Journal of Avian Biology 48: 114–122, 2017 doi: 10.1111/jav.01339 © 2016 The Authors. This is an Online Open article Guest Editor: Anders Hedenström. Editor-in-Chief: Jan-Åke Nilsson. Accepted 15 November 2016

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 ([email protected]) and S. Hahn, Dept of Migration, Swiss Ornithological Inst., Sempach, Switzerland. – K. Nagy and Z. Nagy, MME/BirdLife, Budapest, Hungary.­

The central-eastern European populations of and house martin have declined in the last decades. The 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. The 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 . All individuals crossed the 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. Thus, 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. The 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 in the significantly since 1999, whereas only 8% show positive western Palearctic have declined in recent decades (Sander- trends (Szép et al. 2012). The information deficiency in rela- son et al. 2006). Candidate factors are (Both tion to the migration and non-breeding areas of these popu- et al. 2006), changes of habitats in breeding (Donald et al. lations are immense, especially as they often play key roles on 2001), migration, and non-breeding areas (Zwarts et al. the dynamics of the entire European populations (BirdLife 2009, Maggini and Bairlein 2011). To identify carry-over 2004). The sand martin riparia and house martin effects and seasonal interactions on population development urbicum are typical examples: their populations (Harrison et al. 2011) we need comprehensive knowledge suffered from strong declines with mean annual population about the whereabouts of individuals during the entire growth rates of –2.7% in sand martins (during 1986–2014, annual cycle. In contrast to detailed information available Szép unpubl.) and –4.7% in house martins (1999–2014, for breeding periods, we are still lacking information for Szép et al. 2012). Information on their distribution during migration and non-breeding periods (Vickery et al. 2014), the non-breeding period is almost entirely lacking. especially for long distance species. The sand martins breeding in eastern Hungary were In the Pannonian basin (central-eastern Europe), 58% out found among the first where adverse climate conditions in of 26 common long distance migrant species have declined potential African non-breeding areas (Sahel) could be cor- related with the decreasing annual survival rates (Szép 1995). This is an open access article under the terms of the Creative Despite the huge effort on ringing with almost 140 000 indi- Commons Attribution License, which permits use, distribution viduals in eastern Hungary during more than 30 yr, there and reproduction in any medium, provided the original work is is no recovery in Africa for this breeding population. For properly cited. other Hungarian and the neighbouring Czech and Slovakian

