Phytolith-inferred transfer function for paleohydrological reconstruction of Dajiuhu peatland, central China

• Published in: Holocene (Sevenoaks) Vol. 28; no. 10; pp. 1623 - 1630
• Main Authors: Liu, Hongye, Gu, Yansheng, Lun, Zijian, Qin, Yangmin, Cheng, Shenggao
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.10.2018; Sage Publications Ltd
• Subjects: Calibration; Data; Data processing; Distribution; Ecological monitoring; Groundwater table; Hydrologic data; Hydrology; Magnetic permeability; Magnetic susceptibility; Organic carbon; Peat; Peatlands; Reconstruction; Redundancy; Soil; Soil investigations; Soil surfaces; Spatial distribution; Total organic carbon; Transfer functions; Variance; Variance analysis; Water depth; Water table; China; phytolith; transfer function; depth to water table; central China; environmental variables; Dajiuhu peatland
• ISSN: 0959-6836; 1477-0911
• DOI: 10.1177/0959683618782590

Depth to water table (DWT, the depth from the water surface to the top of the peat surface) is one of the most important environmental variables related to the habitat types and distribution of vegetation within a subalpine peatland. The distribution of phytolith assemblages and basic environmental data from 43 surface soil samples with significant ecological and hydrological gradients were investigated to generate transfer functions for quantitative reconstruction of paleoenvironmental changes in Dajiuhu peatland, central China. Detrended correspondence analysis (DCA) and redundancy analysis (RDA) were employed to explore the relationship between main environmental variables and phytolith morphotypes and distributions. Our results indicate that the spatial distribution of phytoliths was significantly correlated with the DWT (25% variance), total organic carbon (TOC, 10% variance) and magnetic susceptibility (χ, 7% variance). We established the transfer functions for the significant variables based on modern analogue technique (MAT), weighted averaging techniques (WA) and weighted averaging partial least squares (WA-PLS), and model performance was assessed using bootstrap cross-validation. The high correspondence of the predicted DWT results based on phytolith-environment calibration data with observed data reflects that the phytolith-based WA-PLS is a reliable effective calibration method for the quantitative DWT reconstruction of ombrotrophic (rain-fed) subalpine peatland.