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Understanding how soil respiration (Rs) responds to sustained nitrogen loading is critical for constraining carbon–climate feedbacks. However, current assessments largely overlook the potential for substantial temporal shifts in these responses. Here, we address this gap by synthesizing time-series Rs records from long-term manipulation experiments worldwide. We reveal a nonlinear temporal trajectory in Rs responses to nitrogen addition, transitioning from short-term stimulation to long-term suppression. Nitrogen addition rate did not significantly accelerate this temporal shift, but higher nitrogen inputs produced stronger overall suppression. Our findings extend the prevailing spatial-oriented analyses by showing that nitrogen enrichment effects on soil carbon fluxes depend strongly on exposure duration and cumulative nitrogen input. Abstract Soil stores the largest pool of actively cycling carbon (C) on land, and its dynamics under global changes are critical for projecting climate feedbacks. Global nitrogen (N) deposition has more than doubled since the 1860s; however, the temporal dynamics of soil C emissions under prolonged N deposition are poorly understood. Here, using a global time-series dataset compiled from 38 long-term experiments in forests and grasslands, we find that the response of soil respiration (Rs) to N addition systematically shifts from a transient increase persisting for approximately 2 y to a sustained suppression over time (mean effect = −6%; 95% CI = [−10%, −3%]). Rs in forests and grasslands followed consistent nonlinear trajectories, characterized by a rapid initial decline in the magnitude of the response, which progressively leveled off. Notably, suppression of Rs emerged when cumulative N inputs exceeded a threshold of ~100 kg N ha−1. Consequently, the suppression was both stronger and occurred more rapidly under high-level N additions (>50 kg N ha−1 y−1). These temporal dynamics were associated with N-induced soil acidification and related changes in microbial properties. Overall, these findings indicate that accurate prediction of land–atmosphere C fluxes under global change requires models to capture the reported temporal dynamics.