Content uploaded by Tibor Szép
Author content
All content in this area was uploaded by Tibor Szép on Feb 11, 2017
Content may be subject to copyright.
114
Discovering the migration and non-breeding areas of sand martins
and house martins breeding in the Pannonian basin (central-eastern
Europe)
Tibor Szép, Felix Liechti, Károly Nagy, Zsolt Nagy and Steffen Hahn
T. Szép, Inst. of Environmental Science, Univ. of Nyíregyháza, Nyíregyháza, Hungary. – F. Liechti (felix.liechti@vogelwarte.ch) and S. Hahn,
Dept of Bird Migration, Swiss Ornithological Inst., Sempach, Switzerland. – K. Nagy and Z. Nagy, MME/BirdLife, Budapest, Hungary.
e central-eastern European populations of sand martin and house martin have declined in the last decades. e driv-
ers for this decline cannot be identified as long as the whereabouts of these long distance migrants remain unknown
outside the breeding season. Ringing recoveries of sand martins from central-eastern Europe are widely scattered in the
Mediterranean basin and in Africa, suggesting various migration routes and a broad non-breeding range. e European
populations of house martins are assumed to be longitudinally separated across their non-breeding range and thus
narrow population-specific non-breeding areas are expected. By using geolocators, we identified for the first time, the
migration routes and non-breeding areas of sand martins (n 4) and house martins (n 5) breeding in central-eastern
Europe.
In autumn, the Carpathian Bend and northern parts of the Balkan Peninsula serve as important pre-migration areas for
both species. All individuals crossed the Mediterranean Sea from Greece to Libya. Sand martins spent the non-breeding
season in northern Cameroon and the Lake Chad Basin, within less than a 700 km radius, while house martins were widely
scattered in three distinct regions in central, eastern, and southern Africa. us, for both species, the expected strength of
migratory connectivity could not be confirmed.
House martins, but not sand martins, migrated about twice as fast in spring compared to autumn. e spring migra-
tion started with a net average speed of 400 km d–1 for sand martins, and 800 km d–1 for house martins. However,
both species used several stopover sites for 0.5–4 d and were stationary for nearly half of their spring migration. Arrival at
breeding grounds was mainly related to departure from the last sub-Saharan non-breeding site rather than distance, route,
or stopovers. We assume a strong carry-over effect on timing in spring.
Various populations of long distance migratory birds in the
western Palearctic have declined in recent decades (Sander-
son et al. 2006). Candidate factors are climate change (Both
et al. 2006), changes of habitats in breeding (Donald et al.
2001), migration, and non-breeding areas (Zwarts et al.
2009, Maggini and Bairlein 2011). To identify carry-over
effects and seasonal interactions on population development
(Harrison et al. 2011) we need comprehensive knowledge
about the whereabouts of individuals during the entire
annual cycle. In contrast to detailed information available
for breeding periods, we are still lacking information for
migration and non-breeding periods (Vickery et al. 2014),
especially for long distance passerine species.
In the Pannonian basin (central-eastern Europe), 58% out
of 26 common long distance migrant species have declined
significantly since 1999, whereas only 8% show positive
trends (Szép et al. 2012). e information deficiency in rela-
tion to the migration and non-breeding areas of these popu-
lations are immense, especially as they often play key roles on
the dynamics of the entire European populations (BirdLife
2004). e sand martin Riparia riparia and house martin
Delichon urbicum are typical examples: their populations
suffered from strong declines with mean annual population
growth rates of –2.7% in sand martins (during 1986–2014,
Szép unpubl.) and –4.7% in house martins (1999–2014,
Szép et al. 2012). Information on their distribution during
the non-breeding period is almost entirely lacking.
e sand martins breeding in eastern Hungary were
found among the first where adverse climate conditions in
potential African non-breeding areas (Sahel) could be cor-
related with the decreasing annual survival rates (Szép 1995).
Despite the huge effort on ringing with almost 140 000 indi-
viduals in eastern Hungary during more than 30 yr, there
is no recovery in Africa for this breeding population. For
other Hungarian and the neighbouring Czech and Slovakian
© 2016 e Authors. is is an Online Open article
Guest Editor: Anders Hedenström. Editor-in-Chief: Jan-Åke Nilsson. Accepted 15 November 2016
Journal of Avian Biology 48: 114–122, 2017
doi: 10.1111/jav.01339
is is an open access article under the terms of the Creative
Commons Attribution License, which permits use, distribution
and reproduction in any medium, provided the original work is
properly cited.
115
populations, there are only eight recoveries from the African
continent, Lake Chad (2), Morocco, east of Tunisia (4), DR
Congo and two nearby recoveries from Israel and Lebanon
in spring (Heneberg 2008, Szép 2009). us, sand martins
are assumed to migrate on a broad front (Turner and Rose
1989), and should be widely distributed in sub-Saharan
Africa, eastern and southern Africa (Walther et al. 2010).
e house martin is one of the ten most common Palae-
arctic African migrants (Hahn et al 2009) but spatial infor-
mation during the non-breeding season is very scant (Hill
1997). For birds breeding in Germany there are just six
recoveries from the African non-breeding areas spanning
the Central African Republic, Cameroon, DR Congo, and
Zambia (Bairlein et al. 2014). Moreover for the large popu-
lation in the UK, there is only a single recovery from Nigeria
(Hill 2002). House martins breeding in northern Europe
had been recovered in southern Africa (Hill 2002, Valkama
2014), whereas the little available information for birds from
central-eastern Europe points to migration routes across the
Balkan peninsula, southern Italy and north-western Libya
during autumn, and north-western Algeria, Malta, and the
Balkans during spring (Cepák 2008, Králl and Karcza 2009).
