The High–Low Arctic boundary: How is it determined and where is it located?

Geobotanical subdivision of landcover is a baseline for many studies. The High–Low Arctic boundary is considered to be of fundamental natural importance. The wide application of different delimitation schemes in various ecological studies and climatic scenarios raises the following questions: (i) What are the common criteria to define the High and Low Arctic? (ii) Could human impact significantly change the distribution of the delimitation criteria? (iii) Is the widely accepted temperature criterion still relevant given ongoing climate change? and (iv) Could we locate the High–Low Arctic boundary by mapping these criteria derived from modern open remote sensing and climatic data? Researchers rely on common criteria for geobotanical delimitation of the Arctic. Unified circumpolar criteria are based on the structure of vegetation cover and climate, while regional specifics are reflected in the floral composition. However, the published delimitation schemes vary greatly. The disagreement in the location of geobotanical boundaries across the studies manifests in poorly comparable results. While maintaining the common principles of geobotanical subdivision, we derived the boundary between the High and Low Arctic using the most up‐to‐date field data and modern techniques: species distribution modeling, radar, thermal and optical satellite imagery processing, and climatic data analysis. The position of the High–Low Arctic boundary in Western Siberia was clarified and mapped. The new boundary is located 50–100 km further north compared to all the previously presented ones. Long‐term anthropogenic press contributes to a change in the vegetation structure but does not noticeably affect key species ranges. A previously specified climatic criterion for the High–Low Arctic boundary accepted in scientific literature has not coincided with the boundary in Western Siberia for over 70 years. The High–Low Arctic boundary is distinctly reflected in biodiversity distribution. The presented approach is appropriate for accurate mapping of the High–Low Arctic boundary in the circumpolar extent

SiDroForest: a comprehensive forest inventory of Siberian boreal forest investigations including drone-based point clouds, individually labeled trees, synthetically generated tree crowns, and Sentinel-2 labeled image patches

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.</p

Strong shrub expansion in tundra-taiga, tree infilling in taiga and stable tundra in central Chukotka (north-eastern Siberia) between 2000 and 2017

Vegetation is responding to climate change, which is especially prominent in the Arctic. Vegetation change is manifest in different ways and varies regionally, depending on the characteristics of the investigated area. Although vegetation in some Arctic areas has been thoroughly investigated, central Chukotka (NE Siberia) with its highly diverse vegetation, mountainous landscape and deciduous needle-leaf treeline remains poorly explored, despite showing strong greening in remote-sensing products. Here we quantify recent vegetation compositional changes in central Chukotka over 15 years between 2000/2001/2002 and 2016/2017. We numerically related field-derived information on foliage projective cover (percentage cover) of different plant taxa from 52 vegetation plots to remote-sensing derived (Landsat) spectral indices (Normalised Difference Vegetation Index (NDVI), Normalised Difference Water Index (NDWI) and Normalised Difference Snow Index (NDSI)) using constrained ordination. Clustering of ordination scores resulted in four land-cover classes: (1) larch closed-canopy forest, (2) forest tundra and shrub tundra, (3) graminoid tundra and (4) prostrate herb tundra and barren areas. We produced land-cover maps for early (2000, 2001 or 2002) and recent (2016 or 2017) time-slices for four focus regions along the tundra-taiga vegetation gradient. Transition from graminoid tundra to forest tundra and shrub tundra is interpreted as shrubification and amounts to 20% area increase in the tundra-taiga zone and 40% area increase in the northern taiga. Major contributors of shrubification are alder, dwarf birch and some species of the heather family. Land-cover change from the forest tundra and shrub tundra class to the larch closed-canopy forest class is interpreted as tree infilling and is notable in the northern taiga. We find almost no land-cover changes in the present treeless tundra

Foliage projective cover of 57 vegetation sites of central Chukotka from 2016

Field investigations were performed in four areas forming a vegetation gradient from a treeless mountainous tundra (16-KP-04; Lake Rauchuagytgyn area) via tundra-taiga transition zone (16-KP-01, Lake Ilirney area; 16-KP-03, Nutenvut lakes area) to a northern taiga (16-KP-02, Bolshoy Anyuy river area). In total, 57 sites were investigated. The sites were chosen to cover a large NDVI gradient (0.3 - 0.8). The sites differ in elevation (100-900 m a. s. l.), slope angle (0-54°) and aspect (overall south aspects prevail). For every field site a detailed description of the vegetation was made. Foliage projective cover for all major taxa estimated as percent and averaged from five representative 2 x 2 m plots within circular sites with a diameter of 30 m: one at the centre and four 7.5 m away in each of the cardinal directions (south, north, west, east). Presence of deadwood and open soil were also recorded. All data was collected by scientists from Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research and University of Potsdam, Germany, The Institute for Biological problems of the Cryolithozone, Russian Academy of Sciences, Siberian branch, and The Institute of Natural Sciences, North-Eastern Federal University of Yakutsk, Yakutsk, Russia

