Vegetation History and Archaeobotany

, Volume 16, Issue 2–3, pp 197–202 | Cite as

Estimating the amount of compositional change in late-Quaternary pollen-stratigraphical data

  • H. J. B. BirksEmail author
Original Article


Detrended canonical correspondence analysis is used to estimate the amount of palynological change or compositional turnover in ten Holocene pollen-stratigraphical sequences from Setesdal, southern Norway. The results, when the analyses are standardised for the same time interval, show that the highest amounts of change occurred at sites in the south of Setesdal where there is a richer tree flora. This primarily methodological study provides a robust approach to answering the question as to how much change is recorded within a pollen sequence, and to summarising the amount of change between sequences.


Detrended canonical correspondence analysis Turnover Beta-diversity Compositional change Pollen stratigraphies Sequence comparisons 



This paper is dedicated to Hans-Jürgen Beug on the occasion of his 75th birthday in recognition of his many contributions to European pollen morphology and to Quaternary vegetational history in Europe, the Mediterranean basin, West Africa and the Himalaya, and of his warm friendship and musical hospitality.

I thank Sylvia M. Peglar for providing the pollen-stratigraphical data, Einar Heegaard for assistance with the age-depth modelling, Mark Hill and Jim Ritchie for discussions about quantifying turnover, André Lotter and Karin Zonneveld for valuable reviews, and Cathy Jenks for help in preparing the manuscript. The work in Setesdal was supported by the Norwegian Research Council (NFR) and its NORPAST and NORPEC projects. This is publication A133 from the Bjerknes Centre for Climate Research, Bergen.


