Nutrient Cycling in Agroecosystems

, Volume 114, Issue 1, pp 85–98 | Cite as

Carbon sequestration and nitrogen uptake in a temperate silvopasture system

  • C. DoldEmail author
  • Andrew L. Thomas
  • A. J. Ashworth
  • D. Philipp
  • D. K. Brauer
  • T. J. Sauer
Original Article


Agroforestry systems (AFS) have the potential to foster long-term carbon sequestration and nutrient uptake. Yet, information on sequestration rates is still scarce, especially for AFS in temperate regions and for maturing AFS. This study aims to determine the rate and amount of carbon and nitrogen uptake in a 17-year-old northern red oak (Quercus rubra)–pecan (Carya illinoinensis) silvopastoral planting in Fayetteville, AR, USA. Seven oak and pecan trees were felled to develop AFS-specific allometric equations for above-ground biomass, carbon, and nitrogen. Tree-stand woody biomass (DWw), carbon (Cw) and nitrogen (Nw) and leaf biomass (DWL), carbon (CL), and nitrogen (NL) were calculated with these equations. Diameter at 1.37 m above ground (DBH) was measured annually, and a non-linear mixed-effect model was used to estimate absolute (AGR) and relative growth rates. DWw and Cw was 7.1 and 3.4 Mg ha−1 for pecan and 26.6 and 12.7 Mg ha−1 for oak, which corresponds to a carbon sequestration rate of 0.75 and 0.20 Mg C ha−1 yr−1, respectively. Total N uptake was approximately 66 and 71 g N tree−1 yr−1 for oak and pecan. The mixed-effect model with individual-tree-level random effects for all parameters provided the best representation of DBH growth of oak and pecan, likely due to the high heterogeneity of site characteristics. The AGR explained the non-linear plant growth and reached its maximum of 0.017 and 0.0179 m yr−1 for oak and pecan, respectively, 11 years after planting. This suggests that carbon and nitrogen uptake also declined after 11 years.


Quercus rubra Carya illinoinensis Carbon sequestration Nitrogen uptake Mixed effect models Allometric equations 



The authors wish to thank C. E. T. Paine, University of Stirling, UK, who gave valuable insight to the application of mixed effect models in R. This research was supported in part by an appointment to the Agricultural Research Service (ARS) Research Participation Program administered by the Oak Ridge Institute for Science and Education (ORISE) through an interagency agreement between the US Department of Energy (DOE) and the US Department of Agriculture (USDA). ORISE is managed by ORAU under DOE contract number DE-AC05-06OR23100. All opinions expressed in this paper are the author’s and do not necessarily reflect the policies and views of USDA, ARS, DOE, or ORAU/ORISE. This work was partially funded through the Center for Agroforestry, University of Missouri under cooperative agreements with the USDA-ARS Dale Bumpers Small Farm Research Center, Booneville, AR. The authors also thank Dr. David Burner (USDA-ARS), the technical staff of USDA-ARS (Kevin Jensen, Kent Heikens, Gavin Simmons, and Forrest Goodman), as well as student assistants from the University of Missouri (Samuel Sergent and Matthew Cruise) for their help in the field and lab.


