Background and objective: Sequestering carbon from the atmosphere is becoming increasingly important in the fight against climate change. Urban green spaces are increasingly recognized as effective carbon sinks, and many cities are striving to achieve carbon neutrality. carbon statistics for trees and shrubs are essential to attaining this goal and enhancing the carbon uptake capacity of urban green spaces.Methods: Historically, carbon studies have primarily focused on forest trees; however, as urban green spaces have expanded in recent years, research on shrubs utilized in these areas is gradually increasing. This study aims to measure the carbon fraction of representative native shrubs in urban green spaces in Korea.Results: The carbon fraction was compared by component, including evergreen (n = 325) and deciduous (n = 911) shrubs, as well as standard shrubs (n = 1279) and vines (n = 45). The results indicated that evergreen shrubs contained a higher carbon fraction than deciduous shrubs (p < .05), and standard shrubs exhibited a greater carbon fraction than vines (p < .05). Furthermore, biomass allocation shifted from leaves and roots to stems as shrubs aged, with deciduous shrubs allocating more biomass to roots than evergreens.Conclusion: These results can be integrated with dry weight measurements for each shrub species to estimate carbon storage, providing crucial data to inform spatial planning and species selection for maximizing carbon sequestration.

Urban vegetation plays a role as a sink, but accurately estimating carbon storage requires cultivar-specific allometric equations due to variations in growth patterns. This study develops and compares carbon storage models for cultivars of Hibiscus syriacus L.: ‘Wonhwa’ and ‘Chilbo’, ranked first and second in preference in South Korea and most widely planted in urban areas, to address the lack of specific data for these popular varieties. We destructively sampled 106 trees from experimental nurseries in Korea, measuring growth parameters, partitioned biomass, and component-specific carbon content. A non-linear regression equation modeled the relationship between root collar diameter (RCD) and total carbon storage. RCD proved the most effective predictor, resulting in high-performance power-function models (R² = 0.99) for both cultivars: ‘Wonhwa’ (CS = 0.02RCD^2.41) and ‘Chilbo’ (CS = 0.01RCD^2.38). An extra sum-of-squares F-test confirmed a statistically significant difference between the models (p < 0.001). Notably, both cultivars exhibited a branch-dominant allocation pattern (accounting for approximately 50–51% of total biomass), which contrasts significantly with the stem-dominant pattern typically observed in forest-grown trees. The observed inter-cultivar differences indicate that using a single species-level equation can yield inaccurate carbon estimates. Consequently, we recommend that urban managers apply these cultivar-specific equations rather than generic species-level models to minimize estimation uncertainty and support precise carbon inventory management.

With the acceleration of global urbanization, neighborhood green spaces have emerged as important carbon sinks. However, current urban carbon inventories frequently neglect the understory shrub layer owing to morphological heterogeneity and a lack of standardized allometric models. To address this limitation, we analyzed 13 major shrub species (n = 665) through whole-plant excavation. Hierarchical cluster analysis and linear discriminant analysis classified the 13 species into three functional morphological groups based on intrinsic morphological traits (basal stem density, root-to-shoot biomass allocation, and secondary radial growth capacity) (p < 0.001): small shrubs (Type I), large shrubs with high root-to-shoot allocation (Type II), and multi-stemmed sprouting shrubs (Type III). Standard models accurately estimated biomass for Type I species, whereas symbolic regression improved the prediction of the complex non-linear biomass allocation of Type II species. For Type III species, characterized by multi-stemmed growth and anthropogenic management, robust regression provided stable biomass estimates. Gompertz growth models predicted carbon sequestration trajectories, indicating that urban shrubs function as rapid carbon sinks during the early establishment stage. To facilitate practical application, we developed the Urban Forest Carbon Storage Calculator, which integrates Monte Carlo simulation and bootstrapping to generate 95% confidence intervals for species-specific biomass estimation. This study quantifies the overlooked carbon value of the urban shrub layer and provides a morphology-driven methodological approach and a practical tool for sustainable urban forest management.