Conservation Genetics

, Volume 13, Issue 1, pp 165–181 | Cite as

Population structure and landscape genetics in the endangered subterranean rodent Ctenomys porteousi

  • Fernando J. Mapelli
  • Matías S. Mora
  • Patricia M. Mirol
  • Marcelo J. Kittlein
Research Article

Abstract

In order to devise adequate conservation and management strategies for endangered species, it is important to incorporate a reliable understanding of its spatial population structure, detecting the existence of demographic partitions throughout its geographical range and characterizing the distribution of its genetic diversity. Moreover, in species that occupy fragmented habitats it is essential to know how landscape characteristics may affect the genetic connectivity among populations. In this study we use eight microsatellite markers to analyze population structure and gene flow patterns in the complete geographic range of the endangered rodent Ctenomys porteousi. Also, we use landscape genetics approaches to evaluate the effects of landscape configuration on the genetic connectivity among populations. In spite of geographical proximity of the sampling sites (8–27 km between the nearest sites) and the absence of marked barriers to individual movement, strong population structure and low values of gene flow were observed. Genetic differentiation among sampling sites was consistent with a simple model of isolation by distance, where peripheral areas showed higher population differentiation than those sites located in the central area of the species’ distribution. Landscape genetics analysis suggested that habitat fragmentation at regional level has affected the distribution of genetic variation among populations. The distance of sampling sites to areas of the landscape having higher habitat connectivity was the environmental factor most strongly related to population genetic structure. In general, our results indicate strong genetic structure in C. porteousi, even at a small spatial scale, and suggest that habitat fragmentation could increase the population differentiation.

Keywords

Population structure Landscape genetics Habitat fragmentation Ctenomys 

References

  1. Alvarez-Castañeda ST, Patton JL (2004) Geographic genetic architecture of the pocket gopher (Thomomys bottae) populations in Baja California, Mexico. Mol Ecol 13:2287–2301PubMedGoogle Scholar
  2. Antinuchi CD, Zenuto RR, Luna F, Cutrera AP, Perisinotti P, Busch C (2006) Energy budget in subterranean rodents: insights from the tuco-tuco Ctenomys talarum (Rodentia: Ctenomyidae). In: Kelt DA, Salazar-Bravo JA, Patton JL (eds) The quintessential naturalist: honoring the life and legacy of Oliver Pearson. University of California Press, Berkeley, pp 111–140Google Scholar
  3. Balding DJ, Nichols RA (1995) A method for quantifying differentiation between populations at multi-allelic loci and its implications for investigating identity and paternity. Genetica 96:3–12PubMedGoogle Scholar
  4. Banks SC, Lindenmayer DB, Ward SJ, Taylor AC (2005) The effects of habitat fragmentation via forestry plantation establishment on spatial genotypic structure in the small marsupial carnivore, Antechinus agilis. Mol Ecol 14:1667–1680PubMedGoogle Scholar
  5. Beaumont MA (1999) Detecting population expansion and decline using microsatellites. Genetics 153:2013–2029PubMedGoogle Scholar
  6. Bergl RA, Vigilant L (2007) Genetic analysis reveals population structure and recent migration within the highly fragmented range of the Cross River gorilla (Gorilla gorilla diehli). Mol Ecol 16:501–516PubMedGoogle Scholar
  7. Berry O, Tocher MD, Sarre SD (2004) Can assignment tests measure dispersal? Mol Ecol 13:551–561PubMedGoogle Scholar
