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Catch organism assemblages along artificial reefs area and adjacent waters in Haizhou Bay
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Shike Gao1, Bin Xie3, Chengyu Huang1, Xiao Zhang1, Shuo Zhang1, 4, *, Wenwen Yu2
Acta Oceanologica Sinica | 2024, 43(2) : 34 - 42
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Acta Oceanologica Sinica | 2024, 43(2): 34-42
• Marine Chemistry •
Catch organism assemblages along artificial reefs area and adjacent waters in Haizhou Bay
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Shike Gao1, Bin Xie3, Chengyu Huang1, Xiao Zhang1, Shuo Zhang1, 4, *, Wenwen Yu2
Affiliations
  • 1 College of Marine Living Resource Sciences and Management, Shanghai Ocean University, Shanghai 201306, China
  • 2 Jiangsu Research Institute of Marine Fisheries, Nantong 226007, China
  • 3 Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, 361005, China
  • 4 Joint Laboratory for Monitoring and Conservation of Aquatic Living Resources In the Yangtze Estuary, Shanghai 200000, China
Published: 2024-02-25 doi: 10.1007/s13131-023-2226-2
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To better understand the community patterns mediated by connectivity in artificial reefs of coastal areas, it is necessary to understand the distribution and coexistence of organisms with artificial reefs area and adjacent waters. This study was conducted to examine main catches assemblages collected by trawls in Haizhou Bay, which included five habitats: the artificial reef area (AR), aquaculture area (AA), natural area (NA), estuary area (EA) and comprehensive effect area (CEA). The result shows that the total abundances of species in the five habitats were highly different (univariate PERMANOVA: P = 0.001, n = 24), but some species were also unique in their habitat (e.g. Scapharca subcrenata and Glossaulax didyma in AA). The body size distribution of specific species between habitats are different. For Collichthys lucidus, their body size in AR (14.63 cm ± 1.64 cm) and EA (14.3 cm ± 0.85 cm) is higher than that in NA (10.65 cm ± 1.64 cm), CEA (11.28 cm ± 1.85 cm) and AA (12.1 cm ± 0.43 cm), which indicates the potential connection from AR to EA mediated by their adult population. We concluded that artificial reefs in AR can be considered key components that have the ability to support species assemblages in adjacent habitats. This study has implications for the conservation and monitoring of species assemblages in coastal areas in terms of that artificial reefs can be applied in different stages of habitat protection implementation and in different combinations of scenarios.

assemblage  /  artificial reefs  /  adjacent water  /  Haizhou Bay
Shike Gao, Bin Xie, Chengyu Huang, Xiao Zhang, Shuo Zhang, Wenwen Yu. Catch organism assemblages along artificial reefs area and adjacent waters in Haizhou Bay[J]. Acta Oceanologica Sinica, 2024 , 43 (2) : 34 -42 . DOI: 10.1007/s13131-023-2226-2
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1 Introduction
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The global trends of continuous processes associated with human activities and coastal development, such as overfishing, habitat destruction and marine environmental pollution, have led to general degradation of the entire coastal ecosystem, which has imposed tremendous pressure on estuaries, harbors, gulfs and nearshore regions (Walker and Schlacher, 2014; Dance and Rooker, 2015; Reis-Filho et al., 2019). Over the years, many artificial reefs have been constructed as human–made structures to increase environmental quality and species abundance in marine ecosystems for coastal ecological restoration (Seaman and Sprague, 1991; Ammar, 2009; Mclean et al., 2015; Komyakova et al., 2019) by creating suitable habitats and places for many marine organisms to grow, reproduce, forage and hide (Sherman et al., 2002). At present, ecological principles combining the planning, design and operation of artificial reefs have been extensively investigated in many coastal areas (Whitmarsh et al., 2008; Walker and Schlacher, 2014; Tessier et al., 2015; Folpp et al., 2020). Given that artificial reefs aim to retard marine habitat degradation, protect endangered species and restore biodiversity, artificial reefs are regarded as conservation and enhancement tools for marine environments and habitat recovery (Dafforn et al., 2015; Becker et al., 2017).
