Increasing taxonomic resolution in pollen identification: Sample size, spatial sampling bias and implications for palaeoecology

Abstract

Many studies proposing methods for differentiating fossil pollen of different species derive diagnostic identification criteria from small sample sizes and/or modern pollen collected from limited areas within species ranges. Here, we evaluate the importance of sample size and population representation in pollen identification methods, in an examination of morphological measurements on over 21,000 pollen from three alder species (Alnus viridis subsp. sinuata, Alnus incana subsp. tenuifolia and Alnus rubra) in western North America. We assess the sensitivity of morphometric analyses and multi-trait classification models of Alnus pollen to changes in sample size and spatial sampling breadth, by randomly reducing our large dataset in size and by splitting the dataset into regional subsets. Sensitivity analyses demonstrate that using small sample sizes to identify diagnostic morphological traits for pollen identification can result in misleading conclusions about interspecific morphological differences in pollen types and ultimately in misidentification of pollen. Pollen identification methods based on reference samples collected from limited regions are prone to bias, due to regional differences in modern pollen morphology. Our study reveals the importance of using large sample sizes from across species ranges when attempting to determine the diagnostic morphological features for fossil pollen identification. We recommend basing identification criteria on pollen from as many individual plants per species as possible, as opposed to numerous pollen grains from only a small number of individuals, because at least in Alnus, individual plants produce morphologically similar pollen.