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dc.contributor.authorSiipilehto, Jouni
dc.contributor.authorAllen, Micky
dc.contributor.authorNilsson, Urban
dc.contributor.authorBrunner, Andreas
dc.contributor.authorHuuskonen, Saija
dc.contributor.authorHaikarainen, Soili
dc.contributor.authorSubramanian, Narayanan
dc.contributor.authorAntón-Fernández, Clara
dc.contributor.authorHolmström, Emma
dc.contributor.authorAndreassen, Kjell
dc.contributor.authorHynynen, Jari
dc.date.accessioned2021-11-19T12:16:14Z
dc.date.available2021-11-19T12:16:14Z
dc.date.created2021-01-05T14:46:18Z
dc.date.issued2020
dc.identifier.citationSilva Fennica. 2020, 54 (5), .
dc.identifier.issn0037-5330
dc.identifier.urihttps://hdl.handle.net/11250/2830490
dc.description.abstractNew mortality models were developed for the purpose of improving long-term growth and yield simulations in Finland, Norway, and Sweden and were based on permanent national forest inventory plots from Sweden and Norway. Mortality was modelled in two steps. The first model predicts the probability of survival, while the second model predicts the proportion of basal area in surviving trees for plots where mortality has occurred. In both models, the logistic function was used. The models incorporate the variation in prediction period length and in plot size. Validation of both models indicated unbiased mortality rates with respect to various stand characteristics such as stand density, average tree diameter, stand age, and the proportion of different tree species, Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.), and broadleaves. When testing against an independent dataset of unmanaged spruce-dominated stands in Finland, the models provided unbiased prediction with respect to stand age.
dc.language.isoeng
dc.titleStand-level mortality models for nordic boreal forests
dc.typePeer reviewed
dc.typeJournal article
dc.description.versionpublishedVersion
dc.source.pagenumber21
dc.source.volume54
dc.source.journalSilva Fennica
dc.source.issue5
dc.identifier.doi10.14214/sf.10414
dc.identifier.cristin1865705
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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