times the birds were
recorded being in water) as compared to the rest
of the annual cycle (Fig. 3). Travel speed for all
individuals was higher during the northbound
migration compared to the southbound migration
(paired t-test: t15 = 9.56, p < 0.001; Box 1), and
birds arrived back at the breeding colony in late
May−early June, having completed an average
round trip migration distance of 58 500 km (range:
50 200−78 500 km; Box 1).
Autumn migration
Start date 3 Sep (24 Aug−11 Sep)
Crossing Equator 4 Oct (23 Sep−22 Oct)
End date 19 Nov (5−27 Nov)
Total migration duration (d) 78 (68−93)
Migration distance (km) 22900 (19500−34800)
Travel speed (km d−1) 294 (258−420)
Non-breeding period
Wintering latitude South of 63° S
Wintering longitude 55° W−94° E
No. days at non-breeding site 137 (127−153)
Movement distance (km) 10812 (5279−19480)
Spring migration
Start date 5 Apr (31 Mar−16 Apr)
Crossing Equator 26 Apr (17 Apr−11 May)
End date 30 May (23 May−6 Jun)
Total migration duration (d) 54 (39−64)
Migration distance (km) 24800 (19600−29700)
Travel speed (km d−1) 435 (334−518)
Total track length (km) 58500 (50200−78500)
Total daylight hours 6985 (6750−7232)
Box 1. Summary data (mean and range) of key migration
and non-breeding period parameters of 16 geolocator-
tracked Arctic terns from a breeding colony in Longyear-
byen, Svalbard
(a) (b)
Fig. 1. Migration routes and stopover areas of 16 geolocator-tracked Arctic terns during (a) southbound and (b) northbound mi-
gration. Breeding site in Longyearbyen, Svalbard, is marked with an orange diamond, stopover sites longer than 3 d are marked
with dots. Background map source: Blue Marble Next Generation, https:// visibleearth. nasa. gov/ collection/ 1484/ blue-marble
Mar Ecol Prog Ser 638: 1–12, 2020
3.2. Migration routes and wind
In both seasons, terns on average be -
nefited from tailwind support along their
chosen migration routes (Figs 4 & 5).
During the southbound migration, terns
on average experienced 0.4 ± 0.6 m s1
(SD) tailwind support, while during the
northbound migration the experienced
tailwind support was substantially
stronger, averaging 2.2 ± 1.2 m s1
(paired t-test: t15 = 5.34, p < 0.001;
Fig. 5). Testing for the wind support on
reversed migration routes (travelling
along the spring routes in autumn and
autumn routes in spring) revealed that
terns would experience significantly
more headwinds in both migration sea-
sons (southbound migration: 2.1 ± 0.8 m
s1, paired t-test: t15 = 8.36, p < 0.001;
northbound migration: 0.2 ± 0.7 m s1,
paired t-test: t15 = 6.81, p < 0.001; Fig. 5).
After excluding the 2 outlying indi-
viduals that made a loop at the begin-
ning of the autumn migration and had
exceptionally high travel speeds, there
was no relationship between wind sup-
port and individual southbound travel
speed (β= 0.72 ± 7.38, F1,12 < 0.01, r2=
0.01, p = 0.924), while there was a posi-
tive relationship between the experi-
Fig. 2. Non-breeding areas (February−April) of 16 geolocator-tracked Arctic
terns. Stationary sites where birds remained for at least 7 d are marked with
dots; lines show movements within the non-breeding areas. Location data from
late November (after the southbound migration) until early-mid February are
not available due to 24 h daylight as all birds resided south of the Antarctic
Jul Aug Sep Oct Nov Dec Jan Feb Mar
Apr May Jun
Average no. of times in water per day
Fig. 3. Weekly average (± SD) number of times per day when geolocators were submerged in water during the annual cycle.
Migration periods are marked with grey bars on top (higher colour intensity corresponds to overlapping migration periods of
more individuals) and individual timings of start and end of migration are indicated by open circles
Hromádková et al.: Environmental effects on the longest animal migration 7
enced wind support and individual north-
bound travel speeds (β= 28.89 ± 9.33, F1,14
= 9.6, r2= 0.41, p = 0.008).
3.3. Stopover areas and ocean
While on migration, terns spent on aver-
age 32 ± 7.9 d (SD) on stopover sites during
the southbound migration and 10 ± 7 d
Wind speed
(m s–1)
Wind support
(m s–1)
(a) (b)
Fig. 4. Wind support along the migration routes of 16 geolocator-tracked Arctic terns during (a) southbound and (b) north-
bound migration. Lines show the most likely migration paths coloured according to the wind support in each segment (brown:
headwind, turquoise: tailwind). Directions of arrows indicate gridded wind directions and background heatmap shows wind
speed; both are averaged across the migration period of the tracked Arctic terns. Breeding site in Longyearbyen, Svalbard,
is marked with a black dot
Average wind support (m s–1)
(a) (b)
Fig. 5. Average wind support across the entire
migration route for 16 geolocator-tracked Arc-
tic terns during (a) southbound and (b) north-
bound migration. Wind support along the re-
alised migration routes is shown in dark grey
and reversed routes (spring routes in autumn
and vice versa) are shown in light grey. Box
plots show median values with interquartile
ranges (IQR; boxes), whiskers extend to 1.5×
the IQR, outliers are given as open circles
Mar Ecol Prog Ser 638: 1–12, 2020
during the northbound migration.
Stopover sites of the tracked terns were
located in areas where ocean produc-
tivity was higher (mean ± SD; 6.28 ±
0.43 ln[mg C m−2 d−1]) as compared to
migration corridors (6.03 ± 0.39 ln[mg
C m−2 d−1]; paired t-test: t18 = 3.87, p =
0.001; Fig. 6). Weekly locations of
stopover areas and migration corridors
with the underlying ocean productivity
maps can be found in Fig. S3.
3.4. Migration timing and daylight
In both seasons and particularly in
spring, terns on average crossed the
Equator significantly later than the
equinoxes (autumn average: +12 ± 8 d (SD), t-test:
t15 = 6.402, p < 0.001, spring average: +38 ± 6 d; t-test:
t15 = 23.334, p < 0.001; Fig. 7). Despite the low syn-
chronisation between crossing the Equator and
equinoxes, birds still on average experienced 6985 ±
123 h (SD) of daylight during the annual cycle, which
corresponds to 79.7% of all available daylight on
Earth per year (365 days × 24 h = 8760 h).
