Fifty thousand years of Arctic vegetation and megafaunal diet



Although it is generally agreed that the Arctic flora is among the youngest and least diverse on Earth, the processes that shaped it are poorly understood. Here we present 50 thousand years (kyr) of Arctic vegetation history, derived from the first large-scale ancient DNA metabarcoding study of circumpolar plant diversity. For this interval we also explore nematode diversity as a proxy for modelling vegetation cover and soil quality, and diets of herbivorous megafaunal mammals, many of which became extinct around 10 kyr bp (before present). For much of the period investigated, Arctic vegetation consisted of dry steppe-tundra dominated by forbs (non-graminoid herbaceous vascular plants). During the Last Glacial Maximum (25–15 kyr bp), diversity declined markedly, although forbs remained dominant. Much changed after 10 kyr bp, with the appearance of moist tundra dominated by woody plants and graminoids. Our analyses indicate that both graminoids and forbs would have featured in megafaunal diets. As such, our findings question the predominance of a Late Quaternary graminoid-dominated Arctic mammoth steppe.

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Figure 1: Sample localities.
Figure 2: Taxonomic diversity of Arctic plant assemblages during the last 50 kyr.
Figure 3: Proportional abundance of two families—Teratocephalidae and Cephalobidae—among the total soil nematode community at contemporary tundra and steppe sites in Yukon, Canada.
Figure 4: Plant growth form composition over time and across sample types, estimated by high-throughput sequencing of DNA from 242 permafrost samples.


  1. 1

    Anderson, P. M., Edwards, M. E. & Brubaker, L. B. in The Quaternary Period in the United States. Developments in Quaternary Science (eds Gillespie, A. E., Porter, S. C. & Atwater, B. F. ) 427–440 (Elsevier, 2003)

    Google Scholar 

  2. 2

    Murray, D. F. in Arctic and Alpine Biodiversity: Patterns, Causes and Ecosystem Consequences (eds Chapin, F. S. & Körner, C. ) 21–32 (Springer, 1995)

    Google Scholar 

  3. 3

    Lamb, H. F. & Edwards, M. E. in Vegetation History. Handbook of Vegetation Science 7 (eds Huntley, B. & Webb, T. III ) 519–555 (Kluwer Academic, 1988)

    Google Scholar 

  4. 4

    Kienast, F., Schirrmeister, L., Siegert, C. & Tarasov, P. E. Palaeobotanical evidence for warm summers in the East Siberian Arctic during the last cold stage. Quat. Res. 63, 283–300 (2005)

    Article  Google Scholar 

  5. 5

    Willerslev, E. et al. Diverse plant and animal genetic records from Holocene and Pleistocene sediments. Science 300, 791–795 (2003)

    Article  ADS  CAS  Google Scholar 

  6. 6

    Haile, J. et al. Ancient DNA reveals late survival of mammoth and horse in interior Alaska. Proc. Natl Acad. Sci. USA 106, 22352–22357 (2009)

    Article  ADS  CAS  PubMed  Google Scholar 

  7. 7

    Jørgensen, T. et al. A comparative study of ancient sedimentary DNA, pollen and macrofossils from permafrost sediments of northern Siberia reveals long-term vegetational stability. Mol. Ecol. 21, 1989–2003 (2012)

    Article  CAS  PubMed  Google Scholar 

  8. 8

    Lydolph, M. C. et al. Beringian paleoecology inferred from permafrost-preserved fungal DNA. Appl. Environ. Microbiol. 71, 1012–1017 (2005)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. 9

    Andersen, K. et al. Meta-barcoding of ‘dirt’ DNA from soil reflects vertebrate biodiversity. Mol. Ecol. 21, 1966–1979 (2012)

    Article  CAS  PubMed  Google Scholar 

  10. 10

    Parducci, L. et al. Glacial survival of boreal trees in northern Scandinavia. Science 335, 1083–1086 (2012)

    Article  ADS  CAS  PubMed  Google Scholar 

  11. 11

    Haile, J. et al. Ancient DNA chronology within sediment deposits: are paleobiological reconstructions possible and is DNA leaching a factor? Mol. Biol. Evol. 24, 982–989 (2007)

    Article  CAS  PubMed  Google Scholar 

  12. 12

    Yoccoz, N. G. et al. DNA from soil mirrors plant taxonomic and growth form diversity. Mol. Ecol. 21, 3647–3655 (2012)

