Short-term responses of the macrobenthic community to stock enhancement in the mangrove areas of Yueqing Bay, East China Sea

doi:10.21203/rs.3.rs-7268575/v1

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Short-term responses of the macrobenthic community to stock enhancement in the mangrove areas of Yueqing Bay, East China Sea

https://doi.org/10.21203/rs.3.rs-7268575/v1

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Stock enhancement is recognized as a vital strategy for achieving sustainable development, and the assessment of short-term effects following such enhancements is essential. In this study, we conducted an ecological survey in the mangrove areas of Yueqing Bay (East China Sea) prior to stock enhancement (October 2021), followed by post-enhancement monitoring from January to October 2022. This provided macrobenthos data across five seasons, enabling an analysis of changes in the macrobenthic community structure and evaluation of the short-term effects of stock enhancement. The results revealed that stock enhancement increased the species number, abundance, and biomass of macrobenthos; improved the similarity and secondary productivity of the macrobenthic community; and enhanced the benthic ecological quality. The main contributor to the average dissimilarity in the macrobenthic community before and after stock enhancement was Pseudomphala latericea. The increased population of Phascolosoma esculenta (detritivores) provides more organic matter for P. latericea (omnivores) while reducing predation on P. latericea by carnivores. These combined effects led to differences in the macrobenthic community before and after stock enhancement. Importantly, mangrove areas are particularly susceptible to human activities. Therefore, effective management following stock enhancement is crucial.

Stock enhancement

Macrobenthic community

Yueqing Bay

Mangrove areas

The rapid growth of the global population and socio-economic development has led to a rising demand for aquatic products, presenting significant challenges to marine ecosystems (Cheng and Jiang 2010). Urgent issues that need to be addressed include overfishing, severe declines in fishery resources, inefficient fishing techniques, and the slow growth of incomes that are reliant on fisheries. In response, various governments have implemented a series of fisheries management measures, which can be categorized into controlling fishing efforts, establishing marine protected areas, and implementing stock enhancement strategies for marine biological resources (Cheng and Jiang 2010). Among these, stock enhancement is regarded as the most direct and fundamental approach to restoring fishery resources and an essential strategy for achieving sustainable development (Grimes 1998), although many attempts have fallen short of expectations (Boyce et al. 1993; Svåsand et al. 2000). Current stock enhancement activities primarily focus on economic benefits, with insufficient attention given to social and ecological outcomes. Compared with economically valuable aquatic species such as fish, shrimp, and crabs, species released for ecological restoration—particularly endemic, rare, and endangered species—are relatively scarce in both species and quantity (Luo et al. 2016; Yang et al. 2009). Moreover, most stock enhancement efforts have concentrated on restoring aquatic biological resources; while few studies have explored the potential of stock enhancement to optimize the ecological functions of tidal flat wetlands (Du et al. 2024).

Yueqing Bay, an important marine aquaculture area in Zhejiang Province, is bordered by Yuhuan City to the east, Yueqing City to the west, and Wenling City to the north, and is endowed with abundant tidal flat resources (Li et al. 2021). Yuhuan City has committed to preserving the "northernmost boundary" of China's mangroves by implementing the principle that "lucid waters and lush mountains are invaluable assets" and actively promoting marine ecological restoration and industrial transformation through initiatives such as mangrove planting and rehabilitation. In 2021, relevant departments in Yuhuan launched stock enhancement activities to support ecological restoration in mangrove areas. Phascolosoma esculenta, a key macrobenthic component of local mangroves, was selected for release. This species is important for the creation of a famous tonic and other uses in traditional medicine (Wu and Xu 2018). P. esculenta is an ecologically important, reliable bioindicator species due to its sensitivity to heavy metals and organic pollutants (Liu et al. 2022).

