From rhizosphere to ecosystem: a cross-scale framework for biological nitrification inhibition research in natural plant communities*

YU Qinghan; CUI Xiaoyong

doi:10.7523/j.ucas.2026.024

Journal of University of Chinese Academy of Sciences >

0 260423

DOI: https://doi.org/10.7523/j.ucas.2026.024

From rhizosphere to ecosystem: a cross-scale framework for biological nitrification inhibition research in natural plant communities^*

YU Qinghan ,
CUI Xiaoyong

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College of Life Sciences, University of Chinese Academy of Sciences, Beijing 101408, China；Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing 101408, China

†E-mail：cuixy@ucas.ac.cn

Received date: 2026-01-27

Revised date: 2026-04-23

Online published: 2026-04-23

Supported by

*National Science Foundation of China(42371057)

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Abstract

Biological nitrification inhibition (BNI), a mechanism where plants suppress rhizospheric ammonium oxidation through specialized exudates, was initially identified in unmanaged ecosystems. However, contemporary research predominantly focuses on its agronomic applications for enhancing nitrogen fertilizer use efficiency. To address the critical knowledge gap regarding BNI's ecological roles in chronically nitrogen-limited ecosystems characterized by multispecies interactions and environmental heterogeneity, we advocate a paradigm shift: transitioning from crop-centric BNI screening to recognizing BNI as a plant functional trait whose context-dependent expression modulates rhizosphere nitrogen dynamics, plant-plant competition, and ecosystem nitrogen retention. This perspective necessitates a cross-scale framework addressing four interconnected questions: (1) Trait integration: How can BNI be incorporated as a rhizosphere process trait within plant trait spectra or networks, and how does it co-vary with resource-acquisition strategies, root traits, and nitrogen-form preference? (2) Rhizosphere mechanisms and microbial targets: Through which pathways do BNIs act in soils, including release, transport, sorption/degradation, and differential effects on ammonia-oxidizing microorganisms (e.g., AOA/AOB), and under what conditions are assay-based inhibitory effects translated into observable soil-process responses? (3) Community assembly mechanisms and ecological consequences: How does interspecific variation in BNI reshape rhizosphere NH₄⁺/NO₃^- supply to influence competition, coexistence, plant-soil feedbacks, and ecosystem nitrogen retention? (4) Macro-scale patterns and drivers: What macro-scale patterns are expected for BNI expression and associated nitrification suppression, and how are they shaped by climatic constraints, edaphic regulation, microbial community structure, and phylogenetic history? This framework bridges methodological advances (e.g., root exudate metabolomics) with ecological theory (e.g., trait-based community ecology), while proposing three operational strategies: (1) Modeling integration: Incorporate net nitrification rates, nitrification potential, and nitrification fluxes as core response variables in ecosystem models; (2) Experimental design: Implement gradient network experiments spanning soil moisture, pH, and substrate heterogeneity to quantify BNI-environment interactions; (3) Mechanistic scaling: Develop process-based models linking root exudate chemistry to nitrifier community assembly and N₂O emission hotspots. By linking mechanistic understanding with ecosystem-scale prediction, this framework repositions BNI from a localized soil process to a foundational concept for understanding nitrogen retention and transformation in natural ecosystems, with implications for sustainable nitrogen management under climate change.

Key words： Biological nitrification inhibition (BNI); rhizosphere; nitrification potential; ammonia oxidizers; root exudates; community assembly; biogeography

Cite this article

YU Qinghan , CUI Xiaoyong . From rhizosphere to ecosystem: a cross-scale framework for biological nitrification inhibition research in natural plant communities^*[J]. Journal of University of Chinese Academy of Sciences, 0 : 260423 . DOI: 10.7523/j.ucas.2026.024

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