Population genetics of the Plumbeous Sierra-finch (Geospizopsis unicolor) across the Ecuadorian paramos: uncovering the footprints of the last ice age

  • Elisa BonaccorsoEmail author
  • Carlos Rodríguez-Saltos
  • Almudena Vélez-Márquez
  • Jesús Muñoz
Original Article


We explored how climate change during the last ~ 21,000 years may have affected the distribution and demography of the Plumbeous Sierra-finch (Geospizopsis unicolor) across the Ecuadorian paramos. Also, given the current island-like configuration of this ecosystem, we attempted to identify areas that may hold genetically isolated populations, as well as the potential geographic-ecological barriers causing such isolation. To this end, we used paleoclimatic modeling and a series of population genetic analyses based on two mitochondrial markers. Our models show an expansion of the potential distribution of the species during the Last Glacial Maximum (LGM) compared to the current potential distribution, and the genetic data show signals of population expansion loosely around the LGM. Our results depict a picture of relatively low genetic structure of the Plumbeous Sierra-finch along the paramos of Ecuador, but there is evidence of potential isolation of populations in the paramos of Galeras-Chiles (northern Ecuador).


Pleistocene Last Glacial Maximum Ecuador Andes High Andean birds Genetic isolation 


Die Populationsgenetik des Bleiämmerlings Geospizopsis unicolor in den Paramoregionen Ecuadors: Fußspuren der letzten Eiszeit.

Wir untersuchten, auf welche Weise klimatische Veränderungen während der letzten ~ 21,000 Jahre Verbreitung und demografische Struktur des Bleiämmerlings Geospizopsis unicolor in den Paramoregionen Ecuadors beeinflusst haben könnten. In Anbetracht der aktuellen inselartigen Verteilung dieses Ökosystems versuchten wir außerdem, sowohl Regionen ausfindig zu machen, welche gegenwärtig isolierte Populationen beherbergen, als auch potenzielle geografisch-ökologische Barrieren zu identifizieren, welche eine solche Isolation verursacht haben könnten. Dazu setzten wir paläoklimatische Modelle und eine Reihe populationsgenetischer Analysen auf der Grundlage zweier mitochondrialer Marker ein. Unsere Modelle zeigen eine Ausdehnung der potenziellen Verbreitung der Art während des Letzteiszeitlichen Maximums (engl.: Last Glacial Maximum, LGM) im Vergleich zur derzeitigen potenziellen Verbreitung, und die genetischen Daten liefern Signale einer Populationsausdehnung im Bereich des LGM. Außerdem zeichnen unsere Ergebnisse das Abbild einer relativ geringen genetischen Strukturierung beim Bleiämmerling in den Paramoregionen Ecuadors, es gibt allerdings Hinweise auf die potenzielle Isolation der Populationen in den Paramos von Galeras-Chiles (Nordecuador) von denen anderer Paramoregionen.



We are grateful to D. Bahamonde, H. F. Cadena, J. Castillo, M. Ninazunta, A. Charpentier, C. Rodríguez, G. Nazati, M. Santacruz, J. Sindram, J. Nilsson, P. Sornoza, and J. Freile for their assistance with fieldwork/collecting. M. E. Ordóñez, C. Barnes, M. G. Nichols, D. Flores, and G. Gavilanes performed laboratory work. F. Cuesta provided the file of paramo units. This study was funded by the Secretaría Nacional de Ciencia y Tecnología, SENACYT (PIC-08-470), Universidad Tecnológica Indoamérica, and Universidad San Francisco de Quito (Collaboration Grants and Fondos COCIBA, HUBI ID 5447). Permits for sample collection and genetic analyses were issued by the Ministerio del Ambiente, Ecuador (008-09 ICFAU-DNB/MA; 001-12 IC-FAU-FLO-DPAC/MA; 001-10 IC-FAU-DNB/MA; Contrato de Acceso a Recursos Genéticos MAE-DNBCM-2015-0017). Bob Zink made invaluable comments on a previous version of this manuscript. Ignacio Moore provided key information on Zonotrichia capensis reproduction.

