IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i15p6370-d1442690.html
   My bibliography  Save this article

Mortality of Boreal Trees

Author

Listed:
  • Petri P. Kärenlampi

    (Lehtoi Research, 81235 Lehtoi, Finland)

Abstract

A dataset collected from central South Finland was used to investigate the mortality of boreal trees. The mortality rate was found to be the order of three times that predicted by earlier Nordic mortality models, being in the upper range of international literature observations. Small subpopulations of any tree species tend to die out. The mortality of downy birch increases with stand basal area, as well as with stand age. The mortality of Norway spruce and silver birch increases after 100 years, while that of Scots pine is invariant to age. It is suspected that the high mortality of conifers is due to climatic phenomena of anthropogenic origin. As the relative loss rate of basal area is insensitive to stand basal area, the mortality of trees does not strongly regulate thinning practices, but stand-replacing damage can be avoided by retaining a larger timber stock, along with an enhanced proportion of deciduous trees.

Suggested Citation

  • Petri P. Kärenlampi, 2024. "Mortality of Boreal Trees," Sustainability, MDPI, vol. 16(15), pages 1-17, July.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:15:p:6370-:d:1442690
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/15/6370/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/15/6370/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Díaz-Yáñez, Olalla & Mola-Yudego, Blas & González-Olabarria, José Ramón, 2019. "Modelling damage occurrence by snow and wind in forest ecosystems," Ecological Modelling, Elsevier, vol. 408(C), pages 1-1.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ali Jahani & Maryam Saffariha, 2022. "Tree failure prediction model (TFPM): machine learning techniques comparison in failure hazard assessment of Platanus orientalis in urban forestry," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(2), pages 881-898, January.
    2. Félix Bastit & Marielle Brunette & Claire Montagne-Huck, 2021. "Earth, wind and fire: A multi-hazard risk review for natural disturbances in forests," Working Papers of BETA 2021-25, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:15:p:6370-:d:1442690. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.