UPSC Seminar: Bertold Mariën
Date:
Tuesday, December 20, 2022 15:00 - 16:00
Duration:
1 Hour
Categories:
UPSC Seminar
Bertold Mariën
IceLab Postdoc in Statistical Learning for Chronosilviculture, a collaboration project between the groups of Jun Yu & Maria E. Eriksson
Title: Autumn phenology and the timing of leaf senescence
Host: Maria E. Eriksson & Jun Yu
Abstract:
The coloring of leaves in many tree species is a prominent phenomenon. The timing of this process, however, is not yet completely understood. The timing of leaf senescence in beech, oak, birch and poplar trees was investigated during four exceptional dry and warm years. Two aspects were adressed: (I) determining the timing of the leaf senescence and (II) determining the fine-root phenology throughout the year to investigate a possible coupling between the phenology of the leaves and fine-roots. Substantial attention has been given to detecting phenological transition dates in longitudinal data of the chlorophyll content index and fine-roots. Especially the use of generalized additive models (GAMs) and generalized additive models for location, scale and shape (GAMLSS) has been explored in relation to the detection of phenological transition date.
Bertold Mariën
IceLab Postdoc in Statistical Learning for Chronosilviculture, a collaboration project between the groups of Jun Yu & Maria E. Eriksson
Title: Autumn phenology and the timing of leaf senescence
Host: Maria E. Eriksson & Jun Yu
Abstract:
The coloring of leaves in many tree species is a prominent phenomenon. The timing of this process, however, is not yet completely understood. The timing of leaf senescence in beech, oak, birch and poplar trees was investigated during four exceptional dry and warm years. Two aspects were adressed: (I) determining the timing of the leaf senescence and (II) determining the fine-root phenology throughout the year to investigate a possible coupling between the phenology of the leaves and fine-roots. Substantial attention has been given to detecting phenological transition dates in longitudinal data of the chlorophyll content index and fine-roots. Especially the use of generalized additive models (GAMs) and generalized additive models for location, scale and shape (GAMLSS) has been explored in relation to the detection of phenological transition date.