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

Felipe Bravo , M. Fabrika , Christian Ammer , Susana Barreiro , Kamil Bielak , Lluis Coll , Teresa Fonseca , Ahto Kangur , Magnus Löf , Katarina Merganičová , Maciej Pach , Hans Pretzsch , Dejan Stojanovic , Laura Schuler , Sanja Peric , Thomas Rötzer , Miren del Rio , Martina Dodan , Andres Bravo-Oviedo

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.Keywords: dynamics, ecology, growth, yield, empirical, classification.
Author Felipe Bravo
Felipe Bravo,,
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, M. Fabrika
M. Fabrika,,
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, Christian Ammer
Christian Ammer,,
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, Susana Barreiro
Susana Barreiro,,
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, Kamil Bielak
Kamil Bielak,,
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, Lluis Coll
Lluis Coll,,
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, Teresa Fonseca
Teresa Fonseca,,
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, Ahto Kangur
Ahto Kangur,,
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, Magnus Löf
Magnus Löf,,
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, Katarina Merganičová
Katarina Merganičová,,
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et al.`
Journal seriesForest Systems, ISSN 2171-5068, e-ISSN 2171-9845, (N/A 40 pkt)
Issue year2019
Vol28
No1
Pages1-18
Publication size in sheets0.85
ASJC Classification1105 Ecology, Evolution, Behavior and Systematics; 1107 Forestry; 1111 Soil Science
DOIDOI:10.5424/fs/2019281-14342
Languageen angielski
LicenseJournal (articles only); author's original; Other open licence; after publication
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Modelling approaches for mixed forests dynamics prognosis. Research gaps and opportunities of 18-06-2019
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Modelling approaches for mixed forests dynamics prognosis. Research gaps and opportunities
Score (nominal)40
Score sourcejournalList
Publication indicators WoS Citations = 1; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 0.696; WoS Impact Factor: 2018 = 1.138 (2) - 2018=1.346 (5)
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