Self-potential signals related to tree transpiration in a Mediterranean climate

Abstract

Plant transpiration is a crucial process in the water cycle, and its quantification is essential for understanding terrestrial ecosystem dynamics. While sap flow measurements offer a direct method for estimating individual tree transpiration, their effectiveness may be limited by the use of point sensors; species-specific calibration requirements; and baseline uncertainties, particularly the assumption of negligible nighttime flow, which may not always hold. Self-potential (SP), a passive geophysical method, holds potential for constraining transpiration rates, though many questions remain regarding the electrophysiological processes occurring within trees. In this study, we continuously measured tree SP and sap velocity on three tree species for 1 year in a Mediterranean climate. Using wavelet coherence analysis and variational mode decomposition, we explored the empirical relationship between tree SP and transpiration. Our analysis revealed strong coherence between SP and sap velocity at diurnal timescales, with coherence weakening and phase shifts increasing on days with higher water supply. We estimated electrokinetic coupling coefficients using a linear regression model between SP and sap velocity variations at the diurnal scale, resulting in values typically found in porous geological media. During dry seasons, the electrokinetic effect emerges as the primary contribution to tree SP, indicating its potential utility in assessing transpiration rates. Our results emphasize the need for improved electrode configurations and physiochemical modelling to elucidate tree SP in relation to transpiration.