Modelling aboveground stem volume and tree biomass for Searsia lancea (L.f.) FABarkley in Central Bushveld, South Africa

Abstract

This study sought to develop an allometric model for estimating the stem volume and aboveground biomass of the karee (Searsia lancea) tree, which is characterised by its multi-stemmed structure. Stratified random sampling was conducted by selecting two blocks from both the sparse and dense karee stands. Within each block, three sparse and three dense karee stands were identified. In every selected block, three thinning treatments, comprising no thinning, 50% thinning, and complete clear-felling of karee stems, were randomly assigned to the selected stands. A total of 110 randomly selected stems were destructively harvested and sliced into smaller sections to measure their wet mass and volume. Then, models were developed by regressing the stem diameter at breast height (DBH) and height against the tree biomass and stem volume. The graphical plots revealed that the relationships among these tree parameters were not linear. The coefficient of determination (R2), adjusted R2, residual standard error, mean squared error and residual mean squared error were calculated as model performance metrics. The model with the lowest Akaike information criterion value was selected as the best model. Models including both DBH and tree height gave the most accurate biomass and stem volume estimates, while DBH-only models also performed satisfactorily. Estimated biomass and stem volume were consistently higher in dense than in sparse stands. The findings highlight the potential of karee woodlands for sustainable bioenergy production and carbon sequestration. In general, if karee woodland is managed sustainably, it has high potential as an energy source through pellet production.