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Biomass accumulation in the secondary forests of abandoned pastures and slash-and-burn agricultural fallows is an important but poorly constrained component of the regional carbon budget for the Brazilian Amazon. Using empirical relationships derived from a global analysis, we predicted potential aboveground biomass accumulation (ABA) for the region\'s regrowth forests based on soil texture and climate data. For regrowth forests on nonsandy soils, the globally derived relationship provided a nearly unbiased linear predictor of Amazonian validation data consisting of 66 stands at seven sites; there was no significant difference between stands that regrew following use as pasture land and those that regrew following slash-and-burn agriculture. For regrowth forests on nonsandy soil, the 1 sigma error range of our ABA model was 58%-171% for the Amazonian validation data. For regrowth forests on sandy soils, the validation data were limited to 19 stands at one site, and the globally derived relationship was substantially biased multiplicatively and nonlinearly. Hence we developed a regional refinement by adding to our validation data ABA values from the two Amazonian sites with sandy soil that had previously been included in the global analysis. Based on a conservative jackknife goodness-of-fit assessment (leaving out one site at a time), we calculated a 1 sigma error range of 42%-158% for our sandy soil Amazonian regrowth forest ABA model. We present our predictions of potential regrowth forest ABA as a set of 0.5 degrees resolution maps for the region at 5, 10, and 20 years following abandonment.

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