Agroforestry Systems

, Volume 93, Issue 3, pp 1119–1132 | Cite as

Aboveground biomass allometric equations and carbon content of the shea butter tree (Vitellaria paradoxa C.F. Gaertn., Sapotaceae) components in Sudanian savannas (West Africa)

  • Kangbéni DimobeEmail author
  • Dethardt Goetze
  • Amadé Ouédraogo
  • Sylvanus Mensah
  • Koffi Akpagana
  • Stefan Porembski
  • Adjima Thiombiano


Vitellaria paradoxa is one of the most economically important trees in West Africa. Although being a key component of most sub-Sahara agroforestry systems, little information and argument exist regarding its biomass and carbon potential. Here, we developed biomass equations for V. paradoxa tree components in Sudanian savannas. A destructive sampling approach was applied, which was based on measuring stem, branch and foliage biomass of thirty individual trees selected from a wide spectrum of diameter at breast height (dbh) and tree height (h). Basal diameter (d20), dbh, h and crown diameter (cd) were measured and used as predictors in biomass equations. Carbon content was estimated using the ash method. Variance explained in biomass allometric equations ranged from 81 to 98%, and was lower for foliage than for branch and stem biomass models, suggesting that leaf allometries are less responsive to tree size than branch and stem allometries. Stem biomass was best predicted by d20, branch biomass by dbh, and leaf biomass by crown diameter. For aboveground biomass, adding height to dbh as compound variable (dbh2 × h) did not make any significant change, as compared with model based on dbh alone. However, adding crown diameter to dbh and height reduced the error by 15% and improved model fits. Carbon contents in V. paradoxa foliage, branch and stem were 55.29, 55.37 and 55.82%, respectively, and higher than reference value suggested by the IPCC. Established allometric equations can be used to accurately predict aboveground biomass of the species in the Sudanian savannas of West Africa.


Allometry Biomass uncertainty Crown diameter Destructive sampling Estimation error Semi-arid area 



The authors express their gratitude to the German Federal Ministry of Education and Research (BMBF) through the program WASCAL (West African Science Service Center on Climate Change and Adapted Land Use, for funding this research. The authors are very grateful to the Ministry of Environment of Burkina Faso for the permission to cut trees in the study sites, and to work in protected areas. Our thanks are extended to the field assistants and local people who helped in data collection. Finally, we would like to thank the anonymous reviewers for their helpful comments that greatly improved this article.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Allen SE, Grimshaw HM, Rowland AP (1986) Chemical analysis. In: Moore PD, Chapman SB (eds) Methods of plant ecology. Blackwell, Oxford, pp 285–344Google Scholar
  2. Alvarez E, Duque A, Saldarriaga J, de las Salas G, del Valle I, Lema A, Moreno F, Orrego S, Rodríguez L (2012) Tree above-ground biomass allometries for carbon stocks estimation in the natural forests of Colombia. For Ecol Manag 267:297–308CrossRefGoogle Scholar
  3. Antin C, Pélissier R, Vincent G, Couteron P (2013) Crown allometries are less responsive than stem allometry to tree size and habitat variations in an Indian monsoon forest. Trees 27:1485–1495CrossRefGoogle Scholar
  4. Arbonnier M (2002) Arbres, arbustes et lianes des zones sèches d’Afrique de l’Ouest. VersaillesGoogle Scholar
  5. Baker TR, Phillips OL, Malhi Y, Almeida S, Arroyo L, Di Fiore A, Erwin T, Killeen TJ, Laurance SG, Laurance WF (2004) Variation in wood density determines spatial patterns in Amazonian forest biomass. Glob Change Biol 10:545–562CrossRefGoogle Scholar
  6. Baskerville G (1972) Use of logarithmic regression in the estimation of plant biomass. Can J For Res 2:49–53CrossRefGoogle Scholar
