Advertisement

Demographic history and spatial genetic structure in a remnant population of the subtropical tree Anadenanthera colubrina var. cebil (Griseb.) Altschul (Fabaceae)

  • Alejandra L. Goncalves
  • María V. García
  • Myriam Heuertz
  • Santiago C. González-MartínezEmail author
Research Paper

Abstract

Key message

A remnant population of Anadenanthera colubrina var. cebil in Northern Argentina showed a mixed mating system, high genetic diversity, and moderate spatial genetic structure, which was stronger in saplings than in adults. Demographic history analyses revealed an ancient population expansion. Despite high genetic diversity, high inbreeding suggests caution in the use of this stand as seed source.

Context

Information on fine-scale spatial genetic structure (FSGS) and demographic history is essential to determine which mechanisms are responsible for population persistence and evolution. This is particularly important in fragmented biomes, such as the seasonally dry tropical forests.

Aims

To assess the level of genetic diversity and population genetic structure in a remnant population of A. colubrina var. cebil, and to evaluate the influence of historical and contemporary environmental change on the genetic constitution of this population.

Methods

Eight microsatellites were typed in 60 adults and 59 saplings. The existence of (non-spatial) genetic clusters was evaluated using STRUCTURE and PCAs. FSGS was evaluated by kinship analyses and sPCA. MCMCglmm models were used to provide insights into factors underlying FSGS. Demographic history was studied using bottleneck statistics and approximate Bayesian computation.

Results

We found high levels of genetic diversity and high inbreeding. Genetic structure was stronger in saplings than in adult trees, probably due to assortative mating, and was not explained by altitude or DBH. Demographic analyses suggested an ancient population expansion.

Conclusion

Patterns of inbreeding and relatedness suggest a mixed mating system. High genetic diversity and moderate genetic structure suggest long-term population viability. High inbreeding suggests caution when using this stand as a source of material for reforestation.

Keywords

Paranaense biogeographic province Fine-scale spatial genetic structure Demographic modelling Genetic diversity Inbreeding Microsatellites 

Notes

Acknowledgements

We thank Entidad Binacional Yacyretá for granting access to Campo San Juan Nature Reserve. Fieldwork benefited from the assistance of M.R. Kostlin. A.L. Goncalves wishes to thank to Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) for providing her doctoral fellowship. This study is part of the PhD thesis of A.L. Goncalves at the Universidad Nacional de La Plata.

