Efficacy of Simulated K, P, and Mg Uptake by Loblolly Pine Seedlings as Described by Three Mechanistic Nutrient Uptake Models.

Mechanistic nutrient uptake models provide a means to improve understanding of important plant nutrient uptake process. However, most studies to date have focused on tests of individual models. In this study we evaluated results obtained with the NST 3.0, SSAND, and PCats models with earlier predictions obtained with the NUTRIENT UPTAKE model using K, P, and Mg uptake data for loblolly pine (Pinus taeda L.) seedlings taken from the literature. Uptake of the three elements was simulated and sensitivity analyses conducted with the three models. Results indicate that compared to earlier values obtained with the NUTRIENT UPTAKE model, the three newer models have improved our ability to predict the uptake of K and P, with differences between simulated and observed values for all three models being within ±5% of observed, and the NST prediction being the closest at 98% and 100% for P and K, respectively. The prediction on Mg uptake by the three models is still inadequate with underestimation of the maximal influx at high concentrations (I_max) thought to be the major reason. All three models have very similar sensitivity analysis patterns, which are consistent with those of the NUTRIENT UPTAKE model, and indicate that I_max and mean root radius (r₀) are the most sensitive parameters.