Haizhou Bay, which is located in Lianyungang City, Jiangsu Province, is one of the important fishing grounds in the Yellow Sea. Because of numerous human activities (e.g. overfishing, port construction and waterway transportation), since the 1980s, the habitat environment and fishery resources in Haizhou Bay have been vastly and adversely affected, suffering habitat fragmentation and destruction of the ecosystem structure (Zhang et al., 2006; Zhang et al., 2013). Since 2002, the local government has begun to build marine protected areas (MPAs) dominated by artificial reefs for ecological restoration and resource conservation in Haizhou Bay (Zhang et al., 2006). The construction of artificial reefs affects aquatic biodiversity and food web ecology by affecting the flow of water, sediments and organisms (Clark and Edwards, 1999; Sherman et al., 2002). These processes in turn affect the community structures and ecological patterns in adjacent waters (Keller et al., 2017; Reeds et al., 2018). However, the impacts of artificial reefs on marine ecosystems and communities in adjacent waters, as well as the ontogenetic shifts and utilization patterns of reef species, are largely unknown, especially in temperate seas. To support the sustainable socioeconomic development of MPAs, as well as the ecosystem approaches in fishery management and spatial planning in coastal areas (Olds et al., 2016; Liao et al., 2017), it is necessary to thoroughly explore the biodiversity in artificial reefs and adjacent waters.
In this study, we used a multi–habitat approach, focusing on species–habitat associations in five habitats along artificial reefs and adjacent waters in Haizhou Bay. We aimed to (1) compare and analyze species abundance in artificial reefs and adjacent waters to determine whether there are spatial differences in assemblages between habitats, and (2) identify single species based on their body sizes to determine whether there is potential connection between habitats. Our research helps provide a more scientific basis and better improve specific planning for improving the strategy, fishery management and construction of MPA networks in temperate coastal habitats in China.
2 Material and methods
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2.1 Study area
Haizhou Bay, which is located in the westernmost part of the Southern Yellow Sea, is mainly composed of sandy and muddy habitats and is an open bay with an area of approximately 877 km2 (Xie et al., 2007). The climate and hydrology of Haizhou Bay are greatly influenced by the mainland, and most fishing areas are controlled by coastal currents (Luo and Li, 2009). The tidal in this region is mainly rotating flow, with a velocity of 0.4–0.65 m/s and a direction from northeast to southwest, and the tidal range is between 2.69–5.05 m (Xie et al., 2007).
2.2 Definition of habitat types
The site design refers to the satellite image and current direction. According to the available geographical coordinate data sets in the study area (34°49.20'–34°55.00'N, 119°16.167'–119°59.50'E) and the direction of Yellow Sea Warm Current (YSWC) and Yellow Sea Coastal Current (YSCC) described in Fig. 1 (Sun et al., 2003; Zhang et al., 2017), five major investigation areas with 24 sampling sites ranging from the Linhong Estuary to the artificial reef area were set. In the real sea area, there are clear dividing area between habtiats (e.g. AA/AR and EA/AA). NA and CEA can also be clearly divided according to the current direction (northeast to southwest). The brief description of each habitat were listed in Table 1.
2.3 Sample collection
The environmental and fishery resource surveys presented in this study were conducted in the coastal waters of Haizhou Bay in October 2020, corresponding to autumn in the study area, when the fishery resources were at their best (Sun et al., 2010; Su et al., 2015). Environmental data were recorded by a conductivity, temperature, and depth (CTD) measuring system, and fish and invertebrate were sampled by a single ship with a wing single capsule bottom trawl (15 m × 4 m × 8 m, mesh size: 1cm × 1 cm) at each site. The fishery investigation was conducted for approximately 30 mins at each site, and the speed of the ship was 2.4 kn to maintain a relatively consistent distance of each tow as much as possible. A large number of reefs were commonly present at the bottom of AR and in culture nets and cages in AA, and we could only sample around these habitats. To obtain the specific pelagic species in the center of AR and AA, the gill nets (30 m × 1.5 m, mesh size: 2.5 cm × 2.5 cm) were used in these habitats under a depth of 2 m for 2 days, which was fixed by the ship dropping anchor at the fore and after target sites. The gill nets were also used in other habitats with same condition for sampling balance. After a rough identification for fishes, crabs, shrimps or other taxa, the samples were packed into 100 cm × 150 cm PVC bags with fresh ice for preservation. The collection, treatment and analysis of samples were in accordance with the relevant provisions of the Specifications for Oceanographic Survey-Part 6: Marine Biological Survey (GB/T 12763.6–2007). The basic biological indicators (weight and length) and numbers of all samples were recorded at the onshore laboratory (the total length of each sample was measured accurate to 0.1 cm). All species were identified to the lowest possible classification level (http://www.fishbase.org).
