Reconstructing long-term forest microclimate dynamics: validating mechanistic modeling with historical measurements

Accurately assessing the impacts of climate change on forest ecosystems requires understanding how macroclimate and microclimate interact over time. Forest microclimates, strongly influenced by canopy cover and terrain, often deviate significantly from regional macroclimate. Recent research has highlighted the role of forest microclimate buffering for understory plant communities, which seem to be less impacted by global climate change. However, the increasing magnitude and frequency of macroclimatic extremes and associated forest disturbances could still threaten these communities, potentially overwhelming the forest buffering capacity and significantly altering plant community composition. Addressing these uncertainties requires long-term microclimate time-series. Yet, long-term datasets on forest microclimatic dynamics remain scarce. 

Here, we aim to fill this gap by leveraging detailed historical microclimate measurements from the 1950s in central European forests. These unique data serve as a foundation for developing and validating mechanistic microclimate models, enabling the reconstruction of long-term microclimate dynamics. Using biophysical principles, mechanistic modeling provides a robust approach to simulating near-ground temperature and humidity conditions based on macroclimatic inputs and local landscape and vegetation characteristics. By integrating macroclimate data with our in situ microclimate measurements, this research paves the way for exploring how forest microclimates influence plant community composition over time and disentangling the relative contributions of micro- and macroclimatic drivers to long-term vegetation change.