Spatial Heterogeneity and Key Influencing Factors of Soil Organic Carbon, Soil Total Nitrogen, and Carbon to Nitrogen Ratio in main plantations of Torreya grandis cv. Merrillii

Abstract

Soil organic carbon （SOC） and soil total nitrogen （STN） serve as important indicators of the elemental balance within forest ecosystems reflecting soil fertility and quality. Accurate knowledge regarding the spatial variability of regional SOC, STN, and C∶N ratio and their influencing factors is of great significance for precise fertilization and soil health. In this study, a total of 117 topsoil samples （0-20 cm in depth） based on a 1 km×1 km grid were collected in the Torreya grandis cv. Merrillii plantation in Zhejiang Province. A combination of multi-dimensional statistical approaches （random forest model, structural equation model, redundancy analysis, and variation partitioning analysis） and diverse spatial analytical techniques （geostatistics, Moran's I index, etc.） were applied to reveal the spatial distributions and influencing factors of SOC, STN, and C∶N ratio in the Torreya. grandis cv. Merrillii region. The results showed that the average ω（SOC）, ω（STN）, and C∶N ratio were 17.63 g·kg-1, 1.48 g·kg-1, and 12.65, respectively, and their coefficients of variation were 68.08%, 67.41%, and 46.03%, respectively, indicating a moderate degree of variability. In general, the SOC, STN, and C∶N ratio of the Torreya grandis cv. Merrillii plantations were at an intermediate level in the national plantation. The semi-variance results showed that the nugget/sill values of SOC, STN, and C∶N ratio were 49.98%, 45.88%, and 49.93%, respectively, demonstrating a moderate level of spatial autocorrelation. The spatial distribution results showed that SOC, STN, and C∶N ratio decreased from northeast to southwest, with the majority of the region exhibiting above-medium fertility levels of SOC. The results of correlation analysis and redundancy analysis indicated that AN, AP, and AK were significantly correlated with both SOC, STN, and C∶N ratio （P<0.05）. The results of random forest, structural equation model, and variation partitioning analysis evidenced that the main influencing factors of SOC and STN were soil-available nutrients （AN, AP, and AK）. Therefore, our results could provide important insights for enhancing soil carbon and nitrogen pools in special plantations in Zhejiang Province, enhancing the capacity of plantations to adapt to regional climate change through ecological measures such as appropriate fertilization practices and strategic understory vegetation cultivation.