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Modelling future growth of mountain forests under changing environments
ID Bošela, Michal (Avtor), ID Merganičová, Katarína (Avtor), ID Torresan, Chiara (Avtor), ID Cherubini, Paolo (Avtor), ID Fabrika, M. (Avtor), ID Heinze, Berthold (Avtor), ID Höhn, Maria (Avtor), ID Kašanin-Grubin, Milica (Avtor), ID Klopčič, Matija (Avtor), ID Mészáros, Ilona (Avtor), ID Pach, Maciej (Avtor), ID Střelcová, Katarina (Avtor), ID Temperli, Cristian (Avtor), ID Tonon, Giustino (Avtor), ID Pretzsch, Hans (Avtor), ID Tognetti, Roberto (Avtor)

URLURL - Izvorni URL, za dostop obiščite https://link.springer.com/chapter/10.1007/978-3-030-80767-2_7 Povezava se odpre v novem oknu
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Izvleček
Models to predict the effects of different silvicultural treatments on future forest development are the best available tools to demonstrate and test possible climate-smart pathways of mountain forestry. This chapter reviews the state of the art in modelling approaches to predict the future growth of European mountain forests under changing environmental and management conditions. Growth models, both mechanistic and empirical, which are currently available to predict forest growth are reviewed. The chapter also discusses the potential of integrating the effects of genetic origin, species mixture and new silvicultural prescriptions on biomass production into the growth models. The potential of growth simulations to quantify indicators of climate-smart forestry (CSF) is evaluated as well. We conclude that available forest growth models largely differ from each other in many ways, and so they provide a large range of future growth estimates. However, the fast development of computing capacity allows and will allow a wide range of growth simulations and multi-model averaging to produce robust estimates. Still, great attention is required to evaluate the performance of the models. Remote sensing measurements will allow the use of growth models across ecological gradients.

Jezik:Angleški jezik
Ključne besede:SDG 15, climate-smart forestry, CLIMO, forestry management, modelling
Tipologija:1.16 - Samostojni znanstveni sestavek ali poglavje v monografski publikaciji
Organizacija:BF - Biotehniška fakulteta
Status publikacije:Objavljeno
Različica publikacije:Objavljena publikacija
Leto izida:2022
Št. strani:Str. 223-262
PID:20.500.12556/RUL-133426 Povezava se odpre v novem oknu
UDK:630*61+630*22:630*111
DOI:10.1007/978-3-030-80767-2_7 Povezava se odpre v novem oknu
COBISS.SI-ID:86700547 Povezava se odpre v novem oknu
Datum objave v RUL:26.11.2021
Število ogledov:1227
Število prenosov:148
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Gradivo je del monografije

Naslov:Climate-smart forestry in mountain regions
Uredniki:Roberto Tognetti, Melanie Smith, Pietro Panzacchi
Kraj izida:Cham
Založnik:Springer
ISBN:978-3-030-80766-5
COBISS.SI-ID:86678787 Povezava se odpre v novem oknu
Naslov zbirke:Managing forest ecosystems (Online)
Številčenje v zbirki:ǂvol. ǂ40
ISSN zbirke:2352-3956

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:gorski gozdovi, sonaravno gozdarstvo, podnebno pametno gozdarstvo, modeliranje

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