Abstract
Global soil nitrogen (N) cycling remains poorly understood due to its complex driving mechanisms. Here, we present a comprehensive analysis of global soil δ 15 N, a stable isotopic signature indicative of the N input–output balance, using a machine‐learning approach on 10,676 observations from 2670 sites. Our findings reveal prevalent joint effects of climatic conditions, plant N‐use strategies, soil properties, and other natural and anthropogenic forcings on global soil δ 15 N. The joint effects of multiple drivers govern the latitudinal distribution of soil δ 15 N, with more rapid N cycling at lower latitudes than at higher latitudes. In contrast to previous climate‐focused models, our data‐driven model more accurately simulates spatial changes in global soil δ 15 N, highlighting the need to consider the joint effects of multiple drivers to estimate the Earth's N budget. These insights contribute to the reconciliation of discordances among empirical, theoretical, and modeling studies on soil N cycling, as well as sustainable N management.