Vegetation History and Archaeobotany

, Volume 27, Issue 2, pp 365–379 | Cite as

Biome changes and their inferred climatic drivers in northern and eastern continental Asia at selected times since 40 cal ka bp

  • Fang TianEmail author
  • Xianyong Cao
  • Anne Dallmeyer
  • Gerrit Lohmann
  • Xu Zhang
  • Jian Ni
  • Andrei Andreev
  • Patricia M. Anderson
  • Anatoly V. Lozhkin
  • Elena Bezrukova
  • Natalia Rudaya
  • Qinghai Xu
  • Ulrike Herzschuh
Original Article


Recent global warming is pronounced in high-latitude regions (e.g. northern Asia), and will cause the vegetation to change. Future vegetation trends (e.g. the “arctic greening”) will feed back into atmospheric circulation and the global climate system. Understanding the nature and causes of past vegetation changes is important for predicting the composition and distribution of future vegetation communities. Fossil pollen records from 468 sites in northern and eastern Asia were biomised at selected times between 40 cal ka bp and today. Biomes were also simulated using a climate-driven biome model and results from the two approaches compared in order to help understand the mechanisms behind the observed vegetation changes. The consistent biome results inferred by both approaches reveal that long-term and broad-scale vegetation patterns reflect global- to hemispheric-scale climate changes. Forest biomes increase around the beginning of the late deglaciation, become more widespread during the early and middle Holocene, and decrease in the late Holocene in fringe areas of the Asian Summer Monsoon. At the southern and southwestern margins of the taiga, forest increases in the early Holocene and shows notable species succession, which may have been caused by winter warming at ca. 7 cal ka bp. At the northeastern taiga margin (central Yakutia and northeastern Siberia), shrub expansion during the last deglaciation appears to prevent the permafrost from thawing and hinders the northward expansion of evergreen needle-leaved species until ca. 7 cal ka bp. The vegetation-climate disequilibrium during the early Holocene in the taiga-tundra transition zone suggests that projected climate warming will not cause a northward expansion of evergreen needle-leaved species.


Siberia China Northern Asia Model-data comparison Pollen Permafrost Vegetation-climate disequilibrium 



The authors would like to express their gratitude to all the palynologists who, either directly or indirectly, contributed their pollen records to the pollen dataset. This research was supported by the German Research Foundation (DFG) and PalMod project (BMBF). Jian Ni was supported by the National Key Research and Development Program of China (2016YFC0502101). The work of Andrei Andreev was also partly performed under the Russian Government Program of Competitive Growth of Kazan Federal University. The work of Natalia Rudaya was founded by the Alexander von Humboldt Foundation (Ref 3.3-RUS-1151158-HFST-E); Ministry of Education and Science of the Russian Federation, Project no. 14.Z50.31.0010 of the Altai State University; Russian Government Program of Competitive Growth of Kazan Federal University; and the Russian Foundation for Basic Research (RFBR), Grant no. 16-55-44065. Additional support was provided to Anatoly Lozhkin by the Russian Foundation for Fundamental Research (15-05-06420) and Russian Academy of Sciences, Far East Branch (15-I-2-067). Cathy Jenks provided help with language editing.

Supplementary material

334_2017_653_MOESM1_ESM.pdf (10 mb)
Supplementary material 1 (PDF 10198 KB)