114 populations, there are only eight recoveries from the African size  100 pairs). Average body mass of the geolocator-har- continent, Lake Chad (2), Morocco, east of Tunisia (4), DR nessed birds at deployment was 13.4 g (SD  0.80, n  80); Congo and two nearby recoveries from Israel and Lebanon thus geolocators mass was 4.5% of body mass. in spring (Heneberg 2008, Szép 2009). Thus, sand martins We recaptured five sand martins in May–June of 2013 are assumed to migrate on a broad front (Turner and Rose (two females and one male at Szabolcs and two females 1989), and should be widely distributed in sub-Saharan at Gávavencsellő), and received geolocator data from four Africa, eastern and southern Africa (Walther et al. 2010). birds (one geolocator failed). Additionally, another female The house martin is one of the ten most common Palae- with a geolocator was identified at Szabolcs using a digital arctic African migrants (Hahn et al 2009) but spatial infor- camera, but was not recaptured. All recaptured birds were mation during the non-breeding season is very scant (Hill active breeders. The return rate of geolocator-harnessed birds 1997). For birds breeding in Germany there are just six varied between Szabolcs (5.8%) and Gávavencsellő (18.2%), recoveries from the African non-breeding areas spanning but not significantly (Fisher’s exact test, p  0.19). Return the Central African Republic, Cameroon, DR Congo, and rates of geolocator-harnessed birds and controls (caught at Zambia (Bairlein et al. 2014). Moreover for the large popu- the same catching events in 2012) showed significant dif- lation in the UK, there is only a single recovery from Nigeria ference at Szabolcs (control: 17.8%, n  129, geolocators: (Hill 2002). House martins breeding in northern Europe 5.8%, n  69 birds, Fisher’s exact test, p  0.028), but not had been recovered in southern Africa (Hill 2002, Valkama at Gávavencsellő (control: 21.7%, n  46, geolocators: 2014), whereas the little available information for birds from 18.2%, n  11, Fisher’s exact test, p  1.0). The return rate central-eastern Europe points to migration routes across the of females was double that of males, but the difference was Balkan peninsula, southern Italy and north-western Libya not significant (female: 4/40, male: 2/40, Fisher’s exact test, during autumn, and north-western Algeria, Malta, and the p  0.67). Balkans during spring (Cepák 2008, Králl and Karcza 2009). House martins were equipped with geolocators at Albeit small, this tantalising information raises the sugges- Nagyhalász-Homoktanya (48.076°N, 21.752°E 21 males, tion that European house martins might be longitudinally 18 females and 1 adult of unknown sex) and at Tiszabercel separated in Africa with eastern populations overwintering (48.158°N, 21.643°E three males and seven females between in , central populations in Zambia, Zimbabwe 19 July and 3 August 2012). The mean body mass of geolo- and South Africa, and western populations distributed in the cator-harnessed birds was 17.1 g (SD  1.04, n  50), while region of the Bight of Benin (Hill 2002). the geolocator mass was 3.5% of adult body mass. The colony In this paper we investigate the migration and non-breed- at Nagyhalász-Homoktanya comprised 317 nests (41% with ing areas of sand martins and house martins breeding in the clutches), whereas at Tiszabercel the colony consisted of Pannonian basin using geolocators, and compare our results 43 nests (51% with clutches). with the ringing recoveries of the two species during the Five geolocator-harnessed birds were recaptured at non-breeding season. Finally, we also study the diurnal and the colony of Nagyhalász-Homoktanya (three males, two nocturnal use of cavities during the non-breeding season to females) in July of 2013. The return rate (12.5%) was lower explain the very low numbers of African recoveries especially than 38.9% return rate of control birds (n  18) (Fisher’s for house martins. exact test, p  0.035). At Tiszabercel neither geolocator nor control birds were recaptured.

Methods Light-level data analysis

Studied populations We calculated positions using the R-package GeoLight (Lis- ovski and Hahn 2012). However, we could not use light The sand martin population we studied breeds along the data from breeding ranges to calibrate sun elevation angles river Tisza in eastern Hungary and has been intensively because of the non-natural sunset and sunrise that the birds monitored since 1986 (Szép et al. 2003b). The house mar- experienced inside cavities where they nest. We therefore tin colonies we studied are situated in two villages along the used median sun elevation angle (–2.7°) for all individu- upper section of the river Tisza, where 40–280 birds have als of both species derived by the Hill–Ekstrom calibration been ringed annually since 2010. method (Lisovski and Hahn 2012) from long non-breeding stationary periods ( 50 d). This sun elevation angle was Deployment of geolocators very close to the one measured with the same geolocator in another study (–2.8) that looked at more than 100 barn In 2012, we equipped adult breeders of both species with (Liechti et al. 2014). SOI GDL2 ver. 1.2 (Swiss Ornithological Inst., Sempach, Switzerland) geolocators using a modified leg-loop harness Data filtering (Supplementary material Appendix 1). Including the har- ness, these geolocators weigh 0.6 g. Light level was recorded every five minutes and varied Sand martins were captured at the end of the breeding between 0 (total darkness) and 63 (maximum value; for sen- season, between 9–25 July 2012, in two colonies along the sor specific details see Adamík et al. 2016). Based on these river Tisza, at Szabolcs (48.188°N, 21.488°E, 35 males, 34 values, we defined three time periods per day: 1) a sunrise females, colony size  1700 pairs), and at Gávavencsellő period that lasted from the first light value  0 after at least (48.199°N, 21.588°E, five males, six females, colony four hours of zero values until the light value reached the

