Effective coastal management of seagrass systems requires identifying both extant meadows and degraded areas suitable for recovery. However, these decisions often rely on distribution maps that provide limited information on ecological condition or carbon potential. Here, we develop an ensemble habitat modeling (EHM) framework for seagrass meadows around Guanglu Island, China, to test whether a habitat suitability index (HSI) can serve as a proxy for ecological performance and carbon storage potential. By integrating multiple single-algorithm predictions, the ensemble model reduced algorithm-dependent variation and achieved strong predictive performance (ROC = 0.967, TSS = 0.876), with predictions capturing 92.59% to 98.98% of the 2023 field-mapped meadow area. HSI was positively associated with aboveground biomass and shoot density. A predictive model fitted directly with biomass as the response showed that aboveground biomass increased with HSI, with a leave-one-out cross-validated RMSE of 77.68 g DW m⁻². High HSI samples also exhibited smaller relative deviations from the theoretical biomass–density envelope and a greater realized fraction of theoretical biomass potential. Modeled sediment carbon densities were consistent with the 2023 sediment comparison, thereby supporting conditional carbon stock screening. Our findings support the use of ensemble-derived HSI as a local spatial proxy for biomass-related ecological potential, rather than as a direct measure of habitat quality, actual biomass, or realized carbon stock. By separating predicted suitable habitat, observed meadow distribution, and model-based potential carbon stock, the framework provides a spatial screening tool for conservation prioritization, restoration opportunity assessment, and blue carbon planning under explicitly stated ecological and modeling assumptions.

Stock enhancement can effectively increase population sustainablility and improve fishery resources, making it crucial to discern the suitable habitats for stock enhancement based on efficiency considerations. In this paper, a comprehensive model was established to simulate environmental characteristics in the Liaodong Bay. A habitat suitability model was developed by considering the optimal growth conditions of the Portunus trituberculatus larvae (PTL). The coupled model showed that the optimal area for stock-enhancement with PTL occurs in late June, and the initial suitable habitat area identified represents 17.12% of the whole Liaodong Bay. Based on the larval migration model of PTL, the deviation between the larvae and the suitable habitat, as well as the actual available area for stock enhancement, were further determined after larval release in the initial suitable habitat. Only 33.67% of the larvae fulfilled the criteria of remaining within the suitable habitat for 95% of the time, and these larvae represented 6.19% of the whole area of Liaodong Bay. These findings means that the truly area available for stock enhancement is likely to be a very small portion of the entire bay, and more precise release of larvae will be necessary to ensure survival rates after release. Our study actually provides a methodological framework for the identification of suitable environment of stock enhancement. This methodology can provide technical guidance for the stock enhancement of marine larvae with same applicability for other bays, which in turn contributes to the sustainable use of marine ecosystem services and fisheries resources.