  8. Bjilsma R, Bundgaard J, Boerema A (2000) Does inbreeding affect the extinction risk of small populations? predictions from Drosophila. J Evol Biol 13:502–514Google Scholar
  9. Bouteiller C, Perrin N (2000) Individual reproductive success and effective population size in the greater white-footed shrew Crocidura russula. P Roy Soc Lond B Bio 267:701–705Google Scholar
  10. Brown WM, George MJ, Wilson AC (1979) Rapid evolution of animal mitochondrial DNA. Proc Natl Acad Sci USA 76:1967–1971PubMedGoogle Scholar
  11. Busch C, Antinuchi CD, del Valle JC, Kittlein MJ, Malizia AI, Vassallo AI, Zenuto RR (2000) Population ecology of subterranean rodents. In: Lacey EA, Patton JL, Cameron GN (eds) Life underground: the biology of subterranean rodents. University of Chicago Press, Chicago, pp 183–226Google Scholar
  12. Cabe PR, Pagel RB, Hanlon TJ, Aldrich ME, Connors L, Marsh DM (2007) Fine-scale population differentiation and gene flow in a terrestrial salamander (Plethodon cinereus) living in continuous habitat. Heredity 98:53–60PubMedGoogle Scholar
  13. Cegelski CC, Waits LP, Anderson NJ (2003) Assessing population structure and gene flow in Montana wolverines (Gulo gulo) using assignment-based approaches. Mol Ecol 12:2907–2918PubMedGoogle Scholar
  14. Ciofi C, Beaumont MA, Swingland IR, Bruford MW (1999) Genetic divergence and units for conservation in the Komodo dragon Varanus komodoensis. P Roy Soc Lond B Bio 266:2269–2274Google Scholar
  15. Clark-Laboratories (1999) Idrisi32. Clark University, WorcesterGoogle Scholar
  16. Cornuet JM, Luikart G (1996) Description and power analysis of two tests for detecting recent population bottlenecks from allele frequency data. Genetics 144:2001–2014PubMedGoogle Scholar
  17. Coulon A, Cosson JF, Angibault JM, Cargnelutti B, Galan M, Morellet N, Petit E, Aulagnier S, Hewison AJM (2004) Landscape connectivity influences gene flow in a roe deer population inhabiting a fragmented landscape: an individual-based approach. Mol Ecol 13:2841–2850PubMedGoogle Scholar
  18. Crisci JV (2001) The voice of historical biogeography. J Biogeogr 28:157–168Google Scholar
  19. Cutrera AP, Lacey EA, Busch C (2005) Genetic structure in a solitary rodent (Ctenomys talarum): implications for kinship and dispersal. Mol Ecol 14:2511–2523PubMedGoogle Scholar
  20. Cutrera AP, Antinuchi CD, Mora MS, Vassallo AI (2006) Home-range and activity patterns of the South American subterranean rodent Ctenomys talarum. J Mammal 87:1183–1191Google Scholar
  21. D’Elía G, Lessa EP, Cook JA (1998) Geographic structure, gene flow and maintenance of melanism in Ctenomys rionegrensis (Rodentia: Octodontidae). Z Säugetierk 63:285–296Google Scholar
  22. Davies KF, Melbouurne BA (2007) The tails of two geckos tell the story of dispersal in fragmented landscape. Mol Ecol 16:3289–3291PubMedGoogle Scholar
  23. Di Rienzo A, Peterson AC, Garza JC, Valdes AM, Stalkin M, Freimer NB (1994) Mutational processes of simple sequence repeat loci in human populations. Proc Natl Acad Sci USA 91:3166–3170PubMedGoogle Scholar
  24. Díaz GB, Ojeda RA (2000) Libro rojo de mamíferos amenazados de la Argentina. Sociedad Argentina para el Estudio de los Mamíferos, MendozaGoogle Scholar
  25. Dionne M, Caron F, Dodson JJ, Bernatchez L (2008) Landscape genetics and hierarchical genetic structure in Atlantic salmon: the interaction of gene flow and local adaptation. Mol Ecol 17:2382–2396PubMedGoogle Scholar
  26. El Jundi TARJ, Freitas TRO (2004) Genetic and demographic structure in a population of Ctenomys lami (Rodentia, Ctenomyidae). Hereditas 140:18–23PubMedGoogle Scholar
  27. Excoffier L, Laval G, Schneider S (2005) ARLEQUIN ver. 3.0: an integrated software packaged for population genetics data analysis. Evol Bioinform 1:47–50Google Scholar
