Evaluation of Pedotransfer Equations to Predict Deep Soil Carbon Stock in Tropical Podzols Compared to Other Soils of the Brazilian Amazon Forest

摘要

According to the soil measurement procedures proposed by the Intergovernmental Panel on Climate Change (TPCC), the sampling depth for SOC stock estimation is centred on the upper soil horizons where rootbiomass and organic matter inputs are concentrated, depending on soil type and ecosystem, typically between 0 and 0.3 m. However, recent research in areas of Amazonian Podzols has shown that these soils store a great amount of carbon in thick spodic horizons (Bh). The amount of carbon stored in deep Bh horizons of Podzols (down to 3 m) may exceed 80 kg C m~2 in some regions of the Amazon. Thus, a better understanding of the vertical distribution of the SOC in Amazonian soils is an urgent matter considering the volume of carbon stored in Podzols, in acontext of global climate change. Given this, the main goal of this research was to test and to propose pedotransfer functions based on several Amazonian soil profiles in order to estimate SOC stock and evaluate different soil attributes that could be used to infer indirectly, soil bulk density. For this propose, we selected around 320 pedons that were collected in the region of the Rio Negro Basin, to model the vertical distribution of SOC stock using a series of negative exponential profile depth functions and parametric/nonparametric functions for Podzols. The derived function parameters were used to predict carbon stock in deep horizons for all studied profiles and to explain the vertical behaviour of the SOC stock in Podzol profiles. The soil bulk density of Amazonian soils was properly modelled by symbolic regression, considering pH, clay content and SOC as the most relevant variables likely to affect soil bulk density values. We observed that the SOC stored in deep horizons of non-podzolic soils can be modelled by exponential decay equations. However, in Podzol, the vertical distribution of carbon stock is highly complex with asignificant increase in deep horizons, which cannot be explained by negative exponential functions. Our findings have shown that the SOC stock of Amazonian soils, excluding Podzols, can be predicted by fitted exponential functions (RMSE: 0.9 kg C m-2). However, the vertical variation of SOC stored in Podzol profiles can be modelled just by complex equations (equal-area spline RMSE: 13.6 kg C nT2; Fourier RMSE 15.9 kg C m"2 and Sum of Sines RMSE: 15.0 kg C m~2) with a large number of parameters. According to the results achieved in this research, we concluded that the SOC stock of Podzols can be indirectly estimated for the whole soil profile by integrating the Sum of Sines and Fourier equations, which is not possible when applying an equal-area splinefitting due to the absence of model parameters. Moreover, spodic horizons store most of the carbon pool of podzolic regions and the Podzols have more than twice of the capability of storing carbon when compared to other Amazonian soils.