Journal of Ornithology

, Volume 159, Issue 2, pp 355–366 | Cite as

Weak evidence for fine-scale genetic spatial structure in three sedentary Amazonian understorey birds

  • Juliana Menger
  • Jasmin Unrein
  • Maria Woitow
  • Martin Schlegel
  • Klaus Henle
  • William E. Magnusson
Original Article

Abstract

The ecological characteristics of a species, along with small-scale landscape features are known to affect the patterns of genetic structure within populations. Due to dispersal limitation, closely-related individuals tend to be closer spatially, leading to spatial genetic structure. Physical barriers also may prevent individuals from dispersing further, and lead individuals on one side of a barrier to be more related than individuals from different sides. We tested these hypotheses by examining patterns of fine-scale spatial genetic structure within populations of three relatively sedentary Amazonian-forest understorey birds that differ in their ecological requirements. We sampled birds in a 10,000 ha reserve, covered by largely undisturbed old-growth forests and traversed by a central ridge. We found positive spatial genetic structure at short distances only for Percnostola rufifrons, a treefall-gap specialist. Positive genetic structure occurred at 6 km for Glyphorynchus spirurus, a solitary bark-forager; no spatial genetic structure was found for Gymnopithys rufigula, an army-ant follower. Individuals of none of the three species were more related on a given side of the ridgeline than between different sides but, at greater distances, there was a tendency of individuals located on opposite sides of the ridgeline to be less related than individuals located on the same side, for all species analysed. Our study indicates that local topographic features do not prevent, but likely reduce, gene flow within populations in continuous forests, and that the development of fine-scale spatial genetic structure may depend on the dispersal propensity of a species. Thus, studies of species assemblages need to account for the different ecological characteristics of the constituent species.

Keywords

Gymnopithys rufigula Glyphorynchus spirurus Microsatellites Neotropical birds Percnostola rufifrons Spatial genetic structure 

Zusammenfassung

Schwache Hinweise auf eine räumlich-genetische Feinstruktur bei drei sesshaften Vögeln aus dem Unterholz des Amazonas Waldes Die ökologischen Eigenschaften einer Art beeinflussen zusammen mit kleinmaßstäbigen Landschaftsmerkmalen die Form der genetischen Struktur innerhalb von Populationen. Aufgrund einer begrenzten Ausbreitung befinden sich nahverwandte Individuen in räumlicher Nähe zueinander, was zu einer räumlich-genetischen Struktur führt. Physikalische Barrieren können ebenfalls die Individuen an einer weiteren Ausbreitung hindern. Das führt dazu, dass Individuen auf der einen Seite der Barriere näher miteinander verwandt sind als Individuen von unterschiedlichen Seiten. Wir haben diese Hypothesen durch die Untersuchung der räumlich-genetischen Feinstruktur innerhalb der Populationen von drei relativ sesshaften Vogelarten, die im Unterholz des Amazonas Regenwaldes leben und sich in ihren ökologischen Anforderungen unterscheiden, getestet. Die Proben wurden in einem 10.000 ha großen Reservat gesammelt, welches größtenteils mit unberührtem Primärwald bedeckt und von einer zentral liegenden Kammlinie durchzogen ist. Nur für Percnostola rufifrons haben wir eine positive räumlich-genetische Struktur auf kurzen Distanzen gefunden. Dieser ist ein Spezialist für kleine Lichtungen, sogenannte „treefall-gaps“. Eine positive räumlich-genetische Struktur wurde für den solitär lebenden Glyphorynchus spirurus bei einer Distanz von 6 km festgestellt, welcher nach Insekten in der Rinde von Bäumen sucht. Für den Wanderameisen folgenden Gymnopithys rufigula wurde keine räumlich-genetische Struktur gefunden. Hinzu kommt, dass bei allen Arten die Individuen auf einer Seite der Kammlinie nicht näher verwandt waren als Individuen von unterschiedlichen Seiten. Auf größere Distanzen gesehen, konnte für alle drei Vogelarten eine Tendenz festgestellt werden, dass Individuen von unterschiedlichen Seiten der Kammlinie weniger miteinander verwandt waren als Individuen einer Seite. Unsere Studie zeigt, dass lokale topografische Gegebenheiten nicht den Genfluss in Populationen in zusammenhängenden Wäldern verhindern, aber möglicherweise reduzieren und dass die Entstehung einer räumlich-genetischen Feinstruktur vermutlich von der Ausbreitungsneigung der Art abhängt. Folglich müssen bei Untersuchungen zu Artenzusammensetzungen die verschiedenen ökologischen Besonderheiten der einzelnen Spezies berücksichtigten.

