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LC-33 Abstract

Integrating Satellite, Modeling and Synthesis Approaches to Understand the Role of Selective Logging on Biogeochemical Cycles in Amazonia

Gregory Paul Asner — Carnegie Institution (US-PI)
Mercedes Bustamante — UnB - Universidade de Brasília (SA-PI)

Selective logging is a dominant form of land use in the Brazilian Amazon. Although we are approaching the end of major NASA involvement in LBA, surprisingly little is known about the biogeochemical effects of logging in Amazon forests and the carbon cycle. At the scale of the entire Basin, the extent of logging remains hotly contested, with current estimates ranging from 4,000-23,000 km2 yr-1. Furthermore, until very recently, there was little information on changes in nutrient stocks and dynamics in selectively logged forests – changes that largely determine the long-term effects of timber harvests on the carbon cycle. During LBA Phase-II, we have developed, tested and successfully employed a method to quantify the extent of selective logging in the Brazilian Amazon using Landsat 7 ETM+ data with the new Carnegie Landsat Analysis System (CLAS). CLAS will produce the first high spatial resolution geographic coverages of selective logging extent and canopy fractional cover over large regions, and these data products are highly correlated with field-measured forest gap fraction, the volume and biomass of wood removed from the forest, foliage deposited on the forest floor, and coarse woody debris remaining in the harvest sites. This automated, high-resolution remote sensing approach now opens a door to regional-scale synthesis of logging extent and intensity as well as the resulting changes in carbon and nutrient stocks.



We propose to extend our remote sensing studies from LBA Phase-II by applying our forthcoming Amazon selective logging data products, along with a literature synthesis of biogeochemical responses to logging, to extrapolate carbon and nutrient stock changes associated with this land use. We will also couple the CLAS products to MODIS phenology data in the TerraFlux biogeochemical model, using a forest canopy radiative transfer sub-model as the method of linkage, to predict changes in NPP and carbon storage in select Amazon forest stands that have undergone selective logging. Finally, we will use the CLAS logging products to assess spatio-temporal relationships between timber harvest and deforestation (clear-cutting) over large regions of the Amazon basin.



The project will produce synthesis products to be freely shared by LBA investigators and the international community. These include: (1) regional extrapolations of selective logging extent, canopy damage and its estimated impact on carbon and nutrient stocks; (2) a synthesis review of nutrient and carbon cycle responses to selective logging during and following harvest; (3) stand-level simulations of how timber harvests that alters nutrient stocks/fluxes ultimately impact rates of forest regeneration and carbon accumulation; and (4) a spatially-specific analysis of selective logging as a potential precursor to deforestation across the Brazilian Amazon frontier. This project will have an educational component, including: (a) training a Brazilian and an American post-doc, including exchange between the co-PIs labs; (b) short-course training of students from the Universidade de Brasilia in biogeochemical modeling and remote sensing; and (c) faculty training on biogeochemical modeling for future teaching endeavors in Brazil.

The project will directly address LBA questions LC-Q3, CD-Q3b, CD-Q3c, and ND-Q1. In doing so, we will contribute to answering the overall LBA question: “How do tropical forest conversion, re-growth and selective logging influence carbon storage, nutrient dynamics, trace gas fluxes, and the prospect for sustainable land use in Amazonia?” Our study represents a major synthesis on the logging issue using a combination of satellite, computer modeling and literature review approaches. As such, the lead PI (Greg Asner) volunteers to coordinate an LBA-wide synthesis of logging extent and its effects on the biophysical, biogeochemical, and biosphere-atmosphere exchange processes in Amazonia.

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