Date: 17th November 2021
Time: 13:00
Title: Uncovering hidden patterns in forests: How drone-based remote sensing can help to monitor tree responses to environmental pressures
Location: Remotely via Zoom
Host: Matt Robson
Abstract: As sessile organism with a long life span, trees have been forced to develop a range of mechanism to withstand environmental pressures and prevent damage. Response mechanisms range from rapid physiological adjustments of chemical and functional traits over a day or a season, to structural traits acclimation occurring over several years. At the population level, phenotypic traits of better adapted genotypes are passed over generations and species have been found to shift their distribution ranges as a response to a warming climate.
All these changes in tree phenotype and species distributions are difficult to monitor with classical techniques, which either lack the individual tree resolution or are not scalable to entire tree populations. Thanks to the introduction of drone platforms for scientific applications, remote sensing has opened unprecedented ways for high-throughput tree phenotyping and is slowly gaining ground as an effective tool to monitor tree species stress tolerance and resilience in the face of a changing climate.
This talk spans over three case studies, each of which features a story of monitoring tree responses to the environment via drone-based remote sensing. For the first case study we start in a dry Swiss alpine valley where, taking advantage of a long-term irrigation experiment, we monitored Scots pine concurrent and long-term response to soil water availability. The second case study reveals how the ability of remote sensing to track the invisible phenology of evergreens can support genome-wide association studies in the context of a common garden experiment. Specifically, we compared spring phenology of white spruce genotypes, a trait potentially responsible for a competitive advantage in resource access. In the last case study, we look at how remote sensing can support monitoring of species assisted migration and hybridization. In particular, we look at phenotypic traits allowing to distinguish European and Oriental beech species, with the latter being proposed as a candidate species for assisted migration at critical sites, due to its presumed higher drought tolerance.
Drone-based remote sensing approaches offer new perspectives for forest monitoring that can contribute to the development of climate-smart forest management strategies. The newly gained understanding can further improve the representation of acclimation and adaptation processes in vegetation models, allowing improved prediction of tree responses to future warmer and drier conditions.
Petra D´Odorico is interested in the study of plant and ecosystem responses to the environment, especially forests. Her current research focus is on tree phenotyping for traits linked with phenology, stress responses and species determination. She uses high-throughput plant phenotyping methods based on drone-based remote sensing in combination with classical physiological measurement techniques.