Abstract
Global soil nitrogen (N) cycling remains poorly understood due to its complex driving mechanisms. Here, we present a comprehensive analysis of global soil δ15N, 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 δ15N. The joint effects of multiple drivers govern the latitudinal distribution of soil δ15N, 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 δ15N, 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.
Original language | English (US) |
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Article number | e17309 |
Journal | Global change biology |
Volume | 30 |
Issue number | 5 |
DOIs | |
State | Published - May 2024 |
Externally published | Yes |
Keywords
- Rayleigh theory
- climatic conditions
- natural and anthropogenic forcings
- nitrogen isotope
- plant traits
- soil properties
ASJC Scopus subject areas
- Global and Planetary Change
- Environmental Chemistry
- Ecology
- General Environmental Science