Dynamics of a human-modified tropical peat swamp forest revealed by repeat lidar surveys.

Tropical peat swamp forests (PSFs) are globally important carbon stores under threat. In Southeast Asia, 35% of peatlands had been drained and converted to plantations by 2010, and much of the remaining forest had been logged, contributing significantly to global carbon emissions. Yet, tropical forests have the capacity to regain biomass quickly and forests on drained peatlands may grow faster in response to soil aeration, so the net effect of humans on forest biomass remains poorly understood. In this study, two lidar surveys (made in 2011 and 2014) are compared to map forest biomass dynamics across 96 km2 of PSF in Kalimantan, Indonesia. The peatland is now legally protected for conservation, but large expanses were logged under concessions until 1998 and illegal logging continues in accessible portions. It was hypothesized that historically logged areas would be recovering biomass while recently logged areas would be losing biomass. We found that historically logged forests were recovering biomass near old canals and railways used by the concessions. Lidar detected substantial illegal logging activity-579 km of logging canals were located beneath the canopy. Some patches close to these canals have been logged in the 2011-2104 period (i.e. substantial biomass loss) but, on aggregate, these illegally logged regions were also recovering. Unexpectedly, rapid growth was also observed in intact forest that had not been logged and was over a kilometre from the nearest known canal, perhaps in response to greater aeration of surface peat. Comparing these results with flux measurements taken at other nearby sites, we find that carbon sequestration in above-ground biomass may have offset roughly half the carbon efflux from peat oxidation. This study demonstrates the power of repeat lidar survey to map fine-scale forest dynamics in remote areas, revealing previously unrecognized impacts of anthropogenic global change.

Allometric equations for integrating remote sensing imagery into forest monitoring programmes.

Remote sensing is revolutionizing the way we study forests, and recent technological advances mean we are now able - for the first time - to identify and measure the crown dimensions of individual trees from airborne imagery. Yet to make full use of these data for quantifying forest carbon stocks and dynamics, a new generation of allometric tools which have tree height and crown size at their centre are needed. Here, we compile a global database of 108753 trees for which stem diameter, height and crown diameter have all been measured, including 2395 trees harvested to measure aboveground biomass. Using this database, we develop general allometric models for estimating both the diameter and aboveground biomass of trees from attributes which can be remotely sensed - specifically height and crown diameter. We show that tree height and crown diameter jointly quantify the aboveground biomass of individual trees and find that a single equation predicts stem diameter from these two variables across the world's forests. These new allometric models provide an intuitive way of integrating remote sensing imagery into large-scale forest monitoring programmes and will be of key importance for parameterizing the next generation of dynamic vegetation models.