Abstract:Recruitment process serves as a critical biological foundation for sustainable resource maintenance. Understanding and accurately predicting the variability in recruitment has become a core challenge in fisheries management. Previous methods for predicting the recruitment of South Pacific albacore (Thunnus alalunga) have challenges in handling multicollinearity among environmental variables and identifying key drivers, often leading to model overfit and reduced predictive accuracy. To address these issues, this study applied the LASSO regression algorithm to optimize variable selection and improve prediction accuracy. Models were developed based on observational data from 2000 to 2017, and then coupled with CMIP6 multi-model climate projections, to predict recruitment trends from 2018 to 2100.The results indicated that LASSO effectively eliminated variable redundancy through shrinkage estimation, enhancing model prediction accuracy. The optimal model explained 45.9% of variance, with sea surface temperature (SST) and mixed layer depth (MLD) identified as critical predictors. Projections revealed that under high-emission scenarios (SSP5-8.5, SSP3-7.0), the population recruitment by the 2070s would approach the ecological threshold lower limit (near zero), significantly elevating collapse risks. In contrast, under the low-carbon pathway (SSP1-2.6), recruitment exhibited persistent decline trends. This study provided with an effective methodological framework for fisheries stock prediction and variable selection, while establishing a climate-recruitment coupled prediction model to provide quantitative decision-making support for formulating adaptive management strategies and mitigating population collapse risks.

Abstract:To understand current status of fish spawning and suitable spawning habitats in northern Liaodong Bay, this study utilized data from 14 surveys on fish eggs and larvae. Cluster analysis, non-metric multidimensional scaling (NMDS), and similarity percentage analysis (SIMPER) were applied to characterize the community structure of fish eggs and larvae. Canonical correspondence analysis (CCA) and Mantel tests were used to explore the spatial-temporal distribution patterns of ichthyoplankton and their relationships with environmental variables, including sea surface and bottom temperature (SSTand SBT), sea surface and bottom salinity (SSS and SBS), depth, monthly runoff of the Liao River (RD), and plankton wet weight (WW). A total of 51 fish species at early life stages were identified and recorded during the survey period. The community structure of fish eggs and larvae exhibited significant monthly succession, with species turnover rates exceeding 50% and average monthly dissimilarity over 71.2%. NMDS and month-based cluster analyses revealed that fish eggs could be classified into three groups, while larvae could be divided into four groups. The major spawning period in the northern Liaodong Bay occurred from late May to late July and in December. No single species overwhelmingly dominated the early life stage assemblages. The primary spawning species included Pholis fangi, Ammodytes personatus, Planilaza haematocheilus, Konosirus punctatus, Engraulis japonicus, Scomberomorus niphonius, Thryssa kammalensis, Setipinna tenuifilis, Johnius grypotus, and Cynoglossus joyneri. From late May to late July, the main spawning grounds were concentrated near the estuarine areas of the Xiaoling, Daling, Liao, and Daliao rivers, from Jinzhou Bay to the north of Baisha Bay. In December, larvae were mainly concentrated in the waters north of Lianshan Bay to Taiping Bay. SST, RD, and Depth were identified as the key environmental factors affecting the spatio-temporal variation of fish early life stage communities. SST had a particularly important influence, driving seasonal shifts in dominant spawning species, with temperature preferences shifting from warm-temperate to warm-temperate & warm-water and eventually to cold-temperate types. The spatial distributions of S. tenuifilis and J. grypotus eggs, as well as K. punctatus, T. kammalensis, and P. haematocheilus larvae, were positively correlated with SST, while the densities of E. japonicus, S. niphonius eggs and P. fangi, A. personatus larvae showed negative correlations with SST. RD influenced the gradient of salinity and nutrient levels, indirectly affecting the distribution of fish eggs and larvae. The distributions of C. joyneri, J. grypotus eggs and K. punctatus, P. fangi, T. kammalensis larvae were positively correlated with RD, whereas S. niphonius eggs and A. personatus larvae were negatively correlated. Depth was closely related to the physical-chemical characteristics of the water column and the structure of biological communities, significantly affecting fish spawning ground selection. J. grypotus, C. joyneri eggs and P. haematocheilus larvae were positively associated with depth, whereas S. tenuifilis eggs and K. punctatus, T. kammalensis larvae showed negative correlations. This study provides baseline data for the evaluation and conservation of early life stages of fish in Liaodong Bay.