115 maximum (63) level; 2) a sunset period that lasted from the shift between two equal and consecutive sun-events was less, last maximum light level until the last value above zero, fol- or equal to five minutes, the second time period (daytime lowed by at least four hours of zero values; 3) a lightness or night-time) was classified as a stationary period; 2) if a period that lasted from the end of the sunrise period until time shift was more than five minutes between two equal the start of the sunset period. sun-events but smaller than between the two sun-events in Both species breeds in dark burrows or half-cup nests and, the step before, we assume that the bird was stationary dur- occasionally, they use similar sites (e.g. holes, caves) outside ing the second time period (daytime or night-time); 3) if a the breeding season. This behaviour can be used to divide time shift was more than five minutes between two equal recorded sun events (sunrise and sunset) into two classes: sun-events, and larger than between the two sun-events in natural and non-natural (Liechti et al. 2014, Gow et al. the step before, we supposed that the bird was moving dur- 2015). To filter such potentially biased light data, we defined ing the second time period (daytime or night-time); 4) if non-natural sunrises and sunsets on the basis of whether or condition 2 was true, but the difference in the duration of not the first/last light value was below or above an empiri- the actual day (or night, respectively) and the day before (or cally derived threshold. When the level of first/last light night, respectively) was larger than 10 min, then the period value was less than 5 (84.5% of 5313 cases), the minimum was classified as an uncertain stationary period. length of sunrise/sunset varied between 10–20 min; in other These rules are arbitrary and specifically adapted to the cases (first/last light value   5, 15.5%) the minimum data we collected with this type of geolocator. Neverthe- length of these periods varied between 0–20 min. In the first less, our classification is based on objective rules and, most case, we considered the sunrise or sunset as natural, while in importantly, is independent of calculated positions. Thus, all the second as non-natural. Zero light values during sunrise/ geographical positions within a stationary period (not inter- sunset could also indicate the use of dark sites during the rupted by a movement period) were pooled to a single site, entire sunrise/sunset period. Such events were significantly and if median geographic position between consecutive sites more frequent when the first/last light value was 5 or higher was within a 200 km radius, then sites were pooled. Sites (30.2% of 775 cases) than for lower values (6.6% of 4537 were defined by their median and 90% quartile of all geo- 2 cases; c 1  405.64, p  0.001). Consequently, sunset and graphical positions within this time period. sunrise periods with a zero value were also defined as unnatu- The seasonal pattern was defined by four specific station- ral. Finally, differences in shading between consecutive sun ary periods: 1) the end of the breeding period was defined events (sunrise and sunset) can cause an asymmetry in day by departure from the breeding grounds (leaving the first and night length and lead to error in the calculation of noon stationary site within 200 km from the breeding grounds); and midnight, thus longitude. We therefore calculated the 2) arrival at the first, and departure from the last site north difference in the length of consecutive sun event periods and of the Mediterranean Sea defined the pre-migratory period; for further analyses, days and nights with differences larger 3) arrival at the first and departure from the last site south than 55 min (upper 5% quartile) were excluded, as well as all of the ( 23.5°N) defined the non-breeding resi- non-natural sun events (example in Supplementary material dence period; 4) arrival at breeding grounds was defined by Appendix 1, Fig. A1). a stationary period within 200 km or by the occurrence of frequent unnatural sun events due to nest cavity visits. The Defining stationary periods initiation and end of autumn migration was defined by the end of the pre-migratory period and the start of the non- Geolocation divides the temporal pattern of observations breeding residency. Spring migration was defined by the end into two time steps per 24 h (daytime and night-time), and of the non-breeding residency and the start of the breed- we assumed that considerable shifts in consecutive sunrises ing period. The area associated with the longest stationary or sunsets indicate a movement. Generally, stationary peri- period south of the Sahara ( 23.5°N) was defined as the ods were defined based on the time shifts between two con- main residence area during the non-breeding period. secutive, equal sun-events (sunrises or sunsets, respectively), We defined the time period of autumn migration as which include the two time steps (daytime and night-time). the last date of the last stationary site ( 5 d) north of We decided not to use the changepoint algorithm imple- the Mediterranean Sea, and the first date of the first sta- mented in the GeoLight-software, instead applied some tionary site ( 5 d) south of the Sahara desert (latitude simple rules easy to follow. Our light data had a low impact  23.5°N). The period of spring migration was defined of shading (except cavity-use), thus, from visual inspection vice versa. alone it was obvious that some of the very short stopover periods (1–3 d) were missed by the standard algorithm. By Use of cavities using the same data as the standard algorithm we therefore developed a few arbitrary but objective rules to define sta- Sand martins and house martins are diurnal foragers of aer- tionary periods. There were almost no differences in sta- ial plankton and use cavities for breeding as well as perhaps tionary periods longer than 7 d, but we could identify in for resting (Cramp 1988). We quantified the use of cavi- addition some short stopovers during migration. We believe ties within the annual cycle and identified days with cavity that this pragmatic approach facilitated the opportunity to visits during daylight when periods of light records of zero derive more detailed results than with a standard approach occurred for at least five minutes. Cavity use during nights in our dataset. We determined for each time step whether it was determined if either sunrise or sunset was defined as was a stationary or movement period by applying the fol- unnatural events. In the case of one bird (S4, sand martin) lowing rules when all sun events were natural: 1) if the time the geolocator had slipped to the side, thus data could not be

