Soil pH and latitude as a major predictor of C:N:P stoichiometry in Germany

Soil stoichiometry governs nutrient cycling to ensure optimal ecosystem functionality. Although the soil carbon‑nitrogen‑phosphorus (C:N:P) stoichiometry and ecosystem functioning are closely related, much less is known about how environmental predictors regulate the spatial distribution of these ratios in temperate regions. Specifically, the statistical relationships of soil properties (such as soil pH and clay content), climate variables (like precipitation and temperature), and topographic features (i.e., slope and aspect) on C:N:P stoichiometric patterns at regional scales remain poorly understood. In our study, we combined Cubist machine learning for spatial predictions with state-of-the-art statistical approaches—generalized additive models and structural equation modeling—to disentangle the quantitative relationships between environmental predictors and soil C:N, C:P, and N:P ratios across Germany. The relative importance analysis of environmental predictors shows that soil pH is the major predictor of stoichiometric ratios, acting through its fundamental control on nutrient availability. Higher soil pH corresponded to lower stoichiometric ratios and vice versa. Latitude emerged as another important predictor due to its effect on temperature, which plays a crucial role in these ratios, such that increasing latitude corresponds to lower ratios. As expected, wall-to-wall spatial distribution maps of the stoichiometric ratios showed varying patterns due to different environmental predictor influences. These findings enhance our understanding of environmental-stoichiometric interactions and offer valuable insights needed for sustainable soil management in temperate regions.