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Title:Modelling dominant tree heights of Fagus sylvatica L. using function-on-scalar regression based on forest inventory data
Authors:ID Engel, Markus (Author)
ID Mette, Tobias (Author)
ID Falk, Wolfgang (Author)
ID Poschenrieder, Werner (Author)
ID Fridman, Jonas (Author)
ID Skudnik, Mitja (Author)
Files:URL URL - Source URL, visit https://www.mdpi.com/1999-4907/14/2/304
 
.pdf PDF - Presentation file, download (3,65 MB)
MD5: 77932D959431B7EE541EF91A628677C1
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo SciVie - Slovenian Forestry Institute
Abstract: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.
Keywords:hierarchical GAMs, functional regression, Fagus sylvatica, provenance, assisted migration
Publication status:Published
Publication version:Version of Record
Publication date:01.01.2023
Year of publishing:2023
Number of pages:16 str.
Numbering:Vol. 14, iss. 2 [article. no. 304]
PID:20.500.12556/DiRROS-16379 New window
UDC:630*
ISSN on article:1999-4907
DOI:10.3390/f14020304 New window
COBISS.SI-ID:145998083 New window
Note:Nasl. z nasl. zaslona; Opis vira z dne 21. 3. 2023;
Publication date in DiRROS:21.03.2023
Views:667
Downloads:312
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Record is a part of a journal

Title:Forests
Shortened title:Forests
Publisher:MDPI
ISSN:1999-4907
COBISS.SI-ID:3872166 New window

Document is financed by a project

Funder:EC - European Commission
Funding programme:European Commission
Project number:952314
Name:Adaption strategies in forestry under global climate change impact
Acronym:ASFORCLIC

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.

Secondary language

Language:Slovenian
Keywords:funkcionalna regresija, Fagus sylvatica, provinenca


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