Canadian Forest Service Publications

Development of TRIPLEX-Management model for simulating the response of forest growth to pre-commercial thinning. 2011. Wang, W.; Peng, C.; Zhang, S.Y.; Zhou, X.; Larocque, G.R.; Kneeshaw, D.D.; Lei, X. Ecol. Model. 222: 2249-2261.

Year: 2011

Available from: Laurentian Forestry Centre

Catalog ID: 34766

Language: English

CFS Availability: PDF (request by e-mail)

Available from the Journal's Web site.
DOI: 10.1016/j.ecolmodel.2010.09.019

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In order to simulate forest growth response to pre-commercial thinning (PCT), TRIPLEX1.0 – a processbased model designed to predict forest growth as well as carbon (C) and nitrogen (N) dynamics – was modified and improved to also simulate managed forest ecosystem thinning practices. A three-parameter Weibull distribution model was integrated to simulate thinning treatments within the newly developed TRIPLEX-Management model. The thinning intensity component within the model allows users to simulate thinning treatments by applying basal area, stand density and volume to quantify thinning intensity. Natural mortality decreased following thinning due to an increase in growing space for residual stems. Predicted litterfall pools also increased after thinning events took place. The TRIPLEX-Management model was tested against published observational data for Jack Pine (Pinus banksiana Lamb.) stands subjected to PCT in Northwestern Ontario, Canada. The coefficients of determination (R2) between the predicted and observed variables including stand density, mean DBH (diameter at breast height), the quadratic mean DBH, total volume and merchantable volume as well as belowground, aboveground, and total biomass ranged from 0.50 to 0.88 (n = 20, P < 0.001) with the exception of mean tree height (R2 = 0.25, n = 20, P < 0.05). Overall, the Willmott index of agreement between predicted and observed variables ranged from 0.97 to 1.00. Results show that the TRIPLEX-Management model is generally capable of simulating growth response to PCT for Jack Pine stands.

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