Macrobenthos are crucial components of mangrove ecosystems, linking primary producers and top predators while playing a key role in material cycling and energy flow (Snelgrove 1998). Shifts in the macrobenthic community can reflect environmental changes and act as crucial bioindicators for ecosystem evaluation (Jia et al. 2025). In recent years, the increase in stock enhancement activities and the increasing significance of macrobenthos in marine ecosystems has caused the impacts of stock enhancement on macrobenthos to become an important research topic (Du et al. 2024; Jia et al. 2025; Yang et al. 2024). However, research on the response of macrobenthic communities in mangrove areas to stock enhancement is limited. Existing studies have focused primarily on changes in diversity indices and the Multivariate AMBI (M-AMBI) in the Yueqing Bay mangrove areas before and after stock enhancement (Yang et al. 2024). Evaluating the ecological effects of stock enhancement through community composition and structural characteristics provides direct evidence and comprehensive support for understanding the mechanisms by which stock enhancement impacts benthic animal communities. Additionally, short-term changes in the macrobenthic community can be used to assess the immediate effects of stock enhancement. Based on these short-term assessment results and dynamic monitoring data, targeted optimization can be implemented to facilitate effective ecological restoration (Ren et al. 2016).

Therefore, the objectives of this study were: 1) to explore the short-term effects of stock enhancement on the macrobenthic community in mangroves; and 2) to evaluate the short-term effects of population enhancement based on changes in the community before and after stock enhancement. This study not only provides a valuable reference for ecological restoration in mangrove areas but also offers robust support for future ecological conservation and resource management.

2.1 Stock Enhancement Implement

This study was conducted in six mangrove ecological restoration zones located in the central part of the Yueqing Bay. The tidal regime is characterized by regular semidiurnal tides, and the substrate is primarily composed of clayey silt. The main mangrove species is Kandelia candel, with plantations concentrated in the high- and middle-tide zones. The released P. esculenta populations were all first-generation (F1) seedlings derived from locally bred parents in Yueqing Bay, with body lengths ≥ 10 mm. The wet sowing method was used for stock enhancement, which involved uniformly distributing the seedlings within premarked areas on the mudflat during high tide or when the tide had not yet receded from the high-tide zone. A total of 10 million P. esculenta were released in each restoration zone, amounting to 60 million individuals across all zones. Six identical monitoring sections were established based on the release sites (Fig. 1). Each section was subdivided into high-tide, mid-tide, and low-tide zones, resulting in 18 monitoring stations.

2.2 Data Collection

To establish a baseline prior to stock enhancement, an ecological survey was conducted in October 2021. Stock enhancement was then implemented in November 2021 across six mangrove ecological restoration zones in Yueqing Bay. Post-enhancement monitoring surveys were conducted seasonally in January 2022 (2022.01), April 2022 (2022.04), July 2022 (2022.07), and October 2022 (2022.10) to assess ecological changes..

For macrobenthic sampling, a 25 cm×25 cm×30 cm frame was used, with four sampling quadrats (totaling 0.25 m²) at each site. The biological samples were processed using a sieve washing method with a 0.5 mm mesh sieve. After cleaning, all the samples were bottled separately on site, fixed in a 75% alcohol solution, and brought back to the laboratory for classification, identification, counting, and weighing.

2.3 Index of Relative Importance (IRI)

The Index of Relative Importance was used to rank and analyze the dominant species of macrobenthos. The formula for calculating the IRI (Pinkas 1971) is as follows:

IRI = (N + W) × F

where N denotes the percentage of individuals of a species in a section, W represents its biomass percentage, and F is its occurrence frequency (number of sections where the species is present divided by total sections). A species is considered dominant when its IRI > 1000 (He et al. 2013).

2.4 Community Structure Analysis

The analysis of the macrobenthic community structure began with the square root transformation of the macrobenthic abundance data. A Bray–Curtis similarity matrix was then calculated, followed by hierarchical cluster analysis (Cluster) and nonmetric multidimensional scaling (NMDS). NMDS is particularly effective in revealing the response of biological communities to continuous abiotic environmental gradients (Zhou and Zhang 2003). The stress coefficient indicates the credibility of the analysis (Clarke and Warwick 2001). Specifically, when stress < 0.01, the results are fully reliable; when 0.01 < stress < 0.05, the results are reliable; when 0.05 < stress < 0.1, the results are generally reliable; and when stress < 0.2, the results provide some reference value. Analysis of similarities (ANOSIM) was used to assess the significance of differences in species composition among clustered groups. Additionally, the similarity percentage (SIMPER) program was employed to compute the average contribution of each species to within-group similarity and between-group differences.