  1. Abaimov AP, Sofronov MA (1996) Main trends of past-fire successions in the near-tundra forests of Central Siberia. In: Goldammer JG, Furyaev VV (eds) Fire in ecosystems of boreal Eurasia. Kluwer Academic Publishers, Dordrecht, pp 372–386CrossRefGoogle Scholar
  2. Abaimov AP, Zyryanova OA, Prokushkin SG (2002) Long-term investigations of larch forests in cryolithic zone of Siberia: brief history, recent results and possible changes under global warming. Eurasian J Forest Res 5:95–106Google Scholar
  3. Algvere KV (1966) Forest economy in the U.S.S.R.: An analysis of Soviet competitive potentialities. Studia Forestalia Suecica 39. Skogshögskolan, StockholmGoogle Scholar
  4. Alpat’ev AM, Arkhangel’skii AM, Podoplelov NY, Stepanov AY (1976) Fizicheskaya geografiya SSSR (Aziatskaya chast’). Vysshaya Shkola, MoscowGoogle Scholar
  5. Andersen KK, Azuma N, Barnola JM et al (2004) High resolution record of Northern Hemisphere climate extending into the last interglacial period. Nature 431:147–151CrossRefGoogle Scholar
  6. Berger A (1978) Long-term variations of daily insolation and Quaternaryclimate changes. J Atmos Sci 35:2,362–2,367Google Scholar
  7. Bigelow NH, Brubaker LB, Edwards ME et al (2003) Climate change and arctic ecosystems: 1. Vegetation changes north of 55°N between the last glacial maximum, mid-Holocene, and present. J Geophys Res 108:8170. CrossRefGoogle Scholar
  8. Binney H, Edwards M, Macias-Fauria M et al V (2017) Vegetation of Eurasia from the last glacial maximum to present: key biogeographic patterns. Quat Sci Rev 157:80–97CrossRefGoogle Scholar
  9. Binney HA, Willis KJ, Edwards ME et al (2009) The distribution of late-Quaternary woody taxa in northern Eurasia: evidence from a new macrofossil database. Quat Sci Rev 28:2,445–2,464Google Scholar
  10. Blaauw M, Christen JA (2011) Flexible paleoclimate age-depth models using an autoregressive gamma process. Bayesian Anal 6:457–474Google Scholar
  11. Came RE, Oppo DW, McManus JF (2007) Amplitude and timing of temperature and salinity variability in the subpolar North Atlantic over the last 10,000 years. Geology 35:315–318CrossRefGoogle Scholar
  12. Cao X, Herzschuh U, Ni J, Zhao Y, Böhmer T (2015) Spatial and temporal distributions of major tree taxa in eastern continental Asia during the last 22,000 years. Holocene 25:79–91CrossRefGoogle Scholar
  13. Cao X, Ni J, Herzschuh U, Wang Y, Zhao Y (2013) A late Quaternary pollen dataset from eastern continental Asia for vegetation and climate reconstructions: set up and evaluation. Rev Palaeobot Palynol 194:21–37CrossRefGoogle Scholar
  14. Chen Y, Ni J, Herzschuh U (2010) Quantifying modern biomes based on surface pollen data in China. Glob Planet Chang 74:114–131CrossRefGoogle Scholar
  15. Cheng H, Edwards RL, Sinha A et al (2016) The Asian monsoon over the past 640,000 years and ice age terminations. Nature 534:640–646CrossRefGoogle Scholar
  16. Dallmeyer A, Claussen M, Ni J et al (2017) Biome changes in Asia since the mid-Holocene—an analysis of different transient Earth system model simulations. Clim Past 13:107–134CrossRefGoogle Scholar
  17. Ermakov N, Cherosov M, Gogoleva P (2002) Classification of ultracontinental boreal forests in central Yakutia. Folia Geobot 37:419–440CrossRefGoogle Scholar
  18. Fang J, Piao S, Zhou L, He J, Wei F, Myneni RB, Tucker CJ, Tan K (2005) Precipitation patterns alter growth of temperature vegetation. Geophys Res Lett 32:411–415CrossRefGoogle Scholar
  19. Frost GV, Epstein HE (2014) Tall shrub and tree expansion in Siberian tundra ecotones since the 1960s. Glob Chang Biol 20:1,264–1,277Google Scholar