Albeit small, this tantalising information raises the sugges-
tion that European house martins might be longitudinally
separated in Africa with eastern populations overwintering
in east Africa, central populations in Zambia, Zimbabwe
and South Africa, and western populations distributed in the
region of the Bight of Benin (Hill 2002).
In this paper we investigate the migration and non-breed-
ing areas of sand martins and house martins breeding in the
Pannonian basin using geolocators, and compare our results
with the ringing recoveries of the two species during the
non-breeding season. Finally, we also study the diurnal and
nocturnal use of cavities during the non-breeding season to
explain the very low numbers of African recoveries especially
for house martins.
Methods
Studied populations
e sand martin population we studied breeds along the
river Tisza in eastern Hungary and has been intensively
monitored since 1986 (Szép et al. 2003b). e house mar-
tin colonies we studied are situated in two villages along the
upper section of the river Tisza, where 40–280 birds have
been ringed annually since 2010.
Deployment of geolocators
In 2012, we equipped adult breeders of both species with
SOI GDL2 ver. 1.2 (Swiss Ornithological Inst., Sempach,
Switzerland) geolocators using a modified leg-loop harness
(Supplementary material Appendix 1). Including the har-
ness, these geolocators weigh 0.6 g.
Sand martins were captured at the end of the breeding
season, between 9–25 July 2012, in two colonies along the
river Tisza, at Szabolcs (48.188°N, 21.488°E, 35 males, 34
females, colony size 1700 pairs), and at Gávavencsellő
(48.199°N, 21.588°E, five males, six females, colony
size 100 pairs). Average body mass of the geolocator-har-
nessed birds at deployment was 13.4 g (SD 0.80, n 80);
thus geolocators mass was 4.5% of body mass.
We recaptured five sand martins in May–June of 2013
(two females and one male at Szabolcs and two females
at Gávavencsellő), and received geolocator data from four
birds (one geolocator failed). Additionally, another female
with a geolocator was identified at Szabolcs using a digital
camera, but was not recaptured. All recaptured birds were
active breeders. e return rate of geolocator-harnessed birds
varied between Szabolcs (5.8%) and Gávavencsellő (18.2%),
but not significantly (Fisher’s exact test, p 0.19). Return
rates of geolocator-harnessed birds and controls (caught at
the same catching events in 2012) showed significant dif-
ference at Szabolcs (control: 17.8%, n 129, geolocators:
5.8%, n 69 birds, Fisher’s exact test, p 0.028), but not
at Gávavencsellő (control: 21.7%, n 46, geolocators:
18.2%, n 11, Fisher’s exact test, p 1.0). e return rate
of females was double that of males, but the difference was
not significant (female: 4/40, male: 2/40, Fisher’s exact test,
p 0.67).
House martins were equipped with geolocators at
Nagyhalász-Homoktanya (48.076°N, 21.752°E 21 males,
18 females and 1 adult of unknown sex) and at Tiszabercel
(48.158°N, 21.643°E three males and seven females between
19 July and 3 August 2012). e mean body mass of geolo-
cator-harnessed birds was 17.1 g (SD 1.04, n 50), while
the geolocator mass was 3.5% of adult body mass. e colony
at Nagyhalász-Homoktanya comprised 317 nests (41% with
clutches), whereas at Tiszabercel the colony consisted of
43 nests (51% with clutches).
Five geolocator-harnessed birds were recaptured at
the colony of Nagyhalász-Homoktanya (three males, two
females) in July of 2013. e return rate (12.5%) was lower
than 38.9% return rate of control birds (n 18) (Fisher’s
exact test, p 0.035). At Tiszabercel neither geolocator nor
control birds were recaptured.
Light-level data analysis
We calculated positions using the R-package GeoLight (Lis-
ovski and Hahn 2012). However, we could not use light
data from breeding ranges to calibrate sun elevation angles
because of the non-natural sunset and sunrise that the birds
experienced inside cavities where they nest. We therefore
used median sun elevation angle (–2.7°) for all individu-
als of both species derived by the Hill–Ekstrom calibration
method (Lisovski and Hahn 2012) from long non-breeding
stationary periods ( 50 d). is sun elevation angle was
very close to the one measured with the same geolocator type
in another study (–2.8) that looked at more than 100 barn
swallows (Liechti et al. 2014).
Data filtering
Light level was recorded every five minutes and varied
between 0 (total darkness) and 63 (maximum value; for sen-
sor specific details see Adamík et al. 2016). Based on these
values, we defined three time periods per day: 1) a sunrise
period that lasted from the first light value 0 after at least
four hours of zero values until the light value reached the
116
maximum (63) level; 2) a sunset period that lasted from the
last maximum light level until the last value above zero, fol-
lowed by at least four hours of zero values; 3) a lightness
period that lasted from the end of the sunrise period until
the start of the sunset period.
Both species breeds in dark burrows or half-cup nests and,
occasionally, they use similar sites (e.g. holes, caves) outside
the breeding season. is behaviour can be used to divide
recorded sun events (sunrise and sunset) into two classes:
natural and non-natural (Liechti et al. 2014, Gow et al.
