Testate amoeba as palaeohydrological indicators in the permafrost peatlands of north-east European Russia and Finnish Lapland

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record. To explore the use of testate amoeba for investigating the impacts of climate change on permafrost peatland hydrology, we established a new modern training set from Arctic permafrost peatlan...

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Bibliographic Details
Published in:Journal of Quaternary Science
Main Authors: Zhang, H, Amesbury, MJ, Ronkainen, T, Charman, DJ, Gallego-Sala, AV, Valiranta, M
Format: Article in Journal/Newspaper
Language:English
Published: Wiley for Quaternary Research Association 2017
Subjects:
Online Access:http://hdl.handle.net/10871/29357
https://doi.org/10.1002/jqs.2970
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Summary:This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record. To explore the use of testate amoeba for investigating the impacts of climate change on permafrost peatland hydrology, we established a new modern training set from Arctic permafrost peatlands in north-east European Russia and Finnish Lapland. Ordination analyses showed that water-table depth (WTD) was the most important control on testate amoeba distribution. We developed a new testate amoeba-based WTD transfer function and thoroughly tested it. We found that our transfer function had strong predictive power. The best- performing model was based on tolerance-downweighted weighted averaging with inverse deshrinking (R2 1⁄4 0.77, RMSEP 1⁄4 5.62 cm with leave-one-out cross validation). The new transfer function was applied to a short peat core from Arctic Russia and revealed two major hydrological shifts, which could be validated against plant macrofossil data. We also compared our model to another two models from more temperate peatlands. Comparison of the different testate amoeba datasets suggests that testate amoeba ecohydrological relationships are similar for permafrost peatlands to those in more temperate regions, but there are some differences that suggest a need for training datasets that are fully representative of permafrost peatlands. H.Z. acknowledges the PhD study grant from the China Scholarship Council (grant no. 201404910499). Research was financed by the Academy of Finland and by the University of Helsinki.