Supplementary material

10336_2019_1700_MOESM1_ESM.docx (25 kb)
Supplementary material 1 (DOCX 26 kb)


  1. Arévalo E, Davis SK, Sites JW (1994) Mitochondrial DNA sequence divergence and phylogenetic relationships among eight chromosome races of the Sceloporus grammicus complex (Phrynosomatidae) in Central Mexico. Syst Biol 43:387–418CrossRefGoogle Scholar
  2. Bates JM (2002) The genetic effects of forest fragmentation on five species of Amazonian birds. J Avian Biol 33:276–294CrossRefGoogle Scholar
  3. Beltrán K, Salgado S, Cuesta F, León-Yánez S, Romoleroux K, Ortiz E, Cárdenas A, Velástegui A (2009) Distribución espacial, sistemas ecológicos y caracterización florística de los páramos en el Ecuador. Ecociencia, Proyecto Páramo Andino y Herbario QCA, QuitoGoogle Scholar
  4. Cárdenas ML, Gosling WD, Pennington RT, Poole I, Sherlock SC, Mothes P (2014) Forest of the tropical eastern Andean flank during the middle Pleistocene. Palaeogeogr Palaeoclimatol Palaeoecol 393:76–89CrossRefGoogle Scholar
  5. Clement M, Posada D, Crandall KA (2000) TCS: a computer program to estimate gene genealogies. Mol Ecol 2000:1657–1659CrossRefGoogle Scholar
  6. Colinvaux PA, Bush MB, Steinitz-Kannan M, Miller MC (1997) Glacial and postglacial pollen records from the Ecuadorian Andes and Amazon. Quat Res 48:69–78CrossRefGoogle Scholar
  7. Cuesta F, Salgado S, De Bièvre B, Beltrán K (2011) Unidades fisiográficas de los Páramos Andinos. CONDESAN-Proyecto Páramo Andino. Mecanismo de Información de Páramos
  8. Ehlers J, Gibbard PL, Hughes PD (eds) (2011) Developments in quaternary sciences: quaternary glaciations-extent and chronology: a closer look, vol 15. Elsevier, New York, pp 773–802Google Scholar
  9. Elith J, Kearney M, Phillips S (2010) The art of modelling range-shifting species. Methods Ecol Evol 1:330–342CrossRefGoogle Scholar
  10. Ersts PJ (2019) Geographic Distance Matrix Generator (version 1.2.3). American Museum of Natural History, Center for Biodiversity and Conservation. Accessed 20 June 2019
  11. Excoffier L, Lischer HEL (2010) Arlequin suite version 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour 10:564–567CrossRefGoogle Scholar
  12. Fjeldså J, Krabbe N (1990) Birds of the High Andes. Zoological Museum, University of Copenhagen, DenmarkGoogle Scholar
  13. Gosling WD, Bush MB, Hanselman JA, Chepstow-Lusty A (2008) Glacial-interglacial changes in moisture balance and the impact on vegetation in the southern hemisphere Tropical Andes (Bolivia/Peru). Palaeogeogr Palaeoclimatol Palaeoecol 259:35–50CrossRefGoogle Scholar
  14. Grant WS (2015) Problems and cautions with sequence mismatch analysis and Bayesian skyline plots to infer historical demography. J Hered 106:333–346CrossRefGoogle Scholar
  15. Guayasamin JM, Bonaccorso E, Duellman WE, Coloma LA (2010) Genetic differentiation in the nearly extinct Harlequin Frogs (Bufonidae: Atelopus), with emphasis on the Andean Atelopus ignescens and A. bomolochos species complexes. Zootaxa 2574:55–68CrossRefGoogle Scholar
  16. Harpending RC (1994) Signature of ancient population growth in a low-resolution mitochondrial DNA mismatch distribution. Hum Biol 66:591–600Google Scholar
  17. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978CrossRefGoogle Scholar
  18. Hooghiemstra H, Ran ETH (1994) Late Pliocene-Pleistocene high resolution pollen sequence of Colombia: an overview of climatic change. Quat Int 21:63–80CrossRefGoogle Scholar
  19. Hooghiemstra H, van der Hammen T (2004) Quaternary Ice-Age dynamics in the Colombian Andes: developing and understanding of our legacy. Philos Trans R Soc Lond B 359:173–181CrossRefGoogle Scholar
  20. Jaramillo A (2019) Plumbeous Sierra-finch (Geospizopsis unicolor). In: del Hoyo J, Elliott A, Sargatal J, Christie DA, de Juana E (eds) Handbook of the birds of the world alive. Lynx, Barcelona. Accessed 6 July 2017
  21. Kearse M, Moir R, Wilson A, Stone-Havas S, Cheung M, Sturrock S, Buxton S, Cooper A, Markowitz S, Duran C, Thierer T, Ashton B, Mentjies P, Drummond A (2012) Geneious basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28:1647–1649CrossRefGoogle Scholar
  22. Krabbe N (2008) Arid valleys as dispersal barriers to High Andean forest birds in Ecuador. Cotinga 29:28–30Google Scholar
