Investigating plant functional traits, taxonomy and phenology as drivers of leaf spectral variation

Mitigation of the ongoing biodiversity crisis requires thorough understanding of species dynamics across scales. However, monitoring plant species and their functional traits is time-consuming and challenging to implement across larger spatial scales and through time. Spectroscopy is emerging as a promising tool for monitoring plant functional and taxonomic diversity within and between ecosystems. This relies on the presence of a functional and taxonomic signal in leaf optical properties, which in turn depends on the spectral similarity of species, intra- and interspecific trait variation, and the timing of the measurements. In order to address these relations in natural and semi-natural ecosystems in Denmark, we are compiling a spectral library of plants. An important methodological aspect of this work is to assess how leaf degradation, and the phenological stage of the plant, affect leaf optical properties. This was assessed by measuring leaf spectra from 350 – 2500 nm of four plant species, representing different plant functional types, from the same site over five months. We measured leaves at the time of sampling, and repeatedly after detachment from the plant to test how sampling strategy, potential leaf degradation after detachment and phenological stage influence leaf optical properties. Furthermore, we collected spectral and functional trait data of dominant plant species in 100 vegetation plots across the Store Åmose nature area in July and August. We present results of the spectral and functional differences among species and taxonomic levels, and the significance of leaf degradation and phenology on measured spectra. Leaf water and chorophyll content are expected to be the major drivers of spectral variation over time. However, subtle spectral signals may reflect other biochemical traits or leaf biophysical changes during the growing season. These dynamics are expected to depend on plant ecology, functional types, and environmental conditions such as wet and dry habitats. Our results will demonstrate the potential (and challenges) of using spectroscopy for taxonomic and functional identification of plants. We will provide insights into the role of leaf sampling strategy and phenology on spectral signals of plant species, which can inform the planning of future remote sensing and field campaigns.