Herbaceous layer projective vegetation cover at 56 sites in Central and Eastern Yakutia, in Summer 2021 (RU-Land_2021_Yakutia)

Herbaceous layer projective vegetation cover is given in percent for each taxon and multiple quadrats at 57 sites with different vegetation types. The cover of different vegetation types at the sites is given in percent as well. The vegetation surveys were carried out in four different study areas in the Sakha Republic, Russia: in the mountainous region of the Verkhoyansk Range within the Oymyakonsky and Tomponsky District (Event EN21-201 - EN21-219), and in three lowland regions of Central Yakutia within the Churapchinsky, Tattinsky and the Megino-Kangalassky District (Event EN21220 - EN21264). The study area is located within the boreal forest biome that is underlain by permafrost soils. The aim was to record the projective ground vegetation in different boreal forest types studied during the RU-Land_2021_Yakutia summer field campaign in August and September 2021. The ground vegetation projective cover in percent was assessed within a circular forest plot of 15m radius. Depending on the heterogeneity of the forest plot, multiple vegetation types (VA, VB, or VC) were surveyed separately. The assignment of a vegetation type is always unique to a site. Up to four quadrats of 2x2 m were surveyed per vegetation type and projective cover in percent recorded separately for herbaceous and moss layers. All vegetation smaller than 40 cm was recorded. Additionally, ground vegetation projective cover was surveyed in 4 rings of 50 cm width around the center of the circular forest plot. Photos of quadrats were taken at the time of survey. In total, 491 quadrats at 57 forest plots were investigated. All data were collected by scientists form the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) Germany, the University of Potsdam Germany, and the North-Easter Federal University of Yakutsk (NEFU) Russia

Aggregated herbaceous layer projective vegetation cover at 56 sites in Central and Eastern Yakutia, in Summer 2021 (RU-Land_2021_Yakutia)

Aggregated herbaceous layer projective vegetation cover is given in percent for each taxon for 57 sites. The cover of different vegetation types at the sites is given in percent as well. The vegetation surveys were carried out in four different study areas in the Sakha Republic, Russia: in the mountainous region of the Verkhoyansk Range within the Oymyakonsky and Tomponsky District (Event EN21-201 - EN21-219), and in three lowland regions of Central Yakutia within the Churapchinsky, Tattinsky and the Megino-Kangalassky District (Event EN21220 - EN21264). The study area is located within the boreal forest biome that is underlain by permafrost soils. The aim was to record the projective ground vegetation in different boreal forest types studied during the RU-Land_2021_Yakutia summer field campaign in August and September 2021. The ground vegetation projective cover in percent was assessed within a circular forest plot of 15m radius. Depending on the heterogeneity of the forest plot, multiple vegetation types (VA, VB, or VC) were surveyed separately. The assignment of a vegetation type is always unique to a site. Up to four quadrats of 2x2 m were surveyed per vegetation type and projective cover in percent recorded separately for herbaceous and moss layers. All vegetation smaller than 40 cm was recorded. Additionally, ground vegetation projective cover was surveyed in 4 rings of 50 cm width around the center of the circular forest plot. Photos of quadrats were taken at the time of survey. Average ground vegetation cover per plot was calculated by using an average weighted by vegetation types for each site. The ring survey data was not included in the plot average. In total, 491 quadrats at 57 forest plots were investigated. All data were collected by scientists form the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) Germany, the University of Potsdam Germany, and the North-Easter Federal University of Yakutsk (NEFU) Russia

Moss layer projective vegetation cover at 56 sites in Central and Eastern Yakutia, in Summer 2021 (RU-Land_2021_Yakutia)

Moss layer projective vegetation cover is given in percent for each taxon and multiple quadrats at 57 sites with different vegetation types. The cover of different vegetation types at the sites is given in percent as well. The vegetation surveys were carried out in four different study areas in the Sakha Republic, Russia: in the mountainous region of the Verkhoyansk Range within the Oymyakonsky and Tomponsky District (Event EN21-201 - EN21-219), and in three lowland regions of Central Yakutia within the Churapchinsky, Tattinsky and the Megino-Kangalassky District (Event EN21220 - EN21264). The study area is located within the boreal forest biome that is underlain by permafrost soils. The aim was to record the projective ground vegetation in different boreal forest types studied during the RU-Land_2021_Yakutia summer field campaign in August and September 2021. The ground vegetation projective cover in percent was assessed within a circular forest plot of 15m radius. Depending on the heterogeneity of the forest plot, multiple vegetation types (VA, VB, or VC) were surveyed separately. The assignment of a vegetation type is always unique to a site. Up to four quadrats of 2x2 m were surveyed per vegetation type and projective cover in percent recorded separately for herbaceous and moss layers. All vegetation smaller than 40 cm was recorded. Additionally, ground vegetation projective cover was surveyed in 4 rings of 50 cm width around the center of the circular forest plot. Photos of quadrats were taken at the time of survey. In total, 491 quadrats at 57 forest plots were investigated. All data were collected by scientists form the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) Germany, the University of Potsdam Germany, and the North-Easter Federal University of Yakutsk (NEFU) Russia