Abstract:The relationships between the distribution of marine fish and environmental factors have long been a focal point in marine ecology research. The hierarchical multispecies community model (HMSC), a multivariate hierarchical generalized linear mixed-effects model grounded in Bayesian statistics, enables simultaneous analysis of how environmental conditions, interspecific relationships, and phylogeny influence species distribution patterns. To investigate the environmental adaptability of fish species and their interspecific interactions in the coastal waters of Guangdong, we constructed five HMSC models. These models were developed using fisheries independent data from bottom trawl surveys conducted during four spring cruises in 2018, 2019, 2020, and 2022, and related environmental data on water depth, surface salinity, and surface temperature. The research results showed models with random effects fit the data better than those without random effects. The introduction of random effects enables the models to detect hidden variables that have not been observed yet, thereby improving the models' ability to fit complex ecological relationships. However, during the cross-validation process, these hidden variables could not be accurately estimated. As a result, the prediced R2 values of models without random effects were close to those of models with random effects. In particular, when random effects were added to the models related to predators at higher trophic levels, the model fit improved considerably. This indicates that interspecific relationships have a remarkable effect on the distribution of predators. Water depth is a crucial factor affecting the distribution of fish in the coastal waters of Guangdong, accounting for 62.1% of the variance in fish distribution. Moreover, most fish species exhibited nonlinear relationships with water depth. Changes in water depth often triggered a series of chain reactions in related factors such as temperature and salinity. The explanatory powers of surface temperature and surface salinity were relatively weak, accounting for only 3.5% and 3.3% of the variance, respectively. This might be due to the limitation of the survey time, as the environmental impacts on fish vary across different seasons. The random effects of some fish species had a relatively high explanatory rate. This suggests that, in addition to being influenced by water depth, surface temperature, and surface salinity, the distribution and survival of these fish species might also be affected by other potential factors. The relationships among fish populations could be broadly classified into two distinct groups. The first group of fish species predominantly exhibited positive correlations with other species. These fish were mostly small in size and inhabited the bottom or near-bottom layers of the water column. Their similar spatial distributions and comparable body sizes likely contributed to the significant positive associations observed among them. This suggests that shared ecological niches and habitat preferences play a crucial role in fostering co-occurrence patterns within this group. In contrast, the second group of fish species showed predominantly negative correlations with others. This phenomenon was likely linked to their positions in the food chains. Some species within this group occupied lower trophic levels, making them prey for a wide range of other fish, while others were higher-level predators. Such trophic interactions, whether as prey or predator, created competitive or predatory relationships that lead to negative correlations in their distributions. These findings underscore the inadequacy of relying solely on individual environmental factors to explain fish distribution patterns. Instead, both water depth and interspecific relationships emerge as key determinants of fish distribution in the coastal waters of Guangdong. Water depth influences various environmental conditions, while interspecific interactions shape the co-existence and distribution of species. Overall, the results of this study provide essential theoretical insights and empirical data that can inform the sustainable management of fish resources and the conservation of marine ecosystems in the coastal waters of Guangdong.

Abstract:Miichthys miiuy is one of the main economic fish species in the offshore waters of Zhejiang Province. In order to investigate the spatio-temporal distribution of this local fish stock, this study developed suitability curves of M. miiuy to environmental factors, using relative abundance and associated environmental data from the bottom trawl fishery surveys during 2022 to 2023 in the offshore waters of Zhejiang. Subsequently, boosted regression trees (BRT) was applied to estimate the weight of each environmental factor, and two composite habitat suitability index (HSI) models were established using the arithmetic mean method (AMM) and the geometric mean method (GMM), separately. The accuracy of HSI models was evaluated using the Akaike information criterion (AIC). The results revealed distinct seasonal patterns in the optimal habitats of M. miiuy in offshore Zhejiang. In spring, optimal habitats were primarily located in the Zhoushan fishing grounds and the waters surrounding the Dongtou Islands, characterized by bottom salinity of 28.0‒32.1, temperature of 14.2‒16.3 ℃, dissolved oxygen of 7.8‒9.5 mg/L, and water depth of 16‒41 m. During summer, optimal habitats shifted to coastal estuary waters, with optimal ranges of 26.4‒31.5 for bottom salinity, 24.8‒28.1 ℃ for temperature, 6.9‒8.7 mg/L for dissolved oxygen, and 14‒35 m for depth. In autumn, optimal habitats moved further offshore, with preferred conditions of 28.4‒33.1 for bottom salinity, 19.2‒24.2 ℃ for temperature, 5.8‒8.4 mg/L for dissolved oxygen, and 21‒44 m for depth. Winter habitats were concentrated between 123°E and 124°E, with optimal ranges of 30.0‒34.1 for bottom salinity, 11.0‒14.1 ℃ for temperature, 8.3‒9.6 mg/L for dissolved oxygen, and 43‒60 m for depth. The BRT identified bottom salinity as the most influential factor in spring and summer, while depth and bottom temperature dominated in autumn and winter. Based on AIC evaluation, the GMM-weighted HSI model exhibited higher accuracy in autumn, whereas the AMM-weighted HSI model performed better in spring, summer, and winter. These results highlight significant seasonal variations in the spatio-temporal distribution of M. miiuy habitat, which might be driven by dynamic environmental factors and the distinguish habits of this species.