  23. La Frenierre J, Huh KI, Mark BG (2011) Chapter 56: Ecuador, Peru and Bolivia. In: Ehlers J, Gibbard PL, Hughes PD (eds) Developments in quaternary sciences: quaternary glaciations-extent and chronology: a closer look, vol 15. Elsevier, New York, pp 773–802CrossRefGoogle Scholar
  24. La Sorte FA, Jetz W (2010) Projected range contractions of montane biodiversity under global warming. Proc R Soc B Biol 277:3401–3410CrossRefGoogle Scholar
  25. Lerner HRL, Meyer M, James HF, Hofreiter M, Fleischer RC (2011) Multilocus resolution of phylogeny and timescale in the extant adaptive radiation of Hawaiian honeycreepers. Curr Biol 21:1838–1844CrossRefGoogle Scholar
  26. Librado P, Rozas J (2009) DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25:1451–1452CrossRefGoogle Scholar
  27. Moret P (2009) Altitudinal distribution, diversity and endemicity of Carabidae (Coleoptera) in the páramos of Ecuadorian Andes. Ann Soc Entomol Fr 45:500–510CrossRefGoogle Scholar
  28. Neigel JE, Avise JC (1993) Application of a random walk model to geographic distributions of animal mitochondrial DNA variation. Genetics 135:1209–51220Google Scholar
  29. Parmesan C, Yohe G (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature 421:37–42CrossRefGoogle Scholar
  30. Peterson AT (2011) Ecological niche conservatism: a time-structured review of evidence. J Biogeogr 38:817–827CrossRefGoogle Scholar
  31. Peterson AT, Soberón J, Sánchez-Cordero V (1999) Conservatism of ecological niches in evolutionary time. Science 285:1265–1267CrossRefGoogle Scholar
  32. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190:231–259CrossRefGoogle Scholar
  33. Prugnolle F, de Meeus T (2002) Inferring sex-biased dispersal from population genetic tools: a review. Heredity 88:161–165CrossRefGoogle Scholar
  34. Ramos-Onsins SE, Rozas J (2002) Statistical properties of new neutrality tests against population growth. Mol Biol Evol 19:2092–2100CrossRefGoogle Scholar
  35. Ridgely RS, Greenfield PJ (2001) The Birds of Ecuador. I. Status, distribution, and taxonomy. Cornell University Press, IthacaGoogle Scholar
  36. Rogers AR, Harpending H (1992) Population growth makes waves in the distribution of pairwise genetic differences. Mol Biol Evol 9:552–569Google Scholar
  37. Schneider S, Excoffier L (1999) Estimation of past demographic parameters from the distribution of pairwise differences when the mutation rates vary among sites: application to human mitochondrial DNA. Genetics 152:1079–1089Google Scholar
  38. Sierra R, Cerón C, Palacios W, Valencia R (1999) Propuesta preliminar de un sistema de clasificación de vegetación para el Ecuador continental. Proyecto INEFAN/GEF-BIRF y EcoCiencia, QuitoGoogle Scholar
  39. Sorenson MD, Ast JC, Dimcheff DE, Yuri T, Mindell DP (1999) Primers for a PCR-based approach to mitochondrial genome sequencing in birds and other vertebrates. Mol Phylogenet Evol 12:105–114CrossRefGoogle Scholar
  40. Urrego DH, Hooghiemstra H, Rama-Corredor O, Martrat B, Grimalt JO, Thompson L, Contributors Data (2015) Rapid millennial-scale vegetation changes in the Tropical Andes. Clim Past Discuss 11:1701–1739CrossRefGoogle Scholar
  41. Warren DL, Seifert SN (2011) Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecol Appl 21:335–342CrossRefGoogle Scholar
  42. Zink RM (1994) The geography of mitochondrial DNA variation, population structure, hybridization, and species limits in the Fox Sparrow (Passerella iliaca). Evolution 48:96–111Google Scholar

Copyright information

© Deutsche Ornithologen-Gesellschaft e.V. 2019

Authors and Affiliations

  1. 1.Laboratorio de Biología Evolutiva, Instituto BIOSFERA, and Colegio de Ciencias Biológicas y AmbientalesUniversidad San Francisco de QuitoQuitoEcuador
  2. 2.Centro de Investigación de la Biodiversidad y Cambio ClimáticoUniversidad Tecnológica IndoaméricaQuitoEcuador
  3. 3.Pontificia Universidad Católica del EcuadorQuitoEcuador
  4. 4.Master Oficial en Biodiversidad en Áreas Tropicales y su ConservaciónUniversidad Internacional Menéndez Pelayo-CSICMadridSpain
  5. 5.Real Jardín Botánico (RJB-CSIC)MadridSpain

Personalised recommendations