Evaluation of ecological health of Hainan Island inshore waters in the South China Sea based on preliminary fish biotic integrity index (Actinopterygii and Elasmobranchii)

Abstract

The well-being of marine ecosystems significantly influences biodiversity and ecological equilibrium amidst pressing challenges such as overfishing, water pollution, and climate change. Drawing upon data from two fishery stock surveys conducted in the inshore waters of Hainan Island in 2022, this study undertook a comprehensive evaluation of the marine ecosystem's health status in the region. Employing the Fish Index of Biological Integrity (F-IBI) analysis method, coupled with an examination of the structural and functional aspects of the fish community, our research sheds light on the prevailing conditions. Our study revealed a spatial dichotomy within the fish communities of the study area and delineated them into two distinct groups: the northwestern and southeastern ones, with evident disparities in community structure between the two. By employing indicator screening and calculation, we segmented the fish health index in the inshore waters of Hainan Island into five tiers. Despite discernible anthropogenic influences, the ecological health of these waters remained generally robust. Notably, the mean F-IBI of fall (56.30) significantly exceeded that of spring (48.16) (P < 0.01). Furthermore, regarding spatial distribution, the ecological well-being of the southeastern waters surpassed that of the northwestern and Qionghzhou Strait waters. This study represents a pioneer endeavor to apply ecological health assessment methodologies towards informing resource management and conservation strategies for the inshore fisheries of Hainan Island. By furnishing a scientific foundation, our research contributes to the pursuit of sustainable marine ecological development within this locale.

Headnote

Abstract

The well-being of marine ecosystems significantly influences biodiversity and ecological equilibrium amidst pressing challenges such as overfishing, water pollution, and climate change. Drawing upon data from two fishery stock surveys conducted in the inshore waters of Hainan Island in 2022, this study undertook a comprehensive evaluation of the marine ecosystem's health status in the region. Employing the Fish Index of Biological Integrity (F-IBI) analysis method, coupled with an examination of the structural and functional aspects of the fish community, our research sheds light on the prevailing conditions. Our study revealed a spatial dichotomy within the fish communities of the study area and delineated them into two distinct groups: the northwestern and southeastern ones, with evident disparities in community structure between the two. By employing indicator screening and calculation, we segmented the fish health index in the inshore waters of Hainan Island into five tiers. Despite discernible anthropogenic influences, the ecological health of these waters remained generally robust. Notably, the mean F-IBI of fall (56.30) significantly exceeded that of spring (48.16) (P < 0.01). Furthermore, regarding spatial distribution, the ecological well-being of the southeastern waters surpassed that of the northwestern and Qionghzhou Strait waters. This study represents a pioneer endeavor to apply ecological health assessment methodologies towards informing resource management and conservation strategies for the inshore fisheries of Hainan Island. By furnishing a scientific foundation, our research contributes to the pursuit of sustainable marine ecological development within this locale.

Keywords

ecological health assessment, environmental factors, fish community structure, F-IBI, Hainan Island

(ProQuest: ... denotes formulae omited.)

Introduction

Amid escalating pressures on the global marine environment, the conservation of marine biodiversity and ecosystem health has captured international focus (Palumbi et al. 2009). Marine ecosystems, harboring a significant portion of the planet's biodiversity, arc essential for providing irreplaceable resources, including food, medicinal products, ecological services, and cultural values (Parsons et al. 2014; Canonico et al. 2019). Situated as the second largest island of China, Hainan Island features a unique and intricate marine ecosystem. The island's biodiversity and ecological conditions are critical to maintaining regional and global ecological balance and promoting sustainable development (He et al. 2014; Hu et al. 2018).

Hainan Island's strategic geographic location, abundant marine biological resources, and dynamic marine environment have made the inshore waters a pivotal site for marine scientific research and resource management. Recent challenges such as global climate change (Poloczanska et al. 2013), overfishing (Pauly and Zeller 2016), marine pollution (Jambeck et al. 2015), and habitat degradation (Halpern et al. 2015) have posed significant threats to the biodiversity in these waters, thereby garnering substantial attention from the scientific and regulatory communities. It has been observed that the coastal economic activities of Hainan Island increasingly threaten marine life and their habitats, with biodiversity and living marine resources experiencing various disturbances (Wang et al. 2008; Fu et al. 2018). Addressing the challenge of accurately assessing ecological health remains a critical research priority (Borja et al. 2008).

