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Allometric Equations for Predicting Biomass of Daniellia oliveri (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon

Received: 27 April 2019     Accepted: 18 June 2019     Published: 10 August 2019
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Abstract

Allometric relationships for estimating biomass of Daniellia oliveri (Rolfe) Hutch & Dalz. stand were investigated in the sudano-guinea savannah of Ngaoundere, Cameroon. A total of 17 individual trees from Daniellia oliveri were harvested in Bini-Dang savannah across a range of diameter classes, from 5 to 40 cm. Diameter at breast height (D) and total height (H) were determined and considered as predictor variables, while total above-ground biomass, stem, branch, leaf and root biomass were the output variables of the allometric models. Among many models tested, the best ones were chosen according to the coefficient of determination adjusted (R2adj), the residual standard error (RSE) and the Akaike Information Criteria. The main results showed that the multiplication of tree H with D in the allometric equation did not improve in the degree of fitness of the allometric equations, except for leaf biomass. The fit allometric biomass of Daniellia oliveri model for leaf, branch, stem and root biomass and above ground biomass were the follow: Ln(Bl)= 3.0303 + 0.744*Ln(D2H); Ln(Bb) = 3.772 + 2.701*Ln(D); Ln(Bs) = 2.663 + 2.218*Ln(D), Ln(Br) = 2.072 + 1.920*Ln(D) and Ln(Bt) = -2.089 + 2.374*Ln(D) respectively. The root biomass represented on average 28% of the total aboveground biomass and these two biomasses were positively and significantly correlated (r = 0.93, p ˂ 0.05 and n = 11). For the Daniellia oliveri stands studied, the diameter at breast height (D) alone showed a very strong accuracy of estimation. It is concluded that the use of tree height in the allometric equation can be neglected for the species, as far as the present study area is concerned. Therefore, for estimating the biomass of Daniellia oliveri, the use of D as an independent variable in the allometric equation with a power equation would be recommended. The paper describes details of tree biomass allometry, which is important in carbon stock, sylviculture and savannah management.

Published in Ecology and Evolutionary Biology (Volume 4, Issue 2)
DOI 10.11648/j.eeb.20190402.11
Page(s) 15-22
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Allometry, Regression, Biomass, Daniellia oliveri, Savannah of Ngaoundere, Cameroon

References
[1] Arbonnier, M. 2002. Arbres, arbustes et lianes des zones sèches d’Afrique de l’Ouest. Montpellier: Cirad éditions.
[2] Mapongmetsem, P. M. 2005. Phénologie et apports au sol des substances biogènes de la litière des feuilles de fruitiers sauvages des savanes soudano-guinéennes. Thèse de Doctorat d’Etat, Université de Yaoundé I, Cameroun. 268p.
[3] Von Maydell, H. J. 1990. Arbres et arbustes du sahel: leurs caractéristiques et leurs utilisations. Weikersheim, GTZ.
[4] Gautier, D., Hautdidier, B., Ntoupka, M., Onana, J., Perrot N. & Tapsou, T. 2002. Fiches techniques des arbres utiles aux paysans du Nord Cameroun. Caractéristiques de l’arbre, ce qu’en font les paysans et ce qu’ils pourraient en faire. 106p.
[5] Letouzey, R. 1968. Etude phytogéographique du Cameroun. Ed. Le chevalier (Paris), 551p.
[6] Tchobsala 2011. Impact des coupes de bois sur la végétation naturelle de la zone périurbaine de Ngaoundéré (Adamaoua). Thèse de Doctorat/Ph. D, Université de Yaoundé I, Cameroun 204 p.
[7] Mapongmetsem, P. M. 2006. Domestication of Vitex madiensis in the Adamaoua highlands of Cameroon: phenology and propagation. Akdeniz Universitesi Ziraa Fakultesi Dergisi. 19 (2): 269-278.
[8] Ibrahima, A., Mapongmetsem, P. M. & Hassan, M. 2006. Influence de quelques facteurs zoo-anthropiques sur la phytodiversité ligneuse des savanes soudano-guinéennes de l’Adamaoua, Cameroun. Annales De la Faculté des Sciences, Université de Yaoundé I, Série Sci. de la Nat. et de la Vie. 36 (3): 65–85.