2.4 Species community analysis in different habitats
The species abundance in each habitat was calculated to evaluate the relationship between the use of different habitat types and species size. All species were identified at the species level, and the species numbers were counted.
2.4.1 Community difference and similarity
The distribution of species abundance among different habitats was calculated using the habitat as a fixed factor. The differences in species abundance between habitats were analysed by permutational univariate analysis of variance (PERMANOVA) based on a Bray–Curtis distance, and post hoc pairwise comparisons were evaluated using the PERMANOVA t statistic, with a P ≤ 0.05 significance level. Then nonmetric multidimensional scale analysis (NMDS) was used for visualization, with the data of species abundance in five habitats. To assess the similarity of species abundance among habitats, a heatmap was produced by clustering the samples on the x–axis with Bray–Curtis similarity (based on Whittaker′s index of association: Clarke and Gorley, 2015) on the y–axis.
2.4.2 Species–habitat associations based on sizes
The three fishes with the highest abundance (Amblychaeturichthys hexanema (n = 84), Chaeturichthys stigmatias (n = 55), and Collichthys lucidus (n = 120) and the top three most abundant shrimp and crabs (Oratosquilla oratoria (n = 143), Trachypenaeus curvirostris (n = 65), and Portunus trituberculatus (n = 141)) were selected to verify species–habitat associations based on their body sizes. Boxplots were produced using body size frequency data from each habitat type, and a generalized linear model (GLM) was used to test the differences of body size between habitats.
2.5 Tool for data analyses
The survey map were made in ArcGIS (v. 10.3). The PERMANOVA and PERMDISP analyses, as well as the visualization of NMDS and clustring heatmap were performed in R software (v. 4.0.3), using the R package “vegan”, and GLM were performed using the R package “mgcv” (Anderson–Cook, 2007).
3 Results
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3.1 Species community characteristics
A total of 10 234 individuals were collected from five habitats, including 68 species belonging to 42 families (Table S1). In total, 2867 individuals belonging to 21 families and 35 species were collected in AR, 3213 individuals from 29 families and 39 species were collected in AA, and 2664 individuals belonging to 22 families and 39 species were collected in CEA. In contrast, fewer species were found in EA (1263 individuals belonging to 13 species in 8 families) and NA (227 individuals belonging to 20 species in 15 families) (Fig. 2).
The predominant family in AR was Gobiidae (4 species, 12.1%, represented by C. stigmatis), followed by Penaeidae (5 species, 15.1%, represented by T. curvirostris). The most dominant family in AA was Clupeidae (2 species, 5.1%), represented by the species Sardinella zunas. The families in NA were mainly composed of Gobiidae (2 species, 10%), Portunidae (1 specy, 5%) and Penaeidae (2 species, 15%), and those in EA were composed of Portunidae (2 species, 16.7%), P. trituberculatus and Charybdis japonica. The dominant family in CEA was Penaeidae (1 specy, 2.6%). In terms of the number of individuals, Gobiidae was the dominant family of AR, accounting for 26.6% of all species, followed by Penaeidae, which accounted for 21.8% of all species. Clupeidae was the main family in AA, accounting for approximately 41.6%, and Gobiidae was the main family in NA, accounting for 25.6%. The most dominant family in EA was Portunidae, accounting for 77.6%. Oratosquilla oratoria of Squillidae was the dominant species in CEA, accounting for approximately 30% (Fig. 3).
3.2 Species assemblages and utilization of different habitats
Nearly all species were widely distributed in the five habitats, with the majority using two, three, or four habitats at the same time, but only Gobiidae, Squillidae, Cynoglossidae, Sciaenidae, Penaeidae and Portunidae were found living in all five habitats, among which C. stigmatias, O. oratoria and P. trituberculatus had the largest numbers (Table S1). There were 18 specific species that appeared to use a single habitat, including 10 species of Platycephalidae and Pholidae in AR, Apogonidae in NA and Mugilidae and Paguridae in AA (S1).
