Modern pollen from small hollows reflects Athrotaxis cupressoides density across a wildfire gradient in subalpine forests of the Central Plateau, Tasmania, Australia

Pollen assemblages from 50 small hollows were used to resolve fire-caused vegetation patterns in a ~2-km2 subalpine landscape on the Central Plateau of Tasmania, Australia. Sites were characterized by varying abundance of the dominant tree species, Athrotaxis cupressoides, reflecting mortality from a wildfire that occurred 53 years prior to sampling. Sites were classified a priori based on fire-related Athrotaxis mortality as burned (100% standing dead), unburned (<5% standing dead), and mixed (intermediate proportions). Non-parametric analysis of variance and discriminant analysis were used to quantify the variability in key pollen taxa and pollen ratios among burn classifications. The ratio of Athrotaxis to Poaceae pollen was the clearest metric distinguishing among burn classifications. When discriminant analysis was informed with data from the eight most dominant pollen data, samples were classified with high accuracy (0.96–0.98). Macroscopic charcoal concentrations varied widely among sites, but median values were consistent with inferred fire patterns, increasing in abundance from unburned to burned sites. The results support the use of small hollows to resolve fine-scale vegetation patterns (e.g. within 100 m of a site). The discriminant analysis function was also applied to five late-Holocene pollen samples from the study area, to test the potential of these methods to classify samples with unknown group assignments. The posterior probability of assigned group membership ranged from 0.85 to 0.99, demonstrating the similarity of the fossil pollen to the calibration dataset. Our calibration dataset provides a means to classify fossil samples from the region in terms of Athrotaxis cover and fire-caused mortality. This approach could be applied to other regions to quantify disturbance-related vegetation patterns or spatial heterogeneity over Holocene timescales.