  20. Harris I, Jones PD, Osborn TJ, Lister DH (2014) Updated high-resolution grids of monthly climatic observations—the CRU TS3.10 dataset. Int J Climatol 34:623–642CrossRefGoogle Scholar
  21. Harrison SP, Jolly D, Laarif F et al (1998) Intercomparison of simulated global vegetation distribution in response to 6 kyr bp orbital forcing. J Clim 11:2,721–2,742CrossRefGoogle Scholar
  22. Harrison SP, Prentice IC, Barboni D, Kohfeld K, Ni J, Sutra JP (2010) Ecophysiological and bioclimatic foundations for a global plant functional classification. J Veg Sci 21:300–317CrossRefGoogle Scholar
  23. Helbig M, Pappas C, Sonnentag O (2016) Permafrost thaw and wildfire: Equally important drivers of boreal tree cover changes in the Taiga Plains, Canada. Geophys Res Lett 43:1,598–1,606Google Scholar
  24. Herzschuh U, Birks HJB, Laepple T, Andreev A, Melles M, Brigham-Grette J (2016) Glacial legacies on interglacial vegetation at the Pliocene–Pleistocene transition in NE Asia. Nat Commun 11967.
  25. Hilbig W (1995) The vegetation of Mongolia. SPB Academic Publishing, AmsterdamGoogle Scholar
  26. Hou X (2001) Vegetation Atlas of China. Science Press, BeijingGoogle Scholar
  27. Huang J, Yu H, Dai A, Wei Y, Kang L (2017) Drylands face potential threat under 2 °C global warming target. Nat Clim Chang 7:412–422. CrossRefGoogle Scholar
  28. Huang J, Yu H, Guan X, Wang G, Guo R (2015) Accelerated dryland expansion under climate change. Nat Clim Chang 6:166–171. CrossRefGoogle Scholar
  29. Kaplan JO (2001) Geophysical applications of vegetation modeling. PhD Dissertation, Lund University, LundGoogle Scholar
  30. Kaplan JO, Bigelow NH, Prentice IC et al (2003) Climate change and arctic ecosystems: 2. Modeling, paleodata-model comparisons, and future projections. J Geophys Res 108:8171. CrossRefGoogle Scholar
  31. Laskar J, Robutel P, Joutel F, Gastineau M, Correia ACM, Levrard B (2004) A long-term numerical solution for the insolation quantities of the Earth. Astron Astrophys 428:261–285CrossRefGoogle Scholar
  32. Liu H, Cui H, Pott R, Speier M (1999) The surface pollen of the woodland-steppe ecotone in southeastern Inner Mongolia, China. Rev Palaeobot Palynol 105:237–250CrossRefGoogle Scholar
  33. Liu H, Williams AP, Allen C et al (2013) Rapid warming accelerates tree growth decline in semi-arid forests of Inner Asia. Glob Chang Biol 19:2,500–2,510Google Scholar
  34. Lloyd AH, Bunn AG, Berner L (2011) A latitudinal gradient in tree growth response to climate warming in the Siberian taiga. Glob Chang Biol 17:1,935–1,945Google Scholar
  35. Meyer H, Opel T, Laepple T, Dereviagin AY, Hoffmann K, Werner M (2015) Long-term winter warming trend in the Siberian Arctic during the mid- to late Holocene. Nat Geosci 8:122–125CrossRefGoogle Scholar
  36. Miller GH, Alley R, Brigham-Grette J, Fitzpatrick JJ, Polyak L, Serreze MC, White JWC (2010) Arctic amplification: can the past constrain the future?. Quat Sci Rev 29:1,779–1,790Google Scholar
  37. Morgan JA, Pataki DE, Körner C et al (2004) Water relations in grassland and desert ecosystems exposed to elevated atmospheric CO2. Oecologia 140:11–25CrossRefGoogle Scholar
  38. Nelson JA, Morgan JA, LeCain DR, Mosier AR, Milchunas DG, Parton WJ (2004) Elevated CO2 increases soil moisture and enhances plant water relations in a long-term field study in the semi-arid shortgrass steppe of Northern Colorado. Plant Soil 259:169–179CrossRefGoogle Scholar
  39. Ni J, Cao X, Jeltsch F, Herzschuh U (2014) Biome distribution over the last 22,000 year in China. Palaeogeogr Palaeoclimatol Palaeoecol 409:33–47CrossRefGoogle Scholar