The total abundances of species in the five habitats were highly different (univariate PERMANOVA: P = 0.001, n = 24) (Table S2). The pairwise PERMANOVAs indicated that all the habitats (e.g. AR/NA: P = 0.008, n = 5) accounted for the main variations in species abundance (Table S3). According to nonmentric mulidimensional scale (NMDS), the species assemblages recorded over five habitats were relatively well defined, with very little overlapping. The points in EA had a close distance, which means a weak species similarity compared to other habitats. Even though the points of CEA and AR do not overlap, the layout formed by the points of two habitats intersects, which indicates a potential relationship between species composition among these two habitats (Fig. 4).
The heatmap that combines the two cluster analyses of the assemblage data identified four separate groups of habitat types (top dendrogram) and five principal groups (left dendrogram) of taxa with similar habitat associations (Fig. 5). NA formed an isolated profile. A second group was formed by AR and CEA, while the third group included AA and EA. Upon cross–referencing these clusters with species recorded during the study, two groups of 12 species (Fig. 5–II and Fig. 5–VI) from a number of different families were strongly associated with AR. This group included O. oratoria, Johnius belangerii and Pennahia argentata, which was also recorded extensively in CEA. Two groups of 4 species (Fig. 5–II) and 10 (Fig. 5–V) species were strongly associated with CEA, while two groups of 2 (Fig. 5–I) and 19 (Fig. 5–III) species were mainly detected in AA. Only 3 species were strongly associated with NA, and some unique species including Penaeus semisulcatus (Fig. 5–I), Alpheus distinguendus (Fig. 5–II) and Heikea japonica (Fig. 5–III), dispersed in each group were found in EA.
Different species, even within the same family, presented varying degrees of habitat partitioning (Fig. 5). In the case of the family Gobiidae, for example, C. stigmatias and Tridentiger barbatus were most often associated with AR, and Amblychaeturichthys hexanema and Odontamblyopus rubicundus were associated predominantly with CEA, while Cryptocentrus filifer were most common in EA.
3.3 Length and size classes of species
A total of 608 species were used to describe their body size distribution in different habitats (Fig. 6). The body size of A. hexanema in AA was higher than that in CEA (P = 0.0001, n = 65) and AR (P = 0.001, n = 12), and that in EA was higher than that in CEA (P = 0.0001, n = 65) and AR (P = 0.008, n = 12). The body size of C. lucidus in AR was higher than that in AA (P = 0.018, n = 3), CEA (P = 0.0001, n = 86) and NA (P = 0.0001, n = 6), and that in EA was higher than that in CEA (P = 0.0001, n = 86) and NA (P = 0.0001, n = 6). The body size of O. oratoria in EA was higher than that in AA (P = 0.019, n = 18), AR (P = 0.0001, n = 47), CEA (P = 0.003, n = 62) and NA (P = 0.0001, n = 10), and that in CEA was higher than that in AR (P = 0.001, n = 86) and NA (P = 0.031, n = 6), and that in AA was higher than that in AR (P = 0.004, n = 86) and NA (P = 0.026, n = 6). While there is no difference of body size of C. stigmatias, T. curvirostris and P. trituberculatus between habitats.
4 Discussion
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In this study, we conduct a multi–habitat survey on the catch organisms in the artificial reef area and adjacent waters of Haizhou Bay. In the past, the study of fishery resources in Haizhou Bay focused only on artificial reef areas and contrasting areas (Zhang et al., 2006; Su et al., 2015), and contrasting areas include CEA, AA (e.g. shellfish culturing area, algae culturing area), NA and other habitats. Therefore, the contrasting areas consisting of multiple habitats may affect the effect assessments on artificial reefs and the results of fishery resource analysis, which is not scientific or reasonable. In addition, comparing the distributions of fishery resources in a single habitat cannot explain the intrinsic connections of habitats (Perry et al., 2018). Therefore, the study area of Haizhou Bay was clearly divided into five habitats, which was conducive to the study of the potential relationship between the characteristics of fishery resources and the interaction of population structures in artificial reefs and adjacent waters.