2015). To filter such potentially biased light data, we defined
non-natural sunrises and sunsets on the basis of whether or
not the first/last light value was below or above an empiri-
cally derived threshold. When the level of first/last light
value was less than 5 (84.5% of 5313 cases), the minimum
length of sunrise/sunset varied between 10–20 min; in other
cases (first/last light value 5, 15.5%) the minimum
length of these periods varied between 0–20 min. In the first
case, we considered the sunrise or sunset as natural, while in
the second as non-natural. Zero light values during sunrise/
sunset could also indicate the use of dark sites during the
entire sunrise/sunset period. Such events were significantly
more frequent when the first/last light value was 5 or higher
(30.2% of 775 cases) than for lower values (6.6% of 4537
cases; c21 405.64, p 0.001). Consequently, sunset and
sunrise periods with a zero value were also defined as unnatu-
ral. Finally, differences in shading between consecutive sun
events (sunrise and sunset) can cause an asymmetry in day
and night length and lead to error in the calculation of noon
and midnight, thus longitude. We therefore calculated the
difference in the length of consecutive sun event periods and
for further analyses, days and nights with differences larger
than 55 min (upper 5% quartile) were excluded, as well as all
non-natural sun events (example in Supplementary material
Appendix 1, Fig. A1).
Defining stationary periods
Geolocation divides the temporal pattern of observations
into two time steps per 24 h (daytime and night-time), and
we assumed that considerable shifts in consecutive sunrises
or sunsets indicate a movement. Generally, stationary peri-
ods were defined based on the time shifts between two con-
secutive, equal sun-events (sunrises or sunsets, respectively),
which include the two time steps (daytime and night-time).
We decided not to use the changepoint algorithm imple-
mented in the GeoLight-software, instead applied some
simple rules easy to follow. Our light data had a low impact
of shading (except cavity-use), thus, from visual inspection
alone it was obvious that some of the very short stopover
periods (1–3 d) were missed by the standard algorithm. By
using the same data as the standard algorithm we therefore
developed a few arbitrary but objective rules to define sta-
tionary periods. ere were almost no differences in sta-
tionary periods longer than 7 d, but we could identify in
addition some short stopovers during migration. We believe
that this pragmatic approach facilitated the opportunity to
derive more detailed results than with a standard approach
in our dataset. We determined for each time step whether it
was a stationary or movement period by applying the fol-
lowing rules when all sun events were natural: 1) if the time
shift between two equal and consecutive sun-events was less,
or equal to five minutes, the second time period (daytime
or night-time) was classified as a stationary period; 2) if a
time shift was more than five minutes between two equal
sun-events but smaller than between the two sun-events in
the step before, we assume that the bird was stationary dur-
ing the second time period (daytime or night-time); 3) if a
time shift was more than five minutes between two equal
sun-events, and larger than between the two sun-events in
the step before, we supposed that the bird was moving dur-
ing the second time period (daytime or night-time); 4) if
condition 2 was true, but the difference in the duration of
the actual day (or night, respectively) and the day before (or
night, respectively) was larger than 10 min, then the period
was classified as an uncertain stationary period.
ese rules are arbitrary and specifically adapted to the
data we collected with this type of geolocator. Neverthe-
less, our classification is based on objective rules and, most
importantly, is independent of calculated positions. us, all
geographical positions within a stationary period (not inter-
rupted by a movement period) were pooled to a single site,
and if median geographic position between consecutive sites
was within a 200 km radius, then sites were pooled. Sites
were defined by their median and 90% quartile of all geo-
graphical positions within this time period.
e seasonal pattern was defined by four specific station-
ary periods: 1) the end of the breeding period was defined
by departure from the breeding grounds (leaving the first
stationary site within 200 km from the breeding grounds);
2) arrival at the first, and departure from the last site north
of the Mediterranean Sea defined the pre-migratory period;
3) arrival at the first and departure from the last site south
of the Sahara ( 23.5°N) defined the non-breeding resi-
dence period; 4) arrival at breeding grounds was defined by
a stationary period within 200 km or by the occurrence of
frequent unnatural sun events due to nest cavity visits. e
initiation and end of autumn migration was defined by the
end of the pre-migratory period and the start of the non-
breeding residency. Spring migration was defined by the end
of the non-breeding residency and the start of the breed-
ing period. e area associated with the longest stationary
period south of the Sahara ( 23.5°N) was defined as the
main residence area during the non-breeding period.
We defined the time period of autumn migration as
the last date of the last stationary site ( 5 d) north of
the Mediterranean Sea, and the first date of the first sta-
tionary site ( 5 d) south of the Sahara desert (latitude
23.5°N). e period of spring migration was defined
vice versa.
Use of cavities
Sand martins and house martins are diurnal foragers of aer-
ial plankton and use cavities for breeding as well as perhaps
for resting (Cramp 1988). We quantified the use of cavi-
ties within the annual cycle and identified days with cavity
visits during daylight when periods of light records of zero
occurred for at least five minutes. Cavity use during nights
was determined if either sunrise or sunset was defined as
unnatural events. In the case of one bird (S4, sand martin)
the geolocator had slipped to the side, thus data could not be
117
southern Africa (distance 8050 km) (Fig. 1C). ree of the
five birds we tracked stayed in one area for an average of 159
d (range: 144–177 d, Supplementary material Appendix 1,
Table A1), while two birds (H3, H4) used two separated sites
(400 km, 1200 km) (Fig. 1C). Between March and May, all
the tracked birds moved to other sites, an average of 1350
km (range: 750–2050 km) from their main non-breeding
residences (Supplementary material Appendix 1, Table A1,
Fig. 1C). Surprisingly, only three of the five individuals we
tracked moved northwards to sites closer to the southern
Saharan border while two birds moved to sites in the west/
southwest and stayed there for at least three weeks before
departing for their spring migration.
