Abstract
The application of biomass models for quantifying forests’ above-ground biomass is essential for sustainable forest management. However, lack of knowledge in modelig biomass of individual tree growth hinders the sustainable management of Dry Afromontane forests. In this study, models to estimate above-ground biomass were developed for Rhus ruspolii, Ekebergia capensis, and Nuxia congesta. To develop the models, a total of 45 trees from different diameter classes were selected, felled, and divided into different biomass compartments. For the model’s development, diameter at breast height (DBH), total height (TH), diameter at stump height (DSH), and wood density (WD) were used as independent variables. Models’ performances were evaluated using RSE, adjusted coefficient of determination, and AIC. Also, model validations were done by using rRMSE, mean absolute deviation, bias, and coefficient of variation. Models 5 (Adj-R2 = 0.92), 6 (Adj-R2 = 0.97), and 8 (Adj-R22 = 0.82) were the best fitted models for Nuxia congesta, Ekebergia capensis, and Rhus ruspolii, respectively. The average wood densities of Ekebergia capensis, Nuxia congesta, and Rhus ruspolii were 0.59, 0.50, and 0.69, respectively. The variation between observed biomass and estimated biomass using new models was statistically not significant ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"><a:mi>p</a:mi><a:mo>></a:mo><a:mn>0.05</a:mn></a:math> ). Thus, the biomass models developed here can be important tools to accurately estimate above-ground biomass in the Menagesha Suba forest and can be integrated into decision support tools.
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Claims 7
Claim · model-written summary
Model 5 was the best fitted above-ground biomass model for Nuxia congesta (Adj-R2 = 0.92).
- Taxon
- Nuxia congesta
Nuxia congestae0 - Outcome
- best fitted modelse0
- Value
- Adj-R2 = 0.92e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Models 5 (Adj-R2 = 0.92), 6 (Adj-R2 = 0.97), and 8 (Adj-R22 = 0.82) were the best fitted models for Nuxia congesta, Ekebergia capensis, and Rhus ruspolii, respectively”
Claim · model-written summary
Model 6 was the best fitted above-ground biomass model for Ekebergia capensis (Adj-R2 = 0.97).
- Taxon
- Ekebergia capensis
Ekebergia capensise0 - Outcome
- best fitted modelse0
- Value
- Adj-R2 = 0.97e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Models 5 (Adj-R2 = 0.92), 6 (Adj-R2 = 0.97), and 8 (Adj-R22 = 0.82) were the best fitted models for Nuxia congesta, Ekebergia capensis, and Rhus ruspolii, respectively”
Claim · model-written summary
Model 8 was the best fitted above-ground biomass model for Rhus ruspolii (Adj-R22 = 0.82).
Verbatim
e0“Models 5 (Adj-R2 = 0.92), 6 (Adj-R2 = 0.97), and 8 (Adj-R22 = 0.82) were the best fitted models for Nuxia congesta, Ekebergia capensis, and Rhus ruspolii, respectively”
Claim · model-written summary
The average wood density of Ekebergia capensis was 0.59.
- Taxon
- Ekebergia capensisEkebergia capensise0
- Outcome
- average wood densitiese0
- Value
- 0.59e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The average wood densities of Ekebergia capensis, Nuxia congesta, and Rhus ruspolii were 0.59, 0.50, and 0.69, respectively”
Claim · model-written summary
The average wood density of Nuxia congesta was 0.50.
- Taxon
- Nuxia congestaNuxia congestae0
- Outcome
- average wood densitiese0
- Value
- 0.50e0
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The average wood densities of Ekebergia capensis, Nuxia congesta, and Rhus ruspolii were 0.59, 0.50, and 0.69, respectively”
Claim · model-written summary
The average wood density of Rhus ruspolii was 0.69.
Verbatim
e0“The average wood densities of Ekebergia capensis, Nuxia congesta, and Rhus ruspolii were 0.59, 0.50, and 0.69, respectively”
Claim · model-written summary
Estimated biomass from the new models did not differ significantly from observed biomass.
Verbatim
e0“The variation between observed biomass and estimated biomass using new models was statistically not significant”