In this study, we show that Arctic terns breeding at
78° N in Svalbard migrate to non-breeding sites south
of 63° S in the Weddell Sea covering up to 80 000 km
on their round-trip journeys. This impressive migra-
tion is facilitated by tailwind support along the cho-
sen migration routes in spring, and food-rich stopover
areas for refuelling. Despite the low synchronisation
between Equator crossing and equi noxes, which
would allow for maximizing the experienced daylight
(and thus, the amount of time when birds can forage),
the tracked terns still experienced ca. 80% of all
available daylight hours on the Earth per year, which
is the most by any animal in the world. These findings
suggest that the amount of time when the birds
can feed is not the limiting factor during migration,
but terns rather shift between seasonally specific
Productivity [ln(mg C m–2 day–1)]
OctSep Nov MayApr
Stopover areas
Migration corridors
Southbound migration Northbound migration
Fig. 6. Weekly ocean productivity at stopover areas (black circles) and migration corridors (grey circles) of Arctic terns during
the southbound and northbound migration. Data are mean ± SD
Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun
Fig. 7. Latitude and experienced daylight duration as a function of time across
the annual cycle indicating the underlying phenological patterns of 16 individ-
ually tracked Artic terns. The dashed parts of the black lines indicate the non-
breeding period when birds were exposed to 24 h polar day making latitude
estimates impracticable. Grey dashed line marks the Equator and shaded ar-
eas indicate periods 2 wk on either side of the equinoxes. Daylight duration
was calculated as the time between civil dawn and civil dusk when the geo-
metric centre of the sun is 6° below the horizon
Hromádková et al.: Environmental effects on the longest animal migration
exploitation of tailwind support (in spring) and ocean
areas of high food abundance (particularly in au -
tumn) to facilitate their remarkable migration.
4.1. Migration, non-breeding areas and population
In our study, we did not find differences in migra-
tion patterns between males and females, correspon-
ding to earlier studies on trans-Equatorial migratory
seabirds (Shaffer et al. 2006, Guilford et al. 2009,
Magnusdottir et al. 2012, Mosbech et al. 2012). Arctic
terns from Svalbard migrated to their non-breeding
areas in Antarctica via 2 distinct routes following
either the west coast of Africa or the east coast of
South America; both of these routes are known from
earlier studies (González-Solís et al. 2007, Guilford et
al. 2009, Egevang et al. 2010, Fijn et al. 2013, Volkov
et al. 2017, Alerstam et al. 2019). Similarly, the Wed-
dell Sea, where most of our tracked terns over-win-
tered, has previously been established as a prime
non-breeding area for Arctic terns breeding across
various longitudes in the northern hemisphere
(Egevang et al. 2010, Fijn et al. 2013, McKnight et al.
2013, Volkov et al. 2017).
Terns from our study site on average departed
from Svalbard on 3 September, which is from 1 to
2 mo later than previously shown in studies from
more southerly breeding areas (Table S1; Egevang
et al. 2010, Fijn et al. 2013, Loring et al. 2017,
Volkov et al. 2017, Alerstam et al. 2019, Redfern
& Bevan 2020a). The late departure date of our
tracked individuals corresponds with later depar-
ture of other species from northern latitudes
(Butler et al. 1998, Gilg et al. 2013, Davis et al.
2016). As a general pattern, migratory birds breed-
ing at higher latitudes depart from their breeding
areas later than their southern conspecifics, owing
to the later onset of the breeding season at high
latitudes (Conklin et al. 2010, Briedis et al. 2016).
Similarly, our tracked terns arrived at the breeding
sites later than their conspecifics breeding at more
southern latitudes (Egevang et al. 2010, Fijn et al.
2013, Loring et al. 2017, Volkov et al. 2017, Aler-
stam et al. 2019, Redfern & Bevan 2020a). Such
population-level differences in migration timing
can lead to significant variation in migration
strategies, as different populations face different
environmental conditions en route (González-Solís
et al. 2009, Sittler et al. 2011, Hanssen et al. 2016).
In the case of Arctic terns, Alerstam et al. (2019)
suggested that population-specific migration strate-
gies are driven by intraspecific competition and
different costs of migration. Subsequently,
between-population differences in migration timing
lead to population-specific wintering sites. Com-
parative assessment across populations corresponds
with this hypothesis, as terns from Svalbard arrive
in Antarctica relatively late compared to other
populations and over-winter almost exclusively in
the Weddell Sea. Breeding populations from lower
latitudes arrive in Antarctica relatively earlier and
often over-winter further east in the Indian Ocean
(e.g. Alerstam et al. 2019, Redfern & Bevan 2020b).
We found that terns increased their feeding rate
before arrival at the breeding site in spring
(Fig. 3). At least 2 potential explanations for this
may be brought forward: (1) behavioural changes
regarding increased floating on water. However,
using high-frequency data, McKnight et al. (2013)
showed that Arctic terns spend only a small frac-
tion of time floating on water, deeming this an
unlikely explanation. (2) Birds increased their
feeding frequency before arrival at the breeding
site. Earlier studies confirmed Arctic terns as in -
come breeders (species that primarily use local
resources for egg production; Drent & Daan 1980,
Hobson et al. 2000, Mallory et al. 2017); thus, this
increase in feeding rate should not be attributed
to resource deposition for future egg production.
Moreover, we found that both sexes increased
their feeding rate, further ruling out this behaviour
as part of the capital breeding strategy. Another
explanation for the observed changes in feeding
rate may be attributed to changing conditions in
food availability. When food is abundant, birds
may require less time for feeding (e.g. at the
breeding sites), while when food is scarce it may
require more effort and time to feed. However,
ocean productivity data indicate high food avail-
ability at the place and time when the birds
showed increased feeding rate, implying that food
availability may not be the main driver behind the
observed pattern. A more likely explanation may
be preparation against the forthcoming reduction
in feeding time due to courtship behaviour and
incubation. This explanation is also supported by
the reduced number of times when the birds were
in water after their arrival at the breeding sites,
suggesting that birds could at least partially be
using previously stored reserves for body mainte-
nance during egg incubation. Moreover, body
mass of the tagged individuals captured during
incubation showed a decline of 0.75 g d1over the
capturing period, further supporting this premise.
