Agroforestry Systems

, Volume 92, Issue 1, pp 183–194 | Cite as

Exploration of the aboveground carbon sequestration and the growth estimation models of four species in agroforestry system of semi-arid region, Myanmar



Carbon sequestration in agroforestry systems plays an important role for climate change regulation. Policy makers make use of growth models for carbon estimations of the large scale projects in designing regulation. This study revealed the aboveground carbon sequestration potentials and established allometric growth models of four species in agroforestry. Based on the results, the aboveground carbon storages of Morinda tinctoria Roxb., Terminalia oliveri Brandis., Rhus paniculata Wall. and Emblica officinalis Gaertn. were 6.88, 6.59, 4.34 and 3.53 kg C tree−1, respectively. In comparison between two types of agroforestry, a mixture of M. tinctoria and E. officinalis had a higher carbon sequestration potential (1331 kg C ha−1) than a mixture of R. paniculata and T. oliveri (1151.40 kg C ha−1). A hyperbolic growth model and a basic quadratic model were the best-fit models for R. paniculata and E. officinalis, respectively, while a basic logarithmic model was the best fit for both M. tinctoria and T. oliveri. This study highlighted that both Akaike Information Criterion, Furnival index and coefficient of determination should be taken into consideration for model selection, as opposed to only considering the coefficient of determination. The study also pointed out that a mixture of M. tinctoria and T. oliveri should be considered as a tentative model for agroforestry plantations to enhance the carbon storage in semi-arid area in the future.


Carbon storage Growth model Morinda tinctoria Rhus paniculata Terminalia oliveri Emblica officinalis 



We would like to thank all reviewers and everyone who help our field data collection and arrangement. This work was supported by the 2015 Research Fund of the University of Seoul.