  28. Falush D, Stephens M, Pritchard JK (2003) Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587PubMedGoogle Scholar
  29. Felsenstein J (1993) Phylogeny Inference Package (PHYLIP). Version 3.5. University of Washington, SeattleGoogle Scholar
  30. Fernández-Stolz GP, Stolz JFB, de Freitas TRO (2007) Bottlenecks and dispersal in the tuco-tuco das dunas, Ctenomys flamarioni (Rodentia: Ctenomyidae), in southern Brazil. J Mammal 88:935–945Google Scholar
  31. Ferris SD, Sage RD, Prager EM, Ritte U, Wilson AC (1983) Mitochondrial evolution in mice. Genetics 105:681–721PubMedGoogle Scholar
  32. Foll M, Gaggiotti OE (2006) Identifying the environmental factors that determine the genetic structure of populations. Genetics 174:875–891PubMedGoogle Scholar
  33. Frankham R, Lees K, Montgomery ME, England PR, Lowe E, Briscoe DA (1999) Do population size bottlenecks reduce evolutionary potential? Anim Conserv 2:255–260Google Scholar
  34. Funk WC, Blouin MS, Corn PS, Maxell BA, Pilliod DS, Amish S, Allendorf FW (2005) Population structure of Columbia spotted frogs (Rana luteiventris) is strongly affected by the landscape. Mol Ecol 14:483–496PubMedGoogle Scholar
  35. Gaggiotti OE, Bekkevold D, Jorgensen HBH, Foll M, Carvalho GR, Andre C, Ruzzante D (2009) Disentangling the effects of evolutionary demographic, and environmental factors influencing genetic structure of natural populations: Atlantic herring as a case study. Evolution 63:2939–2951PubMedGoogle Scholar
  36. Gava A, de Freitas TRO (2004) Microsatellite analysis of a hybrid zone between chromosomally divergent populations of Ctenomys minutus from southeastern Brazil (Rodentia: Ctenomyidae). J Mammal 85:1201–1206Google Scholar
  37. Gonçalves GL, de Freitas TRO (2009) Intraspecific variation and genetic differentiation of the collared tuco-tuco (Ctenomys torquatus) in southern Brazil. J Mammal 90:1020–1031Google Scholar
  38. Goossens B, Chikhi L, Jalil MF, Ancrenaz M, Lackman-Ancrenaz I, Mohamed M, Andau P, Bruford MW (2005) Patterns of genetic diversity and migration in increasingly fragmented and declining orang-utan (Pongo pygmaeus) populations from Sabah, Malaysia. Mol Ecol 14:441–456PubMedGoogle Scholar
  39. Goossens B, Chikhi L, Ancrenaz M, Lackman-Ancrenaz I, Andau P, Bruford MW (2006) Genetic signature of anthropogenic population collapse in orang-utans. Plos Biol 4:285–291Google Scholar
  40. Goudet J (2001) FSTAT, a program to estimate and test gene diversities and fixation indices (version 2.9.3). http://www.unil.ch/izea/softwares/fstat.html
  41. Guo S, Thompson E (1992) Performing the exact test of Hardy–Weinberg proportion for multiples alleles. Biometrics 48:361–372PubMedGoogle Scholar
  42. Hanski I (1994) A practical model of metapopulation dynamics. J Anim Ecol 63:151–162Google Scholar
  43. Hanski I (1999) Metapopulation ecology. Oxford University Press, New YorkGoogle Scholar
  44. Hanski I, Gilpin ME (1997) Metapopulation biology: ecology genetics and evolution. Academic Press, San DiegoGoogle Scholar
  45. Holycross AT, Douglas ME (2007) Geographic isolation, genetic divergence, and ecological non-exchangeability define conservation units in a threatened sky-island rattlesnake. Biol Conserv 134:142–154Google Scholar
  46. Hurston H, Voith L, Bonanno J, Foufopoulos J, Pafilis P, Valakos E, Anthony N (2009) Effects of fragmentation on genetic diversity in island populations of the Aegean wall lizard Podarcis erhardii (Lacertidae, Reptilia). Mol Phylogenet Evol 52:395–405PubMedGoogle Scholar
  47. Jacobsen BH, Hansen MM, Loeschcke V (2005) Microsatellite DNA analysis of northern pike (Esox lucius L.) populations: insights into the genetic structure and demographic history of a genetically depauperate species. Biol J Linn Soc 84:91–101Google Scholar
