Analysis of the Ecosystem Structure and Energy Flow in the Waters of the Wangjiadao Islands

Abstract

Marine islands play a crucial role in marine ecosystems. The waters of the Wangjiadao islands, which are located in the Northern Yellow Sea, are one of the typical island ecosystems. Sea cucumbers and shellfish are important target species, but information on ecological capacity is lacking. Using the EWE model, a food web model was constructed for the waters of Wangjiadao Island in order to estimate the potential biomass of selected species that could proliferate without destabilizing the ecosystem. The model consists of 22 functional groups that were selected for their functional roles within the ecosystem and the availability of data. The potential for fishery biomass enhancement is significant, with sea cucumber biomass increasing by 242%, Mizuhopecten yessoensis biomass increasing by 42%, Chlamys farreri biomass increasing by 1.6%, Ruditapes philippinarum biomass increasing by 0.5% and Portunus trituberculatus biomass increasing by 134%, reflecting the development of the Wangjiadao Islands water’s ecosystem, and the results can be used as a reference for fisheries resource management.

1. Introduction

Marine islands play a crucial role in marine ecosystems. Due to the uncontrolled exploitation of some island resources in recent years, which has resulted in a severe decline of major fishery resource species, the scientific conservation of island ecosystems has gained increasing global attention [1]. The waters surrounding the Wangjiadao islands in Dalian, China, in the Northern Yellow Sea are abundant with shellfish and benthic species. The primary uses of the Wangjiadao islands are tourism and marine fishing. To utilize fisheries’ resources in the waters of the Wangjiadao islands scientifically, it is essential to undertake a scientific investigation of the marine ecosystem’s structure and develop appropriate fishing resource management strategies. There are currently a few articles on the distribution of organisms and ecological environment in the Wangjiadao islands’ waters, primarily on the distribution of red tide plankton [2] and the assessment of tourism value [3] in the Wangjiadao islands’ waters, but none on ecosystem analysis.

Ecopath is a model for analyzing the structure and function of marine [4,5] and freshwater [6,7] ecosystems. Polovina [8] initially proposed the model, followed by Ulanowicz et al. [9], who completed its theoretical module based on the ecological perspective of energy analysis, and Walters et al. [10] supplemented the Ecopath model with two plates, Ecosim and Ecospace, which are now widely used in aquatic ecosystem analysis. Numerous scientists have developed Ecopath-based ecosystem models for ponds, lakes, estuaries, the Bohai Sea, the Yellow Sea, the East China Sea, the South China Sea and artificial reefs in order to investigate ecosystem structure, function and energy flow characteristics [11,12,13,14,15,16,17,18,19]. In this study, the Ecopath model was used to analyze the ecosystem of the Wangjiadao islands’ waters in Dalian, China in order to elucidate the structural characteristics and energy flow patterns of the ecosystem and provide a theoretical foundation for the enhancement and management of marine fishery resources.

2. Materials and Methods

2.1. Data Source

The data for this study were obtained from field surveys in April, September and November 2019 in the Wangjiadao islands’ waters (Figure 1). This consists of phytoplankton, zooplankton, macrobenthos and swimming animals. Sampling and survey methods were developed according to the Marine Survey Specification [20]. The experimental protocols were approved by the Animal Care and Protection Committee of Dalian Ocean University.

2.2. Research Methods and Rationale

The Ecopath model defines an ecosystem as a series of ecologically related functional groups, all of which can essentially cover the pathways of ecosystem energy flow and quantitatively describe the energy flow between organisms in the ecosystem to demonstrate the scale of this ecosystem, as well as evaluate the stability and maturity of the system and the competition and predation relationship within the system [21,22].

The Ecopath model is controlled by a consumption equation based on the principle of energy conservation and a biomass equation based on the principle of matter conservation [23]. The equations are formulated as follows:

$$Q_i=P_i+R_i+U_i$$

(1)

where Q_i, P_i, R_i and U_i are the consumption, production, respiration and undigested food of functional group i, respectively;

$$B_i\cdot (P/B_i)=({\displaystyle \sum B_j\cdot Q/B_j)\cdot D{C}_{ji}+E_i+Y_i+B{A}_i+B_i\cdot P{B}_i(1-E{E}_i)}$$

(2)

where B_i, E_i and Y_i are the biomass, net emigration and catch of functional group i, respectively; BA_i, EE_i and P/B_i are the bioaccumulation rate, ecotrophic efficiency, and the ratio of production to its biomass of functional group i, respectively, and; B_j and Q/B_j are the ratio of biomass of predator j and biomass to consumption, respectively, and; DC_ji is the proportion of prey i consumed by predator j.

