Simulation of Shelterwood Logging in the Global Forest Model (G4M)

Gusti, M., Di Fulvio, F. ORCID: https://orcid.org/0000-0002-7317-6360, & Forsell, N. (2020). Simulation of Shelterwood Logging in the Global Forest Model (G4M). In: Advances in Intelligent Systems and Computing V. pp. 730-742 Zbarazh, Ukraine: Springer. ISBN 978-3-030-63270-0 10.1007/978-3-030-63270-0_50.

Full text not available from this repository.
Project: Alternative models and robust decision-making for future forest management (ALTERFOR, H2020 676754)

Abstract

An algorithm for simulation of shelterwood logging at the forest scale has been developed for the Global Forest Model (G4M). The algorithm was tested for a spruce forest with a mean annual increment 10 m3/(ha year) and rotation length maximizing mean annual increment, 91 years, and regeneration time 37 years in a 1000-year simulation against the conventional clearcut logging. Changing the forest management practice from the clearcut logging to the shelterwood logging results in oscillations of the biomass and harvest with decreasing amplitude until a new steady state is reached. The transition to the new steady state lasts about 600 years. At the steady state the stem biomass of the forest under shelterwood logging is about 30% greater than under the clearcut logging, while the harvest is about 3% lower. The algorithm produces adequate results in comparison to the clearcut logging. The algorithm extends the features of G4M to simulate shelterwood logging on regional and global scales.

Item Type: Book Section
Uncontrolled Keywords: Shelterwood logging; Simulation; Algorithm; Global forest model (G4M); Forest
Research Programs: Biodiversity and Natural Resources (BNR)
Biodiversity and Natural Resources (BNR) > Integrated Biosphere Futures (IBF)
Depositing User: Luke Kirwan
Date Deposited: 05 Mar 2021 09:40
Last Modified: 27 Aug 2021 17:34
URI: https://pure.iiasa.ac.at/17070

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