CERES: Impacts of Air Pollution and Climate Extremes on the Resilience of European Forests

Context

Forests play a major role in the global carbon (C) and water cycles as well as in mitigating climate change. Global change drivers such as air pollution (nitrogen, sulfur), but also extreme events in air temperature, precipitation, soil and atmospheric dryness have direct effects on the functioning of forests and might reduce or even offset the effectiveness of nature-based solutions in the future. Defining effective mitigation strategies needs to consider resilience, i.e., resistance and recovery, of forests to air pollution and extreme events. This requires a mechanistic understanding of tree ecophysiological processes that drive forest CO₂ uptake and evaporative cooling, and directly affect the capacity of forests for mitigating climate change.

Objectives

In CERES, we aim to improve the mechanistic understanding of how changes in tree ecophysiology in response to air pollution and climate extremes drive the forest ecosystem's capacity to sequester C and its evaporative cooling. Our hypothesis is that spatio-temporal variations in atmospheric N and S deposition interact with climate drivers (positively or negatively depending on their magnitude) to change trends in resistance, recovery, and resilience of forests in response to extreme events.

More specifically, we ask

1. How have climate extremes evolved in regions with different air pollution since the start of measurements, in terms of frequency, intensity, duration, and volatility?
2. What is the magnitude and the trend direction in resistance, recovery, and resilience of C gain and water loss of different tree species as well as forests?
3. How is the tree level response (in terms of growth and water use) linked to the forest-level response (in terms of CO₂ and H₂O fluxes) to air pollution and climate extremes?
4. How does the projection of forest CO₂ and H₂O flux responses to global change drivers look under future climate conditions?

To answer these questions, we will combine different long-term datasets on climate with data on tree and ecosystem levels to identify ecophysiological resistance and recovery responses to climate extremes under different air pollution. We will use statistical and process-based models to project future forest responses to global change drivers.