In this study, the ecological capacity was defined as the maximum capacity of a target species that did not significantly alter the main energy flow and food web structure of the ecosystem after the introduction of a large number of target species [24]. To estimate the ecological capacity of the main economic species, based on the Ecopath model that reflected the current energy flow state of the Wangjiadao islands’ waters, the biomass of the target species in the model was gradually increased to represent the expansion of the scale of enhancement of the target species in the actual production (the corresponding fishing yield also increased). The Ecopath model had to adjust other parameters to rebalance the system and determined the ecological capacity of the target species in the process of iterations. Therefore, if the biomass of the target species was increased until the EE > l of another functional group in the system was found, it meant that the biomass allowed in the system at that time was the ecological capacity of the target species [25].

2.3. Ecopath Model Building

The Ecopath model needs to divide the functional groups after taking into account the characteristics of different species, including individual size, feeding habits, biomass, habitat and taxonomic groups, etc. [26]. In this study, nine species of sea cucumber, Mizuhopecten yessoensis, Chlamys farreri, Ruditapes philippinarum, Ostrea gigas Thunberg, Scapharca broughtonii, Penaeus orientalis, Portunus trituberculatus and Oratosquilla oratoria were used as target organisms in the Wangjiadao islands’ waters. To calculate the ecological capacity of the target organisms, each of the nine species was divided into one independent functional group, and the remaining organisms were divided into 13 functional groups based on their size, biology and feeding characteristics, for a grand total of 22 functional groups (

Table 1. Functional groups and main species of marine ranch ecosystem in Wangjiadao islands’ waters.

No.	Group Name	Species Composition
1	Scomber japonicus	Scomber japonicus
2	Platycephalus indicus	Platycephalus indicus
3	Other pelagic fish	Pholis nebulosa, Scomberomorus niphonius, Engraulis japonius, Setipinna tenuifilis
4	Other demersal fish	Larimichthys polyactis, Gobiidae tenuifilis, Hexagrammos otakii
5	Stichopus japonicus	Stichopus japonicus
6	Penaeus orientalis	Penaeus japonicus, Fenneropenaeus chinensis
7	Portunus trituberculatus	Portunus trituberculatus
8	Oratosquilla oratoria	Oratosquilla oratoria
9	Small crustaceans	Alpheus distinguendus, Palaemon gravieri
10	Mizuhopecten yessoensis	Mizuhopecten yessoensis
11	Chlamys farreri	Chlamys farreri
12	Ruditapes philippinarum	Ruditapes philippinarum
13	Ostrea gigas thunberg	Ostrea gigas thunberg
14	Scapharca broughtonii	Scapharca broughtonii
15	Other mollusks	Abalone, Octopodidae, Rapana venosa
16	Copepods	Calanus sinicus, Euchaeta concinna
17	Other benthos	Nereis succinea
18	Microzooplankton	Protozoa, Rotifer
19	Other macrozooplankton	Euphysora spp.
20	Macroalgae	zostera marina, Porphyra, crispata, Kjellm, Gelidium amansii
21	Phytoplankton	diatom, Cyanobacteria, Dinoflagellates
22	Detritus	Bodies of animals and plants, excrement Organic matter imported from rivers

).

