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Abstract. Coarse dead wood is an important component of forestcarbon stocks, but it is rarely measured in Amazon forests and is typicallyexcluded from regional forest carbon budgets. Our study is based on lineintercept sampling for fallen coarse dead wood conducted along 103 transectswith a total length of 48 km matched with forest inventory plots wherestanding coarse dead wood was measured in the footprints of larger areas ofairborne lidar acquisitions. We developed models to relate lidar metrics andLandsat time series variables to coarse dead wood stocks for intact, logged,burned, or logged and burned forests. Canopy characteristics such as gaparea produced significant individual relations for logged forests. For totalfallen plus standing coarse dead wood (hereafter defined as total coarsedead wood), the relative root mean square error for models with only lidarmetrics ranged from 33 % in logged forest to up to 36 % in burnedforests. The addition of historical information improved model performanceslightly for intact forests (31 % against 35 % relative root mean squareerror), not justifying the use of a number of disturbance events fromhistorical satellite images (Landsat) with airborne lidar data.Lidar-derived estimates of total coarse dead wood compared favorably withindependent ground-based sampling for areas up to several hundred hectares.The relations found between total coarse dead wood and variables quantifyingforest structure derived from airborne lidar highlight the opportunity toquantify this important but rarely measured component of forest carbon overlarge areas in tropical forests.

Estimation of coarse dead wood stocks in intact and degraded forests in the Brazilian Amazon using airborne lidar