  40. Ni J, Yu G, Harrison SP, Prentice IC (2010) Palaeovegetation in China during the late Quaternary: biome reconstructions based on a global scheme of plant functional types. Palaeogeogr Palaeoclimatol Palaeoecol 289:44–61CrossRefGoogle Scholar
  41. Niemeyer B, Klemm J, Pestryakova LA, Herzschuh U (2015) Relative pollen productivity estimates for common taxa of the northern Siberian Arctic. Rev Palaeobot Palynol 221:71–82CrossRefGoogle Scholar
  42. Normand S, Ricklefs RE, Skov F, Bladt J, Tackenberg O, Svenning JC (2011) Postglacial migration supplements climate in determining plant species ranges in Europe. Proc Royal Soc B: Biol Sci 278:2,644–2,653.
  43. Pailler D, Bard E (2002) High frequency paleoceanographic changes during the past 140,000 years recorded by the organic matter in sediments off the Iberian Margin. Palaeogeogr Palaeoclimatol Palaeoecol 181: 431–452CrossRefGoogle Scholar
  44. Prentice IC, Cramer W, Harrison SP, Leemans R, Monserud RA, Solomon AM (1992) A global biome model based on plant physiology and dominance, soil properties and climate. J Biogeogr 19:117–134CrossRefGoogle Scholar
  45. Prentice IC, Guiot J, Huntley B, Jolly D, Cheddadi R (1996) Reconstructing biomes from palaeoecological data: a general method and its application to European pollen data at 0 and 6 ka. Clim Dyn 12:185–194CrossRefGoogle Scholar
  46. Prentice IC, Webb III T (1998) BIOME 6,000: reconstructing global mid-Holocene vegetation patterns from palaeoecological records. J Biogeogr 25:997–1,005Google Scholar
  47. Rogers BM, Soja AJ, Goulden ML, Randerson JT (2015) Influence of tree species on continental differences in boreal fires and climate feedbacks. Nat Geosci 8:228–234CrossRefGoogle Scholar
  48. Rudaya N, Nazarova L, Novenko E et al (2016) Quantitative reconstructions of mid-late Holocene climate and vegetation in the north-eastern Altai Mountains recorded in Lake Teletskoye. Glob Planet Chang 141:12–24CrossRefGoogle Scholar
  49. Shichi K, Takahara H, Krivonogov SK, Bezrukova EV, Kashiwaya K, Takehara A, Nakamura T (2009) Late Pleistocene and Holocene vegetation and climate records from Lake Kotokel, central Baikal region. Quat Int 205:98–110CrossRefGoogle Scholar
  50. Sturm M, McFadden J, Liston G (2001) Snow-shrub interactions in Arctic tundra: a hypothesis with climatic implications. J Clim 14:336–344CrossRefGoogle Scholar
  51. Sun W, Song X, Mu X, Gao P, Wang F, Zhao G (2015) Spatiotemporal vegetation cover variations associated with climate change and ecological restoration in the Loess Plateau. Agric For Meteorol 209–210:87–99CrossRefGoogle Scholar
  52. Svenning JC, Sandel B (2013) Disequilibrium vegetation dynamics under future climate change. Am J Bot 100:1,266–1,286Google Scholar
  53. Tarasov PE, Andreev AA, Anderson PM et al (2013) A pollen-based biome reconstruction over the last 3.562 million years in the Far East Russian Arctic—new insights into climate-vegetation relationships at the regional scale. Clim Past 9:2,759–2,775CrossRefGoogle Scholar
  54. Tarasov PE, Volkova VS, Webb T III et al (2000) Last glacial maximum biomes reconstructed from pollen and plant macrofossil data from northern Eurasia. J Biogeogr 27:609–620CrossRefGoogle Scholar
  55. Tarasov PE, Webb T III, Andreev AA et al (1998) Present-day and mid-Holocene biomes reconstructed from pollen and plant macrofossil data from the Former Soviet Union and Mongolia. J Biogeogr 25:1,029–1,053Google Scholar
  56. Tchebakova NM, Parfenova E, Soja AJ (2009) The effects of climate, permafrost and fire on vegetation change in Siberia in a changing climate. Environ Res Lett 4:045,013CrossRefGoogle Scholar