2.4. Source of Functional gr 2.4 Source of Functional Group Parameters

In this study, wet weight (t·km⁻²) was used to represent the energy flow in the Wangjiadao islands waters’ ecosystem when using the Ecopath model, and limited the time period to 1 year [25]. The biomass of organic detritus was determined using the empirical method given by Pauly et al. [27]. For the purpose of calculating their biomass, zooplanktons were categorized, identified and counted, and functional groupings were categorized based on their biomass. Phytoplankton were converted according to the correlation between seawater chlorophyll density and phytoplankton biomass [28]. The biomass of macroalgae was estimated using the truncated sample strip method [19]. The biomass of fishes, shrimps and crabs was obtained using the trawl sweeping sea area method. The biomass of Philippine clams was obtained using the clam rake net sweeping sea area method. The biomass of shellfish, such as scallops and arks, was obtained by random sampling and weighing in the sea area in a hanging cage. The biomass of benthic organisms was obtained using a grab mud collector, and auxiliary drift gill nets and geo-cage nets were used to collect fish, cephalopods and others. The biomass of benthic organisms, sea cucumbers and shellfish functional groups was estimated by combining underwater cameras (SCUBA divers). The P/B and Q/B values of each functional group of fish were calculated based on the derivation of empirical equations proposed by Pauly [29] and Palomares et al. [30], and the P/B and Q/B values of other functional groups were estimated by referring to the functional groups of similar marine areas or ecosystems with similar characteristics. The food composition of each functional group was established by analyzing the contents of the stomach and consulting the literature on comparable waters at the same latitude. The fishing data of Wangjiadao islands’ waters were estimated based on the real local fishing yield.

2.5. Model Quality Analysis

The accuracy and reliability of the sources of the Ecopath model parameters are the main factors affecting their quality. In this study, the Pedigree index (abbreviated p-index) was used to evaluate the source and quality of the input parameters in the model and to quantify the uncertainty of the model input parameters [31]. The input parameters were identified according to the quality of the data sources, with the order of data quality being: sample measurements, formula estimation, reference to other models and references. The uncertainty range of 0 to 1 was used as the uncertainty range for the parameters B, P/B, Q/B and DC. The p index of each functional group can be used as an evaluation index of the overall quality of the Ecopath model of the Wangjiadao islands waters’ ecosystem [23], which was calculated as follows.

$$P={\displaystyle \sum _{i=1}^n\frac{I_{ij}}{n}}$$

(3)

where n represents the total number of functional groups in the Wangjiadao islands waters’ ecosystem model, I_ij represents the p-index of the ith functional group in the system model and j represents the B, P/B, Q/B, catch and food matrix.

3. Results

3.1. Analysis of Energy Flow Data of Wangjiadao Islands Waters’ Ecosystem

3.1.1. Trophic Level Characteristics of Wangjiadao Islands Waters’ Ecosystem

The values of Ecopath model parameters in Wangjiadao islands’ waters were shown in

Table 2. Estimated parameters of functional groups of the Ecopath model in the marine ecosystem of Wangjiadao islands’ waters.

Group Name	Trophic Level	Biomass (t/km²)	Production/Biomass (a−1)	Consumption/Biomass (a−1)	Ecotrophic Efficiency	Production/Consumption (a−1)
Scomber japonicus	3.91	1.81	2.16	5.20	0.07	0.41
Platycephalus indicus	3.79	1.43	1.28	11.35	0.11	0.11
Other pelagic fish	3.47	13.10	0.99	7.10	0.69	0.14
Other demersal fish	3.13	1.60	3.91	6.54	0.62	0.59
Stichopus japonicus	2.30	54.20	1.30	3.36	0.31	0.39
Penaeus orientalis	3.34	3.35	25.37	45.20	0.35	0.56
Portunus trituberculatus	3.52	1.28	3.13	12.30	0.82	0.25
Oratosquilla oratoria	2.94	3.66	1.10	8.00	0.44	0.14
Small Crustaceans	2.56	46.00	6.10	41.22	0.46	0.15
Mizuhopecten yessoensis	2.30	417.10	1.86	16.65	0.41	0.11
Chlamys farreri	2.57	346.60	1.67	6.10	0.49	0.27
Ruditapes philippinarum	2.51	194.00	5.00	20.00	0.13	0.25
Ostrea gigas thunberg	2.71	175.50	3.99	16.90	0.14	0.24
Scapharca broughtonii	2.51	114.30	22.86	457.3	0.11	0.05
Other molluscs	2.30	18.30	5.30	50.60	0.92	0.11
Copepods	2.05	260.00	68.90	150.10	0.76	0.46
Other benthos	3.13	11.00	5.13	27.50	0.49	0.19
Microzooplankton	2.00	265.00	88.30	297.90	0.97	0.29
Other Macrozooplankton	2.00	15.03	27.00	57.70	0.88	0.47
Macroalgae	1.00	14.64	100.00	--	0.71	--
Phytoplankton	1.00	400.90	285.00	--	0.81	--
Detritus	1.00	311.60	--	--	0.57	--

Notes: The bold italic part is the estimated value of the model, and the others are input values.

