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There is increasing interest in the application of digital soil mapping (DSM) projections to infer changes in soil carbon across both space and time. This approach relies on the assumption that the spatially modeled soil carbon-environment relationship can be transferred over time. However, this assumption is rarely tested due to a lack of temporally independent validation data. This paper assesses this assumption by developing models of topsoil organic carbon stocks (SOCS) with a deep learning algorithm and data covering mainland China pertaining to the 1980s and 2010s. The temporal prediction performance of models capturing a specific period was assessed by evaluating their performance in the prediction of data during another period. The results revealed that the prediction accuracy of temporal modeling decreased, as indicated by the coefficient of determination, and was lower than that of spatial modeling. The lower prediction accuracy obtained with the DSM-projection approach may result from differences in the magnitudes of influential variables across periods. We found that different levels of environmental similarity and model projection sensitivity to dynamic variables may cause discrepancies in forecast and hindcast accuracy. Our results demonstrate that the prediction error in temporal modeling is related to the degree of environmental similarity between periods. Our findings generally support the implementation of the DSM-projection approach in soil carbon change modeling. However, caution should be exercised, as there exists much uncertainty regarding the projection of spatial models over time. • DSM projection may facilitate a more precise estimation of large-scale soil carbon changes. • Discrepancies in the environment between periods reduce the temporal predictive skill. • The variability in the model performance is related to the magnitude of environmental influences. [ABSTRACT FROM AUTHOR]

Abstract: Holocene environmental change and environmental archaeology are important components of an international project studying the human-earth interaction system. This paper reviews the progress of Holocene environmental change and environmental archaeology research in the Yangtze River Valley over the last three decades, that includes the evolution of large freshwater lakes, Holocene transgression and sea-level changes, Holocene climate change and East Asian monsoon variation, relationship between the rise and fall of primitive civilizations and environmental changes, cultural interruptions and palaeoflood events, as well as relationship between the origin of agriculture and climate change. These research components are underpinned by the dating of lacustrine sediments, stalagmites and peat to establish a chronology of regional environmental and cultural evolution. Interdisciplinary and other environment proxy indicators need to be used in comparative studies of archaeological site formation and natural sedimentary environment in the upper, middle and lower reaches of the Yangtze River Valley. Modern technology such as remote sensing, molecular bioarchaeology, and virtual reality, should be integrated with currently used dating, geochemical, sedimentological, and palaeobotanical methods of analysis in environmental archaeology macro- and micro-studies, so as to provide a greater comprehensive insight into Holocene environmental and cultural interaction and change in the Yangtze River Valley area. [Copyright &y& Elsevier]