In response to these challenges, the Index of Biological Integrity (IBI) and the Fish-based Index of Biotic Integrity (F-IBI) have emerged as prominent tools for assessing the health of freshwater and marine ecosystems (Karr 1981; Liao and Huang 2013; Li et al. 2018), and the approach was initially proposed by Karr (1981) and has evolved into one of the most extensively utilized indicators in research on aquatic ecosystem health (Kerans and Karr 1994). The handling and identification of fish are comparatively easier compared to other organisms, as they exhibit higher sensitivity towards environmental stresses. Additionally, being positioned at the top of the food chain enhances the potential application of indicators based on fish communities (Karr 1991). The F-IBI, in particular, offers a comprehensive measure of ecosystem health by amalgamating data on fish community structure, species diversity, and functional groups (Huang et al. 2022). For instance, Abhijna and Kumar (2017) used F-IBI to examine the biological integrity of two Indian lakes, and Veli-Akkulam and Vellayani found that the biological integrity of the lakes far away from the source of pollution was preserved. Conversely, Li et al. (2013) applied the F-IBI to highlight the detrimental effects of dam construction on the fish communities of the Lancang/Mekong River. Hence, the F-IBI provides a robust framework for quantifying ecosystem health and guiding conservation and resource management strategies.

As an integral component of the South China Sea ecosystem, the marine ecological health of inshore Hainan Island waters influences not only local biodiversity and fisheries but also broader stability and sustainability of the regional marine ecosystem. Although extensive research has been conducted on the biodiversity in Hainan's inshore waters, studies focusing on their ecological health arc scant (Sun et al. 2012). This study leverages bottom trawl fishery survey data collected in May and September 2022, while the F-IBI construction method was introduced, and the research objectives are to:

* Delineate the structure and distribution patterns of the fish community.

* Develop an ecological health assessment index tailored for the inshore waters of Hainan Island.

* Evaluate the health status of this study area.

Materials and methods

Study area. The inshore waters of Hainan Island (Fig. 1) arc renowned for their rich biodiversity and distinctive marine ecosystems. This unique geographic setting (17°47'00"-20°12'00"N and 108°21'00"-lll°33'00"E) hosts a diverse array of ecologically significant environments including coral reefs, seagrass meadows, and shoals. Notably, these waters arc also abundant in mangrove ecosystems, particularly around Haikou and Wenchang, providing crucial habitats for a variety of fishes, crustaceans, and birds. Several national nature reserves have been established within this region to conserve the marine biodiversity. These include the Coral Reef National Reserve, Tongguling National Reserve, the Dongzhaigang National Nature Reserve in Sanya, and the Boundary Island National Marine Park in Lingshui. These reserves play a pivotal role in conserving coral reef ecosystems and serve as invaluable natural laboratories for scientific research. Furthermore, the unique currents and rich plankton communities present in the waters around Hainan Island are central to the studies on geographic distribution of marine organisms, marine ecological dynamics, and primary productivity (Liu 2013; Li et al. 2014).

Data sources. In the spring (May) and fall (September) of 2022, we conducted two surveys on marine ecology and fishery resources in the inshore waters of Hainan Island. In this study, our surveys employed an otter trawler Guibeiyu 69068 with main engine power of 436 kW. The headrope length of the trawl net measured 37.7 m and the codend mesh was 20 cm. Considering the variations in the surrounding environment of Hainan Island, we established a total of 50 survey stations encompassing the shallow region with a depth of 200 meters (Liu 2013; Li et al. 2014). This area is characterized by high fishing activity around Hainan Island, thus enabling a more comprehensive survey and analysis to reasonably evaluate the ecological health status of this region. For each survey, at each station one trawl was conducted lasting one hour at a steady speed of around 3 knots. All the trawl samplings were conducted during daytime.

