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Wiley, Ecohydrology, 1(8), p. 33-45, 2014

DOI: 10.1002/eco.1483

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Simultaneous measurements of stem radius variation and sap flux density reveal synchronisation of water storage and transpiration dynamics in olive trees

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This paper is available in a repository.

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Abstract

Continuous stem water relations, sap flux and radial variation, and soil moisture were monitored in rainfed and irrigated mature olive (Olea europaea L.) trees in field conditions in central Italy. A mathematical procedure was applied to describe plant–environment dependences in order to facilitate the identification of the orrespondence between stem factors (sap flow and diameter variation) and environmental parameters (water availability and evaporative demand). A direct correspondence between the time series of the monitored parameters was observed in the two growing seasons. Soil water content was synchronous to stem diameter variation in irrigated trees, whereas they were asynchronous in rainfed conditions. On a daily basis, sap flux density showed an opposite trend with respect to patterns of vapour pressure deficit and evapotranspiration (ET0) in spring, corresponded to the course of ET0 in summer and lagged behind ET0 in autumn. Maximum daily shrinkage was correlated with vapour pressure deficit (R2 = 0.50, in rainfed; R2 = 0.51, in irrigated plants), whereas it was not significantly related to ET0. Conversely, cumulative sap flow showed a good relationship with ET0 (R2 = 0.60, in rainfed; R2 = 0.51, in irrigated plants) and scaled exponentially with maximum daily shrinkage (R2 = 0.56, in rainfed; R2 = 0.61, in irrigated plants), indicating consistent radial transfer of water between xylem and phloem. The proposed analytical approach highlights the importance of combining measured parameters and sensor outputs in order to determine adjustments of specific plant functionality traits, such as the dynamics of water status in trees, for modelling and practical uses. This study also indicates a different accounting of the effect of microclimatic variables on plant signals based on stem sensors.