Description: Sea ice is a key factor for the functioning and services provided by polar marine ecosystems. However, ecosystem responses to sea-ice loss are largely unknown because time-series data are lacking. Here, we use shotgun metagenomics of marine sedimentary ancient DNA off Kamchatka (Western Bering Sea) covering the last ~20,000 years. We traced shifts from a sea ice-adapted late-glacial ecosystem, characterized by diatoms, copepods, and codfish to an ice-free Holocene characterized by cyanobacteria, salmon, and herring. By providing information about marine ecosystem dynamics across a broad taxonomic spectrum, our data show that ancient DNA will be an important new tool in identifying long-term ecosystem responses to climate transitions for improvements of ocean and cryosphere risk assessments. We conclude that continuing sea-ice decline on the northern Bering Sea shelf might impact on carbon export and disrupt benthic food supply and could allow for a northward expansion of salmon and Pacific herring.

Description: The SiDroForest (Siberian drone-mapped forest inventory) data collection is an attempt to remedy the scarcity of forest structure data in the circumboreal region by providing adjusted and labeled tree-level and vegetation plot-level data for machine learning and upscaling purposes. We present datasets of vegetation composition and tree and plot level forest structure for two important vegetation transition zones in Siberia, Russia; the summergreen–evergreen transition zone in Central Yakutia and the tundra–taiga transition zone in Chukotka (NE Siberia). The SiDroForest data collection consists of four datasets that contain different complementary data types that together support in-depth analyses from different perspectives of Siberian Forest plot data for multi-purpose applications. i. Dataset 1 provides unmanned aerial vehicle (UAV)-borne data products covering the vegetation plots surveyed during fieldwork (Kruse et al., 2021, https://doi.org/10.1594/PANGAEA.933263). The dataset includes structure-from-motion (SfM) point clouds and red–green–blue (RGB) and red–green–near-infrared (RGN) orthomosaics. From the orthomosaics, point-cloud products were created such as the digital elevation model (DEM), canopy height model (CHM), digital surface model (DSM) and the digital terrain model (DTM). The point-cloud products provide information on the three-dimensional (3D) structure of the forest at each plot. ii. Dataset 2 contains spatial data in the form of point and polygon shapefiles of 872 individually labeled trees and shrubs that were recorded during fieldwork at the same vegetation plots (van Geffen et al., 2021c, https://doi.org/10.1594/PANGAEA.932821). The dataset contains information on tree height, crown diameter, and species type. These tree and shrub individually labeled point and polygon shapefiles were generated on top of the RGB UVA orthoimages. The individual tree information collected during the expedition such as tree height, crown diameter, and vitality are provided in table format. This dataset can be used to link individual information on trees to the location of the specific tree in the SfM point clouds, providing for example, opportunity to validate the extracted tree height from the first dataset. The dataset provides unique insights into the current state of individual trees and shrubs and allows for monitoring the effects of climate change on these individuals in the future. iii. Dataset 3 contains a synthesis of 10 000 generated images and masks that have the tree crowns of two species of larch (Larix gmelinii and Larix cajanderi) automatically extracted from the RGB UAV images in the common objects in context (COCO) format (van Geffen et al., 2021a, https://doi.org/10.1594/PANGAEA.932795). As machine-learning algorithms need a large dataset to train on, the synthetic dataset was specifically created to be used for machine-learning algorithms to detect Siberian larch species. iv. Dataset 4 contains Sentinel-2 (S-2) Level-2 bottom-of-atmosphere processed labeled image patches with seasonal information and annotated vegetation categories covering the vegetation plots (van Geffen et al., 2021b, https://doi.org/10.1594/PANGAEA.933268). The dataset is created with the aim of providing a small ready-to-use validation and training dataset to be used in various vegetation-related machine-learning tasks. It enhances the data collection as it allows classification of a larger area with the provided vegetation classes. The SiDroForest data collection serves a variety of user communities. The detailed vegetation cover and structure information in the first two datasets are of use for ecological applications, on one hand for summergreen and evergreen needle-leaf forests and also for tundra–taiga ecotones. Datasets 1 and 2 further support the generation and validation of land cover remote-sensing products in radar and optical remote sensing. In addition to providing information on forest structure and vegetation composition of the vegetation plots, the third and fourth datasets are prepared as training and validation data for machine-learning purposes. For example, the synthetic tree-crown dataset is generated from the raw UAV images and optimized to be used in neural networks. Furthermore, the fourth SiDroForest dataset contains S-2 labeled image patches processed to a high standard that provide training data on vegetation class categories for machine-learning classification with JavaScript Object Notation (JSON) labels provided. The SiDroForest data collection adds unique insights into remote hard-to-reach circumboreal forest regions.