Funding

Financial support was provided by PICTO UNaM 2011 N°0133 from “Agencia Nacional de Promoción Científica y Tecnológica” and “Universidad Nacional de Misiones” to M.V. García, and by PIP N° 112-2015001-00860CO from CONICET, to M.V. García. This work has also been supported by ANR’s “Investissement d’Avenir” grants (CEBA: ANR-10-LABX-25-01).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Aguilar R, Quesada M, Ashworth L, Herrerias-Diego YV, Lobo J (2008) Genetic consequences of habitat fragmentation in plant populations: susceptible signals in plant traits and methodological approaches. Mol Ecol 17(24):5177–5188PubMedCrossRefGoogle Scholar
  2. Aldrich PR, Hamrick JL, Chavarriaga P, Kochert G (1998) Microsatellite analysis of demographic genetic structure in fragmented populations of the tropical tree Symphonia globulifera. Mol Ecol 7(8):933–944PubMedCrossRefGoogle Scholar
  3. Anderson CD, Epperson BK, Fortin MJ, Holderegger R, James P, Rosenberg MS, Scribner KT, Spear S (2010) Considering spatial and temporal scale in landscape-genetic studies of gene flow. Mol Ecol 19(17):3565–3575PubMedCrossRefGoogle Scholar
  4. Araújo ED, Costa M, Chaud-Netto J, Fowler HG (2004) Body size and flight distance in stingless bees (Hymenoptera: Meliponini): inference of flight range and possible ecological implications. Braz J Biol 64(3B):563–568PubMedCrossRefGoogle Scholar
  5. Barrandeguy ME, Prinz K, García MV, Finkeldey R (2012) Development of microsatellite markers for Anadenanthera colubrina var. cebil (Fabaceae), a native tree from South America. Am J Bot 99(9):e372–e374PubMedCrossRefGoogle Scholar
  6. Barrandeguy ME, García MV, Prinz K, Pomar RR, Finkeldey R (2014) Genetic structure of disjunct Argentinean populations of the subtropical tree Anadenanthera colubrina var. cebil (Fabaceae). Plant Syst Evol 300(7):1693–1705CrossRefGoogle Scholar
  7. Barrett SCH, Arunkumar R, Wright SI (2014) The demography and population genomics of evolutionary transitions to self-fertilization in plants. Philos Trans R Soc Lond Ser B Biol Sci 369(1648):20130344CrossRefGoogle Scholar
  8. Bauni V, Homberg M (2015) Reserva Natural Campo San Juan. Fundación de Historia Natural Félix de Azara, Buenos Aires 108 pGoogle Scholar
  9. Bauni V, Capmourteres V, Homberg MA, Zuleta GA (2013) Distribution and status of the extant xenarthrans (Mammalia: Xenarthra) in the southern cone mesopotamian savanna, Argentina. Edentata 14:35–50CrossRefGoogle Scholar
  10. Berens DG, Braun C, González-Martínez SC, Griebeler EM, Nathan R, Böhning-Gaese K (2014) Fine-scale spatial genetic dynamics over the life cycle of the tropical tree Prunus africana. Heredity 113(5):401–407PubMedPubMedCentralCrossRefGoogle Scholar
  11. Brookfield JFY (1996) A simple new method for estimating null allele frequency from heterozygote deficiency. Mol Ecol 5:453–455CrossRefGoogle Scholar
  12. Buzatti RS, Ribeiro RA, Lemos Filho JPD, Lovato MB (2012) Fine-scale spatial genetic structure of Dalbergia nigra (Fabaceae), a threatened and endemic tree of the Brazilian Atlantic Forest. Genet Mol Biol 35(4):838–846CrossRefGoogle Scholar
  13. Cabrera AL (1971) Fitogeografía de la República Argentina. Bol Soc Argent Bot 14(1–2):1–42Google Scholar
  14. Carrió E, Rosselló JA (2013) Salt drying: a low-cost, simple and efficient method for storing plants in the field and preserving biological repositories for DNA diversity research. Mol Ecol Resour 14(2):344–351PubMedCrossRefGoogle Scholar
  15. Chakraborty R, Zhong Y, Jin L, Budowle B (1994) Nondetectability of restriction fragments and independence of DNA fragment sizes within and between loci in RFLP typing of DNA. Am J Hum Genet 55(2):391–401PubMedPubMedCentralGoogle Scholar
  16. Chapuis MP, Estoup A (2007) Microsatellite null alleles and estimation of population differentiation. Mol Biol Evol 24(3):621–631PubMedPubMedCentralCrossRefGoogle Scholar
