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Elsevier, Biomass and Bioenergy, 1(35), p. 473-488

DOI: 10.1016/j.biombioe.2010.09.007

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A novel approach to simulate growth of multi-stem willow in bioenergy production systems with a simple process-based model (3PG)

Journal article published in 2011 by Beyhan Y. Amichev ORCID, Ryan D. Hangs, Ken C. J. Van Rees
This paper is available in a repository.
This paper is available in a repository.

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Abstract

An important requirement for commercialization of willow biomass production in short-rotation crop (SRC) plantations is the reliable and cost-efficient estimation of biomass yield. Predictions and simulations of willow stand biomass have been problematic due to issues with modeling the multi-stem growth form of willow. The aim of this paper was to develop a new approach for managing allometric measurements from multi-stemmed willow for stand growth simulations. The 3PG model (Physiological Principles in Predicting Growth) was parameterized for willow and was used for biomass yield simulation for an entire 22-yr cycle (seven 3-yr rotations) of willow in SRC plantations. The multi-stemmed growth form was transformed into a single-stem modeling form by deriving whole plant willow allometric relationships using detailed stem-level measurements of basal area, stem biomass and volume. 3PG model predictions for plant diameter, height, biomass, and stand biomass and volume were within the 95% confidence range of mean plot values. Model simulations showed that after seven 3-yr rotations only 20% of planted cuttings would survive (a decrease from 15,152 to 3022 plants ha−1), but stand volume would increase continuously with each subsequent rotation. 3PG predictions for cumulative (for 22 yr) aboveground biomass was 272 Mg ha−1 and mean annual yield was 12 Mg ha−1 yr−1, comparing favorably with other findings. To our knowledge, this work is the first where the 3PG model was calibrated and used for willow species. Once parameterized for a specific willow clone, 3PG can predict biomass accumulation for any agricultural land in North America using only available soil and climate data.