Das Potential von Erdbeobachtungen zur Erfassung von Mustern der Biodiversität europäischer Wälder und Analyse deren Resilienz - OBEF-Accross2

Abstract

The following section summarizes the scientific and technical achievements and contributions accomplished during the entire duration of OBEF-Accross2. We have successfully reached most of the scheduled objectives and goals and made unexpected and very relevant contributions. Furthermore, we exceeded project expectations in the context of methodological development and evaluation. These achievements can be summarized as follow: 1) We have developed robust simulation frameworks that allowed us to evaluate several methodological approaches for remote estimation of plant functional diversity at different scales. The frameworks’ plausibility was validated using remote sensing (RS) and field observations. 2) For the first time, we have answered four relevant questions regarding the potential and limitations of remote sensing of plant functional diversity in a robust and generalizable way: 1) which functional diversity metrics (FDMs) can capture plant functional diversity from space? 2) Can spectral traits (e.g., reflectance factors) or optical traits (plant trait estimates) capture plant functional diversity? 3) Can single-image analyses infer plant functional diversity in a way comparable at local and global scales? and 4) How do the different RS features (i.e., spectral configuration, spatial resolution, and uncertainty) affect the estimation of plant functional diversity? 3) We have developed a global normalization method that provides directly comparable FDMs for different RS missions and field datasets. In addition, the new approach allowed using equivalent number metrics in RS for the first time, providing unbiased partitioning of biodiversity at different scales (alpha, beta, and gamma) using FDMs. 4) We have evaluated the role of different plant traits in the relationships between plant functional and spectral diversity using machine learning and model analysis techniques. 5) We have processed spaceborne imagery from DESIS and Sentinel-2 MSI sensors to generate functional diversity maps of the FunDivEUROPE network and compared them with field data. Moreover, we have extended Sentinel-2 time series analysis to map plant functional diversity in eddy-covariance stations in support of biodiversity-ecosystem function analyses. In this context, we have explored ways to improve the characterization and interpretation of the temporal variability of plant functional diversity. 6) We have conceptualized a processing chain to map functional diversity from Sentinel-2 imagery and identified the remaining challenges to achieve an operational setup. 7) We have analyzed the relationships between functional diversity and ecosystem functional responses, proving the capability of remote sensing to explain ecosystem functional properties and its increasing role in ecosystem stability in arid environments.