2.5 Secondary Productivity

The formula for calculating the secondary productivity of the macrobenthic community (Brey 1990; Yan et al. 2012) is as follows:

P = A^0.27×B^0.73/10^0.4

where P represents the secondary productivity of macrobenthos per section (AFDW, g·m⁻²·a⁻¹), A denotes the abundance of macrobenthos per section (ind./m²), and B indicates the ash-free dry weight biomass of macrobenthos per section (g/m²). The conversion ratio from wet weight to dry weight for biomass is 5:1 (Waters 1977), and the ratio from dry weight to ash-free dry weight (AFDW) is 10:9 (Holme and McIntyre 1984).

2.6 Macrozoobenthos Pollution Index

The macrozoobenthic pollution index (MPI) is based on the ABC curve, which is transformed into an index method, expanding the three pollution levels of the ABC curve into four levels (Cai 2003). The MPI calculation formula is as follows:

MPI = 10^{(2 + k)} [∑ (A_i - B_i)]/S^1 + k,

k = |∑ (A_i - B_i) |/∑ (A_i - B_i).

When ∑ (A_i - B_i) is positive, k = 1; when ∑ (A_i - B_i) is negative, k = -1. A_i and B_i represent the cumulative percentage dominance of the ith species arranged in order of abundance dominance and biomass dominance, respectively. Notably, they do not necessarily refer to the abundance and biomass of the same species.

The pollution level of marine areas can be assessed on the basis of MPI values as follows: severe pollution: MPI > 4 (bad); moderate pollution: 0 < MPI ≤ 4 (moderate); mild pollution: -6 < MPI ≤ 0 (good); and a clean marine environment: MPI < -6 (high).

2.7 Data Processing

ArcGIS Desktop 10.8 was employed to create a map of the sampling section distribution. Microsoft Excel 2019 was used to calculate the relative importance index, MPI, and secondary productivity of the macrobenthic community. GraphPad Prism 9.5.0 was utilized to generate pie charts, bar charts, and line graphs. SPSS 19.0 statistical software was used to analyze the data, and one-way analysis of variance (ANOVA) and Tukey's HSD post hoc tests were conducted on macrobenthic community parameters.

3.1 Changes in Community Composition

During the research period, a total of 121 species of macrobenthos were collected. As shown in Fig. 2a, the proportions of Mollusca, Arthropoda, Annelida, Echinodermata, Chordata, Cnidaria, Nemertea, and Brachiopoda are 48 (39.67%), 30 (24.79%), 29 (23.97%), 5 (4.13%), 5 (4.13%), 2 (1.65%), 1 (0.83%), and 1 (0.83%), respectively.

The number of macrobenthic species before and after stock enhancement ranged from 38 to 59, with the highest count observed in April 2022 and the lowest in January 2022. Mollusca was the most abundant group in terms of species number in October 2021, July 2022, and October 2022, whereas Arthropoda and Annelida dominated in January 2022 and April 2022, respectively (Fig. 2b). A comparison of the differences before and after stock enhancement revealed that the number of species exhibited fluctuating trends. Comparing October 2022 with October 2021, the number of species among the macrobenthos increased.

Figure 2 Composition of the macrobenthic community in the mangrove areas of Yueqing Bay: (a) species composition; (b) proportions of species at different times

3.2 Changes in Dominant Species

As shown in Table 1, a total of 8 dominant species of macrobenthos were found in Yueqing Bay. Among them, there were 5 species of Arthropoda, 2 species of Mollusca, and 1 species of Annelida. Both P. esculenta and Tubuca arcuata were common dominant species. Specifically, in October 2021, there were 3 dominant species: T. arcuata, P. esculenta, and Metaplax longipes. In January 2022, there were 4 dominant species: P. esculenta, T. arcuata, Ilyoplax serrata, and Pseudomphala latericea. In April 2022, there were 6 dominant species: P. esculenta, P. latericea, Sinocorophium sinensis, Potamocorbula laevis, T. arcuata, and M. longipes. In July 2022, there were 5 dominant species: T. arcuata, P. latericea, M. longipes, P. esculenta, and Parasesarma plicatum. In October 2022, there were 6 dominant species: T. arcuata, P. latericea, M. longipes, P. esculenta, I. serrata, and P. plicatum. Comparing October 2022 with October 2021, the number of dominant species increased, and the IRI values were more uniform.

