Comparing regional and supra-regional transfer functions for palaeohydrological reconstruction from Holocene peatlands

Abstract

Testate amoebae-based transfer functions are commonly used in peatland palaeoclimate studies. These models have been developed in several regions of the world and are sometimes used for palaeohydrological reconstruction from fossil data in locations where no transfer functions exist. Limitations of this approach may include missing modern analogues and problems associated with site-specific or regional factors in testate amoebae ecology and biogeography. This study presents new testate amoebae-hydrology transfer functions based on data from six peatlands in Northern England. Transfer functions were generated for water table depth and moisture content using weighted averaging tolerance downweighted regression with inverse deshrinking and model performance was assessed using leave-one-out (jacknifing) cross-validation.To examine the robustness of applying transfer functions extra-regionally, we performed a number of spatially independent cross-validation (SICV) tests using contemporary testate amoebae and environmental data from established Northern Ireland and European transfer functions. Inferred water table depths were consistent with observed values in terms of position along the hydrological gradient, however magnitudes varied. We then applied the three independent transfer functions to fossil data from a peatland in Northern England to compare the reconstructions. The results show that the direction of the reconstructions is consistent in terms of wet/dry shifts.However, variation in the magnitudes of the reconstructed water tables is apparent.This probably reflects the sampling regime, including temporal/seasonal effects, and differences in testate amoebae ecology between regions and individual sites.

Late Holocene ecohydrological and carbon dynamics of a UK raised bog: impact of human activity and climate change

“…While other studies have noted a reduced C accumulation rate over periods of increased BSW, particularly during the LIA (Oldfield et al, 1997;Mauquoy et al, 2002) the analysis from MTM suggests a relatively constant accumulation rate over the last~2400 years except the MWP. Lower accumulation over the wetter periods could be related to reduced net primary productivity (NPP) during colder conditions (Mauquoy et al, 2002;Charman et al, 2013) and/or differential decay of more aquatic species such as Sphagnum cuspidatum (Johnson and Damman, 1991). The high C accumulation over the MWP shown here is most likely a result of increased NPP and species composition/litter type (Borren et al, 2004;Laiho, 2006;Beilman et al, 2009) as higher LORCA rates have been associated with woody and ericaceous peats (Loisel and Garneau, 2010).…”

“…Exceptions to this were the splitting out of Assulina scandinavica from the Assulina seminulum group (cf. Turner et al, 2013). Cladoceran remains of the genus Alona, and the Rotifer Habrotrocha angusticollis were also counted.…”

“…The transfer function assumes a relationship between water table depth (WTD) and fossil testate amoebae assemblage based on modern speciesenvironment data. The transfer function of Turner et al (2013), based on a training set of 116 samples from northern England (including 25 from MTM) is used here. The weighted averaging (tolerance downweighted with inverse deshrinking) model has been rigorously tested through spatially-independent cross-validation (SICV) with species-environment data from Northern Ireland and Europe (Charman et al, 2007).…”

“…Although magnitudes of change should be viewed with caution when employing a transfer function approach to palaeohydrological reconstruction (Turner et al, 2013), this rapid deepening of the water table represents the largest shift within the last 2,000 years, from a reconstructed WTD of~3 cm to~29 cm.…”

“…Further refinement of the potential effects of eutrophication at the bog surface due to animal grazing could be aided by the addition of coprophilous fungal spore analysis (van Geel, 1978;Davis, 1987;van Geel and Aptroot, 2006). (Turner et al, 2013) is shown with maximum sample-specific error ranges based on 1,000 bootstrap cycles. The diagram has been zoned using constrained Euclidian distance cluster analysis, with fine-tuning by eye based on assemblage changes.…”