Urban forest canopy structural complexity is associated with carbon sequestration and optimization potential in Beijing

Urban forests contribute to carbon uptake and climate regulation in cities, but the role of canopy structural complexity (CSC) in urban forest carbon sequestration remains insufficiently quantified. Here, we combined GEDI spaceborne LiDAR, terrestrial laser scanning and machine-learning models to assess the association between CSC and net primary productivity in Beijing’s urban forests. Greater CSC was associated with higher productivity, potentially reflecting more efficient canopy light capture and stronger vertical structural differentiation. Natural urban forests exhibited higher CSC and stronger CSC–carbon sequestration associations than managed urban forests, whereas managed urban forests showed greater improvement potential under CSC-oriented optimization scenarios. Soil organic carbon and local climate were the dominant correlates of CSC, while road density and landscape fragmentation were associated with reduced canopy complexity. Scenario-based simulations indicated that CSC-oriented management could increase productivity by up to 21.2% overall and by 47.8% in some managed urban forests. These findings highlight the value of three-dimensional canopy structure as a management-relevant indicator of urban forest carbon sequestration potential.