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Mapping Landscape Scale Variations of Forest Structure, Biomass, and Productivity in Amazonia : Volume 6, Issue 3 (04/06/2009)

By Saatchi, S.

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Book Id: WPLBN0004005280
Format Type: PDF Article :
File Size: Pages 45
Reproduction Date: 2015

Title: Mapping Landscape Scale Variations of Forest Structure, Biomass, and Productivity in Amazonia : Volume 6, Issue 3 (04/06/2009)  
Author: Saatchi, S.
Volume: Vol. 6, Issue 3
Language: English
Subject: Science, Biogeosciences, Discussions
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Gonzalez, G. L., Higuchi, N., Phillips, O. L., Zutta, B., Arroyo, L., Peacock, J.,...Pitman, N. (2009). Mapping Landscape Scale Variations of Forest Structure, Biomass, and Productivity in Amazonia : Volume 6, Issue 3 (04/06/2009). Retrieved from

Description: Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA. Landscape and environmental variables such as topography, geomorphology, soil types, and climate are important factors affecting forest composition, structure, productivity, and biomass. Here, we combine a network of forest inventories with recently developed global data products from satellite observations in modeling the potential distributions of forest structure and productivity in Amazonia and examine how geomorphology, soil, and precipitation control these distributions. We use the RAINFOR network of forest plots distributed in lowland forests across Amazonia, and satellite observations of tree cover, leaf area index, phenology, moisture, and topographical variations. A maximum entropy estimation (Maxent) model is employed to predict the spatial distribution of several key forest structure parameters: basal area, fraction of large trees, fraction of palms, wood density, productivity, and above-ground biomass at 5 km spatial resolution. A series of statistical tests at selected thresholds as well as across all thresholds and jackknife analysis are used to examine the accuracy of distribution maps and the relative contributions of environmental variables. The final maps were interpreted using soil, precipitation, and geomorphological features of Amazonia and it was found that the length of dry season played a key role in impacting the distribution of all forest variables except the wood density. Soil type had a significant impact on the wood productivity. Most high productivity forests were distributed either on less infertile soils of western Amazonia and Andean foothills, on crystalline shields, and younger alluvial deposits. Areas of low elevation and high density of small rivers of Central Amazonia showed distinct features, hosting mainly forests with low productivity and smaller trees.

Mapping landscape scale variations of forest structure, biomass, and productivity in Amazonia

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