Abstract:As an important fishery resource in the offshore waters of Shandong Province, the fishing ground distribution of Sepia esculenta and its relationships with influencing factors have attracted much attention. This study constructed a generalized additive model (GAM) based on Tweedie distribution to analyze the distribution characteristics of Sepia esculenta fishing grounds in the offshore waters of Shandong Province and their relationships with fishing pressure and environmental factors, using monitoring data of fishery production from 2018 to 2023. The results showed that Sepia esculenta fishing grounds are mainly distributed in the Haizhou Bay fishing grounds and Qinghai fishing grounds in the central Yellow Sea. The center of gravity of the fishing grounds for Sepia esculenta tended to shift northwards annually, and showed a trend moving from northwest to southeast monthly. Through model comparison, the Tweedie GAM model, which includes fishing, environmental, and time factors, had the best fitting effect and predictive performance. Sea bottom salinity, sea bottom temperature, and depth that are suitable for the distribution of Sepia esculenta in autumn are 31‒34, 16‒22 ℃, and approximate 28 m, respectively. The fishing effort of the current year had a positive effect on the catch per unit effort (CPUE) of Sepia esculenta, while the fishing effort of the previous year had a negative effect. This study revealed the impact of external driving factors on the distribution of Sepia esculenta resources, which is of great significance for the rational planning of commercial fishing production, strengthening the scientific management and resource conservation of Sepia esculenta.

Abstract:Accurate assessment of marine biodiversity is fundamental to fisheries management and ecological conservation. Optimizing sampling design is crucial for improving the estimation precision of species richness as an essential biodiversity indicator. Based on seasonal bottom trawl survey data collected from August 2014 to May 2015 in the coastal waters of Guangdong, this study employed computer-simulated resampling techniques to compare the effects of simple random sampling (SRS) and stratified random sampling (StRS) on the estimation of fishery species richness under varying numbers of sampling sites and frequencies. The results showed that the species detection rate increased rapidly with the addition of sampling sites when their number was low, and the increasing rate gradually slowed as the number of sites increased. To achieve a 90% species detection rate, 44 sampling sites were required for year-round seasonal sampling; for an 80% detection rate, the minimum number of sites needed was 36, with the summer-autumn-winter or summer-autumn-spring seasonal combinations being the most efficient. Both the absolute values of relative estimation error (REE) and relative bias (RB) decreased as the number of sampling sites increased. StRS exhibited significantly lower absolute REE and RB values than SRS (P＜0.05). After excluding rare species, the number of sites required to achieve a 90% detection rate decreased to 20, and the absolute REE and RB values also declined, indicating that rare species increased sampling variability. The design effects (De) of 15 stratified sampling combinations were all below 1, demonstrating that StRS had higher sampling efficiency in Guangdong coastal fisheries surveys, particularly when the number of sampling sites was limited. This study provides a scientific basis for optimizing sampling designs in Guangdong coastal fisheries surveys, and suggests selecting site numbers and seasonal combinations based on monitoring precision requirements and cost constraints.