Notes

Acknowledgements

The Brazilian Science Funding Agency CAPES awarded a stipend to JM (Process 12401-12-9). The Brazilian Program for Biodiversity Research PPBio (Grant 457544/2012-0), the National Institute for Amazonian Biodiversity INCT-CENBAM (Grant 573721/2008-4) and the Brazilian Long-Term Ecological Research Project PELD (Grant 403764/2012-2) through the Brazilian National Research Council CNPq supported this study. Fieldwork infrastructure, guidance and technical support was provided by INPA, PPBio, PELD and the program Large-Scale Biosphere–Atmosphere Experiment in Amazonia (LBA). The German Centre for Integrative Biodiversity Research-iDiv provided additional support for consumables.

Compliance with ethical standards

Ethical approval

All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. All activities involving birds were conducted under approval of the Brazilian Centre for Bird Conservation-CEMAVE (Permit 3576) and the Brazilian Biodiversity Authorization and Information System-SISBIO (Permit 34850). All necessary steps to minimize animal suffering during handling were taken and birds were never kept in captivity or injured by any means. None of the three studied species is globally threatened (BirdLifeInternational 2016).

References

  1. Alcaide M, Serrano D, Tella JL, Negro JJ (2009) Strong philopatry derived from capture–recapture records does not lead to fine-scale genetic differentiation in lesser kestrels. J Anim Ecol 78:468–475. doi: 10.1111/j.1365-2656.2008.01493.x CrossRefPubMedGoogle Scholar
  2. Antongiovanni M, Metzger JP (2005) Influence of matrix habitats on the occurrence of insectivorous bird species in Amazonian forest fragments. Biol Conserv 122:441–451. doi: 10.1016/j.biocon.2004.09.005 CrossRefGoogle Scholar
  3. Banks SC, Peakall ROD (2012) Genetic spatial autocorrelation can readily detect sex-biased dispersal. Mol Ecol 21:2092–2105. doi: 10.1111/j.1365-294X.2012.05485.x CrossRefPubMedGoogle Scholar
  4. Barnett JR, Woltmann S, Stenzler L, Bogdanowicz SM, Lovette IJ (2007) Isolation and characterization of microsatellite markers from the chestnut-backed antbird, Myrmeciza exsul. Mol Ecol Notes 7:1070–1072. doi: 10.1111/j.1471-8286.2007.01780.x CrossRefGoogle Scholar
  5. Barnett JR, Ruiz-Gutierrez V, Coulon A, Lovette IJ (2008) Weak genetic structuring indicates ongoing gene flow across White-ruffed Manakin (Corapipo altera) populations in a highly fragmented Costa Rica landscape. Conserv Genet 9:1403–1412. doi: 10.1007/s10592-007-9463-3 CrossRefGoogle Scholar
  6. Bates JM (2002) The genetic effects of forest fragmentation on five species of Amazonian birds. J Avian Biol 33:276–294. doi: 10.1034/j.1600-048X.2002.330310.x CrossRefGoogle Scholar
  7. BirdLifeInternational (2016) IUCN Red List for birds. http://www.birdlife.org on 05/12/2016
  8. Blake JG, Loiselle BA (2012) Temporal and spatial patterns in abundance of the Wedge-billed Woodcreeper (Glyphorynchus spirurus) in lowland Ecuador. Wilson J Ornithol 124:436–445CrossRefGoogle Scholar
  9. Brown LM, Ramey RR, Tamburini B, Gavin TA (2004) Population structure and mitochondrial DNA variation in sedentary Neotropical birds isolated by forest fragmentation. Conserv Genet 5:743–757. doi: 10.1007/s10592-004-1865-x CrossRefGoogle Scholar