Spring migration
ree sand martins migrated straight to the north across the
desert, while one bird followed a westerly loop (Fig. 1B).
Sand martins departed between 11 April and 7 May, and
used 5–6 stopover sites with an average stopover duration of
1.5 d (0.5–4 d) (Fig. 2B, Supplementary material Appendix 1,
Table A1). Arrival at the breeding colonies was between 29
April and 24 May resulting in a migration duration of 14 d
(range: 8–17 d) (Fig. 2B). eir overall migration speed was
an average of 349 km d–1 (range: 241–498 km d–1), while
their net migration speed, excluding times spent at stopover
sites (mean: 6 d, range: 6–11 d), was 621 km d–1 (range: 424–
822 km d–1, Supplementary material Appendix 1, Table A1).
In contrast, house martins used two distinct migration
routes related to difference in their main non-breeding sites.
Birds from eastern Africa moved along an eastward loop
across the Arabian Peninsula, Turkey, and the Balkan Penin-
sula and thus avoiding the crossing of the Mediterranean sea
(Fig. 1D), while individuals overwintering in central Africa
and South Africa moved straight across the desert and then
crossed the central part of the Mediterranean sea through
Malta/Sicily, southern Italy and Adriatic Sea, a very similar
flyway to two of the tracked sand martins. Individuals over-
wintering in central and eastern Africa departed between 26
April and 8 May (Fig. 2D), and stopped over at 3–7 sites for
an average of one day (0.5–4 d). ey arrived at the breeding
sites between 5 and 18 May, after 10 d (6–16 d) on migration
(Fig. 2D, Supplementary material Appendix 1, Table A1).
e bird overwintering in southern Africa left this site at the
end of March and moved northwards to central Africa using
three stationary sites (2–6.5 d). From these sites onwards,
their migration was very similar to others (Fig. 2D); average
overall migration speed was 594 km d–1 (range: 360–887 km
d–1), and net migration speed, excluding time spent at stop-
over sites (mean: 4 d, range: 2–9 d), was 1081 km d–1 (range:
615–1462 km d–1, Supplementary material Appendix 1,
Table A1). In both species, individuals with the southernmost
main non-breeding sites left sub-Saharan Africa earlier and
were first to arrive at the breeding grounds.
Usage of cavities during the annual cycle
e majority of birds of both species used cavities during the
day when breeding but only occasionally during migration and
the non-breeding residence period (Fig. 3A). Cavity use during
the nights occured most frequently during the breeding period
used for defining cavity usage (one third of positioning data
was influenced).
Data available from Movebank Data Repository: < doi:
10.5441/001/1.214298181 > (Szép et al. 2016).
Results
Autumnal pre-migration period
Sand martins departed from their breeding sites before
August (Szép unpubl.), although exact departure dates were
not recorded because the logging season started 1 August.
In August, all tracked birds were roaming in the Carpathian
Bend or in Serbia, Romania, and Bulgaria until departing for
their southbound migration (Fig. 1A, Supplementary mate-
rial Appendix 1, Table A1).
Tracked house martins departed between the end of July
(K. Nagy unpubl.) and the first half of August from their
breeding site to the Carpathian Bend (three individuals) as
well as to western Ukraine and western parts of Romania.
(Fig. 1C, Supplementary material Appendix 1, Table A2).
Autumn migration
e autumn migration coincided with the equinox period,
and thus latitudinal estimates are not available during this
period. However, longitudinal data indicated migratory
tracks across the Balkan region with subsequent traverses of
the Mediterranean Sea in both species (Fig. 1A, C). Sand
martins showed a clear shift in longitude, with an easterly
shift in the first half of the migration period and westerly in
the second. e sand martins departed on average at 9 Sep-
tember (5–14 of September) and arrived after 17 d (16–20
d) at the non-breeding areas (mean: 26 September, range:
23–30 September) (Fig. 2A). e overall migration speed
averaged at 229 km d–1 (range: 155–271 km d–1).
Based on longitudinal positions house martins followed a
more or less straight route to the non-breeding area in sub-
Saharan Africa (Fig. 1C). ey departed on average also at 8
September (5–12 September) and arrived after 24 d (21–30)
at the non-breeding area (mean: 3 October, range: 2–5 Octo-
ber) south of the Sahara (Fig. 2C). e overall migration
speed averaged at 193 km d–1 (range: 176–219 km d–1).
Non-breeding residence
e main non-breeding areas of tracked sand martins were
situated in the Lake Chad Basin (Fig. 1A), and thus, on aver-
age 4250 km (3850–4600 km) separated from the breeding
sites (great circle distance). ree of four birds used a single
non-breeding site for on average 170 d (range: 151–193 d),
and one bird (S2) used three distant areas (400 km, 750
km, Fig. 1A). Before spring migration, between March and
May, two individuals moved to pre-migratory sites near Lake
Chad for about 12–39 d (Fig. 1A).
House martins were distributed widely across sub-
Saharan Africa; we tracked two individuals in central Africa
(4250 and 4500 km great circle distances from their breeding
sites), two individuals in eastern Africa (Uganda, Ethiopia,
distances of 4250 and 5200 km), and one individual in
118
Discussion
is study has revealed, for the first time, the spatio-tempo-
ral migration patterns and non-breeding locations for indi-
vidual sand martins and house martins.
and less often during non-breeding residence and migration
periods (Fig. 3B). Results show that house martins used cavi-
ties more often on their African non-breeding (15.3 vs 0.7%,
c21 95.129, p 0.001) and breeding sites (80.3 vs 50.4%,
c21 36.219, p 0.001) than sand martins (Fig. 3B).