For the sorting of the captured fishes, we referred to the most recent ichthyological literature (Shen and Wu 2011; Chen 2014; Chen and Zhang 2015; Wu and Zhong 2021) while the taxonomic status of species was verified using Fricke et al (2024) and WoRMS Editorial Board (2024). Fish samples from each station were sorted, weighed, counted, and biologically measured on-site, with weight measurements recorded to the nearest 0.1 g. Samples that could not be identified to species level onboard were cryopreserved for further identification in the laboratory.

F-IBI reference point selection. Currently, there is no uniform international standard for selecting reference points in marine studies, which are generally categorized into two types: those that utilize historical data as the baseline (Li et al. 2018), and those that choose areas either untouched or minimally impacted by human activities (Das et al. 2013) as the baseline. However, the inshore waters of Hainan Island present challenges in this regard due to the absence of comprehensive historical data and the lack of areas completely free from human disturbance (Stoddard et al. 2006). Consequently, for this study, five survey stations (SI6, SI9, S32, S45, and S50) were selected as reference sites for this study. These stations represent well-preserved marine habitats that are minimally disturbed by human activities. They are primarily situated in the sea area adjacent to the national nature reserve or in natural sea areas distanced from human influences.

Screening of F-IBI candidate indicators. In this study, we selected a total of 25 candidate indicators sensitive to ecological disturbances, such as species composition and abundance, trophic guild, thermal tolerance, reproductive guild, and habitat preference (Li et al. 2013; Li et al. 2018; Karr 1981) (Table 1). The selection process involved several screening steps: (1) Distribution range screening (Barbour et al. 1996): indicators were excluded if the number of species was fewer than 10 across all survey stations, if the variation in proportions across all stations was less than 10%, or if more than 90% of the indicator values at all stations were zero. (2) Discriminative ability screening (Zhu et al. 2021): indicators were removed if the medians for reference and observation sites fell within the 25th to 75th percentile range of each other. (3) Calculation of correlation coefficients (Zhang et al. 2020): the remaining indicators underwent correlation analysis, and any with a correlation coefficient (|R|) less than 0.9 were retained (|R| < 0.9); otherwise, the more informative of the correlated indicators was selected. (In Suppl. material 1, we have added specific data and detailed calculations and results for the ten indicators retained.)

F-IBI calculations. Among the standardization methods for IBI system evaluation, the ratio method is the most accurate and effective method (Wang et al. 2005), so the ratio method was used in this study. The standardization of each indicator was divided into two methods (Zhao et al. 2019):

The index of decreasing value as interference increases and its standardized index mode are as follows

...

where: P and O are the standardized index and raw value of the zth indicator at the /h survey site, respectively, and S9 is the standardized threshold for the zlh indicator, taking the raw value of the zlh indicator at the 95th percentile of all survey sites.

The index of increasing value as interference increases and its standardized index mode are as follows

...

where: maxO_j is the maximum value of the ith indicator j across all survey sites, and Sⁱ⁵ is the standardized threshold for the zth indicator, taken as the raw value of the 5th percentile of the ith indicator across all survey sites.

The F-IBI value for each survey site is the mean of the standardized indices of each parameter at that site

...

Where: IBI_j is the F-IBI value of the jth survey site and m is the number of indicators after screening.

The 25% quartile of the F-IBI score at the reference points was classified as a health criterion, and F-IBI values above this criterion were evaluated as healthy. F-IBI values below this criterion were categorized into four intervals from high to low, representing good, fair, poor and bad ecosystem health, respectively.

Data analysis-Index of Relative Importance (IRI). The ecological dominance of fish communities during different seasons was evaluated using the index of relative importance (IRI), calculated using three components (Pinkas et al. 1971; Martin et al. 1996).

...

where 7V% is the percentage of individuals of a specific fish species in relation to the total catch, W% is the percentage of the total weight that a particular fish species contributes to the overall catch weight, and F% is the frequency of occurrences of that species across all sampling stations. Based on the IRI, species classifications are as follows: species with an IRI value of 1000 or more are deemed dominant; those with IRI values ranging from 100 to 1000 are considered important; species with IRI values between 10 and 100 are categorized as common; and species with IRI values less than 10 are classified as rare.