Mar Ecol Prog Ser 638: 1–12, 2020
4.2. Migration patterns and the environment
Our findings suggest that the terns benefit from
using a looped migration strategy where southbound
and northbound migration routes do not overlap. By
adapting the migration routes to the prevailing wind
patterns across the Atlantic Ocean, Arctic terns take
advantage of tailwind support en route. During the
autumn migration, wind support along the 2 main
autumn migration flyways —southeastern and south-
western Atlantic is essentially different. The over-
all net wind support during the autumn migration
was negligible, and individuals migrating through
the southeastern Atlantic generally experienced
more headwinds. Following this flyway may have a
trade-off between relying on wind support and
fuelling at food-rich stopovers, as ocean productivity
in the southeastern Atlantic during this time of year is
higher compared to the southwestern Atlantic (i.e.
the coasts of Brazil; Fig. S3a−k).
Wind support was particularly pronounced during
the northbound migration when strong tailwinds
likely contributed to the exceptionally fast travel
speed of terns: a 1.5-fold increase compared to travel
speed during the southbound migration (Fig. 4, Box 1;
sensu Kemp et al. 2010). Similar increases in seasonal
travel speed have also been found in other seabirds
(Felicísimo et al. 2008, González-Solís et al. 2009). In
contrast, Hensz (2015) did not find wind to be a signif-
icant predictor for travel speed during either south-
bound or northbound migration of Arctic terns. Wind
exploitation might also be used in combination with a
fly-and-forage strategy (Strandberg & Alerstam 2007)
to further increase travel speed. A fly-and-forage mi-
gration strategy is advantageous when an individual
carries enough energy reserves from the non-breed-
ing grounds and does not need to frequently refuel at
stopovers (Strandberg & Alerstam 2007).
Stopover use, however, seems to play a more
important role in route choice during the southbound
migration. Tracked birds navigated between stop -
over sites of high ocean productivity with migration
corridors passing over areas of lower productivity
(Fig. 6 & Fig. S3). Such patterns in Arctic terns were
first documented by McKnight et al. (2013) as birds
from Alaska migrated along the west coast of the
Americas. Similar patterns were described in a study
where terns were tracked from Greenland and Ice-
land (Hensz 2015). During both migration periods,
one of the main stopover areas of our tracked birds
corresponded with the well-known refuelling area
for migrating seabirds in the North Atlantic (Catry et
al. 2011, Sittler et al. 2011, Gilg et al. 2013), also
known as the North Atlantic drift province
(Longhurst 2010). According to Bourne & Casement
(1996), Arctic terns are present in the area from late
April until late October, with a distinct peak in
August. This time window corresponds with breed-
ing site departure dates of terns from lower (Egevang
et al. 2010, Fijn et al. 2013, Loring et al. 2017, Volkov
et al. 2017) and higher latitudes (our study; Box 1).
Because terns are exclusively diurnal foragers
(McKnight et al. 2013), we predicted that they will
time their migration to cross the Equator close to the
autumnal and vernal equinoxes, thus experiencing
the longest foraging hours (Alerstam 2003). How-
ever, during both migration seasons, terns crossed
the Equator significantly later than the equinoxes,
suggesting that available daylength is not a limiting
factor during migration. The large variation we
observed in Equator crossing dates of the tracked
terns suggests that crossing time is rather flexible.
Furthermore, on southbound migration, Arctic terns
from a breeding site in Sweden crossed the Equator
almost 2 mo earlier than terns in our study (Alerstam
et al. 2019; Table S1). Such population differences
indicate that the timing of crossing the Equator on a
population level is mainly influenced by the timing of
departure from breeding sites rather than by envi-
ronmental conditions.
Collectively, our findings suggest that the slower
southbound migration is primarily guided by com-
muting between food-rich stopovers, whereas the
faster spring migration is adapted to take advantage
of the prevailing wind patterns to facilitate a shorter
migration duration. Disentangling the influence of
environmental drivers behind seasonal migration
strategies of Arctic terns brings us a step closer to
understanding the ecology of the world’s longest ani-
mal migration. Our results provide a means to better
understand the delicate relationship between sea-
sonal migration strategies of birds and variation in
environmental conditions, which may be disrupted
by the ongoing global climate change.
Acknowledgements. We thank all of our field assistants for
their help in locating and capturing birds, Simeon Lisovski
for help with processing wind data, and Radka Piálková for
guidance in the lab. We also thank the Czech Arctic Scien-
tific Infrastructure of the University of South Bohemia in
>eské Budeˇ jovice − the Josef Svoboda Station in Svalbard
(CzechPolar2 project LM2015078 supported by the Ministry
of Education, Youth and Sports of the Czech Republic) for
housing us during the field season. Financial support was
provided by the Palacky University Endowment Fund (to
M.B.), by the Ministry of Education, Youth and Sports of the
Czech Republic (LM2015078 to T.H. and V.P.), Grant
Hromádková et al.: Environmental effects on the longest animal migration
Agency of the University of South Bohemia (GAJU n. 04-
151/2016/P and n. 048/2019/P to T.H.), The Explorers Club
Exploration Fund Grant (to T.H.) and the Latvian Council
of Science (LZP/2019/45 to M.B.). All experiments were
conducted according to Norwegian law. The study was
approved by the Norwegian Food Safety Authority (ref.
number 19/69972) and by the Governor of Svalbard (ref.
number 17/00693-8) and is registered in the Research in
Svalbard database (RiS ID 10805).
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Editorial responsibility: Stephen Wing,
Dunedin, New Zealand
Submitted: October 31, 2019; Accepted: February 25, 2020
Proofs received from author(s): March 13, 2020
... Trans-equatorial migratory seabirds cover vast distances at sea, with the Arctic Tern (Sterna paradisaea) known for the longest migration of any organism (Egevang et al. 2010;Fijn et al. 2013;Wong et al. 2021). Using miniaturized light-level geolocators, researchers have shown that Arctic Terns display seasonally distinct migration strategies Hromádková et al. 2020) and that individuals from distant breeding colonies can share similar migration routes (Wong et al. 2021). However, these studies have primarily focused on inferring population-level movements of Arctic Terns and identifying key marine habitats used in migration (Egevang et al. 2010;Fijn et al. 2013;McKnight et al. 2013;U.S. Fish & Wildlife Service 2013;Alerstam et al. 2019;Hromádková et al. 2020;Redfern and Bevan 2020;Wong et al. 2021), with less attention paid to the potential effects of latitudinal differences in breeding sites and individuals' physical characteristics on migratory behavior and phenology. ...
