Spatial distributions and the main driving factors of soil total nitrogen in Zhejiang Province, China

• Spatial distributions and driving factors of STN was studied. • Spatial distribution pattern of STN in Zhejiang province was determined. • Nitrogen deposition was the main factor influencing the spatial variability of STN. • Partial dependence plots showing the dependence of STN on predictors were presented. Nitrogen is an indispensable element in the growth and development stages of various crops, as well as an important component of soil nutrients. It plays an important role in farmland ecosystems. Studying the spatial distribution of soil total nitrogen (STN) is essential for improving the efficiency of soil fertility management and for a better understanding of the soil nitrogen cycle. In the study, the STN content data of surface soil (0–20 cm) were obtained from 19,119 sampling sites within an area of 7.47 × 10 4 km 2 based on a multi-purpose regional geochemical survey established in Zhejiang Province, China, from 2002 to 2018. The spatial distribution and main driving factors of STN were determined using the random forest model. The results showed that the average STN content in the topsoil of the Zhejiang Province was 1.48 g⋅kg −1 . Among the different land-use types, grassland soil had the highest STN content of 1.55 g⋅kg −1 , and alfisol had the highest STN content of 2.59 g⋅kg −1 . The spatial distribution of STN content was high in the northern part and low in the southern part of the study area. The results of the random forest analysis showed that nitrogen deposition, pH, and mean annual precipitation (MAP) were the most important factors influencing the spatial variability of STN. The STN content exhibited a nonlinear decrease with an increase in pH and MAP and a nonlinear increase with an increase in nitrogen deposition. This study provides decision-makers with synthesized information on the spatial variability of STN and its driving factors in Zhejiang Province, which is important for accurately grasping the spatial distribution characteristics of STN to implement precision agriculture management measures.