Summary
One of the most pressing ecological questions is how trees and forests can survive in increasing intensity and frequency of droughts and extreme heat. Wide-spread drought-related tree mortality has been witnessed globally over the last decade and in 2022, Europe suffered from the worst drought in 500 years. Understanding and predicting the impact of drought and heat on tree mortality is limited due to lack of knowledge on the environmental conditions that lead to tree mortality.
For the first time, it is feasible to quantify spatial and temporal tree mortality patterns and capture tree structure and species over large geographic regions at the individual tree-level. This enables me to aim to uncover environmental thresholds and key environmental drivers of drought- and heat-related tree mortality at the species-level for various forest biomes. Use of state-of-the-art remote sensing and deep learning methods allows me to capture where, when and what kind of trees (species, structure) have died for tens of millions of trees to increase our understanding of spatial and temporal tree mortality patterns. My approach uses laser scanning data to provide detailed tree 3D characterization and calculation of tree position within tree community (competition) and the landscape (water availability, microclimate). Then, combining these variables with information on tree xylem vulnerability, pest insects, soil temperature and climate, we can ultimately reveal species-specific environmental thresholds and key drivers of drought- and heat-related tree mortality. This research will open new horizons, bringing ecophysiology, remote sensing, forest ecology and entomology together, and developing methods to quantify drivers of tree mortality in much greater depth than has been possible to date. From these findings, we will be able to inform forest managers and policy makers which forests are at risk for increasing the resilience of future forests.
For the first time, it is feasible to quantify spatial and temporal tree mortality patterns and capture tree structure and species over large geographic regions at the individual tree-level. This enables me to aim to uncover environmental thresholds and key environmental drivers of drought- and heat-related tree mortality at the species-level for various forest biomes. Use of state-of-the-art remote sensing and deep learning methods allows me to capture where, when and what kind of trees (species, structure) have died for tens of millions of trees to increase our understanding of spatial and temporal tree mortality patterns. My approach uses laser scanning data to provide detailed tree 3D characterization and calculation of tree position within tree community (competition) and the landscape (water availability, microclimate). Then, combining these variables with information on tree xylem vulnerability, pest insects, soil temperature and climate, we can ultimately reveal species-specific environmental thresholds and key drivers of drought- and heat-related tree mortality. This research will open new horizons, bringing ecophysiology, remote sensing, forest ecology and entomology together, and developing methods to quantify drivers of tree mortality in much greater depth than has been possible to date. From these findings, we will be able to inform forest managers and policy makers which forests are at risk for increasing the resilience of future forests.
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| Web resources: | https://cordis.europa.eu/project/id/101116404 |
| Start date: | 01-01-2024 |
| End date: | 31-12-2028 |
| Total budget - Public funding: | 1 812 500,00 Euro - 1 812 500,00 Euro |
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Original description
One of the most pressing ecological questions is how trees and forests can survive in increasing intensity and frequency of droughts and extreme heat. Wide-spread drought-related tree mortality has been witnessed globally over the last decade and in 2022, Europe suffered from the worst drought in 500 years. Understanding and predicting the impact of drought and heat on tree mortality is limited due to lack of knowledge on the environmental conditions that lead to tree mortality.For the first time, it is feasible to quantify spatial and temporal tree mortality patterns and capture tree structure and species over large geographic regions at the individual tree-level. This enables me to aim to uncover environmental thresholds and key environmental drivers of drought- and heat-related tree mortality at the species-level for various forest biomes. Use of state-of-the-art remote sensing and deep learning methods allows me to capture where, when and what kind of trees (species, structure) have died for tens of millions of trees to increase our understanding of spatial and temporal tree mortality patterns. My approach uses laser scanning data to provide detailed tree 3D characterization and calculation of tree position within tree community (competition) and the landscape (water availability, microclimate). Then, combining these variables with information on tree xylem vulnerability, pest insects, soil temperature and climate, we can ultimately reveal species-specific environmental thresholds and key drivers of drought- and heat-related tree mortality. This research will open new horizons, bringing ecophysiology, remote sensing, forest ecology and entomology together, and developing methods to quantify drivers of tree mortality in much greater depth than has been possible to date. From these findings, we will be able to inform forest managers and policy makers which forests are at risk for increasing the resilience of future forests.
Status
SIGNEDCall topic
ERC-2023-STGUpdate Date
12-03-2024
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