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    Eine neue Generation von Ertragstafeln für die Baumarten Eiche, Buche, Fichte, Douglasie und Kiefer in Nordwestdeutschland

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    Author(s)
    Albert, Matthias
    Nagel, Jürgen
    Schmidt, Matthias
    Nagel, Ralf-Volker
    Spellmann, Hermann
    Collection
    AG Universitätsverlage
    Language
    German
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    Abstract
    The new, fourth generation of yield tables for the tree species oak, beech, spruce, Douglas fir and pine replaces the yield tables for the previously mentioned tree species in Schober's yield table collection from 1975, while retaining their formal structure. A fundamental revision of the content of these classic yield tables was urgently required in order to adequately take into account the effects of greatly changed environmental conditions and deviating silvicultural treatment and utilization concepts on the growth and structure of the stands. This volume provides an introductory overview of the data basis, the assumed silvicultural treatment concept, scoring and application requirements. One section provides information on the application of the yield tables in stands not treated in accordance with the yield tables. The tabular presentation of the yield tables as well as supplementary tables and graphs form the main part of this volume. The article is aimed at users of yield tables from forestry practice and science. Translated with DeepL.com (free version)
    URI
    https://library.oapen.org/handle/20.500.12657/94237
    Keywords
    yield charts; forest science; Northwest Germany
    DOI
    10.17875/gup2024-2636
    ISBN
    978-3-86395-640-0
    Publisher
    Universitätsverlag Göttingen
    Publication date and place
    2024
    Classification
    Technology, engineering, agriculture
    Technology, engineering, agriculture
    Rights
    https://creativecommons.org/licenses/by-sa/4.0/deed.de
    • Harvested from Göttingen

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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