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

ABSTRACT 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 dep...

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Bibliographic Details
Published in:Journal of Quaternary Science
Main Authors: Zhang, Hui, Amesbury, Matthew J., Ronkainen, Tiina, Charman, Dan J., Gallego‐Sala, Angela V., VÄliranta, Minna
Other Authors: China Scholarship Council
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2017
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Online Access:http://dx.doi.org/10.1002/jqs.2970
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjqs.2970
https://onlinelibrary.wiley.com/doi/pdf/10.1002/jqs.2970
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Summary:ABSTRACT 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 ( R 2 = 0.77, RMSEP = 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.