  17. Charlesworth D (2003) Effects of inbreeding on the genetic diversity of populations. Philos Trans R Soc Lond Ser B Biol Sci 358(1434):1051–1070CrossRefGoogle Scholar
  18. Chybicki IJ, Burczyk J (2009) Simultaneous estimation of null alleles and inbreeding coefficients. J Hered 100(1):106–113PubMedCrossRefGoogle Scholar
  19. Cialdella AM (2000) Flora Fanerogámica Argentina, Fascículo 67: Fabaceae Subfamilia Mimosoideae. Proflora-CONICET, Córdoba 10 pGoogle Scholar
  20. Clark DA, Clark DB (1984) Spacing dynamics of a tropical rain forest tree: evaluation of the Janzen-Connell model. Am Nat 124:769–788CrossRefGoogle Scholar
  21. Comita LS, Queenborough SA, Murphy SJ, Eck JL, Xu K, Krishnadas M, Beckman N, Zhu Y (2014) Testing predictions of the Janzen–Connell hypothesis: a meta-analysis of experimental evidence for distance-and density-dependent seed and seedling survival. J Ecol 102(4):845–856PubMedPubMedCentralCrossRefGoogle Scholar
  22. Cornuet JM, Luikart G (1996) Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics 114:2001–2014Google Scholar
  23. Cornuet JM, Santos F, Beaumont MA, Robert CP, Marin JM, Balding DJ, Guillemaud T, Estoup A (2008) Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation. Bioinformatics 24(23):2713–2719PubMedPubMedCentralCrossRefGoogle Scholar
  24. Csilléry K, Blum MG, Gaggiotti OE, François O (2010) Approximate Bayesian computation (ABC) in practice. Trends Ecol Evol 25(7):410–418PubMedCrossRefPubMedCentralGoogle Scholar
  25. Davies SJ, Cavers S, Finegan B, White A, Breed MF, Lowe AJ (2013) Pollen flow in fragmented landscapes maintains genetic diversity following stand-replacing disturbance in a neotropical pioneer tree, Vochysia ferruginea Mart. Heredity 115(2):125–129PubMedPubMedCentralCrossRefGoogle Scholar
  26. de Medeiros RLS, de Souza VC, Neto MAB, de Araújo L, da Silva Barbosa A, de Medeiros RLS (2016) Estrutura da regeneração natural de Anadenanthera colubrina em fragmento de brejo de altitude em Bananeiras, PB. Pesq Flor Bras 36(86):95–101CrossRefGoogle Scholar
  27. de Noir FA, Bravo S, Abdala R (2002) Dispersal mechanisms in some woody native species of Chaco Occidental and Serrano. Quebracho 9:140–150Google Scholar
  28. de Oliveira Melo AT, Coelho ASG, Pereira MF, Blanco AJV, Franceschinelli EV (2014) High genetic diversity and strong spatial genetic structure in Cabralea canjerana (Vell) Mart (Meliaceae): implications to Brazilian Atlantic Forest tree conservation. Nat Conserv 12(2):129–133CrossRefGoogle Scholar
  29. de Souza TV, Torres IC, Steiner N, Paulilo MTS (2015) Seed dormancy in tree species of the Tropical Brazilian Atlantic Forest and its relationships with seed traits and environmental conditions. Braz J Bot 38(2):243–264CrossRefGoogle Scholar
  30. Di Rienzo A, Peterson AC, Garza JC, Valdes AM, Slatkin M, Freimer NB (1994) Mutational processes of simple-sequence repeat loci in human populations. Proc Natl Acad Sci 91(8):3166–3170PubMedCrossRefGoogle Scholar
  31. Dick CW, Hardy OJ, Jones FA, Petit RJ (2008) Spatial scales of pollen and seed-mediated gene flow in tropical rain forest trees. Trop Plant Biol 1(1):20–23CrossRefGoogle Scholar
  32. Doligez A, Baril C, Joly HI (1998) Fine-scale spatial genetic structure with nonuniform distribution of individuals. Genetics 148(2):905–919PubMedPubMedCentralGoogle Scholar
  33. DRYFLOR (2016) Plant diversity patterns in neotropical dry forests and their conservation implications. Science 353(6306):1383–1387CrossRefGoogle Scholar
  34. Earl DA, vonHoldt BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour 4(2):359–361CrossRefGoogle Scholar
  35. Ellstrand NC, Elam DR (1993) Population genetic consequences of small population size: implications for plant conservation. Annu Rev Ecol Syst 24(1):217–242CrossRefGoogle Scholar
  36. Epperson BK (2003) Geographical genetics. Princeton University Press, Princeton 376 pGoogle Scholar
