A preliminary assessment of the space-for-time substitution method in soil carbon change prediction

Prediction of the soil C response to environmental change is often limited by the absence of temporal soil monitoring data from which applicable models can be developed. This constrains the understanding of the processes governing soil C cycling in data-poor areas. Here, we demonstrate a method to predict soil organic C (SOC) change over time based on the space-for-time (SFT) substitution method by constructing spatial and temporal datasets of SOC change from soil datasets pertaining to four periods over the past 40 yr in China. We empirically test the assumption that environmental drivers of the spatial gradients of SOC variation also drive SOC change over time. We find that the accuracy of SOC change predictions obtained with the SFT method is comparable to that of predictions directly obtained with temporal models, with the prediction performance ranging from 86 to 118%. Our results generally support the application of the SFT method to model SOC dynamics over time and highlight the importance of this method to better understand soil C cycling in ecosystems associated with insufficient soil monitoring data. Our findings provide a priori guidance for the suitability of the SFT method as an approach to infer the soil C response to environmental change.

Automated summary

This study demonstrates the use of the space-for-time substitution method to predict soil organic C change over time in data-poor areas. The results show that the accuracy of the predictions obtained with this method is comparable to that of predictions obtained with temporal models.