Atypical soil carbon distribution across a tropical steepland forest catena

Soil organic carbon (SOC) in a humid subtropical forest in Puerto Rico is higher at ridge locations compared to valleys, and therefore opposite to what is commonly observed in other forested hillslope catenas. To better understand the spatial distribution of SOC in this system, plots previously characterized by topographic position, vegetation type and stand age were related to soil depth and SOC. Additional factors were also investigated, including topographically-related differences in litter dynamics and soil chemistry. To investigate the influence of litter dynamics, the Century soil organic model was parameterized to simulate the effect of substituting valley species for ridge species. Soil chemical controls on C concentrations were investigated with multiple linear regression models using iron, aluminum and clay variables. Deeper soils were associated with indicators of higher landscape stability (older tabonuco stands established on ridges and slopes), while shallower soils persisted in more disturbed areas (younger non-tabonuco stands in valleys and on slopes). Soil depth alone accounted for 77% of the observed difference in the mean 0 to 60 cm SOC between ridge soils (deeper) and valley soils (shallower). The remaining differences in SOC were due to additional factors that lowered C concentrations at valley locations in the 0 to 10 cm pool. Model simulations showed a slight decrease in SOC when lower litter C:N was substituted for higher litter C:N, but the effects of different woody inputs on SOC were unclear. Multiple linear regression models with ammonium oxalate extractable iron and aluminum, dithionite-citrate-extractable iron and aluminum, and clay contents explained as much as 74% of the variation in C concentrations, and indicated that organo-mineral complexation may be more limited in poorly developed valley soils. Thus, topography both directly and indirectly affects SOC pools through a variety of inter-related processes that are often not quantified or captured in terrestrial carbon models. Published by Elsevier B.V.