RESUMEN
Lichens dominate a significant part of the Earth's land surface, and are valuable bioindicators of various environmental changes. In the northern hemisphere, the largest lichen biomass is in the woodlands and heathlands of the boreal zone and in tundra. Despite the global coverage of lichens, there has been only limited research on their spectral properties in the context of remote sensing of the environment. In this paper, we report spectral properties of 12 common boreal lichen species. Measurements of reflectance spectra were made in laboratory conditions with a standard spectrometer (350-2500 nm) and a novel mobile hyperspectral camera (400-1000 nm) which was used in a multiangular setting. Our results show that interspecific differences in reflectance spectra were the most pronounced in the ultraviolet and visible spectral range, and that dry samples always had higher reflectance than fresh (moist) samples in the shortwave infrared region. All study species had higher reflectance in the backward scattering direction compared to nadir or forward scattering directions. Our results also reveal, for the first time, that there is large intraspecific variation in reflectance of lichen species. This emphasizes the importance of measuring several replicates of each species when analyzing lichen spectra. In addition, we used the data in a spectral clustering analysis to study the spectral similarity between samples and species, and how these similarities could be linked to different physical traits or phylogenetic closeness of the species. Overall, our results suggest that spectra of some lichen species with large ground coverage can be used for species identification from high spatial resolution remote sensing imagery. On the other hand, for lichen species growing as small assemblages, mobile hyperspectral cameras may offer a solution for in-situ species identification. The spectral library collected in this study is available in the SPECCHIO Spectral Information System.
RESUMEN
Lichens are combinations of two symbiotic organisms, a green alga or cyanobacterium and a fungus. They grow in nearly all terrestrial ecosystems and survive in habitats, which are very dry or cold, or too poor in nutrients to maintain vegetation growth. Because lichens grow on visible surfaces and exhibit spectral properties, which are clearly different from, for example, vegetation, it is possible to distinguish them in remote sensing data. In this first systematic review article on remote sensing of lichens, we analyze and summarize which lichen species or genera, and in which habitats and geographical regions, have been remotely sensed, and which remote sensing or spectroscopic technologies have been used. We found that laboratory or in situ measured spectra of over 70 lichen species have been reported to date. We show that studies on remote sensing of lichens fall under seven broad themes: (1) collection of lichen spectra for quantification of lichen species or characteristics, (2) pollution monitoring with lichens as ecological indicators, (3) geological and lithological mapping, (4) desert and dryland monitoring, (5) animal habitat monitoring, (6) land cover or vegetation mapping, and (7) surface energy budget modeling.
RESUMEN
The photochemical reflectance index (PRI) is regarded as a promising proxy to track the dynamics of photosynthetic light use efficiency (LUE) via remote sensing. The implementation of this approach requires the relationship between PRI and LUE to scale not only in space but also in time. The short-term relationship between PRI and LUE is well known and is based on the regulative process of non-photochemical quenching (NPQ), but at the seasonal timescale the mechanisms behind the relationship remain unclear. We examined to what extent sustained forms of NPQ, photoinhibition of reaction centres, seasonal changes in leaf pigment concentrations, or adjustments in the capacity of alternative energy sinks affect the seasonal relationship between PRI and LUE during the year in needles of boreal Scots pine. PRI and NPQ were highly correlated during most of the year but decoupled in early spring when the foliage was deeply downregulated. This phenomenon was attributed to differences in the physiological mechanisms controlling the seasonal dynamics of PRI and NPQ. Seasonal adjustments in the pool size of the xanthophyll cycle pigments, on a chlorophyll basis, controlled the dynamics of PRI, whereas the xanthophyll de-epoxidation status and other xanthophyll-independent mechanisms controlled the dynamics of NPQ at the seasonal timescale. We conclude that the PRI leads to an underestimation of NPQ, and consequently overestimation of LUE, under conditions of severe stress in overwintering Scots pine, and most likely also in species experiencing severe drought. This severe stress-induced decoupling may challenge the implementation of the PRI approach.