Estuary area is a major source of nutrient transport to the ocean and represents an important transition region in which energy from land and sea mixes, and this area is dominated by a variety of communities (Pasquaud et al., 2008; Howe et al., 2017). However, we did not observe a high level of species abundance in EA, which may be related to EA being subjected to the strongest interference by humans and large variation of salinity (13.09 to 17.06) (Li et al., 2011; Zhang et al., 2020; Deng et al., 2022). Furthermore, the water level (4.40 to 10.21 m) of EA fluctuates due to the intermittent influence of tides (tidal range: 2.69 m–5.05 m), which may lead to different assemblages (Gao et al., 2009; Yang et al., 2014; Zhang et al., 2017). Aquaculture area presents species assemblage with a variety of benthic shellfish and snails that other habitats do not include, which could explain the remarkably high benthic abundance in AA. The current in Haizhou Bay includes a branch of the YSWC and the YSCC, which flows from northeast to southwest (Sun et al., 2003). The research of Zhang (2013) showed that the spatial pattern of macroinvertebrate communities in Haizhou Bay under the influence of seasonal variations in different water masses, currents and other factors. Therefore, the high species abundance in CEA is expected, as it is the gathering place of the AA, AR and NA habitats under that influence of currents. As for NA, some samples are small.
Artificial reefs are an effective way to increase habitats and populations of fish species (Folpp et al., 2020); thus, we assume that AR is a mosaic that connects other habitats. Since artificial reefs were placed in local habitats, the abundance of species has shown an increasing trend over time (Wang et al., 2017), which is similar to results from most temperate seas (Lowry et al., 2014; Smith et al., 2016; Folpp et al., 2020). In this study, AR included almost all species (mostly fish, shrimps and crabs) present in the other habitats except for species specific to EA, AA, and NA, especially benthic mollusks in AA (Figs 2 and 3). According to the results of cluster analysis, most species utilized multiple habitats (Fig. 5), however, the composition of community structures were totally different between habitats (Fig. 4). This could be attributed to each habitat having a relatively unique assemblage, especially in AR, AA and CEA, among which AR had the largest number of species, at up to 24 (Fig. 5). Given that AA and CEA were not originally adjacent to each other, mediation by artificial reefs in AR as artificial habitats may increase the abundance of species among these habitats. This conclusion has been confirmed in most previous studies (Ammar, 2009; Lowry et al., 2014; Mclean et al., 2015; Smith et al., 2016; Wang et al., 2017; Komyakova et al., 2019; Folpp et al., 2020). Therefore, we believe that the similarity and uniqueness of the assemblages between habitats can indicate the ability of artificial reefs in AR to support assemblages comparable to those identified in adjacent habitats.
In the present study, strong links were also identified between the size–related assemblages and the distribution of habitats in artificial reefs and adjacent waters. There is significantly different body size of A. hexanema between some habtiats, and no difference in the body size of C. stigmatias was found, which may be related to the weak swimming ability and settlement behavior of Gobiidae after reaching adulthood, resulting in uneven distribution of individual size between habitats (Han et al., 2013). The body size of P. trituberculatus, with strong swimming ability, also showed no difference between habitats in this study (Fig. 6). The reason is that P. trituberculatus is active in coastal waters (e.g. EA, AR and NA in this study) (Yue et al., 2020). Moreover, EA is also the discharge area of P. trituberculatus in Haizhou Bay, which also indicates that the effect of stock enhancement to this species is positive. In total, the regularity of body size variations in each species in different habitats is not strong, which was related to many factors. On the one hand, differences in body size may be caused by differences in the growth rates of species in different habitats (Sogard, 1997). Longer, faster–growing fish are more likely to survive to maturity (Moss et al., 2005). On the other hand, differences may also be due to size–based selective mortality resulting in differences in body size. Density–dependent settlement, growth and mortality are often the major factors controlling recruitment success (Juanes, 2007). In addition, the observed vatiations in the body size gradients of C. lucidus and O. oratoria in different habitats reflect potential species–habitat associations of some marine species in different habitats. For example, similar body sizes of C. lucidus appeared in both AR and EA, which were higher than those in other habitats (Fig. 6). First, changes in habitat are often accompanied by diet shifts (Yang et al., 2018), indicating that the feeding environments created by AR and EA for C. lucidus may be relatively similar and implying that artificial reefs in AR could increase fish abundance by attracting fish (Lowry et al., 2014). Second, it should be noted that C. Lucidus is a migratory fish, and their appearance in AR may be due to migration of the mobile species from other sea areas (Jiang et al., 2016). Therefore, we consider that for some mobile species like C. Lucidus, there is variation in the size of individuals in different habitats, and their migration is an important media for potential connections between habitats, but more empirical studies are needed before a convincing conclusion can be drawn.