Table 1
Dominant macrobenthic species in the mangrove areas of Yueqing Bay
Species	Function group	Index of Relative Importance (IRI)
Species	Function group	2021.10	2022.01	2022.04	2022.07	2022.10
Tubuca arcuata	Ph (Zhang et al. 2019)	6396.57	2466.91	1415.59	3658.84	4469.70
Phascolosoma esculenta	D (Li et al. 2014)	4413.69	6833.65	2821.28	1855.20	2475.37
Ilyoplax serrata	Ph (Liao et al. 2013)	-	2463.86	-	-	1263.67
Metaplax longipes	Ph (You et al. 2011)	1736.53	-	1198.36	1903.83	2478.60
Parasesarma plicatum	Ph (Li et al. 2014)	-	-	-	1326.21	1192.69
Sinocorophium sinensis	Ph (You et al. 2011)	-	-	1773.76	-	-
Pseudomphala latericea	O (Wang et al. 2020)	-	2287.46	1895.83	2661.51	2728.35
Potamocorbula laevis	Pl (Zhang et al. 2019)	-	-	1419.47	-	-
Note: "-" indicates that the species had an IRI < 1000; Pl: planktophagous; Ph: phytophagous; O: omnivorous; D: detritivorous;

3.3 Changes in Abundance and Biomass

The average abundance of macrobenthos before and after stock enhancement ranged from 248.00 to 1924.00 ind./m², with the highest recorded value in April 2022 and the lowest in October 2021 (Fig. 3a). Notably, the abundance in April 2022 was particularly high due to the emergence of numerous S. sinensis and P. laevis in Section T2. The average biomass ranged from 52.43 to 251.29 g/m², with the highest value recorded in July 2022 and the lowest in January 2022 (Fig. 3b). One-way ANOVA results based on time showed that the macrobenthic abundance in April 2022 and the macrobenthic biomass in July 2022 had significantly increased in comparison with October 2021. A comparison of the differences before and after stock enhancement revealed that the abundance initially increased and then decreased, whereas the biomass first decreased, then increased, and finally decreased again. Comparing October 2022 with October 2021, both the abundance and biomass of macrobenthos increased (P > 0.05).

3.4 Analysis of Community Dissimilarities

Cluster analysis of the macrobenthic abundance data revealed that the macrobenthic communities in the mangrove areas of Yueqing Bay could be categorized into two groups, designated as Group A and Group B, based on a 46% similarity level (Fig. 4a). Data from October 2021 was classified into Group a, while data from January 2022 to October 2022 was classified into Group b. Non-metric multidimensional scaling (NMDS) results (Fig. 4b) confirmed this categorization, with a stress value of 0 (< 0.1) indicating a good fit. The ANOSIM results revealed that the differences in macrobenthic community structure between different cluster groups were not significant (global R = 0.667, P = 20%>0.05). SIMPER analysis was conducted on the macrobenthos to identify the species that characterized the community. No average similarity within cluster group a was found. The average similarity among species within cluster group b was 49.76%, with P. latericea (17.67%), P. esculenta (14.23%), and I. serrata (11.17%) as the primary contributors. The average dissimilarity between cluster groups A and B was 55.97%, with P. latericea (8.43%) as the primary contributor.

3.5 Changes in Secondary Productivity

The average secondary productivity of the macrobenthic community before and after stock enhancement ranged from 14.44 to 35.93 g·m⁻²·a⁻¹, with the highest value observed in July 2022 and the lowest in January 2022 (Fig. 5). One-way ANOVA results based on time indicated a significant increase in secondary productivity in April 2022 and July 2022 compared with that in October 2021. A comparison of the differences before and after stock enhancement revealed that the secondary productivity of the macrobenthic community first decreased, then increased, and finally decreased again, which was consistent with the trend in biomass. Comparing October 2022 with October 2021, secondary productivity improved (P > 0.05).

