Abstract
Tropical peat swamp forests in Indonesia store huge amounts of carbon and are responsible for enormous carbon emissions every year due to forest degradation and deforestation. These forest areas are in the focus of REDD+ (reducing emissions from deforestation, forest degradation, and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks) projects, which require an accurate monitoring of their carbon stocks or aboveground biomass (AGB). Our study objective was to evaluate multi-temporal LiDAR measurements of a tropical forested peatland area in Central Kalimantan on Borneo. Canopy height and AGB dynamics were quantified with a special focus on unaffected, selective logged and burned forests. More than 11,000 ha were surveyed with airborne LiDAR in 2007 and 2011. In a first step, the comparability of these datasets was examined and canopy height models were created. Novel AGB regression models were developed on the basis of field inventory measurements and LiDAR derived height histograms for 2007 (r2 = 0.77, n = 79) and 2011 (r2 = 0.81, n = 53), taking the different point densities into account. Changes in peat swamp forests were identified by analyzing multispectral imagery. Unaffected forests accumulated on average 20 t/ha AGB with a canopy height increase of 2.3 m over the four year time period. Selective logged forests experienced an average AGB loss of 55 t/ha within 30 m and 42 t/ha within 50 m of detected logging trails, although the mean canopy height increased by 0.5 m and 1.0 m, respectively. Burned forests lost 92% of the initial biomass. These results demonstrate the great potential of repetitive airborne LiDAR surveys to precisely quantify even small scale AGB and canopy height dynamics in remote tropical forests, thereby featuring the needs of REDD+.
Highlights
Considering the global climate change, efforts are being made to reduce global greenhouse gas emissions
Changes in canopy height were evaluated on the basis of CHMs
This study demonstrates the enormous potential of multi-temporal airborne LiDAR surveys to accurately estimate aboveground biomass (AGB) dynamics in carbon rich tropical peat swamp forests
Summary
Considering the global climate change, efforts are being made to reduce global greenhouse gas emissions. One example of such a climate change mitigation mechanism is REDD+ which aims at reducing emissions from deforestation, forest degradation, and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks [1]. Tropical peatlands accumulate additional carbon in thick belowground peat deposits which are sustained by intact forests on top of it. The largest known tropical peat deposits occur in Southeast. Deforestation, forest degradation, and peatland degradation in Southeast Asia produce considerable carbon emissions (more than 220 Mt·C·y−1) [7,8]. Between 1997 and 2006, these activities were responsible for 23% of the total anthropogenic CO2 emissions worldwide [9]
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