Modeling interplant competition in maize: Integrating density-dependent specific leaf area plasticity enhances canopy light and nitrogen use efficiency

• The adjustment of SLA under dense planting optimizes canopy photosynthesis and resource use efficiency • GreenLab-Maize with parameterized SLA can predict the effects of intensified interplant competition Optimizing plant density through modeling strategies is essential for improving resource-use efficiency and productivity in modern maize production systems. Functional–structural plant models (FSPMs) such as GreenLab provide a powerful framework for simulating crop growth and yield formation, yet their ability to represent interplant competition under high-density conditions remains limited, largely due to the oversimplified treatment of specific leaf area (SLA). To address this gap, a two-year field experiment (2022–2023) composed of four maize plant densities (3, 6, 9 and 12 plants m -2 , denoted as PD3, PD6, PD9, and PD12, respectively), was conducted to examine density-driven changes in leaf structural and functional traits and to evaluate the role of SLA plasticity in regulating canopy light and nitrogen use efficiency. Increased plant density substantially reshaped canopy architecture and resource distribution. Compared to PD3, higher densities (PD6, PD9, and PD12) increased leaf orientation value, SLA, photosynthetic nitrogen-use efficiency (PNUE), radiation-use efficiency (RUE) and crop growth rate (CGR), while reducing individual leaf area (LA), specific leaf nitrogen content (SLN) and light-saturated photosynthetic rate (A max ). Further analyses showed that density-induced SLA plasticity enhanced PNUE and adjusted the ratio of nitrogen to light extinction coefficients (K N /K L ), thereby partially compensating for the decline in leaf photosynthetic capacity caused by reduced SLN. At the canopy scale, SLA was strongly and positively associated with RUE, highlighting its role in enhancing canopy photosynthesis under interplant competition. Subsequently, the observed SLA responses to plant density were parameterized and incorporated into the GreenLab-Maize model. Compared to the standard model, the revised model markedly improved predictions of LA, leaf area index, RUE and accumulated biomass under high-density conditions. Overall, this study establishes SLA plasticity as a key adaptive trait for resource optimization in dense stands and provide a validated method to enhance the realism of competition simulations in FSPMs.