3.5 MPI Results and Consistency with M-AMBI Trends

The average MPI before and after stock enhancement ranged from − 21.14 to 0.24, with the highest value recorded in April 2022 and the lowest in October 2022 (Fig. 6a). One-way ANOVA results based on time showed a significant increase in MPI in January 2022 and April 2022 compared with that in October 2021. A comparison of the differences before and after stock enhancement revealed that the benthic ecological quality first decreased then increased. Quality was at its lowest, rated as "moderate", in April 2022, whereas at all other times, it was rated "high". Except for the period from July to October 2022, its trend was generally the same as that of the M- AMBI (Fig. 6b). Comparing October 2022 with October 2021, both indices indicated a slight improvement in benthic ecological quality (P > 0.05).

4.1 Macrobenthic Community Characteristics

Species composition is a fundamental characteristic of a community and a critical aspect of community ecology research (Zhou 2021). In this study, a total of 121 species of macrobenthos were collected, surpassing the 65 species recorded in the historical data from 2004–2005 (Zheng et al. 2007) and the 113 species reported in another study from 2006–2007 (Peng et al. 2011). This may be attributed to the multiple survey sections and the long time span as well as an increase in biodiversity in the mangrove areas (Chen et al. 2013) of Yueqing Bay due to the recent planting of additional mangroves (Chen 2016). Mangroves promote macrobenthic diversity and abundance by improving the microhabitats and food resources of macrobenthos (Demopoulos and Smith 2010; Frith 1977). Mollusca, Arthropoda, and Annelida were the dominant groups in the mangrove areas of Yueqing Bay, which is consistent with historical survey data (Peng et al. 2011; Zheng et al. 2006). The average abundance and biomass of macrobenthos were 798.13 ind./m² and 140.51 g/m², respectively, both of which were higher than historical levels (Zheng et al. 2007).

Changes in the dominant species of macrobenthos can effectively reflect variations in community structure and environmental shifts (Song et al. 2022; Yan et al. 2020). Historical studies in the mangrove areas of Yueqing Bay identified 19 dominant macrobenthic species (Peng et al. 2011), whereas 8 dominant species were observed in this study, with only 2 species (A. latericea and M. longipes) found in both datasets. Possible reasons for this discrepancy include the following: 1) There is a significant temporal gap between the studies. The previous study was conducted from 2006 to 2007, whereas the current study was conducted from 2021 to 2022, suggesting that the macrobenthic community in Yueqing Bay has changed. Yueqing Bay has undergone large-scale mangrove planting since 2005 (Chen 2016), and the study by Peng et al. coincided with a relatively early stage of mangrove growth, which may have contributed to the identification of a greater number of dominant species (Huang et al. 2017). 2) Differences in research methods. An earlier study used dominance (Y) as an evaluation index, whereas this study employed the Index of Relative Importance (IRI). The use of different methodologies could contribute to the observed discrepancy. Compared to Y, the IRI offers a more comprehensive and quantitative reflection of changes in dominant species (Han et al. 2004) and can indicate the importance of dominant species in community productivity (Smith and Knapp 2003). Among the common dominant species, A. latericea is primarily distributed in surface mud and is a frequent dominant species in mangrove ecosystems (Huang et al. 2017; Lin et al. 2021; Ma et al. 2018). M. longipes is phytophagous (Ph), and the increase in mangrove litter and organic debris provides an abundant food source (Zhang et al. 2019), which may explain why these species have maintained their dominant status over time.

4.2 Short-term responses of the Macrobenthos Community to Stock Enhancement

In this study, the number of macrobenthic species was generally greater after stock enhancement than before, with the exception of January 2022. This can be attributed to lower winter water temperatures, which can limit the survival of warm-water species (Zhou et al. 2016). When comparing October 2022 with October 2021, the number of macrobenthic species increased. Most species were common both before and after stock enhancement, with few species, typically those considered rare, uniquely present in low abundance before or after stock enhancement. For instance, Philine kinglipini and Amalda rubiginosa were observed before stock enhancement, whereas Eucrate crenata and Peronia verruculata were found after stock enhancement. Therefore, stock enhancement increased the number of macrobenthic species while largely preserving the species composition (Wang 2016).