  1. Bennett KD (1996) Determination of the number of zones in biostratigraphical sequences. New Phytol 132:155–170CrossRefGoogle Scholar
  2. Bennett KD, Humphry RW (1995) Analysis of late-glacial and Holocene rates of vegetational change at two sites in the British Isles. Rev Palaeobot Palynol 85:263–287CrossRefGoogle Scholar
  3. Birks HJB, Gordon AD (1985) Numerical methods in Quaternary pollen analysis. Academic Press, LondonGoogle Scholar
  4. Birks HJB, Line JM (1992) The use of rarefaction analysis for estimating palynological richness from Quaternary pollen-analytical data. The Holocene 2:1–10Google Scholar
  5. Bratton SP (1975) A comparison of the beta diversity function of the overstory and herbaceous understory of a deciduous forest. Bull Torrey Botanical Club 102:55–60CrossRefGoogle Scholar
  6. Cleveland WS (1979) Robust locally-weighted regression and smoothing scatterplots. J Am Stat Assoc 74:829–836CrossRefGoogle Scholar
  7. Eide W, Birks HH, Bigelow NH, Peglar SM, Birks HJB (2006) Holocene forest development along the Setesdal valley, southern Norway, reconstructed from macrofossil and pollen evidence. Veget Hist Archaeobot 15:65–85CrossRefGoogle Scholar
  8. Erjnæs R (2000) Can we trust gradients extracted by detrended correspondence analysis? J Veget Sci 11:565–572CrossRefGoogle Scholar
  9. Grimm EC, Jacobson GL (1992) Fossil-pollen evidence for abrupt climate changes during the past 18000 years in eastern North America. Clim Dyn 6:179–184CrossRefGoogle Scholar
  10. Heegaard E, Birks HJB, Telford RJ (2005) Relationships between calibrated ages and depth in stratigraphical sequences: an estimate procedure by mixed-effect regression. The Holocene 15:612–618CrossRefGoogle Scholar
  11. Heegaard E, Lotter AF, Birks HJB (2006) Aquatic biota and the detection of climate change: are there consistent aquatic ecotones? J Paleolimnol 35:507–518CrossRefGoogle Scholar
  12. Hill MO, Gauch HG (1980) Detrended correspondence analysis, an improved ordination technique. Vegetatio 42:47–58CrossRefGoogle Scholar
  13. Jacobson GJ, Grimm EC (1986) A numerical analysis of Holocene forest and prairie vegetation in central Minnesota. Ecology 67:958–966CrossRefGoogle Scholar
  14. Janssen CR, Birks HJB (1994) Recurrent groups of pollen types in time. Rev Palaeobot Palynol 82:165–173CrossRefGoogle Scholar
  15. Legendre P, Borcard D, Peres-Neto PR (2005) Analyzing beta diversity: partitioning the spatial variation of community composition data. Ecol Monogr 75:435–450Google Scholar
  16. Lotter AF, Birks HJB (2003) The Holocene palaeolimnology of Sägistalsee and its environmental history—a synthesis. J Paleo- limnol 30:333–342CrossRefGoogle Scholar
  17. Lotter AF, Ammann B, Sturm M (1992) Rates of change and chronological problems during the late-glacial period. Clim Dyn 6:233–239CrossRefGoogle Scholar
  18. McCune B, Grace JB (2002) Analysis of ecological communities. MjM Software Design, Glenden Beach, OR, USAGoogle Scholar
  19. Moen A (1999) National Atlas of Norway: Vegetation. Norwegian Mapping Authority, HønefossGoogle Scholar
  20. Smith AG (1965) Problems of inertia and threshold related to post-glacial habitat changes. Proc Royal Soc Lond B 161:331–342CrossRefGoogle Scholar
  21. Smol JP, Wolfe AP, Birks HJB, 23 others (2005) Climate-driven regime shifts in the biological communities of arctic lakes. Proc Natl Acad Sci USA 102:4397–4402CrossRefGoogle Scholar
  22. Stuiver M, Reimer PJ (1993) Extended 14C data-base and revised CALIB 3.0 14C age calibration program. Radiocarbon 35:215–230Google Scholar
  23. Stuiver M, Reimer PJ, Bard E, Beck JW, Burr GS, Hughen KA, Kromer B, McCormac G, van der Plicht J, Spurk M (1998) INTCAL98 radiocarbon age calibration 24000-0 cal b.p. Radiocarbon 40:1041–1083Google Scholar
  24. Telford RJ, Heegaard E, Birks HJB (2004) All age-depth models are wrong: but how badly? Quat Sci Rev 23:1–5CrossRefGoogle Scholar
  25. ter Braak CJF (1983) Principal components biplots and alpha and beta diversity. Ecology 64:454–462CrossRefGoogle Scholar
  26. ter Braak CJF (1985) Correspondence analysis of incidence and abundance data: properties in terms of a unimodal response model. Biometrics 41:859–873CrossRefGoogle Scholar
  27. ter Braak CJF (1986) Canonical correspondence analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology 67:1167–1179CrossRefGoogle Scholar
  28. ter Braak CJF (1987) Ordination. In: Jongman RHG, ter Braak CJF, van Tongren OFR (eds) Data analysis in community and landscape ecology. Pudoc, Wageningen, pp 91–173Google Scholar
  29. ter Braak CJF, Šmilauer P (2002) CANOCO Reference Manual and CanoDraw for Windows User's Guide: Software for Canonical Community Ordination (version 4.5). Microcomputer Power, Ithaca, NY, USAGoogle Scholar
  30. ter Braak CJF, Verdonschot PFM (1995) Canonical correspondence analysis and related multivariate methods in aquatic ecology. Aquatic Sci 57:255–289CrossRefGoogle Scholar
  31. Velland M (2001) Do commonly used indices of β-diversity measure species turnover? J Veget Sci 12:545–552Google Scholar
  32. Wilson MV, Mohler CL (1983) Measuring compositional change along gradients. Vegetatio 54:129–141CrossRefGoogle Scholar

Copyright information

© Springer Verlag 2006

Authors and Affiliations

  1. 1.Department of Biology and Bjerknes Centre for Climate ResearchUniversity of BergenBergenNorway
  2. 2.Environmental Change Research CentreUniversity College LondonLondonUK

Personalised recommendations