Figure 1. Individual tracks of sand martins (A, B) and house martins (C, D) from breeding areas in the Pannonian basin to the nonbreeding
areas in Africa (A, C) and back (B, D). Each colour represents an individual track. Subsequent stationary periods of an individual are con-
nected by dashed lines, except for the autumn migration period during equinox times. e connecting lines are interpretations due to
longitudinal information alone. Stationary periods are labelled by a digit (individual 1–5), a character (time period a autumn, w winter,
s spring) and second digit (sequence of individual time period). Stationary sites with more than 20 positions were marked by the median
and the 90% range of the positions, for shorter stopover periods (with circles) the median and an arbitrary standard error of 200 km for
longitude, and 300 km for latitude are indicated. For sand martins all distant captures/recaptures from the studied population are indi-
cated in panel (A) (autumn ▾, 1 August to 11 September) and panel (B) (spring ⚫, 8 April to 24 May). For further details see Supplemen-
tary material Appendix 1, Table A1.
119
but not fully with the 38 spring recapture/recoveries from
our studied population, which are distributed along the
wide west–east range of the Mediterranean basin (Fig. 1B).
While recoveries do point towards a more widespread non-
breeding range in Africa with low migratory connectivity,
our results support the opposite view. Due to considerable
differences in reporting rates among the different countries,
ringing recoveries/recaptures have a considerable geographi-
cal bias. However, our small sample size does not allow for
a final conclusion with respect to the strength of migratory
connectivity. Obviously, the main non-breeding area of our
studied population is situated more to the east compared to
recoveries of the western and central European populations
(Mead 2002, Walther et al. 2010, Bairlein et al. 2014). Trace
element profiles of feathers grown by the British and Span-
ish martins while in Africa (overwintering in the western
Sahel) differed from Hungarian birds (Szép et al. 2003a) in
concordance with the geolocation result.
In contrast, the house martins in our study are shown to
occupy a much larger non-breeding range than sand martins.
We identified three distant, non-breeding areas in central,
eastern, and southern Africa that appear to have weak migra-
tory connectivity. Very few central European birds have been
recovered from central Africa (Bairlein et al. 2014), and
records of non-breeding areas in eastern Africa represent
e Carpathian Bend is well known as an important
area for the preparation of autumn migration in both spe-
cies (Králl and Karcza 2009, Szép 2009), but our study now
shows that some northern parts of the Balkan Peninsula are
similar important. Recapture data from birds from our stud-
ied populations confirm this finding (Fig. 1A).
When migrating, our track records show that sand mar-
tins move along the Balkan Peninsula, and cross the Mediter-
ranean Sea at Greece in a narrow band, in contrast to recent
recoveries from Italy and Malta that indicate a much wider
autumn migration corridor (Cepák 2008, Heneberg 2008,
Králl and Karcza 2009, Szép 2009). Mismatch between our
records and others may be due to the specific weather con-
ditions during the study year, as all individuals we studied
departed for their autumn migration within a very narrow
nine day time period. In addition, individuals from both
species followed a route which included just a 500 km sea
crossing. However, due to a lack of latitudinal information,
we cannot distinguish whether, or not, this directional shift
occurred in northern Africa (Fig. 1A).
Contrary to our expectations, the studied sand martins
spent the non-breeding season in an area with a radius of
less than 700 km in northern Cameroon and the Lake Chad
Basin. is result is consistent with two central-eastern Euro-
pean population ringed birds recovered from Lake Chad,
01.09.2012
08.09.2012
15.09.2012
22.09.2012
29.09.2012
06.10.2012
13.10.2012
20.10.2012
27.10.2012
02000 4000 6000
Distance from the breeding area (km)
1w1
2w1
3w1
4w1
(A)
01.04.2013
08.04.2013
15.04.2013
22.04.2013
29.04.2013
06.05.2013
13.05.2013
20.05.2013
27.05.2013
Distance to the breeding area (km)
1w1
2w4
3w2
4w2
(B)
01.09.2012
08.09.2012
15.09.2012
22.09.2012
29.09.2012
06.10.2012
13.10.2012
20.10.2012
27.10.2012
02000 4000 6000
Distance from the breeding area (km)
1w1
2w1
3w1
4w1
5w1
(C)
01.04.2013
08.04.2013
15.04.2013
22.04.2013
29.04.2013
06.05.2013
13.05.2013
20.05.2013
27.05.2013
–6000–4000 –2000 0
–6000 –4000 –2000 0
Distance to the breeding area (km)
1w2
2w3
3w3
4w7
5w2
(D)
Figure 2. Individual timing of migration and distances covered for the sand martins (A, B) and the house martins (C, D) in autumn (A, C)
and spring (B, D). Distances (km) are given in relation to the breeding sites. Dots refer to arrival and departure at the specific site indicated
in the legends (cf. Fig. 1).
120
behaviour could be estimated. e most striking difference
in migratory routes was not between species, but rather
between geographical positions of main non-breeding areas.
