Plant and Soil

, Volume 139, Issue 2, pp 209–218

Modeling magnesium, phosphorus and potassium uptake by loblolly pine seedlings using a Barber-Cushman approach

  • J. M. Kelly
  • S. A. Barber
  • G. S. Edwards
Article

Abstract

The Barber-Cushman mechanistic nutrient uptake model, which has been utilized extensively to describe and predict nutrient uptake by crop plants, was evaluated for its ability to predict K, Mg, and P uptake by loblolly pine (Pinus taeda L.) seedlings. Sensitivity analyses were also used to investigate the impact of changes in soil nutrient supply, root morphological, and root uptake kinetics parameters on simulated nutrient uptake. Established experimental techniques were utilized to define the 11 parameters needed to model uptake by 1-0 seedlings of K, Mg, and P from a modified A horizon soil (Lilly series). Model predictions of K and P uptake over a 180-d growth period were underestimated by 6 and 11%, respectively. Estimates of Mg uptake were underestimated by 62%. While the level of agreement between predicted and observed K and P values was quite acceptable, analysis of parameter values and results of sensitivity analyses both indicated that the model underestimation of Mg uptake was the result of applying an Imax value developed under relatively low Mg concentration to a situation in which the functional Imax would be much higher due to the dominance of passive versus active uptake. Overall results of sensitivity analyses indicate that under the circumstances investigated, Imax, was the primary variable controlling plant uptake of K, Mg, and P. The dominance of this term over others was due to the relatively high Cli values for all three nutrients. Reducing (-50%) or increasing (+ 100%) other soil supply, root morphological, and remaining root uptake kinetics values did not substantially alter model estimates of nutrient uptake.

Key words

Barber-Cushman model Cli Imax loblolly pine nutrient uptake sensitivity analysis 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adams F 1974 Soil solution. In The Plant Root and its Environment. Ed. E WCarson. pp 441–481. University Press of Virginia, Charlottesville, VA.Google Scholar
  2. Barber S A 1984 Soil Nutrient Bioavailability: A Mechanistic Approach. Wiley, New York.Google Scholar
  3. Claassen N and Barber S A 1974 A method for characterizing the relation between nutrient concentration and flux into roots of intact plants. Plant Physiol. 54, 564–568.Google Scholar
  4. Gillespie A R and Pope P E 1990 Rhizosphere acidification increases phosphorus recovery of black locust. II. Model predictions and measured recovery. Soil Sci. Soc. Am. J. 54, 538–541.Google Scholar
  5. Ingestad T 1982 Relative addition rate and external concentration: Driving variables used in plant nutrition research. Plant Cell Environ. 5, 443–453.Google Scholar
  6. Ingestad T 1988 A fertilization model based on the concepts of nutrient flux density and nutrient productivity. Scand. J. For. Res. 3, 157–173.Google Scholar
  7. Ingestad T and Ågren G I 1988 Nutrient uptake and allocation at steady-state nutrition. Physiol. Plant. 72, 450–459.Google Scholar
  8. Kelly J M and Barber S A 1991 Magnesium uptake kinetics in loblolly pine seedlings. Plant and Soil 134, 227–232.CrossRefGoogle Scholar
  9. Kovar J L and Barber S A 1990 Potassium supply characteristics of thirty-three soils as influenced by seven rates of potassium. Soil Sci. Soc. Am. J. 54, 1356–1361.Google Scholar
  10. Mengel D B and Barber S A 1974 Rate of nutrient uptake per unit of corn root under field conditions. Agron. J. 66, 399–402.Google Scholar
  11. Nye P H and Tinker P B 1977 Solute Movement in the Soil-Root System. Blackwell Scientific Publishers, Oxford, UK.Google Scholar
  12. Oats K and Barber S A 1987 Nutrient Uptake: A microcomputer program to predict nutrient absorption from soil by roots. J. Agron. Educ. 16, 65–68.Google Scholar
  13. Rengel Z and Robinson D L 1990 Modeling magnesium uptake from an acid soil. II. Barber-Cushman model. Soil Sci. Soc. Am. J. 54, 791–795.Google Scholar
  14. Silberbush M and Barber S A 1983 Prediction of phosphorus and potassium uptake by soybeans with a mechanistic mathematical model. Soil Sci. Soc. Am. J. 47, 262–265.Google Scholar
  15. Simmons G L and Kelly J M 1989 Effects of acidic precipitation, O3, and soil Mg status on throughfall, soil, and seedling loblolly pine nutrient concentrations. Water Air Soil Pollut. 43, 199–210.Google Scholar
  16. South D B and Davey C B 1983 The southern forest nursery soil testing program. Circular 265 Alabama Agric. Exp. Station, Auburn Al.Google Scholar
  17. Tennant D 1975 A test of a modified line intersect method of estimating root length. J. Ecol. 63, 995–1001.Google Scholar
  18. VanRees K C J, Comerford N B and McFee W W 1990 Modeling potassium uptake by slash pine seedlings from low-potassium-supplying soils. Soil Sci. Soc. Am. J. 54, 1505–1507.Google Scholar
  19. Warncke D D and Barber S A 1973 Diffusion of zinc in soils: III. Relation to zinc adsorption isotherms. Soil Sci. Soc. Am. J. 37, 355–358.Google Scholar

Copyright information

© Kluwer Academic Publishers 1992

Authors and Affiliations

  • J. M. Kelly
    • 1
  • S. A. Barber
    • 2
  • G. S. Edwards
    • 1
  1. 1.Cooperative Forest Studies ProgramTennessee Valley AuthorityOak RidgeUSA
  2. 2.Agronomy DepartmentPurdue UniversityWest LafayetteUSA

Personalised recommendations