Carbon flux and forest dynamics: Increased deadwood decomposition in tropical rainforest tree‐fall canopy gaps

Tree mortality rates are increasing within tropical rainforests as a result of global environmental change. When trees die, gaps are created in forest canopies and carbon is transferred from the living to deadwood pools. However, little is known about the effect of tree‐fall canopy gaps on the activity of decomposer communities and the rate of deadwood decay in forests. This means that the accuracy of regional and global carbon budgets is uncertain, especially given ongoing changes to the structure of rainforest ecosystems. Therefore, to determine the effect of canopy openings on wood decay rates and regional carbon flux, we carried out the first assessment of deadwood mass loss within canopy gaps in old‐growth rainforest. We used replicated canopy gaps paired with closed canopy sites in combination with macroinvertebrate accessible and inaccessible woodblocks to experimentally partition the relative contribution of microbes vs. termites to decomposition within contrasting understorey conditions. We show that over a 12 month period, wood mass loss increased by 63% in canopy gaps compared with closed canopy sites and that this increase was driven by termites. Using LiDAR data to quantify the proportion of canopy openings in the study region, we modelled the effect of observed changes in decomposition within gaps on regional carbon flux. Overall, we estimate that this accelerated decomposition increases regional wood decay rate by up to 18.2%, corresponding to a flux increase of 0.27 Mg C ha−1 year−1 that is not currently accounted for in regional carbon budgets. These results provide the first insights into how small‐scale disturbances in rainforests can generate hotspots for decomposer activity and carbon fluxes. In doing so, we show that including canopy gap dynamics and their impacts on wood decomposition in forest ecosystems can help improve the predictive accuracy of the carbon cycle in land surface models.

Griffiths (2021) Global Change Biology