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Naslov:Modelling dominant tree heights of Fagus sylvatica L. using function-on-scalar regression based on forest inventory data
Avtorji:ID Engel, Markus (Avtor)
ID Mette, Tobias (Avtor)
ID Falk, Wolfgang (Avtor)
ID Poschenrieder, Werner (Avtor)
ID Fridman, Jonas (Avtor)
ID Skudnik, Mitja (Avtor)
Datoteke:URL URL - Izvorni URL, za dostop obiščite https://www.mdpi.com/1999-4907/14/2/304
 
.pdf PDF - Predstavitvena datoteka, prenos (3,65 MB)
MD5: 77932D959431B7EE541EF91A628677C1
 
Jezik:Angleški jezik
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:Logo SciVie - Gozdarski inštitut Slovenije
Povzetek: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.
Ključne besede:hierarchical GAMs, functional regression, Fagus sylvatica, provenance, assisted migration
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Datum objave:01.01.2023
Leto izida:2023
Št. strani:16 str.
Številčenje:Vol. 14, iss. 2 [article. no. 304]
PID:20.500.12556/DiRROS-16379 Novo okno
UDK:630*
ISSN pri članku:1999-4907
DOI:10.3390/f14020304 Novo okno
COBISS.SI-ID:145998083 Novo okno
Opomba:Nasl. z nasl. zaslona; Opis vira z dne 21. 3. 2023;
Datum objave v DiRROS:21.03.2023
Število ogledov:397
Število prenosov:170
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
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Gradivo je del revije

Naslov:Forests
Skrajšan naslov:Forests
Založnik:MDPI
ISSN:1999-4907
COBISS.SI-ID:3872166 Novo okno

Gradivo je financirano iz projekta

Številka projekta:klifW005
Naslov:klifW005

Financer:EC - European Commission
Program financ.:European Commission
Številka projekta:952314
Naslov:Adaption strategies in forestry under global climate change impact
Akronim:ASFORCLIC

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:funkcionalna regresija, Fagus sylvatica, provinenca


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