  1. Adame P, Hynynen J, Cañellas I, del Río M (2008) Individual-tree diameter growth model for rebollo oak (Quercus pyrenaica Willd.) coppices. For Ecol Manag 255:1011–1022. CrossRefGoogle Scholar
  2. Adhikari K, Owens PR, Ashworth AJ, Sauer TJ, Libohova Z, Richter JL, Miller DM (2018) Topographic controls on soil nutrient variations in a silvopasture system. AGE 1(1):1–15CrossRefGoogle Scholar
  3. Baah-Acheamfour M, Carlyle CN, Lim S-S, Bork EW, Chang SX (2016) Forest and grassland cover types reduce net greenhouse gas emissions from agricultural soils. Sci Total Environ 571:1115–1127. CrossRefGoogle Scholar
  4. Baskerville GL (1972) Use of logarithmic regression in the estimation of plant biomass. Can J For Res 2:49–53. CrossRefGoogle Scholar
  5. Borden KA, Anglaaere LCN, Adu-Bredu S, Isaac ME (2017) Root biomass variation of cocoa and implications for carbon stocks in agroforestry systems. Agrofor Syst. Google Scholar
  6. Chojnacky DC, Heath LS, Jenkins JC (2014) Updated generalized biomass equations for North American tree species. Forestry 87:129–151CrossRefGoogle Scholar
  7. Clifford D, Cressie N, England JR, Roxburgh SH, Paul KI (2013) Correction factors for unbiased, efficient estimation and prediction of biomass from log–log allometric models. For Ecol Manag 310:375–381. CrossRefGoogle Scholar
  8. Coyle DR, Coleman MD (2005) Forest production responses to irrigation and fertilization are not explained by shifts in allocation. For Ecol Manag 208:137–152CrossRefGoogle Scholar
  9. Dixon R (1995) Agroforestry systems: sources of sinks of greenhouse gases? Agrofor Syst 31:99–116CrossRefGoogle Scholar
  10. Dixon RK, Winjum JK, Andrasko KJ, Lee JJ, Schroeder PE (1994) Integrated land-use systems: assessment of promising agroforest and alternative land-use practices to enhance carbon conservation and sequestration. Clim Change 27:71–92CrossRefGoogle Scholar
  11. Gamble JD, Johnson G, Current DA, Wyse DL, Sheaffer CC (2016) Species pairing and edge effects on biomass yield and nutrient uptake in perennial alley cropping systems. Agron J 108(3):1020–1029CrossRefGoogle Scholar
  12. Grams TEE, Andersen CP (2007) Competition for resources in trees: physiological versus morphological plasticity. In: Esser K, Löttge U, Beyschlag W, Murata J (eds) Progress in botany. Progress in botany, vol 68. Springer, BerlinGoogle Scholar
  13. Harja D, Vincent G, Mulia R, Van Noordwijk M (2012) Tree shape plasticity in relation to crown exposure. Trees 26:1275–1285CrossRefGoogle Scholar
  14. Harper MD, Phillips WM, Haley GJ (1969) Soil survey of Washington County, Arkansas. USDA Soil Conservation Service. US Govt Printing Office, Washington, DCGoogle Scholar
  15. Jenkins JC, Chojnacky DC, Heath LS, Birdsey RA (2004) Comprehensive database of diameter-based biomass regressions for North American tree species. Gen Tech Rep NE-319 Newtown Square, PA: US Department of Agriculture, Forest Service, Northeastern Research Station 1Google Scholar
  16. Johnson JD (1990) Dry-matter partitioning in loblolly and slash pine: effects of fertilization and irrigation. For Ecol Manag 30:147–157CrossRefGoogle Scholar
  17. Kumar MB, Suman JB, Jamaludheen V, Suresh TK (1998) Comparison of biomass production, tree allometry and nutrient use efficiency of multipurpose trees grown in woodlot and silvopastoral experiments in Kerala, India. For Ecol Manag 112:145–163CrossRefGoogle Scholar
  18. Kuyah S, Dietz J, Muthuri C, Jamnadass R, Mwangi P, Coe R et al (2012) Allometric equations for estimating biomass in agricultural landscapes: II. Belowground biomass. Agric Ecosyst Environ 158:225–234. CrossRefGoogle Scholar
  19. Lee JJ, Dodson R (1996) Potential carbon sequestration by afforestation of pasture in the South-Central United States. Agron J 88:381–384. CrossRefGoogle Scholar
