Wood formation in Norway spruce on a lowland site in Slovenia in 2015 and comparison with other conifers all over Europe

Useros, Fernando; Balzano, Angela; Prislan, Peter; Luis, Martín de; Gričar, Jožica; Merela, Maks; Čufar, Katarina

doi:10.26614/les-wood.2017.v66n02a02

Cited by 2 publications

(1 citation statement)

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“…Mudeli 5 järgi nihkub radiaalkasvu algus laiuskraadi kohta 1 päeva võrra hilisemaks ja lõpp 1,4 päeva võrra varasemaks. Kasvu alguse ja kestuse tugevat seost laiuskraadist on tõdetud ka varasemalt (Useros et al, 2017). Mudel 5 (tabel 3) prognoosib kasvu dendromeetri vaatlustel kolm nädalat varasemaks ja üheksa päeva hilisemaks kui puidu anatoomiliste vaatluste (mikrosüdamiku või nõela meetod) järgi.…”

Section: Tulemusedunclassified

Puude hooajalise radiaalkasvu mõõtmiskuupäevaks moodustunud osa arvutusmudel Eesti tingimuste jaoks

2022

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Knowledge about the seasonal dynamics of tree growth and its relationship with environmental factors is necessary to eliminate the uncertainty due to ongoing climate change and for more precise growth modelling when re-measurements are done periodically. Despite the increasing number of studies monitoring seasonal wood formation, a considerable part of European forests, including Estonia, lacks such information. In this article, we present a date-dependent model for determining the share of seasonal radial growth for the three most common tree species in the region (Scots pine, Norway spruce and silver birch) for Estonian conditions. Since seasonal tree growth monitoring data were unavailable for Estonia, we used published seasonal radial growth data from Lithuania by Dr Adomas Vitas (2011). We tested four functions (Kumaraswamy, Weibull, Gompertz and logistic) on obtained data to approximate the seasonal development of radial growth. Kumaraswamy’s function could track the course of seasonal radial growth gains the best; thus, this function was chosen for further use. We obtained data on intra-annual radial growth from published research studies from neighbouring countries and determined the dates of growth initiation and cessation for Estonian conditions. Finally, we combined Kumaraswamy’s function and the predicted radial growth onset and cessation dates into the model that could predict the seasonal growth course and thus were able to estimate the share of newly formed increment from the dates.

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Section: Tulemusedunclassified