Speakers
Description
Remote sensing is frequently used to assess biodiversity, particularly species and functional diversity. Common approaches rely on the spectral diversity of plant canopies. Spectral diversity, however, exhibits temporal dynamics that remain inadequately understood. We investigated these dynamics in a nutrient-rich floodplain meadow in northern Germany, characterized by dense grassland vegetation and tall forbs. Using thirty-six 1 m² diameter circular plots, we quantified species diversity using the Shannon index and functional diversity using Rao's quadratic entropy, which integrates plant traits like leaf size, specific leaf area, leaf dry matter content, leaf mass, and canopy height from the LEDA dataset. Spectral diversity across six dates during the growing season was measured with a field spectrometer in five spots of each plot’s canopy and quantified using dissimilarity between these five subplot measurements across 166 wavelengths (405 nm to 2445 nm). Early in the growing season, we observed a strong positive correlation among species, functional, and spectral diversity. As the season progressed, the initially positive relationship between spectral diversity and other dimensions weakened and, in some cases, turned negative. This shift reflects changes in vegetation structure affecting spectral response. Initially, with sparse and uniform vegetation cover, spectral signals were influenced by species diversity and their unique light absorption properties, alongside functional traits of early-season plants. As the season progressed and canopy density increased, spectral responses became less sensitive to ground-level variations. Dominance of signals from higher canopy components led to a more uniform spectral signature, despite ongoing species and functional diversity at ground level. This likely explains the observed decline or reversal in the correlation between spectral diversity and other biodiversity metrics. Our study emphasizes the importance of considering temporal dynamics in studying biodiversity and spectral diversity relationships. Insights can improve remote sensing for accurate biodiversity monitoring across different growing season stages.
| Status Group | Postdoctoral Researcher |
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