Journal of Ornithology

, Volume 156, Issue 4, pp 991–998 | Cite as

Pattern of non-breeding movements by Stone-curlews Burhinus oedicnemus breeding in Northern Italy

  • Dimitri GiunchiEmail author
  • Chiara Caccamo
  • Alessia Mori
  • James W. Fox
  • Felipe Rodríguez-Godoy
  • N. Emilio Baldaccini
  • Enrica Pollonara
Original Article


The identification of year-round geographical ranges and the quantification of the degree of migratory connectivity are fundamental to the successful conservation of migratory bird populations. The Stone-curlew Burhinus oedicnemus is a species of conservation concern in Europe, but its ecology and behaviour are relatively poorly investigated. In particular, its migratory behaviour and the locations of the wintering ranges of most European populations are not known in detail because of a lack of specific studies and the scarcity of ringing recoveries. This study aimed to identify the wintering areas of a Stone-curlew population breeding in the Taro River Regional Park (Parma, northern Italy) by integrating the information obtained from ringing recoveries (n = 2), geolocators (n = 7), and GPS data loggers (n = 2). Furthermore, we compared two approaches to inferring the location of an assumed stationary bird using geolocator data. The different sources were quite coherent, indicating that tagged Stone-curlews did not leave the Mediterranean basin throughout the year and passed the winter in Sardinia or in Tunisia. The recorded wintering sites coincided with areas where breeding (and possibly resident) populations are reported, further emphasising the importance of these areas for the conservation of the species throughout the annual cycle. To our knowledge, our study represents the first thorough analysis performed to uncover the movements of a Mediterranean population of Stone-curlews. Furthermore, it proves the great potential of the tracking devices used in this work to provide information on the migration and non-breeding sites of elusive species, for which the application of mark–recapture/re-sighting techniques is hindered by profound limitations.


Migration Geolocator GPS Ringing 


Muster des Zugverhaltens von in Norditalien brütenden Trielen Burhinus oedicnemus außerhalb der Brutzeit Die ganzjährige Identifikation der Aufenthaltsgebiete sowie die Quantifizierung des Zugverhaltens sind elementar für den erfolgreichen Schutz von Zugvögeln. Triele Burhinus oedicnemus gelten in Europa als in ihrem Bestand gefährdet, und dennoch wird ihre Verhaltensökologie unzureichend untersucht. Besonders das Zugverhalten und die Überwinterungsquartiere vieler europäischer Populationen sind im Detail nicht bekannt, da entweder spezifische Untersuchungen oder Ringfundmeldungen fehlen. Das Ziel dieser Studie war es, die Überwinterungsquartiere einer im Gebiet des Flusses Taro „Parco Taro“(Parma, Norditalien) brütenden Population von Trielen, zu identifizieren. Hierfür wurden die Informationen von Ringfunden (n = 2), Geolokatoren (n = 7) und GPS-Loggern (n = 2) zusammengefasst. Des Weiteren verglichen wir zwei Ansätze für die Bestimmung des Aufenthaltsortes eines augenscheinlich nicht ziehenden Vogels mittels Geolokatoren. Die unterschiedlichen Informationsquellen erwiesen sich als weitgehend übereinstimmend und deuteten darauf hin, dass die markierten Triele sich ganzjährlich im Mittelmeergebiet aufhielten und den Winter auf Sardinien oder in Tunesien verbrachten. Weiterhin stimmten die ermittelten Überwinterungsquartiere mit Brutquartieren vermutlicher standtreuer Triele überein. Dies unterstreicht die ganzjährige Bedeutung dieser Landstriche für den Schutz der Triele. Unsere Studie repräsentiert unseres Wissens die erste vollständige Analyse zu Bewegungsmustern einer Mittelmeerpopulation von Trielen. Darüber hinaus belegt sie das große Potenzial von Standortbestimmungstechniken für den Erhalt von Informationen zum Zugverhalten und zu Überwinterungsquartieren schwer zugänglicher Arten, für welche Rückfangmethoden oder herkömmliche Beobachtungstechniken sich als stark eingeschränkt erwiesen.



