Sequestration of carbon in commercial plantations and farm forestry

Abstract

Commercial plantations and farm forestry have the potential to increase the average carbon storage in woody biomass through afforestation, integration of belt plantings into farms, or increasing the average length of harvest rotations. In Australia, such increases in carbon storage are estimated at national- and project-scale through application of the stand-level carbon accounting model FullCAM, with predictions predominantly influenced by an input layer of biomass potential and calibrated yield curve parameters. Recent revision of the biomass potential input layer in FullCAM necessitated a refinement of yield curve calibrations for plantations and farm forestry, and therefore provided an opportunity to expand the capability of the model. Here we collated and analysed 16,749 observations of yields of above-ground biomass (AGB, Mg DM ha−1) from 8,749 independent plantation stands to assess whether growth differed between regions, species, management regimes and planting configurations and inform grouping of calibration sites into 17 different categories of tree plantings across Australia, with each having unique yield curve calibrations. Eight of the categories comprised species (or hybrids) that are commonly established in Australia, while other species (for which there were less AGB data) were grouped into generic multi-species categories based on plant functional type and/or planting configuration (block or belt). In revising the model calibrations, the trade-off between model accuracy and utility was considered. Across all plantation categories, stand age and biomass potential alone explained an average of 60% of the variation in observed AGB, with little (<10%) additional variation explained by factors such as region, species in the multi-species categories, or whether considering differences in yields from new plantings vs. regrowth post coppice harvesting. Although predictions were unbiased overall, they may nonetheless provide erroneous predictions at a given site. Although individual over- and under-predictions will tend to cancel out for carbon accounting at the national-scale, at the project-scale where carbon offsets are monetarised, discounting for uncertainty may be implemented.