[9] Mahmood, H., Siddique, M. R. H., Costello, L., Birigazzi, L., Abdullah, S. M. R., Henry, M., Siddiqui, B. N., Aziz, T., Ali, S., Al Mamun, A., Forhad, M. I. K., Akhter, M., Iqbal, Z. & Mondol, F. K. 2019. Allometric models for estimating biomass, carbon and nutrient stock in the Sal zone of Bangladesh. iForest. 12: 69-75.
[10] Brown, S. 1997. Estimating Biomass and Biomass Change of Tropical Forests: a Primer. FAO Forestry Paper no134. FAO, Rome. 45, 106.
[11] Ibrahima, A., Schmidt, P., Ketner, P. & Mohren, G. J. M. 2002. Phytomasse et cycle des nutriments dans la forêt tropicale dense humide du sud Cameroun. Tropenbos Cameroon Documents 9. The Tropenbos Cameroon Programme.
[12] Djomo, A. N., Ibrahima, A., Saborowski, J. & Gravenhorst, G. 2010. Allometric Equations for Biomass Estimations in Cameroon and Pan Moist Tropical Equations Including Biomass Data from Africa. Forest Ecology and Management. 260: 1873-1885.
[13] Laminou Manzo, O., Moussa, M., Issoufou, HBA, Abdoulaye, D., Morou, B., Youssifi, S., Mahamane, A. & Paul, R. 2015. Equations allométriques pour l’estimation de la biomasse aérienne de Faidherbiaalbida (Del.) Achev dans les agrosystèmes d’Aguié, Niger. International Journal of Biological and Chemical Sciences. 9 (4): 1863-1874.
[14] Mensah, S., Veldtman, R. & Seifert, T. 2017. Allometric Models for Height and Aboveground Biomass of Dominant Tree Species in South African Mistbelt Forests. Southern Forests: A Journal of Forest Science. 79: 19-30.
[15] Návar, J, Méndez, E, Nájera, A, Graciano, J, Dale, V. & Parresol, B. 2004. Biomass equations for shrub species of Tamaulipanthornscrub of North-eastern Mexico. Journal of Arid Environment. 59: 657-74.
[16] Mamadou Laminou, M. A. 2014. Equations de prédiction de la Biomasse de quelques espèces ligneuses des savanes de Ngaoundéré, Cameroun. Mémoire de Master en Biologie des Organismes Végétaux, Faculté des Sciences, Université de Ngaoundéré, 51p.
[17] Ahmadou, I. 2014. Equations de l’estimation de la Biomasse des huit espèces ligneuses de savanes de Ngaoundéré, Cameroun. Mémoire de Master en Biologie des Organismes Végétaux, Faculté des Sciences, Université de Ngaoundéré, 47p.
[18] Halilou, A. 2015. Equations de prédiction de la Biomasse de quelquesespèces ligneuses de savanes de Ngaoundéré, Cameroun. Mémoire de Master en Biologie des Organismes Végétaux, Faculté des Sciences, Université de Ngaoundéré, 54p.
[19] Nam, V. T., Van Kuijk, M. & Anten, N. P. R. 2016. Allometric equations for aboveground and belowground biomass estimations in an evergreen forest in Vietnam. PLoS ONE. 11 (6): 1-19.
[20] Chave, J., Rejou-Mechain M., Burquez, A., Chidumayo, E., Colgan, M. S., Delitti, W. B. C., Duque, A., Eid, T., Fearnside, P. M., Goodman, R. C., Henry, M., Martínez-Yrízar, A., Mugasha, W. A., Muller-Landau, H. C., Mencuccini, M., Nelson, B. W., Ngomanda, A., Nogueira, E. M., Ortiz-Malavassi, E., Pélissier, R., Ploton, P., Ryan, C. M., Saldarriaga, J. G. & Vieilledent, G. 2014. Improved allometric models to estimate the aboveground biomass of tropical trees. Global Change Biology. 20: 3177–3190.
