Fundamentally, there is no link established between spectra, traits and genetics. Even if we use ‘genetics’ as a summary term to include phylogenies or phenotypic vs. genotypic variation, little evidence exists, how remote sensing can contribute to directly assessing phylogenies or genetic structure from in-situ or even remotely sensed data at species level. We propose to establish a regional scale framework using exhaustive in-situ validation data from Laegern, Borneo as well as modeled and controlled experimental data to advance this field and infer partial taxonomies from remotely sensed data of regional communities.
We will extend current Laegern activities to include a controlled common garden experiment using existing facilities at the UZH (greenhouse, etc.) to grow 1-3 dominant tree species in a controlled environment. We continue to further describe in-vivo behavior of the Laegern and Borne forests using very high resolution sampling schemes, including phenocams, drones, and LiDAR/spectroscopy approaches. LiDAR will include high-resolution ground based methods to derive additional morphological traits related to tree architecture. This will as facilitate the up-scaling of leaf-level traits to canopy level.
A framework will be established to relate spectroscopy and LiDAR to traits to genetics using direct and indirect pathways. Focus for traits will be on traits where systematic modeling supports trait retrieval (e.g. such as emerging anthocyanin retrieval or canopy element topology), as well as establishing links to genetic structure.
We will showcase in comparison to other experiments (Jena, Cedar Creek, etc.) that genetic structure can be retrieved a regional scale in comparative low gradients as compared to existing work (Aspen, Arabidopsis).