Macro-algae flora and succession characteristics in the mussel culture zones in Gouqi island, Zhejiang Province Yan Huang 1,2, Bin Sun1,2, Pei-Min He1,2, 1College of Fisheries and Life Sciences, Shanghai Ocean University, Shanghai 201306 2 Marine Scientific Research Institute, Shanghai Ocean University, Shanghai 201306 Abstract: Macro-algae flora of the mussel culture zones in Gouqi island, Zhejiang Province, was surveyed from 2014 to 2015. Seventy species of macro-algae were identified, belonging to 31 genera, 21 families, 14 orders, and three phyla. Thirty-eight species from 16 genera belong to Rhodophyta, 21 species from seven genera belong to Phaeophyta, and 11 species from eight genera belong to Chlorophyta. Rhodophyta, Chlorophyta, and Phaeophyta contributed to 54.29%, 30%, and 15.71% of the total number of species, respectively. The dominant species were Undaria pinnatifida, Sargassum horneri, Grateloupia livida, Grateloupia turuturu, Ulva pertusa, Ulva lactuca, Hypnea boergesenii, Ulva linza, Cladophora utriculosa, and Amphiroa ephedraea. Seasonal alternation of macro-algae species was evident; there were 52 species in spring, 42 species in winter, 38 species in autumn, and 30 species in summer. Macro-algae biomass was highest in spring and lower in autumn > summer > and winter. The diversity of macro-algae communities also changed seasonally; the diversity index (H’) was highest in autumn and lower in summer > winter > and spring. The results of de-trended correspondence analysis suggested that temperature was the most important environmental factor affecting the distribution of the macro-algae in mussel culture zones. Wind, water currents, and human disturbances were also important factors affecting algal communities. Keywords: mussel, culture zones, Gouqi Island, macro-algae flora, dominant species, biomass Introduction Gouqi Island belongs to Shengsi county, Zhoushan city, Zhejiang province. It is located in the eastern part of Shengsi islands, Zhoushan islands, northeast. Gouqi Island is the second largest island in Shengsi county (Gu et al., 2015). Gouqi Island has a moderate and moist climate, with evident climate changes during the four seasons. The annual average surface temperature in Gouqi Island is about 17 ºC. Gouqi Island is the center of the Zhoushan fishing ground; it is on the edge of the subtropical sea area, possessing a fertile water body and abundant resources (Zhang et al., PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 2007). Mussel farming is an important economic industry in Gouqi Island. According to incomplete statistics (from 2015), the farming area and yield show a yearly positive trend, mainly concentrated in Houtou Bay. The mussel farming area in Gouqi Island has reached 12,370 mu (Chines unit: 1 mu =0.06666667 ha), 62,000 metric tons of production, and a production value of 149.7 million yuan. As the mussel farming industry expands, eutrophication in the breeding sea area occurs, as do other problems such as frequent occurrence of red tide (Chai et al., 2013; Wang et al., 2015), pollution risk, and the presence of Cd and Pb in mussels (Zhang et al., 2015). Studies have shown that, in combined shellfish and seaweed mariculture, algae can absorb excess nutrients in the aquaculture water, reducing the degree of eutrophication, and purifying the aquaculture water body (Zheng & Li, 2014). Algae are highly valuable for use in fertilizers (Zheng & Li, 2014), as chemical raw materials, for food (Han et al., 2012), for cosmetics (Li et al., 2015), for energy plants (Zhou & Bi, 2011), for marine medicine (Peng et al., 2011), etc. Algae are used in China and abroad, with as many as 150–250 kinds of large-scale algae applications in food and in business research (Kumari et al., 2010). The rational utilization and development of algae resources, will greatly improve the economic benefits of polyculture (Huang et al., 2015). So far, the study of mussel culture zones has focused on the quality of mussels, and the aquaculture water quality ( Gu et al., 2015; Wang et al., 2015; Zhang et al., 2015). Large-scale algae community composition, characteristics, and variations in aquaculture areas, have not been reported. In this study, we focused on macro-algae in the mussel culture zones of Gouqi Island, Houtou Bay. We analyzed the seasonal change and succession characteristics of the macro-algae community during the four seasons (spring, summer, autumn, and winter), so as to lay a theoretical basis for using macro-algae for bioremediation of seawater culture zones in the future, for establishing an ecological pattern of shellfish and seaweed mariculture, and for sustainable development of mariculture. Survey stations setting and survey methods The mussel culture zones in Gouqi Island area are about 4 km2, located along a shore 4000 m long and 1000 m wide (offshore of the coast). Inside the mussel culture zones, there are about 2000 marine cultivation units (100 × 50 m) (Wang et al., 2015) spaced every 3 m. Within each unit the cable is set up every 2 m; cylindrical floating balls (bottom diameter 35 cm, 50 cm high) are PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 fixed on the cable. The culture zones have around 20,000 cables and 800,000 floating balls. Mussels are cultured under the floating balls, whose submerged part is about 25 cm high. This submerged part produces a large number of macro-algae, in a living area of about 0.37 m2. There is also a certain amount of macro-algae living on the mussel farming cables. We set three investigation