Abstract:Biodiversity plays an important role in regulating and supporting ecosystem functions and services, whereas in recent years, multiple pressures, including overfishing, habitat destruction and climate change, have led to severe declines of biodiversity in marine and coastal ecosystems. Consequently, the biodiversity-ecosystem functioning (BEF) relationship has become one of the research focuses in the field of biodiversity conservation. Previous literatures have accounted for the BEF in the marine ecosystems, and suggested that biodiversity can sustain ecological functions through complementary effects and other approaches; however, relevant studies neglected the interactions among different trophic levels and their heterogeneous responses to biodiversity. In this study, we investigated the spatial and temporal distribution of the biomass and species diversity of the fishery biomes in Haizhou Bay, based on the bottom trawl surveys in the area in autumn from 2013 to 2023. Species distribution models and structural equation models (SEM) were used to examine the relationships between environmental factors, species diversity (richness and evenness) and biomass at different trophic levels (the species were divided into high, medium, and low levels according to their feeding habits). Among them, SEM was used to consider the correlations between multiple variables simultaneously and to intuitively reflect the direction and intensity of their possible effects. This provided an effective tool to delineate the interspecific interactions at different trophic levels, as well as a new perspective for the study of BEF mechanisms. The results revealed that the biomass of different trophic levels showed significant interannual fluctuations in Haizhou Bay, and their spatial distribution patterns also differed substantially. Species richness showed strong interannual fluctuations, whereas the changes in evenness were relatively small over time. The SEM model suggested that species diversity had substantially different influences on the biomass of different trophic levels. Specifically, richness had a significant positive correlation with the biomass of the middle trophic level, which reflected the complementary effect of ecological niches. Species evenness showed a negative correlation with the biomass of the middle and high trophic levels, consistent with the selection effects in the community. The biomass of low and high trophic levels was less responsive to the diversity indicators, and only evenness was found to correlate with the biomass of high trophic level. The diverged responses to biodiversity indicated that ecological niche complementarity and selection effects worked differently for different trophic levels. Additionally, significant correlations were found between different trophic levels, and environmental factors influenced the biomass through both direct and indirect pathways. That is, significant positive correlations were found between bottom temperature and high-trophic-level biomass and between salinity and low-trophic-level biomass, where there were negative correlations between the other environmental factors and biomass. This study reveals the complexity of the BEF relationships in marine ecosystems as noted by the differential effects of biodiversity on different trophic levels of the community, which emphasized that the trophic structure of the ecosystem should be taken into account when exploring the BEF relationships in marine ecosystems. In future studies, care should be taken not to treat the total community biomass in a simplified way, but to carry out analyses with full considerations of ecosystem structures, trophic-level compositions, and spatial and temporal scales, and to incorporate interactions among species to reveal the relationship between species diversity and biomass. The results may promote the scientific understanding on the BEF relationships in marine ecosystems, and provide theoretical support for the conservation of biodiversity and the collaborative management in Haizhou Bay. Further studies were suggested to focus on comparing different methodologies for SEMs, such as including latent variables and time lag effects in the model structure to explore the effects of time-continuous effects on biomass, in order to provide in-depth investigations of the BEF relationship in marine ecosystems.

Abstract:To investigate inter- and intra-specific trophic relationships among dominant coral reef fishes in Qilianyu Islands of the Xisha Islands, the trophic structure characteristics of six common and dominant fish species were analyzed using carbon (δ13C) and nitrogen (δ¹⁵N) stable isotope techniques in September 2021. The results indicate that Naso lituratus had the highest δ13C and the lowest δ¹⁵N values with averages at (−10.88± 1.42)‰ and (5.74±0.37)‰, respectively. In contrast, Zanclus cornutus had the lowest δ¹³C value with an average of (−15.27±0.74‰), and Gnathodentex aureolineatus demonstrated the highest δ¹⁵N value at (9.94±0.73)‰. N. lituratus and Ctenochaetus binotatus primarily distributed in areas with high δ13C and low δ¹⁵N values, while Z. cornutus, Chaetodon auriga, G. aureolineatus, and Epinephelus merra tended to occupy areas characterized by low δ¹³C and high δ¹⁵N isotopic signatures. Mean trophic levels (TL) of N. lituratus, C. binotatus, Z. cornutus, C. auriga, G. aureolineatus, and