The genetic structure of the European breeding populations of a declining farmland bird, the ortolan bunting (Emberiza hortulana), reveals conservation priorities

  • Caroline Moussy
  • Raphaël Arlettaz
  • José Luis Copete
  • Svein Dale
  • Valery Dombrovski
  • Jaanus Elts
  • Romain Lorrillière
  • Riho Marja
  • Eric Pasquet
  • Markus Piha
  • Tuomas Seimola
  • Gunnar Selstam
  • Frédéric Jiguet
Research Article

Abstract

Anthropogenic activities, such as agricultural intensification, caused large declines in biodiversity, including farmland birds. In addition to demographic consequences, anthropogenic activities can result in loss of genetic diversity, reduction of gene flow and altered genetic structure. We investigated the distribution of the genetic variation of a declining farmland and long-distance migratory bird, the ortolan bunting Emberiza hortulana, across its European breeding range to assess the impact of human-driven population declines on genetic diversity and structure in order to advise conservation priorities. The large population declines observed have not resulted in dramatic loss of genetic diversity, which is moderate to high and constant across all sampled breeding sites. Extensive gene flow occurs across the breeding range, even across a migratory divide, which contributes little to genetic structuring. However, gene flow is asymmetric, with the large eastern populations acting as source populations for the smaller western ones. Furthermore, breeding populations that underwent the largest declines, in Fennoscandia and Baltic countries, appear to be recently isolated, with no gene exchange occurring with the eastern or the western populations. These are signs for concern as declines in the eastern populations could affect the strength of gene flow and in turn affect the western populations. The genetic, and demographic, isolation of the northern populations make them particularly sensitive to loss of genetic diversity and to extinction as no immigration is occurring to counter-act the drastic declines. In such a situation, conservation efforts are needed across the whole breeding range: in particular, protecting the eastern populations due to their key role in maintaining gene flow across the range, and focussing on the northern populations due to their recent isolation and endangered status.

Keywords

Endangered species Gene flow Genetic diversity Long-distance migrant 

Notes

Acknowledgements

This project was funded by a grant obtained from the LabEx BCDiv at the MNHN. It was part of a global research investigating the migration strategy of the species funded by the French Ministry of Ecology (Ministère de l’Écologie, du Développement Durable et de l’Énergie), Fédération Départementale des Chasseurs des Landes, Conseil Général des Landes, Conseil Régional d’Aquitaine, and Association de Défense des Chasses Traditionnelles à la Matole. This study was possible thanks to international collaboration and we are grateful to all participants to field work for collecting samples for genetic analysis. In particular, we offer our thanks to Maxime Zucca, Romain Provost, Benoit Fontaine, Anne-Christine Monnet, Simon Rolland, Pierre Fiquet, Lionel Courmont, Sébastien Blache, Dzmitry Zhurauliou, Pavel Kharytonau, Juha Honkala, Tuomo Jaakkonen, Johanna Lakka, Lars Erik Johannessen, Marc Pérez and Carlos Grande. We also would like to thank the staff at the Service de Systématique Moléculaire UMS2700 for their advice and assistance during molecular work, especially Regis Debruyne for his assistance in the shot-gun sequencing on the Ion Torrent platform and in HRM analysis, Jawad Abdelkrim for advice in processing the NGS reads and Josie Lambourdière for sharing her invaluable experience in developing and optimizing the microsatellite loci. PCR products were genotyped at the Gentyane platform, INRA Clermont-Ferrand, France.

Supplementary material

10592_2018_1064_MOESM1_ESM.docx (44 kb)
Supplementary material 1 (DOCX 43 KB)

