Understanding the Influence of Tree Size Distribution on the CTL Harvesting Productivity of Two Different Size Harvesting Machines

Author:

Ackerman Simon1ORCID,Bekker James2ORCID,Astrup Rasmus3,Talbot Bruce1ORCID

Affiliation:

1. Stellenbosch University Department of Forest and Wood Science

2. Stellenbosch University Industrial Engineering

3. Norwegian Institute for Bioeconomy Research

Abstract

Abstract Tree size determines harvester productivity. Stand management determines tree size distributions. Understanding the effect of tree size distribution on harvesting productivity is central for optimizing management of operations. To investigate tree size distribution on harvester productivity, productivity functions for a medium and larger-sized harvesters were applied to harvester derived tree size distributions from 35 clearfelled pine stands. These functions were applied to a normal distribution of trees covering the same tree size ranges. Productivity differences were analysed on a stand-by-stand basis. Results showed that for the large harvester, productivity rates remained constant (67.1 vs 67.6 m3 PMH− 1) indicating relatively little sensitivity to variations in tree size distributions. Although the standard deviation (SD) halved from 11.6 to 5.6 in the case of the uniform tree distribution. The smaller harvesters, productivity decreased by 15% from 47.3 to 40.1 m3 PMH− 1 and the coefficient of variation (CV) by 6% in the same transition to a uniform distribution. Further investigation was done on more skewed tree size distributions, a family of nine Weibull distributions was generated, representing combinations of three mean DBH classes (25cm, 30 cm, and 35cm) and three levels of CV (15%, 20%, 25%), for each DBH class. Results clearly indicate that different distribution shapes have different effects on different machine sizes, and that a low CV correlates to a higher productivity in larger tree sizes. A more uniform tree size distribution also provides more predictable results (lower CV), which would promote machine scheduling and result in fewer discrepancies on production rates.

Publisher

Research Square Platform LLC

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