Modelling approaches for mixed forests dynamics prognosis. Research gaps and opportunities

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2019-04-29
Author
Bravo, Felipe
Fabrika, Marek
Ammer, Christian
Barreiro, Susana
Bielak, Kamil
Coll Mir, Lluís
Fonseca, T.
Kangur, Ahto
Löf, Magnus
Merganičová, Katarina
Pach, Maciej
Pretzsch, Hans
Stojanović, Dejan
Schuler, Laura
Peric, Sanja
Rötzer, Thomas
del Río, Miren
Dodan, Martina
Bravo Oviedo, Andrés
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Bravo, Felipe; Fabrika, Marek; Ammer, Christian; Barreiro, Susana; Bielak, Kamil; Coll Mir, Lluís; ... Bravo Oviedo, Andrés. (2019) . Modelling approaches for mixed forests dynamics prognosis. Research gaps and opportunities. Forest Systems, 2019, vol. 28, num. 1, p. eR002. https://doi.org/10.5424/fs/2019281-14342.
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Abstract
Aim of study: Modelling of forest growth and dynamics has focused mainly on pure stands. Mixed-forest management lacks systematic procedures to forecast the impact of silvicultural actions. The main objective of the present work is to review current knowledge and forest model developments that can be applied to mixed forests. Material and methods: Primary research literature was reviewed to determine the state of the art for modelling tree species mixtures, focusing mainly on temperate forests. Main results: The essential principles for predicting stand growth in mixed forests were identified. Forest model applicability in mixtures was analysed. Input data, main model components, output and viewers were presented. Finally, model evaluation procedures and some of the main model platforms were described. Research highlights: Responses to environmental changes and management activities in mixed forests can differ from pure stands. For greater insight into mixed-forest dynamics and ecology, forest scientists and practitioners need new theoretical frameworks, different approaches and innovative solutions for sustainable forest management in the context of environmental and social changes.
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http://hdl.handle.net/10459.1/66727
DOI
https://doi.org/10.5424/fs/2019281-14342
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Forest Systems, 2019, vol. 28, num. 1, p. eR002
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cc-by (c) Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), 2019
Except where otherwise noted, this item's license is described as cc-by (c) Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), 2019