Skip to main content
SLU:s publikationsdatabas (SLUpub)

Forskningsartikel2023Vetenskapligt granskadÖppen tillgång

Modelling Dominant Tree Heights of Fagus sylvatica L. Using Function-on-Scalar Regression Based on Forest Inventory Data

Engel, Markus; Mette, Tobias; Falk, Wolfgang; Poschenrieder, Werner; Fridman, Jonas; Skudnik, Mitja

Sammanfattning

European beech (Fagus sylvatica L.) is an important tree species throughout Europe but shifts in its suitable habitats are expected in the future due to climate change. Finding provenances that are still economically viable and ecologically resilient is an ongoing field of research. We modelled the dominant tree heights of European beech as a trait reflecting growth performance dependent on provenance, climate and soil conditions. We derived dominant tree heights from national forest inventory (NFI) data from six European countries spanning over large ecological gradients. We performed function-on-scalar regression using hierarchical generalized additive models (HGAM) to model both the global effects shared among all provenances and the effects specific to a particular provenance. By comparing predictions for a reference period of 1981-2010 and 2071-2100 in a RCP 8.5 scenario, we showed that changes in growth performance can be expected in the future. Dominant tree heights decreased in Southern and Central Europe but increased in Northern Europe by more than 10 m. Changes in growth performance were always accompanied by a change in beech provenances, assuming assisted migration without dispersal limitations. Our results support the concept of assisted migration for the building of resilient future forests and emphasize the use of genetic data for future growth predictions.

Nyckelord

hierarchical GAMs; functional regression; Fagus sylvatica; provenance; assisted migration

Publicerad i

Forests
2023, Volym: 14, nummer: 2, artikelnummer: 304
Utgivare: MDPI

    Globala målen

    SDG13 Vidta omedelbara åtgärder för att bekämpa klimatförändringarna och dess konsekvenser

    UKÄ forskningsämne

    Skogsvetenskap

    Publikationens identifierare

    DOI: https://doi.org/10.3390/f14020304

    Permanent länk till denna sida (URI)

    https://res.slu.se/id/publ/121869