Reconstructions of four-dimensional spatiotemporal characteristics of soil organic carbon stock in coastal wetlands during the last decades

Abstract

In the context of multiple disturbances, soil organic carbon stock (SOCS) in coastal wetlands experiences drastic spatiotemporal variations, which involve four dimensions. However, the finiteness and discontinuity of historical field soil data hinder the four-dimensional SOCS reconstruction in coastal wetlands. In this study, the zonal and progressive simulations were integrated to reconstruct the four-dimensional characteristics of coastal wetland SOCS by using field soil data in current time point and remote sensing data during the last decades. The zonal simulation was adopted to conduct the two-dimensional simulation at a low cost of field survey. The spatial and temporal progressive simulations were implemented based on the close relationships among soil factors in different depths and at different time points, respectively, for realizing the three- and four-dimensional simulations. The demonstration of the study in Chongming Island, an important coastal wetland in China, validated the low cost, high accuracy, and good applicability of the approach. Over the entire island during the last decades, SOCS in surface layer showed overall increasing characteristics, while SOCS in intermediate and bottom layers did not exhibit distinct change trend. Generally, SOCS in surface layer increased and that in intermediate and bottom layers decreased along the gradient from the shoreline to the inner island. Continuous sediment discharge and deposition enlarged the areas of coastal wetlands and thus increased SOCS in the alongshore areas. Human activities distinctly increased SOCS through long-term and large-scale agricultural activities in the inner island, while decreased it through urbanization. Then, healthy, coordinated, and sustainable measures for increasing coastal wetland SOCS were proposed from perspectives of scale control, spatial configuration, and quality promotion. Therefore, this approach could reconstruct SOCS four-dimensional characteristics and achieve the conversions of soil data from point to area, from surface to bottom, and from present to past.