Data analysis-calculation of diversity indices. The Shannon-Wiener diversity index (77) was used in this study to calculate community species diversity based on biomass density (Li and Chen 2008). The improved formula proposed by Wilhm (1970) was employed for the calculation, which is defined as follows

...

Margalef species richness index (D)

...

where S represents the total number of fish species captured in the study area, P. denotes the weight percentage of the ith fish species, and TV represents the total number of individuals of captured fishes.

Similarity analysis of community structure. We determined potential spatial clustering of fish community structure using cluster rank clustering, which is based on the group-averagcd connectivity of the Bray-Curtis similarity matrix. Prior to calculation, fish abundance data were square root transformed (Clarke 1993). To evaluate the significance of changes in community structure between groups, we utilized an Analysis of Similarity (ANOSIM) method, focusing on fish species composition and relative abundance (Clarke 1993). Non-metric Multidimensional Scaling (NMDS) was subsequently applied to validate the clustering accuracy and characterize the fish composition in the inshore waters of Hainan Island. The effectiveness of NMDS was gauged using a stress coefficient, with values under 0.05 indicating a well-represented two-dimensional dot plot, values between 0.05 and 0.10 suggesting generally credible results, and values between 0.10 and 0.20 offering some interpretative significance (Clarke and Ainsworth 1993).

Results

Fish species composition. In the spring and fall surveys, we captured a total of 363 fish species from 24 orders, 114 families, and 226 genera (Suppl. material 2), of which 347 were ray-finned fishes (Actinopterygii) spanning 18 orders, 105 families, and 217 genera, representing 95.59% of the total number of species. The most prevalent order was Perciformes, represented by 181 species from 56 families and 107 genera, comprising 49.86% of the total number of species, and including nine Gobiidae species (2.48%). The next most common order was Scorpaeniformes (10.74%), with 39 species across 8 families and 31 genera, followed by Pleuronectiformes (9.37%), with 34 species in 7 families and 19 genera, and Anguilliformcs (6.06%), with 22 species in 8 families and 13 genera. Species from other orders constituted < 5% of the total. Additionally, we recorded 15 species of elasmobranchs (Elasmobranchii) (4.13%) from 5 orders, 8 families, and 8 genera. Notably, Myliobatiformes had the highest species count (5 species), while Orectolobiformes only 1 species. In addition to numerous ray-finned fished and elasmobranchs, we collected also a single species representing Cyclostomata (Fig. 2). The most frequently occurring species were: Acropoma japonicum Günther, 1859, Decapterus maruadsi (Temminck ct Schlegel, 1843), Saurida tumbil (Bloch, 1795), Saurida undosquamis (Richardson, 1848), Champsodon atridorsalis Ochiai ct Nakamura, 1964, and Photopectoralis bindus (Valenciennes 1835), appearing in > 60% of the survey sites (Table 2).

Based on dietary preferences, the survey identified 48 piscivorous species (13.22% of the total), 2 generalist species (0.55%), 142 omnivorous species (39.12%), 33 zooplanktivorous species (9.09%), and 138 benthic-animal-feeding species (38.02%). Thermally, 335 species (92.29%) are warm-temperate, 25 species (6.89%) are warm-water, and 3 species (0.83%) are cold-temperate species. Regarding reproductive types, 323 species (88.98%) lay floating eggs, 13 species (3.58%) lay attached eggs, 7 species (1.93%) lay adhesive sinking eggs, 5 species (1.38%) lay adhesive floating eggs, and 15 species (4.13%) are ovoviviparous. Ecologically, 244 species (67.22%) are demersal or near-demersal, 61 species (16.80%) are pelagics, and 58 species (15.98%) are reef-associated (Suppl. material 2).

