A coupled LSTM model for predicting blue carbon and fishery dynamics in tropical coastal wetlands under climate change.

Coastal wetlands, including mangroves, seagrass beds, and coral reefs, provide critical blue carbon sequestration services and nursery habitats that support fishery resources. However, the bidirectional coupling between blue carbon stocks and fishery abundance remain poorly quantified, particularly under accelerating environmental change in tropical marginal seas. This study presents the first coupled LSTM framework for bidirectional blue carbon-fishery prediction in tropical coastal wetlands. We developed a coupled Long Short-Term Memory (LSTM) neural network model to predict the bidirectional relationship between blue carbon stocks and fishery resource abundance in the coastal ecosystems of Guangdong Province and Hainan Island, China. Field surveys were conducted at 15 representative sites from 2018 to 2025, generating 96 monthly observations of environmental variables (sea surface temperature, salinity, dissolved oxygen, turbidity, nutrients), biological indicators (mangrove above-ground biomass, soil organic carbon, seagrass coverage, coral cover), and fishery metrics (catch per unit effort, species richness, juvenile abundance). The LSTM model achieved superior predictive performance compared to baseline methods, with root mean square error of 0.142 Mg C ha⁻¹ for blue carbon prediction (R² = 0.93) and 0.108 kg h⁻¹ for CPUE prediction (R² = 0.89). Feature importance analysis revealed that mangrove soil organic carbon was the strongest predictor of fishery CPUE (Shapley value = 0.187), while sea surface temperature exerted the greatest influence on blue carbon stock variability. Scenario simulations for 2025-2026 indicate that under a moderate warming scenario (SST increase of 0.8 °C), blue carbon stocks are projected to decline by 7.2% (95% CI: 5.8-8.6%), with associated fishery CPUE reductions of 11.4% (95% CI: 9.2-13.6%). These findings provide a novel predictive framework for ecosystem-based management of tropical coastal wetlands and highlight the vulnerability of coupled social-ecological systems to climate change.