Identified passage areas in the spring across the central part
of the Mediterranean basin coincide very well with most
recapture sites known for both Pannonian populations
(Cepák 2008, Heneberg 2008, Králl and Karcza 2009, Szép
2009). Only two house martins overwintering in eastern
Africa circumvented the Mediterranean Sea on their spring
migration as is the case in other insectivorous birds (i.e.
red-backed shrikes; Tottrup et al. 2012). Although autumn
migration routes can only be reconstructed here using lon-
gitudinal information, there is good evidence that none of
the individuals followed the same route in both autumn and
spring. Migration duration in sand martins was very simi-
lar in autumn and spring, while house martins spent almost
three times more days on their autumn compared to their
spring migration. As a result, the overall travelling speed of
house martins was about 16% lower than the sand martins
in autumn, but 70% faster in the spring. Indeed, five out
of the nine birds we tracked returned in spring in 10 d or
less. Departure and arrival dates were also less synchronous
in the spring compared to the autumn for all individuals of
both species, but there was a high correlation in departure
and arrival dates (r 0.88, Pearson) with the exception
of the house martins in autumn. In both seasons, migratory
distances were slightly longer for house martins than they
were for sand martins (∼ 20%), taking into account the first
(for autumn) and the last (for spring) sub-Saharan stationary
sites. ere were also no obvious differences in overall migra-
tion speeds in the spring within species compared to dates,
distances, or chosen route. us, in both species, arrival at
breeding grounds was strongly determined by the date of
departure from the last sub-Saharan non-breeding site.
During spring migration, when time spent at stopover-
sites could be estimated, individuals of both species where
stationary for nearly half of their migration period. Net
migration speeds were over 400 km d–1 for sand martins,
rising to twice this value for house martins, over 800 km
d–1; this strongly suggests that these birds use tail winds, as
air speeds measured for migrating sand martins and house
martins average around 40 km h–1 (Liechti and Bruderer
2002). In contrast, net migration speeds during the spring
tended to be higher for individuals using more distant non-
breeding residence areas; these birds must have either been
able to accumulate more fuel reserves before departure, prof-
ited from abundant food resources en route, or benefited
more from tail winds. As none of the individuals (in both
species) surpassed another during spring migration, and
because spring migration was generally fast (especially in
house martins), we assume that there is a strong carry-over
effect between departure from sub-Saharan Africa and arrival
at breeding grounds although more track records will clearly
be needed to statistically support this assumption.
To define stationary periods during spring migration
in such details, we had to overcome the standard method
used so far (GeoLight). We must admit that our approach
provided reliable results only because of the high quality
light data, with very minor shading effects (Lisovski et al.
2012). Based on our data, the fastest spring migration of
a house martin (H5) was reconstructed using a movement
new results for central-eastern European breeding house
martins. Non-breeding areas in southern Africa were already
known for northern European and German populations
(Hill 2002, Bairlein et al. 2014, Valkama 2014), but had
not been recorded before for central-eastern European popu-
lations. All the non-breeding sites for Pannonian birds are
situated east with respect to indirectly assigned non-breeding
areas for a Dutch population (Hobson et al. 2012) and some
north Italian individuals (Ambrosini et al. 2011). Neverthe-
less, there is considerable overlap in the non-breeding areas
now known for Pannonian house martins with several other
European populations; as a result, our findings do not sup-
port the hypothesis that there is a longitudinal separation in
the non-breeding areas of European populations (Hill 2002,
Ambrosini et al. 2011). Within the pre-migratory period,
two of our five house martins moved considerably westward,
towards an area where birds from the western and central
European population have also been recovered during this
time of the year (Bairlein et al. 2014). However, whether
or not these birds spent their whole non-breeding period
within this area remains unclear.
One reason for the low recovery rate of house martins
compared to other swallows might be their more frequent
use of cavities (e.g. caves, trees, buildings) during the non-
breeding season in Africa. Such roosts are much more diffi-
cult to find, are occupied by a smaller number of individuals,
and therefore are less attractive to local people than the huge
roosts of the other two swallow species (Hill 2002).
Spring migrations of our studied individuals took
place after the equinox and, therefore, tracks and stopover
0
20
40
60
80
100
120
Premigratory,
autumn
Migration,
autumn
WinteringMigration,
spring
Breeding
Frequency of usage of cavities
during day(%)
Season
House martin Sand martin
(A)
0
20
40
60
80
100
Premigratory,
autumn
Migration,
autumn
WinteringMigration,
spring
Breeding
Frequency of usage of cavities
during nights(%)
Season
House martin Sand martin
***
***
(B)
Figure 3. Frequency of cavities usage (mean SD) of sand martins
and house martins during the day (A) and the night (B) for the four
non-breeding periods defined (see Methods) and the breeding sea-
son (significant differences are marked with ***: p 0.001).
121
Both, C., Bouwhuis, S., Lessells, C. M. and Visser, M. E. 2006.
Climate change and population declines in a long-distance
migratory bird. – Nature 441: 81–83.
Cepák, J. 2008. Jiricka obcena (house martin). – In: Cepák, J.,
Klvana, P., Škopek, L., Schröpfer, L., Jelínek, M., Horák, D.,
Formánek, J. and Zárybnický, J. (eds), Czech and Slovak bird
migration atlas. Aventinum, pp. 337–339.
Cramp, S. 1988. e birds of the Western Palearctic, vol. 5.
– Oxford Univ. Press.
Donald, P. F., Green, R. E. and Heath, M. F. 2001. Agricultural
intensification and the collapse of Europe’s farmland bird
populations. – Proc. R. Soc. B 268: 25–29.
Gomez, J., Michelson, C. I., Bradley, D. W., Norris, D. R., Berzins,
L. L., Dawson, R. D. and Clark, R. G. 2014. Effects of
geolocators on reproductive performance and annual return
rates of a migratory songbird. – J. Ornithol. 155: 37–44.
Gow, E. A., Wiebe, K. L. and Fox, J. W. 2015. Cavity use through-
out the annual cycle of a migratory woodpecker revealed by
geolocators. – Ibis 157: 167–170.
