Individual-tree- and stand-based development following natural disturbance in a heterogeneously structured forest: A LiDAR-based approach

- Forest development after natural disturbance was analyzed using LiDAR.
- Individual trees were detected using LiDAR data supported by CIR aerial imagery.
- Individual-tree-based growth of future forest development was simulated.
- Naturally regenerating forests exhibit structural heterogeneity in the early-seral stages.
- The feasibility of LiDAR data for modeling post-disturbed stands is shown.

Large-scale severe natural disturbance events drive spatial and temporal patterns of forests by altering forest structure, composition, and functions. In the Bavarian Forest National Park in Germany, windthrow events led to large disturbances caused by the European bark beetle (Ips typographus L.). Until recently, it was assumed that at the initial stage of regeneration, trees tend to form a homogeneous stand structure, whereas structural heterogeneity is an attribute of later developmental stages. Yet recent studies provide evidence that under certain conditions structural heterogeneity can arise much earlier in stand development. Here we combined LiDAR data and forest growth modeling based on individual trees to develop a workflow for studying forest development in post-disturbed areas in the upper montane regions of the national park. The current forest structure was derived from LiDAR data of individually detected trees and a set of forest structural attributes were derived. The results served as input to simulate tree development spatio-temporally for a period of 80 years. Several spatial statistics, including landscape and spatial point pattern metrics, were calculated to assess the structural heterogeneity. The results showed that naturally regenerating forests on post-disturbed sites reveal structural heterogeneity already at the early-seral stage. Moreover, a significant portion of the eventual old-growth structural heterogeneity might already be determined in the early successional stages. Our workflow highlights the use of multi-sensor aerial remote sensing to provide detailed structural information useful for the investigation of early-phase forest dynamics.