[21] Röhling, S., Demant, B., Dunger, K., Neubauer, M., Oehmichen, K., Riedel, T. & Stümer, W. 2019. Equations for estimating belowground biomass of Silver Birch, Oak and Scots Pine in Germany. iForest. 12: 166-172.
[22] Nogueira, E. M., Fearnside, P. M., Nelson, B. W., Barbosa, R. I. & Keizer, E. W. H. 2008. Estimates of forest biomass in the Brazilian Amazon: new allometric equations and adjustments to biomass from wood-volume inventories. Forest Ecology and Management. 256 (11): 1853-1867.
[23] Ketterings, Q. M., Coe, R., van Noordwijk, M., Ambagu, Y. & Palm, C. A. 2001. Reducing uncertainty in use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests. Forest Ecology and Management. 146: 199–202.
[24] Liepinš, J., Lazdinš, A. & Liepinš, K. 2018. Equations for estimating above- and belowground biomass of Norway spruce, Scots pine, birch spp. and European aspen in Latvia. Scandinavian Journal of Forest Research. 33 (1): 58-70.
[25] Ter-Mikaelian, M. T. & Korzukhin, M. D. 1997. Biomass equations for sixtyfive North American tree species. Forest Ecology and Management. 97: 1-24.
[26] Smith, A., Granhus, A. & Rasmus, A. 2016. Functions for estimating belowground and whole tree biomass of birch in Norway. Scandinavian Journal of Forest Research. 31 (6): 568-582.
[27] Amarasing, M. D. & Balasubrananiam, S. 1992. Net primary productivity of two mangrove forests stands on the northwest coast of Sri Lanka. Hydrobiologia. 247, 37–47.
[28] Clough, B. F., Dixon, P., & Dalhaus, O. 1997. Allometric relationships for estimating biomass in multistemed mangrove trees. Australian Journal of Botany. 45: 1023–1031.
[29] Ong, J. E., Gong, W. K. & Wong, C. H. 2004. Allometry and partitioning of the mangrove, Rhizophoraapiculata. Forest Ecology and Management. 188: 395–408.
[30] Suzuki, E. &Tagawa, E. 1983. Biomass of a mangrove forest and a sedge marsh on Ishigakiisland, south Japan. Japanese Journal of Ecology. 33: 231-234.
[31] Tamai, S., Nakasuga, T., Tabuchi, R. & Ogino, K. 1986. Standing biomass of mangrove forests in southern Thailand. Journal of Japanese Forest Society. 68 (9): 384-388.
[32] Poungparn, S., Komiyama, A., Jintana, V., Piriyauaota, S., Sangtiean, T., Tanapermpool, P., Patanaponpaiboon, P. & Kato, S. 2002. A quantitative analysis on the root system of a mangrove, Xylocarpusgranatum Koenig. Tropics. 12: 35-42.
[33] Bognounou, F., Sawadogo, M., Boussim, I. J. & Guinko, S. 2008. Equations d’estimation de la biomasse foliaire de cinq espèces ligneuses soudaniennes du Burkina Faso. Sécheresse. 19 (3): 201-5.
[34] Lufafa, A., Diédhiou, I., Ndiaye, N. A. S., Séné, M., Kizito, F., Dick, R. P. Noller, J. S. 2009. Allometric relationships and peak-season community biomass stocks of native shrubs in senegal’speanuntbassin. Journal of Arid environments. 73 (3): 260-266.
[35] Suchel, J. B. La répartition des pluies et régimes pluviométriques au Cameroun, Centre de Recherches Africaines, Université fédérale du Cameroun. 1971; 29p.
[36] Carrière, M. 1989. Les communautés végétales sahéliennes en Mauritanie (Région de Kaédi), analyse de la reconstitution annuelle du couvert herbacé. Thèse de Doctorat, Université de Paris Sud Orsay, IE. M. V. T. Maisons-Alfort, CENERV., Nouakchott.
[37] Boutrais, J. 197. Les conditions naturelles de l’élevage sur le plateau de l’Adamaoua (Cameroun)”, Cahiers ORSTOM, Série Sci. Hum. XV (2): 145-198.
