The Arctic treeline ecotone is characterized by a steep vegetation gradient from arctic tundra to northerntaiga forests, which is thought to influence the water chemistry of thermokarst lakes in this region.Environmentally sensitive diatoms respond to such ecological changes in terms of variation in diatomdiversity and richness, which so far has only been documented by microscopic surveys. We applied nextgenerationsequencing to analyse the diatom composition of lake sediment DNA extracted from 32 lakesacross the treeline in the Khatanga region, Siberia, using a short fragment of the rbcL chloroplast gene as agenetic barcode. We compared diatom richness and diversity obtained from the genetic approach withdiatom counts from traditional microscopic analysis. Both datasets were employed to investigate diversityand relationships with environmental variables, using ordination methods. After effective filtering of theraw data, the two methods gave similar results for diatom richness and composition at the genus level(DNA 12 taxa; morphology 19 taxa), even though there was a much higher absolute number of sequencesobtained per genetic sample (median 50,278), compared with microscopic counts (median 426). Dissolvedorganic carbon explained the highest percentage of variance in both datasets (14.2 % DNA; 18.7 %morphology), reflecting the compositional turnover of diatom assemblages along the tundra-taigatransition. Differences between the two approaches are mostly a consequence of the filtering process ofgenetic data and limitations of genetic references in the database, which restricted the determination ofgenetically identified sequence types to the genus level. The morphological approach, however, allowedidentifications mostly to species level, which permits better ecological interpretation of the diatom data.Nevertheless, because of a rapidly increasing reference database, the genetic approach with sediment DNAwill, in the future, enable reliable investigations of diatom composition from lake sediments that will havepotential applications in both paleoecology and environmental monitoring.

Excel file contains genetically identified sequence types, their abundances, their similarity to Genbank references, their taxonomic identity and their DNA sequence.

Supplement to: Dulias, Katharina; Stoof-Leichsenring, Kathleen Rosmarie; Pestryakova, Luidmila A; Herzschuh, Ulrike (2016): Sedimentary DNA versus morphology in the analysis of diatom-environment relationships. Journal of Paleolimnology, 16 pp