How are spectrally relevant plant traits distributed across plant functional gradients?
Various plant traits that affect the spectral properties of plant canopies can be retrieved using optical earth observation data and thus enable to map plant functional properties (Kattenborn 2017). From a remote sensing perspective, the mechanistic response of these optically relevant plant traits is already quite well understood and formulated in process-based models, i.e. canopy radiative transfer models (RTMs). The latter model the reflectance of plant properties using the sun and observer (sensor) orientation and defined plant traits. However, the relationship of these traits towards plant functioning was not systematically assessed. Thus, the present study examines how spectrally relevant traits (those implemented in PROSAIL) are related to two established plant functional schemes, i.e. the leaf economic spectrum (LES) and CSR plant strategies. The trait expressions were measured in-situ in 42 cultivated herbaceous plants. As expected these plant traits indeed relate to the assessed gradients of plant functioning (LES and CSR). As expected traits related to leaf properties (e.g. pigments and dry matter content) show clear correspondence to the LES. Traits related to the canopy structure show no or very little correspondence to the LES but clearly relate to CSR plant strategies which reflect plant functioning at the level of plant individuals or communities. Multiple trait expressions such as LAI, canopy foliage mass (LMA * LAI), faPAR and fAPAR integrated over a growing season feature comparable or even higher correlations to the CSR space than traits that were originally used to allocate CSR scores (e.g. LMA or LDMC). Our results therefore highlight that spectrally relevant plant traits are a valuable alternative or addition to traits traditionally used in trait-based ecology. These traits might not only enrich the suite of potential indicators to characterize plant functional gradients using EO data; they also allow to establish physical and therefore explicit relationships which advance our theoretical understanding as well as the operationalization of such knowledge into mapping and monitoring approaches. References 1. Kattenborn, T., Fassnacht, F. E., Pierce, S., Lopatin, J., Grime, J. P., Schmidtlein, S. 2017. Linking plant strategies and plant traits derived by radiative transfer modelling. Journal of Vegetation Science, 28(4).