  7. Basuki TM, Van Laake PE, Skidmore AK, Hussin YA (2009) Allometric equations for estimating the above-ground biomass in tropical lowland Dipterocarp forests. For Ecol Manage 257:1684–1694CrossRefGoogle Scholar
  8. Bayala J, Ouédraogo S, Ong C (2009) Early growth performance and water use of planted West African provenances of Vitellaria paradoxa C.F. Gaertn (karité) in Gonsé, Burkina Faso. Agrofor Syst 75:117–127CrossRefGoogle Scholar
  9. Bayen P, Bognounou F, Lykke AM, Ouédraogo M, Thiombiano A (2015) The use of biomass production and allometric models to estimate carbon sequestration of Jatropha curcas L. plantations in western Burkina Faso. Environ Dev Sustain. Google Scholar
  10. Boffa J-M (2015) Opportunities and challenges in the improvement of the shea (Vitellaria paradoxa) resource and its management Occasional Paper 24. World Agroforestry Centre, NairobiGoogle Scholar
  11. Brown S (1997) Estimating biomass and biomass change of tropical forests: a primer. Food & Agriculture Organization, RomeGoogle Scholar
  12. Brown S (2002) Measuring carbon in forests: current status and future challenges. Environ Pollut 116:363–372CrossRefGoogle Scholar
  13. Brown S, Gillespie AJR, Lugo AE (1989) Biomass estimation methods for tropical forests with applications to forest inventory data. For Sci 35:881–902Google Scholar
  14. Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach. Springer Science & Business Media, New YorkGoogle Scholar
  15. Cai S, Kang X, Zhang L (2013) Allometric models for aboveground biomass of ten tree species in northeast China. Ann For Res 56:105–122Google Scholar
  16. Chambers JQ, dos Santos J, Ribeiro RJ, Higuchi N (2001) Tree damage, allometric relationships, and above-ground net primary production in central Amazon forest. For Ecol Manag 152:73–84CrossRefGoogle Scholar
  17. Chauhan SK, Gupta N, Ritu Yadav S, Chauhan R (2009) Biomass and carbon allocation in different parts of agroforestry tree species. Indian For 135(7):981–993Google Scholar
  18. Chauhan SK, Sharma SC, Beri V, Ritu Yadav S, Gupta N (2010) Yield and carbon sequestration potential of wheat (Triticum aestivum) and poplar (Populus deltoides) based agri-silvicultural system. Indian J Agric Sci 80(2):129–135Google Scholar
  19. Chauhan SK, Sharma R, Sharma SC, Gupta N, Ritu (2012) Evaluation of poplar (Populus deltoides Bartr. Ex Marsh.) boundary plantation based agri-silvicultural system for wheat-paddy yield and carbon storage. Int J Agric For 2(5):239–246Google Scholar
  20. Chave J, Condit R, Aguilar S, Hernandez A, Lao S, Perez R (2004) Error propagation and scaling for tropical forest biomass estimates. Philos Trans R Soc B Biol Sci 359:409–420CrossRefGoogle Scholar
  21. Chave J, Andale C, Brown S, Cairns MA, Chambers JQ, Eamus D, Fölster H, Fromard F, Higuchi N, Kira T, Lescure JP, Nelson BW, Ogawa H, Puig H, Riéra B, Yamakura T (2005) Tree allometry and improved estimation of carbon stock and balance in tropical forests. Oecologia 145:87–99CrossRefGoogle Scholar
  22. Chave J, Rejou Mechain M, Burquez A, Chidumayo E, Colgan MS, Delitti WBC, Duque A, Eid T, Fearnside PM, Goodman RC, Henry M, Martinez-Yrizar A, Mugasha WA, Muller-Landau HC, Mencuccini M, Nelson BW, Ngomanda A, Nogueira EM, Ortiz-Malavassi E, Pélissier R, Ploton P, Ryan CM, Saldarriaga JG, Vieilledent G (2014) Improved allometic models to estimate the above ground biomass of tropical trees. Global Change Biol 20:3177–3190CrossRefGoogle Scholar
  23. Djomo AN, Picard N, Fayolle A, Henry M, Ngomanda A, Ploton P, McLellan J, Saborowski J, Adamou I, Lejeune P (2016) Tree allometry for estimation of carbon stocks in African tropical forests. Forestry 89:446–455CrossRefGoogle Scholar
  24. Driessen P, Deckers J, Spaargaren O, Nachtergaele F (2001) In: Lecture notes on the major soils of the world. Food and Agriculture Organization (FAO), RomeGoogle Scholar
  25. Elias M, Potvin C (2003) Assessing inter-and intra-specific variation in trunk carbon concentration for 32 neotropical tree species. Can J For Res 33(6):1039–1045CrossRefGoogle Scholar