. The trophic levels of all functional groups in this ecosystem were concentrated in the range of 1~3.91, The trophic levels of all functional groups in this ecosystem were concentrated in the range of 1~3.91, with Scomber japonicus having the highest trophic level, followed by Platycephalus indicus with 3.79. With a trophic level of 1, macroalgae, phytoplankton and detritus had the lowest level. The trophic levels of sea cucumbers and bivalves ranged from 2.30 to 2.71, with the oyster (Ostrea gigas thunberg) having the highest trophic level. The ecological efficiency (EE) value of each functional group was in the range of 0.07–0.97, with small zooplankton having the highest EE values.

3.1.2. Trophic Level Energy Flow and Transfer Efficiency of Wangjiadao Islands Waters’ Ecosystem

The energy flow pathways of trophic levels and the food web structure of Wangjiadao islands waters’ ecosystem were shown in Figure 2. The Figure revealed that there were two major food chains in the waters, i.e., a detritus food chain starting from detritus, and a grazing food chain starting from primary producers, such as phytoplankton and macroalgae.

According to the network analysis of the Ecopath model, the Wangjiadao islands waters ecosystem’s energy flow primarily occurred between four trophic levels. Figure 3 depicted the energy flow relationship among organisms. Trophic level I consisted of detritus, macroalgae and phytoplankton, while the majority of nutrient flow of consumer functional groups in the Wangjiadao islands waters’ ecosystem was concentrated in trophic levels II and III.

Table 3. Distribution of integrated trophic-level energy flow in the Wangjiadao islands waters’ ecosystem.

Trophic Levels	Integrated Trophic Level Energy Flow Distribution
	Consumption by Predators	Export	Flow to Detritus	Respiration	Throughput
V	2.93	0.25	11.12	15.23	29.53
IV	29.53	7.50	380.70	519.10	936.90
III	936.90	403.9	15,398.00	19,505.00	36,245.00
II	36,245.00	460.5	66,473.00	50,226.00	153,405.00
I	153,405.00	44,589.00	21,797.00	0	219,790.00
Sum	190,619.00	45,461.00	104,062.00	70,268.00	410,409.00

displayed the distribution of trophic level energy flow. The total flow of the system was 410,409 tkm²·a⁻¹, with the flow of trophic levels I and II accounting for the majority, 53.55 percent and 37.38 percent, respectively. The total flow of each trophic level was inversely proportional to its trophic level, in accordance with the ecological energy pyramid law.

According to

Table 4. Transfer efficiency of trophic level of ecosystem in Wangjiadao islands’ waters.

Source	Trophic Level (TL)
	II	III	IV
Producer	24.45	3.620	4.696
Detritus	23.30	4.661	3.723
All flows	24.01	4.013	4.247
Proportion of total flow originating from detritus			43%
Transfer efficiencies (calculated as geometric mean for TL II-IV)
From primary producers			7.463%
From detritus			7.395%
Total transfer efficiencies			7.423%

, the transfer efficiency of energy flow from the producer between trophic level I and II in the Wangjiadao islands waters’ ecosystem was the highest (24.45%). The total energy transfer efficiency of the Wangjiadao islands waters’ ecosystem was 24.01%, while the integrated transfer efficiency from trophic level II to level IV was 4.013% and 4.247%, respectively. In the Wangjiadao islands waters’ ecosystem, the proportion of energy flowing into the ecosystem via the detritus food chain (43.00%) was lower than that of the grazing food chain (57.00%), indicating that the grazing food chain was the primary mode of energy flow. The primary producers’ transfer efficiency was 7.463%, which was slightly higher than that of detritus (7.395%). The total transfer efficiency of the Wangjiadao islands waters’ ecosystem was 7.423%, which was lower than the Lindemann efficiency of 10.00%.