... Using miniaturized light-level geolocators, researchers have shown that Arctic Terns display seasonally distinct migration strategies Hromádková et al. 2020) and that individuals from distant breeding colonies can share similar migration routes (Wong et al. 2021). However, these studies have primarily focused on inferring population-level movements of Arctic Terns and identifying key marine habitats used in migration (Egevang et al. 2010;Fijn et al. 2013;McKnight et al. 2013;U.S. Fish & Wildlife Service 2013;Alerstam et al. 2019;Hromádková et al. 2020;Redfern and Bevan 2020;Wong et al. 2021), with less attention paid to the potential effects of latitudinal differences in breeding sites and individuals' physical characteristics on migratory behavior and phenology. ...
... Southbound migratory behavior appears to be driven primarily by the phenology and distribution of food-rich marine stopover sites, with terns stopping frequently to refuel . In contrast, during the northbound migration, terns use strong tailwinds to travel back to their breeding grounds quickly, a pattern presumably driven by a need to secure favorable nesting sites and initiate breeding as early as possible (Hromádková et al. 2020). Many other long-distance migratory birds have faster northbound than southbound migrations and take migration routes that favor foraging or weather conditions (Nilsson et al. 2013;Hahn et al. 2014;Horton et al. 2016). ...
Full-text available
Arctic Terns (Sterna paradisaea) share a few routes to undertake the longest annual migrations of any organism. To understand how the wide spatial range of their breeding colonies may affect their migration strategies (e.g., departure date), we tracked 53 terns from five North American colonies distributed across 30° of latitude and 90° of longitude. While birds from all colonies arrived in Antarctic waters at a similar time, terns nesting in the Arctic colonies migrated back north more slowly and arrived to their breeding grounds later than those nesting in the colony farther south. Arrival dates in Antarctic waters coincided with the start of favorable foraging conditions (i.e., increased ocean productivity), and similarly arrival dates at breeding colonies coincided with the start of local favorable breeding conditions (i.e., disappearance of snow and ice). Larger birds followed a more direct southbound migration route than smaller birds. On both southbound and northbound migrations, daily distances traveled declined as time spent in contact with the ocean increased, suggesting a trade-off between resting/foraging and traveling. There was more unexplained variation in behavior among individuals than among colonies, and one individual had a distinctive stop around Brazil. Terns nesting in the Arctic have a narrow time window for breeding that will likely increase with continuing declines in sea ice and snow. Departing Arctic Terns likely have few clues about the environmental conditions they will encounter on arrival, and their response to environmental changes at both poles may be assisted by large individual variation in migration strategy.
... Gilg et al. 2013), and Arctic terns appear to be a good model for understanding pelagic, offshore migration due to their wide geographic extent across different oceanic zones and remote environments. Studies to date sug-gest that understanding Arctic tern migration could be useful to inform the timing of migration with shifting oceanic productivity (McKnight et al. 2013) and broader environmental drivers of pelagic migration (Hromádková et al. 2020). Most studies of migratory behaviour of Arctic terns have focused on those marked on breeding colonies in Europe (Fijn et al. 2013, Hromádková et al. 2020, Redfern & Bevan 2020, Greenland (Egevang et al. 2010), or the USA (McKnight et al. 2013, US Fish & Wildlife Service 2013, Duffy et al. 2014. ...
... Studies to date sug-gest that understanding Arctic tern migration could be useful to inform the timing of migration with shifting oceanic productivity (McKnight et al. 2013) and broader environmental drivers of pelagic migration (Hromádková et al. 2020). Most studies of migratory behaviour of Arctic terns have focused on those marked on breeding colonies in Europe (Fijn et al. 2013, Hromádková et al. 2020, Redfern & Bevan 2020, Greenland (Egevang et al. 2010), or the USA (McKnight et al. 2013, US Fish & Wildlife Service 2013, Duffy et al. 2014. No migration information existed to date from Arctic terns breeding in Canada, despite the importance of the Canadian Arctic to their widespread distribution (Gaston et al. 2012, Hatch et al. 2020) and observed declines in some Canadian breeding colonies (Gilchrist & Robertson 1999, Maftei et al. 2015, Mallory et al. 2018. ...
... We investigated patterns in the southbound and northbound migration routes used by Arctic terns, including the first recorded routes for Canadian Arctic terns and the first record of northbound migration routes for an Alaskan population of Arctic terns. We compared our findings to those from colonies on Svalbard (Norway; Hromádková et al. 2020), the Baltic Sea (Sweden; Alerstam et al. 2019), the Netherlands (Fijn et al. 2013), Greenland and Iceland (Egevang et al. 2010 ...
The Arctic tern is an iconic seabird, famous for its annual migrations between the Arctic and the Antarctic. Its wide geographical range has impeded knowledge of potential population bottlenecks during its annual bi-hemispheric movements. Although Arctic terns breed in the Pacific, Atlantic, and Arctic coasts of North America, few tracking studies have been conducted on North American Arctic terns, and none in Canada, which represents a significant proportion of their circumpolar breeding range. Using light-level geolocators, we tracked 53 Arctic terns from 5 breeding colonies across a wide latitudinal and longitudinal range within North America. We compared the routes taken by birds in our study and migration timing to those previously tracked from Greenland, Iceland, The Netherlands, Sweden, Norway, Maine (USA), and S. Alaska (USA). Most Arctic terns tracked globally used one of 3 southbound migration routes: (1) Atlantic West Africa; (2) Atlantic Brazil; and (3) Pacific coastal, and one of 2 northbound migration routes: (1) Mid-ocean Atlantic and (2) Mid-ocean Pacific. Some other trans-equatorial seabirds also used these migration routes, suggesting that Arctic tern routes may be important for other species. The migration timing for southbound and northbound migrations was generally different between tracked tern colonies worldwide but generally fell within a 1-2 mo window. Our research suggests that conservation management of Arctic terns during their migration should dynamically adapt with the times of the year that terns use parts of their route. Future identification of common multi-species seabird flyways could aid the international negotiations required to conserve pelagic seabirds such as Arctic terns.