  26. Fang Z, Bailey RL (1998) Height–diameter models for tropical forests on Hainan Island in southern China. For Ecol Manag 110:315–327CrossRefGoogle Scholar
  27. Fayolle A, Doucet JL, Gillet JF, 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. For Ecol Manage 305:29–37CrossRefGoogle Scholar
  28. Feldpausch TR, Banin L, Phillips OL, Baker TR, Lewis SL, Quesada CA, Affum-Baffoe K, Arets EMM, Berry NJ, Bird M, Brondizio ES, de Camargo P, Chave J, Djagbletey G, Domingues TF, Drescher M, Fearnside PM, Franca MB, Fyllas NM, Lopez-Gonzalez G, Hladik A, Higuchi N, Hunter MO, IidaY Salim KA, Kassim AR, Keller M, Kemp J, King DA, Lovett JC, Marimon BS, Marimon-Junior BH, Lenza E, Marshall AR, Metcalfe DJ, Mitchard ETA, Moran EF, Nelson BW, Nilus R, Nogueira EM, Palace M, Patino S, Peh KSH, Raventos MT, Reitsma JM, Saiz G, Schrodt F, Sonke B, Taedoumg HE, Tan S, White L, Woll H, Lloyd J (2010) Height–diameter allometry of tropical forest trees. Biogeosci Discuss 7:7727–7793CrossRefGoogle Scholar
  29. Fonseca W, Alice FE, Rey-Benayas JM (2012) Carbon accumulation in aboveground and belowground biomass and soil of different age native forest plantations in the humid tropical lowlands of Costa Rica. New For 43(2):197–211CrossRefGoogle Scholar
  30. Fontès J, Guinko S (1995) Carte de la végétation et de l’occupation du sol du Burkina Faso. Notice explicative. Ministère de la Coopération Française. Projet Campus (88 313 101), ToulouseGoogle Scholar
  31. Ganeshaiah K, Barve N, Nath N, Chandrashekara K, Swamy M, Shaanker R (2003) Carbon allocation in different components of some tree species of India: a new approach for carbon estimation. Curr Sci 85(11):1528Google Scholar
  32. Gower ST, Kucharik CJ, Norman JM (1999) Direct and indirect estimation of leaf area index, f APAR, and net primary production of terrestrial ecosystems. Remote Sens Environ 70:29–51CrossRefGoogle Scholar
  33. Henry M, Picard N, Trotta C, Manlay RJ, Valentini R, Bernoux M, Saint-André L (2011) Estimating tree biomass of sub-Saharan African forests: a review of available allometric equations. Silva Fenn 45(3B):477–569CrossRefGoogle Scholar
  34. Hoen HF, Solberg B (1994) Potential and economic efficiency of carbon sequestration in forest biomass through silvicultural management. For Sci 40(3):429–451Google Scholar
  35. IPCC (2007) Climate change: mitigation. Contribution of Working Group III to the Fourth Assessment ReportGoogle Scholar
  36. Jana BK, Biswas S, Majumder M, Roy PK, Mazumdar A (2009) Comparative assessment of carbon sequestration rate and biomass carbon potential of young Shorea robusta and Albizzia lebbek. Int J Hydro-Clim Eng Assoc Water Enviro-Model 1:1–15Google Scholar
  37. Jasaw GS, Saito O, Takeuchi K (2015) Shea (Vitellaria paradoxa) butter production and resource use by urban and rural processors in Northern Ghana. Sustainability 7:3592–3614CrossRefGoogle Scholar
  38. Jibrin A, Abdulkadir A (2015) Allometric models for biomass estimation in Savanna Woodland Area, Niger State, Nigeria. Int J Environ Chem Ecol Geol Geophys Eng 9:270–278Google Scholar
  39. Ketterings QM, Coe R, van Noordwijk M, Palm CA (2001) Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests. For Ecol Manag 146:199–209CrossRefGoogle Scholar
  40. Kraenzel M, Castillo A, Moore T, Potvin C (2003) Carbon storage of harvest-age teak (Tectona grandis) plantations, Panama. For Ecol Manag 173(1):213–225CrossRefGoogle Scholar
  41. Kuyah S, Dietz J, Muthuri C, Jamnadass R, Mwangi P, Coe R, Neufeldt H (2012) Allometric equations for estimating biomass in agricultural landscapes: II. Belowground biomass. Agric Ecosyst Environ 158:225–234CrossRefGoogle Scholar
  42. Lamien N, Ouédraogo SJ, Diallo OB, Guinko S (2004) Productivité fruitière du karité (Vitellaria paradoxa Gaertn. CF, Sapotaceae) dans les parcs agroforestiers traditionnels au Burkina Faso. Fruits 59:423–429CrossRefGoogle Scholar
  43. Litton CM, Boone Kauffman J (2008) Allometric models for predicting aboveground biomass in two widespread woody plants in Hawaii. Biotropica 40:313–320CrossRefGoogle Scholar