E. merra were 2.24, 2.45, 2.89, 3.20, 3.48, and 3.02, respectively. The isotopic niche of G. aureolineatus occupied the highest position and had the largest values, with CR, NR, TA, SEA, and SEAc reaching 5.90, 3.18, 9.00, 2.09, and 2.11, respectively. Z. cornutus exhibited the smallest isotopic niche among both omnivorous and carnivorous fishes, positioned at the lowest tail. Among herbivorous fishes, the isotopic niche of N. lituratus was larger than that of C. binotatus, but remained below the latter. Overall, δ¹⁵N values of omnivorous and carnivorous fishes were larger than herbivorous fishes, and the stable isotope core niches of all fish species exhibited complete non-overlapping distributions. G. aureolineatus and E. merra might exhibit differences in spatial, temporal, and dietary ecological niches, resulting in non-overlapping core isotopic niches. N. lituratus and C. binotatus likely differed in spatial and dietary ecological strategies, leading to distinct core isotopic niches. Z. cornutus exhibited distinctive dietary differences compared to other species, resulting in non-overlapping isotopic niche with others. Lastly, C. auriga, characterized by strong territorial behavior and diverse food sources, suggesting niche separation from other fishes primarily through spatial and dietary divergences. Strong positive correlations between standard length and δ¹⁵N were observed in all species except Z. cornutus (r=0.39–0.58, P＜0.05). In the standard length group of 161–183 mm, G. aureolineatus exhibited the highest values of TA (total area) and SEA (standard ellipse area) (6.51 and 1.98, respectively). C. auriga in the 121–140 mm standard length group showed the maximum standard ellipse area corrected (SEAc) value (2.87). For Z. cornutus, the 85–100 mm standard length group had the lowest values of TA, SEA, and SEAc (0.40, 0.38, and 0.51, respectively). Except for N. lituratus and Z. cornutus, the trophic levels of the remaining four fish species increased with increasing standard length groups. Different standard length groups of E. merra exhibited the highest degree of isotopic niche overlap, suggesting intense intraspecific food competition within the species. The isotopic niches among different standard length groups of other fish species exhibited minimal overlap, suggesting that intraspecific food competition was relatively low. This study provides with quantitative evidence for trophic structuring in coral reef fish assemblages around the Qilianyu Islands. The findings will contribute to understanding food web dynamics in the South China Sea coral ecosystems and have implications for marine conservation planning.

Abstract:Exploring the interactions between marine mammals and fisheries is essential for ecosystem-based fisheries management. In recent years, the conservation of fishery resources in the adjacent waters of Zhangzi Island has continuously improved, leading to a gradual increase in the number of cetaceans such as minke whales (Balaenoptera acutorostrata) and finless porpoises (Neophocaena asiaeorientalis sunameri). However, activities such as pelagic trawling and offshore recreational fishing continue to impact the prey resources of these cetaceans. Despite this, the broader ecological interactions between cetaceans and fisheries, particularly their roles in the food web and their impacts on the structure and function of offshore ecosystems, remain unclear. To address this gap, a food web model was developed using Ecopath for the coastal waters adjacent to the Zhangzi Island. This model allowed to assess the ecosystem's structural and functional characteristics, examine the trophic roles of cetaceans, and analyze their interactions with fisheries. The results indicated that trophic levels (TL) within the ecosystem ranged from 1.00 to 4.24, with minke whales at 3.74 and finless porpoises at the highest level (4.24). The keystone index and relative total impact of finless porpoises (−0.53 and 0.33, respectively) was greater in magnitude than those of minke whales (−0.82, 0.17). Mixed trophic impact (MTI) analysis revealed that both the minke whale and finless porpoise exerted greater negative than positive impacts on trophic levels IV and III species. Notably, the finless porpoise showed the strongest negative influence on the food web (7.5%), with particularly pronounced effects on trophic level III species (14.5% positive vs 22.2% negative impacts). Among fishing activities, pelagic trawling (30.8%) and recreational fishing (26.7%) demonstrated the highest negative impacts on the food web. In this ecosystem, cetacean consumption accounted for merely 0.3% of total species consumption, while diving fishing (39.2%) and pelagic trawling (24.5%) dominated the total consumption flows. Furthermore, niche overlap index indicated substantial resource competition between finless porpoises and pelagic trawling (0.75), whereas overlap indices between both cetaceans (minke whale: 0.03; finless porpoise: 0.33) and overall fisheries remained relatively low. Although the finless porpoise exhibited stronger interactions with fisheries, the food web impacts from cetaceans’ predation were significantly lower than those caused by fishery exploitation. These findings provide valuable references for achieving coordinated management of local marine mammal conservation and fishery resources.

