Aboveground Biomass Models for Indigenous Tree Species in the Dry Afromontane Forest, Central Ethiopia
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 abo...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | International Journal of Forestry Research |
| Online Access: | http://dx.doi.org/10.1155/2023/4901521 |
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| author | Tamiru Lemi Abeje Eshete Getinet Seid Sinke Mulugeta Dereje Egeta Mindaye Teshome |
| author_facet | Tamiru Lemi Abeje Eshete Getinet Seid Sinke Mulugeta Dereje Egeta Mindaye Teshome |
| author_sort | Tamiru Lemi |
| collection | DOAJ |
| description | 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 (p>0.05). 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. |
| format | Article |
| id | doaj-art-dee82a3cb12b41c29d22a586ee68dd94 |
| institution | Kabale University |
| issn | 1687-9376 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Forestry Research |
| spelling | doaj-art-dee82a3cb12b41c29d22a586ee68dd942025-08-20T03:26:16ZengWileyInternational Journal of Forestry Research1687-93762023-01-01202310.1155/2023/4901521Aboveground Biomass Models for Indigenous Tree Species in the Dry Afromontane Forest, Central EthiopiaTamiru Lemi0Abeje Eshete1Getinet Seid2Sinke Mulugeta3Dereje Egeta4Mindaye Teshome5Ethiopian Forestry DevelopmentEthiopian Forestry DevelopmentJimma UniversityEthiopian Forestry DevelopmentEthiopian Forestry DevelopmentEthiopian Forestry DevelopmentThe 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 (p>0.05). 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.http://dx.doi.org/10.1155/2023/4901521 |
| spellingShingle | Tamiru Lemi Abeje Eshete Getinet Seid Sinke Mulugeta Dereje Egeta Mindaye Teshome Aboveground Biomass Models for Indigenous Tree Species in the Dry Afromontane Forest, Central Ethiopia International Journal of Forestry Research |
| title | Aboveground Biomass Models for Indigenous Tree Species in the Dry Afromontane Forest, Central Ethiopia |
| title_full | Aboveground Biomass Models for Indigenous Tree Species in the Dry Afromontane Forest, Central Ethiopia |
| title_fullStr | Aboveground Biomass Models for Indigenous Tree Species in the Dry Afromontane Forest, Central Ethiopia |
| title_full_unstemmed | Aboveground Biomass Models for Indigenous Tree Species in the Dry Afromontane Forest, Central Ethiopia |
| title_short | Aboveground Biomass Models for Indigenous Tree Species in the Dry Afromontane Forest, Central Ethiopia |
| title_sort | aboveground biomass models for indigenous tree species in the dry afromontane forest central ethiopia |
| url | http://dx.doi.org/10.1155/2023/4901521 |
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