Allometric models to predict DBH from stump diameter in coppice-regenerated post-fire eucalypt plantations
Year: 2026
Type: article
Abstract: Short-rotation plantations (SRPs), including eucalypt woodlots, now constitute an integral component of the afforestation strategies of many tropical nations under the Paris Agreement. However, wildfires and undocumented clear-cutting are common in these plantations, often occurring prior to reliable measurement of stem volume variables, especially the diameter at breast height (DBH), a key parameter for forest biomass and carbon scaling. In such scenarios, DBH can be reconstructed using allometric models based on the stump diameter (DS). However, locally derived DS–D models are scarce in East Africa, and forest inventories mostly rely on generic equations whose broad specifications do not adequately capture site-specific disturbances such as fire and rotational clear-cutting. This study developed DS–D models using data from 115 destructively and non-destructively sampled Eucalyptus camaldulensis trees across first-rotation, post-fire, and coppice-regenerated stands in the Kenyan savanna. Generalized additive models, ANCOVA, and linear mixed-effects models were employed using under-bark (DSuB) and over-bark (DSoB) stum diameters serving as primary predictors. Model validations were through conventional analytical techniques and machine learning-based cross-validation procedures. Results from post-fire plots indicated a significant negative shift in the intercept, suggesting variation in bark allocation as a response to fire. Models based on DSuB demonstrated greater predictive stability than those based on DSoB across different disturbance conditions. Locally calibrated models reduced prediction errors by up to 35% in disturbed plots, emphasizing the importance of disturbance-sensitive, site-specific models for enhancing biomass and carbon accounting in forest ecosystems.
Source: Ecological Modelling
Authors: Denis U.O. Austin, Eshetu Yirdaw
Institution: University of Helsinki
Language: English
Subfield: Nature and Landscape Conservation
Field: Environmental Science
Domain: Physical Sciences
SDGs: Life on land, Climate action
Open Access status: hybrid
Estimated APC paid: $2,810
Funder: Helsingin Yliopisto
OpenAlex ID: W7166642497
