Ecological Indicators (May 2022)
Unveiling the complex canopy spatial structure of a Mediterranean old-growth beech (Fagus sylvatica L.) forest from UAV observations
Abstract
In front of climate change scenarios and global loss of biodiversity, it is essential to monitor the structure of old-growth forests to study ecosystem status and dynamics to inform future conservation and restoration programmes. We propose an Unmanned Aerial Vehicle (UAV)-based framework to monitor fine-grained forest top canopy structure in a primary old-growth beech (Fagus sylvatica L.) forest in Pollino National Park, Italy, which belongs to the UNESCO World Heritage (UNESCO WH) serial site “Ancient and Primeval beech forests of the Carpathians and other regions of Europe”. Canopy profile, gap properties and their spatial distribution patterns were analysed using the canopy height model (CHM) derived from UAV surveys. Very high-resolution orthomosaic images coupled with direct field measurement data were used to assess gap detection accuracy and CHM validation. Forest canopy properties along with the vertical layering of the canopy were further explored using second-order statistics. The reconstructed canopy profile revealed a bimodal top height frequency distribution. The upper canopy layer (h > 14 m) was the most represented canopy height, with the remaining 50% split between the medium and lowest layer; 551 gaps were identified within 11.5 ha. Gap size varied between 2 m2 and 353 m2, and 19 m2was the mean gap size; the gap size-frequency relationship reflected a power-law probability distribution. About 97 % of the gaps were <100 m2 in size, showing a significant tendency to cluster. Most gaps were located in the upper and medium canopy layers; however, the highest relative gap area was found in the lowest layer. These results confirmed the high natural integrity of the ecosystem processes that distinguish the old-growth beech stands in respect to managed woodlands. Our findings demonstrate that the low-cost UAV-DAP (Digital Aerial Photogrammetry) workflow has the potential to generate realistic old-growth forest canopy attributes at a very fine scale. The proposed protocol can be adopted for monitoring the structural dynamics of high-value natural forest ecosystems as in the case of UNESCO WH sites or other old-growth stands. This approach is also helpful for mapping and deriving spatially explicit canopy structure information over confined forest areas and determining where conservation actions should be directed to preserve or restore natural ecosystem function.
