Strategies to optimize modeling habitat suitability of Bertholletia excelsa in the Pan-Amazonia.

AIM: Amazon-nut (Bertholletia excelsa) is a hyperdominant and protected tree species, playing a keystone role in nutrient cycling and ecosystem service provision in Amazonia. Our main goal was to develop a robust habitat suitability model of Amazon-nut and to identify the most important predictor variables to support conservation and tree planting decisions. LOCALIZATION: Amazon region, South America. METHODS: We collected 3,325 unique Amazon-nut records and assembled >100 spatial predictor variables organized across climatic, edaphic, and geophysical categories. We compared suitability models using variables (a) selected through statistical techniques; (b) recommended by experts; and (c) integrating both approaches (a and b). We applied different spatial filtering scenarios to reduce overfitting. We additionally fine-tuned MAXENT settings to our data. The best model was selected through quantitative and qualitative assessments. RESULTS: Principal component analysis based on expert recommendations was the most appropriate method for predictor selection. Elevation, coarse soil fragments, clay, slope, and annual potential evapotranspiration were the most important predictors. Their relative contribution to the best model amounted to 75%. Filtering of the presences within a radius of 10 km displayed lowest overfitting, a satisfactory omission rate and the most symmetric distribution curve. Our findings suggest that under current environmental conditions, suitable habitat for Amazon-nut is found across 2.3 million km2, that is, 32% of the Amazon Biome. MAIN CONCLUSION: The combination of statistical techniques with expert knowledge improved the quality of our suitability model. Topographic and soil variables were the most important predictors. The combination of predictor variable selection, fine-tuning of model parameters and spatial filtering was critical for the construction of a reliable habitat suitability model.

Methane emissions from Amazonian Rivers and their contribution to the global methane budget.

Methane (CH4 ) fluxes from world rivers are still poorly constrained, with measurements restricted mainly to temperate climates. Additional river flux measurements, including spatio-temporal studies, are important to refine extrapolations. Here we assess the spatio-temporal variability of CH4 fluxes from the Amazon and its main tributaries, the Negro, Solimões, Madeira, Tapajós, Xingu, and Pará Rivers, based on direct measurements using floating chambers. Sixteen of 34 sites were measured during low and high water seasons. Significant differences were observed within sites in the same river and among different rivers, types of rivers, and seasons. Ebullition contributed to more than 50% of total emissions for some rivers. Considering only river channels, our data indicate that large rivers in the Amazon Basin release between 0.40 and 0.58 Tg CH4  yr(-1) . Thus, our estimates of CH4 flux from all tropical rivers and rivers globally were, respectively, 19-51% to 31-84% higher than previous estimates, with large rivers of the Amazon accounting for 22-28% of global river CH4 emissions.

Composition of particulate and dissolved organic matter in a disturbed watershed of southeast Brazil (Piracicaba River basin).

The elemental and isotopic composition of particulate and dissolved organic matter was investigated in the Piracicaba River basin, São Paulo State, Brazil. Comparison of riverine organic matter from the Piracicaba River basin, a region where rivers and streams receive urban sewage and industrial effluents, with data reported for the pristine Amazon system revealed significant differences associated with anthropogenic impacts. One important difference was N enrichment in the particulate organic material of the Piracicaba basin rivers, due to (a) urban and industrial effluents, and (b) enhanced phytoplankton growth, which results from the combination of nutrient enrichment and damming of sections of the rivers. Radiocarbon concentrations were overall more depleted (older 14C age) in the Piracicaba basin rivers than in the Amazon, which may reflect the importance of soil erosion in the former. Analyses of stable and radioactive carbon isotopes and lignin-derived compounds indicated that coarse particulate organic material is composed of a mixture of soil particles and degraded organic matter from C3 and C4 vascular plants. Fine particulate organic material was composed mainly of soil particles and phytoplankton cell remains, the latter especially during low water. Ultrafiltered dissolved organic matter was the most degraded fraction according to its lignin oxidation products, and showed the greatest influence of C4 plant sources.