116 used for defining cavity usage (one third of positioning data southern Africa (distance 8050 km) (Fig. 1C). Three of the was influenced). five birds we tracked stayed in one area for an average of 159 Data available from Movebank Data Repository: < doi: d (range: 144–177 d, Supplementary material Appendix 1, 10.5441/001/1.214298181 > (Szép et al. 2016). 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 Results km (range: 750–2050 km) from their main non-breeding residences (Supplementary material Appendix 1, Table A1, Autumnal pre-migration period Fig. 1C). Surprisingly, only three of the five individuals we tracked moved northwards to sites closer to the southern Sand martins departed from their breeding sites before Saharan border while two birds moved to sites in the west/ August (Szép unpubl.), although exact departure dates were southwest and stayed there for at least three weeks before not recorded because the logging season started 1 August. departing for their spring migration. In August, all tracked birds were roaming in the Carpathian Bend or in Serbia, Romania, and Bulgaria until departing for Spring migration their southbound migration (Fig. 1A, Supplementary mate- rial Appendix 1, Table A1). Three sand martins migrated straight to the north across the Tracked house martins departed between the end of July desert, while one bird followed a westerly loop (Fig. 1B). (K. Nagy unpubl.) and the first half of August from their Sand martins departed between 11 April and 7 May, and breeding site to the Carpathian Bend (three individuals) as used 5–6 stopover sites with an average stopover duration of well as to western Ukraine and western parts of Romania. 1.5 d (0.5–4 d) (Fig. 2B, Supplementary material Appendix 1, (Fig. 1C, Supplementary material Appendix 1, Table A2). Table A1). Arrival at the breeding colonies was between 29 April and 24 May resulting in a migration duration of 14 d Autumn migration (range: 8–17 d) (Fig. 2B). Their overall migration speed was an average of 349 km d–1 (range: 241–498 km d–1), while The autumn migration coincided with the equinox period, their net migration speed, excluding times spent at stopover and thus latitudinal estimates are not available during this sites (mean: 6 d, range: 6–11 d), was 621 km d–1 (range: 424– period. However, longitudinal data indicated migratory 822 km d–1, Supplementary material Appendix 1, Table A1). tracks across the Balkan region with subsequent traverses of In contrast, house martins used two distinct migration the Mediterranean Sea in both species (Fig. 1A, C). Sand routes related to difference in their main non-breeding sites. martins showed a clear shift in longitude, with an easterly Birds from eastern Africa moved along an eastward loop shift in the first half of the migration period and westerly in across the Arabian Peninsula, Turkey, and the Balkan Penin- the second. The sand martins departed on average at 9 Sep- sula and thus avoiding the crossing of the Mediterranean sea tember (5–14 of September) and arrived after 17 d (16–20 (Fig. 1D), while individuals overwintering in central Africa d) at the non-breeding areas (mean: 26 September, range: and South Africa moved straight across the desert and then 23–30 September) (Fig. 2A). The overall migration speed crossed the central part of the Mediterranean sea through averaged at 229 km d–1 (range: 155–271 km d–1). Malta/Sicily, southern Italy and Adriatic Sea, a very similar Based on longitudinal positions house martins followed a flyway to two of the tracked sand martins. Individuals over- more or less straight route to the non-breeding area in sub- wintering in central and eastern Africa departed between 26 Saharan Africa (Fig. 1C). They departed on average also at 8 April and 8 May (Fig. 2D), and stopped over at 3–7 sites for September (5–12 September) and arrived after 24 d (21–30) an average of one day (0.5–4 d). They arrived at the breeding at the non-breeding area (mean: 3 October, range: 2–5 Octo- sites between 5 and 18 May, after 10 d (6–16 d) on migration ber) south of the Sahara (Fig. 2C). The overall migration (Fig. 2D, Supplementary material Appendix 1, Table A1). speed averaged at 193 km d–1 (range: 176–219 km d–1). The bird overwintering in southern Africa left this site at the end of March and moved northwards to central Africa using Non-breeding residence three stationary sites (2–6.5 d). From these sites onwards, their migration was very similar to others (Fig. 2D); average The main non-breeding areas of tracked sand martins were overall migration speed was 594 km d–1 (range: 360–887 km situated in the Lake Chad Basin (Fig. 1A), and thus, on aver- d–1), and net migration speed, excluding time spent at stop- age 4250 km (3850–4600 km) separated from the breeding over sites (mean: 4 d, range: 2–9 d), was 1081 km d–1 (range: sites (great circle distance). Three of four birds used a single 615–1462 km d–1, Supplementary material Appendix 1, non-breeding site for on average 170 d (range: 151–193 d), Table A1). In both species, individuals with the southernmost and one bird (S2) used three distant areas (400 km, 750 main non-breeding sites left sub-Saharan Africa earlier and km, Fig. 1A). Before spring migration, between March and were first to arrive at the breeding grounds. May, two individuals moved to pre-migratory sites near Lake Chad for about 12–39 d (Fig. 1A). Usage of cavities during the annual cycle House martins were distributed widely across sub- Saharan Africa; we tracked two individuals in central Africa The majority of birds of both species used cavities during the (4250 and 4500 km great circle distances from their breeding day when breeding but only occasionally during migration and sites), two individuals in eastern Africa (Uganda, Ethiopia, the non-breeding residence period (Fig. 3A). Cavity use during distances of 4250 and 5200 km), and one individual in the nights occured most frequently during the breeding period