The dominance of certain species in a biological community is closely linked to community stability. A greater degree of species dominance leads to a more unbalanced and fragile community ; a lower degree of species dominance leads to a more stable community (Ding et al. 2021; Zhou 2021). Before stock enhancement, there were three dominant species, with T. arcuata exhibiting an extremely high Index of Relative Importance (IRI) value of 6396.57. Aside from a high IRI value for P. esculenta in January 2022 due to the stocking event, the number of dominant species increased after stock enhancement, leading to more uniform IRI values. Compared with those in October 2021, the abundance and biomass of P. esculenta in October 2022 increased by 10.37% and 17.70%, respectively. However, stock enhancement caused significant changes throughout the entire macrobenthic community, resulting in more pronounced increases in species number, abundance, and biomass, which led to a decrease in the IRI value of P. esculenta from 4413.69 in October 2021 to 2475.37 in October 2022. Crabs are often considered ecosystem engineers (Lee 2008), and an increase in dominant crab species after stock enhancement can effectively promote the decomposition and transformation of mangrove litter, thereby increasing and enriching primary production in mangrove ecosystems (Xu et al. 2010).

After stock enhancement, the abundance and biomass of macrobenthos were generally greater than before enhancement, with the exception of biomass in January 2022. The lower biomass in January 2022 can be attributed to seasonal factors that limited the survival of warm-water species (Zhou et al. 2016). Despite seasonal constraints, abundance was greater in January 2022 than in October 2021, because many P. esculenta survived after stock enhancement. Notably, the emergence and subsequent dominance of S. sinensis and P. laevis in Section T2 led to the particularly high abundance observed in April 2022. These species were only abundant in Section T2 and less prevalent in other sections, possibly due to their cultivation and use as pond bait (Leng et al. 2013). by local fishermen Secondary productivity is a key indicator for assessing the state of ecosystems (Asmus 1987; Tumbiolo and Downing 1994), and an increase in secondary productivity may enhance the resistance of the macrobenthic community to organic pollution stress (Du et al. 2024). Biomass is the most significant factor influencing changes in secondary productivity, and the trends in secondary productivity and biomass are often closely aligned (Tumbiolo and Downing 1994), as observed in this study. After stock enhancement, the secondary productivity of the macrobenthic community was generally greater than before, except in January 2022.

In terms of community differences, based on the results of CLUSTER and NMDS analyses, the macrobenthic communities before stock enhancement were grouped separately at a 46% similarity level, whereas those after stock enhancement were clustered together. The difference in macrobenthic community structure before and after stock enhancement was not significant (P > 0.05), indicating that stock enhancement increased the similarity of macrobenthic communities but did not fundamentally alter the community structure. The primary contributor to the average dissimilarity in the macrobenthic community before and after stock enhancement was P. latericea. Phascolosoma esculenta, a detritivore (D), prefers to inhabit muddy or muddy-sandy mangrove areas in the mid-to-high tide zone. P. latericea is distributed mainly in the surface mud layer and is an omnivorous (O) predator (Wang et al. 2024). Omnivores primarily feed on plant litter, carrion, or small bivalves or absorb organic matter from the water through their skin or gill epithelia (Meng et al. 2023). Stock enhancement introduced many P. esculenta strains into the mangrove areas. Some P. esculenta die due to adaptability, environmental factors, and ecological carrying capacity, producing large amounts of organic matter and carrion that omnivores, such as P. latericea, can utilize. However, both omnivores and detritivores are preyed upon by carnivores (Ca) (Ge et al. 2008). The increase in P. esculenta reduced the number of P. latericea individuals preyed upon by carnivores. These factors collectively made P. latericea the main contributor to the differences in the macrobenthic community.

