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-R2 = 0.72 and 0.98), while bt–dbh performed poorer (pseudo-R2 = 0.42). Models for the total tree, merchantable stem and branches volume were developed with different options for independent variables, where pseudo-R2 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.

Species specific allometric equations, biomass expansion factor and wood density of native tree species in dry afromontane forest of Ethiopia

“…Comparison was made using AIC, residual standard error, adj.R squared and p-value. Finally the results were compared with (Brown and Lugo, 1989;Chave et al, 2005 andDjomo et al, 2016;Asrat et al, 2020).…”

“…In contrast, indirect methods adopted already developed allometric models and Biomass Expansion Factors (BEFs) to estimate tree biomass and are cost effective and time efficient (Peltier et al, n.d.). Basic wood density are also calculated as (dry weight divided by green volume) may also be used to predict biomass either when using allometric models or along with biomass expansion factors and volume data (Asrat et al, 2020).…”

“…Most biomass models are developed for tropical tree species grown particularly in Latin America and South Africa. Though, some studies in recently emerged in East África and Ethiopia (Mamo and Sterba, 2006;Zewdie et al, 2009;Henry et al, 2010;Tesfaye et al, 2016;Fayolle et al, 2018;Asrat et al, 2020), Attempts to develop biomass equations in Sub-Saharan Africa in general and Ethiopia in particular are very limited (Moges et al, 2010;Henry et al, 2011;Tesfaye et al, 2016).…”

“…Pan-tropical allometric equations developed by many researchers may over or underestimate the biomass, due to tree species may differ greatly in tree architecture and wood gravity (Ketterings et al, 2001) and thus, species-specific equations would improve the accuracy of the biomass estimates. Species-specific allometric equations use one or more measurable variables of tree dimensions such as trunk diameter, height, average crown diameter and wood specific density (Kangas and Maltamo, 2006;Asrat et al, 2020). This has high potential to increase the accuracy of biomass and carbon estimation for financial reward by improving MRV activities of the country.…”

Use of Remotely Sensed Data to Enhance Estimation of Aboveground Biomass for the Dry Afromontane Forest in South-Central Ethiopia

“…This model has DBH, height and wood basic density as predictor variables. Wood basic density values were obtained from [48]. For plantation forests, tree AGB was estimated using species-specific allometric models.…”