Representational Bias in Phytoliths from Modern Soils of Central North America: Implications for Paleovegetation Reconstructions
Abstract Understanding localized patterns and community compositions of vegetation in an environment is critical to the reconstruction of climatic and ecological conditions across all spatiotemporal scales. One of the most accurate and useful ways to characterize vegetation, and therefore to describe the climatic and ecological conditions of a location, is through the plant fossil record. Phytoliths (plant silica microfossils) are often preserved in the absence of other paleobotanical data and are becoming more widely used for deep-time vegetation reconstructions. Significant work has been done to standardize the analytical methodology of phytolith extraction, statistical analysis, and interpretation, but more detailed investigations are needed to understand how well a given soil assemblage represents the actual aboveground plant biomass for a given ecosystem. We present results from paired soil phytolith assemblages and local vegetation assemblages across the central United States, including temperate forest, grassland, and rangeland/scrubland ecosystems. Phytolith assemblages obtained via extractions from soil A-horizons were compared to percent cover of species and plant biomass estimates obtained via in situ field observations and aerial estimates of tree cover to analyze differences in the relative abundance of forest/woody vegetation vs. grasses. Soil phytolith assemblages from all sites average a 29% bias toward the grass morphotypes as compared to actual aboveground biomass observations, and comparisons to percent cover yielded broadly comparable bias figures. Percent bias estimates do not show significant correlations to most environmental factors (temperature, precipitation, local elevation), however, an extremely strong correlation (p