Description: Sea ice is a key factor for the functioning and services provided by polar marine ecosystems. However, ecosystem responses to sea-ice loss are largely unknown because time-series data are lacking. Here, we use shotgun metagenomics of marine sedimentary ancient DNA off Kamchatka (Western Bering Sea) covering the last ~20,000 years. We traced shifts from a sea ice-adapted late-glacial ecosystem, characterized by diatoms, copepods, and codfish to an ice-free Holocene characterized by cyanobacteria, salmon, and herring. By providing information about marine ecosystem dynamics across a broad taxonomic spectrum, our data show that ancient DNA will be an important new tool in identifying long-term ecosystem responses to climate transitions for improvements of ocean and cryosphere risk assessments. We conclude that continuing sea-ice decline on the northern Bering Sea shelf might impact on carbon export and disrupt benthic food supply and could allow for a northward expansion of salmon and Pacific herring.

Description: Upscaling plant biomass distribution and dynamics is essential for estimating carbon stocks and carbon balance. In this respect, the Russian Far East is among the least investigated sub-Arctic regions despite its known vegetation sensitivity to ongoing warming. We representatively harvested above-ground biomass (AGB; separated by dominant taxa) at 40 sampling plots in central Chukotka. We used ordination to relate field-based taxa projective cover and Landsat-derived vegetation indices. A general additive model was used to link the ordination scores to AGB. We then mapped AGB for paired Landsat-derived time slices (i.e. 2000/2001/2002 and 2016/2017), in four study regions covering a wide vegetation gradient from closed-canopy larch forests to barren alpine tundra. We provide AGB estimates and changes in AGB that were previously lacking for central Chukotka at a high spatial resolution and a detailed description of taxonomical contributions. Generally, AGB in the study region ranges from 0 to 16 kg m−2, with Cajander larch providing the highest contribution. Comparison of changes in AGB within the investigated period shows that the greatest changes (up to 1.25 kg m−2 yr−1) occurred in the northern taiga and in areas where land cover changed to larch closed-canopy forest. As well as the notable changes, increases in AGB also occur within the land-cover classes. Our estimations indicate a general increase in total AGB throughout the investigated tundra–taiga and northern taiga, whereas the tundra showed no evidence of change in AGB.

Description: The study of environmental ancient DNA provides us with the unique opportunity to link environmental with ecosystem change over a millennial timescale. Paleorecords such as lake sediments contain genetic pools of past living organisms that are a valuable source of information to reconstruct how ecosystems were and how they changed in response to climate in the past. Here, we report on paleometagenomics of a sedimentary record in northern Siberia covering the past 6700 years. We integrated taxonomic with functional gene analysis, which enabled to shed light not only on community compositions but also on eco-physiological adaptations and ecosystem functioning. We reconstructed the presence of an open boreal forest 6700 years ago that over time was gradually replaced by tundra. This vegetation change had major consequences on the environmental microbiome, primarily enriching bacterial and archaeal ammonia oxidizers (e.g., Nitrospira, Nitrosopumilus, and Ca. Nitrosocosmicus) in the tundra ecosystem. We identified a core microbiome conserved through time and largely consisting of heterotrophic bacteria of the Bacteroidetes phylum (e.g., Mucilaginibacter) harboring numerous functional genes for degradation of plant-biomass and abiotic and biotic stress resistance. Archaea were also a key functional guild, involved in nitrogen and carbon cycling, not only methanogenesis but possibly also degradation of plant material via enzymes such as cellulases and amylases. Overall, the paleo-perspective offered by our study can have a profound impact on modern climate change biology, by helping to explain and predict the ecological interplay among multiple ecosystem levels based on past experiences.

Description: Climate change is expected to cause major shifts in boreal forests which are in vast areas of Siberia dominated by two species of the deciduous needle tree larch (Larix). The species differ markedly in their ecosystem functions, thus shifts in their respective ranges are of global relevance. However, drivers of species distribution are not well understood, in part because paleoecological data at species level are lacking. This study tracks Larix species distribution in time and space using target enrichment on sedimentary ancient DNA extracts from eight lakes across Siberia. We discovered that Larix sibirica, presently dominating in western Siberia, likely migrated to its northern distribution area only in the Holocene at around 10,000 years before present (ka BP), and had a much wider eastern distribution around 33 ka BP. Samples dated to the Last Glacial Maximum (around 21 ka BP), consistently show genotypes of L. gmelinii. Our results suggest climate as a strong determinant of species distribution in Larix and provide temporal and spatial data for species projection in a changing climate.

