China has recently launched extensive marine ranching projects, highlighting the need for scientific evaluation of ecosystem structure and function to guide their development. This study established two energy flow models and an evaluation index system to assess the structure, function, carrying capacity, and ecological status of both a marine ranching ecosystem and a nearby control site in the Beibu Gulf. The results show that the ranching ecosystem outperformed the control ecosystem in terms of food chain length, system size, and ecological carrying capacity of economically important species. The ranching ecosystem was classified as “relatively good”, while the control ecosystem was deemed “relatively poor”, which may confirm the success of the ranching efforts. Mussels, large crabs, and scorpaenidae were identified as key species for stock enhancement based on their biomass potential. Scenario simulations using Ecosim, driven by biomass and fishing factors, indicate that stock enhancement strategies targeting MOB (mussels, oysters, and barnacles) significantly improved the ranching ecosystem, raising its status to “good”. However, the simulations also revealed that stock enhancement had limited effects on optimizing food web structure, system organization, and energy transfer efficiency, suggesting that a combination of strategies is necessary for further improvement.

The vertically generalized production model (VGPM) is one of the most important methods for estimating marine net primary productivity (PP) using remote sensing. However, different data sources and parameterization schemes of the input variables for the VGPM can introduce uncertainties to the model results. This study compared the PP results from different data sources and parameterization schemes of three major input variables (i.e., chlorophyll-a concentration ($C_{opt}$), euphotic depth ($Z_{eu}$), and maximum photosynthetic rate ($P_{opt}^B$)) and evaluated the sensitivity of VGPM in the Yellow and Bohai Seas on the inputs. The results showed that the sensitivity in the annual mean PP was approximately 40%. Seasonally, the sensitivity was lowest in the spring (35%), highest in the winter (70%), and approximately 60% in the summer and autumn. Spatially, the sensitivity in nearshore water (water depth < 40 m) was more than 60% and around two times higher than that in deep water areas. Nevertheless, all VGPM results showed a decline trend in the PP from 2003 to 2020 in the Yellow and Bohai Seas. The influence of $P_{opt}^B$ and $C_{opt}$ was important for the magnitude of annual mean PP. The PP seasonal variation pattern was highly related to the parameterization scheme of $P_{opt}^B$, whereas the spatial distribution was mostly sensitive to the data sources of $C_{opt}$.

China has recently launched extensive marine ranching projects, highlighting the need for scien-tific evaluation of ecosystem structure and function to guide their development. This study estab-lished two energy flow models and an evaluation index system to assess the structure, function, carrying capacity, and ecological status of both a marine ranching ecosystem and a nearby control site in the Beibu Gulf. The results showed that the ranching ecosystem outperformed the control ecosystem in terms of food chain length, system size, and the ecological carrying capacity of eco-nomically important species. The ranching ecosystem was classified as "relatively good," while the control ecosystem was deemed "relatively poor," confirming the success of the ranching efforts. Mussels, large crabs, and Scorpaenidae were identified as key species for stock enhancement based on their biomass potential. Scenario simulations using Ecosim, driven by biomass and fishing factors, indicated that stock enhancement strategies targeting MOB (mussels, oysters, and barna-cles) significantly improved the ranching ecosystem, raising its status to "good." However, the simulations also revealed that stock enhancement had limited effects on optimizing food web structure, system organization, and energy transfer efficiency, suggesting that a combination of strategies is necessary for further improvement.