Amazon drought and its implications for forest flammability and tree growth: a basin-wide analysis

摘要

Severe drought in moist tropical forests provokes large carbon emissions by increasing forest flammability and tree mortality, and by suppressing tree growth. The frequency and severity of drought in the tropics may increase through stronger El Nino Southern Oscillation (ENSO) episodes, global warming, and rainfall inhibition by land use change. However, little is known about the spatial and temporal patterns of drought in moist tropical forests, and the complex relationships between patterns of drought and forest fire regimes, tree mortality, and productivity. We present a simple geographic information system soil water balance model, called RisQue (Risco de Queimada - Fire Risk) for the Amazon basin that we use to conduct an analysis of these patterns for 1996-2001. RisQue features a map of maximum plant-available soil water (PAW(max)) developed using 1565 soil texture profiles and empirical relationships between soil texture and critical soil water parameters. PAW is depleted by monthly evapotranspiration (ET) fields estimated using the Penman-Monteith equation and satellite-derived radiation inputs and recharged by monthly rain fields estimated from 266 meteorological stations. Modeled PAW to 10 m depth (PAW(10 m)) was similar to field measurements made in two Amazon forests. During the severe drought of 2001, PAW(10 m) fell to below 25% of PAW(max) in 31% of the region's forests and fell below 50% PAW(max) in half of the forests. Field measurements and experimental forest fires indicate that soil moisture depletion below 25% PAW(max) corresponds to a reduction in leaf area index of approximately 25%, increasing forest flammability. Hence, approximately one-third of Amazon forests became susceptible to fire during the 2001 ENSO period. Field measurements also suggest that the ENSO drought of 2001 reduced carbon storage by approximately 0.2 Pg relative to years without severe soil moisture deficits. RisQue is sensitive to spin-up time, rooting depth, and errors in ET estimates. Improvements in our ability to accurately model soil moisture content of Amazon forests will depend upon better understanding of forest rooting depths, which can extend to beyond 15 m. RisQue provides a tool for early detection of forest fire risk.