  10. Brumfield RT, Tello JG, Cheviron ZA, Carling MD, Crochet N, Rosenberg KV (2007) Phylogenetic conservatism and antiquity of a tropical specialization: Army-ant-following in the typical antbirds (Thamnophilidae). Mol Phylogenet Evol 45:1–13. doi: 10.1016/j.ympev.2007.07.019 CrossRefPubMedGoogle Scholar
  11. Burney CW, Brumfield RT (2009) Ecology predicts levels of genetic differentiation in Neotropical birds. Am Nat 174:358–368. doi: 10.1086/603613 CrossRefPubMedGoogle Scholar
  12. Chaves-Campos J, DeWoody JA (2008) The spatial distribution of avian relatives: do obligate army-ant-following birds roost and feed near family members? Mol Ecol 17:2963–2974. doi: 10.1111/j.1365-294X.2008.03811.x CrossRefPubMedGoogle Scholar
  13. Crochet PA (2000) Genetic structure of avian populations—allozymes revisited. Mol Ecol 9:1463–1469. doi: 10.1046/j.1365-294x.2000.01026.x CrossRefPubMedGoogle Scholar
  14. Dawson DA et al (2010) New methods to identify conserved microsatellite loci and develop primer sets of high cross-species utility—as demonstrated for birds. Mol Ecol Resour 10:475–494. doi: 10.1111/j.1755-0998.2009.02775.x CrossRefPubMedGoogle Scholar
  15. Dawson D et al (2013) High-utility conserved avian microsatellite markers enable parentage and population studies across a wide range of species. BMC Genomics 14:176. doi: 10.1186/1471-2164-14-176 CrossRefPubMedPubMedCentralGoogle Scholar
  16. Double MC, Peakall R, Beck NR, Cockburn A (2005) Dispersal, philopatry, and infidelity: Dissecting local genetic structure in superb fairy-wrens (Malurus cyaneus). Evolution 59:625–635PubMedGoogle Scholar
  17. Earl DA, vonHoldt BM (2011) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4:359–361. doi: 10.1007/s12686-011-9548-7 CrossRefGoogle Scholar
  18. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol 14:2611–2620. doi: 10.1111/j.1365-294X.2005.02553.x CrossRefPubMedGoogle Scholar
  19. Fernandes AM (2013) Fine-scale endemism of Amazonian birds in a threatened landscape. Biodivers Conserv 22:2683–2694. doi: 10.1007/s10531-013-0546-9 CrossRefGoogle Scholar
  20. Fernandes AM, Gonzalez J, Wink M, Aleixo A (2013) Multilocus phylogeography of the Wedge-billed Woodcreeper Glyphorynchus spirurus (Aves, Furnariidae) in lowland Amazonia: widespread cryptic diversity and paraphyly reveal a complex diversification pattern. Mol Phylogenet Evol 66:270–282. doi: 10.1016/j.ympev.2012.09.033 CrossRefPubMedGoogle Scholar
  21. Fletcher RJ Jr, Robertson EP, Wilcox RC, Reichert BE, Austin JD, Kitchens WM (2015) Affinity for natal environments by dispersers impacts reproduction and explains geographical structure of a highly mobile bird. Proc R Soc B Biol Sci. doi: 10.1098/rspb.2015.1545 Google Scholar
  22. Greenwood PJ (1980) Mating systems, philopatry and dispersal in birds and mammals. Anim Behav 28:1140–1162. doi: 10.1016/S0003-3472(80)80103-5 CrossRefGoogle Scholar
  23. Greenwood PJ, Harvey PH (1982) The natal and breeding dispersal of birds. Annu Rev Ecol Syst 13:1–21. doi: 10.1146/annurev.es.13.110182.000245 CrossRefGoogle Scholar
  24. Gutiérrez-Pinto N, Cuervo AM, Miranda J, Pérez-Emán JL, Brumfield RT, Cadena CD (2012) Non-monophyly and deep genetic differentiation across low-elevation barriers in a Neotropical montane bird (Basileuterus tristriatus; Aves: Parulidae). Mol Phylogenet Evol 64:156–165. doi: 10.1016/j.ympev.2012.03.011 CrossRefPubMedGoogle Scholar
  25. Hardy OJ, Vekemans X (2002) Spagedi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Mol Ecol Notes 2:618–620. doi: 10.1046/j.1471-8286.2002.00305.x CrossRefGoogle Scholar