  20. Lines ER, Zavala MA, Purves DW, Coomes DA (2012) Predictable changes in aboveground allometry of trees along gradients of temperature, aridity and competition. Glob Ecol Biogeogr 21:1017–1028CrossRefGoogle Scholar
  21. Martin AR, Thomas SC (2011) A reassessment of carbon content in tropical trees. PLOS ONE 6(8):e23533CrossRefGoogle Scholar
  22. Merwin ML, Easter M, Townsend LR, Vining RC, Johnson GL (2009) Estimating carbon stock change in agroforestry and family forestry practices. Agroforestry comes of age: putting science into practice proceedings of the 11th north American agroforestry conference, 31 May - 3 June, Columbia, Missouri, USA, p 17–24Google Scholar
  23. Morgan JA et al (2010) Carbon sequestration in agricultural lands of the United States. J Soil Water Conserv 65:6A–13A. CrossRefGoogle Scholar
  24. Nair PKR (2012) Carbon sequestration studies in agroforestry systems: a reality-check. Agrofor Syst 86:243–253. CrossRefGoogle Scholar
  25. Nair PKR, Nair VD (2002) Carbon storage in North American agroforestry systems. In: Kimble JM, Heath LS, Birdsey RA, Lal R (eds) The potential of US forest soils to sequester carbon and mitigate the greenhouse effect. CRC Press, Boca Raton, pp 385–394. Google Scholar
  26. Nair PKR, Mohan Kumar B, Nair VD (2009) Agroforestry as a strategy for carbon sequestration. J Plant Nutr Soil Sci 172:10–23CrossRefGoogle Scholar
  27. Nath CD, Pélissier R, Ramesh BR, Garcia C (2011) Promoting native trees in shade coffee plantations of southern India: comparison of growth rates with the exotic Grevillea robusta. Agrofor Syst 83:107–119. CrossRefGoogle Scholar
  28. NOAA (2016) National oceanic and atmospheric administration network, weather station at the Northwest Arkansas Regional Airport. Accessed Jan 2016
  29. Paine CET, Marthews TR, Vogt DR, Purves D, Rees M, Hector A, Turnbull LA (2012) How to fit nonlinear plant growth models and calculate growth rates: an update for ecologists. Methods Ecol Evol 3:245–256. CrossRefGoogle Scholar
  30. Peichl M, Thevathasan NV, Gordon AM, Huss J, Abohassan RA (2006) Carbon sequestration potentials in temperate tree-based intercropping systems, Southern Ontario, Canada. Agrofor Syst 66:243–257. CrossRefGoogle Scholar
  31. Philipson CD, Saner P, Marthews TR, Nilus R, Reynolds G, Turnbull LA, Hector A (2012) Light-based regeneration niches: evidence from 21 dipterocarp species using size-specific RGRs. Biotropica 44:627–636. CrossRefGoogle Scholar
  32. Pinheiro J, Bates B (2000) Mixed-effects models in S and S-PLUS. Springer, New York. CrossRefGoogle Scholar
  33. R Development Core Team (2011) R: a language and environment for statistical computing. R foundation for statistical computing, Vienna, ISBN: 3-900051-07-0.
  34. Rance SJ, Mendham DS, Cameron DM (2017) Assessment of crown woody biomass in Eucalyptus grandis and E. globulus plantations. New For 48:381–396CrossRefGoogle Scholar
  35. Rees M, Osborne Colin P, Woodward FI, Hulme Stephen P, Turnbull Lindsay A, Taylor Samuel H (2010) Partitioning the components of relative growth rate: how important is plant size variation? Am Nat 176:E152–E161. CrossRefGoogle Scholar
  36. Roxburgh SH, Paul KI, Clifford D, England JR, Raison RJ (2015) Guidelines for constructing allometric models for the prediction of woody biomass: how many individuals to harvest? Ecosphere 6(3):38. CrossRefGoogle Scholar
  37. Saldarriaga JG, West DC, Tharp ML, Uhl C (1988) Long-term chronosequence of forest succession in the upper Rio Negro of Colombia and Venezuela. J Ecol 76:938–958. CrossRefGoogle Scholar
  38. Sauer TJ, Hernandez-Ramirez G (2011) Agroforestry. In: Hatfield JL, Sauer TJ (eds) Soil management: building a stable base for agriculture. Soil Science Society of America, Madison, pp 351–370. Google Scholar