  44. Lovett P (2004) The shea butter value chain: production, transformation and marketing in West Africa. Technical Report No. 2, USAID West Africa Trade HubGoogle Scholar
  45. Lovett PN, Haq N (2000) Evidence for anthropic selection of the sheanut tree (Vitellaria paradoxa). Agrofor Syst 48:273–288CrossRefGoogle Scholar
  46. Mbow C, Verstraete MM, Sambou B, Diaw AT, Neufeldt H (2013) Allometric models for aboveground biomass in dry savanna trees of the Sudan and Sudan-Guinean ecosystems of Southern Senegal. J For Res 19:340–347CrossRefGoogle Scholar
  47. Mensah S, Veldtman R, du Toit B, Glèlè Kakaï R, Seifert T (2016a) Aboveground biomass and carbon in a South African mistbelt forest and the relationships with tree species diversity and forest structures. Forests 7:79CrossRefGoogle Scholar
  48. Mensah S, Glèlè Kakaï R, Seifert T (2016b) Patterns of biomass allocation between foliage and woody structure: the effects of tree size and specific functional traits. Ann For Res 59(1):49–60CrossRefGoogle Scholar
  49. Mensah S, Veldtman R, Seifert T (2017) Allometric models for height and aboveground biomass of dominant tree species in South African Mistbelt forests. South For J For Sci 79(1):19–30CrossRefGoogle Scholar
  50. Meyer T, D’Odorico P, Okin GS, Shugart HH, Caylor KK, O’Donnell FC, Bhattachan A, Dintwe K (2014) An analysis of structure: biomass structure relationships for characteristic species of the western Kalahari, Botswana. Afr J Ecol 52:20–29CrossRefGoogle Scholar
  51. Montagu KD, Düttmer K, Barton CVM, Cowie AL (2005) Developing general allometric relationships for regional estimates of carbon sequestration—an example using Eucalyptus pilularis from seven contrasting sites. For Ecol Manage 204:115–129CrossRefGoogle Scholar
  52. Morote FAG, Serrano FRL, Andrés M, Rubio E, Jimenez JLG, de las Heras J (2012) Allometries, biomass stocks and biomass allocation in the thermophilic Spanish juniper woodlands of Southern Spain. For Ecol Manag 270:85–93CrossRefGoogle Scholar
  53. Návar J (2009) Biomass component equations for Latin American species and groups of species. Ann For Sci 66:1–21CrossRefGoogle Scholar
  54. Ngomanda A, Engone Obiang N, Lebamba J, Moundounga Mavouroulou Q, Gomat H, Mankou GS, Loumeto J, Midoko Iponga D, Kossi Ditsouga F, Zinga Koumba R, Botsika Bobé KH, Mikala Okouyi C, Nyangadouma R, Lépengué N, Mbatchi B, Picard N (2014) Site specific versus pantropical allometric equations: which option to estimate the biomass of a moist central African forest? For Ecol Manag 312:1–9CrossRefGoogle Scholar
  55. Nogueira EM, Fearnside PM, Nelson BW, Barbosa RI, Keizer EWH (2008) Estimates of forest biomass in the Brazilian Amazon: new allometric equations and adjustments to biomass from wood-volume inventories. For Ecol Manag 256:1853–1867CrossRefGoogle Scholar
  56. Paustian K, Cole CV, Sauerbeck D, Sampson N (1998) CO2 mitigation by agriculture: an overview. Clim Change 40:135–162CrossRefGoogle Scholar
  57. Peichl M, Arain MA (2006) Above-and belowground ecosystem biomass and carbon pools in an age-sequence of temperate pine plantation forests. Agric For Meteorol 140:51–63CrossRefGoogle Scholar
  58. Picard N, Rutishauser E, Ploton P, Ngomanda A, Henry M (2015) Should tree biomass allometry be restricted to power models? For Ecol Manag 353:156–163CrossRefGoogle Scholar
  59. Ploton P, Barbier N, Momo ST, Réjou-Méchain M, Boyemba Bosela F, Chuyong GB, Dauby G, Droissart V, Fayolle A, Goodman RC (2016) Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries. Biogeosciences 13:1571–1585CrossRefGoogle Scholar
  60. Poulsen G (1981) Important forest products in Africa other than wood-a preliminary study (Project Report RAF/78/025)Google Scholar
  61. Preece ND, Lawes MJ, Rossman AK, Curran TJ, Van Oosterzee P (2015) Modelling the growth of young rainforest trees for biomass estimates and carbon sequestration accounting. For Ecol Manage 351:57–66CrossRefGoogle Scholar
