Assessment and correction of representational bias in phytoliths from modern soil in the Dongting Lake Basin, China

Abstract

Understanding how well topsoil phytoliths represent their aboveground plant communities, and then correcting for any representational bias, is the basis for the accurate phytolith-based reconstruction of past vegetation. We evaluated the representational bias in topsoil phytoliths at 39 sampling sites in forest, shrub, and herb communities in the Dongting Lake Basin, China. We compared the types, concentrations, and percentages of topsoil phytoliths and corresponding plant community phytoliths within the same plant community and quantified the relationships. We observed significant representational biases. Combined with the representation indices of phytoliths, we quantitatively defined the vegetation representativeness of different phytolith types in the topsoil samples. We defined four categories of representation: Associated types, Over-represented types, Under-represented types, and “Special” types. We observed differences in the vegetation representativeness of different topsoil phytolith types, and the same phytolith type also showed significant differences in vegetation representativeness between different plant communities. Additionally, using the preservation index (R-value), we corrected the representational bias of topsoil phytoliths between the different plant communities. After validation, we found that the corrected topsoil phytoliths more accurately represented quantitative changes in the aboveground plant communities. Therefore, the preservation index (R value) is an effective means of correcting the representational bias of topsoil phytoliths, and it can provide the basis for more accurate phytolith-based reconstructions of past vegetation.