Climate and topography controls on soil water-stable aggregates at regional scale: Independent and interactive effects

Abstract

Detailed information on the variability of soil–water stable aggregates (WSA) is critical for soil management practices, ecosystem services and soil erosion. Topography and climate are two of the most important factors influencing WSA variability at the regional to global scales, especially when soil management, agricultural practices, and soil types are similar, yet few studies have examined their independent and interactive effects on WSA. This work was conducted in the karst region of southwest China to investigate the influence of climatic and topographic variables on WSA variability at the regional scale. A total of 569 topsoil samples (0–20 cm) were collected by random sampling under long-term continuous mono-cropping of tobacco in March 2021. Classical statistics, semivariogram, recursive feature elimination (RFE) algorithm, random forest (RF), and GeoDetector were applied to investigate the relationships between WSA variability and several environmental factors, including 6 topographic, 11 temperature-, and 8 precipitation-related variables. Classical statistics showed that the mean WSA content was 51.67%, varying between 40.84% and 64.05%. Semivariogram analysis revealed the strong spatial autocorrelation of WSA (nugget effect = 10.09%). Based on the REF results, both RF modelling and GeoDetector identified 5 climatic variables, namely isothermality (BIO3), annual precipitation (BIO12), precipitation of wettest month (BIO13), precipitation of driest month (BIO14), and precipitation seasonality (BIO15), which dominated WSA variability at the regional scale. Moreover, the linear and non-linear fits of the key variables to WSA showed that BIO3, BIO12, BIO13, and BIO14 presented highly significantly negative correlations (p < 0.01) with WSA, whereas BIO15 had a highly significantly positive correlation (p < 0.01). The Spearman correlation coefficients of BIO3, BIO12, BIO13, BIO14, and BIO15 with WSA were 0.32, 0.44, 0.3, 0.37, and 0.41, respectively (p < 0.01). The interactive effects between topography and the five key climatic variables could facilitate the interpretation of individual variables for WSA variability. The dominant climatic factors of WSA variability changed along different topographical locations. Overall, this study identifies climatic (mainly precipitation) variables that dominated WSA variability at the regional scale and defines the interactive effects of these variables with topography on WSA variability. The results of this work contribute to explaining the complex causes of soil aggregate stability at large scale and provide clues to the management of soil security under climate change.