UNDERSTANDING CANOPY DEFOLIATION OF EUROPEAN FORESTS UNDER RECENT CLIMATE CHANGES TO PREDICT FUTURE ADAPTATION SCENARIOS

There is increasing interest to identify patterns of current plastic and evolutionary response of plants populations to climate change. Under the hypothesis that plasticity (i.e., the adaptability of an organism to changes in its environment) can be reflected by tree health status, one possible analytical approach is the analysis of long-term forest health data obtained since the 1980s from ca. 6000 ICP Forests plots across Europe. Defoliation was proven to be significantly related to tree growth and driven by climate, although tree age, biotic agents, species-specific interactions and nitrogen deposition may play a role. Here we investigate whether subtle changes in forest health condition and their time trends permit identifying species-specific responses to climate change and can therefore be used to project future conditions according to climate change scenarios. We will use novel methods for decomposing the effect-response into time spectra of different length and lag.

There is increasing interest to identify patterns of current plastic and evolutionary response of plants populations to climate change. Under the hypothesis that plasticity (i.e., the adaptability of an organism to changes in its environment) can be reflected by tree health status, one possible analytical approach is the analysis of long-term forest health data obtained since the 1980s from ca. 6000 ICP Forests plots across Europe. Defoliation was proven to be significantly related to tree growth and driven by climate, although tree age, biotic agents, species-specific interactions and nitrogen deposition may play a role. Here we investigate whether subtle changes in forest health condition and their time trends permit identifying species-specific responses to climate change and can therefore be used to project future conditions according to climate change scenarios. We will use novel methods for decomposing the effect-response into time spectra of different length and lag.