Spatial patterns of fish communities. Hierarchical cluster analysis (CA), using group-averaged connectivity and based on the Bray-Curtis similarity matrix, spatially classifies all survey sites into two groups in both seasons (Fig. 3). In the spring season, group I is primarily located in the northwestern waters in the Beibu Gulf and Qiongzhou Strait. This region features dense human population, heavy marine traffic, and significant anthropogenic interferences. Conversely, group II is distributed in the southeastern waters and characterized by open-sea environment, several protected areas, an intact natural landscape, and less anthropogenic interferences. Dominant fish species in the spring season include Acropoma japonicum, Decapterus maruadsi, and Trachurus japonicus (Temminck et Schlegel, 1844) (Table 2). NMDS plots indicate significant differences between the two groups with only partial overlap. The NMDS plots are consistent with CA, confirming the meaningfulness of the classifications. ANOSIM confirms highly significant differences in fish community structure between the two clusters (R = 0.527, P < 0.01). In the fall season, the clustering remains unchanged in spatial distribution as compared to that of the spring season. Featuring dominant species include Photopectoralis bindus, Saurida tumbil, and Johnius belangerii (Cuvier, 1830) (Table 2). NMDS plots indicate that the stress was < 0.2, suggesting some explanatory significance. ANOSIM also shows a highly significant difference (R = 0.72, P< Q.01) in the structure of fish community between the two groups.

Selection of core indicators and establishment of F-IBI. The 25 candidate indicators presented in Table 1 underwent an initial distributional range test, resulting in the exclusion of candidates M4, M9, Mil, Ml5, Ml 7M20, and M25 due to nonapplicability. The remaining 16 indicators were assessed for discriminating ability using the box-and-line plot method. It was determined that the medians of six indicators-Ml, M5, MIO, M13, Ml4, and Ml6-fell within the 25th to 75th percentile range of the opposing side (Fig. 4). Subsequently, Pearson analysis was conducted to refine the selection, identifying М2, М3, M6, M7, M8, M12, and M21-M24 as core indicators for constructing the Fish-based Index of Biotic Integrity (F-IBI), as detailed in Fig. 5. These core indicators were standardized as shown in Table 1, and F-IBI values were calculated for each station in each season (Fig. 6). The health assessment system's grading criteria for the inshore waters of Hainan Island, as outlined in Table 3, categorizes the ecological status as follows: F-IBI > 68.58 indicates "healthy"; 51.44 < F-IBI < 68.58 signifies "good"; 34.29 < F-IBI < 51.44 denotes "fair"; 17.15 < F-IBI < 34.29 reflects "poor"; and F-IBI <17.15 represents "bad".

Patterns of ecological health. The F-IBI assessments indicated that the majority of sampled sites were in "good" or "fair" health in both seasons (Suppl. material 3, Fig. 6). Seasonal variations were also observed, with F-IBI values ranging from 25.50 to 62.89 in spring and from 41.01 to 70.06 in fall, and the corresponding mean values were 48.16 ± 8.99 and 56.30 ± 7.77, respectively. The ecological health of Hainan Island's inshore waters showed improvement in fall as compared to spring. A one-way analysis of variance (ANOVA) confirmed a highly significant difference between the two seasons (F = 23.498, P < 0.01). Spatially, no site exhibited extremely poor health in either season, with the highest F-IBI scores recorded at station S45 in spring and at station S16 in fall. Overall, sites in the southeastern waters showed better ecological health than those in the northwestern and Qiongzhou Strait waters.

Discussion

Analysis of fish community structure. Fish community structure is a critical aspect in marine ecological study, indicating biodiversity, ecosystem health, and the impact of environmental changes (Bellwood et al. 2004). The diversity of fish species is one of the important indicators of ecosystem health (Lorcau et al. 2001; Cardinale et al. 2012). In China, where Hainan Island serves as a significant fishery base, analyzing the fish community structure in its inshore waters is vital for guiding management and conservation efforts. This study highlights a high proportion of bony fishes and the dominance of Perciformcs, indicating robust species diversity and good ecosystem health (Figs 3, 6, Table 2), aligning with findings by Magurran (2013) and Worm et al. (2006) on the relationship between biodiversity and ecosystem stability. Moreover, the spatial distribution patterns of fish communities are shaped by various environmental factors, including water temperature, salinity, pollution, and habitat destruction (Jackson et al. 2001; Heino et al. 2009), with human activities such as overfishing, marine pollution, and habitat degradation posing direct threats to fish diversity and distribution (Pauly et al. 1998; Worm et al. 2006).

