Aboveground biomass equations for sustainable production of fuelwood in a native dry tropical afro-montane forest of Ethiopia

Abstract

Abstract& Key message Biomass equations are presented for five tree species growing in a natural forest in Ethiopia. Fitted models showed more accurate estimations than published generalized models for this dry tropical forest. & Context Biomass equations are needed to correctly quantify harvestable stock and biomass for sustainability efforts in forest management, but this kind of information is scarce in Ethiopia. & Aims This study sought to develop biomass models for five of the most common native tree species in the Chilimo dry afro-montane mixed forest in the central highlands of Ethiopia: Allophyllus abyssinicus, Olea europaea ssp. cuspidata, Olinia rochetiana, Rhus glutinosa, and Scolopia theifolia. Comparison with generalized models was intended to show the greater accuracy of the specific models. & Methods A total of 90 trees from different diameter classes were selected, felled, and divided into different biomass compartments. Biomass equation models were fitted using jointgeneralized least squares regression to ensure the additivity property between the biomass compartments and total biomass. & Results These were the first models developed for these species in African tropical forests. Models were including diameter at breast height and total height as independent variables, obtaining more accurate biomass estimations using these models than from generalized models. & Conclusion Fitted models are reliable for estimating aboveground biomass in the Chilimo forest and for more general application in similar forest types. Model applicability for biomass or carbon estimation is high within forest inventory data contexts.

Allometric Models for Predicting Aboveground Biomass of Trees in the Dry Afromontane Forests of Northern Ethiopia

“…It is not surprising that the best local multispecies model from this study performed better than the previously published general models (Table 6). Such a result also emphasizes the importance to develop local models to get more accurate biomass estimations when local estimates are required [9,18]. The two pan-tropical general multispecies models developed for dry tropical forests [10] and for all tropical forests [11] gave relatively good predictions with nonsignificant differences for our site (5.2% and 5.3% respectively).…”

“…For instance, the general multispecies pan-tropical models developed by Chave et al [10,11] have been used for estimating AGB of different forest types in many parts of the world, including Ethiopia. Nevertheless, there are many studies (e.g., [15,18,19]) that showed a significant bias in AGB for different forest types when these models were applied.…”

“…Ex Mirb. in Wof-Washa dry Afromontane forest using a non-destructive method; (2) local species-specific models developed by Tesfaye et al [18] for Allophyllus abyssinicus (Hochst.) Radlk., Olea europaea L. subsp.…”

Ecuaciones de aditividad para la estimación de biomasa aérea de Pinus cembroides Zucc.

“…La variación explicada por las ecuaciones de aditividad fue alta, esto se debe a que en su estructura se incluyeron como variables independientes al Dn y a la H. El uso de estas variables en la predicción de la biomasa ha sido discutido ampliamente por diferentes autores, debido a que pueden mejorar significativamente los resultados de ajuste y la capacidad de predicción (Bi et al, 2004;Li y Zhao, 2013), en lugar de emplear únicamente al Dn como variable predictora. Además, al incluir a la H en las ecuaciones se tiene información relacionada sobre la competencia y/o fertilidad del sitio ocasionando estimaciones menos sesgadas (Tesfaye et al, 2015). El uso del Dn como única variable predictora para la estimación de biomasa a nivel del árbol, ha mostrado buenos estadísticos de ajuste para diferentes especies de coníferas (Návar, González, Graciano, Dale y Parresol, 2004;Acosta-Mireles et al;2002;Díaz-Franco et al, 2007).…”

Growth and survival rate of endemic trees of Ethiopia: Olea africana and Hagenia abysinicca in the degraded lake of Haramaya Watershed, Ethiopia

“…This is due the fact that the country has a wide variety of ecological characteristics associated with ample diversity of plant and animal species (Alemayehu, 2002). However, a number of studies indicated that almost all of the natural vegetation of Ethiopia is under an extreme pressure of anthropogenic threats (Yirdaw, 1996;Million, 2001;Tesfaye, 2015;Newton and Cantarello 2015). Given about 85% of the population Ethiopia is living in the rural areas, their livelihood system is either directly or indirectly depends on agriculture, which provides about 52% of the country's GDP (World Bank, 2000;CIA, 2001).…”