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  1. Article: The High-Low Arctic boundary: How is it determined and where is it located?

    Ermokhina, Ksenia A / Terskaia, Anna I / Ivleva, Tatiana Yu / Dudov, Sergey V / Zemlianskii, Vitalii А / Telyatnikov, Michael Yu / Khitun, Olga V / Troeva, Elena I / Koroleva, Natalia E / Abdulmanova, Svetlana Yu

    Ecology and evolution

    2023  Volume 13, Issue 10, Page(s) e10545

    Abstract: 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 ... ...

    Abstract 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.
    Language English
    Publishing date 2023-09-28
    Publishing country England
    Document type Journal Article
    ZDB-ID 2635675-2
    ISSN 2045-7758
    ISSN 2045-7758
    DOI 10.1002/ece3.10545
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Book ; Online: SiDroForest

    Geffen, Femke / Heim, Birgit / Brieger, Frederic / Geng, Rongwei / Shevtsova, Iuliia A. / Schulte, Luise / Stuenzi, Simone M. / Bernhardt, Nadine / Troeva, Elena I. / Pestryakova, Luidmila A. / Zakharov, Evgenii S. / Pflug, Bringfried / Herzschuh, Ulrike / Kruse, Stefan

    eISSN: 1866-3516

    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

    2022  

    Abstract: 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 ... ...

    Abstract 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 ...
    Subject code 333
    Language English
    Publishing date 2022-11-11
    Publishing country de
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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