117 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. The 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. and less often during non-breeding residence and migration Discussion periods (Fig. 3B). Results show that house martins used cavi- ties more often on their African non-breeding (15.3 vs 0.7%, This study has revealed, for the first time, the spatio-tempo- 2 c 1  95.129, p  0.001) and breeding sites (80.3 vs 50.4%, ral migration patterns and non-breeding locations for indi- 2 c 1  36.219, p  0.001) than sand martins (Fig. 3B). vidual sand martins and house martins.

118 (A) (B) 01.09.2012 01.04.2013

08.09.2012 08.04.2013

15.09.2012 15.04.2013

22.09.2012 22.04.2013

29.09.2012 1w1 1w1 29.04.2013 2w1 2w4 06.10.2012 3w1 3w2 06.05.2013 4w1 4w2 13.10.2012 13.05.2013

20.10.2012 20.05.2013

27.10.2012 27.05.2013 0 2000 4000 6000 –6000 –4000 –2000 0 Distance from the breeding area (km) Distance to the breeding area (km)

(C) (D) 01.09.2012 01.04.2013

08.09.2012 08.04.2013

15.09.2012 15.04.2013

22.09.2012 22.04.2013 1w1 1w2 29.09.2012 2w1 2w3 29.04.2013 3w1 3w3 06.10.2012 06.05.2013 4w1 4w7 13.10.2012 5w1 5w2 13.05.2013

20.10.2012 20.05.2013

27.10.2012 27.05.2013 0 2000 4000 6000 –6000–4000 –2000 0 Distance from the breeding area (km) Distance to the breeding area (km)

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).