    Article  CAS  PubMed  Google Scholar 

  13. 13

    Willerslev, E. & Cooper, A. Ancient DNA. Proc. R. Soc. Lond. B 272, 3–16 (2005)

    Article  CAS  Google Scholar 

  14. 14

    Sønstebø, J. H. et al. Using next-generation sequencing for molecular reconstruction of past Arctic vegetation and climate. Mol. Ecol. Resour. 10, 1009–1018 (2010)

    Article  CAS  PubMed  Google Scholar 

  15. 15

    Hebsgaard, M. B. et al. The farm beneath the sand—an archaeological case study on ancient ‘dirt’ DNA. Antiquity 83, 430–444 (2009)

    Article  Google Scholar 

  16. 16

    Arnold, L. J. et al. Paper II - Dirt, dates and DNA: OSL and radiocarbon chronologies of perennially frozen sediments in Siberia, and their implications for sedimentary ancient DNA studies. Boreas 40, 417–445 (2011)

    Article  Google Scholar 

  17. 17

    Hopkins, D. M. in Paleoecology of Beringia (eds Hopkins, D. M., Matthews, J. V. Jr, Schweger, C. E. & Young, S. B. ) 3–28 (Academic, 1982)

  18. 18

    Ritchie, J. C. & Cwynar, L. C. in Paleoecology of Beringia (eds Hopkins, D. M., Matthews, J. V. Jr, Schweger, C. E., Young, S. B. & Stanley, V. ) 113–126 (Academic, 1982)

    Google Scholar 

  19. 19

    Guthrie, R. D. Frozen Fauna of the Mammoth Steppe (Univ. Chicago Press, 1990)

    Google Scholar 

  20. 20

    Yeates, G. W. Diversity of nematode faunae under three vegetation types on a pallic soil in Otago, New Zealand. NZ J. Zool. 23, 401–407 (1996)

    Article  Google Scholar 

  21. 21

    Sohlenius, B. Influence of climatic conditions on nematode coexistence — a laboratory experiment with a coniferous forest soil. Oikos 44, 430–438 (1985)

    Article  Google Scholar 

  22. 22

    Yeates, G. W. Nematodes as soil indicators: functional and biodiversity aspects. Biol. Fertil. Soils 37, 199–210 (2003)

    Google Scholar 

  23. 23

    Dufrêne, M. & Legendre, P. Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol. Monogr. 67, 345–366 (1997)

    Google Scholar 

  24. 24

    Ruess, L., Michelsen, A. & Jonasson, S. Simulated climate change in subarctic soils: responses in nematode species composition and dominance structure. Nematology 1, 513–526 (1999)

    Article  Google Scholar 

  25. 25

    Sørensen, L. I., Mikola, J., Kytoviita, M.-M. & Olofsson, J. Trampling and spatial heterogeneity explain decomposer abundances in a sub-Arctic grassland subjected to simulated reindeer grazing. Ecosystems 12, 830–842 (2009)

    Article  Google Scholar 

  26. 26

    Popovici, I. & Ciobanu, M. Diversity and distribution of nematode communities in grasslands from Romania in relation to vegetation and soil characteristics. Appl. Soil Ecol. 14, 27–36 (2000)

    Article  Google Scholar 

  27. 27

    Hoschitz, M. & Kaufmann, R. Nematode community composition in five alpine habitats. Nematology 6, 737–747 (2004)

    Article  Google Scholar 

  28. 28

    Poinar, H. N. et al. Molecular coproscopy: dung and diet of the extinct ground sloth Nothrotheriops shastensis . Science 281, 402–406 (1998)

    Article  ADS  CAS  PubMed  Google Scholar 

  29. 29

    Hofreiter, M. et al. A molecular analysis of ground sloth diet through the last glaciation. Mol. Ecol. 9, 1975–1984 (2000)

    Article  CAS  PubMed  Google Scholar 

  30. 30

    Soininen, E. M. E. et al. Analysing diet of small herbivores: the efficiency of DNA barcoding coupled with high-throughput pyrosequencing for deciphering the composition of complex plant mixtures. Front. Zool. 6, 16 (2009)

    Article  PubMed  PubMed Central  Google Scholar 

  31. 31

    Zimov, S. A., Zimov, N. S., Tikhonov, A. N. & Chapin, F. S. I. Mammoth steppe: a high-productivity phenomenon. Quat. Sci. Rev. 57, 26–45 (2012)