  26. Hermes C, Döpper A, Schaefer HM, Segelbacher G (2016) Effects of forest fragmentation on the morphological and genetic structure of a dispersal-limited, endangered bird species. Nat Conserv 16:39–58. doi: 10.3897/natureconservation.16.10905
  27. Heywood JS (1991) Spatial analysis of genetic variation in plant populations. Annu Rev Ecol Syst 22:335–355. doi: 10.1146/annurev.es.22.110191.002003 CrossRefGoogle Scholar
  28. Husemann M, Cousseau L, Callens T, Matthysen E, Vangestel C, Hallmann C, Lens L (2015) Post-fragmentation population structure in a cooperative breeding Afrotropical cloud forest bird: emergence of a source-sink population network. Mol Ecol 24:1172–1187. doi: 10.1111/mec.13105 CrossRefPubMedGoogle Scholar
  29. Isler ML, Alonso JA, Isler PR, Whitney BM (2001) A new species of Percnostola antbirds (Passeriformes: Thamnophilidae) from Amazonian Peru, and an analysis of species limits within Percnostola rufifrons. Wilson Bull 113:164–176. doi: 10.1676/0043-5643(2001) CrossRefGoogle Scholar
  30. Jakobsson M, Rosenberg NA (2007) CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23:1801–1806. doi: 10.1093/bioinformatics/btm233 CrossRefPubMedGoogle Scholar
  31. Johnson EI, Stouffer PC, Vargas CF (2011) Diversity, biomass, and trophic structure of a Central Amazonian Rainforest bird community. Braz J Ornithol 19:1–16Google Scholar
  32. Kalinowski ST, Taper ML, Marshall TC (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol Ecol 16:1099–1106. doi: 10.1111/j.1365-294X.2007.03089.x CrossRefPubMedGoogle Scholar
  33. Karr JR (1976) Seasonality, resource availability, and community diversity in tropical bird communities. Am Nat 110:973–994CrossRefGoogle Scholar
  34. Khimoun A et al (2016) Habitat specialization predicts genetic response to fragmentation in tropical birds. Mol Ecol 25:3831–3844. doi: 10.1111/mec.13733 CrossRefPubMedGoogle Scholar
  35. Koenig WD, Van Vuren D, Hooge PN (1996) Detectability, philopatry, and the distribution of dispersal distances in vertebrates. Trends Ecol Evol 11:514–517. doi: 10.1016/S0169-5347(96)20074-6 CrossRefPubMedGoogle Scholar
  36. Laurance SGW, Gomez MS (2005) Clearing width and movements of understory rainforest birds. Biotropica 37:149–152. doi: 10.1111/j.1744-7429.2005.04099.x CrossRefGoogle Scholar
  37. Laurance SGW, Stouffer PC, Laurance WF (2004) Effects of road clearings on movement patterns of understory rainforest birds in Central Amazonia. Conserv Biol 18:1099–1109. doi: 10.1111/j.1523-1739.2004.00268.x CrossRefGoogle Scholar
  38. Lynch M, Ritland K (1999) Estimation of pairwise relatedness with molecular markers. Genetics 152:1753–1766PubMedPubMedCentralGoogle Scholar
  39. Marantz CA, Aleixo A, Bevier LR, Patten MA (2003) Family Dendrocolaptidae (Woodcreepers). In: del Hoyo J, Elliott A, Sargatal J, Christie DA (eds) Handbook of the Birds of the World. Lynx Edicions Barcelona, pp 358–447Google Scholar
  40. Menger J, Gerth M, Unrein J, Henle K, Schlegel M (2017a) Isolation and characterization of polymorphic microsatellite loci from the Rufous-throated Antbird Gymnopithys rufigula (Aves: Thamnophilidae). Wilson J Ornithol 129:407–411CrossRefGoogle Scholar
  41. Menger J, Henle K, Magnusson WE, Soro A, Husemann M, Schlegel M (2017b) Genetic diversity and spatial structure of the Rufous-throated Antbird (Gymnopithys rufigula), an Amazonian obligate army-ant follower. Ecol Evol 7:2671–2684. doi: 10.1002/ece3.2880 CrossRefPubMedPubMedCentralGoogle Scholar
