Even if we succeed in decarbonizing the world’s economy, the targeted global temperature increase of 1.5 to 2 K by 2100 will still produce significant changes in the water cycle . One predicted change is an increase in the frequency and severity of droughts in Europe . For forests, the consequences of these droughts are expected to range from productivity decline to abrupt mortality . By 2100 these effects are projected to translate into economic losses estimated to range between 14 and 50% in the forestry sector . Forest stakeholders and policymakers are well aware of the need to adapt to future climate; yet, despite decades of research our predictions of the effects of droughts on forest ecosystems are still highly uncertain – a lack of knowledge that calls for novel approaches and knowledge transfer.
Land surface models (LSMs) simulate the biophysical and biogeochemical processes of the interaction between the terrestrial biosphere and the atmosphere. They are a key component of the so-called ‘Earth systems models’ used for recommendations by the intergovernmental panel for climate change, and where they are expected to tackle large-scale questions related to land-atmosphere interactions. The predictive power of LSMs is hampered by their over-parameterization , that implies that a good result can be obtained for the wrong reasons. Indeed, most physiological processes are represented by semi-empirical equations, with parameters calibrated for specific sites and conditions that do not always have ecological meaning and that might not necessarily hold under future climate. For LSMs to be able to simulate forest response to droughts outside their calibration range requires the implementation of the main physiological characteristics the so-called ‘traits’ that vary with environmental conditions , and drive trees’ response to environmental changes.
This requirement leads to the overall challenge of this fellowship, to advance the representation of drought- related physiological processes in LSMs using the cutting-edge multidisciplinary approach of trait modelling. The aim is to enhance society’s understanding of future impacts of drought on European forests.