  48. Kalinowski ST, Taper ML, Marshall TC (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol Ecol 16:1099–1100PubMedGoogle Scholar
  49. Keller L, Arcese P, Smith J, Hochachka WM, Stearns SC (1994) Selection against inbred song sparrows during a natural population bottleneck. Nature 372:356–357PubMedGoogle Scholar
  50. Kimura M, Ohta T (1978) Stepwise mutation model and distribution of allele frequencies in a finite population. Proc Natl Acad Sci USA 75:2868–2872PubMedGoogle Scholar
  51. Kittlein MJ, Gaggiotti OE (2008) Interactions between environmental factors can hide isolation by distance patterns: a case study of Ctenomys rionegrensis in Uruguay. P Roy Soc Lond B Bio 275:2633–2638Google Scholar
  52. Kraaijeveld-Smit FJL, Beebee TJC, Griffiths RA, Moore RD, Schley L (2005) Low gene flow but high genetic diversity in the threatened Mallorcan midwife toad Alytes muletensis. Mol Ecol 14:3307–3315PubMedGoogle Scholar
  53. Lacey EA (2001) Microsatellite variation in solitary and social tuco-tucos: molecular properties and population dynamics. Heredity 86:628–637PubMedGoogle Scholar
  54. Lacey EA, Maldonado JE, Clabaugh JP, Matocq MD (1999) Interspecific variation in microsatellites isolated from tuco-tucos (Rodentia: Ctenomyidae). Mol Ecol 8:1753–1768Google Scholar
  55. Lacy RC (1997) The importance of genetic variation to the viability of mammalian populations. J Mammal 78:320–335Google Scholar
  56. Lada H, Thomson JR, Mac Nally R, Taylor AC (2008) Impact of massive landscape change on a carnivorous marsupial in south-eastern Australia: inferences farm landscape genetics analysis. J Appl Ecol 45:1732–1741Google Scholar
  57. Lampert KP, Rand AS, Muller UG, Ryan MJ (2003) Fine-scale genetic pattern and evidence for sex-biased dispersal in the tungara frog, Physalaemus pustulosus. Mol Ecol 12:3325–3334PubMedGoogle Scholar
  58. Lande R (1995) Breeding plans for small populations base don the dynamics of quantitative genetic variance. In: Ballou JD, Gilpin M, Foose TJ (eds) Population management for survival and recovery. Columbia University Press, New York, pp 318–340Google Scholar
  59. Lande R, Barrowclough G (1987) Effective population size, genetic variation and their use in population management. In: Soulé ME (ed) Viable population for conservation. Cambridge University Press, New York, pp 87–123Google Scholar
  60. Leclerc E, Mailhot Y, Mingelbier M, Bernatchez L (2008) The landscape genetics of yellow perch (Perca flavescens) in a large fluvial ecosystem. Mol Ecol 17:1702–1717PubMedGoogle Scholar
  61. Luikart G, Sherwin WB, Steele BM, Allendorf FW (1998) Usefulness of molecular markers for detecting population bottleneck via monitoring genetic change. Mol Ecol 7:963–974PubMedGoogle Scholar
  62. Manel S, Gaggiotti OE, Waples RS (2005) Assignment methods: matching biological questions with appropriate techniques. Trends Ecol Evol 20:136–142PubMedGoogle Scholar
  63. Mantel N (1967) The detection of disease clustering and a generalized regression approaches. Cancer Res 27:209–220PubMedGoogle Scholar
  64. Mapelli FJ, Kittlein MJ (2009) Influence of patch and landscape characteristics on the distribution of the subterranean rodent Ctenomys porteousi. Landsc Ecol 24:723–733Google Scholar
  65. Mapelli FJ, Mora MS, Mirol PM, Kittlein MJ (2011) Effects of quaternary climatic changes on the phylogeography and historical demography of the subterranean rodent Ctenomys porteousi. J Zool (in press)Google Scholar
  66. Massarini A, Dopazo HJ, Bouzat JL, Hasson E, Reig OA (1992) The population genetic structure of Ctenomys porteousi (Rodentia: Octodontidae). Biochem Syst Ecol 20:723–734Google Scholar