... This pattern differs from other seabirds that follow similar migratory paths. For instance, Arctic terns migrate 1.5 times faster in spring than in fall while covering similar distances (Egevang et al. 2010, Hromádková et al. 2020. The slower travel speed in spring and the higher number of daily immersions (more time in contact with saltwater) compared to fall provide evidence that jaegers adopt some sort of flyand-forage migration strategy in spring (Strandberg & Alerstam 2007). ...
... We reported for the first time migratory movements of long-tailed jaegers breeding in the Canadian Arctic. Only a few arctic seabirds are long-distance trans-equatorial migrants like long-tailed jaegers (Egevang et al. 2010, Stenhouse et al. 2012, Davis et al. 2016, Hromádková et al. 2020. Although several of these species share similar migratory paths and stop over areas (Davies et al. 2021), the optimal migration strategies appear species specific. ...
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Long-distance migratory seabirds need to adjust their migration strategy according to internal (breeding, molting) and external factors (seasonality, resource availability). Time-minimizing strategies are common during spring migration to arrive at the optimal time to breed. We studied the annual movements and migration strategy of the long-tailed jaeger Stercorarius longicaudus, a small arctic-nesting seabird. First, we documented year-round movements (routes, wintering sites) of male and female jaegers breeding in the Canadian Arctic. We then compared their migration strategies between seasons (phenology, stopover use, travel distance, speed) to determine whether they adopt a time-minimizing strategy in spring. Over 6 years, we collected 43 tracks from geolocators deployed on Bylot and Igloolik islands. Jaegers departed the breeding site over a 5-week period and traveled on average 32375 km (round trip) before returning to breed, one of the longest documented migrations on Earth. Birds used a major stopover area east of the Grand Banks of Newfoundland in spring and fall, and wintered in high marine productivity areas of the South Atlantic. Unexpectedly, the spring migration was 40% longer and 32% slower than in fall and birds increased their time spent on water (foraging and/or resting) by 61%. A time-minimizing strategy in fall may help to reach the wintering site rapidly and start molting early. In spring, a fly-and-forage strategy seems to be adopted to increase foraging effort, probably for the accumulation of body reserves before breeding and in anticipation of unfavorable conditions that may prevail at arrival on their arctic breeding site.
... Interestingly, we found that the tracked birds of a given colony and species generally used preferred routes and reached specific wintering areas instead of dispersing in all possible directions from the colony (Figs. 5 & S4). Similar results have been found in previous studies on the same species (Hatch et al. 2010, Frederiksen et al. 2012, Mosbech et al. 2012, Fayet et al. 2016, Merkel et al. 2021 and in many other seabird species such as Arctic terns, long-tailed skuas, sooty shearwaters and wandering albatrosses (Shaffer et al. 2006, Weimerskirch et al. 2015, van Bemmelen et al. 2017, Hromádková et al. 2020. Seabird migration patterns therefore did not match the dispersive migration definition (Newton 2007). ...
... In particular, birds reaching the North-West Atlantic travelled along South-East Greenland in the autumn and came back by crossing the Atlantic Ocean south from Iceland. These routes are likely to follow wind and current regimes, which may reduce the energetic costs of migration and ultimately shape the geographic distribution of birds in the non-breeding season (Adams & Flora 2010, Hromádková et al. 2020. The fact that several species share the same migration routes also increases the need to consider protection of 'migratory corridors' as a broader ecosystem unit rather than species-specific routes and areas. ...
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Bird migration is commonly defined as a seasonal movement between breeding and non-breeding grounds. It generally involves relatively straight and directed large-scale movements, with a latitudinal change, and specific daily activity patterns comprising less or no foraging and more traveling time. Our main objective was to describe how this general definition applies to seabirds. We investigated migration characteristics of 6 pelagic seabird species (little auk Alle alle, Atlantic puffin Fratercula arctica, common guillemot Uria aalge, Brünnich’s guillemot U. lomvia, black-legged kittiwake Rissa tridactyla and northern fulmars Fulmarus glacialis). We analysed an extensive geolocator positional and saltwater immersion dataset from 29 colonies in the North-East Atlantic and across several years (2008−2019). We used a novel method to identify active migration periods based on segmentation of time series of track characteristics (latitude, longitude, net-squared displacement). Additionally, we used the saltwater immersion data of geolocators to infer bird activity. We found that the 6 species had, on average, 3 to 4 migration periods and 2 to 3 distinct stationary areas during the non-breeding season. On average, seabirds spent the winter at lower latitudes than their breeding colonies and followed specific migration routes rather than non-directionally dispersing from their colonies. Differences in daily activity patterns were small between migratory and stationary periods, suggesting that all species continued to forage and rest while migrating, engaging in a ‘fly-and-forage’ migratory strategy. We thereby demonstrate the importance of habitats visited during seabird migrations as those that are not just flown over, but which may be important for re-fuelling.
... animal migration should depend on how individuals adjust behaviors between and within seasons [2], because changing behaviors as weather and ecological variables vary along the route can reduce the costs of migration [3,4] and even lead to the avoidance of hazardous weather events to ensure survival [5]. Although mechanistic explanations of decision-making remain unclear [6], research on birds has shown that individuals can select favorable winds [5,7,8], weather [9,10], flight altitudes [11], routes [12,13] and stopover frequency [14] and sites [15,16]. Between years, changes in migratory timing for several species have also been documented [e.g. ...
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Background Birds that forage while covering distance during migration should adjust traveling behaviors as the availability of foraging habitat changes. Particularly, the behavior of those species that depend on bodies of water to find food yet manage to migrate over changing landscapes may be limited by the substantial variation in feeding opportunities along the route. Methods Using GPS tracking data, we studied how traveling behaviors vary with available foraging habitat during the long-distance migration of Caspian terns (Hydroprogne caspia), a bird with a specialized diet based on fish that needs bodies of water to forage. We measured individual variation in five traveling behaviors related to foraging along the route and used linear mixed effects models to test the following variables as predictors of traveling behaviors: proportion of overlap with water bodies, weather conditions, days at previous stopover and days of migration. Also, we tested if during traveling days flight height and speed varied with time of day and if birds were in areas with greater proportion of water bodies compared to what would be expected by chance from the landscape. Results We found variation in migratory traveling behaviors that was mainly related to the proportion of overlap with water bodies and experienced tailwinds. Suggesting a mixed migratory strategy with fly-and-foraging, Caspian terns reduced travel speed, flew fewer hours of the day, had lower flight heights and increased diurnal over nocturnal migratory flight hours as the proportion of overlap with water bodies increased. Birds had lower flight speeds and higher flight heights during the day, were in foraging habitats with greater proportions of water than expected by chance but avoided foraging detours. Instead, route tortuosity was associated with lower wind support and cloudier skies. Conclusions Our findings show how birds may adjust individual behavior as foraging habitat availability changes during migration and contribute to the growing knowledge on mixed migratory strategies of stopover use and fly-and-forage.