We are grateful to all the people who helped us during the fieldwork, and in particular to Renato Carini and Renzo Rusticali. The Taro River Regional Park supported part of the research.

Supplementary material

10336_2015_1219_MOESM1_ESM.jpg (662 kb)
Fig. S1. Maps reporting the filtered WINT fixes (filled dots) of geolocator-tagged birds estimated by means of method 1 along with kernel densities encompassing 50 % (KDE 50 %) of the maximum density. Supplementary material 1 (JPEG 663 kb)
10336_2015_1219_MOESM2_ESM.jpg (681 kb)
Fig. S2. Maps reporting the filtered NEST fixes (filled dots) of geolocator-tagged birds estimated by means of method 1 along with kernel densities encompassing 50 % (KDE 50 %) of the maximum density. Supplementary material 2 (JPEG 682 kb)
10336_2015_1219_MOESM3_ESM.jpg (223 kb)
Fig. S3. Distributions of the most likely NEST locations of geolocator-tagged birds estimated by means of method 1 (A, centroid of KDE 50 %) or method 2 (B, latitude = average and range of the three northernmost available NEST fixes; longitude = average ± SD of all available NEST fixes). Open square and diamond indicate the two members of the same breeding pair. Deployment and recapture sites of each bird were considered coincident (Nest site in the figure) because their distance was always less than 150 m. Supplementary material 3 (JPEG 223 kb)


