2015
DOI: 10.1016/j.quascirev.2015.04.019
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Testing peatland water-table depth transfer functions using high-resolution hydrological monitoring data

Abstract: Transfer functions are now commonly used to reconstruct past environmental variability from palaeoecological data. However, such approaches need to be critically appraised. Testate amoeba-based transfer functions are an established method for the quantitative reconstruction of past water-table variations in peatlands, and have been applied to research questions in palaeoclimatology, peatland ecohydrology and archaeology. We analysed automatically-logged peatland water-table data from dipwells located in Englan… Show more

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Cited by 48 publications
(47 citation statements)
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“…Because the transfer function is based on one‐time water‐table measurements, the reconstruction was detrended using linear regression following Swindles et al. ().…”
Section: Methodsmentioning
confidence: 99%
“…Because the transfer function is based on one‐time water‐table measurements, the reconstruction was detrended using linear regression following Swindles et al. ().…”
Section: Methodsmentioning
confidence: 99%
“…The use of single-shot water table measurements for testate amoeba-based hydrodrological studies has been debated previously (e.g. Bobrov et al 1999;Booth 2008;Swindles et al 2015). Whilst the method only provides a 'snapshot' of the seasonal water table variability, it has been shown to adequately represent the relative hydrological status of sample locations and is sufficient to drive a hydrological gradient for transfer function development (Swindles et al 2015).…”
Section: Methodsmentioning
confidence: 99%
“…Bobrov et al 1999;Booth 2008;Swindles et al 2015). Whilst the method only provides a 'snapshot' of the seasonal water table variability, it has been shown to adequately represent the relative hydrological status of sample locations and is sufficient to drive a hydrological gradient for transfer function development (Swindles et al 2015). Sampling should not be carried out, however, during 8 periods of extreme weather such as summer drought or after heavy rain Swindles et al 2009).…”
Section: Methodsmentioning
confidence: 99%
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