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

  1. Bravo, Felipe 1
  2. Fabrika, Marek 2
  3. Ammer, Christian 3
  4. Barreiro, Susana 4
  5. Bielak, Kamil 5
  6. Coll, Lluis 6
  7. Fonseca, Teresa 7
  8. Kangur, Ahto 8
  9. Löf, Magnus 9
  10. Merganičová, Katarina 10
  11. Pach, Maciej 11
  12. Pretzsch, Hans 12
  13. Stojanović, Dejan 13
  14. Schuler, Laura 14
  15. Peric, Sanja 15
  16. Rötzer, Thomas 12
  17. del Río, Miren 16
  18. Dodan, Martina 15
  19. Bravo-Oviedo, Andrés 17
  1. 1 Instituto Universitario de Investigación en Gestión Forestal Sostenible (iuFOR) Universidad de Valladolid & INIA. Departamento de Producción Vegetal y Recursos Forestales, E.T.S. Ingenierías Agrarias Universidad de Valladolid Campus de Palencia Spain
  2. 2 Department of Forest Management and Geodesy, Faculty of Forestry, Technical University in Zvolen.
  3. 3 Abteilung Waldbau und Waldökologie der gemäßigten Zonen, Georg-August-Universität Göttingen, Göttingen.
  4. 4 Forest Research Center, School of Agriculture, University of Lisbon, Lisbon. Forest Ecology and Forest Management Group, Wageningen University and Research; Droevendaalsesteeg 3a, 6708PB Wageningen, The Netherlands.
  5. 5 Department of Silviculture, Warsaw University of Life Sciences.
  6. 6 Departament d’Enginyeria Agroforestal, E.T.S.E.A., Universitat de Lleida - Centre de Ciència i Tecnologia Forestal de Catalunya (CTFC), Solsona.
  7. 7 Forest Research Center, School of Agriculture, University of Lisbon, Lisbon. Universidade de Trás-os-Montes e Alto Douro, Department of Forest Sciences and Landscape Arquitecture, Vila Real.
  8. 8 Estonian University of Life Sciences, Department of Forest Management, Tartu.
  9. 9 Inst för sydsvensk skogsvetenskap - SLU , Alnarp.
  10. 10 Czech University of Life Sciences, Prague, Faculty of Forestry and Wood Sciences, Praha, Suchdol.
  11. 11 Department of Silviculture, Institute of Forest Ecology and Silviculture, University of Agriculture, Krakow.
  12. 12 Chair for Forest Growth and Yield Science, Technische Universität München.
  13. 13 Institute of Lowland Forestry and Environment, University of Novi Sad, Novi Sad.
  14. 14 Institute of Terrestrial Ecosystems, ETH Zurich.
  15. 15 Croatian Forest Research Institute, Jastrebarsko.
  16. 16 Instituto Universitario de Investigación en Gestión Forestal Sostenible (iuFOR) Universidad de Valladolid & INIA. INIA. Forest Research Centre INIA-CIFOR, Madrid.
  17. 17 Instituto Universitario de Investigación en Gestión Forestal Sostenible (iuFOR) Universidad de Valladolid & INIA. INIA. Forest Research Centre INIA-CIFOR, Madrid. National Museum of Natural Sciences – Spanish National Research Council (MNCN-CSIC). Department of Biogeography and Global Change, Madrid.
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Revista:
Forest systems

ISSN: 2171-5068

Año de publicación: 2019

Volumen: 28

Número: 1

Tipo: Artículo

DOI: 10.5424/FS/2019281-14342 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: Forest systems

Objetivos de desarrollo sostenible

Resumen

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.

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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. Additional keywords: dynamics, ecology, growth, yield, empirical, classification. Authors´ contributions: FB and MF conceived the idea and structure of the article and wrote the final version of the manuscript; all other co-authors compiled and prepared information, wrote parts of the manuscript and revised different manuscript drafts. Citation: Bravo, F., Fabrika, M., Ammer, C., Barreiro, S., Bielak, K., Coll, L., Fonseca, T., Kangur, A., Löf, M., Merganičová, K., Pach, M., Pretzsch, H., Stojanović, D., Schuler, L., Peric, S., Rötzer, T., Río, M. del, Dodan, M., Bravo-Oviedo, A. (2019). Modelling approaches for mixed forests dynamics prognosis. Research gaps and opportunities. Forest Systems, Volume 28, Issue 1, eR002. https:// doi.org/10.5424/fs/2019281-14342 Received: 29 Nov 2018. Accepted: 29 Apr 2019. Copyright © 2019 INIA. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC-by 4.0) License. Funding: COST Action FP1206 EuMIXFOR (COST Association, European Comission), APVV-0480-12 and APVV-15-0265 (Slovak Research and Development Agency) and AGL-2014-51964-C2-1-R (Spanish Ministry of Economy and Competitiveness). Competing interests: The authors have declared that no competing interests exist. Correspondence should be addressed to Felipe Bravo: fbravo@pvs.uva.es

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