Anticipatory responses to drought by plants: What are the environmental cues?

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Authors

Pedro José Aphalo, Víctor O. Sadras

Abstract

This study is an attempt to reconcile the physics-driven variation in reference evapotranspiration (ET0) and possible sensory-driven anticipatory acclimation that contributes to tolerance of dry weather spells and drought by plants growing in open fields. We use an original data set measured at high temporal resolution. These data include the standard meteorological observations plus detailed observations of different bands of sunlight: UV-B, UV-A, photosynthetically active and global down-welling short-wave radiation, blue, red and far-red light from two growth seasons at Helsinki, Finland. We also report ET0 computed with the FAO formulation of the Penman-Monteith equation. We assessed the correlations among variables at different time scales and their performance as predictors of ET0. We conclude that all studied bands of sunlight are consistently good predictors of ET0. UV radiation is a specially good predictor of the daily course of ET0 while longer wavelengths function better in the prediction of day to day variation in ET0. In most cases sunlight bands that plants are known to sense through specific photoreceptors can explain more than 95% of the variation in ET0, making them as cues carrying information on the demand side of the water budget of vegetation. Sunlight as sensed by plants is consequently a good candidate as driver of anticipatory acclimation to likely future drought events.

DOI

https://doi.org/10.32942/osf.io/ypqea

Subjects

Agriculture, Ecology and Evolutionary Biology, Engineering, Environmental Sciences, Life Sciences, Other Physical Sciences and Mathematics, Physical Sciences and Mathematics, Plant Sciences, Water Resource Management

Keywords

acclimation, anticipation, cue, drought, evaporation, plants, signal, sunlight, Transpiration, water balance, Weather

Dates

Published: 2021-09-29 20:27

License

CC-BY Attribution-No Derivatives 4.0 International

Additional Metadata

Data and Code Availability Statement:
The original data and the LaTeX source of the manucript also containing all the R code used for data analysis will be made publicly available as soon as possible. All R code used for data analysis is run when the PDF is generated. The data file is large at 250 MB (compressed in R's data format).

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