  39. Sauer TJ et al (2015) Nutrient cycling in an agroforestry alley cropping system receiving poultry litter or nitrogen fertilizer. Nutr Cycl Agroecosys 101:167–179CrossRefGoogle Scholar
  40. Schoeneberger MM (2009) Agroforestry: working trees for sequestering carbon on agricultural lands. Agrofor Syst 75:27–37. CrossRefGoogle Scholar
  41. Schoeneberger M et al (2012) Branching out: agroforestry as a climate change mitigation and adaptation tool for agriculture. J Soil Water Conserv 67:128A–136A. CrossRefGoogle Scholar
  42. Schroth G, do Socorro Souza da Mota M, de Assis Elias ME (2015) Growth and nutrient accumulation of Brazil nut trees (Bertholletia excelsa) in agroforestry at different fertilizer levels. JFR 26(2):347–353Google Scholar
  43. Sharrow SH, Ismail S (2004) Carbon and nitrogen storage in agroforests, tree plantations, and pastures in western Oregon, USA. Agrofor Syst 60:123–130. CrossRefGoogle Scholar
  44. Shen H, Zhu Z (2008) Efficient mean estimation in log-normal linear models. J Statl Plan Inference 138:552–567. CrossRefGoogle Scholar
  45. Smith MW, Wood BW (2006) Pecan tree biomass estimates. HortScience 41:1286–1291CrossRefGoogle Scholar
  46. Smith MW, Wood BW, Raun WR (2007) Recovery and partitioning of nitrogen from early spring and midsummer applications to pecan trees. J Am Soc Hortic Sci 132(6):758–763CrossRefGoogle Scholar
  47. Stovall JP, Fox TR, Seiler JR (2013) Allometry varies among 6-year-old Pinus taeda (L.) clones in the virginia piedmont. For Sci 59:50–62Google Scholar
  48. Swan A, Williams SA, Brown K, Chambers A, Creque J, Wick J, Paustian K (2015) COMET-planner: carbon and greenhouse gas evaluation for NRCS conservation practice planning, 64 p.
  49. Thomas A, Brauer D, Sauer T, Coggeshall M, Ellersieck M (2008) Cultivar influences rootstock and scion survival of grafted black walnut. J Am Pomol Soc 62:3–12Google Scholar
  50. Thomas AL, Reid WR, Sauer TJ (2015) Establishment and early development of ‘Kanza’, ‘Peruque’, and other pecan cultivars in northern US growing regions. Acta Hortic 1070:143–147CrossRefGoogle Scholar
  51. Udawatta RP, Jose S (2012) Agroforestry strategies to sequester carbon in temperate North America. Agrofor Syst 86:225–242. CrossRefGoogle Scholar
  52. West PW, Ratkowsky DA, Davis AW (1984) Problems of hypothesis testing of regressions with multiple measurements from individual sampling units. For Ecol Manag 7:207–224. CrossRefGoogle Scholar
  53. Wolz KJ, Branham BE, DeLucia EH (2018) Reduced nitrogen losses after conversion of row crop agriculture to alley cropping with mixed fruit and nut trees. Agric Ecosyst Environ 258:172–181CrossRefGoogle Scholar
  54. Zhou X, Brandle JR, Awada TN, Schoeneberger MM, Martin DL, Xin Y, Tang Z (2011) The use of forest-derived specific gravity for the conversion of volume to biomass for open-grown trees on agricultural land. Biomass Bioenergy 35:1721–1731CrossRefGoogle Scholar
  55. Zhou X, Schoeneberger MM, Brandle JR et al (2014) Analyzing the uncertainties in use of forest-derived biomass equations for open-grown trees in agricultural land. Forest Sci 61:144–161CrossRefGoogle Scholar
  56. Ziegler J et al (2016) A model for estimating windbreak carbon within COMET-farm™. Agrofor Syst 90:875–887. CrossRefGoogle Scholar

Copyright information

© This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection 2019

Authors and Affiliations

  1. 1.National Laboratory for Agriculture and the EnvironmentUSDA-ARSAmesUSA
  2. 2.Division of Plant Sciences, Southwest Research CenterUniversity of MissouriVernonUSA
  3. 3.USDA-ARS, Poultry Production and Products Safety Research UnitUniversity of ArkansasFayettevilleUSA
  4. 4.Division of Agriculture, Department of Animal Science, AFLS B114University of ArkansasFayettevilleUSA
  5. 5.USDA-ARS Conservation and Production Research LabBushlandUSA

Personalised recommendations