  67. Matocq MD (2004) Reproductive success and effective population size in woodrats (Neotoma macrotis). Mol Ecol 13:1635–1642PubMedGoogle Scholar
  68. Miller SA, Dikes DD, Polesky HH (1988) A simple salting procedure for extracting DNA from human nucleated cells. Nucleic Acids Res 16:215Google Scholar
  69. Mirol P, Giménez MD, Searle JB, Bidau CJ, Faulkes CG (2010) Population and species boundaries in the South American subterranean rodent Ctenomys in a dynamic environment. Biol J Linn Soc 100:368–383Google Scholar
  70. Monachesi A (1995) Las inundaciones en el sudoeste de la provincia de Buenos Aires, Argentina: Un problema de actores y estrategias. Revista Semestral de la Red de Estudios Sociales en Prevención de Desastres en America Latina 5:1–9Google Scholar
  71. Mora MS, Lessa EP, Kittlein MJ, Vassallo AI (2006) Phylogeography of the subterranean rodent Ctenomys autralis in sand-dune habitats: evidence of population expansion. J Mammal 87:1192–1203Google Scholar
  72. Mora MS, Lessa EP, Cutrera AP, Kittlein MJ, Vassallo AI (2007) Phylogeographic structure in the subterranean tuco-tuco Ctenomys talarum (Rodentia: Ctenomyidae): contrasting the demographic consequences of regional and habitat-specific histories. Mol Ecol 16:3453–3465PubMedGoogle Scholar
  73. Mora MS, Mapelli FJ, Gaggiotti OE, Kittlein MJ, Lessa EP (2010) Dispersal and population structure at different spatial scales in the subterranean rodent Ctenomys australis. BMC Genetics 11:9PubMedGoogle Scholar
  74. Nei M (1972) Genetic distance between populations. Am Nat 106:283–292Google Scholar
  75. Opazo JC, Burgueño MP, Carter MJ, Palma RE, Bozinovic F (2008) Phylogeography of the subterranean rodent Spalacopus cygnus (Caviomorpha, Octodontidae). J Mammal 89:837–844Google Scholar
  76. Piggott MP, Banks SC, Taylor AC (2006) Population structure of brush-tailed rock-wallaby (Petrogale penicillata) colonies inferred from analysis of faecal DNA. Mol Ecol 15:93–105PubMedGoogle Scholar
  77. 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 90:502–503Google Scholar
  78. Pritchard JK, Wen W (2003) Documentation for STRUCTURE software: Version 2. http://www.pritch.bsd.uchicago.edu
  79. Pritchard J, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959PubMedGoogle Scholar
  80. Proctor M, McLellan BN, Strobeck C, Barclay MR (2005) Genetic analysis reveals demographic fragmentation of grizzly bears yielding vulnerably small populations. P Roy Soc Lond B Bio 272:2409–2416Google Scholar
  81. Rice WR (1989) Analysing tables of statistical tests. Evolution 43:223–225Google Scholar
  82. Rosenberg MS, Anderson CD (2011) PASSaGE: Pattern Analysis, Spatial Statistics and Geographic Exegesis. Version 2. Meth Ecol Evol 2:229–232Google Scholar
  83. Rouse JW, Haas RH, Schell JA, Deering DW, Harlan JC (1974) Monitoring the vernal advancement of retrogradation of natural vegetation. Technical report, NASA/GSFC, Type III, Final Report, GreenbeltGoogle Scholar
  84. Rousset F (1997) Genetic differentiation and estimation of gene flow from F statistics under isolation by distance. Genetics 145:1219–1228PubMedGoogle Scholar
  85. Scarpati OE, Lay JAF, Capriolo AD (2008) La inundación del año 2001 en la provincia de Buenos Aires, Argentina. Mundo Agrario 9:1–17Google Scholar
  86. Schweizer M, Excoffier L, Heckel G (2007) Fine-scale genetic structure and dispersal in the common vole (Microtus arvalis). Mol Ecol 16:2463–2473PubMedGoogle Scholar
  87. Shaffer G, Fellers GM, Magee A, Voss R (2000) The genetics of amphibian declines: population substructure in the Yosemite Toad, Bufo canorus (Anura, Bufonidae) based on single-strand conformation polymorphism analysis (SSCP) and mitochondrial DNA sequence data. Mol Ecol 9:245–257PubMedGoogle Scholar
