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Research article2019Peer reviewed

Using linear mixed models to evaluate stand level growth rates for dipterocarps and Macaranga species following two selective logging methods in Sabah, Borneo

Lussetti, Daniel; Kuljus, Kristi; Ranneby, Bo; Ilstedt, Ulrik; Falck, Jan; Karlsson, Anders

Abstract

To understand and predict the dynamics and productivity of the world's tropical rainforests after logging is a major challenge for ecologists and forest managers. Realistic forest-dynamics models for this biome are largely lacking. Using linear mixed models, we analyse basal area development for the commercially valuable tree species of dipterocarps and the fast-growing pioneer Macaranga spp., following two selective logging methods; supervised logging (SL) and conventional logging (CL) combined with- or without pre-harvest climber cutting (SLC and SL, and CLC and CL, respectively). After logging there was an initial period of about five years before recovery started. During the 18-year study period, the average stand basal area growth rates of the dipterocarp group in the SLC treatment was double that in the CL treatment, revealing a faster recovery. Eighteen years after logging, SL and SLC treatments recovered 93% and 84%, respectively, of the initial standing dipterocarp basal area, compared to 73% and 72% recovery for the CL and CLC treatments. SLC treatments reduced the overall establishment of pioneer species (Macaranga spp.) by about 45% in contrast to CL and CLC treatments. Our study provides a framework for evaluating and comparing growth rates in tropical forests for different logging methods. The results suggest that a combination of directional felling, pre-aligned skid trails and pre-harvest climber cutting can improve future yields in tropical rainforests.

Keywords

Basal area growth; Climber cutting; Dipterocarpaceae; LMM; Reduced impact logging; Sustainable forest management

Published in

Forest Ecology and Management
2019, volume: 437, pages: 372-379

SLU Authors

Global goals (SDG)

SDG15 Life on land

UKÄ Subject classification

Forest Science

Publication identifier

  • DOI: https://doi.org/10.1016/j.foreco.2019.01.044

Permanent link to this page (URI)

https://res.slu.se/id/publ/98575