Hierarchical clustering and NMDS suggest that differences in spatial distribution of fishes are related to variations in circulation patterns, fishing intensity, and habitat types. Fish communities in spring and fall primarily clustered into two regions-northwest and southeast waters-reflecting significant ecological differences. The northwest waters in the Beibu Gulf and Qiongzhou Strait experience substantial anthropogenic impact from fishing activities and marine traffic, creating a complex and disturbed environment. Conversely, the southeast waters are characterized by more protected zones and lesser human disturbance and maintain a more natural and intact ecological state. Differences in seafloor topography also influence community clustering, with shallow shoals and deep troughs in the northwest and marginal ditches and canyons in the southeast featuring complex terrain and varying slopes (Lin 1995; Zhao et al. 2007). Additionally, both regions support high plankton biomass and distribution of the food resources plays a crucial role in attracting fish aggregations (Xie et al. 2019). In summary, differences in fish community composition are influenced by a multitude of factors, however, the underlying mechanisms through which each factor exerts its influence necessitate comprehensive exploration using more extensive biological and environmental data.

F-IBI system construction. This study introduces the F-IBI system and modifies it to assess the ecological health of the specific marine environment inshore waters around the Hainan Island. Unlike its applications in rivers and lakes (Angermeier and Schlosser 1987; Aparicio et al. 2011), our study has shown that indices based on fish thermotolerance and habitat preference are useful for classifying biological integrity of the regions fish community.

The study aims to develop an F-IBI index system tailored to the specific conditions off Hainan Island, with a particular focus on commercial demersal fish species, which are crucial due to the increased fishing pressure and the significance to local fisheries. Fish belonging to different taxa exhibit distinct responses to fishing pressure and environmental changes, thereby rendering these indicators dynamic throughout various epochs. The vastness and ecological complexity of Hainan's maritime area necessitate a flexible and adaptive approach to indicator selection and modification. For instance, certain indicators, such as trophic guild, thermal tolerance, are influenced by interannual variability or extreme climate conditions (Brandl et al. 2020; Harri et al. 2022), impacting the reliability of the indicators. Additionally, biogeographic variations may cause divergent life histories and strategies among the same fish species across different marine areas (Cowman et al. 2017), necessitating careful consideration and adjustment of indicators based on empirical data. Therefore, constructing an F-IBI index system is an iterative process, requiring ongoing revisions based on real-world conditions and scientific advances. This continuous improvement ensures the scientific accuracy and reliability of the system, thereby providing a more effective approach for evaluating and managing the marine ecosystem health surrounding Hainan Island.

Evaluation of local ecosystem health. The F-IBI system primarily assesses ecosystem health based on the structure and function of fish communities. However, to evaluate ecosystem health more comprehensively, it is also necessary to integrate indicators of human impacts on the marine environment. In this study, seasonal variations were evident, with mean F-IBI scores of 48.16 in spring and 56.30 in fall, indicating an improvement in ecological health during the latter season compared with previous studies (Su et al. 2022). Research has demonstrated a correlation between F-IBI scores and the intensity of anthropogenic impacts; higher human interference generally results in lower F-IBI scores (Liu et al. 2016). The waters surrounding Hainan Island are closed to fishing activities from May to August, and the survey for the fall expedition was conducted in early September. Following a few months of fishing moratorium, the offshore waters experience reduced fishing pressure, leading to resource recovery. Consequently, both the resource status and ecological environment are expected to reach an improved state during this season. Therefore, it is anticipated that the index in fall may surpass that observed in spring. Other factors influencing F-IBI scores include physical and chemical conditions of the marine environment, such as water temperature, salinity, and oxygen levels (Lou et al. 2015). For instance, affected by industrial waste discharges, the waters surrounding the western portion of Hainan Island and the Qiongzhou Strait exhibit adverse physical and chemical environments. These conditions have the potential to detrimentally impact marine ecosystems, consequently resulting in lower F-IBI scores (Li et al. 2017), negatively impacting the marine ecosystem and thus reducing F-IBI scores. In the northwest waters of Hainan Island, where F-IBI scores were adversely affected by nearby coastal development activities such as tourism and port construction, which restrict the available space and resources for marine life (Cen et al. 2012; Sun et al. 2014). Furthermore, severe coral bleaching, especially in the western waters, has drastically affected fish habitats and breeding grounds, diminishing species diversity and lowering F-IBI scores (Lang 2023). In contrast, sites near national nature reserves (e.g., SI6, S36, S47) exhibited higher F-IBI scores due to less human disturbance and more intact and diverse habitats.