References

  1. Belkhir K, Borsa P, Chikhi L et al (2004) GENETIX 4.05, logiciel sous Windows TM pour la genetique des populations. Université de Montpellier II, MontpellierGoogle Scholar
  2. Bensch S, Andersson T, Akesson S (1999) Morphological and molecular variation across a migratory divide in Willow Warblers, Phylloscopus trochilus. Evolution 53:1925–1935CrossRefPubMedGoogle Scholar
  3. Benton TG, Bryant DM, Cole L, Crick HQP (2002) Linking agricultural practice to insect and bird populations: a historical study over three decades. J Appl Ecol 39:673–687CrossRefGoogle Scholar
  4. Bijlsma R, Loeschcke V (2012) Genetic erosion impedes adaptive responses to stressful environments. Evol Appl 5:117–129CrossRefPubMedGoogle Scholar
  5. BirdLife International (2015) Species factsheet: Emberiza hortulana. http://www.birdlife.org. Accessed Sept 2016
  6. Cousseau L, Husemann M, Foppen R et al (2016) A longitudinal genetic survey identifies temporal shifts in the population structure of Dutch house sparrows. Heredity 117:259–267CrossRefPubMedPubMedCentralGoogle Scholar
  7. Crochet P-A (2000) Genetic structure of avian populations: allozymes revisited. Mol Ecol 9:1463–1469CrossRefPubMedGoogle Scholar
  8. Dale S (2001) Female-biased dispersal, low female recruitment, unpaired males, and the extinction of small and isolated bird populations. Oikos 92:344–356CrossRefGoogle Scholar
  9. Dale S (2010) Sibling resemblance in natal dispersal distance and direction in the ortolan bunting Emberiza hortulana. Ibis 152:292–298CrossRefGoogle Scholar
  10. Dale S, Lunde A, Steifetten Ø (2005) Longer breeding dispersal than natal dispersal in the ortolan bunting. Behav Ecol 16:20–24CrossRefGoogle Scholar
  11. Donald PF, Green RE, Heath MF (2001) Agricultural intensification and the collapse of Europe’s farmland bird populations. Proc R Soc London Ser B 268:25–29CrossRefGoogle Scholar
  12. Donald PF, Sanderson FJ, Burfield IJ, van Bommel FPJ (2006) Further evidence of continent-wide impacts of agricultural intensification on European farmland birds, 1990–2000. Agric Ecosyst Environ 116:189–196CrossRefGoogle Scholar
  13. Earl DA, VonHoldt BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4:359–361CrossRefGoogle Scholar
  14. Eckert CG, Samis KE, Lougheed SC (2008) Genetic variation across species’ geographical ranges: the central-marginal hypothesis and beyond. Mol Ecol 17:1170–1188CrossRefPubMedGoogle Scholar
  15. Eif JR (2013) Long-term trends in bird populations: a review of patterns and potential drivers in North America and Europe. Acta Ornithol 48:1–16CrossRefGoogle Scholar
  16. Elts J, Tätte K, Marja R (2015) What are the important landscape components for habitat selection of the ortolan bunting Emberiza hortulana in northern limit of range? Eur J Ecol 1:13–25Google Scholar
  17. Epps CW, Keyghobadi N (2015) Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change. Mol Ecol 24:6021–6040CrossRefPubMedGoogle Scholar
  18. Eurostat (2016) Land cover, land use and landscape. https://ec.europa.eu/eurostat/statistics-explained/index.php/Land_cover,_land_use_and_landscape. Accessed Sept 2016
  19. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14:2611–2620CrossRefPubMedGoogle Scholar
  20. Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131:479–491PubMedPubMedCentralGoogle Scholar
  21. Fourcade Y, Richardson DS, Keiss O et al (2016) Corncrake conservation genetics at a European scale: the impact of biogeographical and anthropological processes. Biol Conserv 198:210–219CrossRefGoogle Scholar
  22. Frankham R, Ballou JD, Briscoe DA (2004) Introduction to conservation genetics, 4th edn. Cambridge University Press, CambridgeGoogle Scholar
  23. Goudet J (1995) FSTAT (version 1.2): a computer program to calculate F-statistics. J Hered 86:485–486CrossRefGoogle Scholar
  24. Goudet J (2001) FSTAT, a program to estimate and test gene diversities and fixation indices (version 2.9.3). http://www2.unil.ch/popgen/software. Accessed Sept 2016
  25. Goudet J (2005) HIERFSTAT, a package for R to compute and test hierarchical F-statistics. Mol Ecol Notes 5:184–186CrossRefGoogle Scholar
  26. Goudet J, Raymond M, de Meeüs T, Rousset F (1996) Testing differentiation in diploid populations. Genetics 144:1933–1940PubMedPubMedCentralGoogle Scholar
  27. Greenwood PJ (1980) Mating systems, philopatry and dispersal in birds and mammals. Anim Behav 28:1140–1162CrossRefGoogle Scholar
  28. Gregory RD, Strien A, Van Vorisek P et al (2005) Developing indicators for European birds. Philos Trans R Soc B 360:269–288CrossRefGoogle Scholar