  57. Tian F, Cao X, Dallmeyer A, Ni J, Zhao Y, Wang Y, Herzschuh U (2016) Quantitative woody cover reconstructions from eastern continental Asia of the last 22 ka reveal strong regional peculiarities. Quat Sci Rev 137:33–44CrossRefGoogle Scholar
  58. Wang Y, Herzschuh U (2011) Reassessment of Holocene vegetation change on the upper Tibetan Plateau using the pollen-based REVEALS model. Rev Palaeobot Palynol 168:31–40CrossRefGoogle Scholar
  59. Xia J, McGuire AD, Lawrence D et al (2017) Terrestrial ecosystem model performance in simulating productivity and its vulnerability to climate change in the northern permafrost region. J Geophys Res Biogeosciences 122:430–446CrossRefGoogle Scholar
  60. Xu QH, Cao X, Tian F, Zhang SR, Li YC, Li M, Liu Y, Liang J (2014) Relative pollen productivities of typical steppe species in northern China and their potential in past vegetation reconstruction. Sci China Earth Sci 57:1,254–1,266Google Scholar
  61. Xu QH, Li YC, Yang XL, Zheng ZH (2007) Quantitative relationship between pollen and vegetation in northern China. Sci China Series D Earth Sci 50:582–599CrossRefGoogle Scholar
  62. Zhao WW, Andreev AA, Wennrich V, Tarasov PE, Anderson P, Lozhkin AV, Melles M (2015) The Réunion Subchron vegetation and climate history of the northeastern Russian Arctic inferred from the Lake El’gygytgyn pollen record. Palaeogeogr Palaeoclimatol Palaeoecol 436:167–177CrossRefGoogle Scholar
  63. Zhilich S, Rudaya N, Nazarova L, Krivonogov S, Pozdnyakov D (2017) Environmental dynamics of the Baraba forest-steppe (Siberia) over the last 8000 years and their impact on the types of economic life of the population. Quat Sci Rev 163:152–161CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Fang Tian
    • 1
    • 2
    Email author
  • Xianyong Cao
    • 1
  • Anne Dallmeyer
    • 2
  • Gerrit Lohmann
    • 3
    • 4
  • Xu Zhang
    • 3
  • Jian Ni
    • 5
  • Andrei Andreev
    • 6
    • 7
  • Patricia M. Anderson
    • 8
  • Anatoly V. Lozhkin
    • 9
  • Elena Bezrukova
    • 10
    • 11
  • Natalia Rudaya
    • 7
    • 11
    • 12
    • 13
  • Qinghai Xu
    • 14
  • Ulrike Herzschuh
    • 1
    • 15
    • 16
  1. 1.Research Unit Potsdam, Alfred Wegener InstituteHelmholtz Centre for Polar and Marine ResearchPotsdamGermany
  2. 2.Max Planck Institute for MeteorologyHamburgGermany
  3. 3.Alfred Wegener InstituteHelmholtz Centre for Polar and Marine ResearchBremerhavenGermany
  4. 4.MARUM-Center for Marine Environmental SciencesUniversity of BremenBremenGermany
  5. 5.College of Chemistry and Life SciencesZhejiang Normal UniversityJinhuaChina
  6. 6.Institute of Geology and MineralogyUniversity of CologneCologneGermany
  7. 7.Institute of Geology and Petroleum TechnologiesKazan Federal UniversityKazanRussia
  8. 8.Earth and Space Sciences and Quaternary Research CenterUniversity of WashingtonSeattleUSA
  9. 9.North East Interdisciplinary Science Research InstituteFar East Branch Russian Academy of SciencesMagadanRussia
  10. 10.Vinogradov Institute of Geochemistry, Siberian BranchRussian Academy of SciencesIrkutskRussia
  11. 11.Institute of Archaeology and Ethnography, Siberian BranchRussian Academy of SciencesNovosibirskRussia
  12. 12.Department of Archaeology and EthnographyNovosibirsk State UniversityNovosibirskRussia
  13. 13.Department of Archaeology and EthnographyAltai State UniversityBarnaulRussia
  14. 14.College of Resources and Environment SciencesHebei Normal UniversityShijiazhuangChina
  15. 15.Institute of Earth and Environment ScienceUniversity of PotsdamPotsdamGermany
  16. 16.Institute of Biochemistry and BiologyUniversity of PotsdamPotsdamGermany

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