Hahn, S., Bauer, S. and Liechti, F. 2009. e natural link between
Europe and Africa – 2.1 billion birds on migration. – Oikos
118: 624–626.
Harrison, X. A., Blount, J. D., Inger, R., Norris, D. R. and Bearhop,
S. 2011. Carry-over effects as drivers of fitness differences in
animals. – J. Anim. Ecol. 80: 4–18.
Heneberg, P. 2008. Brehule ricni (sand martin). – In: Cepák, J.,
Klvana, P., Škopek, L., Schröpfer, L., Jelínek, M., Horák, D.,
Formánek, J. and Zárybnický, J. (eds), Czech and Slovak bird
migration atlas. Aventinum, pp. 329–331.
Hill, L. A. 1997. Trans-Saharan recoveries of house martins
(Delichon urbica), with discussion on ringing, roosting and
sightings in Africa. – Safring News 26: 7–12.
Hill, L. A. 2002. House martin. – In: Wernham, C. V., Toms, M.
P., Marchant, J. H., Clark, J. A., Siriwardena, G. M. and
Baillie, S. R. (eds), Britain and Ireland: the migration atlas:
movements of the birds of Britain and Ireland. Poyser,
pp. 465–467.
Hobson, K. A., Van Wilgenburg, S. L., Piersma, T. and Wassenaar,
L. I. 2012. Solving a migration riddle using isoscapes: house
martins from a Dutch village winter over west Africa. – PLoS
One 7: e45005.
Králl, A. and Karcza, Z. 2009. Molnár fecske (house martin). – In:
Csörgő, T., Karcza, Z., Halmos, G., Magyar, G., Gyurácz, J.,
Szép, T., Bankovics, A., Schmidt, A. and Schmidt, E. (eds),
Magyar madárvonulási atlasz. (Hungarian bird migration
atlas.) Kossuth, pp. 415–416.
Liechti, F. and Bruderer, L. 2002. Wingbeat frequency of barn
swallows and house martins: a comparison between free
flight and wind tunnel experiments. – J. Exp. Biol. 205:
2461–2467.
Liechti, F., Scandolara, C., Rubolini, D., Ambrosini, R., Korner-
Nievergelt, F., Hahn, S., Lardelli, R., Romano, M., Caprioli,
M., Romano, A., Sicurella, B. and Saino, N. 2014. Timing of
migration and residence areas during the non-breeding period
of barn swallows Hirundo rustica in relation to sex and
population. – J. Avian Biol. 45: 1–12.
Lisovski, S. and Hahn, S. 2012. GeoLight – processing and
analysing light-based geolocator data in R. – Methods Ecol.
Evol. 3: 1055–1059.
Lisovski, S., Hewson, C. M., Klaassen, R. H. G., Korner-Nievergelt,
F., Kristensen, M. W. and Hahn, S. 2012. Geolocation by
light: accuracy and precision affected by environmental factors.
– Methods Ecol. Evol. 3: 603–612.
Maggini, I. and Bairlein, F. 2011. Body condition and stopover of
trans-Saharan spring migrant passerines caught at a site in
southern Morocco. – Ring. Migr. 26: 31–37.
Mead, C. 2002. Sand martin. – In: Wernham, C. V., Toms, M. P.,
Marchant, J. H., Clark, J. A., Siriwardena, G. M. and Baillie,
period of 4.5 d, resulting in an average ground speed of 52
km h–1. is is a realistic speed, well in line with known
ground speeds measured by radar for small migrating pas-
serines (Liechti and Bruderer 2002). Finally, as all the speeds
we estimated were within a realistic range, our filtering seems
to provide feasible results.
Conclusions
In contrast to the existing ringing recoveries from our sand
martin population, the migration and non-breeding residency
of the studied sand martins was fairly concentrated. Instead,
for our studied house martins non-breeding residency of the
five individuals was distributed across a huge area in sub-
saharan Africa, not supporting proposed population specific
non-breeding ranges. Due to the small sample size these pre-
liminary conclusions need to be verified by further investiga-
tions. e geolocator study provided substantial information
for the whereabouts of the Pannonian populations of sand
martin and house martin. However, there are also drawbacks
of the method. For instance the lower return rates of geo-
locator birds compared to controls calls for cautious use of
geolocators on such small birds, especially aerial feeders (see
also Gomez et al. 2014, Scandolara et al. 2014) and careful
interpretation of data on timing (Arlt et al. 2013). However,
geolocation remains the only method to track the martins
to date.
Acknowledgements – We thank Ákos Pelenczei, Zoltán Görögh,
János Danku, Annamária Danku, Beáta Bokor, Ivett Kakszi, Zsolt
Hörcsik, the members of the local chapter of the MME/BirdLife
Hungary for the important help in the field work, and Edit Molnár
for processing our field data. e deployment of the geolocators
and related field works were carried out with the permission of the
Hungarian National Inspectorate for Environment, Nature and
Water (14/2104/5/2012). e study was donated by ‘Madárvé-
delem határok nélkül’ HUSK/1101/2.2.1/0336 project of the EU
and by the local chapter of the MME/BirdLife Hungary. e Swiss
federal office for environment contributed financial support for the
development of the data loggers (UTF-Nr. 254, 332, 363, 400).
References
Adamík, P., Emmenegger, T., Briedis, M., Gustafsson, L., Henshaw,
I., Krist, M., Laaksonen, T., Liechti, F., Procházka, P., Salewski,
V. and Hahn, S. 2016. Barrier crossing in small avian migrants:
individual tracking reveals prolonged nocturnal flights into the
day as a common migratory strategy. – Sci. Rep. 6: 21560.