  42. Milá B, Wayne RK, Fitze P, Smith TB (2009) Divergence with gene flow and fine-scale phylogeographical structure in the wedge-billed woodcreeper, Glyphorynchus spirurus, a Neotropical rainforest bird. Mol Ecol 18:2979–2995. doi: 10.1111/j.1365-294X.2009.04251.x CrossRefPubMedGoogle Scholar
  43. Moore RP, Robinson WD, Lovette IJ, Robinson TR (2008) Experimental evidence for extreme dispersal limitation in tropical forest birds. Ecol Lett 11:960–968. doi: 10.1111/j.1461-0248.2008.01196.x CrossRefPubMedGoogle Scholar
  44. O’Donnell S, Logan CJ, Clayton NS (2012) Specializations of birds that attend army ant raids: an ecological approach to cognitive and behavioral studies. Behav Proc 91:267–274. doi: 10.1016/j.beproc.2012.09.007 CrossRefGoogle Scholar
  45. Peakall ROD, Smouse PE (2006) Genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol Ecol Notes 6:288–295. doi: 10.1111/j.1471-8286.2005.01155.x CrossRefGoogle Scholar
  46. Peakall R, Smouse PE (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update Bioinformatics 28:2537–2539. doi: 10.1093/bioinformatics/bts460 PubMedGoogle Scholar
  47. Peakall R, Ruibal M, Lindenmayer DB (2003) Spatial autocorrelation analysis offers new insights into gene flow in the Australian bush rat, Rattus fuscipes. Evolution 57:1182–1195. doi: 10.1111/j.0014-3820.2003.tb00327.x CrossRefPubMedGoogle Scholar
  48. Powell LL, Cordeiro NJ, Stratford JA (2015a) Ecology and conservation of avian insectivores of the rainforest understory: a pantropical perspective. Biol Conserv 188:1–10. doi: 10.1016/j.biocon.2015.03.025 CrossRefGoogle Scholar
  49. Powell LL, Wolfe JD, Johnson EI, Hines JE, Nichols JD, Stouffer PC (2015b) Heterogeneous movement of insectivorous Amazonian birds through primary and secondary forest: a case study using multistate models with radiotelemetry data. Biol Conserv 188:100–108. doi: 10.1016/j.biocon.2015.01.028 CrossRefGoogle Scholar
  50. Powell LL, Wolfe JD, Johnson EI, Stouffer PC (2016) Forest recovery in post-pasture Amazonia: testing a conceptual model of space use by insectivorous understory birds. Biol Cons 194:22–30. doi: 10.1016/j.biocon.2015.11.025 CrossRefGoogle Scholar
  51. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedPubMedCentralGoogle Scholar
  52. R Core Team (2016) R: A language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  53. Rambaut A, Suchard MA, Xie D, Drummond AJ (2014) Tracer v1.6. http://beast.bio.ed.ac.uk/Tracer
  54. Rousset F (2008) GENEPOP’007: a complete re-implementation of the genepop software for Windows and Linux. Mol Ecol Resour 8:103–106. doi: 10.1111/j.1471-8286.2007.01931.x CrossRefPubMedGoogle Scholar
  55. Sandoval HJ, Gómez JP, Cadena CD (2016) Is the largest river valley west of the Andes a driver of diversification in Neotropical lowland birds? Auk. doi: 10.1642/AUK-16-91.1 Google Scholar
  56. Şekercioḡlu ÇH, Ehrlich PR, Daily GC, Aygen D, Goehring D, Sandí RF (2002) Disappearance of insectivorous birds from tropical forest fragments. Proc Natl Acad Sci 99:263–267. doi: 10.1073/pnas.012616199 CrossRefPubMedPubMedCentralGoogle Scholar
  57. Seutin G, White BN, Boag PT (1991) Preservation of avian blood and tissue samples for DNA analyses. Can J Zool 69:82–90. doi: 10.1139/z91-013 CrossRefGoogle Scholar