3.1.3. Analysis of Mixed Trophic Effects in Wangjiadao Islands Waters’ Ecosystem

The mixed trophic impact among the biological functional groups in the Wangjiadao islands waters’ ecosystem was shown in Figure 4. The negative effect generally results from predation or competition for niches between species of the same trophic level, and the positive effect comes mainly from the prey and the mutualism from other species. In the Wangjiadao islands waters’ ecosystem model, the detritus, phytoplankton and macroalgae functional groups showed a positive effect on most of the consumer functional groups, especially on Mizuhopecten yessoensis, Chlamys farreri, Ruditapes philippinarum, copepods and sea cucumbers. Because of the food competition between functional groups, Platycephalus indicus showed strong negative effects on other demersal fish, and Portunus trituberculatus showed a strong negative effect on Oratosquilla oratoria. There are also some negative effects between bivalves. In addition, marine fishing had a significant negative effect on the target species.

3.1.4. Analysis of Key Species in Wangjiadao Islands Waters’ Ecosystem

The keystone species of ecosystems are biological species that are relatively low in biomass and play an important role in the ecosystem and the food web by mapping the relationship between the relative overall impact (εi), and the keystone index (KSi) can identify key species [32]. The functional groups of the Wangjiadao islands’ marine ecosystem were arranged in the corresponding figure (Figure 5) according to descending order of key index values. The keystone species corresponded to functional groups with higher εi and higher KSi (values close to, or greater than, 0). According to the keystone index and the relative overall impact value, the benthos group was a keystone species which played an important role in the Wangjiadao islands waters’ ecosystem. In addition, comparing the key indices of other functional groups (

Table 5. Key Species Index and Relative Total Impact of Wangjiadao islands waters’ ecosystem.

Index	Functional Group	Keystone Index #1	Keystone Index #2	Keystone Index #3	Relative Total Impact
1	Scomber japonicus	−0.19	2.93	1.04	0.51
2	Platycephalus indicus	−0.04	3.17	1.26	0.71
3	Other pelagic fish	−0.01	2.25	1.14	0.78
4	Other demersal fishes	−0.72	2.45	0.56	0.15
5	Stichopus japonicus	−0.88	0.77	0.09	0.11
6	Penaeus orientalis	−0.14	2.71	1.06	0.57
7	Portunus trituberculatus	0.05	3.32	1.38	0.88
8	Oratosquilla oratoria	−0.81	2.34	0.45	0.12
9	Small Crustaceans	−0.74	1.71	0.99	0.78
10	Mizuhopecten yessoensis	−0.01	−0.14	−0.89	0.10
11	Chlamys farreri	−1.01	−0.11	−0.47	0.09
12	Ruditapes philippinarum	−0.84	0.28	−0.03	0.12
13	Ostrea gigas thunberg	−0.58	0.58	0.29	0.22
14	Scapharca broughtonii	−0.16	1.18	0.76	0.57
15	Other molluscs	−0.28	1.82	0.76	0.41
16	Copepods	−0.34	0.67	0.41	0.41
17	Other benthos	0.10	2.44	1.28	1.00
18	Microzooplankton	−0.34	0.66	0.31	0.40
19	Other Macrozooplankton	−0.46	1.74	0.62	0.27
20	Macroalgae	−0.34	1.87	0.77	0.36
21	Phytoplankton	−0.17	0.68	0.21	0.64

), the key indices and relative total impact values of other benthic animals were larger (0.1 and 1), indicating that other benthic animals in the current Wangjiadao islands waters’ ecosystem may be key species.

3.1.5. General Characteristics of Wangjiadao Islands’ Marine Ecosystem

According to the network analysis function of the Ecopath model, the calculated parameters describing the energy flow, stability and food network characteristics of the ecosystem were shown in

Table 6. Comparison of energy characteristic parameters in ecosystem before and after enhancement of Wangjiadao islands’ waters.