  1. BirdLife International (2004) Birds in Europe. BirdLife International, WageningenGoogle Scholar
  2. Brichetti P, Fracasso G (2004) Ornitologia Italiana: Tetraonidae–Scolopacidae, vol 2. Perdisa, BolognaGoogle Scholar
  3. Bridge ES, Thorup K, Bowlin MS, Chilson PB, Diehl RH, Fléron RW, Hartl P, Kays R, Kelly JF, Robinson WD, Wikelski M (2011) Technology on the move: recent and forthcoming innovations for tracking migratory birds. Bioscience 61:689–698CrossRefGoogle Scholar
  4. Bridge ES, Kelly JF, Contina A, Gabrielson RM, MacCurdy RB, Winkler DW (2013) Advances in tracking small migratory birds: a technical review of light-level geolocation. J Field Ornithol 84:121–137CrossRefGoogle Scholar
  5. Calenge C (2006) The package “adehabitat” for the R software: a tool for the analysis of space and habitat use by animals. Ecol Model 197:516–519CrossRefGoogle Scholar
  6. Costantini D, Møller AP (2013) A meta-analysis of the effects of geolocator application on birds. Curr Zool 59:697–706Google Scholar
  7. Cramp S, Simmons KEL (1983) The birds of the western Palearctic, vol 3. Oxford University Press, OxfordGoogle Scholar
  8. del Hoyo J, Elliott A, Sargatal J (eds) (1996) Handbook of the birds of the world, vol 3, Hoatzin to auks. Lynx Edicions, BarcelonaGoogle Scholar
  9. Doswald N, Willis SG, Collingham YC, Pain DJ, Green RE, Huntley B (2009) Potential impacts of climatic change on the breeding and non-breeding ranges and migration distance of European Sylvia warblers. J Biogeogr 36:1194–1208CrossRefGoogle Scholar
  10. Dragonetti M, Corsi F, Farsi F, Passalacqua L, Giovacchini P (2014) Roosting behaviour of Stone-curlews. Wader Study Group Bull 121:1–6Google Scholar
  11. Faaborg J, Holmes RT, Anders AD, Bildstein KL, Dugger KM, Gauthreaux SA, Heglund P, Hobson KA, Jahn AE, Johnson DH, Latta SC, Levey DJ, Marra PP, Merkord CL, Nol E, Rothstein SI, Sherry TW, Sillett TS, Thompson FR, Warnock N (2010) Conserving migratory land birds in the New World: do we know enough? Ecol Appl 20:398–418CrossRefPubMedGoogle Scholar
  12. Fiedler W, Bairlein F, Köppen U (2004) Using large-scale data from ringed birds for the investigation of effects of climate change on migrating birds: pitfalls and prospects. In: Moller AP, Fiedler W, Berthold P (eds) Birds and climate change. Elsevier, Amsterdam, pp 49–67Google Scholar
  13. Fraser KC, Stutchbury BJM, Silverio C, Kramer PM, Barrow J, Newstead D, Mickle N, Cousens BF, Lee JC, Morrison DM, Shaheen T, Mammenga P, Applegate K, Tautin J (2012) Continent-wide tracking to determine migratory connectivity and tropical habitat associations of a declining aerial insectivore. Proc R Soc B Biol Sci 279:4901–4906CrossRefGoogle Scholar
  14. Giunchi D, Pollonara E, Baldaccini NE (eds) (2009) L’occhione (Burhinus oedicnemus): biologia e conservazione di una specie di interesse comunitario—indicazioni per la gestione del territorio e delle aree protette. Consorzio del Parco Fluviale Regionale del Taro, CollecchioGoogle Scholar
  15. Green RE, Hodson DP, Holness PR (1997) Survival and movements of Stone-curlews Burhinus oedicnemus ringed in England. Ringing Migr 18:102–112CrossRefGoogle Scholar
  16. Griffiths R, Double MC, Orr K, Dawson RJG (1998) A DNA test to sex most birds. Mol Ecol 7:1071–1075CrossRefPubMedGoogle Scholar
  17. Hill R (1994) Theory of geolocation by light levels. In: LeBouef BJ, Laws RM (eds) Elephant seals: population ecology, behavior, and physiology. University of California Press, Berkeley, pp 227–236Google Scholar
  18. Johnson OW, Fielding L, Fisher JP, Gold RS, Goodwill RH, Bruner AE, Furey JF, Brusseau PA, Brusseau NH, Johnson PM (2012) New insight concerning transoceanic migratory pathways of Pacific Golden-Plovers (Pluvialis fulva): the Japan stopover and other linkages as revealed by geolocators. Wader Study Group Bull 119:1–8Google Scholar
  19. Klaassen RHG, Alerstam T, Carlsson P, Fox JW, Lindström Å (2011) Great flights by great snipes: long and fast non-stop migration over benign habitats. Biol Lett 7:833–835PubMedCentralCrossRefPubMedGoogle Scholar
  20. Knudsen E, Lindén A, Both C, Jonzén N, Pulido F, Saino N, Sutherland WJ, Bach LA, Coppack T, Ergon T, Gienapp P, Gill JA, Gordo O, Hedenström A, Lehikoinen E, Marra PP, Møller AP, Nilsson ALK, Péron G, Ranta E, Rubolini D, Sparks TH, Spina F, Studds CE, Saether SA, Tryjanowski P, Stenseth NC (2011) Challenging claims in the study of migratory birds and climate change. Biol Rev 86:928–946CrossRefPubMedGoogle Scholar
  21. Lisovski S, Hahn S (2012) GeoLight—processing and analysing light-based geolocator data in R. Methods Ecol Evol 3:1055–1059CrossRefGoogle Scholar
