journal article·2026-06-22Open access

Correcting Apparent Priming Bias Unveils Fertilizer Nitrogen‐Risk Archetypes of Surplus and Depletion Across Asian Rice Systems

Xiuyun Liu, Siyuan Cai, Longlong Xia, Jagdish K. Ladha, Xiaoyuan Yan, Xu Zhao

Abstract

ABSTRACT Accurate assessment of fertilizer nitrogen (N) fate is essential for optimizing rice production, yet regional‐scale estimates remain limited. This progress has been fundamentally constrained by the prohibitive cost of isotopic tracing, which has not only limited large‐scale deployment but also prevented the correction of apparent priming effect (APE)‐induced bias, resulting in a systematic misestimation of soil N retention. To overcome this limitation, a continental‐scale framework is developed to quantify fertilizer N fate across Asian rice systems. Ensemble modeling produces the first high‐resolution (5 arcmin) maps of Net Residue and Loss, identifying Eastern and Central China, along with Northern India, as critical Loss hotspots. Accounting for APE reveals that positive priming suppresses the Net Residue of applied N to below 7% (−1%–15%), while 48% (43%–53%) of applied N is lost to the environment, leading to annual environmental costs of US$98.53 (83.25–108.27) billion from reactive‐N emissions. Crucially, three N‐risk archetypes that together encompass 42% of global rice fields emerge: 37% high‐loss/high‐net‐residue, 2% high‐loss‐soil‐depleting, and 3% low‐loss‐soil‐mining. Overall, this framework converges high‐resolution ensemble mapping, apparent priming bias correction, and policy‐oriented N‐risk archetypes to transform N governance from retrospective accounting into a spatially targeted, forward‐looking strategy reconciling food security with environmental and economic sustainability.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Soil Carbon and Nitrogen Dynamics · Soil and Water Nutrient Dynamics · Climate change impacts on agriculture

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of Soil and Sustainable Agriculture Changshu National Agro‐Ecosystem Observation and Research Station Institute of Soil Science Chinese Academy of Sciences Nanjing China

University of Chinese Academy of Sciences Beijing China

University of Chinese Academy of Sciences Nanjing China

Department of Plant Sciences University of California Davis California USA

Funding

National Natural Science Foundation of China · Natural Science Foundation of Jiangsu Province

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