FORFUS-RT3.1

This project is part of the doctoral training unit FORFUS: Forest function under stress

Inspiration

Drought-induced forest disturbances are projected to rise with increasing soil and atmospheric aridity, significantly impacting resource-use efficiency and the overall functioning of the forest ecosystem. The two key metrics for resource-use efficiency are water-use efficiency (WUE) and light-use efficiency (LUE). A comprehensive understanding of the limits of these variables is essential for quantifying the interactions between carbon and water cycles within forests. This knowledge can be instrumental in managing the trade-offs between carbon and water in forest ecosystems under varying environmental conditions.

Innovation

The objectives of FORFUS-RT3.1 are to: (1) understand the impact of drought on the seasonal and interannual variation of satellite multi-spectral signatures, LUE, WUE, canopy conductance (gc) and associated forest ecosystem functioning; and (2) integrate multisensor synergy with environmental variables to develop LUE, WUE and canopy conductance functions for the diagnostic mapping of forest ecosystem functioning metrics.

To achieve these objectives, we will employ time-series analysis to investigate the seasonal and interannual variability of spectral signatures across different satellite platforms (Planet, Sentinel-3, Sentinel-2, Landsat, SMAP). This will be complemented by analyses of time-series data on light-use efficiency (LUE), water-use efficiency (WUE) and conductance (gc) from multiple eddy covariance sites. This approach will enhance our understanding of the significance of remote sensing spectral information in relation to LUE, WUE and gc.

Subsequently, we will apply information theory and/or wavelet analysis to explore the relationships between LUE, WUE, gc, spectral signatures and environmental variables, identifying their principal drivers. We will then develop functional forms for LUE, WUE and gc through synthetic experiments using soil-canopy reflectance, thermal infrared data and surface energy balance models (e.g. SCOPE). Finally, we will integrate model data to apply the derived LUE, WUE and gc functions across forest ecosystems, validating our findings in both drought and normal years.

Impact

This project will enable us to integrate remote sensing technologies with physical models and data-driven analysis to investigate how drought affects light and water-use efficiency in forests. It will enable an advanced understanding of forest vitality, resilience and recovery from drought in relation to biotic-abiotic factors and management practices. The understanding and methods developed in this project are expected to be useful worldwide, in order to strengthen our ability to understand forest ecosystem functioning during drought.