TY - ABST

T1 - Advancing drought stress assessment in trees

T2 - EvolTree Conference 2023

AU - Xu, Jing

AU - Trepekli, Katerina

AU - Ræbild, Anders

AU - Hansen, Ole Kim

PY - 2023

Y1 - 2023

N2 - Studying drought resistance in trees presents a common challenge due to the complexity of physiological responses and the varying importance of traits based on drought intensity, duration, and timing. Traditional methods of quantifying drought stress rely on labor-intensive, time-consuming, and partly destructive sampling using portable equipment to monitor photosynthesis, transpiration rate, and water potential in trees. Furthermore, these methods are often limited to small sample forest areas. To address these limitations, we propose an innovative method that leverages state-of-the-art laser scanners, gas analyzers, thermal and multispectral cameras mounted on drones. This technology enables the simultaneous monitoring of a wide range of tree traits at centimeter resolution, offering a fast and efficient approach to exploit characteristics related to drought adaptation mechanisms. Our research focuses on establishing this method using Nordmann fir as a model species. In 2022, we created artificial drought conditions in potted Nordmann fir clones within a greenhouse, employing three treatments: control, medium dry, and very dry. We conducted both novel drone-based measurements and traditional techniques to compare their efficacy. In September 2022, we extended our investigation to a clonal Nordmann fir plantation by covering selected ground areas with plastic. During the 2023 growing season, we performed drone-based and ground measurements on the trees covered by plastic, with the trees outside the covered area serving as the control group. We will present the results of these two studies, highlighting the benefits of utilizing drone-based remote sensing technologies in forest tree management. The successful application of these sophisticated technologies will revolutionize conventional manual phenotyping of forest trees, replacing laborious and inconsistent methods. This advancement holds great potential for enhancing tree breeding efficiency for climate resilience and providing a valuable tool for assessing the health of forests.

AB - Studying drought resistance in trees presents a common challenge due to the complexity of physiological responses and the varying importance of traits based on drought intensity, duration, and timing. Traditional methods of quantifying drought stress rely on labor-intensive, time-consuming, and partly destructive sampling using portable equipment to monitor photosynthesis, transpiration rate, and water potential in trees. Furthermore, these methods are often limited to small sample forest areas. To address these limitations, we propose an innovative method that leverages state-of-the-art laser scanners, gas analyzers, thermal and multispectral cameras mounted on drones. This technology enables the simultaneous monitoring of a wide range of tree traits at centimeter resolution, offering a fast and efficient approach to exploit characteristics related to drought adaptation mechanisms. Our research focuses on establishing this method using Nordmann fir as a model species. In 2022, we created artificial drought conditions in potted Nordmann fir clones within a greenhouse, employing three treatments: control, medium dry, and very dry. We conducted both novel drone-based measurements and traditional techniques to compare their efficacy. In September 2022, we extended our investigation to a clonal Nordmann fir plantation by covering selected ground areas with plastic. During the 2023 growing season, we performed drone-based and ground measurements on the trees covered by plastic, with the trees outside the covered area serving as the control group. We will present the results of these two studies, highlighting the benefits of utilizing drone-based remote sensing technologies in forest tree management. The successful application of these sophisticated technologies will revolutionize conventional manual phenotyping of forest trees, replacing laborious and inconsistent methods. This advancement holds great potential for enhancing tree breeding efficiency for climate resilience and providing a valuable tool for assessing the health of forests.

U2 - 10.31926/evoltree.2023

DO - 10.31926/evoltree.2023

M3 - Conference abstract in proceedings

SP - 66

BT - Resilient Forests for the Future

A2 - Curtu, Alexandru Lucian

A2 - Ciocîrlan, Elena

PB - Transilvania University of Brașov

Y2 - 12 September 2023 through 15 September 2023

ER -