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

            Thumbnail
            Auteur
            Bambe, Baiba
            Daugavietis, Uldis
            Lazdins, Andis
            Lazdina, Dagnija
            Makovskis, Kristaps
            Daugaviete, Mudrite
            Language
            English
            Afficher la notice complète
            Résumé
            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://doab-dev.siscern.org/handle/20.500.12854/171705
            Keywords
            plantation forest, abandoned, marginal farmlands, forest tree species, soil agrochemical properties, above-ground vegetation, productivity, yield, biomass; thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBC Engineering: general
            DOI
            10.5772/intechopen.88373
            Publisher
            InTechOpen
            Publication date and place
            2020
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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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