Abstract

Density fractionation is now a potential approach for distinguishing among the functions of different soil organic carbon (SOC) pools in a forest ecosystem. The co-existence of evergreen and deciduous forest types in seasonally dry tropics is favorable for clarifying the effect of contrasting plant functional trait on the size and quality of SOC pools under the high temperature regime. We examined whether forest type (deciduous vs. evergreen), mineral factor (aluminum and iron oxide) and climatic condition (temperature and precipitation) affect the size and quality of SOC pools in bulk soil and density fractions in a seasonally dry tropical forest of continental Southeast Asia. The forest type and mineral factor affected the quality and size, respectively, of SOC pools. The forest type had significant effects on carbon-to-nitrogen (C:N) ratios of leaf litter and free form of light fraction. However, variations in the size of the SOC pools at a depth of 0–30cm and in each topsoil density fraction were explained exclusively by the mineral factor, i.e., aluminum oxide extractable by acid ammonium oxalate, regardless of variations in forest type and precipitation pattern. It was suggested that the surface area of clay mineral was the dominant factor for the storage capacity of SOC in the study area. The aluminum and related oxides might also increase intra-aggregate space for occluded form of light fraction. The impact of the climatic factor on the SOC pools was not found in a significant level though its effect including humid tropics on the composition of SOC remains a subject of future investigation. The linear models with variables of SOC and soil organic nitrogen favorably estimated the size of the C and N pools in the light fraction independent of the forest type. These regression models help to estimate the wide-area distribution of labile SOC pools of plant detritus form and its digital mapping, combined with a dataset of bulk SOC content. And it will provide incentives for C sequestration practice under forest management in seasonally dry tropical forests through the spatially-defined assessment of reduction effect of C emissions.

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