  37. Epps CW, Keyghobadi N (2015) Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change. Mol Ecol 24:6021–6040PubMedCrossRefGoogle Scholar
  38. Escudero A, Iriondo JM, Torres ME (2003) Spatial analysis of genetic diversity as a tool for plant conservation. Biol Conserv 113(3):351–365CrossRefGoogle Scholar
  39. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14(8):2611–2620PubMedPubMedCentralCrossRefGoogle Scholar
  40. Ewédjè EBK, Ahanchédé A, Hardy OJ (2017) Breeding system, gene dispersal and small-scale spatial genetic structure of a threatened food tree species, Pentadesma butyracea (Clusiaceae) in Benin. Conserv Genet 18:799–811.  https://doi.org/10.1007/s10592-017-0928-8 CrossRefGoogle Scholar
  41. Excoffier L, Lischer HEL (2010) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol Ecol Resour 10(3):564–567CrossRefGoogle Scholar
  42. Fageria MS, Rajora OP (2013) Effects of harvesting of increasing intensities on genetic diversity and population structure of white spruce. Evol Appl 6(5):778–794PubMedPubMedCentralCrossRefGoogle Scholar
  43. Falguera C, Faggi A, Homberg M, Bogan S, Bauni V (2015) La vegetación de Campo San Juan. In: Bauni V, Homberg M (eds) Campo San Juan. Fundación Félix de Azara, Buenos Aires, pp 53–67Google Scholar
  44. FAO (1986) Databook on endangened tree and shrub species and provenances. FAO, Rome 524 pGoogle Scholar
  45. Feres JM (2013) Diversidade genética, fluxo génico e sistema de cruzamento de Anadenanthera colubrina (Vell.) Brenan e Anadenanthera peregrina (L.) Speg: duas espécies que ocorrem em alta densidade no interior do Estado de São Paulo. PhD Dissertation, University of São Paulo, Brazil, 162 pGoogle Scholar
  46. Flores FF, Sánchez YAC (2010) First results of botanical characterization of honeys produced by Tetragonisca angustula (Apidae, Meliponinae) in Los Naranjos, Salta, Argentina. Bol Soc Argent Bot 45(1–2):81–91Google Scholar
  47. Frankham R (2003) Genetics and conservation biology. C R Biol 326:22–29CrossRefGoogle Scholar
  48. García MV, Balatti PA, Arturi MJ (2007) Genetic variability in natural populations of Paspalum dilatatum Poir analyzed by means of morphological traits and molecular markers. Genet Resour Crop Evol 54:935–946CrossRefGoogle Scholar
  49. Garza JC, Williamson EG (2001) Detection of reduction in population size using data from microsatellite loci. Mol Ecol 10(2):305–318PubMedPubMedCentralCrossRefGoogle Scholar
  50. Gerlach G, Jueterbock A, Kraemer P, Deppermann J, Harmand P (2010) Calculations of population differentiation based on G ST and D: forget G ST but not all of statistics. Mol Ecol 19:3845–3852PubMedCrossRefGoogle Scholar
  51. Goncalves A, Garcia MV, Heuertz M, Gonzalez-Martinez S (2018) Data from “Demographic history and spatial genetic structure in a remnant population of the subtropical tree Anadenanthera colubrina var. cebil (Griseb.) Altschul (Fabaceae)”. V1. figshare. [Dataset].  https://doi.org/10.6084/m9.figshare.7488650.v1
  52. Goudet J (1995) FSTAT (version 1.2): a computer program to calculate F-statistics. J Hered 86:485–486CrossRefGoogle Scholar
  53. Hadfield JD (2010) MCMC methods for multi-response generalized linear mixed models: the MCMCglmm R package. J Stat Softw 33(2):1–22CrossRefGoogle Scholar
  54. Hampe A, El Masri L, Petit RJ (2010) Origin of spatial genetic structure in an expanding oak population. Mol Ecol 19(3):459–471PubMedCrossRefPubMedCentralGoogle Scholar
  55. Hamrick JL (2004) Response of forest trees to global environmental changes. For Ecol Manag 197(1):323–335CrossRefGoogle Scholar
  56. Hamrick JL, Godt MJW (1996) Effects of life history traits on genetic diversity in plant species. Philos Trans R Soc Lond B Biol Sci 351(1345):1291–1298CrossRefGoogle Scholar
  57. Hamrick JL, Murawski DA, Nason JD (1993) The influence of seed dispersal mechanisms on the genetic structure of tropical tree populations. Vegetatio 107(1):281–297Google Scholar