  29. Hoffman JI, Simpson F, Lacy RC et al (2014) High-throughput sequencing reveals inbreeding depression in a natural population. Proc Natl Acad Sci USA 111:3775–3780CrossRefPubMedPubMedCentralGoogle Scholar
  30. Jakobsson M, Rosenberg N (2007) CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23:1801–1806CrossRefPubMedGoogle Scholar
  31. Jiguet F, Arlettaz R, Bauer H et al (2016a) An update of the European breeding population sizes and trends of the ortolan bunting (Emberiza hortulana). Ornis Fenn 93:186–196Google Scholar
  32. Jiguet F, Arlettaz R, Belik V et al (2016b) Migration strategy of the ortolan bunting: final report of the scientific committee. MNHN, Paris. https://spn.mnhn.fr/servicepatrimoinenaturel/images/COMMUNICATION/SUPPORTS/AUTRES_RAPPORTS/FinalReportortolanandappendices.zip
  33. Jombart T (2008) adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24:1403–1405CrossRefPubMedGoogle Scholar
  34. Jombart T, Devillard S, Balloux F (2010) Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet 11:94CrossRefPubMedPubMedCentralGoogle Scholar
  35. Kalinowski ST, Wagner AP, Taper ML (2006) ML-RELATE: a computer program for maximum likelihood estimation of relatedness and relationship. Mol Ecol Notes 6:576–579CrossRefGoogle Scholar
  36. Kalinowski ST, Taper ML, Marshall TC (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol Ecol 16:1099–1106CrossRefPubMedGoogle Scholar
  37. Kamp J, Urazaliev R, Donald PF, Hölzel N (2011) Post-Soviet agricultural change predicts future declines after recent recovery in Eurasian steppe bird populations. Biol Conserv 144:2607–2614CrossRefGoogle Scholar
  38. Kamvar ZN, Tabima JF, Grünwald NJ (2014) Poppr: an R package for genetic analysis of populations with clonal, partially clonal, and/or sexual reproduction. PeerJ 2:e281CrossRefPubMedPubMedCentralGoogle Scholar
  39. Kvist L, Ponnikas S, Belda EJ et al (2011) Endangered subspecies of the reed bunting (Emberiza schoeniclus witherbyi and E. s. lusitanica) in Iberian Peninsula have different genetic structures. J Ornithol 152:681–693CrossRefGoogle Scholar
  40. Menz MHM, Arlettaz R (2011) The precipitous decline of the ortolan bunting Emberiza hortulana: time to build on scientific evidence to inform conservation management. Oryx 46:122–129CrossRefGoogle Scholar
  41. Menz MHM, Mosimann-Kampe P, Arlettaz R (2009) Foraging habitat selection in the last ortolan bunting Emberiza hortulana population in Switzerland: final lessons before extinction. Ardea 97:323–333CrossRefGoogle Scholar
  42. Mettler R, Martin Schaefer H, Chernetsov N et al (2013) Contrasting patterns of genetic differentiation among blackcaps (Sylvia atricapilla) with divergent migratory orientations in Europe. PLoS ONE 8:1–12CrossRefGoogle Scholar
  43. Mimura M, Yahara T, Faith DP et al (2017) Understanding and monitoring the consequences of human impacts on intraspecific variation. Evol Appl 10:121–139CrossRefPubMedGoogle Scholar
  44. Moussy C, Hosken DJ, Mathews F et al (2013) Migration and dispersal patterns of bats and their influence on genetic structure. Mamm Rev 43:183–195CrossRefGoogle Scholar
  45. Norris K (2008) Agriculture and biodiversity conservation: opportunity knocks. Conserv Lett 1:2–11CrossRefGoogle Scholar
  46. Pan-European Common Bird Monitoring Scheme (2016) Species population trends. http://www.ebcc.info/index.php?ID=612. Accessed Sept 2016
  47. Paradis E (2010) Pegas: an R package for population genetics with an integrated-modular approach. Bioinformatics 26:419–420CrossRefPubMedGoogle Scholar
  48. Paradis E, Baillie SR, Sutherland WJ, Gregory RD (1998) Patterns of natal and breeding dispersal in birds. J Anim Ecol 67:518–536CrossRefGoogle Scholar
  49. Piry S, Alapetite A, Cornuet JM et al (2004) GENECLASS2: a software for genetic assignment and first-generation migrant detection. J Hered 95:536–539CrossRefPubMedGoogle Scholar
  50. Potts SG, Biesmeijer JC, Kremen C et al (2010) Global pollinator declines: trends, impacts and drivers. Trends Ecol Evol 25:345–353CrossRefPubMedGoogle Scholar
  51. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedPubMedCentralGoogle Scholar
  52. Prochazka P, Stokke BG, Jensen H et al (2011) Low genetic differentiation among reed warbler Acrocephalus scirpaceus populations across Europe. J Avian Biol 42:103–113CrossRefGoogle Scholar
  53. R Core Team (2016). R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna http://www.R-project.org/
  54. Rambaut A, Drummond A (2009) Tracer v1.5. http://beast.bio.ed.ac.uk/Tracer. Accessed Sept 2016