  1. Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723CrossRefGoogle Scholar
  2. Albrecht A, Kandji ST (2003) Carbon sequestration in tropical agroforestry systems. Agric Ecosyst Envion 99:15–27CrossRefGoogle Scholar
  3. Anscombe FJ (1973) Graphs in statistical analysis. Am Stat 27(1):17–21Google Scholar
  4. Appiah M (2013) Tree population inventory, diversity and degradation analysis of a tropical dry deciduous forest in Afram Plain, Ghana. For Ecol Manag 295:145–154CrossRefGoogle Scholar
  5. Bates DM, Watts DG (1980) Relative curvature measures of nonlinearity. J R Stat Soc B 42:1–16Google Scholar
  6. Bayala J, Balesdent J, Marol C, Zapata F, Teklehaimanot Z, Ouedraogo SJ (2006) Relative contribution of trees and crops to soil carbon content in a parkland system in Burkina Faso using variations in natural 13C abundance. Nutr Cycl Agroecosyst 76:193–201CrossRefGoogle Scholar
  7. Boucher D, Elias P, Lininger K, May-Tobin C, Roquemore S, Saxon E (2011) The root of the problem: what’s driving tropical deforestation today?. Union of Concerned Scientists, CambridgeGoogle Scholar
  8. Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach. Springer, New YorkGoogle Scholar
  9. Burnham KP, Anderson DR, Huyvacrt KP (2011) AICc model selection in the ecological and bheavioral sciences: some background, observations and comparisons. Behav Ecol Sociobiol 65:23–35CrossRefGoogle Scholar
  10. Chauhan SK, Chauhan R (2009) Exploring carbon sequestration in poplar-wheat based integrated cropping system. APA News 35:9–10Google Scholar
  11. Curtis RO (1967) Height-diameter and height-diameter-age equations for second-growth Douglas-fir. For Sci 13:365–375Google Scholar
  12. Dry Zone Greening Department (2011) Thirty years master plan. Ministry of Environmental Conservation and Forestry, MyanmarGoogle Scholar
  13. FAO (1997) Estimating biomass and biomass change of tropical forests: a primer. Food and Agriculture Organization of the United Nations, RomeGoogle Scholar
  14. FAO (1999) A statistical manual for forestry research. Food and Agriculture Organization of the United Nations, Regional office for Aisa and the Pacific, Bangkok, ThailandGoogle Scholar
  15. FAO (2010) Global forest resources assessment 2010. Food and Agriculture Organization of the United Nations, RomeGoogle Scholar
  16. FAO (2013) Advancing agroforestry on the policy agenda: A guide for decision makers. In: Buttoud G, Ajayi O, Detlefsen G, Place F, Torquebiau E (eds) Agroforestry working paper no. 1, Food and Agriculture Organization of the United Nations, RomeGoogle Scholar
  17. FAO (2015) FAO assessment of forests and carbon stocks, 1990–2015. FAO, RomeGoogle Scholar
  18. Farr WA, DeMars DJ, Dealy JE (1989) Height and crown width related to diameter for open-grown western hemlock and Sitka spruce. Can J For Res 19:1203–1207CrossRefGoogle Scholar
  19. Feldpausch TR, Banin L, Phillips OL, Baker TR, Lewis SL, Quesada CA, Affum-Baffoe K, Arets EJMM, Berry NJ, Bird M, Brondizio ES et al (2010) Height-diameter allometry of tropical forest trees. Biogeosciences 8:1106–2011Google Scholar
  20. Forest Department (2011) Forestry in Myanmar. Ministry of Environmental Conservation and Forestry, MyanmarGoogle Scholar
  21. Houghton RA (2012) Carbon emissions and the drivers of deforestation and forest degradation in the tropics. SciVerse ScienceDirect 4:597–603Google Scholar
  22. Huang S, Titus SJ, Wiens DP (1992) Comparison of nonlinear height- diameter functions for major Alberta tree species. Can J For Res 22:1297–1304CrossRefGoogle Scholar
  23. Hunde KK (2015) The role of agroforestry system as strategy to adapt and mitigate climate change: a review with examples from tropical and temperate regions. Clim Change 1:20–25Google Scholar
  24. Jain A, Ansari SA (2013) Quantification by allometric equations of carbon sequestered by Tectona grandis in different agroforestry systems. J For Res 24:699–702CrossRefGoogle Scholar
  25. Jose S (2009) Agroforestry for ecosystem services and environmental benefits: an overview. Agrofor Syst 76:1–10CrossRefGoogle Scholar
  26. Jose S, Bardhan S (2012) Agroforestry for biomass production and carbon sequestration: an overview. Agrofor Syst 86:105–111CrossRefGoogle Scholar
  27. Kangkuso A, Jamili J, Septiana A, Raya R, Sahidin I, Rianse U, Rahim S, Alfirman A, Sharma S, Nadaoka K (2016) Allometric models and aboveground biomass of Lumnitzera racemose Willd. forest in Rawa Aopa Watumohai national park, Southeast Sulawesi, Indonesia. For Sci Technol 12(1):43–50Google Scholar
  28. Khaine I, Woo SY (2015) An overview of interrelationship between climate change and forests. For Sci Technol 11(1):11–18Google Scholar
  29. Kumar A, Sharma MP (2015) Estimation of carbon stocks of Balganga Reserved Forest, Uttarakhand, India. For Sci Technol 11(4):177–181Google Scholar
