Speaker
Description
Partitioning biomass and functions such as effective separation between leaf (green part) from floral part of plant communities allows a more accurate estimation of photosynthetic vs. reproductive investment. Particularly facing the rise in global temperatures due to climate change, plant communities alter their metabolism, growth, and gas exchange, ultimately affecting functional traits. Local-scale predictions of ecosystem risks require high-resolution monitoring of these responses. However, field sampling of plant functional traits detecting early signals of climate impact remains labor-intensive, hence necessitating scalable methods that automatize the detection of reproductive vs. vegetative structures. Proximal sensing, particularly terrestrial laser scanning (TLS), offers a promising solution by enabling non-destructive, high-resolution 3D scans of vegetation capturing plant intensities and complex architecture.
A key TLS output, intensity—the strength of the backscattered laser signal—reflects surface properties and may serve as a functional and phenological trait. We tested this hypothesis by measuring TLS intensity in four plant species (Lotus corniculatus, Plantago lanceolata, Plantago media, and Trifolium pratense) under controlled greenhouse conditions (TraitComic Experiment). Each species exhibited a distinct intensity fingerprint, with further differentiation between floral and vegetative structures. Floral intensity patterns correlated with geometric shape and volume, suggesting a link to phenological traits.
Our findings demonstrate that TLS-derived intensity data at 1550nm alone can discriminate species-specific and phenological features, providing a basis for upscaling to natural grasslands. By linking these signatures to ecosystem functional traits (e.g., water use efficiency, carbon dynamics), TLS intensity could enhance climate resilience assessments. This approach bridges high-resolution remote sensing with ecological trait analysis, offering a scalable tool for biodiversity monitoring under climate change.
| Status Group | Postdoctoral Researcher |
|---|---|
| Poster Presentation Option | Yes, I’m willing to present as a poster. |