  88. Sherwin WB, Moritz C (2000) Managing and monitoring genetic erosion. In: Young AJ, Clarke G (eds) Genetics, demography and viability of fragmented populations. Cambridge University Press, New York, pp 9–34Google Scholar
  89. Sigurgardottir S, Helgason A, Gulcher JR, Stefansson K, Donnelly P (2000) The mutation rate in the human mtDNA control region. Am J Hum Genet 66:1599–1609PubMedGoogle Scholar
  90. Simberloff D (1988) The contribution of population and community biology to conservation science. Annu Rev Ecol Syst 19:473–511Google Scholar
  91. Slatkin M (1987) Gene flow and the geographic structure of natural populations. Science 236:787–792PubMedGoogle Scholar
  92. Slatkin M (1993) Isolation by distance in equilibrium and non-equilibrium populations. Evolution 47:264–279Google Scholar
  93. Sork VL, Nason J, Campbell DR, Fernandez JF (1999) Landscape approaches to historical and contemporary gene flow in plants. Trends Ecol Evol 14:219–224PubMedGoogle Scholar
  94. Steimberg EK, Patton JL (2000) Genetic structure and the geographic of the speciation in subterranean rodents: opportunities and constraints for evolutionary diversification. In: Lacey EA, Patton JL, Cameron GN (eds) Life underground: the biology of subterranean rodents. University of Chicago Press, Chicago, pp 183–226Google Scholar
  95. Storz JF, Beaumont MA (2002) Testing for genetic evidence of population contraction and expansion: an empirical analysis of microsatellite DNA variation using a hierarchical Bayesian model. Evolution 56:154–166PubMedGoogle Scholar
  96. Storz JF, Beaumont MA, Alberts SC (2002) Genetic evidence for long-term population decline in a savannah-dwelling primate: inferences from a hierarchical Bayesian model. Mol Biol Evol 19:1981–1990PubMedGoogle Scholar
  97. Su B, Fu Y, Wang Y, Jin L, Chakraborty R (2001) Genetic diversity and population history of the Red Panda (Ailurus fulgens) as inferred from mitochondrial DNA sequence variations. Mol Biol Evol 18:1070–1076PubMedGoogle Scholar
  98. Taylor PD, Fahrig L, Henein K, Merriam G (1993) Connectivity is a vital element of landscape structure. Oikos 68:571–573Google Scholar
  99. Vaha JP, Erkinaro J, Niemela E, Primmer CR (2007) Life-history and habitat features influence the within-river genetic structure of Atlantic salmon. Mol Ecol 16:2638–2654PubMedGoogle Scholar
  100. Waser PM, Strobeck C (1998) Genetic signatures of interpopulation dispersal. Trends Ecol Evol 13:43–44PubMedGoogle Scholar
  101. Watts PC, Rouquette JR, Saccheri IJ, Kemp SJ, Thompson DJ (2004) Molecular and ecological evidence for small-scale isolation by distance in an endangered damselfly, Coenagrion mercuriale. Mol Ecol 13:2931–2945PubMedGoogle Scholar
  102. Weber JL, Wong C (1993) Mutation of human short tandem repeats. Hum Mol Genet 2:1123–1128PubMedGoogle Scholar
  103. Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358–1370Google Scholar
  104. Wiens JA (1997) Metapopulation dynamics and landscape ecology. In: Hanski I, Gilpin ME (eds) Metapopulation biology: ecology, genetics and evolution. Academic Press, Toronto, pp 43–62Google Scholar
  105. Wlasiuk G, Garza JC, Lessa EP (2003) Genetic and geographic differentiation in the Rio Negro tuco-tuco (Ctenomys rionegrensis): inferring the roles of migration and drift from multiple genetic markers. Evolution 57:913–926PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Fernando J. Mapelli
    • 1
  • Matías S. Mora
    • 1
  • Patricia M. Mirol
    • 2
  • Marcelo J. Kittlein
    • 1
  1. 1.Departamento de Biología, Facultad de Ciencias Exactas y NaturalesUniversidad Nacional de Mar del PlataMar del PlataArgentina
  2. 2.Museo Argentino de Ciencias Naturales “Bernardino Rivadavia”Buenos AiresArgentina

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