Abstract
Mangrove ecosystems provide crucial ecological services but face threats from climate change and unsustainable resource use. This highlights the need for science-based forest management initiatives. Cispatá Bay, located in the Colombian Caribbean, hosts the country’s only mangrove under a regulated sustainable use model. Yet, current management guidelines rely on generalized silvicultural criteria, such as a uniform minimum logging diameter (MLD) of 10 cm and a 14 year cutting cycle (CC), which do not reflect species-specific growth dynamics, potentially compromising sustainability. This study aims to improve sustainable forest management in Cispatá Bay by developing species-specific growth models for Rhizophora mangle , a dominant and heavily harvested species. We introduce a novel methodological framework for sustainable forest management in mangrove ecosystems, integrating dendrochronology and biometric modeling to derive ecological management parameters. We combined tree-ring data from 26 dead individuals with forest inventory measurements and applied nonlinear mixed-effects modeling, accounting for autocorrelation and growth eccentricity. The resulting models yielded biologically meaningful ontogenetic traits, including a maximum mean diameter (A max ) of 40.35 cm, a weighted average growth rate (WAGR) of 0.42 cm year⁻ 1 , a lifespan (t span ) of 95.12 years, and a halflife (t 0.5 ) of 41.09 years. Additionally, we estimated an MLD of 24 cm and a CC of 20 years—both substantially higher than current thresholds. These findings suggest that continued application of generalized metrics may compromise forest regeneration, reduce volume recovery, and undermine long-term sustainability. By integrating dendrochronological techniques with biometric modeling, this research provides a replicable framework for evidence-based forest governance in mangroves.