Canadian Forest Service Publications

TRIPLEX: a generic hybrid model for predicting forest growth and carbon and nitrogen dynamics. 2002. Peng, C.; Liu, J.; Dang, Q.; Apps, M.J.; Jiang, H. Ecological Modelling 153: 109-130.

Year: 2002

Issued by: Pacific Forestry Centre

Catalog ID: 23769

Language: English

Availability: PDF (download)

Mark record


To predict the potential effects of future global environmental changes (e.g. climate, land-use, fire disturbance, and forest harvesting) on the sustainability of forest ecosystems, forest resource managers will need forest simulation models. Basic approaches to modelling forest growth and dynamics include the use of empirical, mechanistic, and hybrid forest simulation models. In this paper, a hybrid, monthly time-step model of forest growth and carbon dynamics (TRIPLEX) is described and tested. The TRIPLEX model integrates the forest production model of 3-PG (For. Ecol. Manage. 95 (1997) 209), the forest growth and yield model of TREENYD3 (Ecol. Model. 90 (1996) 187), and the soil–carbon–nitrogen model of CENTURY4.0 (Global Biogeochem. Cycles 7 (1993) 785). The model is intended to be comprehensive without becoming complex, and minimizes the number of input parameters required, while capturing key processes and important interactions between the carbon and nitrogen cycles of forest ecosystems. It is designed as a hybrid of both empirical and mechanistic components that can be used for (1) making forest management decisions (e.g. growth and yield prediction), (2) quantifying forest carbon budgets, and (3) assessing the effects of climate change in both the short and long term. We tested TRIPLEX against age-dependent growth measurements from 12 permanent sample plots (PSP) in jack pine (Pinus banskiana Lamb.) stands in northern Ontario (Canada). Comparisons of simulated stand growth variables (e.g. tree diameter, height, and stem density) with those observed in PSPs indicated a good agreement over 30 years. Predictions of tree total volume and aboveground biomass were within the expected range for these plots. While the model is promising, future modifications are discussed.