Understanding ecosystem material cycling is crucial for grasping and estimating ecosystems and the global climate. Terrestrial biosphere models (TBMs) simulate the cycling of carbon (C), nitrogen (N), and other materials within ecosystems. For improving TBMs, it is challenging to integrate C and N cycles in plants. In most existing TBMs, C and N cycles in plants are divided completely or combined by simple empirical equations. Meanwhile, in real plants, C and N cycling strongly couple with each other, which determines the physiological activities and structure of plant canopies in response to environmental variables. Under elevated CO₂, previous experimental studies have shown that the photosynthetic rate increases, leaf N declines, and there are no significant changes in leaf area index (LAI). Additionally, it is known that higher N availability increases photosynthesis rate, LAI, and leaf N. However, existing TBMs without sufficient C-N coupling are sometimes unable to predict these plant environmental responses. Hikosaka (2003) proposed a model of C and N dynamics through leaf production and shedding in a plant canopy with optimization theory. This model can simulate plant responses more accurately, but it was too simplified to be incorporated into TBMs. Here, we extended this model by refining the representation of photosynthesis and then constructing new models of deciduous and evergreen trees with different leaf phenology. We verified each plant functional type model by simulating plant responses in LAI, canopy photosynthesis rate (Pc), leaf N, leaf life span (LLS), and nitrogen use efficiency (NUE) to elevated CO₂ and N availability with changing input parameters. Responses in Pc, LAI, and leaf N to elevated CO₂ and N availability were consistent with the results of previous experimental studies. Simulation results also demonstrated that responses to CO₂ depend on leaf dry mass per area (LMA); higher LMA at elevated CO₂ suppresses the decline in leaf N and the increase in LAI, suggesting that it is a key response to improve CO₂ assimilation under elevated CO₂. Furthermore, simulated responses in LLS and NUE differ between models. These results suggested that our models can simulate realistic plant responses and contribute to improving the estimation of plant responses in TBMs.