Conclusions

This study found that bony fishes constituted the majority of the catch, with Perciformcs being the predominant order. The analysis categorized the fishes according to their dietary preferences, thermal tolerances, reproductive strategics, and ecological behaviors, which illustrated the varied distribution of fish across the surveyed area. Hierarchical cluster analysis and NMDS further segregated the survey sites into two distinct groups, underscoring spatial variations. The F-IBI assessments indicated that most sites exhibited good or fair ecological health in both seasons, with noticeable improvements in fall. Notably, the ecological health of the fish community was superior in the southeastern part of the study area to the northwestern sectors. This study presents a comprehensive scientific evaluation of the fishery resources and ecological well-being in the nearshore waters surrounding Hainan Island, offering essential insights for future fishery development planning and ecosystem management strategies within the region.

Acknowledgments

This study was supported by the Science and Technology Fundamental Resources Investigation Program (Grant No. 2023FY100803), the Central Public-interest Scientific Institution Basal Research Fund, CAPS (NO.2023TD93), Biodiversity, Germplasm Resources Bank and Information Database Construction of the South China Sea Project (NO. HNDW2020-112), the Hainan Provincial Natural Science Foundation of China under contract No. 324QN367, and Guangzhou Basic and Applied Basic Research Project (2023A04J1511).

Sidebar

Corresponding author: Dianrong Sun ([email protected])

Academic editor: Sanja Matić-Skoko · Received 1 July 2024 · Accepted 6 September 2024 · Published 14 October 2024

Citation: Yu P, Luo Z, Wang L, Liu Y, Huang Y, Shan B, Yang C, Sun D (2024) Evaluation of ecological health of Hainan Island inshore waters in the South China Sea based on preliminary fish biotic integrity index (Actinopterygii and Elasmobranchii). Acta Ichthyologica et Piscatoria 54: 221-233. https://doi.org/10.3897/aiep.54.130966

Supplementary material 1

Fish species ecological habits catalog in the nearshore waters of Hainan Island

Authors: Peimin Yu, Zhengli Luo, Liangming Wang, Van Liu, Yingbang Huang, Binbin Shan, Changping Yang, Dianrong Sun

Data type: docx

Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons. org/licenses/odbl/1.0). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited.

Link: https ://doi. org/10.3 897/aicp. 54.130966. suppl 1

Supplementary material 2

Health assessment results of the coastal waters of Hainan Island based on Fish Biological Integrity Index

Authors: Peimin Yu, Zhengli Luo, Liangming Wang, Yan Liu, Yingbang Huang, Binbin Shan, Changping Yang, Dianrong Sun

Data type: docx

Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons. org/licenses/odbl/1.0). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited.

Link: https://doi.org/10.3897/aiep.54.130966.suppl2

Supplementary material 3

Seasonal variations

Authors: Peimin Yu, Zhengli Luo, Liangming Wang, Yan Liu, Yingbang Huang, Binbin Shan, Changping Yang, Dianrong Sun

Data type: xlsx

Copyright notice: This dataset is made available under the Open Database License (http://opendatacommons. org/licenses/odbl/1.0). The Open Database License (ODbL) is a license agreement intended to allow users to freely share, modify, and use this Dataset while maintaining this same freedom for others, provided that the original source and author(s) are credited.

Link: https ://doi. org/10.3 897/aiep .54.130966. suppl3

Footnote

* These authors contributed equally to this work.

References

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