Articles | Volume 25, issue 2
https://doi.org/10.5194/we-25-169-2025
https://doi.org/10.5194/we-25-169-2025
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18 Sep 2025
Standard article |  | 18 Sep 2025

Geographically weighted models in palaeoecology: R package and application to testate amoebae in peatlands

Sophie Erb, Matthieu Mulot, Alina Matei, and Edward A. D. Mitchell

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This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
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Cited articles

Amesbury, M. J., Swindles, G. T., Bobrov, A., Charman, D. J., Holden, J., Lamentowicz, M., Mallon, G., Mazei, Y., Mitchell, E. A. D., Payne, R. J., Roland, T. P., Turner, T. E., and Warner, B. G.: Development of a new pan-European testate amoeba transfer function for reconstructing peatland palaeohydrology, Quaternary Sci. Rev., 152, 132–151, https://doi.org/10.1016/j.quascirev.2016.09.024, 2016. a, b, c, d, e, f, g
Amesbury, M. J., Booth, R. K., Roland, T. P., Bunbury, J., Clifford, M. J., Charman, D. J., Elliot, S., Finkelstein, S., Garneau, M., Hughes, P. D. M., Lamarre, A., Loisel, J., Mackay, H., Magnan, G., Markel, E. R., Mitchell, E. A. D., Payne, R. J., Pelletier, N., Roe, H., Sullivan, M. E., Swindles, G. T., Talbot, J., van Bellen, S., and Warner, B. G.: Towards a Holarctic synthesis of peatland testate amoeba ecology: Development of a new continental-scale palaeohydrological transfer function for North America and comparison to European data, Quaternary Sci. Rev., 201, 483–500, https://doi.org/10.1016/j.quascirev.2018.10.034, 2018. a
Belyea, L. R.: Revealing the Emperor's new clothes: niche-based palaeoenvironmental reconstruction in the light of recent ecological theory, Holocene, 17, 683–688, https://doi.org/10.1177/0959683607079002, 2007. a
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Birks, H. J. B.: Quantitative palaeoenvironmental reconstructions from Holocene biological data, in: Global change in the Holocene, edited by: Mackay, A., Battarbee, R. W., Birks, H. J. B., and Oldfield, F., 107–123, https://www.st-andrews.ac.uk/~rjsw/PalaeoPDFs/Birks2003.pdf (last access: 17 June 2025​​​​​​​), 2003. a
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It is well known that the spatial distribution of micro-organisms is heterogeneous. Taking spatiality into account allows for better modelling of the environmental parameters that drive the distribution of living organisms. We show that geographically weighted models perform much better in reconstructing water table depth in peatlands based on testate amoeba communities. The method (R package) can be used for any application of a regression model in the case of heterogeneous spatial distribution.
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