Abstract
BACKGROUND: Plant diversity in the Arctic and at high altitudes strongly depends on and rebounds to climatic and environmental variability and is nowadays tremendously impacted by recent climate warming. Therefore, past changes in plant diversity in the high Arctic and high-altitude regions are used to infer climatic and environmental changes through time and allow future predictions. Sedimentary DNA (sedDNA) is an established proxy for the detection of local plant diversity in lake sediments, but still relationships between environmental conditions and preservation of the plant sedDNA proxy are far from being fully understood. Studying modern relationships between environmental conditions and plant sedDNA will improve our understanding under which conditions sedDNA is well-preserved helping to a.) evaluate suitable localities for sedDNA approaches, b.) provide analogues for preservation conditions and c.) conduct reconstruction of plant diversity and climate change. This study investigates modern plant diversity applying a plant-specific metabarcoding approach on sedimentary DNA of surface sediment samples from 262 lake localities covering a large geographical, climatic and ecological gradient. Latitude ranges between 25°N and 73°N and longitude between 81°E and 161°E, including lowland lakes and elevated lakes up to 5168 m a.s.l. Further, our sampling localities cover a climatic gradient ranging in mean annual temperature between -15°C and +18°C and in mean annual precipitation between 36- and 935 mm. The localities in Siberia span over a large vegetational gradient including tundra, open woodland and boreal forest. Lake localities in China include alpine meadow, shrub, forest and steppe and also cultivated areas. The assessment of plant diversity in the underlying dataset was conducted by a specific plant metabarcoding approach. NEW INFORMATION: We provide a large dataset of genetic plant diversity retrieved from surface sedimentary DNA from lakes in Siberia and China spanning over a large environmental gradient. Our dataset encompasses sedDNA sequence data of 259 surface lake sediments and three soil samples originating from Siberian and Chinese lakes. We used the established chloroplastidal P6 loop trnL marker for plant diversity assessment. The merged, filtered and assigned dataset includes 15,692,944 read counts resulting in 623 unique plant DNA sequence types which have a 100% match to either the EMBL or to the specific Arctic plant reference database. The underlying dataset includes a taxonomic list of identified plants and results from PCR replicates, as well as extraction blanks (BLANKs) and PCR negative controls (NTCs), which were run along with the investigated lake samples. This collection of plant metabarcoding data from modern lake sediments is still ongoing and additional data will be released in the future.