    Article  ADS  Google Scholar 

  32. 32

    Owen-Smith, N. Pleistocene extinctions: the pivotal role of megaherbivores. Paleobiology 13, 351–362 (1987)

    Article  Google Scholar 

  33. 33

    Austrheim, G. & Eriksson, O. Recruitment and life-history traits of sparse plant species in subalpine grasslands. Can. J. Bot. 81, 171–182 (2003)

    Article  Google Scholar 

  34. 34

    Wardle, D. A. & Bardgett, R. D. Human-induced changes in large herbivorous mammal density: the consequences for decomposers. Front. Ecol. Environ. 2, 145–153 (2004)

    Article  Google Scholar 

  35. 35

    Güsewell, S. N. P ratios in terrestrial plants: variation and functional significance. New Phytol. 164, 243–266 (2004)

    Article  Google Scholar 

  36. 36

    Cornelissen, J. et al. Leaf digestibility and litter decomposability are related in a wide range of subarctic plant species and types. Funct. Ecol. 18, 779–786 (2004)

    Article  Google Scholar 

  37. 37

    McLauchlan, K. K., Williams, J. J., Craine, J. M. & Jeffers, E. S. Changes in global nitrogen cycling during the Holocene epoch. Nature 495, 352–355 (2013)

    Article  ADS  CAS  PubMed  Google Scholar 

  38. 38

    van der Wal, R. Do herbivores cause habitat degradation or vegetation state transition? Evidence from the tundra. Oikos 114, 177–186 (2006)

    Article  Google Scholar 

  39. 39

    Bråthen, K. A. et al. Induced shift in ecosystem productivity? Extensive scale effects of abundant large herbivores. Ecosystems 10, 773–789 (2007)

    Article  Google Scholar 

  40. 40

    Reimer, P. J. et al. IntCal09 and Marine09 radiocarbon age calibration curves, 0–50,000 years cal BP. Radiocarbon 51, 1111–1150 (2009)

    Article  CAS  Google Scholar 

  41. 41

    Taberlet, P. et al. Power and limitations of the chloroplast trnL (UAA) intron for plant DNA barcoding. Nucleic Acids Res. 35, e14 (2007)

    Article  CAS  PubMed  Google Scholar 

  42. 42

    Elven, R., Murray, D. F., Razzhivin, V. Y. & Yurtsev, B. A. Annotated Checklist of the Panarctic Flora (PAF) ((Natural History Museum, Univ. Oslo,, 2011)

  43. 43

    Sayers, E. W. et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 37, D5–D15 (2009)

    Article  CAS  PubMed  Google Scholar 

  44. 44

    Bray, J. R. & Curtis, J. T. An ordination of the upland forest communities of southern Wisconsin. Ecol. Monogr. 27, 325–349 (1957)

    Article  Google Scholar 

  45. 45

    Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral. Ecol. 26, 32–46 (2001)

    Google Scholar 

  46. 46

    Shepard, R. N. The analysis of proximities: multidimensional scaling with an unknown distance function. I. Psychometrika 27, 125–140 (1962)

    Article  MathSciNet  MATH  Google Scholar 

  47. 47

    Shepard, R. N. The analysis of proximities: multidimensional scaling with an unknown distance function. II. Psychometrika 27, 219–246 (1962)

    Article  MathSciNet  MATH  Google Scholar 

  48. 48

    Nekola, J. C. & White, P. S. The distance decay of similarity in biogeography and ecology. J. Biogeogr. 26, 867–878 (1999)

    Article  Google Scholar 

  49. 49

    Klotz, S., Kühn, I. & Durka, W. BIOLFLOR (Bundesamt für Naturschutz, 2002)

    Google Scholar 

  50. 50

    NGRIP. dating group, 2008. IGBP PAGES/World Data Center for Paleoclimatology Data Contribution Series # 2008-034. NOAA/NCDC Paleoclimatology Program, Boulder CO, USA. (2008)

  51. 51

    Willerslev, E. et al. Ancient biomolecules from deep ice cores reveal a forested southern Greenland. Science 317, 111–114 (2007)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  52. 52

    Epp, L. S. et al. New environmental metabarcodes for analysing soil DNA: potential for studying past and present ecosystems. Mol. Ecol. 21, 1821–1833 (2012)

