RECONSTRUCTING PLANT ROOT AREA AND WATER UPTAKE PROFILES

Abstract

A major challenge in plant ecology is quantifying how roots obtain water and nutrients from the soil. Stable-isotope analysis of hydrogen and oxygen in plant and soil water is one of the best and least destructive methods for elucidating plant–soil interactions. Plant roots obtain water from various depths in the soil and the isotopic signature of plant stem water reflects the soil water sources. Current methods for inferring plant water sources based on stable isotopes (“simple linear mixing models”) are limited. First, their formulation restricts the number of water sources to a maximum of three (e.g., surface, intermediate, deep-soil water); estimation of additional sources leads to an identifiability problem. Second, simple linear mixing models do not appropriately reflect uncertainty, and most importantly, they cannot be employed to elucidate behavior of the root system itself, such as root activity for water uptake. This study introduces the RAPID (root area profile and isotope deconvolution) algorithm, a powerful approach for reconstructing plant water uptake and root area profiles. The RAPID algorithm overcomes the nonidentifiability problem by incorporating a biophysical model for root water uptake into a Bayesian framework such that the biophysics and prior distributions place biologically realistic constraints on the profiles. Posterior distributions for the proportions of active root area and water acquired from each soil layer are obtained via Markov chain Monte Carlo. We apply the RAPID algorithm to data collected for a desert shrub and examine its sampling implications.