  30. Kyaw NN (2003) Site influence on growth and phenotype of teak (Tectona grandis Linn. F.) in natural forests of Myanmar. PhD Thesis of Der Georg-August-Universität Göttingen, GöttingenGoogle Scholar
  31. Loetsch F, Zohrer F, Haller KE (1973) Forest Inventory, vol 2. BLV Verlagsgesellschaft mBH, MünchenGoogle Scholar
  32. Martinez-Yrizar A, Sarukhan J, Perez-Jimenez A, Rincon E, Maass JM, Solis-Magallanes A, Cervantes L (1992) Above-ground phytomass of a tropical deciduous forest on the coast of Jalisco, Mexico. J Trop Ecol 8:87–96CrossRefGoogle Scholar
  33. Mehtätalo L (2004) A longitudinal height-diameter model for Norway spruce in Finland. Can J For Res 34(1):131–140CrossRefGoogle Scholar
  34. Mehtätalo L (2005) Height-diameter models for scots pine and birch in Finland. Silva Fenn 39(1):55–66CrossRefGoogle Scholar
  35. Meyer HA (1940) A mathematical expression for height curves. J For 38:415–420Google Scholar
  36. Miles L, Newton AC, DeFries RS, Ravilious C, May I, Blyth S, Kapos V, Gordon JE (2006) A global overview of the conservation status of tropical dry forests. J Biogeogr 33:491–505CrossRefGoogle Scholar
  37. Ministry of Forestry of Myanmar (2005) National action programme of Myanmar ot combat desertification in the context of United Nations Convention to Combat Desertification (UNCCD), UNCCDGoogle Scholar
  38. Nair PKR, Nair VD, Kumar BM, Showalter JM (2010) Carbon sequestration in agroforestry systems. Adv Agron 108:237–307CrossRefGoogle Scholar
  39. Nguyen Q, Hoang MH, Öborn J, Noordwijk MV (2013) Multipurpose agroforestry as a climate change resiliency option for farmers: an example of local adaptation in Vietnam. Clim Change 117:241–257CrossRefGoogle Scholar
  40. Nogueira EM, Nelson BW, Fearnside PM, Franҫa MB, de Oliveira ACA (2008) Tree height in Brazil’s ‘arc of deforestation’: shorter trees in south and southwest Amazonia imply lower biomass. For Ecol Manag 255:2963–2972CrossRefGoogle Scholar
  41. Oo TN (2009) Carbon sequestration of tropical deciduous forests and forest plantations in Myanmar. PhD Thesis of Seoul National University, KoreaGoogle Scholar
  42. Palm CA, Vosti SA, Sanchez PA, Ericksen PJ (2005) Slash and burn: the search for alternatives. Columbia University Press, New YorkGoogle Scholar
  43. Rais A, van de Kuilen JWG, Pretzsch H (2014) Growth reaction patterns of tree height, diameter, and volume of Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco) under acute drought stress in Southern Germany. Eur J For Res 133:1043–1056CrossRefGoogle Scholar
  44. Ratkowsky DA, Reedy TJ (1986) Choosing near-linear parameters in the four-parameter logistic model for radioligand and related assays. Biometrics 42:575–582CrossRefPubMedGoogle Scholar
  45. Scaranello MADS, Alves LF, Vieira SA, Camargo PBD, Joly CA, Martinelli LA (2012) Height-diameter relationships of tropical Atalantic moist forest trees in southeastern Braizil. Sci Agric 69:26–37CrossRefGoogle Scholar
  46. Sörensen L, Trux A, Duchrow A, Bodemeyer R (2009) Running dry? Climate change in drylands and how to cope with it. Deutsche Gesellschaft für Technische Zusammenarbeit (GTZ), GmbH, MunichGoogle Scholar
  47. Symonds MRE, Moussalli A (2011) A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion. Behav Ecol Sociobiol 65:13–21CrossRefGoogle Scholar
  48. Tang S (1994) Self-adjusted height-diameter curves and one entry volume model. For Res 7(5):512–518Google Scholar
  49. Temesgen H, Zhang CH, Zhao XH (2014) Modelling tree height-diameter relationships in multi-species and multi-layered forests: a large observational study from Northeast China. For Ecol Manag 316:78–89CrossRefGoogle Scholar
  50. Thakur S, Kumar BM, Kunhamu TK (2015) Coarse root biomass, carbon, and nutrient stock dynamics of different stem and crown classes of silver oak (Grevillea robusta A. Cunn. Ex. R. Br.) plantation in Central Kerala, India. Agrofor Syst 89(5):869–883CrossRefGoogle Scholar
  51. Unruh JD, Haughton PA, Lefebvre PA (1993) Carbon storage in agroforestry: an estimate for sub-Saharan Africa. Clim Res 3:39–52CrossRefGoogle Scholar
  52. Woo SY, Hung TT, Park PS (2011) Stand structure and natural regeneration of degraded forestland in the northern mountainous region of Vietnam. Landsc Ecol Eng 7:251–261CrossRefGoogle Scholar
  53. Wotherspoon A, Thevathasan NV, Gordon AM, Voroney RP (2014) Carbon sequestration potential of five tree species in a 25-year-old temperate tree-based intercropping system in southern Ontario, Canada. Agrofor Syst 88:631–643CrossRefGoogle Scholar
  54. Wykoff WR, Crookston NL, Stage AR (1982) User’s guide to the stand prognosis model. Forest Service, USDA, OgdenCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Department of Environmental HorticultureUniversity of SeoulSeoulKorea

Personalised recommendations