The Carpathian Bend is well known as an important but not fully with the 38 spring recapture/recoveries from area for the preparation of autumn migration in both spe- our studied population, which are distributed along the cies (Králl and Karcza 2009, Szép 2009), but our study now wide west–east range of the Mediterranean basin (Fig. 1B). shows that some northern parts of the Balkan Peninsula are While recoveries do point towards a more widespread non- similar important. Recapture data from birds from our stud- breeding range in Africa with low migratory connectivity, ied populations confirm this finding (Fig. 1A). our results support the opposite view. Due to considerable When migrating, our track records show that sand mar- differences in reporting rates among the different countries, tins move along the Balkan Peninsula, and cross the Mediter- ringing recoveries/recaptures have a considerable geographi- ranean Sea at Greece in a narrow band, in contrast to recent cal bias. However, our small sample size does not allow for recoveries from Italy and Malta that indicate a much wider a final conclusion with respect to the strength of migratory autumn migration corridor (Cepák 2008, Heneberg 2008, connectivity. Obviously, the main non-breeding area of our Králl and Karcza 2009, Szép 2009). Mismatch between our studied population is situated more to the east compared to records and others may be due to the specific weather con- recoveries of the western and central European populations ditions during the study year, as all individuals we studied (Mead 2002, Walther et al. 2010, Bairlein et al. 2014). Trace departed for their autumn migration within a very narrow element profiles of feathers grown by the British and Span- nine day time period. In addition, individuals from both ish martins while in Africa (overwintering in the western species followed a route which included just a 500 km sea Sahel) differed from Hungarian birds (Szép et al. 2003a) in crossing. However, due to a lack of latitudinal information, concordance with the geolocation result. we cannot distinguish whether, or not, this directional shift In contrast, the house martins in our study are shown to occurred in northern Africa (Fig. 1A). occupy a much larger non-breeding range than sand martins. Contrary to our expectations, the studied sand martins We identified three distant, non-breeding areas in central, spent the non-breeding season in an area with a radius of eastern, and southern Africa that appear to have weak migra- less than 700 km in northern Cameroon and the Lake Chad tory connectivity. Very few central European birds have been Basin. This result is consistent with two central-eastern Euro- recovered from central Africa (Bairlein et al. 2014), and pean population ringed birds recovered from Lake Chad, records of non-breeding areas in eastern Africa represent

119 (A) behaviour could be estimated. The most striking difference House martin Sand martin in migratory routes was not between species, but rather 120 between geographical positions of main non-breeding areas. 100 Identified passage areas in the spring across the central part 80 of the Mediterranean basin coincide very well with most (%) 60 recapture sites known for both Pannonian populations

40 (Cepák 2008, Heneberg 2008, Králl and Karcza 2009, Szép 2009). Only two house martins overwintering in eastern

during day 20 Africa circumvented the Mediterranean Sea on their spring 0 Premigratory, Migration, WinteringMigration, Breeding migration as is the case in other insectivorous birds (i.e. Frequency of usage cavities autumn autumn spring red-backed shrikes; Tottrup et al. 2012). Although autumn Season migration routes can only be reconstructed here using lon- gitudinal information, there is good evidence that none of (B) the individuals followed the same route in both autumn and House martin Sand martin spring. Migration duration in sand martins was very simi- *** 100 lar in autumn and spring, while house martins spent almost 80 three times more days on their autumn compared to their

(%) spring migration. As a result, the overall travelling speed of 60 *** house martins was about 16% lower than the sand martins nights 40 in autumn, but 70% faster in the spring. Indeed, five out