    Article  CAS  PubMed  Google Scholar 

  53. 53

    Vestergård, M. Nematode assemblages in the rhizosphere of spring barley (Hordeum vulgare L.) depended on fertilisation and plant growth phase. Pedobiologia 48, 257–265 (2004)

    Article  Google Scholar 

  54. 54

    Brock, F., Higham, T., Ditchfield, P. & Ramsey, C. B. Current pretreatment methods for AMS radiocarbon dating at the Oxford Radiocarbon Accelerator Unit (ORAU). Radiocarbon 52, 103–112 (2010)

    Article  CAS  Google Scholar 

  55. 55

    Hua, Q. & Barbetti, M. Review of tropospheric bomb 14C data for carbon cycle modeling and age calibration purposes. Radiocarbon 46, 1273–1298 (2007)

    Article  Google Scholar 

  56. 56

    Goslar, T., Van der Knaap, W. O., Kamenik, C. & van Leeuwen, J. Free-shape 14C age–depth modelling of an intensively dated modern peat profile. J. Quaternary Sci. 24, 481–499 (2009)

    Article  ADS  Google Scholar 

  57. 57

    Boessenkool, S. et al. Blocking human contaminant DNA during PCR allows amplification of rare mammal species from sedimentary ancient DNA. Mol. Ecol. 21, 1806–1815 (2012)

    Article  CAS  PubMed  Google Scholar 

  58. 58

    Haile, J. in Methods in Molecular Biology – Ancient DNA (eds Shaprio, B. & Hofreiter, M. ) 57–63 (Humana Press Series, 2012)

    Google Scholar 

  59. 59

    Coissac, E. OligoTag: a program for designing sets of tags for next-generation sequencing of multiplexed samples. Methods Mol. Biol. 888, 13–31 (2012)

    Article  PubMed  Google Scholar 

  60. 60

    Ait Baamrane, M. A. et al. Assessment of the food habits of the Moroccan dorcas gazelle in M’Sabih Talaa, west central Morocco, using the trnL approach. PLoS ONE 7, e35643 (2012)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  61. 61

    Taylor, P. G. Reproducibility of ancient DNA sequences from extinct Pleistocene fauna. Mol. Biol. Evol. 13, 283–285 (1996)

    Article  CAS  PubMed  Google Scholar 

  62. 62

    Binladen, J. et al. The use of coded PCR primers enables high-throughput sequencing of multiple homolog amplification products by 454 parallel sequencing. PLoS ONE 2, e197 (2007)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  63. 63

    Jackson, S. T. Representation of flora and vegetation in Quaternary fossil assemblages: known and unknown knowns and unknowns. Quat. Sci. Rev. 49, 1–15 (2012)

    Article  ADS  Google Scholar 

  64. 64

    Birks, H. J. B. & Birks, H. H. Quaternary Palaeoecology (London Edward Arnold, 2004)

    Google Scholar 

  65. 65

    Höfle, C. & Ping, C.-L. Properties and soil development of late-Pleistocene paleosols from Seward Peninsula, northwest Alaska. Geoderma 71, 219–243 (1996)

    Article  ADS  Google Scholar 

  66. 66

    Tomašových, A. & Kidwell, S. M. Predicting the effects of increasing temporal scale on species composition, diversity, and rank-abundance distributions. Paleobiology 36, 672–695 (2010)

    Article  Google Scholar 

  67. 67

    Cornelissen, J. H. C. et al. Global negative vegetation feedback to climate warming responses of leaf litter decomposition rates in cold biomes. Ecol. Lett. 10, 619–627 (2007)

    Article  PubMed  Google Scholar 

  68. 68

    Aerts, R. & Chapin, F. S. I. The mineral nutrition of wild plants revisited: a re-evaluation of processes and patterns. Adv. Ecol. Res. 30, 1–67 (1999)

    Article  Google Scholar 

  69. 69

    Crooks, G. E., Hon, G., Chandonia, J.-M. & Brenner, S. E. WebLogo: a sequence logo generator. Genome Res. 14, 1188–1190 (2004)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. 70

    Dansgaard, W. et al. Evidence for general instability of past climate from a 250-kyr ice-core record. Nature 364, 218–220 (1993)

    Article  ADS  Google Scholar 

  71. 71

    Oksanen, J. Multivariate analysis of ecological communities in R: vegan tutorial. R package version 1.17-7 (2011)

  72. 72

    Caliński, T. & Harabasz, J. A dendrite method for cluster analysis. Commun. Stat. 3, 1–27 (1974)

