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Implementing storm damage in a dynamic vegetation model for regional applications in Sweden

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  • Lagergren, Fredrik
  • Jönsson, Anna Maria
  • Blennow, Kristina
  • Smith, Benjamin

Abstract

Wind is the dominant agent of damage in forests in Western Europe. Traditional wind-damage models calculate a probability for damage or a critical wind speed at which damage occurs. However, in a dynamic vegetation model actual damage to stands and individual trees is needed to get a dynamical progression of the vegetation. We present a prototype for a new approach to modelling forest wind damage at the regional scale, which we incorporate within a dynamic vegetation model. The approach is based on knowledge from both empirical and mechanical models and calculates the damaged fraction of a cohort based on wind load and a sensitivity that depends on the current physical state and history of the cohort in relation to the ecosystem. The modelling concept has been developed, calibrated and evaluated for Swedish conditions but can be applicable to other similar areas with minor modification. Because of the stochastic nature of local wind load and the difficulty of describing the stand-level exposure, the ability to explain observed damage at stand level was low. Regional level variation in damage, which more depends on the wind load, was however explained reasonably well (R2=0.43). We suggest that this is a useful concept for evaluating alternatives of forest management under different climate scenarios in the process of adaptation to future storm-damage risks.

Suggested Citation

  • Lagergren, Fredrik & Jönsson, Anna Maria & Blennow, Kristina & Smith, Benjamin, 2012. "Implementing storm damage in a dynamic vegetation model for regional applications in Sweden," Ecological Modelling, Elsevier, vol. 247(C), pages 71-82.
  • Handle: RePEc:eee:ecomod:v:247:y:2012:i:c:p:71-82
    DOI: 10.1016/j.ecolmodel.2012.08.011
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    References listed on IDEAS

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    1. Seidl, Rupert & Fernandes, Paulo M. & Fonseca, Teresa F. & Gillet, François & Jönsson, Anna Maria & Merganičová, Katarína & Netherer, Sigrid & Arpaci, Alexander & Bontemps, Jean-Daniel & Bugmann, Hara, 2011. "Modelling natural disturbances in forest ecosystems: a review," Ecological Modelling, Elsevier, vol. 222(4), pages 903-924.
    2. Mart-Jan Schelhaas & Geerten Hengeveld & Marco Moriondo & Gert Reinds & Zbigniew Kundzewicz & Herbert Maat & Marco Bindi, 2010. "Assessing risk and adaptation options to fires and windstorms in European forestry," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 15(7), pages 681-701, October.
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    1. Anna Jönsson & Fredrik Lagergren & Benjamin Smith, 2015. "Forest management facing climate change - an ecosystem model analysis of adaptation strategies," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 20(2), pages 201-220, February.
    2. Blanco, Victor & Holzhauer, Sascha & Brown, Calum & Lagergren, Fredrik & Vulturius, Gregor & Lindeskog, Mats & Rounsevell, Mark D.A., 2017. "The effect of forest owner decision-making, climatic change and societal demands on land-use change and ecosystem service provision in Sweden," Ecosystem Services, Elsevier, vol. 23(C), pages 174-208.
    3. Lagergren, Fredrik & Jönsson, Anna Maria, 2017. "Ecosystem model analysis of multi-use forestry in a changing climate," Ecosystem Services, Elsevier, vol. 26(PA), pages 209-224.
    4. Bergkvist, John & Lagergren, Fredrik & Linderson, Maj-Lena Finnander & Miller, Paul & Lindeskog, Mats & Jönsson, Anna Maria, 2023. "Modelling managed forest ecosystems in Sweden: An evaluation from the stand to the regional scale," Ecological Modelling, Elsevier, vol. 477(C).
    5. Jönsson, Anna Maria & Lagergren, Fredrik, 2018. "Effects of climate and soil conditions on the productivity and defence capacity of Picea abies in Sweden—An ecosystem model assessment," Ecological Modelling, Elsevier, vol. 384(C), pages 154-167.
    6. Kolmanič, Simon & Guid, Nikola & Diaci, Jurij, 2014. "ForestMAS – A single tree based secondary succession model employing Ellenberg indicator values," Ecological Modelling, Elsevier, vol. 279(C), pages 100-113.

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