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Biogeosciences An interactive open-access journal of the European Geosciences Union
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© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 08 Apr 2019

Research article | 08 Apr 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Biogeosciences (BG).

Estimation of Coarse Woody Debris Stocks in Intact and Degraded Forests in the Brazilian Amazon Using Airborne Lidar

Marcos A. S. Scaranello1, Michael Keller1,2,3, Marcos Longo1,3, Maiza N. dos-Santos1, Veronika Leitold4, Douglas C. Morton4, Ekena R. Pinagé5,6, and Fernando D. B. Espírito-Santo7,8 Marcos A. S. Scaranello et al.
  • 1Embrapa Informática Agropecuária, Embrapa, Campinas, 13083-886, Brazil
  • 2International Institute of Tropical Forestry, USDA Forest Service, Río Piedras, 00926-1119, Puerto Rico
  • 3Jet Propulsion Laboratory, California Institute of Technology, Pasadena, 91109, USA
  • 4NASA Goddard Space Flight Center, NASA, Maryland, 20771, USA
  • 5School of Life Sciences, University of Technology Sydney, Sydney, 2007, Australia
  • 6College of Forestry, Oregon State University, Corvallis, 97331, USA
  • 7Centre for Landscape and Climate Research (CLCR) and Leicester Institute of Space and Earth Observation (LISEO), School of Geography, Geology and Environment, University of Leicester, Leicester, UK
  • 8Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, 14040-900, Brazil

Abstract. Coarse dead wood is an important component of forest carbon stocks, but it is rarely measured in Amazon forests and is typically excluded from regional forest carbon budgets. Our study is based on line intercept sampling for fallen coarse dead wood conducted along 103 transects with a total length of 48 km matched with forest inventory plots where standing coarse dead wood was measured in the footprints of larger areas of airborne lidar acquisitions. We developed models to relate lidar metrics and Landsat time series variables to coarse dead wood stocks for intact, logged, and burned or logged and burned forests. Canopy characteristics such as gap area produced significant individual relations for logged forests. For total fallen plus standing coarse dead wood (hereafter defined as total coarse dead wood), the relative root mean square error for models with only lidar metrics ranged from 33 % in logged forest to up to 36 % in burned forests. The addition of historical information improved model performance slightly for intact forests (31 % against 35 % relative root mean square error), not justifying the use of number of disturbances events from historical satellite images (Landsat) with airborne lidar data. Lidar-derived estimates of total coarse dead wood compared favorably to independent ground-based sampling for areas up to several hundred hectares. The relations found between total coarse dead wood and structural variables derived from airborne lidar highlight the opportunity to quantify this important, but rarely measured component of forest carbon over large areas in tropical forests.

Marcos A. S. Scaranello et al.
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Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Marcos A. S. Scaranello et al.
Marcos A. S. Scaranello et al.
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Short summary
The coarse dead wood (CDW) component of tropical forest carbon pool is rarely measured. We created models for predicting CDW in Amazonian rainforests by using active remote sensing data. Our models produced site-based estimates of CDW that were similar to independent field estimates found in the literature. Our study provides, for the first time, the opportunity for creating maps of coarse dead wood at large scales in the Amazonian intact and degraded forests.
The coarse dead wood (CDW) component of tropical forest carbon pool is rarely measured. We...