... Because wind has a strong impact on flight costs [5] such prevailing winds and other persistent circulation patterns can create reliable freeways as well as persistent blockades for aerial migrants at regional to continental scales [6][7][8][9][10]. Studies integrating biologging data with atmospheric models generally reveal some alignment of seasonal loop migrations with prevailing winds across marine [11][12][13] as well as terrestrial environments [14][15][16][17]. For landbirds this is especially true over ecological barriers -where exhaustion from battling adverse winds can have lethal consequences [18][19][20]. ...
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Background Route choice and travel performance of fly-forage migrants are partly driven by large-scale habitat availability, but it remains unclear to what extent wind support through large-scale wind regimes moulds their migratory behaviour. We aimed to determine to what extent a trans-equatorial fly-forage migrant engages in adaptive drift through distinct wind regimes and biomes across Africa. The Inter-tropical Front (ITF) marks a strong and seasonally shifting climatic boundary at the thermal equator, and we assessed whether migratory detours were associated with this climatic feature. Furthermore, we sought to disentangle the influence of wind and biome on daily, regional and seasonal travel performance. Methods We GPS-tracked 19 adult Eleonora’s falcons Falco eleonorae from the westernmost population on the Canary Islands across 39 autumn and 36 spring migrations to and from Madagascar. Tracks were annotated with wind data to assess the falcons’ orientation behaviour and the wind support they achieved in each season and distinct biomes. We further tested whether falcon routes across the Sahel were correlated with the ITF position, and how realized wind support and biome affect daily travel times, distances and speeds. Results Changes in orientation behaviour across Africa’s biomes were associated with changes in prevailing wind fields. Falcons realized higher wind support along their detours than was available along the shortest possible route by drifting through adverse autumn wind fields, but compromised wind support while detouring through supportive spring wind fields. Movements across the Sahel-Sudan zone were strongly associated to the ITF position in autumn, but were more individually variable in spring. Realized wind support was an important driver of daily travel speeds and distances, in conjunction with regional wind-independent variation in daily travel time budgets. Conclusions Although daily travel time budgets of falcons vary independently from wind, their daily travel performance is strongly affected by orientation-dependent wind support. Falcons thereby tend to drift to minimize or avoid headwinds through opposing wind fields and over ecological barriers, while compensating through weak or supportive wind fields and over hospitable biomes. The ITF may offer a climatic leading line to fly-forage migrants in terms of both flight and foraging conditions.
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Many animals are highly mobile and have evolved long-distance migrations that make them actors in multiple ecosystems through the year and throughout their life. Most long-distance migrations are adaptations to seasonality and more generally to spatio-temporal patterns in food availability, weather, risk of parasite and pathogen infections, and predation risk. Due to the considerable seasonality in high-latitude environments, with Arctic as extremes, long-distance seasonal migrations are a distinct characteristic of the fauna in these Northern regions. The Arctic is also a seasonal melting pot during the productive summer, when large numbers of organism move in from all over the world. Travelling animals connect ecosystems and serve as spatial vectors, of energy and nutrients and of other organisms that follow (sometimes as active hitchhikers) for parts or the entire route. We provide an overview of central concepts and main spatial and temporal (phenology) patterns of animal migrations, with a focus on migrations to and from as well as within northern regions (i.e. arctic and sub-arctic regions). In particular, we characterize the role of migratory animals as vectors and hosts for infectious agents, and we discuss the concepts of migratory escape, migratory culling, and migratory separation. Understanding drivers and patterns of migrations is essential for understanding the dynamics of diseases and must therefore be considered in veterinary and human medicine and the One Health perspective. We show how climate change and human stressors impact migrations and how these changes may interact with the animals’ capacity to transport parasites and other infectious agents. Throughout, we stress the evolutionary ecology of migrations, a plastic trait under natural selection with complex ecological consequences.
Elucidating the ecological factors underpinning migratory strategies of seabirds is necessary for understanding resilience to environmental change. Arctic terns Sterna paradisaea breed in the Northern Hemisphere and are unique for the global scale of their migration. Geolocator data from 37 Arctic terns breeding in a low-latitude colony, 10 of which were re-tagged in successive years, were analysed to characterise their migratory behaviour and to test the hypothesis that individuals have repeatable migration strategies. Seawater immersion data suggested a fly-forage strategy, with birds remaining on the wing at night and only foraging during daylight. Southward movement was focused initially along Atlantic eastern-boundary upwelling systems. Most terns then reoriented eastwards, crossing the southern Indian Ocean before moving south to the Antarctic. Foraging intensity differed between migration phases. Indian Ocean foraging locations were diverse, and less frequent over deep ocean basins. Foraging intensity was highest in the later stages of return migration, particularly in and around the Azores Confluence Zone. High movement speeds and foraging intensity on return migration may be adaptations to optimise reproductive success. Some aspects of migration phenology were repeatable between years, but trajectories were displaced by wind. Repeat birds did not use the same foraging areas in different years, and their trajectories across the Indian Ocean also differed. The results of this study suggest that the Indian Ocean crossing is a behaviour pattern, surviving since the last ice age, enabling Arctic terns breeding at low-latitude northwest European colonies to arrive at fragmenting Antarctic sea ice when foraging conditions are suitable.
The ever-increasing prevalence of antibiotic-resistant bacteria, primarily due to the frequent use and misuse of antibiotics, is an issue of serious global concern. Migratory birds have a significant role in dissemination of antibiotic-resistant bacteria (ARB), as they acquire resistant bacteria from reservoirs and transport them to other environments which are relatively less influenced by anthropogenically. We have investigated the prevalence of ARB in a long-distance migratory bird, the Arctic tern (Sterna paradisaea) captured from the Svalbard Archipelago. The birds were tagged with geolocators to track their extraordinary long migration, and the cloacal samples were collected before the migration and after the migration by recapturing the same birds. The tracking of 12 birds revealed that during the annual cycle they underwent a total of 166 stopovers (11–18, mean = 3.8) and recovery points along the Atlantic coast. Twelve major bacterial genera were identified from Arctic tern cloacal samples, which are dominated by Staphylococcus spp. and Aerococcus spp. The bacterial isolates showed resistance against 16 antibiotics (before migration) and 17 antibiotics (after migration) out of 17 antibiotics tested. Resistance to β-lactam and quinolone class of antibiotics were frequent among the bacteria. The study highlights the potential role of Arctic tern in the dissemination of multidrug resistant bacteria across far and wide destinations, especially to the polar environments.
