Assessing PROSPECT performance on aquatic plant leaves

PROSPECT is the most widely used optical leaf model for a wide range of remote sensing applications on vegetation and has been developed and parameterised based on empirical data measured almost exclusively on terrestrial plant leaves. As aquatic plants differ substantially from terrestrial plants in leaf morphology and physiology, the validity of the relationships underlying PROSPECT in aquatic plants needs to be verified empirically. To this end, we compiled a comprehensive dataset of leaf spectra and biochemical-structural parameters sampled along a water affinity gradient, including floating and emergent hydrophytes, helophytes and riparian species, and terrestrial plants. In parallel, we designed a multidimensional experiment to explore the performance of PROSPECT across different groups and to characterise sources of modelling error, focusing on aquatic plants. Our results showed that estimates of most leaf parameters from PROSPECT inversions diverged increasingly from measured traits when moving from terrestrial to aquatic species. The suboptimal performance of PROSPECT on aquatic plants appears to be driven by three main factors: difficulties in disentangling leaf dry matter components (particularly proteins), unresolved issues related to the overlap of primary and secondary pigment mixtures and absorption, and the peculiarities of internal leaf structure (i.e. the presence of 'aerenchyma'). These findings highlight the need for careful preliminary evaluation of the applicability and limitations of PROSPECT when applied to vegetation types that differ significantly from the typical terrestrial trees and grasses used for model calibration, including aquatic plants. Such evaluation should be preferably based on empirical data covering natural heterogeneity, so that future applications of remote sensing for mapping aquatic and wetland vegetation characteristics can be improved in terms of robustness and transferability.