Data from: Remote sensing of plant trait responses to field-based plant–soil feedback using UAV-based optical sensors

Plant responses to biotic and abiotic legacies left in soil by preceding
plants is known as plant–soil feedback (PSF). PSF is an important
mechanism to explain plant community dynamics and plant performance in
natural and agricultural systems. However, most PSF studies are short-term
and small-scale due to practical constraints for field-scale
quantification of PSF effects, yet field experiments are warranted to
assess actual PSF effects under less controlled conditions. Here we used
unmanned aerial vehicle (UAV)-based optical sensors to test whether PSF
effects on plant traits can be quantified remotely. We established a
randomized agro-ecological field experiment in which six different cover
crop species and species combinations from three different plant families
(Poaceae, Fabaceae, Brassicaceae) were grown. The feedback effects on
plant traits were tested in oat (Avena sativa) by quantifying the cover
crop legacy effects on key plant traits: height, fresh biomass, nitrogen
content, and leaf chlorophyll content. Prior to destructive sampling,
hyperspectral data were acquired and used for calibration and independent
validation of regression models to retrieve plant traits from optical
data. Subsequently, for each trait the model with highest precision and
accuracy was selected. We used the hyperspectral analyses to predict the
directly measured plant height (RMSE  =  5.12 cm, R2  =  0.79),
chlorophyll content (RMSE  =  0.11 g m−2, R2  =  0.80), N-content
(RMSE  =  1.94 g m−2, R2  =  0.68), and fresh biomass
(RMSE  =  0.72 kg m−2, R2  =  0.56). Overall the PSF effects of the
different cover crop treatments based on the remote sensing data matched
the results based on in situ measurements. The average oat canopy was
tallest and its leaf chlorophyll content highest in response to legacy of
Vicia sativa monocultures (100 cm, 0.95 g m−2, respectively) and in
mixture with Raphanus sativus (100 cm, 1.09 g m−2, respectively), while
the lowest values (76 cm, 0.41 g m−2, respectively) were found in response
to legacy of Lolium perenne monoculture, and intermediate responses to the
legacy of the other treatments. We show that PSF effects in the field
occur and alter several important plant traits that can be sensed remotely
and quantified in a non-destructive way using UAV-based optical sensors;
these can be repeated over the growing season to increase temporal
resolution. Remote sensing thereby offers great potential for studying PSF
effects at field scale and relevant spatial-temporal resolutions which
will facilitate the elucidation of the underlying mechanisms.