  55. Ramos R, Song G, Navarro J et al (2016) Population genetic structure and long-distance dispersal of a recently expanding migratory bird. Mol Phylogenet Evol 99:194–203CrossRefPubMedGoogle Scholar
  56. Rannala B, Mountain JL (1997) Detecting immigration by using multilocus genotypes. Proc Natl Acad Sci USA 94:9197–9201CrossRefPubMedPubMedCentralGoogle Scholar
  57. Reidsma P, Tekelenburg T, Van Den Berg M, Alkemade R (2006) Impacts of land-use change on biodiversity: an assessment of agricultural biodiversity in the European Union. Agric Ecosyst Environ 114:86–102CrossRefGoogle Scholar
  58. Rice W (1989) Analyzing tables of statistical tests. Evolution 43:223–225CrossRefPubMedGoogle Scholar
  59. Rolshausen G, Segelbacher G, Hobson KA, Schaefer HM (2009) Contemporary evolution of reproductive isolation and phenotypic divergence in sympatry along a migratory divide. Curr Biol 19:2097–2101CrossRefPubMedGoogle Scholar
  60. Rousset F (1997) Genetic differentiation and estimation of gene flow from F-statistics under isolation by distance. Genetics 145:1219–1228PubMedPubMedCentralGoogle Scholar
  61. Rousset F (2008) genepop’007: a complete re-implementation of the genepop software for Windows and Linux. Mol Ecol Resour 8:103–106CrossRefPubMedGoogle Scholar
  62. Sarrazin F, Lecomte J (2016) Evolution in the anthropocene. Science 351:922–924CrossRefPubMedGoogle Scholar
  63. Schindler DE, Armstrong JB, Reed TE (2015) The portfolio concept in ecology and evolution. Front Ecol Environ 13:257–263CrossRefGoogle Scholar
  64. Selstam G, Sondell JAN, Olsson P (2015) Wintering area and migration routes for ortolan buntings Emberiza hortulana from Sweden determined with light-geologgers. Ornis Svecica 25:3–15Google Scholar
  65. Thomas CD, Cameron A, Green RE et al (2004) Extinction risk from climate change. Nature 427:145–148CrossRefPubMedGoogle Scholar
  66. Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) Micro-Checker: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes 4:535–538CrossRefGoogle Scholar
  67. Vepsäläinen V, Pakkala T, Piha M, Tiainen J (2005) Population crash of the ortolan bunting Emberiza hortulana in agricultural landscapes of southern Finland. Ann Zool Fennici 42:91–107Google Scholar
  68. Vepsäläinen V, Pakkala T, Piha M, Tiainen J (2007) The importance of breeding groups for territory occupancy in a declining population of a farmland passerine bird. Ann Zool Fennici 44:8–19Google Scholar
  69. Wan Q-H, Wu H, Fujihara T, Fang S-G (2004) Which genetic marker for which conservation genetics issue? Electrophoresis 25:2165–2176CrossRefPubMedGoogle Scholar
  70. Wang C, Schroeder KB, Rosenberg NA (2012) A Maximum-likelihood method to correct for allelic dropout in microsatellite data with no replicate genotypes. Genetics 192:651–669CrossRefPubMedPubMedCentralGoogle Scholar
  71. Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population-structure. Evolution 38:1358–1370PubMedGoogle Scholar
  72. Wilson G, Rannala B (2003) Bayesian inference of recent migration rates using multilocus genotypes. Genetics 163:1177–1191PubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  • Caroline Moussy
    • 1
  • Raphaël Arlettaz
    • 2
    • 3
  • José Luis Copete
    • 4
  • Svein Dale
    • 5
  • Valery Dombrovski
    • 6
  • Jaanus Elts
    • 7
    • 8
  • Romain Lorrillière
    • 1
  • Riho Marja
    • 9
  • Eric Pasquet
    • 10
  • Markus Piha
    • 11
  • Tuomas Seimola
    • 12
  • Gunnar Selstam
    • 13
  • Frédéric Jiguet
    • 1
  1. 1.Centre d’Ecologie et des Sciences de la ConservationUMR7204 MNHN - CNRS - Sorbonne UniversitéParisFrance
  2. 2.Division of Conservation Biology, Institute of Ecology and EvolutionUniversity of BernBernSwitzerland
  3. 3.Valais Field StationSwiss Ornithological InstituteSionSwitzerland
  4. 4.Handbook of the Birds of the World AliveBarcelonaSpain
  5. 5.Faculty of Environmental Sciences and Natural Resource ManagementNorwegian University of Life SciencesÅsNorway
  6. 6.Institute of ZoologyNational Academy of SciencesMinskBelarus
  7. 7.Estonian Ornithological SocietyTartuEstonia
  8. 8.Department of Zoology, Institute of Ecology and Earth SciencesUniversity of TartuTartuEstonia
  9. 9.Estonian Environment AgencyTartuEstonia
  10. 10.UMR7205 ISYEB MNHN-CNRSParisFrance
  11. 11.Finnish Museum of Natural History – LUOMUSUniversity of HelsinkiFinland
  12. 12.Natural Resources Institute Finland – LUKEHelsinkiFinland
  13. 13.Department of Agricultural Research in Northern Sweden, Swedish University of Agricultural Sciences and Dept of Molecular BiologyUniversity of UmeåUmeåSweden

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