Morphological differentiation of Betula (birch) pollen in northwest North America and its palaeoecological application

Lake sediments from arcto-boreal regions commonly contain abundant Betula pollen. However, palaeoenvironmental interpretations of Betula pollen are often ambiguous because of the lack of reliable morphological features to distinguish among ecologically distinct Betula species in western North America. We measured the grain diameters and pore depths of pollen from three tree-birch species (B. papyrifera, B. kenaica and B. neoalaskana) and two shrub-birch species (B. glandulosa and B. nana), and calculated the ratio of grain diameter to pore depth (D/P ratio). No statistical difference exists in all three parameters between the shrub-birch species or between two of the tree-birch species (B. kenaica and B. papyrifera), and B. neoalaskana is intermediate between the shrub-birch and the other two tree-birch species. However, mean pore depth is significantly larger for the tree species than for the shrub species. In contrast, mean grain diameter cannot distinguish tree and shrub species. Mean D/P ratio separates tree and shrub species less clearly than pore depth, but this ratio can be used for verification. The threshold for distinguishing pollen of tree versus shrub birch lies at 2.55 μm and 8.30 for pore depth and D/P ratio, respectively. We'applied these thresholds to the analysis of Betula pollen in an Alaskan lake-sediment core spanning the past 800 years. Results show that shrub birch increased markedly at the expense of tree birch during the‘Little Ice Age’; this patten is not discernible in the profile of total birch pollen.

Minimum count sums for charcoalconcentration estimates in pollen slides: accuracy and potential errors

Charcoal particles in pollen slides are often abundant, and thus analysts are faced with the problem of setting the minimum counting sum as small as possible in order to save time. We analysed the reliability of charcoal-concentration estimates based on different counting sums, using simulated low-to high-count samples. Bootstrap simulations indicate that the variability of inferred charcoal concentrations increases progressively with decreasing sums. Below 200 items (i.e., the sum of charcoal particles and exotic marker grains), reconstructed fire incidence is either too high or too low. Statistical comparisons show that the means of bootstrap simulations stabilize after 200 counts. Moreover, a count of 200-300 items is sufficient to produce a charcoal-concentration estimate with less than+5% error if compared with high-count samples of 1000 items for charcoal/marker grain ratios 0.1-0.91. If, however, this ratio is extremely high or low (> 0.91 or < 0.1) and if such samples are frequent, we suggest that marker grains are reduced or added prior to new sample processing.