    MathSciNet  MATH  Google Scholar 

  73. 73

    Kühn, I., Durka, W. & Klotz, S. BiolFlor — a new plant-trait database as a tool for plant invasion ecology. Divers. Distrib. 10, 363–365 (2004)

    Article  Google Scholar 

  74. 74

    McCune, B., Grace, J. B. & Urban, D. L. Analysis of ecological communities. MjM Software, Gleneden Beach, Oregon, USA ( (2002)

  75. 75

    Clarke, K. R., Somerfield, P. J. & Chapman, M. G. On resemblance measures for ecological studies, including taxonomic dissimilarities and a zero-adjusted Bray–Curtis coefficient for denuded assemblages. J. Exp. Mar. Biol. Ecol. 330, 55–80 (2006)

    Article  Google Scholar 

  76. 76

    Austin, M. P. Inconsistencies between theory and methodology: a recurrent problem in ordination studies. J. Veg. Sci. 24, 251–268 (2013)

    Article  Google Scholar 

  77. 77

    Faith, D. P., Minchin, P. R. & Belbin, L. Compositional dissimilarity as a robust measure of ecological distance. Vegetatio 69, 57–68 (1987)

    Article  Google Scholar 

  78. 78

    Legendre, P. & Legendre, L. Numerical Ecology (Elsevier, 1998)

    Google Scholar 

  79. 79

    Anderson, M. J., Connell, S. D. & Gillanders, B. M. Relationships between taxonomic resolution and spatial scales of multivariate variation. J. Anim. Ecol. 74, 636–646 (2005)

    Article  Google Scholar 

  80. 80

    Gotelli, N. J. & Colwell, R. K. in Biological Diversity: Frontiers in Measurement and Assessment ( Magurran, A. E. & McGill, B. J. ) 39–54 (Oxford Univ. Press, 2011)

    Google Scholar 

  81. 81

    Walther, B. A. & Moore, J. L. The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance. Ecography 28, 815–829 (2005)

    Article  Google Scholar 

  82. 82

    Hortal, J., Borges, P. A. V. & Gaspar, C. Evaluating the performance of species richness estimators: sensitivity to sample grain size. J. Anim. Ecol. 75, 274–287 (2006)

    Article  PubMed  Google Scholar 

  83. 83

    Vavrek, M. J. Fossil: palaeoecological and palaeogeographical analysis tools. Palaeontol. Electronica 14 (1T). 16p (2011)

    Google Scholar 

  84. 84

    Dunn, P. K. Tweedie: tweedie exponential family models. R package version 2.1.7 (2011)

  85. 85

    Davison, J., Öpik, M. & Daniell, T. J. Arbuscular mycorrhizal fungal communities in plant roots are not random assemblages. FEMS Microbiol. Ecol. 78, 103–115 (2011)

    Article  CAS  PubMed  Google Scholar 

  86. 86

    Munch, K., Boomsma, W., Huelsenbeck, J. P., Willerslev, E. & Nielsen, R. Statistical assignment of DNA sequences using Bayesian phylogenetics. Syst. Biol. 57, 750–757 (2008)

    Article  PubMed  Google Scholar 

  87. 87

    Roberts, D. W. labdsv: ordination and multivariate analysis for ecology. R package version 1.5-0 (2007)

  88. 88

    Underwood, A. J. Experiments in Ecology: Their Logical Design and Interpretation Using Analysis of Variance (Cambridge Univ. Press, 1997)

    Google Scholar 

  89. 89

    Shehzad, W. et al. Prey preference of snow leopard (Panthera uncia) in South Gobi, Mongolia. PLoS ONE 7, e32104 (2012)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  90. 90

    Möller, P., Bolshiyanov, D. Y. & Bergsten, H. Weichselian geology and palaeoenvironmental history of the central Taymyr Peninsula, Siberia, indicating no glaciation during the last global glacial maximum. Boreas 28, 92–114 (1999)

    Article  Google Scholar 

  91. 91

    Kuzmina, S. A. et al. The late Pleistocene environment of the Eastern West Beringia based on the principal section at the Main River, Chukotka. Quat. Sci. Rev. 30, 2091–2106 (2011)

    Article  ADS  Google Scholar 

  92. 92

    Kotov, A. N., Lozhkin, A. V. & Ryabchun, V. K. in Formation of Relief, Correlated Sediments and Placer Deposits of the Northern-East of the USSR, SVKNII DVO AN USSR, Magadan 117–131. (1989)

