A novel light use efficiency model incorporating stand age to improve monitoring of mangrove productivity and biomass accumulation

Accurate estimation of gross primary production (GPP) and above-ground biomass (AGB) is fundamental to assessing the carbon sequestration potential of artificial mangrove wetlands. However, pronounced spatiotemporal heterogeneity in stand structure, particularly in restored mangrove forests with diverse age compositions, introduces substantial uncertainty in GPP and AGB quantification. This study presents an innovative framework that explicitly incorporates stand age into the light use efficiency (LUE) model as a physiological constraint, thereby enhancing the accuracy of GPP and AGB estimations. Stand age was mapped using Landsat-7 and sentinel-2 time-series imagery and a random forest classification approach on the Google Earth Engine platform, providing high spatial resolution age distributions. Age-dependent productivity constraints, derived from net primary production–age relationships observed in evergreen broadleaf ecosystems, were incorporated into the LUE model to refine photosynthetic efficiency estimations. Application of this framework to mangrove plantations in the Luoyangjiang Estuary (2000–2022) yielded high accuracy in GPP (RMSE = 9.66 g d −1 , R 2 = 0.95) and AGB (RMSE = 1,051 g·m −2 , R 2 = 0.63) estimations. The results captured exponential AGB growth with stand development, and spatial analysis demonstrated a strong correspondence between biomass distribution and stand age, with mature stands (≥20 years) contributing disproportionately to carbon accumulation. This stand age–integrated approach delivers fine spatial and temporal resolution, offering a practical and transferable tool for monitoring carbon dynamics and informing adaptive management strategies in restored coastal wetlands, thereby supporting the long-term assessment of blue carbon projects.