Small-scale logging leads to clear-cutting in Brazilian Amazon

Stanford, CA-A team of scientists, led by Greg Asner of the Carnegie Institution's Department of Global Ecology, has discovered an important indicator of rain forest vulnerability to clear-cutting in Brazil. Their five-year study is the first to quantify the relationship between selective logging, where loggers extract individual trees from the rain forest, and complete deforestation, or clear-cutting. They found that 16% of rain forests, which had been selectively logged, were completely clear-cut within one year and 32% of logged areas were completely cleared within four years. Virtually all of this double damage occurs within 15 miles (25 km) miles of major roads. Practically no selective logging takes place at distances greater than 15 miles from the roads.

The results, published during the week of July 31, 2006, in the on-line early edition of The Proceedings of the National Academy of Sciences,** come on the heels of recent Brazilian legislation to regulate logging for better sustainability and the announcement by the Brazilian National Space Research Institute (INPE) to develop a remote sensing system to monitor logging in collaboration with the Brazilian non-governmental organization, IMAZON. The on-going work of the Carnegie-led team could bolster the long-term timber management goals and monitoring efforts of the government.

The scientists used their novel high-resolution, remote-sensing techniques to measure logging and combined that information with the deforestation maps that Brazil makes publicly available through the INPE PRODES program. "We surveyed an area that is about three times the size of Texas from 1999 to 2004," explained Asner. Diane Wickland, Manager of the Terrestrial Ecology Program at NASA Headquarters, who funded the study, hailed this work as "a compelling demonstration of how satellite data can be used to provide quantitative information over large regions--regions too large to measure effectively in any other

Contact: Greg Asner
Carnegie Institution

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