Description: Climate warming alters plant composition and population dynamics of arctic ecosystems. In particular, an increase in relative abundance and cover of deciduous shrub species (shrubification) has been recorded. We inferred genetic variation of common shrub species (Alnus alnobetula, Betula nana, Salix sp.) through time. Chloroplast genomes were assembled from modern plants (n = 15) from the Siberian forest-tundra ecotone. Sedimentary ancient DNA (sedaDNA; n = 4) was retrieved from a lake on the southern Taymyr Peninsula and analyzed by metagenomics shotgun sequencing and a hybridization capture approach. For A. alnobetula, analyses of modern DNA showed low intraspecies genetic variability and a clear geographical structure in haplotype distribution. In contrast, B. nana showed high intraspecies genetic diversity and weak geographical structure. Analyses of sedaDNA revealed a decreasing relative abundance of Alnus since 5,400 cal yr BP, whereas Betula and Salix increased. A comparison between genetic variations identified in modern DNA and sedaDNA showed that Alnus variants were maintained over the last 6,700 years in the Taymyr region. In accordance with modern individuals, the variants retrieved from Betula and Salix sedaDNA showed higher genetic diversity. The success of the hybridization capture in retrieving diverged sequences demonstrates the high potential for future studies of plant biodiversity as well as specific genetic variation on ancient DNA from lake sediments. Overall, our results suggest that shrubification has species-specific trajectories. The low genetic diversity in A. alnobetula suggests a local population recruitment and growth response of the already present communities, whereas the higher genetic variability and lack of geographical structure in B. nana may indicate a recruitment from different populations due to more efficient seed dispersal, increasing the genetic connectivity over long distances.

Description: Siberian larch (Larix Mill.) forests dominate vast areas of northern Russia and contribute important ecosystem services to the world. It is important to understand the past dynamics of larches in order to predict their likely response to a changing climate in the future. Sedimentary ancient DNA extracted from lake sediment cores can serve as archives to study past vegetation. However, the traditional method of studying sedimentary ancient DNA—metabarcoding—focuses on small fragments, which cannot resolve Larix to species level nor allow a detailed study of population dynamics. Here, we use shotgun sequencing and hybridization capture with long-range PCR-generated baits covering the complete Larix chloroplast genome to study Larix populations from a sediment core reaching back to 6700 years from the Taymyr region in northern Siberia. In comparison with shotgun sequencing, hybridization capture results in an increase in taxonomically classified reads by several orders of magnitude and the recovery of complete chloroplast genomes of Larix. Variation in the chloroplast reads corroborates an invasion of Larix gmelinii into the range of Larix sibirica before 6700 years ago. Since then, both species have been present at the site, although larch populations have decreased with only a few trees remaining in what was once a forested area. This study demonstrates for the first time that hybridization capture applied directly to ancient DNA of plants extracted from lake sediments can provide genome-scale information and is a viable tool for studying past genomic changes in populations of single species, irrespective of a preservation as macrofossil.

Description: We applied metagenomic shotgun sequencing to a sedimentary ancient DNA (sedaDNA) record from the North Pacific (off Kamchatka) covering the last 20,000 years to trace temporal changes in ecosystem composition and food webs. This dataset contains count data before re-sampling for (1) phototrophic bacterial and eukaryotic pelagic families, (2) and eukaryotic benthic families, and (3) a list of families, their grouping into habitat (pelagic/benthic) and trophic status (phototrophic/heterotrophic), the taxonomic group to which the family belongs, the resampled number of read counts used for the formal analysis, links (edges) in the pelagic network, and Spearman correlation coefficients (ρ〉0.2) and Benjamini-Hochberg adjusted p-values between families and environmental variables (SSTs and IP25). Associated sequencing data, on which the taxonomic classifications are based on, can be found at the European Nucleotide Archive (ENA) under BIOPROJECT: PRJEB46821.

Description: This data set includes meteorological and soil temperature data obtained from two study areas in Eastern Siberia. The first study area is located at Lake Illirney in Chukotka, on a plateau above the treeline. The study site is located in a high-latitude boreal forest zone with alpine tundra above the treeline where the automatic weather station (AWS) is located. The annual average temperature is below zero degrees and results in continuous permafrost. One stand-alone Hobo logger for soil temperature measurements was installed in the soil pit next to the AWS. A second one at the subsite in a sparse larch-dominated forest with an average larch tree height of 12.5 m and 1 % cover of Salix shrubs with an average height of 0.9 m. The second study area is located in a typical boreal forest zone intermixed with some grassland for kettle grazing and shallow lakes. These boreal forest environments experience 6 to 8 months of freezing temperatures reaching extremes of -62 °C in winter and up to 35 °C between May and September. The annual average temperature is below zero degrees and results in continuous permafrost. The AWS is installed on a meadow surrounded by mixed boreal forest. The grassland is grazed by horses in summer and deforestation occurred more than 50 years ago. In addition, one stand-alone hobo logger was installed in the soil pit next to the AWS. In the forest, south of the AWS, a standalone Hobo logger was installed to record a vertical temperature profile. The forest is rather dense and mixed, with deciduous Larix gmelinii and evergreen Picea obovata. The average tree height is 12 m for larch and 5.5 m for spruce.