Journal of Paleolimnology

, Volume 49, Issue 3, pp 363–371

‘Diatoms and pH reconstruction’ (1990) revisited

Original paper

DOI: 10.1007/s10933-013-9697-7

Cite this article as:
Birks, H.J.B. & Simpson, G.L. J Paleolimnol (2013) 49: 363. doi:10.1007/s10933-013-9697-7


The 167 sample lake-water pH-diatom calibration data-set created as part of the Palaeolimnology Programme within the Surface Water Acidification Project (SWAP) is re-analysed numerically using nine different numerical methods, six based on simple two-way weighted-averaging (WA), and the other three involving Gaussian logit regression (GLR) and maximum-likelihood (ML) calibration, the modern analogue technique, or weighted-averaging partial least-squares regression and calibration. Root mean squared error of prediction and maximum bias were estimated for all nine methods based on 10,000 internal and 10,000 external cross-validations involving a training-set, an optimisation-set, and a test-set. The results show that WA with a monotonic deshrinking spline equals or slightly outperforms WA with linear inverse deshrinking, especially in external cross-validation. Methods that employ tolerance downweighting generally have an inferior performance except when combined with monotonic deshrinking. It appears that simple two-way WA extensively used in SWAP cannot be significantly bettered. Thanks to increased computing power, better software, and more rigorous cross-validations, GLR shows good performance, especially in external cross-validation.


Cross-validation Gaussian logit regression Maximum-likelihood calibration Model performance Modern analogue technique Monotonic deshrinking SWAP Tolerance downweighting Weighted-averaging Weighted-averaging partial least-squares 

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of BiologyUniversity of BergenBergenNorway
  2. 2.Bjerknes Centre for Climate ResearchUniversity of BergenBergenNorway
  3. 3.Environmental Change Research CentreUniversity College LondonLondonUK
  4. 4.School of Geography and the EnvironmentUniversity of OxfordOxfordUK
  5. 5.Institute of Environmental Change and SocietyUniversity of ReginaReginaCanada

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