Enhancement of terrestrial carbon (C) sequestration on marginal lands in Canada using bioenergy crops has been proposed. However, factors influencing system-level C gain (SLCG) potentials of maturing bioenergy cropping systems, including belowground biomass C and soil organic carbon (SOC) accumulation, are not well documented. This study, therefore, quantified the long-term C sequestration potentials at the system-level in nine-year-old (2009–2018) woody (poplar clone 2293–29 (Populus spp.), hybrid willow clone SX-67 (Salix miyabeana)), and herbaceous (miscanthus (Miscanthus giganteus var. Nagara), switchgrass (Panicum virgatum)) bioenergy crop production systems on marginal lands in Southern Ontario, Canada. Results showed that woody cropping systems had significantly higher aboveground biomass C stock of 10.02 compared to 7.65 Mg C ha⁻¹ in herbaceous cropping systems, although their belowground biomass C was not significantly different. Woody crops and switchgrass were able to increase SOC significantly over the tested period. However, when long term soil organic carbon (∆SOC) gains were compared, woody and herbaceous biomass crops gained 11.0 and 9.8 Mg C ha⁻¹, respectively, which were not statistically different. Results also indicate a significantly higher total C pool [aboveground + belowground + soil organic carbon] in the willow (103 Mg ha⁻¹) biomass system compared to other bioenergy crops. In the nine-year study period, woody crops had only 1.35 Mg C ha⁻¹ more SLCG, suggesting that the influence of woody and herbaceous biomass crops on SLCG and ∆SOC sequestrations were similar. Further, among all tested biomass crops, willow had the highest annual SLCG of 1.66 Mg C ha⁻¹ y⁻¹.

Warm season perennial C4 grasses (WSGs), switchgrass (Panicum virgatum L.) and miscanthus species (Miscanthus spp.), have been reported to positively influence short-term (15–20 years) soil organic carbon (SOC). In this study, the DayCent model was used to predict changes in long-term SOC stocks under WSGs for moderate (Representative Concentration Pathway (RCP) 4.5) and high (RCP 8.5) warming climate change scenarios in southern Ontario, Canada, and to determine how long the enhanced SOC stock will last when WSGs are converted back to annual crop rotation. The model predicted that a consistent corn–corn–soybean–winter wheat (CCSW) rotation prevented SOC from depletion over the 21st century. Under WSGs, the model predicted high rates of SOC sequestration during the first 20–30 years which then tended to stabilize after 50–60 years. However, the rate of SOC sequestration over 90 years for RCP 4.5 was 0.26 and 0.94 Mg C ha⁻¹ yr⁻¹ for switchgrass and miscanthus, respectively. If 40-year stands of WSGs are converted back to CCSW, the model predicted SOC decline to the previous level in 40–50 years. DayCent predicted that under RCP 8.5 scenario in the second half of the 21st century and in the future, there will be a reduction in SOC stocks, especially under miscanthus stands.

Allometric equations were developed for estimating aboveground biomass carbon (AGBC) in five tree species grown in a tree-based intercropping system at the University of Guelph Agroforestry Research Station, Guelph, Ontario, Canada. A total of 66 representative trees from five species: red oak (Quercus rubra) [n = 12], black walnut (Juglans nigra) [n = 16], black locust (Robinia pseudoacacia) [n = 10], white ash (Fraxinus americana) [n = 15], Norway spruce (Picea abies) [n = 13] were selected, harvested and their aboveground biomass and carbon content were quantified. Three commonly used allometric models were used to develop predictive equations. Regression models were developed and parameterized for each tree species and the best are presented based on information criteria (AIC, AICc, and BIC), mean absolute percentage error (MAPE), over/under estimation (MOUE), root mean square error (RMSE), R², and regression coefficients (a, b) of the observed/predicted (OP) linear regression analysis. All equations with diameter at breast height (D) only and D and tree height (H) as the predictor variables fitted the AGBC data well, with R² > 97% and RMSE < 40. However, a power model using D as the only predictor is recommended as the best model for black walnut, black locust, white ash, and Norway spruce. The models presented are the best fitted allometric equations for the indicated species and are recommended for these species, growing on similar soils under the same temperate conditions at densities of < 125 tree per hectare.