[38] Brabant, P. & Humbel, F. X. 1974. Notice explicative de la carte pédologique de Poli, No. 51, Carte au 1/50000e, Yaoundé.
[39] Yonkeu, S. 1993. Végétation des pâturages de l’Adamaoua (Cameroun): écologie et potentialités pastorales. Thèse de Doctorat, Université de Rennes, France, pp. 207.
[40] Mapongmetsem, P. M., Nkongmeneck, B. A., Rongoumi, G., Dongock, D. & Dongmo, B. 2011. Impact des systèmes d’utilisation des terres sur la conservation de Vitellaria paradoxa Gaertn. (Sapotaceae) dans la région des savanes soudano-guinéennes. International Journal of Environmental Studies. 68 (6): 51-72.
[41] Picard, N., Rutishauser, E., Ploton, P., Ngomanda, A. & Henry, M. 2015. Should Tree Biomass Allometry Be Restricted to Power Models? Forest Ecology and Management. 353: 156-163.
[42] 42] Lotfi, A. 2008. Durabilité écologique des paysages agricoles et production de bois, bocage et néobocage. Disertation, Rennes: Université de Rennes 1.
[43] Nelson, B. W., Mesquita, R., Pereira, J. L. G., de Souza, S. G. A., Batista, G. T. & Couto, L. B. 1999. Allometric Regressions for Improved Estimate of Secondary Forest Biomass in the Central Amazon. Foresr Ecology and Management. 117: 149-167.
[44] Henry, M., Picard, N., Trotta, C., Manlay, R., Valentini, R., Bernoux, M. & Saint-André, L. 2012. Estimating tree biomass of sub-Saharan African forests: a review of available allometric equations. Silva Fennica. 45 (3B): 477–569.
[45] Djomo, A. N., Picard, N., Fayolle, A., Henry, M., Ngomanda, A., Ploton, P., McLellan, J., Saborowski, J., Ibrahima, A. & Lejeune, P. 2016. Tree Allometry for Estimation of Carbon Stocks in African Tropical Forests. Forestry. 89: 446-455.
[46] Parresol, B. R. 1999. Assessing Tree and Stand Biomass: A Review with Examples and Critical Comparisons. Forest Science. 45: 573-593.
[47] Djomo, N. A. & Chimi, D. C. 2017. Tree Allometric Equations for Estimation of Above, Below and Total Biomass in a Tropical Moist Forest: Case Study with Application to Remote Sensing. Forest Ecology and Management. 391: 184-193.
[48] 48] Fayolle, A., Doucet, J. L., Bourland, N. & Lejeune, P. 2013. Tree allometry in Central Africa: Testing the validity of pantropical multi-species allometric equations for estimating biomass and carbon stocks. Forest Ecology and Management. 305: 29-37.
[49] Bagnoud, N. & Kouyaté, A. M. 1996. Estimation du volume de bois des formations savanicoles de la zone soudanienne (cercle de Sikasso) -Tarifs de cubage pour quelques espèces ligneuses et relations dendrométriques pour le bois de feu. Document Appui à la Recherche Forestière de Sikasso (ARFS) 96/3, Ministère du développement rural et de l'environnement, Institut d'Économie Rurale, pp. 86-88.
[50] Traoré, S., Djomo, A. N., N’guessan, A. K., Coulibaly, B., Ahoba, A., Gnahoua, G. M., N’guessan, É. K., Adou Yao, C. Y., N’Dja, J. K. & Guédé N. Z. 2018. Stand Structure, Allometric Equations, Biomass and Carbon Sequestration Capacity of Acacia mangium Wild. (Mimosaceae) in Côte d’Ivoire. Open Journal of Forestry. 8: 42-60.
[51] Vahedi, A. A., Mataji, A., Babayi-kafaki, S., Eshaghi-rad, J., Hodjati, S. M. & Djomo, A. N. 2014. Allometric equation for predicting aboveground biomass of beech-hornbeam stands in the Hyrcanian forests of Iran. Journal of Forest science. 60 (6): 236-246.