  58. 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(4):618–620CrossRefGoogle Scholar
  59. Hardy OJ, Maggia L, Bandou E, Breyne P, Caron H, Chevallier MH, Doligez A, Dutech C, Kremer A, Latouche-Hallé CE, Troispoux V (2006) Fine-scale genetic structure and gene dispersal inferences in 10 Neotropical tree species. Mol Ecol 15(2):559–571PubMedCrossRefGoogle Scholar
  60. Hartl DL, Clark AG (2007) Principles of population genetics, 4th edn. Sinauer Associates, Sunderland 653 pGoogle Scholar
  61. Hedrick PW (1999) Perspective: highly variable loci and their interpretation in evolution and conservation. Evolution 53(2):313–318PubMedCrossRefPubMedCentralGoogle Scholar
  62. Hughes CE, Pennington RT, Antonelli A (2013) Neotropical plant evolution: assembling the big picture. Bot J Linn Soc 171(1):1–18CrossRefGoogle Scholar
  63. Jombart T (2008) adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24(11):1403–1405PubMedPubMedCentralCrossRefGoogle Scholar
  64. Jones FA, Hubbell SP (2006) Demographic spatial genetic structure of the Neotropical tree, Jacaranda copaia. Mol Ecol 15(11):3205–3217PubMedCrossRefGoogle Scholar
  65. Jost L (2008) G ST and its relatives do not measure differentiation. Mol Ecol 17(18):4015–4026PubMedCrossRefGoogle Scholar
  66. Jost L, Archer F, Flanagan S, Gaggiotti O, Hoban S, Latch E (2018) Differentiation measures for conservation genetics. Evol Appl 11(7):1139–1148PubMedPubMedCentralCrossRefGoogle Scholar
  67. Justiniano MJ, Fredericksen TS (1998) Ecología y silvicultura de especies menos conocidas: Curupaú – Anadenanthera colubrina. Proyecto BOLFOR, Santa Cruz 58 pGoogle Scholar
  68. Kalisz S, Nason JD, Hanzawa FM, Tonsor SJ (2001) Spatial population genetic structure in Trillium grandiflorum: the roles of dispersal, mating, history, and selection. Evolution 55(8):1560–1568PubMedCrossRefPubMedCentralGoogle Scholar
  69. Klitgård BB, Lewis GP (2010) Neotropical Leguminosae (Mimosoideae). In: Milliken W, Klitgård B, Baracat A (Eds) Neotropikey–Interactive key and information resources for flowering plants of the Neotropics. www.kew.org/science/tropamerica/neotropikey/families/Leguminosae_(Mimosoideae).htm. Accessed 21 Jan 2019
  70. Latouche-Hallé C, Ramboer A, Bandou E, Caron H, Kremer A (2003) Nuclear and chloroplast genetic structure indicate fine-scale spatial dynamics in a neotropical tree population. Heredity 91(2):181–190PubMedCrossRefGoogle Scholar
  71. Leblois R, Rousset F, Estoup A (2004) Influence of spatial and temporal heterogeneities on the estimation of demographic parameters in a continuous population using individual microsatellite data. Genetics 166(2):1081–1092PubMedPubMedCentralCrossRefGoogle Scholar
  72. Loiselle BA, Sork VL, Nason JD, Graham C (1995) Spatial genetic structure of a tropical understory shrub, Psychotria officinalis (Rubiaceae). Am J Bot 82(11):1420–1425CrossRefGoogle Scholar
  73. Lowe AJ, Breed MF, Caron H, Colpaert N, Dick C, Finegan B, Gardner M, Gheysen G, Gribel R, Harris JBC, Kremer A, Lemes MR, Margis R, Navarro CM, Salgueiro F, Villalobos-Barrantes HM, Cavers S (2018) Standardized genetic diversity-life history correlates for improved genetic resource management of Neotropical trees. Divers Distrib 24(6):730–741CrossRefGoogle Scholar
  74. Mogni VY, Oakley LJ, Prado DE (2015) The distribution of woody legumes in neotropical dry forests: the Pleistocene Arc Theory 20 years on. Edinb J Bot 72:35–60CrossRefGoogle Scholar
  75. Monteiro JM, Cecília de Fátima CB, de Albuquerque UP, de Lucena RFP, Florentino ATN, de Oliveira RLC (2006) Use and traditional management of Anadenanthera colubrina (Vell) Brenan in the semi-arid region of northeastern Brazil. J Ethnobiol Ethnomed 2(6):6PubMedPubMedCentralCrossRefGoogle Scholar
  76. Morand M-E, Brachet S, Rossignol P, Dufour J, Frascaria-Lacoste N (2002) A generalized heterozygote deficiency assessed with microsatellites in French common ash populations. Mol Ecol 11(3):377–385PubMedCrossRefGoogle Scholar