  62. R Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.
  63. Redondo-Brenes A (2007) Growth, carbon sequestration, and management of native tree plantations in humid regions of Costa Rica. New For 34(3):253–268CrossRefGoogle Scholar
  64. Sarmiento G, Pinillos M, Garay I (2005) Biomass variability in tropical American lowland rainforests. Ecotropicos 18(1):1–20Google Scholar
  65. Sharma R, Chauhan SK, Tripathi AM (2016) Carbon sequestration potential in agroforestry system in India: an analysis for carbon project. Agrofor Syst 90(4):631–644CrossRefGoogle Scholar
  66. Shirima DD, Munishi PKT, Lewis SL, Burgess ND, Marshall AR, Balmford A, Swetnam RD, Zahabu EM (2011) Carbon storage, structure and composition of miombo woodlands in Tanzania’s Eastern Arc Mountains. Afr J Ecol 49:332–342CrossRefGoogle Scholar
  67. Sileshi GW (2014) A critical review of forest biomass estimation models, common mistakes and corrective measures. For Ecol Manag 329:237–254CrossRefGoogle Scholar
  68. Smith P, Martino D, Cai Z, Gwary D, Janzen H, Kumar P, McCarl B, Ogle S, O’Mara F, Rice C (2008) Greenhouse gas mitigation in agriculture. Philos Trans R Soc B Biol Sci 363:789–813CrossRefGoogle Scholar
  69. Thomson AM, Calvin KV, Chini LP, Hurt G, Edmonds JA, Bond-Lamberty B, Frolking S, Wise MA, Janetos AC (2010) Climate mitigation and the future of tropical landscapes. Proc Natl Acad Sci USA 107:19633–19638CrossRefGoogle Scholar
  70. UNFCCC (2006) Report of the conference of the Parties serving as the meeting of the Parties to the Kyoto Protocol. 103Google Scholar
  71. Vahedi AA, Mataji A, Babayi-Kafaki S, Eshaghi-Rad J, Hodjati SM, Djomo A (2014) Allometric equations for predicting aboveground biomass of beech-hornbeam stands in the Hyrcanian forests of Iran. J For Sci 60:236–247CrossRefGoogle Scholar
  72. Wani NR, Qaisar KN (2014) Carbon percent in different components of tree species and soil organic carbon pool under these tree species in Kashmir Valley Current World Environment 9Google Scholar
  73. White F (1986) La végétation de l’Afrique-Recherches sur les ressources naturelles. Orstom-Unesco, ParisGoogle Scholar
  74. Xiang W, Zhou J, Ouyang S, Zhang S, Lei P, Li J, Deng X, Fang X, Forrester DI (2016) Species-specific and general allometric equations for estimating tree biomass components of subtropical forests in southern China. Eur J For Res 135:963–979CrossRefGoogle Scholar
  75. Zeng WS, Zhang HR, Tang SZ (2011) Using the dummy variable model approach to construct compatible single-tree biomass equations at different scales—a case study for Masson pine (Pinus massoniana) in southern China. Can J For Res 41:1547–1554CrossRefGoogle Scholar
  76. Zianis D, Mencuccini M (2004) On simplifying allometric analyses of forest biomass. For Ecol Manag 187:311–332CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.UFR-SVT, Laboratory of Plant Biology and EcologyUniversity Ouaga1 Pr Joseph Ki-ZerboOuagadougou 03Burkina Faso
  2. 2.Department of Botany, Institute of Biological SciencesUniversity of RostockRostockGermany
  3. 3.Laboratory of Botany and Plant Ecology, Department of BotanyUniversity of LoméLoméTogo
  4. 4.Laboratory of Biomathematics and Forest EstimationsUniversity of Abomey-CalaviAbomey-CalaviBenin
  5. 5.Department of Forest and Wood ScienceStellenbosch UniversityMatielandSouth Africa

Personalised recommendations