Modelling and quantifying tree biometric properties of dry Afromontane forests of south-central Ethiopia

Abstract Key message Models for quantifying tree biometric properties, imperative for forest management decision-making, including height, diameter, bark thickness and volume were developed, and wood basic density was documented for dry Afromontane forests of south-central Ethiopia. Abstract Tree biometric properties such as height (ht), diameter at breast height (dbh), bark thickness (bt), volume and wood basic density (wbd) are imperative for forest management decision-making. For dry Afromontane forests in south-central Ethiopia, models for quantifying such tree properties are totally lacking. This study, therefore, aimed at developing models for ht based on dbh, for dbh based on stump height diameter (dsh), for bt based on dbh , for volume based on dbh, ht and crown width (crw), as well as documenting wbd data. Comprehensive and representative datasets were collected from Degaga–Gambo and Wondo Genet forests. The ht, dbh and bt modelling were based on 1345 sampled trees during forest inventories, while the volume modelling and wbd documentation were based on 63 destructively sampled trees from 30 species covering 87% of the total basal area in the study sites. Weighted least squares regression was applied for modelling and leave one out cross-validation was used for evaluation. The ht–dbh and dbh–dsh models performed well (pseudo- R 2 = 0.72 and 0.98), while bt–dbh performed poorer (pseudo- R 2 = 0.42). Models for the total tree, merchantable stem and branches volume were developed with different options for independent variables, where pseudo- R 2 varied from 0.74 to 0.98, with smallest values for the branches models The models may be applied to forests outside the present study sites provided that the growing conditions are carefully evaluated. The species-wise wbd was ranging from 0.426 to 0.979 g cm −3 , with the overall mean of 0.588 g cm −3 . The wbd data will be useful for building up a national wbd database and may also be included in the Global Wood Density database. The study represents a significant step towards sustainable forest management including REDD + MRV practices in the dry Afromontane forests of south-central Ethiopia.