  77. Nason JD, Hamrick JL (1997) Reproductive and genetic consequences of forest fragmentation: two case studies of neotropical canopy trees. J Hered 88(4):264–276CrossRefGoogle Scholar
  78. Peakall PE, Smouse R (2012) GenAlEx 6.5: genetic analysis in excel. Population genetic software for teaching and research-an update. Bioinformatics 28:2537–2539PubMedPubMedCentralCrossRefGoogle Scholar
  79. Pennington TR, Laving M (2016) The contrasting nature of woody plant species in different neotropical forest biomes reflects differences in ecological stability. New Phytol 210(1):25–37PubMedCrossRefGoogle Scholar
  80. Pennington TR, Prado DE, Pendry CA (2000) Neotropical seasonally dry forests and quaternary vegetation changes. J Biogeogr 27(2):261–273CrossRefGoogle Scholar
  81. Petit RJ, Hampe A (2006) Some evolutionary consequences of being a tree. Annu Rev Ecol Evol Syst 37:187–214CrossRefGoogle Scholar
  82. Piry S, Luikart G, Cornuet JM (1999) BOTTLENECK: a computer program for detecting recent reductions in the effective population size using allele frequency data. J Hered 90(4):502–503CrossRefGoogle Scholar
  83. Prado DE, Gibbs PE (1993) Patterns of species distributions in the dry seasonal forests of South America. Ann Mo Bot Gard 80(4):902–927CrossRefGoogle Scholar
  84. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155(2):945–959PubMedPubMedCentralGoogle Scholar
  85. Quantum GIS Development Team (2017) QGIS geographic information system. Open Source Geospatial Foundation Project. https://qgis.org. Accessed 21 Jan 2019
  86. Ribeiro RA, Lovato MB (2004) Mating system in a neotropical tree species, Senna multijuga (Fabaceae). Genet Mol Biol 27(3):418–424CrossRefGoogle Scholar
  87. Ridley M (2003) Evolution, 3rd edn. Blackwell Publishing, Oxford 751 pGoogle Scholar
  88. Rodríguez-Quilón I, Jaramillo-Correa JP, Grivet D, Majada J, Alía R, Plomion C, Vendramin GG, González-Martínez SC (2015) Local effects drive heterozygosity–fitness correlations in an outcrossing long-lived tree. Proc R Soc B 282:20152230PubMedCrossRefGoogle Scholar
  89. Roskov Y, Zarucchi J, Novoselova M, Bisby F (2017) ILDIS world database of legumes. In: Roskov Y, Abucay L, Orrell T, Nicolson D, Bailly N, Kirk PM, Bourgoin T, DeWalt RE, Decock W, de Wever A, van Nieukerken E, Zarucchi J, Penev L (eds) Species 2000 and ITIS catalogue of life. Naturalis, Leiden Digital resource at www.catalogueoflife.org/col. Accessed 21 Jan 2019
  90. Rousset F (2008) Genepop’007: a complete re-implementation of the genepop software for Windows and Linux. Mol Ecol Resour 8(1):103–106CrossRefGoogle Scholar
  91. Sánchez-Azofeifa GA, Portillo-Quintero C (2011) Extent and drivers of change of Neotropical seasonally dry tropical forests. In: Dirzo R, Young HS, Mooney HA, Ceballos G (eds) Seasonally dry tropical forests, ecology and conservation. Island Press/Center for Resource Economics, Washington DC, pp 45–57CrossRefGoogle Scholar
  92. Särkinen T, Iganci JR, Linares-Palomino R, Simon MF, Prado DE (2011) Forgotten forests-issues and prospects in biome mapping using seasonally dry tropical forests as a case study. BMC Ecol 11(1):27PubMedPubMedCentralCrossRefGoogle Scholar
  93. Schroeder JW, Tran HT, Dick CW (2014) Fine scale spatial genetic structure in Pouteria reticulata (Engl.) Eyma (Sapotaceae), a dioecious, vertebrate dispersed tropical rain forest tree species. Glob Ecol Conserv 1:43–49CrossRefGoogle Scholar
  94. Schuelke M (2000) An economic method for the fluorescent labeling of PCR fragments. Nat Biotechnol 18(2):233–234PubMedCrossRefGoogle Scholar
  95. Silva CRS, Albuquerque PSB, Ervedosa FR, Mota JWS, Figueira A, Sebbenn AM (2011) Understanding the genetic diversity, spatial genetic structure and mating system at the hierarchical levels of fruits and individuals of a continuous Theobroma cacao population from the Brazilian Amazon. Heredity 106(6):973–985PubMedCrossRefGoogle Scholar
