Unmanned Aerial Vehicle (UAV) Derived Canopy Gaps in the Old-Growth Beech Forest of Mount Pollinello (Italy): Preliminary Results

Abstract

Forest canopy gaps caused by natural disturbances represent the primary driver of forest regeneration dynamics, modifying several ecological factors such as the light environment within an ecosystem. Canopy openings constantly change the shape and structure of forests as well as tree species diversity. The analysis of forest canopy gap spatial patterns in old-growth forests can provide helpful information for their conservation. Moreover, it can be an important reference for outlining sustainable forest management to restore and maintain the original biodiversity and accelerate forest succession towards old-growth characteristics. The main goal of this research was to assess a first forest gap size distribution and analyze their spatial pattern in an old-growth beech (Fagus sylvatica L.) forest in the Pollino National Park (Italy) strict reserve, with no human influence in at least the past 70 years due to its remote location. Using an unmanned aerial vehicle (UAV)-based canopy height model (CHM), we detected and classified 196 canopy gaps ranging from 10 to 343 m2. The gap size-frequency reflected a power-law distribution. Using second-order statistics, following the K and L Ripley’s function, we found that the canopy gaps were spatially clustered distributed. These preliminary results show the predominance of small-scale disturbances, confirmed by the spatial structure analyses highlighting the single tree nature of these processes influenced by site-specific conditions.