Parameter	At Present	After Enhancement
Sum of all consumption/t·km−2·a−1	190,618.91	194,110.50
Sum of all exports/t·km−2·a−1	45,460.69	43,190.28
Sum of all respiratory flows /t·km−2·a−1	70,267.95	72,538.38
Sum of all flows into detritus/t·km−2·a−1	104,061.70	102,427.10
Total system throughput/t·km−2·a−1	410,409.31	412,266.31
Sum of all production/t·km−2·a−1	163,706.09	164,229.00
Calculated total net primary production/t·km−2·a−1	115,728.60	115,728.60
Total primary production/total respiration	1.65	1.59
Net system production/t·km−2·a−1	45,460.69	43,190.27
Total primary production/total biomass	49.10	43.25
Total biomass/total throughput	0.006	0.006
Total biomass (excluding detritus)	2356.83	2675.65
Connectance Index	0.24	0.24
System Omnivory Index	0.18	0.19
Ecopath pedigree	0.475	0.475
Finn Cycling Index	13.89	13.89
Mean Path Length	3.55	3.55

. Total system throughput (TST) is 410,409.31 t·km²·a⁻¹, which quantifies the total consumption, total export, total respiration and total flow into detritus, and reflects the size of the system. The total output is 45,460.69 t·km²·a⁻¹, the total respiration is 70,267.95 t·km²·a⁻¹, the total consumption is 190,618.91 t·km²·a⁻¹, the flow to detritus is 104,061.70 t·km²·a⁻¹ and the total production is 163,706.09 t·km²·a⁻¹, accounting for 11.07%, 17.12%, 46.45%, 25.36% and 39.89% of the total flow of the system, respectively. The sum of the energy output of the system and the energy flow to the debris reached 36.43%, indicating that the energy utilization efficiency of the system was low. The ratio of total primary production to total respiration (TPP/TR) was 1.65, the ratio of total primary production to total biomass (TPP/TB) was 49.10, the system connectance index (CI) was 0.24, the system omnivory index (SOI) was 0.18, the Finn’s cycling index (FCI) was 13.89 and the Finn’s mean path length (MPL) was 3.55 for the Wangjiadao islands’ marine ecosystem.

Without significantly changing the main energy flow and food web structure of the existing fishery ecosystem, the biomass of sea cucumbers, Mizuhopecten yessoensis, Chlamys farreri, Ruditapes philippinarum and Portunus trituberculatus was sequentially increased in the Ecopath model until the EE value was close to, but not yet, >1, at which point the biomass of the target species represented the ecological capacity. The ecological capacity of sea cucumbers, Mizuhopecten yessoensis, Chlamys farreri, Ruditapes philippinarum and Portunus trituberculatus was determined to be 185 t/km², 595 t/km², 352 t/km², 195 t/km² and 3 t/km², respectively. Compared with the original biomass (Table 2), it can be seen that the enhancement capacity of sea cucumbers, Mizuhopecten yessoensis, Chlamys farreri, Ruditapes philippinarum and Portunus trituberculatus were, respectively, 130.8 t/km² (approximately 242% of existing biomass), 177.9 t/km² (approximately 42% of existing biomass), 5.4 t/km² (approximately 1.6% of existing biomass), 1 t/km² (approximately 0.5% of existing biomass) and 1.72 t/km² (approximately 134% of existing biomass). The total energy output of the marine ecosystem and the energy flow to the detritus both decreased after the enhancement of target species, while the total system flow and the total system production relatively increased. Therefore, by increasing the biomass of the target species, the loss of energy within the Wangjiadao islands waters’ ecosystem was reduced and the energy use efficiency of the system was increased (Table 6).

4. Discussion

The Ecopath model is capable of reflecting the general characteristics, trophic relationships and energy flow of each functional group in a specific aquatic ecosystem [23]. In this study, we established the first ecosystem model of Wangjiadao islands’ waters based on 22 functional groups and evaluated the trophic structure and energy flow characteristics in a complex food web. The quality of the Ecopath model is mainly verified by the Pedigree index, which evaluates the source and quality of the input parameters in the model. According to Morissette et al. (2006) [32], the Pedigree index of 150 Ecopath models around the world ranged from 0.16 to 0.68. The data in this study were mainly obtained from in situ biological resources and environmental surveys, and the Pedigree index of the constructed Ecopath model was 0.475, indicating that the input data of the model was reliable and the credibility of the model was high.

