HR: 0800h
AN: B51A-0060    [Abstracts]
TI: Impact of Selective Logging on Phenology in Amazon Rain-Forests
AU: * Koltunov, A
EM: akoltunov@ucdavis.edu
AF: Univercity of California, Davis, One Shields Ave. The Barn, Davis, CA 95616, United States
AU: Ustin, S L
EM: slustin@ucdavis.edu
AF: Univercity of California, Davis, One Shields Ave. The Barn, Davis, CA 95616, United States
AB: Selective logging (SL) in the Brazilian Amazon was recently shown in analyses of Landsat ETM+ data at high spatial resolution to be occurring at rates of about 12000-–20000 km ² per year, thus indicating the central role today of selective logging in disturbance of tropical forests. There has been few studies analyzing the effects of SL on forest phenology and no previous systematic study. Deforestation leads to persistent conversion of forest to another land cover/use type, which typically follows a significantly different phenological trajectory than the previous forest. Such changes in timing, growing season length, and trajectories of growth provide an integrated signal of altered ecosystem functionality. In contrast to deforestation, rapid closure of relatively small canopy gaps following SL may appear similar to natural regeneration phenomena in forests. As a result, forest biospheric processes and functions, as represented by phenological trajectories seem unaffected. We investigated the assumption that no significant change in forest function follows SL by analyzing a time-series of MODIS satellite data at 1-km scale in selectively logged forests in Mato Grosso, Brazil. The area studied is nearly 670000 km ² and is characterized by a large number of small SL events that occurred between 1999 and 2000. We tracked the phenological changes induced by these events using a time series of two MODIS vegetation indexes (VI), the Enhanced Vegetation Index, and the Normalized Difference Water Index. First, we show that even relatively low levels (5-–10%) of canopy damage cause significant and long-lasting (> 3 years) changes in forest phenology. Partial clearing impedes forest green-up in the dry season, progressively dehydrates the canopy, and induces overall seasonal deficits in canopy moisture and greenness. We outline the advanced optimized contextual statistical method used to detect phenological impacts, involving estimation of spectral changes at each 16-day time step. We discuss the SL impact in terms of phenological metrics derived from the observed and predicted time series and in relation to the SL intensity. Given the large and constantly increasing geographic extent of selective logging throughout Amazonia, phenological disturbances may have far- reaching impacts on carbon and water fluxes, nutrient dynamics, and other functional processes in Amazon forests.
DE: 0430 Computational methods and data processing
DE: 0466 Modeling
DE: 0480 Remote sensing
DE: 4227 Diurnal, seasonal, and annual cycles (0438)
DE: 4815 Ecosystems, structure, dynamics, and modeling (0439)
SC: Biogeosciences [B]
MN: 2007 Fall Meeting