20 of the nine birds we tracked returned in spring in 10 d or

during less. Departure and arrival dates were also less synchronous 0 in the spring compared to the autumn for all individuals of Premigratory, Migration, WinteringMigration, Breeding Frequency of usage cavities autumn autumn spring both species, but there was a high correlation in departure Season and arrival dates (r   0.88, Pearson) with the exception of the house martins in autumn. In both seasons, migratory Figure 3. Frequency of cavities usage (mean  SD) of sand martins distances were slightly longer for house martins than they and house martins during the day (A) and the night (B) for the four were for sand martins (∼ 20%), taking into account the first non-breeding periods defined (see Methods) and the breeding sea- son (significant differences are marked with ***: p  0.001). (for autumn) and the last (for spring) sub-Saharan stationary sites. There were also no obvious differences in overall migra- tion speeds in the spring within species compared to dates, new results for central-eastern European breeding house distances, or chosen route. Thus, in both species, arrival at martins. Non-breeding areas in southern Africa were already breeding grounds was strongly determined by the date of known for northern European and German populations departure from the last sub-Saharan non-breeding site. (Hill 2002, Bairlein et al. 2014, Valkama 2014), but had During spring migration, when time spent at stopover- not been recorded before for central-eastern European popu- sites could be estimated, individuals of both species where lations. All the non-breeding sites for Pannonian birds are stationary for nearly half of their migration period. Net situated east with respect to indirectly assigned non-breeding migration speeds were over 400 km d–1 for sand martins, areas for a Dutch population (Hobson et al. 2012) and some rising to twice this value for house martins, over 800 km north Italian individuals (Ambrosini et al. 2011). Neverthe- d–1; this strongly suggests that these birds use tail winds, as less, there is considerable overlap in the non-breeding areas air speeds measured for migrating sand martins and house now known for Pannonian house martins with several other martins average around 40 km h–1 (Liechti and Bruderer European populations; as a result, our findings do not sup- 2002). In contrast, net migration speeds during the spring port the hypothesis that there is a longitudinal separation in tended to be higher for individuals using more distant non- the non-breeding areas of European populations (Hill 2002, breeding residence areas; these birds must have either been Ambrosini et al. 2011). Within the pre-migratory period, able to accumulate more fuel reserves before departure, prof- two of our five house martins moved considerably westward, ited from abundant food resources en route, or benefited towards an area where birds from the western and central more from tail winds. As none of the individuals (in both European population have also been recovered during this species) surpassed another during spring migration, and time of the year (Bairlein et al. 2014). However, whether because spring migration was generally fast (especially in or not these birds spent their whole non-breeding period house martins), we assume that there is a strong carry-over within this area remains unclear. effect between departure from sub-Saharan Africa and arrival One reason for the low recovery rate of house martins at breeding grounds although more track records will clearly compared to other swallows might be their more frequent be needed to statistically support this assumption. use of cavities (e.g. caves, trees, buildings) during the non- To define stationary periods during spring migration breeding season in Africa. Such roosts are much more diffi- in such details, we had to overcome the standard method cult to find, are occupied by a smaller number of individuals, used so far (GeoLight). We must admit that our approach and therefore are less attractive to local people than the huge provided reliable results only because of the high quality roosts of the other two species (Hill 2002). light data, with very minor shading effects (Lisovski et al. Spring migrations of our studied individuals took 2012). Based on our data, the fastest spring migration of place after the equinox and, therefore, tracks and stopover a house martin (H5) was reconstructed using a movement

