The influence of canopy structural traits on the understorey air temperature of tropical forests in Borneo

Changes in vegetation structure caused by selective logging have direct impacts on energy exchange and ecosystem functioning, which may result in altered microclimate. In this study, we investigated how selective logging affected microclimate temperatures in tropical forests of Malaysian Borneo. We used structural metrics derived from Terrestrial Laser Scanner (TLS) obtained in 16 permanent forest plots distributed over a logging intensity gradient. The plots were located within the Stability of Altered Forest Ecosystems (SAFE) Project, the world’s largest forest fragmentation experiment. TLS point clouds were used to calculate the following forest structural traits: Canopy Ratio (CR), Effective Number of Layer (ENL), Foliage Height Diversity (FHD), total Plant Area Index (PAI) and PAI layered for each 5 m height, Relative Height (RH) at 25, 50, 75, 95 and 98 percentiles. TOMST-TMS-4 microclimate dataloggers were installed in the centre of each plot to monitor air temperature at 15 cm above ground every 15 minutes during the year 2019. We then tested whether canopy traits derived from TLS point clouds could explain the variability of minimum, mean and maximum air temperature. We found that not recently logged forest plots had consistently lower understory temperatures and lower daily variability in comparison with heavily logged forest plots. Mean daily temperatures decreased by 0.9 °C for each PAI unit. PAI alone, however, could capture only 21% of the microclimate variability between plots, suggesting that structural metrics accounting for the vertical distribution of vegetation are key for a comprehensive understanding of how disturbances arising from logging affect energy dissipation in tropical forests.