Abstract
Optical remote sensing is potentially highly informative to track Earth’s plant functional diversity. Yet, causal explanations of how and why plant functioning is expressed in canopy reflectance remain limited. Variation in canopy reflectance can be described by radiative transfer models (here PROSAIL) that incorporate plant traits affecting light transmission in canopies. To establish causal links between canopy reflectance and plant functioning, we investigate how two plant functional schemes, i.e. the Leaf Economic Spectrum (LES) and CSR plant strategies, are related to traits with relevance to reflectance. These traits indeed related to both functional schemes, whereas only traits describing leaf properties correlated with the LES. In contrast, traits related to canopy structure showed no correlation to the LES, but to CSR strategies, as the latter integrates both plant economics and size traits, rather than solely leaf economics. Multiple optically relevant traits featured comparable or higher correspondence to the CSR space than those traits originally used to allocate CSR scores. This evidences that plant functions and strategies are directly expressed in reflectance and entails that canopy ‘reflectance follows function’. This opens up new possibilities to understand differences in plant functioning and to harness optical remote sensing data for monitoring Earth´s functional diversity.
Highlights
Through natural selection plants have diversified in various functions in order to adapt to environmental conditions, including abiotic factors and biotic interactions
It can be assumed that bridging plant functioning and canopy reflectance with radiative transfer theory can increase our understanding of how environmental factors and biotic interactions shape plant functional diversity[11] (Fig. 1)
Which role do optically relevant traits play in relation to the Leaf Economic Spectrum (LES)? The set of optically relevant plant traits can be summarised using a three-dimensional feature space (Fig. 3), built by a principal component analysis, with component 1, 2 and 3 explaining 28%, 26% and 16% of the total variation, respectively
Summary
Through natural selection plants have diversified in various functions in order to adapt to environmental conditions, including abiotic factors (e.g. precipitation or nutrient gradients) and biotic interactions (e.g. competition or herbivory). Various studies have demonstrated that optical Earth observation data allows mapping variation in plant functioning, functional types and strategies[13,14,15,16,17,18,19,20]. To fully harness the potential of Earth observation data and to improve available algorithms, it is crucial to understand the underlying processes that enable us to monitor plant functioning The key to such understanding are the traits that contribute to canopy reflectance. We assess the distribution of these traits along plant functional gradients, because knowing more about the links between optically relevant traits and plant functioning allows for mapping and monitoring plant functions in a more mechanistic way This could dramatically improve the robustness and transferability of our models. Both schemes are general approximations of principal functional differences between species that bundle many individual functions to metrics characterising their overall performance towards abiotic and biotic environmental selection pressures
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