[52] Peltier, R., Forkong, C. N., Mama, F., Ntoupka, M., Manlay, R., Henry, M. & Morillon, V. 2007. Évaluation du stock de carbone et de la productivité en bois d’un parc à karités du Nord Cameroun. Revue Bois et Forêts des Tropiques. 294 (4): 12.
[53] Larwanou, M., Yemshaw, Y. & Saâdou, M. 2010. Prediction models for estimating foliar and fruit dry biomasses of five Savannah tree species in the West African Sahel. International Journal of Biological and Chemical Sciences. 4 (6): 2245-2256.
[54] Ebuy, J., Lokombé Dimandja, J. P., Ponette, Q., Sonwa, D. & Picard, N. 2011. Biomass equation for predicting tree aboveground biomass at Yangambi, RDC. Journal of Tropical Forest Science. 23 (2): 125–132. DOI: 10.1088/1748–9326/3/4/045011.
[55] Poupon, H. 1985. Structure et dynamique de la strate ligneuse d’une steppe sahélienne au Nord du Sénégal. Thèse Science Naturelles, Université de Paris Sud, ORSAY. Travaux et Document de L’ORSTOM, 351p.
[56] Eumont, E. 2011. Analyse de la biomasse racinaire d’Abies concolor en Sierra Nevada grâce à la technologie LiDAR et au traitement d’images. Mémoire de master Nancy-université 26p.
[57] GIEC. 2006. Guide pour l’inventaire national des gaz à effet de serre, agriculture, foresterie et autre usage des terres. Institute for Global Environnemental Strategies, Japon. 4: 46-52.
[58] Tchobsala & Mbolo, M., 2013. Characterization and impact of wood logging on plant formations in Ngaoundéré District, Adamawa Region, Cameroon. Journal of Ecology and the Natural Environment. 5 (10): 265-277.
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    Tchindebe Alexandre, Ibrahima Adamou, Tchobsala, Mohamadou Laminou Mal Amadou. (2019). Allometric Equations for Predicting Biomass of Daniellia oliveri (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon. Ecology and Evolutionary Biology, 4(2), 15-22. https://doi.org/10.11648/j.eeb.20190402.11

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    Tchindebe Alexandre; Ibrahima Adamou; Tchobsala; Mohamadou Laminou Mal Amadou. Allometric Equations for Predicting Biomass of Daniellia oliveri (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon. Ecol. Evol. Biol. 2019, 4(2), 15-22. doi: 10.11648/j.eeb.20190402.11

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    Tchindebe Alexandre, Ibrahima Adamou, Tchobsala, Mohamadou Laminou Mal Amadou. Allometric Equations for Predicting Biomass of Daniellia oliveri (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon. Ecol Evol Biol. 2019;4(2):15-22. doi: 10.11648/j.eeb.20190402.11

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  • @article{10.11648/j.eeb.20190402.11,
      author = {Tchindebe Alexandre and Ibrahima Adamou and Tchobsala and Mohamadou Laminou Mal Amadou},
      title = {Allometric Equations for Predicting Biomass of Daniellia oliveri (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon},
      journal = {Ecology and Evolutionary Biology},
      volume = {4},
      number = {2},
      pages = {15-22},
      doi = {10.11648/j.eeb.20190402.11},
      url = {https://doi.org/10.11648/j.eeb.20190402.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.eeb.20190402.11},
      abstract = {Allometric relationships for estimating biomass of Daniellia oliveri (Rolfe) Hutch & Dalz. stand were investigated in the sudano-guinea savannah of Ngaoundere, Cameroon. A total of 17 individual trees from Daniellia oliveri were harvested in Bini-Dang savannah across a range of diameter classes, from 5 to 40 cm. Diameter at breast height (D) and total height (H) were determined and considered as predictor variables, while total above-ground biomass, stem, branch, leaf and root biomass were the output variables of the allometric models. Among many models tested, the best ones were chosen according to the coefficient of determination adjusted (R2adj), the residual standard error (RSE) and the Akaike Information Criteria. The main results showed that the multiplication of tree H with D in the allometric equation did not improve in the degree of fitness of the allometric equations, except for leaf