  22. Lisovski S, Hewson CM, Klaassen RHG, Korner-Nievergelt F, Kristensen MW, Hahn S (2012) Geolocation by light: accuracy and precision affected by environmental factors. Methods Ecol Evol 3:603–612CrossRefGoogle Scholar
  23. Marra PP, Hunter D, Perrault AM (2011) Migratory connectivity and the conservation of migratory animals. Environ Law 41:317–655Google Scholar
  24. McKinnon EA, Fraser KC, Stutchbury BJM (2013) New discoveries in landbird migration using geolocators, and a flight plan for the future. Auk 130:211–222CrossRefGoogle Scholar
  25. Minton C, Gosbell K, Johns P, Christie M, Klaassen M, Hassell C, Boyle A, Jessop R, Fox JW (2011) Geolocator studies on Ruddy Turnstones Arenaria interpres and Greater Sandplovers Charadrius leschenaultii in the East Asian–Australasia Flyway reveal widely different migration strategies. Wader Study Group Bull 118:87–96Google Scholar
  26. Mori A, Baldaccini NE, Baratti M, Caccamo C, Dessì-Fulgheri F, Grasso R, Nouira S, Ouni R, Pollonara E, Rodriguez-Godoy F, Spena MT, Giunchi D (2014) A first assessment of genetic variability in the Eurasian Stone-curlew Burhinus oedicnemus. Ibis 156:687–692CrossRefGoogle Scholar
  27. Naef-Daenzer B (2007) An allometric function to fit leg-loop harnesses to terrestrial birds. J Avian Biol 38:404–407CrossRefGoogle Scholar
  28. Newton I (2008) The migration ecology of birds. Academic, LondonGoogle Scholar
  29. Porter R, Smith PA (2013) Techniques to improve the accuracy of location estimation using light-level geolocation to track shorebirds. Wader Study Group Bull 120:147–158Google Scholar
  30. Rappole JH, Tipton AR (1991) New harness design for attachment of radio transmitters to small passerines. J Field Ornithol 62:335–337Google Scholar
  31. R Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.
  32. Seguin J-F (2011) Répartition et effectif de la population d’œdicnème criard (Burhinus oedicnemus) en Corse. Actualisation dans le cadre de la SCAP et des ZNIEFF. Rapport Ornithys.Google Scholar
  33. SEO/BirdLife (2012) Análisis Preliminar del Banco de Datos de Anillamiento de Aves del Ministerio de Agricultura, Alimentación y Medio Ambiente, para la Realización de un Atlas de Migración de Aves de España. SEO/BirdLife-Fundación Biodiversidad, MadridGoogle Scholar
  34. Smith M, Bolton M, Okil DJ, Okil DJ, Summers RW, Ellis P, Liechti F, Wilson JD (2014) Geolocator tagging reveals Pacific migration of Red-necked Phalarope Phalaropus lobatus breeding in Scotland. Ibis 156:870–873CrossRefGoogle Scholar
  35. Spina F, Volponi S (2008) Atlante della Migrazione degli Uccelli in Italia. 1. Non-Passeriformi. Ministero dell’Ambiente e della Tutela del Territorio e del Mare, Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA), RomaGoogle Scholar
  36. Taylor CM, Norris DR (2010) Population dynamics in migratory networks. Theor Ecol 3:65–73CrossRefGoogle Scholar
  37. Thibault J, Bonaccorsi G (1999) The birds of Corsica: an annotated checklist. British Ornithologists’ Union, TringGoogle Scholar
  38. Tinarelli R, Alessandria G, Giovacchini P, Gola L, Ientile R, Meschini A, Nissardi S, Parodi R, Perco F, Taiariol PL, Zucca C (2009) Consistenza e distribuzione dell’occhione in italia: aggiornamento al 2008. In: Giunchi D, Pollonara E, Baldaccini NE (eds) L’occhione (Burhinus oedicnemus): biologia e conservazione di una specie di interesse comunitario—indicazioni per la gestione del territorio e delle aree protette. Consorzio del Parco Fluviale Regionale del Taro, Collecchio, pp 45–50Google Scholar
  39. Vaughan R, Vaughan-Jennings N (2005) The Stone-curlew Burhinus oedicnemus. Isabelline, FalmouthGoogle Scholar
  40. Webster MS, Marra PP, Haig SM, Bensch S, Holmes RT (2002) Links between worlds: unraveling migratory connectivity. Trends Ecol Evol 17:76–83CrossRefGoogle Scholar
  41. Wikelski M, Kays RW, Kasdin NJ, Thorup K, Smith JA, Swenson GW (2007) Going wild: what a global small-animal tracking system could do for experimental biologists. J Exp Biol 210:181–186CrossRefPubMedGoogle Scholar
  42. Worton BJ (1995) Using Monte Carlo simulation to evaluate kernel-based home range estimators. J Wildl Manage 59:794–800CrossRefGoogle Scholar

Copyright information

© Dt. Ornithologen-Gesellschaft e.V. 2015

Authors and Affiliations

  1. 1.Dipartimento di BiologiaUniversità di PisaPisaItaly
  2. 2.British Antarctic Survey, Natural Environment Research CouncilCambridgeUK
  3. 3.Migrate Technology LtdCambridgeUK
  4. 4.Servicio de Biodiversidad, Gobierno de Canarias, Edf. Servicios Múltiples IILas Palmas de Gran CanariaSpain

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