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    Chapter Plantation Forests: A Guarantee of Sustainable Management of Abandoned and Marginal Farmlands

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    Author(s)
    Bambe, Baiba
    Daugavietis, Uldis
    Lazdins, Andis
    Lazdina, Dagnija
    Makovskis, Kristaps
    Daugaviete, Mudrite
    Language
    English
    Show full item record
    Abstract
    The chapter summarises the research data on cultivating forest crops in abandoned and marginal farmlands (AL). The course of growth and productivity of different tree species in the local climatic conditions is clarified in a variety of agricultural soils. The research results show the most appropriate tree species for short-rotation or special end-use monoculture or mixed plantations, using Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.), silver birch (Betula pendula Roth.), pedunculate oak (Quercus robur L.), grey alder (Alnus incana (L.) Moench), alder (Alnus glutinosa (L.) Gaertn.), wild cherry (Cerasus avium (L.) Moench syn. Prunus avium), aspen (Populus tremula L.), hybrid aspen (Populus tremula x tremuloides), and small-leaved lime (Tilia cordata Mill.). At the same time, research results show sustainability of management of plantation forests—positive impact on soil agrochemical properties, proportionate changes on above-ground vegetation, and improvement of economic benefits of farmlands.
    URI
    https://library.oapen.org/handle/20.500.12657/49369
    Keywords
    plantation forest, abandoned, marginal farmlands, forest tree species, soil agrochemical properties, above-ground vegetation, productivity, yield, biomass
    DOI
    10.5772/intechopen.88373
    Publisher
    InTechOpen
    Publisher website
    https://www.intechopen.com/
    Publication date and place
    2020
    Classification
    Engineering: general
    Rights
    https://creativecommons.org/licenses/by/3.0/
    • Imported or submitted locally

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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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