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\begin{document}

\title{Interactive effects of UV radiation and water deficit on production
characteristics in upland grassland and their estimation by proximity
sensing}



\author[1]{Petr Holub}%
\author[1]{Karel Klem}%
\author[1]{Barbora Veselá}%
\author[1]{Kateřina Surá}%
\author[1]{Otmar Urban}%
\affil[1]{Global Change Research Institute Czech Academy of Sciences}%


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  \date{March 12, 2025}


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\begin{abstract}
Since water deficit (WD) and ultraviolet radiation (UV) trigger similar
protective mechanisms in plants, we tested the hypothesis that UV
modulates grassland acclimation to WD, mainly through changes in the
root/shoot (R/S) ratio, enhances the ability of grassland to acquire
water from the soil and hence affects its productivity. We also tested
the potential of spectral reflectance and thermal imaging for monitoring
the impacts of WD and UV on grassland production parameters. The
experimental plots were manipulated by lamellar shelters allowing
precipitation to pass through or to exclude it. The lamellas were either
transmitting or blocking the UV. The results show that WD resulted in a
significant decrease in above-gound biomass (AB). In contrast,
below-ground biomass (BB), R/S ratio and total biomass (TB) increased
significantly in response to WD, especially in UV exclusion treatment.
UV exposure had a significant effect on AB and BB, but only in the last
year of the experiment. The differences in the effect of WD between
years show that the effect of precipitation removal is largely
influenced by the potential evapotranspiration (PET) in a given year and
hence mainly by air temperatures, while the resulting effect on
production parameters is best correlated with the water balance given by
the difference between precipitation and PET. Canopy temperature and
selected spectral reflectance indices showed a significant response to
WD and also significant relationships with morphological (AB, R/S) and
biochemical (C/N ratio) parameters. In particular, the vegetation
indices NDVI and RDVI provided the best correlations of biomass changes
caused by WD and thus the highest potential to remotely sens drought
effects on terrestrial vegetation.%
\end{abstract}%



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