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A Review of Statistics in Palaeoenvironmental Research

Author

Listed:
  • Maarten Blaauw

    (Queen’s University Belfast)

  • J. Andrés Christen

    (Centro de Investigación en Matemáticas)

  • Marco Antonio Aquino-López

    (Queen’s University Belfast
    Maynooth University)

Abstract

Palaeoecologists use sequences of fossils within deposits from continents and oceans all over the world in order to produce time-series of past environmental dynamics over decades to millennia or longer. Such information can place current and future environmental change into context, for example by showing how climate, environments, ecosystems and humans interacted during past events, and by enabling verification of climate models through ‘hind-casting’ of such events. Through a meta-analysis and focused literature review of currently used statistical approaches in palaeoecological research, we highlight potential pitfalls and suggest ways forward to a fuller statistical understanding of the possibilities and limitations of palaeoecological studies. Statisticians or at least statistical reasoning should be involved in order to quantify uncertainties across the full analytical pipeline of obtaining, analysing and interpreting fossil time-series and could help optimizing the analytical decisions taken at all these steps. Supplementary materials accompanying this paper appear online.

Suggested Citation

  • Maarten Blaauw & J. Andrés Christen & Marco Antonio Aquino-López, 2020. "A Review of Statistics in Palaeoenvironmental Research," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(1), pages 17-31, March.
    • Handle: RePEc:spr:jagbes:v:25:y:2020:i:1:d:10.1007_s13253-019-00374-2
    DOI: 10.1007/s13253-019-00374-2
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    References listed on IDEAS

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    1. Marco A. Aquino-López & Maarten Blaauw & J. Andrés Christen & Nicole K. Sanderson, 2018. "Bayesian Analysis of $$^{210}$$ 210 Pb Dating," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(3), pages 317-333, September.
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