Abstract:Small urban water bodies serve multiple functions within urban ecosystems. However, they often experience significant external pollution and possess limited self-purification capability. The Dishui Lake in Shanghai is a typical urban lentic system, and encounters various ecological challenges. Since 2007, the local authorities have implemented a systematic biomanipulation program, aiming at improving the water quality by enhancing the stock of filter-feeding fish like silver carp (Hypophthalmichthys molitrix) and bighead carp (Aristichys nobilis). Yet, due to the lack of understanding on some key scientific issues such as the current state of the ecosystem, ecological carrying capacity, and the optimization of stock enhancement strategies, the effect of the stock enhancement has not been satisfactory. This study encompasses three primary research components: (1) a quantitative analysis of the current ecosystem structure; (2) a quantitative assessment of the ecological carrying capacity of silver carp and bighead carp; and (3) a prediction of the effects of different strategies on the ecosystem. Related findings are expected to provide a significant foundation for the optimization of stocking strategies in the Dishui Lake, as well as similar urban water bodies. This study was conducted utilizing the Ecopath with Ecosim (EwE) model, which is adept at simultaneously simulating both the static characteristics (Ecopath) and the dynamic processes (Ecosim) of the ecosystem. Primary data for the model were obtained from ecological surveys conducted in the Dishui Lake during 2023 to 2024, while model parameters that were challenging to measure directly were supplemented with reference data from analogous lakes. Importantly, stable isotope analysis was employed to refine the food matrix. Subsequently, an Ecopath model including 15 functional groups was developed for the Dishui Lake to evaluate the status of the ecosystem along with the ecological carrying capacity of silver carp and bighead carp. Ecosim was employed to simulate the potential ecological impacts of various biomanipulation scenarios within the ecosystem. The findings indicated that trophic levels of the 15 functional groups varied between 1.00 and 3.50, while the ecotrophic efficiency ranged from 0.12 to 0.98. The total system throughput for the Dishui Lake was calculated at 3376.93 t/(km² ·a), with a ratio of total primary production to total respiration of 1.59. The connectance index (0.29) and the system omnivory index (0.09) suggested that the ecosystem is at an immature developmental stage. Trophic levels derived from stable isotope analysis exhibited strong correlations with those estimated from Ecopath (R² =0.88, P＜0.01), validating the reliability of the food matrix. The ecological carrying capacity of silver carp and bighead carp was estimated at 22.01 t/km², which was approximately 1.33 times the current biomass. The Ecosim simulation results indicated that increase in the fishing mortality of silver carp and bighead carp would indirectly reduce the biomass of top predators. When the biomass of silver carp and bighead carp reached their ecological carrying capacity, it significantly impacted phytoplankton and zooplankton communities. The current predominance of bighead carp over silver carp was found to be suboptimal for effective algal control. Notwithstanding limitations including parameter uncertainty and unaccounted predator diet plasticity, this study suggests: a gradual increase in the biomass of silver carp and bighead carp; the optimization of the stocking ratios between silver carp and bighead carp; the implementation of integrated management strategies which combine controlled harvesting with multi-trophic stock enhancement; and the establishment of adaptive monitoring protocols. These findings provide a scientific foundation for optimizing biomanipulation strategies in the Dishui Lake and similar urban lentic systems.

Abstract:The energy flow in food web is of great significance for maintaining the structure, function, and stability of marine ecosystem, and helps to gain a deeper understanding of the trophic dynamics and importance of the food web in marine ecosystems. This study constructed a linear inverse model with markov chain monte marlo (LIM-MCMC) based on seasonal biological resource survey data conducted in the Lvsi fishing ground in 2023, and combined it with ecological network analysis (ENA) to explore the energy flow characteristics and ecosystem status of the food web in the area. The results indicated that marine organisms in this area could be divided into 22 functional groups, forming a total of 224 energy flow pathways. The energy assimilated by planktonic animals was transmitted upwards through functional groups such as Konosirus punctatus, other benthic organisms, and other mollusks, to maintain the growth, development, and reproduction of high trophic level organisms. Although planktonic animals have 21 energy outflow pathways, the vast majority of their ingested energy was lost through resporation at 1764.70 kg/(km2 ·year), rather than transferring to high trophic levels. In addition, the total system throughput (TST), total primary production (TPP), total primary production/total respiration (TPP/TR), and connectance (C) were 5421.34 kg/(km2 ·year), 1803.92 kg/(km2 ·year), 1.00, and 0.41, respectively. Additionally, the five ecological network analysis (ENA) indicators, including extent of development (AC), constraint efficiency (CE), Finn's cycling index (FCI), synergism index (b/c), and dominant indirect effects (i/d), of the ecosystem in this study area were 0.93, 0.75, 0.24, 1.32, 5.46, respectively. Compared with other marine ecosystems, this marine ecosystem was larger in scale and more mature, with a relatively complex food web structure that could resist external disturbances to a greater extent. In addition, the development space of the ecosystem in this sea area was relatively large, with low network constraints, low energy utilization efficiency, and high sustainability. This study will contribute to the in-depth study of the nutritional dynamics of the food web in the Lvsi fishing ground and provide scientific basis for the scientific management of fishery resources in the area.