  58. Smith BT et al (2014) The drivers of tropical speciation. Nature 515:406–409. doi: 10.1038/nature13687 CrossRefPubMedGoogle Scholar
  59. Smouse PE, Peakall R (1999) Spatial autocorrelation analysis of individual multiallele and multilocus genetic structure. Heredity 82:561–573. doi: 10.1038/sj.hdy.6885180 CrossRefPubMedGoogle Scholar
  60. Sokal RR, Wartenberg DE (1983) A test of spatial autocorrelation analysis using an isolation-by-distance model. Genetics 105:219–237PubMedPubMedCentralGoogle Scholar
  61. Stouffer PC, Bierregaard RO (1995) Use of Amazonian forest fragments by understory insectivorous birds. Ecology 76:2429–2445. doi: 10.2307/2265818 CrossRefGoogle Scholar
  62. Suh A, Kriegs JO, Brosius J, Schmitz J (2011) Retroposon insertions and the chronology of avian sex chromosome evolution. Mol Biol Evol. doi: 10.1093/molbev/msr147 PubMedGoogle Scholar
  63. Unrein J, Menger J, Weigert A, Henle K, Schlegel M (2017) Isolation and characterisation of novel polymorphic microsatellite markers for the Wedge-billed Woodcreeper Glyphorynchus spirurus. Avian Biol Res 10:24–26. doi: 10.3184/175815617X14799886573066 CrossRefGoogle Scholar
  64. Van Houtan KS, Pimm SL, Bierregaard ROJ, Lovejoy TE, Stouffer PC (2006) Local extinctions in flocking birds in Amazonian forest fragments. Evol Ecol Res 8:129–148Google Scholar
  65. Van Houtan KS, Pimm SL, Halley JM, Bierregaard RO, Lovejoy TE (2007) Dispersal of Amazonian birds in continuous and fragmented forest. Ecol Lett 10:219–229. doi: 10.1111/j.1461-0248.2007.01004.x CrossRefPubMedGoogle 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 4:535–538. doi: 10.1111/j.1471-8286.2004.00684.x CrossRefGoogle Scholar
  67. Vasudev D, Fletcher RJ Jr (2016) Mate choice interacts with movement limitations to influence effective dispersal. Ecol Model 327:65–73. doi: 10.1016/j.ecolmodel.2016.01.014 CrossRefGoogle Scholar
  68. Weir JT (2009) Implications of genetic differentiation in Neotropical montane forest birds. Ann Mo Bot Gard 96:410–433. doi: 10.3417/2008011 CrossRefGoogle Scholar
  69. Willis EO, Oniki Y (1978) Birds and army ants. Annu Rev Ecol Syst 9:243–263CrossRefGoogle Scholar
  70. Willson SK (2004) Obligate army-ant-following birds: a study of ecology, spatial movement patterns, and behavior in Amazonian Peru. Ornithol Monogr. doi: 10.2307/40166802 Google Scholar
  71. Wilson GA, Rannala B (2003) Bayesian inference of recent migration rates using multilocus genotypes. Genetics 163:1177–1191PubMedPubMedCentralGoogle Scholar
  72. Woltmann S, Kreiser BR, Sherry TW (2012) Fine-scale genetic population structure of an understory rainforest bird in Costa Rica. Conserv Genet 13:925–935. doi: 10.1007/s10592-012-0341-2 CrossRefGoogle Scholar
  73. Zimmer KJ, Isler ML (2003) Family Thamnophilidae (Typical antbirds). In: del Hoyo J, Elliot A, Christie DA (eds) Handbook of the birds of the world, vol 8. Broadbills to Tapaculos. Lynx Edicions, Barcelona, pp 448–681Google Scholar

Copyright information

© Dt. Ornithologen-Gesellschaft e.V. 2017

Authors and Affiliations

  1. 1.Department of Conservation BiologyUFZ-Helmholtz Centre for Environmental ResearchLeipzigGermany
  2. 2.Faculty of Biosciences, Pharmacy and PsychologyUniversity of LeipzigLeipzigGermany
  3. 3.German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-LeipzigLeipzigGermany
  4. 4.Coordenação de Pesquisa em Biodiversidade, Instituto Nacional de Pesquisas da Amazônia (INPA)ManausBrazil

Personalised recommendations