The MPI is based on the ABC curve. According to the MPI results, the benthic ecological quality initially declined then increased. In April 2022, the benthic ecological quality reached its lowest point and was categorized as "moderate." During this period, the emergence of numerous small individuals of S. sinensis and P. laevis, which are used as bait, caused the abundance curve to rise above the biomass curve and partially cross it. Human disturbance, the primary factor contributing to moderate pollution, negatively impacted the macrobenthic community structure (Peng et al. 2011). During the survey and sampling period of this study, fishermen were observed harvesting only the large individuals of Phascolosoma esculenta from the tidal flats. The average abundance of Phascolosoma esculenta increased from 30.13 ind./m² in October 2021 to 31.29 ind./m² in October 2022, while the average biomass decreased from 5.17 g/m² to 5.04 g/m², which reflects the impacts of the fishermen’s harvest. Therefore, post-stock enhancement management measures are crucial. According to the MPI results, the difference in benthic ecological quality between October 2021 and October 2022 was minimal, with October 2022 showing slight improvement compared with October 2021. This result is consistent with the M-AMBI findings, indicating that stock enhancement improved benthic ecological quality despite anthropogenic disturbances (Du et al. 2024; Yang et al. 2024).

4.3 Applicability of MPI

Due to the unique application scenarios and the specific applicability of benthic indices, different indices may yield varying conclusions for the same area (Brauko et al. 2016; Gao et al. 2023; Song et al. 2023). In this study, the MPI, which was previously used in the mangrove areas of Yueqing Bay (Long et al. 2008), was selected for evaluation. There are two main reasons for this choice: first, it facilitates the comparison of changes in benthic ecological quality; second, it allows for exploring the applicability of this index in the mangrove areas of Yueqing Bay, thus enriching macrobenthic monitoring techniques. The average MPI value in this study was − 12.79, indicating a high level of benthic ecological quality and a clear improvement over the period from 2004 to 2006 (Long et al. 2008). The M-AMBI was shown to be applicable to the mangrove areas of Yueqing Bay (Yang et al. 2024). The variation curves of the MPI and M-AMBI were generally similar. Both indices identified human disturbances in April 2022 and a slight improvement in benthic ecological quality, suggesting that the MPI results have high reference value.

The MPI has several limitations. It has a relatively late start and a limited dataset; at times, biological and ecological expertise may be required to refine the results (Long et al. 2008). However, its calculation method is simple and user-friendly. Additionally, compared to the results of the diversity indices and ABC curves, the MPI provides more accurate evaluations (Cai 2003). This method is accessible to nonprofessionals and has great potential for further development, such as dividing benthic ecological quality into five categories and defining specific quality ranges for different substrate types. The M-AMBI remains the preferred option for evaluating the mangrove areas of Yueqing Bay. Other benthic indices, such as the MPI, can serve as supplementary references. By considering the evaluation results from multiple indices and analyzing environmental factors, a more objective assessment can be achieved.

Author Contribution

Chen Song: Methodology, Formal analysis, Writing – original draft. Xinyuan Ding: Methodology, Writing – review & editing. Zhou Meng: Writing – review & editing. Xiaobo Wang: Investigation, Conceptualization, Methodology, Resources, Writing – review & editingQingxi Han: Funding acquisition.

Acknowledgments

This research is supported by the National Natural Science Foundation of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Short-term responses of the macrobenthic community to stock enhancement in the mangrove areas of Yueqing Bay, East China Sea

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Abstract

Figures

1. Introduction

2. Materials and methods

2.1 Stock Enhancement Implement

2.2 Data Collection

2.3 Index of Relative Importance (IRI)

2.4 Community Structure Analysis

2.5 Secondary Productivity

2.6 Macrozoobenthos Pollution Index

2.7 Data Processing

3 Results

3.1 Changes in Community Composition

3.2 Changes in Dominant Species

3.3 Changes in Abundance and Biomass

3.4 Analysis of Community Dissimilarities

3.5 Changes in Secondary Productivity

3.5 MPI Results and Consistency with M-AMBI Trends

4 Discussion

4.1 Macrobenthic Community Characteristics

4.2 Short-term responses of the Macrobenthos Community to Stock Enhancement

4.3 Applicability of MPI

Declarations

Author Contribution

Acknowledgments

References

Additional Declarations

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