Abstract

The vertical distribution of absorbing roots is one of the most influential plant traits determining plant strategy to access below ground resources. Yet little is known of natural variability in root distribution since collecting field data is challenging and labor-intensive. Studying stable water isotope compositions in plants could offer a cost-effective and practical solution to estimate the absorbing root surfaces distribution. However, such an approach requires developing realistic inverse modeling techniques that enable robust estimation of rooting distributions and associated uncertainty from xylem water isotopic composition observations. This study introduces an inverse modeling method that supports the assessment of the root allocation parameter (beta) that defines the exponential vertical decay of a plants' absorbing root surfaces distribution with soil depth. The method requires measurements obtained from xylem and soil water isotope composition, soil water potentials, and sap flow velocities when plants' xylem water is sampled at a certain height above the rooting point. In a simulation study, we show that the approach can provide unbiased estimates of beta and its associated uncertainty due to measuring errors and unmeasured environmental factors that can impact the xylem water isotopic data. We also recommend improving the accuracy and power of beta estimation, highlighting the need for considering accurate soil water potential and sap flow monitoring. Finally, we apply the inverse modeling method to xylem water isotope data of lianas and trees collected in French Guiana. Our work shows that the inverse modeling procedure provides a robust analytical and statistical framework to estimate beta. The method accounts for potential bias due to extraction errors and unmeasured environmental factors, which improves the viability of using stable water isotope compositions to estimate the distribution of absorbing root surfaces complementary to the assessment of relative root water uptake profiles.