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Nesting birds often respond to human disturbance as to a predatory act. In the case of the high Arctic, the disturbance of incubating birds may bring further complications due to egg cooling. In addition, it is assumed that birds in the high Arctic are not shy and do not respond to human presence fearfully. We tested how quickly the Arctic terns (Sterna paradisaea) nesting in two colonies in Svalbard return to the nest after human disturbance. One colony was situated inside a town where the terns were regularly harassed by human presence. The second colony was on a glacial foreland where breeding terns have limited experience with humans. We found that terns without frequent experience with humans returned to the nest about 5 min after disturbance, while urban terns habituated to human presence returned within a few tens of seconds. The urban terns in this way likely solve the risk of spending too much time off the nest, which could lead under the conditions of the high Arctic to the stopping of embryogenesis. Terns from a remote colony do not show lower hatching success of their eggs than the urban ones, however, incubation and the whole population of terns could be threatened when there is more frequent disturbance by researchers or tourists.
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The arctic tern Sterna paradisaea completes the longest known annual return migration on Earth, traveling between breeding sites in the northern arctic and temperate regions and survival/molt areas in the Antarctic pack‐ice zone. Salomonsen (1967, Biologiske Meddelelser, Copenhagen Danske Videnskabernes Selskab, 24, 1) put forward a hypothetical comprehensive interpretation of this global migration pattern, suggesting food distribution, wind patterns, sea ice distribution, and molt habits as key ecological and evolutionary determinants. We used light‐level geolocators to record 12 annual journeys by eight individuals of arctic terns breeding in the Baltic Sea. Migration cycles were evaluated in light of Salomonsen's hypotheses and compared with results from geolocator studies of arctic tern populations from Greenland, Netherlands, and Alaska. The Baltic terns completed a 50,000 km annual migration circuit, exploiting ocean regions of high productivity in the North Atlantic, Benguela Current, and the Indian Ocean between southern Africa and Australia (sometimes including the Tasman Sea). They arrived about 1 November in the Antarctic zone at far easterly longitudes (in one case even at the Ross Sea) subsequently moving westward across 120–220 degrees of longitude toward the Weddell Sea region. They departed from here in mid‐March on a fast spring migration up the Atlantic Ocean. The geolocator data revealed unexpected segregation in time and space between tern populations in the same flyway. Terns from the Baltic and Netherlands traveled earlier and to significantly more easterly longitudes in the Indian Ocean and Antarctic zone than terns from Greenland. We suggest an adaptive explanation for this pattern. The global migration system of the arctic tern offers an extraordinary possibility to understand adaptive values and constraints in complex pelagic life cycles, as determined by environmental conditions (marine productivity, wind patterns, low‐pressure trajectories, pack‐ice distribution), inherent factors (flight performance, molt, flocking), and effects of predation/piracy and competition. The arctic tern is probably the animal that performs the longest known migrations. We used geolocator tracking data from a population of arctic terns from the Baltic Sea for evaluating the ecology and evolution of its long‐distance pelagic migration. We also compared with results from geolocator studies of arctic tern populations from Greenland, Netherlands, and Alaska. This comparison revealed unexpected segregation in time and space between tern populations in the same flyway.
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1.Light‐level geolocator tags use ambient light recordings to estimate the whereabouts of an individual over the time it carries the device. Over the past decade, these tags have emerged as an important tool and have been used extensively for tracking animal migrations, most commonly small birds. 2.Analysing geolocator data can be daunting to new and experienced scientists alike. Over the past decades, several methods with fundamental differences in the analytical approach have been developed to cope with the various caveats and the often complicated data. 3.Here we explain the concepts behind the analyses of geolocator data and provide a practical guide for the common steps encompassing most analyses—annotation of twilights, calibration, estimating and refining locations, and extraction of movement patterns—describing good practices and common pitfalls for each step. 4.We discuss criteria for deciding whether or not geolocators can answer proposed research questions, provide guidance in choosing an appropriate analysis method, and introduce key features of the newest open‐source analysis tools. 5.We provide advice for how to interpret and report results, highlighting parameters that should be reported in publications and included in data archiving. 6.Finally, we introduce a comprehensive supplementary online manual that applies the concepts to several datasets, demonstrates the use of open‐source analysis tools with step‐by‐step instructions and code, and details our recommendations for interpreting, reporting and archiving. This article is protected by copyright. All rights reserved.
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Currently, the deployment of tracking devices is one of the most frequently used approaches to study movement ecology of birds. Recent miniaturisation of light‐level geolocators enabled studying small bird species whose migratory patterns were widely unknown. However, geolocators may reduce vital rates in tagged birds and may bias obtained movement data. There is a need for a thorough assessment of the potential tag effects on small birds, as previous meta‐analyses did not evaluate unpublished data and impact of multiple life‐history traits, focused mainly on large species and the number of published studies tagging small birds has increased substantially. We quantitatively reviewed 549 records extracted from 74 published and 48 unpublished studies on over 7,800 tagged and 17,800 control individuals to examine the effects of geolocator tagging on small bird species (body mass <100 g). We calculated the effect of tagging on apparent survival, condition, phenology and breeding performance and identified the most important predictors of the magnitude of effect sizes. Even though the effects were not statistically significant in phylogenetically controlled models, we found a weak negative impact of geolocators on apparent survival. The negative effect on apparent survival was stronger with increasing relative load of the device and with geolocators attached using elastic harnesses. Moreover, tagging effects were stronger in smaller species. In conclusion, we found a weak effect on apparent survival of tagged birds and managed to pinpoint key aspects and drivers of tagging effects. We provide recommendations for establishing matched control group for proper effect size assessment in future studies and outline various aspects of tagging that need further investigation. Finally, our results encourage further use of geolocators on small bird species but the ethical aspects and scientific benefits should always be considered.
