Root Nutrient Uptake Kinetics in Trees

Authors

Matthew E. Craig¹* (craigme@ornl.gov), Anthony P. Walker¹, Colleen M Iversen¹, Larry M. York², Jeffrey Chambers³

Institutions

¹Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN; ²Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN; ³Lawrence Berkeley National Laboratory, Berkeley CA

URLs

• https://ngee-tropics.lbl.gov/

Abstract

Global vegetation models increasingly represent the nutrient costs of plant growth. The parameters governing plant nutrient acquisition are therefore central to accurate carbon cycle projections, yet understanding of nutrient uptake has been limited by the difficulty of measuring root physiological traits. Root nutrient uptake is often described by two Michaelis-Menten parameters: maximum uptake rate (V_max) and substrate affinity (K_m). These parameters may vary by plant functional type or with environmental conditions. Plants may alter nutrient uptake kinetics in response to nutrient limitation or, over longer time scales, may optimize nutrient uptake according to life history strategy. Recent work demonstrates the utility of collating root nutrient uptake measurements, yet there has been very little synthesis work for tree species. This work presents a global dataset of nutrient uptake parameters in tree species. Association of these parameters with root traits was examined using the Fine-Root Ecology Database (FRED 3.0), and meta-analysis was used to evaluate the response of nutrient uptake to nutrient fertilization and other global change drivers. Finally, the sensitivity of the forest demography model FATES to nutrient uptake parameters was determined. The compiled dataset contains observations from more than 50 studies spanning more than 40 tree species. Notably, observations are strongly biased toward temperate tree species, with few observations from tropical forests. Species with acquisitive root traits, like high specific root length, exhibit greater capacity (i.e., greater V_max) and affinity (i.e., lower K_m) for ammonium and nitrate uptake. Nutrient fertilization exerted a strong negative effect on both uptake capacity and affinity. A sensitivity analysis, using E3SM Land Model-FATES, reveals that simulated net primary productivity is highly sensitive to V_max for nitrogen uptake, underscoring the importance of providing new datasets for model parameterization. Overall, nutrient-enabled forest demography models are highly sensitive to nutrient uptake parameters. These parameters are highly variable in tree species but may vary predictably with environmental drivers and life history strategies.