4.1. General Characteristics of Wangjiadao Islands Waters’ Ecosystem

In recent years, the majority of human-generated waste has been discharged into the sea, the coastal waters have been severely polluted, the marine ecosystem has been severely harmed, and the traditional fishery resources have experienced a significant decline [32]. The total transfer efficiency of the Wangjiadao islands waters’ ecosystem was about 7.4 %, which was lower than the Lindemann efficiency (10.00%) [33], which does not exclude that there was a correlation with the sampling method. The ecosystem characteristics evaluated by the Ecopath model can be used to measure the size, maturity and stability of the system. A TPP/TR ratio close to 1, and a smaller TPP/TB ratio, are indicative of a mature ecosystem. The greater CI and SOI values indicate that the structure of the ecosystem is more complex, that the functional groups are more closely linked, and that external environmental changes have less of an effect on the ecosystem, thereby making it more stable. The TPP/TR value of Wangjiadao islands waters’ ecosystem was 1.65, which was obviously higher than 1. The ecosystem was in a growth phase because the amount of biological respiration was lower than the amount of production. The CI and SOI values of the Wangjiadao islands’ ecosystem were 0.24 and 0.18, respectively, which were lower than other similar marine ecosystems [16,24,34,35], indicating that the ecosystem was currently at an early stage of development, with low maturity, poor system stability, simple biological species, and was susceptible to external disturbances. This may be attributed to the fact that the Wangjiadao islands were tourist islands and that environmental degradation and fishing activities (angling, trawling, etc.), induced by frequent human activities, have led to a lack of biodiversity in the area [36,37]. Serious underutilization of primary productivity in the Wangjiadao islands waters’ ecosystem may be attributable to the fact that the sampling biomass was insufficient due to survey conditions, but it also reflects, to some extent, the lack of high trophic level species in the system necessary to fully utilize the primary productivity.

4.2. Suggestions for Increasing Stocking in Wangjiadao Islands Waters

Currently, fishery enhancement is one of the primary techniques for restoring fishery resources [38], and scientific evaluation of enhancement capacity is the key to successful enhancement. The Ecopath model has been successfully applied to the assessment of enhancement capacity [16,39]. The Ecopath model of the Wangjiadao islands’ marine ecosystem was used to simulate enhancement of sea cucumbers, Mizuhopecten yessoensis, Chlamys farreri, Ruditapes philippinarum and Portunus trituberculatus as the main target species, and it was found that Mizuhopecten yessoensis had the highest enhancement capacity in the area, with about 177.9 t/km², followed by sea cucumber, with about 130.8 t/km², and Portunus trituberculatus, Chlamys farreri and Ruditapes philippinarum, with about 1.72 t/km², 5.4 t/km² and 1 t/km², respectively. This may be related to the feeding characteristics of plankton and particulate organic matter, such as debris, as bait. Zhang Zixuan et al. [40] found that the ecological capacity of Mizuhopecten yessoensis in Zhangzidao Island waters was 17.5 times higher after enhancement. It is noteworthy that, although the filter-feeding action of shellfish can improve the efficiency of material cycling and energy flow in the ecosystem and better utilize the remaining production for the purpose of restoration and conservation of fishery resources, shellfish can inhibit sediment resuspension during feeding, and too high a release density will enrich sediment debris with large amounts of nutrient salts, which will be affected by material cycling and hydrodynamics, leading to high nutrients. The high nutrient content of the debris can lead to retransportation into the water column, thus causing polluting damage to the ecosystem [41,42]. Therefore, when carrying out enhancement work, it is necessary to limit the size and quantity and release of them in different years to achieve the purpose of improving economic efficiency and ecological protection. Also, when estimating the ecological capacity, it is known that the main reason for limiting the ecological capacity of the above-mentioned economic species is the biomass of bait organisms, mainly other benthic animals, and it is recommended to release the corresponding bait organisms into the water body to expand the ecological capacity of the main economic species [43].

5. Conclusions

Ecopath software was firstly used to simulate the ecosystem of the Wangjiadao islands’ waters, revealing the energy flow characteristics of this ecosystem, basically reflecting the development status of Wangjiadao islands’ marine ecosystem and assessing the ecological capacity of target species. The results of the study provided a theoretical reference for proliferating target species and managing fishery resources based on the ecosystem.

In the future, we will further investigate the biological resources and environment of the Wangjiadao islands’ waters to analyze the structure and energy flow characteristics of this ecosystem more comprehensively, and to assess the ecological capacity of various economic species and the enhancement capacity of these species by using various ecosystem models, so as to provide a more adequate and detailed theoretical basis for fishery enhancement and efficient use of the Wangjiadao islands’ waters.