  93. 93

    Sher, A. V. et al. Late Cenozoic of the Kolyma Lowland. XIV Pacific Science Congress, Khabarovsk 1–116. (1979)

  94. 94

    Wetterich, S., Schirrmeister, L. & Kholodov, A. L. The joint Russian-German expedition Beringia/Kolyma 2008 during the International Polar Year (IPY) 2007/2008. Reports on Polar and Marine Research 636, 43 (2011)

    Google Scholar 

  95. 95

    Zanina, O. G., Gubin, S. V. & Kuzmina, S. A. Late-Pleistocene (MIS 3-2) palaeoenvironments as recorded by sediments, palaeosols, and ground-squirrel nests at Duvanny Yar, Kolyma lowland, northeast Siberia. Quat. Sci. Rev. 30, 2107–2123 (2011)

    Article  ADS  Google Scholar 

  96. 96

    Ager, T. A. Late Quaternary vegetation and climate history of the central Bering land bridge from St. Michael Island, western Alaska. Quat. Res. 60, 19–32 (2003)

    Article  Google Scholar 

  97. 97

    Muhs, D. R., Ager, T. A., Been, J., Bradbury, J. P. & Dean, W. E. A late Quaternary record of eolian silt deposition in a maar lake, St. Michael Island, western Alaska. Quat. Res. 60, 110–122 (2003)

    Article  CAS  Google Scholar 

  98. 98

    Sanborn, P. T., Smith, C. A., Froese, D. G. & Zazula, G. D. Full-glacial paleosols in perennially frozen loess sequences, Klondike goldfields, Yukon Territory, Canada. Quat. Res. 66, 147–157 (2006)

    Article  Google Scholar 

  99. 99

    Zazula, G. D., Froese, D. G., Elias, S. A. & Kuzmina, S. Arctic ground squirrels of the mammoth-steppe: paleoecology of Late Pleistocene middens (24000–29450 14C yr BP), Yukon Territory, Canada. Quat. Sci. Rev. 26, 979–1003 (2007)

    Article  ADS  Google Scholar 

  100. 100

    Froese, D. G., Zazula, G. D. & Reyes, A. V. Seasonality of the late Pleistocene Dawson tephra and exceptional preservation of a buried riparian surface in central Yukon Territory, Canada. Quat. Sci. Rev. 25, 1542–1551 (2006)

    Article  ADS  Google Scholar 

  101. 101

    Demuro, M. et al. Optically stimulated luminescence dating of single and multiple grains of quartz from perennially frozen loess in western Yukon Territory, Canada: comparison with radiocarbon chronologies for the late Pleistocene Dawson tephra. Quat. Geochronol. 3, 346–364 (2008)

    Article  Google Scholar 

  102. 102

    Beilman, D. W. Holocene and recent carbon accumulation in Svalbard mires. Svalbard Geology Workshop, Tromso Norway 27–29 April. (2011)

  103. 103

    Kosintsev, P. A. et al. Environmental reconstruction inferred from the intestinal contents of the Yamal baby mammoth Lyuba (Mammuthus primigenius Blumenbach, 1799). Quat. Int. 255, 231–238 (2012)

    Article  Google Scholar 

  104. 104

    Boeskorov, G. G. et al. Woolly rhino discovery in the lower Kolyma River. Quat. Sci. Rev. 30, 2262–2272 (2011)

    Article  ADS  Google Scholar 

  105. 105

    Harington, C. R. & Eggleston-Stott, M. Partial carcass of a small Pleistocene horse from Last Chance Creek near Dawson City, Yukon. Curr. Res. Pleistocene 13, 105–107 (1996)

    Google Scholar 

  106. 106

    Sulerzhitsky, L. D. & Romanenko, F. A. Age and dispersal of ‘mammoth’ fauna in Asian Polar region (according to radiocarbon data). Kriosfera Zemli 1, 12–19 (1997)

    Google Scholar 

  107. 107

    Lazarev, P. A. in: Mammals of the Yakutian Anthropogene (ed, Labutin, Y. ) 55–97 [in Russian] (Russian Acad. Sci., 1998)

    Google Scholar 

  108. 108

    Kosintsev, P. A., Lapteva, E. G., Korona, O. M. & Zanina, O. G. Living environments and diet of the Mongochen mammoth, Gydan Peninsula, Russia. Quat. Int. 276–277, 253–268 (2012)

