Canadian Forest Service Publications

Using the carbon budget model of the Canadian forest sector (CBM-CFS3) to examine the impact of harvest and fire on carbon dynamics in selected forest types of the Canadian boreal shield. 2012. Luckai, N.; Larocque, G.R.; Archambault, L.; Paré, D.; Boutin, R.; Groot, A. The Forestry Chronicle. 88:426-438.

Year: 2012

Available from: Laurentian Forestry Centre

Catalog ID: 34043

Language: English

CFS Availability: PDF (request by e-mail)

Abstract

The objective of the study was to assess the responsiveness of the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to management scenarios that included three rotation lengths (50, 100 and 250 years) under harvest and fire disturbances in six forest types (poplar deep soil, black spruce deep soil, jack pine deep and shallow soils, hardwood mixedwood and other conifer lowland). Outputs from five carbon (C) pools were considered: merchantable stemwood (stump height of 30 cm, minimum DBH of 9 cm and a minimum top diameter of 7 cm), deadwood, soil C, total ecosystem C and cumulative total ecosystem C emissions. Yield curves strongly affected the predicted size of all five pools. Longer rotation lengths led to larger pools with the relative differences between rotation lengths varying with stand types. Pools associated with poplar were usually the largest while those of jack pine on shallow sites were generally the smallest. When compared to the starting point of the simulations, cumulative total ecosystem C and C emissions increased with the 100- and 250-year harvest rotations (HARV100 and HARV250, respectively) and declined with the 50-year harvest rotation (HARV50). Fire disturbances resulted in stable pools of cumulative ecosystem C and declines in C emissions. CBM-CFS3 provided realistic pool values but the authors suggest further development of the model depiction of ecosystem processes, especially with respect to the treatment of respiration. In general, the authors recommend that forest management planners consider using an integrated approach that links multiple proven and accepted models under appropriate model linking software.

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