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

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

Authors :
Felipe Bravo
Marek Fabrika
Christian Ammer
Susana Barreiro
Kamil Bielak
Lluis Coll
Teresa Fonseca
Ahto Kangur
Magnus Löf
Katarina Merganičová
Maciej Pach
Hans Pretzsch
Dejan Stojanović
Laura Schuler
Sanja Peric
Thomas Rötzer
Miren del Río
Martina Dodan
Andrés Bravo-Oviedo
Source :
Forest Systems, Vol 28, Iss 1, Pp eR002-eR002 (2019)
Publication Year :
2019
Publisher :
Consejo Superior de Investigaciones Científicas (CSIC), 2019.

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.

Subjects

Subjects :
Forestry
SD1-669.5

Details

Language :
English
ISSN :
21719845 and 92811434
Volume :
28
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Forest Systems
Publication Type :
Academic Journal
Accession number :
edsdoj.b70049d05e1640d3817a155a93801e4f
Document Type :
article
Full Text :
https://doi.org/10.5424/fs/2019281-14342