Remote sensing detection of droughts in Amazonian forest canopies.

*Remote sensing data are a key tool to assess large forested areas, where limitations such as accessibility and lack of field measurements are prevalent. Here, we have analysed datasets from moderate resolution imaging spectroradiometer (MODIS) satellite measurements and field data to assess the impacts of the 2005 drought in Amazonia. *We combined vegetation indices (VI) and climatological variables to evaluate the spatiotemporal patterns associated with the 2005 drought, and explore the relationships between remotely-sensed indices and forest inventory data on tree mortality. *There were differences in results based on c4 and c5 MODIS products. C5 VI showed no spatial relationship with rainfall or aerosol optical depth; however, distinct regions responded significantly to the increased radiation in 2005. The increase in the Enhanced VI (EVI) during 2005 showed a significant positive relationship (P < 0.07) with the increase of tree mortality. By contrast, the normalized difference water index (NDWI) exhibited a significant negative relationship (P < 0.09) with tree mortality. *Previous studies have suggested that the increase in EVI during the 2005 drought was associated with a positive response of forest photosynthesis to changes in the radiation income. We discuss the evidence that this increase could be related to structural changes in the canopy.

Interactions between rainfall, deforestation and fires during recent years in the Brazilian Amazonia.

Understanding the interplay between climate and land-use dynamics is a fundamental concern for assessing the vulnerability of Amazonia to climate change. In this study, we analyse satellite-derived monthly and annual time series of rainfall, fires and deforestation to explicitly quantify the seasonal patterns and relationships between these three variables, with a particular focus on the Amazonian drought of 2005. Our results demonstrate a marked seasonality with one peak per year for all variables analysed, except deforestation. For the annual cycle, we found correlations above 90% with a time lag between variables. Deforestation and fires reach the highest values three and six months, respectively, after the peak of the rainy season. The cumulative number of hot pixels was linearly related to the size of the area deforested annually from 1998 to 2004 (r2=0.84, p=0.004). During the 2005 drought, the number of hot pixels increased 43% in relation to the expected value for a similar deforested area (approx. 19000km2). We demonstrated that anthropogenic forcing, such as land-use change, is decisive in determining the seasonality and annual patterns of fire occurrence. Moreover, droughts can significantly increase the number of fires in the region even with decreased deforestation rates. We may expect that the ongoing deforestation, currently based on slash and burn procedures, and the use of fires for land management in Amazonia will intensify the impact of droughts associated with natural climate variability or human-induced climate change and, therefore, a large area of forest edge will be under increased risk of fires.