Foliage projective cover of 40 vegetation sites of central Chukotka from 2018

Field investigations were performed in four areas: a treeless mountainous tundra (16-KP-04; Lake Rauchuagytgyn area), tundra-taiga transition zone (16-KP-01, Lake Ilirney area) and a northern taiga (18-BIL-01, 18-BIL-02). In total, 40 sites were investigated. The sites were placed to cover different vegetation communities that characterise central Chukotka. Fifteen-metre radius sampling plots (sites) were demarcated in the most homogeneous locations. Heterogeneity was accommodated by roughly assorting vegetation into two to three vegetation types per sampling plot. Within each area of roughly estimated vegetation types we selected three representative 2 x 2 m subplots for representative ground-layer foliage projective cover assessment. Projective cover of tall shrubs and trees was estimated on 15-m radius circular plots directly. All data was collected by scientists from Alfred Wegener Institute (AWI), Helmholtz Centre for Polar and Marine Research and University of Potsdam, Germany, The Institute for Biological problems of the Cryolithozone, Russian Academy of Sciences, Siberian branch, and The Institute of Natural Sciences, North-Eastern Federal University of Yakutsk, Yakutsk, Russia

Aggregated ground vegetation above-ground biomass at 56 sites in Central and Eastern Yakutia, in Summer 2021 (RU-Land_2021_Yakutia)

Aggregated above-ground biomass for ground vegetation is given in g per m² for each taxon at 56 sites. Total ground vegetation biomass in g per m² and in kg for the entire site. The vegetation surveys were carried out in four different study areas in the Sakha Republic, Russia: in the mountainous region of the Verkhoyansk Range within the Oymyakonsky and Tomponsky District (Event EN21-201 - EN21-219), and in three lowland regions of Central Yakutia within the Churapchinsky, Tattinsky and the Megino-Kangalassky District (Event EN21220 - EN21264). The study area is located within the boreal forest biome that is underlain by permafrost soils. The aim was to record the projective ground vegetation in different boreal forest types studied during the RU-Land_2021_Yakutia summer field campaign in August and September 2021. The ground vegetation above-ground biomass was measured for different vegetation types within a circular forest plot of 15m radius. Depending on the heterogeneity of the forest plot, multiple vegetation types (VA, VB, or VC) were chosen for the survey. One quadrat of 50x50 cm was harvested per vegetation type. All vegetation smaller than 40 cm was harvested. Biomass harvest was conducted just outside the circular forest plots, which will serve as long-term monitoring sites. Fresh weights were recorded in field and sub sampling conducted if necessary. Samples were later dried at 60°C until a constant weight was achieved and dry weight was recorded. Average ground vegetation biomass per plot was calculated by using a weighted average for each vegetation type. In total, 79 quadrats at 56 forest plots were harvested. All data were collected by scientists form the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) Germany, the University of Potsdam Germany, and the North-Easter Federal University of Yakutsk (NEFU) Russia

Aggregated moss layer projective vegetation cover at 56 sites in Central and Eastern Yakutia, in Summer 2021 (RU-Land_2021_Yakutia)

Aggregated moss layer projective vegetation cover is given in percent for each taxon for 57 sites. The cover of different vegetation types at the sites is given in percent as well. The vegetation surveys were carried out in four different study areas in the Sakha Republic, Russia: in the mountainous region of the Verkhoyansk Range within the Oymyakonsky and Tomponsky District (Event EN21-201 - EN21-219), and in three lowland regions of Central Yakutia within the Churapchinsky, Tattinsky and the Megino-Kangalassky District (Event EN21220 - EN21264). The study area is located within the boreal forest biome that is underlain by permafrost soils. The aim was to record the projective ground vegetation in different boreal forest types studied during the RU-Land_2021_Yakutia summer field campaign in August and September 2021. The ground vegetation projective cover in percent was assessed within a circular forest plot of 15m radius. Depending on the heterogeneity of the forest plot, multiple vegetation types (VA, VB, or VC) were surveyed separately. The assignment of a vegetation type is always unique to a site. Up to four quadrats of 2x2 m were surveyed per vegetation type and projective cover in percent recorded separately for herbaceous and moss layers. All vegetation smaller than 40 cm was recorded. Additionally, ground vegetation projective cover was surveyed in 4 rings of 50 cm width around the center of the circular forest plot. Photos of quadrats were taken at the time of survey. Average ground vegetation cover per plot was calculated by using an average weighted by vegetation types for each site. The ring survey data was not included in the plot average. In total, 491 quadrats at 57 forest plots were investigated. All data were collected by scientists form the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) Germany, the University of Potsdam Germany, and the North-Easter Federal University of Yakutsk (NEFU) Russia