Ambrosini, R., Orioli, V., Massimino, D. and Bani, L. 2011.
Identification of putative wintering areas and ecological deter-
minants of population dynamics of common house-martin
(Delichon urbicum) and common swift (Apus apus) breeding in
northern Italy. – Avian Conserv. Ecol. 6, doi: 10.5751/ACE-
00439-060103
Arlt, D., Low, M. and Part, T. 2013. Effect of geolocators on
migration and subsequent breeding performance of a long-
distance passerine migrant. – PLoS One 8: e82316.
Bairlein, F., Dierschke, J., Dierschke, V., Salewski, V., Geiter, O.,
Hüppop, K., Köppen, U. and Fiedler, W. 2014. Atlas des
Vogelzugs: Ringfunde Deutscher Brut- und Gastvögel. – Aula
Verlag.
BirdLife 2004. Birds in Europe: population estimates, trends and
conservation status. – BirdLife International, Cambridge.
122
sand martins and house martins breeding in the Pannonian
basin (central-eastern Europe). – Movebank Data Repository,
< doi:10.5441/001/1.214298181 >.
Tottrup, A. P., Klaassen, R. H. G., Strandberg, R., orup, K.,
Kristensen, M. W., Jorgensen, P. S., Fox, J., Afanasyev, V.,
Rahbek, C. and Alerstam, T. 2012. e annual cycle of a trans-
equatorial Eurasian-African passerine migrant: different spa-
tio-temporal strategies for autumn and spring migration.
– Proc. R. Soc. B 279: 1008–1016.
Turner, A. and Rose, C. 1989. Swallows and martins: an identifica-
tion guide and handbook. – Houghton Mifflin Company.
Valkama, J. 2014. House martin (Delichon urbicum). – In:
Valkama, J., Saurola, P., Lehikoinen, A., Lehikoinen, E., Piha,
M., Sola, P. and Luomus, W. (eds), e Finnish bird ringing
atlas volume II. Finnish Museum of Natural History,
pp. 340–342.
Vickery, J. A., Ewing, S. R., Smith, K. W., Pain, D. J., Bairlein, F.,
Skorpilova, J. and Gregory, R. D. 2014. e decline of
Afro-Palaearctic migrants and an assessment of potential
causes. – Ibis 156: 1–22.
Walther, B. A., van Niekerk, A., uiller, W., Baumann, S., Dean,
W. R. J., de Bruijn, B., Gutteridge, K., Jones, P. J., Nikolaus,
G., Pearson, D. J., Robinson, S. P., Salewski, V., Schäffer, N.,
Taylor, P. B., Tushabe, H., Williams, P. H. and Rahbek, C.
2010. A database of Western Palearctic birds migrating within
Africa to guide conservation decisions. – In: Harebottle, D.
M., Craig, A. J. F. K., Anderson, M. D., Rakotomanana, H.
and Muchai, M. (eds), Proceedings of the 12th Pan-African
Ornithological Congress, 2008. Animal Demography Unit,
pp. 50–104.
Zwarts, L., Bijlsma, R. G., van der Kamp, J. and Wymenga, E.
2009. Living on the edge: wetlands and birds in a changing
Sahel. – KNNV Publishing, Zeist.
S. R. (eds), Britian and Ireland: the migration atlas:
movements of the birds of Britain and Ireland. Poyser,
pp. 458–461.
Sanderson, F. J., Donald, P. F., Pain, D. J., Burfield, I. J. and van
Bommel, F. P. J. 2006. Long-term population declines in
Afro-Palearctic migrant birds. – Biol. Conserv. 131: 93–105.
Scandolara, C., Rubolini, D., Ambrosini, R., Caprioli, M., Hahn,
S., Liechti, F., Romano, A., Romano, M., Sicurella, B. and
Saino, N. 2014. Impact of miniaturized geolocators on barn
swallow Hirundo rustica fitness traits. – J. Avian Biol. 45:
417–423.
Szép, T. 1995. Relationship between west-African rainfall and the
survival of central-European sand martins Riparia riparia.
– Ibis 137: 162–168.
Szép, T. 2009. Partifecske (sand martin). – In: Csörgő, T.,
Karcza, Z., Halmos, G., Magyar, G., Gyurácz, J., Szép, T.,
Bankovics, A., Schmidt, A. and Schmidt, E. (eds), Magyar
madárvonulási atlasz. (Hungarian bird migration atlas.)
Kossuth, pp. 403–408.
Szép, T., Møller, A. P., Vallner, J., Kovács, A. and Norman, D.
2003a. Use of trace elements in feathers of sand martin Riparia
riparia for identifying moulting areas. – J. Avian Biol. 34:
307–320.
Szép, T., Szabó, D. Z. and Vallner, J. 2003b. Integrated population
monitoring of sand martin Riparia riparia – an opportunity
to monitor the effects of environmental disasters along the
River Tisza. – Ornis Hungarica 12–13: 169–182.
Szép, T., Nagy, K., Nagy, Z. and Halmos, G. 2012. Population
trends of common breeding and wintering birds in Hungary,
decline of long-distance migrant and farmland birds during
1999–2012. – Ornis Hungarica 20: 13–63.
Szép, T., Liechti, F., Nagy, K., Nagy, Z. and Hahn, S. 2016. Data
from: Discovering the migration and non-breeding areas of
Supplementary material (Appendix JAV-01339 at < www.
avianbiology.org/appendix/jav-01339 >). Appendix 1.