biomass. The fit allometric biomass of Daniellia oliveri model for leaf, branch, stem and root biomass and above ground biomass were the follow: Ln(Bl)= 3.0303 + 0.744*Ln(D2H); Ln(Bb) = 3.772 + 2.701*Ln(D); Ln(Bs) = 2.663 + 2.218*Ln(D), Ln(Br) = 2.072 + 1.920*Ln(D) and Ln(Bt) = -2.089 + 2.374*Ln(D) respectively. The root biomass represented on average 28% of the total aboveground biomass and these two biomasses were positively and significantly correlated (r = 0.93, p ˂ 0.05 and n = 11). For the Daniellia oliveri stands studied, the diameter at breast height (D) alone showed a very strong accuracy of estimation. It is concluded that the use of tree height in the allometric equation can be neglected for the species, as far as the present study area is concerned. Therefore, for estimating the biomass of Daniellia oliveri, the use of D as an independent variable in the allometric equation with a power equation would be recommended. The paper describes details of tree biomass allometry, which is important in carbon stock, sylviculture and savannah management.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Allometric Equations for Predicting Biomass of Daniellia oliveri (Rolfe) Hutch. & Dalz. Stands in the Sudano-Guinea Savannahs of Ngaoundere, Cameroon
    AU  - Tchindebe Alexandre
    AU  - Ibrahima Adamou
    AU  - Tchobsala
    AU  - Mohamadou Laminou Mal Amadou
    Y1  - 2019/08/10
    PY  - 2019
    N1  - https://doi.org/10.11648/j.eeb.20190402.11
    DO  - 10.11648/j.eeb.20190402.11
    T2  - Ecology and Evolutionary Biology
    JF  - Ecology and Evolutionary Biology
    JO  - Ecology and Evolutionary Biology
    SP  - 15
    EP  - 22
    PB  - Science Publishing Group
    SN  - 2575-3762
    UR  - https://doi.org/10.11648/j.eeb.20190402.11
    AB  - Allometric relationships for estimating biomass of Daniellia oliveri (Rolfe) Hutch & Dalz. stand were investigated in the sudano-guinea savannah of Ngaoundere, Cameroon. A total of 17 individual trees from Daniellia oliveri were harvested in Bini-Dang savannah across a range of diameter classes, from 5 to 40 cm. Diameter at breast height (D) and total height (H) were determined and considered as predictor variables, while total above-ground biomass, stem, branch, leaf and root biomass were the output variables of the allometric models. Among many models tested, the best ones were chosen according to the coefficient of determination adjusted (R2adj), the residual standard error (RSE) and the Akaike Information Criteria. The main results showed that the multiplication of tree H with D in the allometric equation did not improve in the degree of fitness of the allometric equations, except for leaf biomass. The fit allometric biomass of Daniellia oliveri model for leaf, branch, stem and root biomass and above ground biomass were the follow: Ln(Bl)= 3.0303 + 0.744*Ln(D2H); Ln(Bb) = 3.772 + 2.701*Ln(D); Ln(Bs) = 2.663 + 2.218*Ln(D), Ln(Br) = 2.072 + 1.920*Ln(D) and Ln(Bt) = -2.089 + 2.374*Ln(D) respectively. The root biomass represented on average 28% of the total aboveground biomass and these two biomasses were positively and significantly correlated (r = 0.93, p ˂ 0.05 and n = 11). For the Daniellia oliveri stands studied, the diameter at breast height (D) alone showed a very strong accuracy of estimation. It is concluded that the use of tree height in the allometric equation can be neglected for the species, as far as the present study area is concerned. Therefore, for estimating the biomass of Daniellia oliveri, the use of D as an independent variable in the allometric equation with a power equation would be recommended. The paper describes details of tree biomass allometry, which is important in carbon stock, sylviculture and savannah management.
    VL  - 4
    IS  - 2
    ER  - 

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Author Information
  • Department of Biological Sciences, Faculty of Sciences, the University of Ngaoundere, Ngaoundere, Cameroon

  • Department of Biological Sciences, Faculty of Sciences, the University of Ngaoundere, Ngaoundere, Cameroon