  96. Soldati GT, de Albuquerque UP (2010) Impact assessment of the harvest of a medicinal plant (Anadenanthera colubrina (Vell) Brenan) by a rural semi-arid community (Pernambuco), northeastern Brazil. Int J Biodivers Sci Ecosyst Serv Manage 6(3–4):106–118CrossRefGoogle Scholar
  97. Spiegelhalter DJ, Best NG, Carlin BR, van der Linde A (2002) Bayesian measures of model complexity and fit. Proc R Soc B 64(4):583–639Google Scholar
  98. Steiner JJ, Poklemba CJ, Fjellstrom RG, Elliott LF (1995) A rapid one-tube genomic DNA extraction process for PCR and RAPD analyses. Nucleic Acids Res 23(13):2569–2570PubMedPubMedCentralCrossRefGoogle Scholar
  99. Tambarussi EV, Sebbenn AM, Alves-Pereira A, Vencovsky R, Cambuim J, da Silva AM, de Moraes MA, de Moraes MLT (2017) Dipteryx alata Vogel (Fabaceae), a neotropical tree with high levels of selfing: implications for conservation and breeding programs. Ann For Res 60(1):243–261Google Scholar
  100. Tarazi R, Sebbenn AM, Kageyama PY, Vencovsky R (2013) Edge effects enhance selfing and seed harvesting efforts in the insect-pollinated Neotropical tree Copaifera langsdorffii (Fabaceae). Heredity 110(6):578–585PubMedPubMedCentralCrossRefGoogle Scholar
  101. Torroba-Balmori P, Budde KB, Heer K, González-Martínez SC, Olsson S, Scotti-Saintagne C, Casalis M, Sonké B, Dick CW, Heuertz M (2017) Altitudinal gradients, biogeographic history and microhabitat adaptation affect fine-scale spatial genetic structure in African and Neotropical populations of an ancient tropical tree species. PLoS One 12(8):e0182515PubMedPubMedCentralCrossRefGoogle Scholar
  102. Tortorelli LA (2009) Maderas y Bosques Argentinos. Orientación Gráfica Editora, Buenos Aires 515 pGoogle Scholar
  103. Troupin D, Nathan R, Vendramin GG (2006) Analysis of spatial genetic structure in an expanding Pinus halepensis population reveals development of fine-scale genetic clustering over time. Mol Ecol 15(12):3617–3630PubMedCrossRefGoogle Scholar
  104. van Oosterhout C, Hutchinson WF, Wills DP, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes 4(3):535–538CrossRefGoogle Scholar
  105. Vekemans X, Hardy OJ (2004) New insights from fine-scale spatial genetic structure analyses in plant populations. Mol Ecol 13(4):921–935PubMedCrossRefGoogle Scholar
  106. von Reis Altschul S (1964) A taxonomic study of the genus Anadenanthera. Contrib Gray Herb Harvard Univ 193:3–65Google Scholar
  107. Wagner HH, Fortin MJ (2013) A conceptual framework for the spatial analysis of landscape genetic data. Conserv Genet 14(2):253–261CrossRefGoogle Scholar
  108. Werneck FP, Costa GC, Colli GR, Prado DE, Sites JW (2011) Revisiting the historical distribution of seasonally dry tropical forests: new insights based on palaeodistribution modelling and palynological evidence. Glob Ecol Biogeogr 20(2):272–288CrossRefGoogle Scholar
  109. Williamson-Natesan EG (2005) Comparison of methods for detecting bottlenecks from microsatellite loci. Conserv Genet 6(4):551–562CrossRefGoogle Scholar
  110. Wright SI, Kalisz S, Slotte T (2013) Evolutionary consequences of self-fertilization. Proc R Soc B 280(1760):20130133PubMedCrossRefGoogle Scholar
  111. Young A, Boyle T, Brown T (1996) The population genetic consequences of habitat fragmentation for plants. Trends Ecol Evol 11(10):413–418PubMedCrossRefGoogle Scholar

Copyright information

© INRA and Springer-Verlag France SAS, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Facultad de Ciencias Exactas, Químicas y NaturalesUniversidad Nacional de MisionesPosadasArgentina
  2. 2.Instituto de Biología Subtropical – Nodo Posadas (UNaM – CONICET)PosadasArgentina
  3. 3.Consejo Nacional de Investigaciones Científicas y TécnicasBuenos AiresArgentina
  4. 4.BIOGECO, INRA, Univ. BordeauxCestasFrance

Personalised recommendations