Development of a new pan-European testate amoeba transfer function for reconstructing peatland palaeohydrology
Quaternary Science Reviews
© 2016 The Authors. Published by Elsevier Ltd. Open Access funded by Natural Environment Research Council. Under a Creative Commons license: https://creativecommons.org/licenses/by/4.0/
In the decade since the first pan-European testate amoeba-based transfer function for peatland palaeohydrological reconstruction was published, a vast amount of additional data collection has been undertaken by the research community. Here, we expand the pan-European dataset from 128 to 1799 samples, spanning 35° of latitude and 55° of longitude. After the development of a new taxonomic scheme to permit compilation of data from a wide range of contributors and the removal of samples with high pH values, we developed ecological transfer functions using a range of model types and a dataset of ∼1300 samples. We rigorously tested the efficacy of these models using both statistical validation and independent test sets with associated instrumental data. Model performance measured by statistical indicators was comparable to other published models. Comparison to test sets showed that taxonomic resolution did not impair model performance and that the new pan-European model can therefore be used as an effective tool for palaeohydrological reconstruction. Our results question the efficacy of relying on statistical validation of transfer functions alone and support a multi-faceted approach to the assessment of new models. We substantiated recent advice that model outputs should be standardised and presented as residual values in order to focus interpretation on secure directional shifts, avoiding potentially inaccurate conclusions relating to specific water-table depths. The extent and diversity of the dataset highlighted that, at the taxonomic resolution applied, a majority of taxa had broad geographic distributions, though some morphotypes appeared to have restricted ranges.
GTS was supported by the Worldwide University Network (‘Arctic Environments, Vulnerabilities and Opportunities’) and a Department of Employment and Learning (Northern Ireland) PhD studentship. ET was supported by UK NERC-funded Doctoral Training Grant NE/G52398X/1. ML was supported by EU grant PSPB-013/2010 (CLIMPEAT, www.climpeat.pl) and grant 2015/17/B/ST10/01656 from the National Science Center (Poland). RJP was supported by the Leverhulme Trust (RPG 2015-162). RJP and YM were supported by the Russian Science Foundation (grant 14-14-00891 for field work and grant 14-50-00029 for taxonomic analysis). AB was supported by the RFBR Scientific Fund (grants 16-04-00451А and 15-29-02518) and by the German Ministry of Education and Research (CARBOPERM-Project, BMBF Grant No. 03G0836). EM was supported by the European Community funded BERI project (Bog Ecosystem Research Initiative; ENV4-CT95–0028) and the Swiss Federal Office for Education and Science (95.0415). DJC was supported by the EU ACCROTELM project (EVK2-CT-2002-00166).
This is the final version of the article. Available from Elsevier via the DOI in this record.
Vol. 152, pp. 132 - 151
- Geography