120 period of 4.5 d, resulting in an average ground speed of 52 Both, C., Bouwhuis, S., Lessells, C. M. and Visser, M. E. 2006. km h–1. This is a realistic speed, well in line with known Climate change and population declines in a long-distance ground speeds measured by radar for small migrating pas- migratory bird. – Nature 441: 81–83. serines (Liechti and Bruderer 2002). Finally, as all the speeds Cepák, J. 2008. Jiricka obcena (house martin). – In: Cepák, J., Klvana, P., Škopek, L., Schröpfer, L., Jelínek, M., Horák, D., we estimated were within a realistic range, our filtering seems Formánek, J. and Zárybnický, J. (eds), Czech and Slovak bird to provide feasible results. migration atlas. Aventinum, pp. 337–339. Cramp, S. 1988. The birds of the Western Palearctic, vol. 5. Conclusions – Oxford Univ. Press. Donald, P. F., Green, R. E. and Heath, M. F. 2001. Agricultural In contrast to the existing ringing recoveries from our sand intensification and the collapse of Europe’s farmland bird martin population, the migration and non-breeding residency populations. – Proc. R. Soc. B 268: 25–29. of the studied sand martins was fairly concentrated. Instead, Gomez, J., Michelson, C. I., Bradley, D. W., Norris, D. R., Berzins, for our studied house martins non-breeding residency of the L. L., Dawson, R. D. and Clark, R. G. 2014. Effects of geolocators on reproductive performance and annual return five individuals was distributed across a huge area insub- rates of a migratory songbird. – J. Ornithol. 155: 37–44. saharan Africa, not supporting proposed population specific Gow, E. A., Wiebe, K. L. and Fox, J. W. 2015. Cavity use through- non-breeding ranges. Due to the small sample size these pre- out the annual cycle of a migratory woodpecker revealed by liminary conclusions need to be verified by further investiga- geolocators. – Ibis 157: 167–170. tions. The geolocator study provided substantial information Hahn, S., Bauer, S. and Liechti, F. 2009. The natural link between for the whereabouts of the Pannonian populations of sand Europe and Africa – 2.1 billion birds on migration. – Oikos martin and house martin. However, there are also drawbacks 118: 624–626. of the method. For instance the lower return rates of geo- Harrison, X. A., Blount, J. D., Inger, R., Norris, D. R. and Bearhop, S. 2011. Carry-over effects as drivers of fitness differences in locator birds compared to controls calls for cautious use of . – J. Anim. Ecol. 80: 4–18. geolocators on such small birds, especially aerial feeders (see Heneberg, P. 2008. Brehule ricni (sand martin). – In: Cepák, J., also Gomez et al. 2014, Scandolara et al. 2014) and careful Klvana, P., Škopek, L., Schröpfer, L., Jelínek, M., Horák, D., interpretation of data on timing (Arlt et al. 2013). However, Formánek, J. and Zárybnický, J. (eds), Czech and Slovak bird geolocation remains the only method to track the martins migration atlas. Aventinum, pp. 329–331. to date. 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. Acknowledgements – We thank Ákos Pelenczei, Zoltán Görögh, Hill, L. A. 2002. House martin. – In: Wernham, C. V., Toms, M. János Danku, Annamária Danku, Beáta Bokor, Ivett Kakszi, Zsolt P., Marchant, J. H., Clark, J. A., Siriwardena, G. M. and Hörcsik, the members of the local chapter of the MME/BirdLife Baillie, S. R. (eds), Britain and Ireland: the migration atlas: Hungary for the important help in the field work, and Edit Molnár movements of the birds of Britain and Ireland. Poyser, for processing our field data. The deployment of the geolocators pp. 465–467. and related field works were carried out with the permission of the Hobson, K. A., Van Wilgenburg, S. L., Piersma, T. and Wassenaar, Hungarian National Inspectorate for Environment, Nature and L. I. 2012. Solving a migration riddle using isoscapes: house Water (14/2104/5/2012). The study was donated by ‘Madárvé- martins from a Dutch village winter over west Africa. – PLoS delem határok nélkül’ HUSK/1101/2.2.1/0336 project of the EU One 7: e45005. and by the local chapter of the MME/BirdLife Hungary. The Swiss Králl, A. and Karcza, Z. 2009. 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Supplementary material (Appendix JAV-01339 at < www. avianbiology.org/appendix/jav-01339 >). Appendix 1.­

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