Finally, there are some places need to be improved in this study. The sample size of species in some areas (e.g. NA) is relatively small, which may lead to representative results. Therefore, more investigations should be conducted in the future. According to the characteristics of the species and environment in temperate seas, it is worth considering selecting the appropriate netting gear during the survey. The coastal waters of the Yellow Sea where Haizhou Bay is located are mainly dominated by muddy and sandy habitats, in which the underwater visibility is low, making it difficult to study communities by diving or snorkeling (Dorenbosch et al., 2007; Wang et al., 2011). Moreover, the current velocity is relatively high, and the methods used for underwater visual surveys, such as baited remote underwater video systems (BRUVs), are very limited (Reis-Filho et al., 2019). Therefore, trawl and gill nets are more commonly used for sampling in this region. However, trawling is the fishing method that caused the greatest harm to fisheries and marine environments (Trenkel et al., 2019). In the future, fishery resources and its community differences could be assessed by combining acoustic telemetrymethods. In addition, whether some migratory species use a variety of habitats to complete their life cycle at different stages in their life histories or simply exhibit cross–habitat behavior remains unclear. It may be necessary to combine otolith microelement (Maciel et al., 2020) or environmental DNA (eDNA) (Yamanaka and Minamoto, 2016) techniques for further in–depth analysis.
5 Conclusions
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In this study, a mesoscale survey of trawling catch communities associated with artificial reefs and adjacent waters was conducted for the first time to describe the characteristics of the rich diversity of species in the coastal water of Haizhou Bay. Our results show that each habitat exhibited species similarity, and some species were also unique in their habitat. We believed that there is a potential species–habitat associations among habitats within artificial reef areas and adjacent waters, and some mobile species can be served as an important media for potential connections between habitats. We concluded that artificial reefs in AR can be considered key components that have the ability to support species assemblages comparable to those identified in adjacent habitats, and can be applied in different stages of habitat protection implementation and in different combinations of scenarios.
Funding
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  • The China Scholarship Council under contract No.202308310175; the China Postdoctoral Science Foundation under contract No.E-6005-00-0042-39; Postdoctoral Fellowship Program of CPSF under contract No. GZC20231539; the Jiangsu Haizhou Bay National Sea Ranching Demonstration Project under contract No. D–8005–18–0188; Shanghai Municipal Science and Technology Commission Local Capacity Construction Project under contract No. 21010502200; the Science Foundation for Youths of Jiangsu Province, China under contract No. BK20170438; the Science and Technology Projects in Nantong under contract No. JC2018014; the Social Livelihood Key Projects of Nantong under contract No. MS22021015.
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Year 2024 volume 43 Issue 2
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doi: 10.1007/s13131-023-2226-2
  • Receive Date：2023-02-11
  • Online Date：2025-11-17
  • Published：2024-02-25
Article Data
Affiliations
History
  • Received：2023-02-11
  • Accepted：2023-06-26
Funding
The China Scholarship Council under contract No.202308310175; the China Postdoctoral Science Foundation under contract No.E-6005-00-0042-39; Postdoctoral Fellowship Program of CPSF under contract No. GZC20231539; the Jiangsu Haizhou Bay National Sea Ranching Demonstration Project under contract No. D–8005–18–0188; Shanghai Municipal Science and Technology Commission Local Capacity Construction Project under contract No. 21010502200; the Science Foundation for Youths of Jiangsu Province, China under contract No. BK20170438; the Science and Technology Projects in Nantong under contract No. JC2018014; the Social Livelihood Key Projects of Nantong under contract No. MS22021015.
Affiliations
    1 College of Marine Living Resource Sciences and Management, Shanghai Ocean University, Shanghai 201306, China
    2 Jiangsu Research Institute of Marine Fisheries, Nantong 226007, China
    3 Third Institute of Oceanography, Ministry of Natural Resources, Xiamen, 361005, China
    4 Joint Laboratory for Monitoring and Conservation of Aquatic Living Resources In the Yangtze Estuary, Shanghai 200000, China

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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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