Understanding forest dynamics and self-organization at multiple hierarchical scales is essential for forest management under nonstationary disturbance regimes. The Matreshka framework employs the hierarchical patch-mosaic concept to scale up vegetation dynamics from the individual level to the landscape level through the ecosystem hierarchical structure. In this framework, individual-based forest simulators can be used to link tree dynamics with stand-level characteristics, while Markov chain processes operate at the level of stands and can be used to model their dynamics. Here we combined these two approaches to understand how forest dynamics at the individual tree scale affect stand-level dynamics under different climate change scenarios. In particular, we simulated and analyzed climate change scenarios where individual tree growth and overall disturbance regimes are altered due to elevated CO2 concentrations, forest fires and disease outbreaks.
Results/Conclusions
The LES individual-based forest model was employed to simulate stand dynamics under all combinations of climate-related environmental changes: 1) baseline conditions, i.e. no changes in tree growth or disturbance regimes, 2) increased catastrophic disturbances at the stand level, 3) increased intermediate and small scale disturbances, which affect only a fraction of trees in the forest stand, and 4) increased tree growth rates under elevated CO2 concentrations and temperatures. We report here the effects of these environmental conditions on the Mean Age, the Basal Area, the Population and the Shade Tolerance Index (a stand succession indicator). We also computed the Markov chain transition matrices for these stand-level characteristics and established their stationarity and equilibrium distributions under each climate change scenarios. Finally, we compared these transition matrices with empirically-derived transition matrices that were previously obtained in Eastern Canada hardwood forests.