    Article  Google Scholar 

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We thank A. Lister, R. D. Guthrie, M. Hofreiter and L. Parducci for thoughts and discussions on our findings and K. Andersen for help identifying possible contamination. We thank T. B. Brand, P. S. Olsen, V. Mirré, L. J. Gillespie, J. M. Saarela, J. Doubt, M. Lomonosova, D. Shaulo, J. E. Eriksen, S. Ickert-Bond, T. Ager, D. Bielman, M. Hajibabaei, A. Telka and S. Zimov for help and providing samples. We thank the Danish National Sequencing Centre. This work was supported by the European Union 6th framework project ECOCHANGE (GOCE-2006-036866, coordinated by P.T.), the Danish National Research Foundation (Centre of Excellence to E.W.), the European Regional Development Fund (Centre of Excellence FIBIR and IUT 20-28 to J.D., M.M. and M.Z.), the Research Council of Norway (191627/V40 to C.B.), the Australian Research Council (DP0558446 to R.G.R.), a Marie Curie International Outgoing Fellowship (PIOF-GA-2009-253376 to E.D.L.) and a Carlsberg Foundation Fellowship (to M.V.).

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The paper represents the joint efforts of several research groups, headed by various people within each group. Rather than publishing a number of independent papers, we have chosen to combine our data in this paper in the belief that this creates a more comprehensive story. The authorship reflects this joint effort. The ECOCHANGE team designed and initiated the project. E.W., M.E.E., J.M., E.D.L., M.V., G.G., J.H., J.C., I.G.A., P.M., D.F., G.Z., A.T., J.A., A.S., G.S., R.G.R., R.D.E.M., M.T.P.G., A.C. and K.H.K. collected the samples. G.G., R.E., A.K.B., J.H.S., C.B., L.G., E.C. and P.T. constructed the plant DNA taxonomic reference libraries and provided taxonomic assignments of the sediment data with input from I.G.A., E.B., S.B., L.S.E., M.E.E. and D.M. E.D.L., M.V., J.H., L.S.E., S.B., C.C., P.W., L.G., G.G. and J.H.S. conducted the genetics laboratory work. T.G. did the dating. F.P., D.R. and V.N. produced and analysed the data concerning the reliability of the trnL approach for estimating herbivore diet. J.D., M.M., M.Z., E.C., M.V., M.R., J.C., S.B., P.B.P., R.C., H.B., R.R., T.M. and P.T. did the analyses. E.D.L. and J.D. produced the figures. E.W. wrote most of the text with input from all authors, in particular J.D., M.M., M.Z., E.D.L., M.E.E., M.V., P.B.P., D.M., K.A.B., N.Y., L.O., C.B., P.T. and R.D.E.M.

Corresponding author

Correspondence to Eske Willerslev.

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Competing interests

The authors note that L.G. and P.T. are co-inventors of patents related to the gh primers and the use of the P6 loop of the chloroplast trnL (UAA) intron for plant identification using degraded template DNA. These patents only restrict commercial applications and have no impact on the use of this locus by academic researchers.

Additional information

All the raw and filtered data concerning plants, nematodes, megafauna and sheep diet are available either from Extended Data and Supplementary Data, or from the Dryad Digital Repository:

Extended data figures and tables

Extended Data Figure 1 Permafrost sample locality details.

a, Radiocarbon dating chronology for the main section at the Main River site, Russia, from which nearly all Main River samples are derived. b, View of the 2009 Duvanny Yar exposure, northeast Siberia. c, yedoma sandy silt in upper c. 12 m of the exposure at Duvanny Yar exposure, northeast Siberia. A large syngenetic ice wedge (top centre) within the yedoma is truncated by a thaw unconformity at a depth of c. 1.9 m below the ground surface, marking the maximum postglacial thaw depth after deposition of the yedoma had ended. People shown for scale, with DNA sediment sample holes to the right of the person on right. d, Calibrated radiocarbon date distributions plotted against depth above river level at Duvanny Yar exposure, northeast Siberia. Although there are some finite dates below 20 m, the general curve shape suggests the radiocarbon dating limit occurs at about this level. e, f, The two Svalbard sites at Colesdalen (e) and Endalen (f).

Extended Data Figure 2 MOTU characterization and data consistency.

ac, Graphs showing the consistency of the DNA-based approach using permafrost samples across the different time periods: average marker size per sample (a); number of reads per sample (b); number of taxa per sample (c). d, WebLogos showing the match between the gh primers and their target sequences in the main plant families involved in the estimation of the proportions of forbs and graminoids70.