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In the western North Atlantic, Common (Sterna hirundo) and Arctic (S. paradisaea) Terns are sympatric at breeding colonies but show divergent migration strategies to coastal areas of South America and pelagic regions of the Antarctic, respectively. During 2013, we studied postbreeding movements of adult Common (n = 130) and Arctic (n = 52) Terns from four breeding colonies in the eastern USA and Canada using digital very high frequency (VHF) transmitters and an array of 62 automated radio telemetry towers. Relative to hatch dates at respective colonies, Arctic Terns departed breeding sites an average of eight days later than Common Terns. Common Terns were detected during the postbreeding period by coastal towers upward of 850 km south of their original nesting sites. The telemetry array detected postbreeding movements of Arctic Terns from the Petit Manan Island colony in the Gulf of Maine as they traveled eastward past Nova Scotia, Canada, mostly during the night. Nantucket Sound, Massachusetts, USA was identified as an important staging area for Common Terns from all colonies, whereby 26% of 53 tagged Common Terns from colonies in the Gulf of Maine and Canada were detected for up to three weeks. Common Terns typically arrived at Nantucket Sound within 2 h of sunset, 2 to 10 days after their last detection at Gulf of Maine and Canadian colonies, suggesting rapid postbreeding dispersal. Postbreeding dispersal of Arctic Terns was poorly documented with the telemetry array, suggesting that this species is not using coastal sites for staging, and is instead departing directly from colonies to offshore staging areas prior to long-distance migrations. We conclude that digital VHF telemetry is a useful method for monitoring regional movements of Common Terns, but additional offshore receiving stations are needed to effectively monitor movements of Arctic Terns away from their nesting colonies.
Arctic Terns spend their breeding and non‐breeding seasons in polar environments at opposite ends of the world. The sensitivity of polar regions to climate change makes it essential to understand the ecology of Arctic Terns but the remoteness of the Antarctic presents a considerable challenge. One solution is to use ‘biologgers’ to monitor remotely their behaviour and distribution in the Antarctic. Data from birds tagged with light‐level global location sensors (geolocators) in 2015 and 2017 showed that a third of their annual cycle was spent amongst Antarctic sea ice. After reaching the East Antarctic in the austral spring, they gradually moved west, foraging in fragmented ice zones of the Antarctic coastline, leaving in the austral autumn for their return northward migration via the Atlantic. Changes in patterns of movement between phases of 24‐h daylight and diel day/night conditions were likely linked to the annual moult, and stable isotope analyses suggest that krill (Euphausia species) was an important component of their diet. There were marked differences in movement behaviour between Arctic Terns tagged in 2015 compared to 2017 that may relate to unusual changes in sea‐ice extent. The Arctic Tern may be unique amongst seabirds that utilise the Antarctic environment in summer in being able to move widely without nesting constraints, and may present a means of characterising the effects of climate change on species dependent for foraging on Antarctic sea‐ice and krill. This article is protected by copyright. All rights reserved.
We investigated the use of stable-isotope analysis as a direct means of tracing allocation of endogenous protein and lipid reserves to reproduction in five gulls (Larus canus, L. delawarensis, L. californicus, L. argentatus, L. philadelphia), four terns (Sterna caspia, S. hirundo, S. paradisaea, Chlidonias niger), and one jaeger (Stercorarius parasiticus) breeding on Great Slave Lake (GSL) in the Northwest Territories. Our approach was based on assumptions that (1) body tissues of birds just arriving at GSL from their assumed marine-associated wintering habitats would have stable-isotope ratios more enriched than those of birds in equilibrium with the local GSL foodweb, and (2) mobilization of these reserves to reproduction could be traced by the isotopic measurement of egg macronutrients. As predicted, the pectoral muscle of six species of arriving birds was more enriched in 13C (x̄ = −21.5‰) and 15N (x̄ = 12.7‰) than was that of postbreeding birds (13C, x̄ = −23.5‰; 15N, x̄ = 9.9‰) or hatching-year birds raised at GSL (13C, x̄ = −24.3‰; 15N, x̄ = 9.0‰). Abdominal fat of arriving Herring Gulls and Mew Gulls was more enriched in 13C (x̄ = −19.7‰) than the fat of other species (x̄ = −23.4‰), indicating lipids of marine origin. We compared isotope values of the local GSL foodweb with dietary values predicted from isotope measurements of egg macronutrients if diets were entirely derived at GSL. Isotopic analysis of lipid-free egg yolk, yolk lipid, and shell carbonate suggested that for most species, little if any endogenous protein reserves were used for reproduction, with the possible exception of Caspian Terns, whose egg protein and egg lipid values, and Common Terns, whose egg protein values, were more enriched in 13C than those of the other species. Although endogenous nutrient reserves likely were important to birds during migration and the initial settling period at GSL, local food supplies were adequate to provide nutrients for reproduction.
It is often implicitly assumed that seabirds migrate using marine environments, but this assumption is increasingly being challenged by electronic tracking data. The arrival and departure routes of Arctic Terns breeding on the North Sea coast of the United Kingdom (UK) are unknown but there has been speculation about the possibility of overland migration. Analysis of light‐level geolocator data from birds breeding on the Farne Islands suggests that these birds arrived and left their North Sea colony overland via the Irish Sea, rather than taking coastal routes along the east coast of the UK and through the English Channel. In addition, some departing birds may enter the North Atlantic by crossing Ireland rather than through the Irish Sea. The direction of arrival in spring had a more‐southerly orientation than the direction of autumn departure. The geolocator data allow migration phenology in relation to breeding to be defined and indicated that the birds arrived around 15 days before the first eggs were laid in the colony. Departure timing may be determined by seasonal progression and not markedly influenced by breeding success. This study supports the idea that overland migration may be a more widespread and consistent strategy for seabirds than has been realised. This article is protected by copyright. All rights reserved.
This book presents an in-depth discussion of the biological and ecological geography of the oceans. It synthesizes locally restricted studies of the ocean to generate a global geography of the vast marine world. Based on patterns of algal ecology, the book divides the ocean into four primary compartments, which are then subdivided into secondary compartments. *Includes color insert of the latest in satellite imagery showing the world's oceans, their similarities and differences *Revised and updated to reflect the latest in oceanographic research *Ideal for anyone interested in understanding ocean ecology -- accessible and informative.