Extended Data Figure 3 Temporal classification of samples, assemblage variation in time and data robustness.

ad, K-means clustering of permafrost plant assemblages. a, Cluster identity of samples derived from pre-LGM, LGM and post-LGM periods for values of K between 2 and 10. Each bar represents a separate sample; different colours reflect different cluster identities. b, The Calinski–Harabasz criterion for different levels of K. Higher values indicate stronger support for a level of partitioning. c, d, Heat maps showing the proportional occurrence of samples from pre-LGM, LGM and post-LGM periods in different clusters, for K = 2 (c) and K = 3 (d). Colours vary from red (low values) to white (high values). eg, Assemblage variation in time and space. e, Nonmetric multidimensional scaling (NMDS) ordination revealed significant variation (PERMANOVA, P < 0.01) in fossil/ancient plant assemblage composition during the three palaeoclimatic periods. f, The effect of spatial distance on similarity when assemblages from different palaeoclimatic periods were compared. The vertical axis represents similarity in floristic composition measured as 1-Bray–Curtis similarity, the horizontal axis depicts ln of distance between sampled communities in kilometres. The greater the spatial distance between pairs of assemblages, the more dissimilar they were. However, the rate of the decay differed depending on which two climatic periods were compared (full model P < 0.001). The weakest distance decay in similarity was observed in the case of comparisons between pre-LGM and post-LGM assemblages. Even if pre-LGM and post-LGM samples came from the same geographic area, their floristic compositions were dissimilar. g, Results of randomization tests. Mean proportional composition of different growth form types in LGM and post-LGM samples. The bars around sample means indicate 95% quantiles derived from 999 bootstrap replicates (where bootstrap N was set to the number of samples in the post-LGM data set; see methods for details). h, Counts of MOTUs exhibiting different growth forms binned over 5-kyr time intervals. The analysis included 218 of the 242 sediment samples, as described in Fig. 4. Numbers immediately below the columns indicate sample sizes. Median (central dot), quartile (box), maximum and minimum (whiskers) counts are shown.

Extended Data Table 1 Site information of the 21 permafrost localities (shown in Fig. 1)
Extended Data Table 2 Statistics regarding length of the P6 loop amplified with the gh primers41 for the most important plant families of the two growth forms (graminoids and forbs)
Extended Data Table 3 Locality information of the seven contemporary tundra and steppe sites in Yukon, Canada, which were analysed for nematode faunal composition (shown in Fig. 3)
Extended Data Table 4 Proportion of 17 permafrost sediments with sequences of the two indicator nematode families Cephalobidae and Teratocephalidae
Extended Data Table 5 Herbivorous mammal taxa derived from Main River permafrost samples for which plant data were available
Extended Data Table 6 Sample information of the eight megafauna gut and coprolite samples from woolly mammoth (Mammuthus primigenius), bison (Bison sp.), woolly rhinoceros (Coelodonta antiquitatis) and horse (Equus lambei) (shown in Fig. 1)

Supplementary information

Supplementary Data 1

Sample information of the 242 Holarctic permafrost samples, classified by region and age group. (XLSX 30 kb)

Supplementary Data 2

Counts of sequence reads corresponding to 154 trnL chloroplast plant MOTUs derived from 242 Holarctic permafrost samples. (XLSX 136 kb)

Supplementary Data 3

Influence of LGM definition on analysis of plant community differences using Permanova and mean within period similarity. (XLSX 14 kb)

Supplementary Data 4

List of plant MOTUs, and their occurrence in the three palaeoclimatic periods, to which the sediment plastid trnL gh region reads were assigned. (XLSX 18 kb)

Supplementary Data 5

List of plant MOTUs, and their occurrence in the three palaeoclimatic periods, of the three families Asteraceae, Cyperaceae and Poaceae) to which the sediment ITS region reads were assigned. (XLSX 15 kb)

Supplementary Data 6

MOTU Identification and counts of sequences of DNA-based diet analysis of wholly mammoth, wholly rhinoceros, horse, and bison using coprolite/gut content. (XLSX 14 kb)

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Willerslev, E., Davison, J., Moora, M. et al. Fifty thousand years of Arctic vegetation and megafaunal diet. Nature 506, 47–51 (2014).

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