sections in the mussel farming area, each section consisting of three sampling stations (S1 –S9) (Fig.1). Fig.1 The sketch map of survey stations We investigated the macro-algae resources in the mussel culture zones in Gouqi island, in April, July, and October 2014, and in January 2015. We collected all the macro-algae attached to ropes and floating balls within a 0.35 m radius around the sample frame. Three samples were randomly selected in each sampling location. We put the macro-algae samples inside thermally insulated boxes with ice packs and took the samples to the laboratory. Sterilized seawater was used to rinse the surface of impurities, absorbent paper was used to blot moisture, and then the algae species were identified (Xia, 2004; Lee, 2008; Sun, 2011). After weighing, we counted the macro-algae species, and calculated the occurrence frequency at each sampling site (Liu et al., 2014). In this paper, we used the Shanno-Wiener (H ') index to evaluate macro-algae species diversity, according to the following formula: H' = -Σ Pi log2 ( Pi) In this formula Pi stands for proportion of the i kind of algae biomass in the total biomass, PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 namely the relative biomass RBi (Ma & Liu, 1994). We used the important value index I as evaluation standard for dominant species, according to the following formula: 𝐵𝑖 𝐹𝑖 Ii = RBi+RFi ;RBi =∑ 𝐵𝑖 ;RFi=∑ 𝐹𝑖 In this formula: Ii is the important value of the i kind of macro-algae; RBi is relative biomass of the kind of macro-algae; RFi is the relative occurrence frequency of the i kind of macro-algae (Liu et al., 2014). We used the Margelef index (E) to evaluate species richness, according to the following formula: E = (S-1) / ln N We used the Pielou index (J') to evaluate species evenness, according to the following formula: J' = H' / log2S In the last two formulas: S stands for total species; N stands for the biomass of all kinds of macro-algae. We used Excel 2016 to organize data; Surfer 8.0 software was used for analysis of survey stations, biomass, and other related data. We used Canoco 5.0 software for de-trended correspondence analysis (DCA) analysis of macro-algae data between different stations. In order to facilitate the mapping and data analysis, we retained only 38 kinds of macro-algae, so that the occurrence frequency was not less than 33.33% in DCA sorting, and in the data log (x + 1) optimization (Leps & Smilauer, 2003). 1. Results 1.1 Species composition Seventy macro-algae species were identified in the mussel culture zones in Gouqi Island (Table 1). These species belonged to 31 genera and three phyla. Thirty-eight species from 16 genera belonged to Rhodophyta, 21 species from seven genera belonged to Phaeophyta, and 11 species from eight genera belonged to Chlorophyta. Rhodophyta, Chlorophyta, and Phaeophyta contributed to 54.29%, 30%, and 15.71% of the total number of species, respectively (Fig. 2). PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 Table 1 Occurrence of Macro-algae in the mussels culture zones of Gouqi island Position distribution Rhodophyta 1 Grateloupia S S S S S S S S S 2 3 4 5 6 7 8 9 pring filicina ( Lamouroux) C.Agardh Grateloupia divaricata Okamura Grateloupia livida (Harv.) Yamada Grateloupia lanceolata (Okamura) Kawaguchi + + + + + + + + + + + + + + + + ramosissima + Okamura Grateloupia okamurae Yamada + + Grateloupia turuturu Yamada + + Ding Corallina sessilis Yendo + + et Ding Sinotubimorpha claviformis Li et S + Grateloupia catenata(Yendo) Li Grateloupia Season + + + + + + + mmer + + + + + + + tumn W inter Abbrevia tion in DCA + + + + + A1 + + + + A2 + + + + + + + + + + Au + + + Su + A3 + + PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 + A4 Corallina officinalis Linnaeus + Amphiroa zonata Yendo Amphiroa ephedraea Decaisne + Callophyllis adhaerens Yamada + Callophyllis adnata Okamura Polysiphonia japonica Harvey + + + + + + Laurencia glandulifera Kütz. Laurencia obtusa Yamada + + + Ceramium japonicum Okamura + + + + + + + + + + + + + + Hypnea charoides J.Agardh + + + + + + A5 + + A6 + A7 + + + + + + + + + A8 + + A9 + + + + + + + + + + + + Chondria crassicaulis Harvey Okamura + + Laurencia composita Yamada pinnatum + + Laurencia pinnataYamada Erythroglossum + + + + + + + + + PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 Hypnea chordacea Kütz. + + Hypnea boergesenii Tanaka + + + + + + + + + + Hypnea cervicornis J. Agardh + + + + + + + + + + Gracilaria lemaneiformis(Bory) Greville Gracilaria tenuistipitata Zhang et Xia var. liui Zhang et Xia + + + + + Gracilaria chouae Zhang et Xia + + A10 + + + A11 + + + A12 + + + + + Gracilaria textorii (Suring.) De + + Toni Chondrus ocellatus Holmes + Pyropia suborbiculata Kjellman + + + + + + + + + + A13 + + A14 + + + + + A15 + + + + + A16 Pyropia yezoensis Ueda + + + + + A17 Lomentaria hakodatensis Yendo + + A18 Lomentaria catenata Harvey + Porphyra haitanensis T. J. Chang et B. F. Zheng + + + + + + + + + + PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 + A19 Ganonema farinose + + Ulva lactuca L. + + + + + Ulva fasciata Delile + + + + + Ulva pertusa Kjellman + + + + + Ulva conglobata Kjellman + + + + + (Lamouroux) Fan et Wang + + + + + + + A20 + + + A21 + + + + A22 + + A23 Chlorophyta Chaetomorpha media (Ag.) + Kuetz. Monostroma nitidum Wittr. + Ulva linza L. + + + + Ulva flexuosa + + + + + + + + + + + + + + + + + + + + + + + + Blidingia minima( Nägeli ex Kützing) Kylin Lamouroux + + Enteromorpha prolifera Bryopsis + pennata J.V. + + + + A24 + + + + + + + A25 + + + + + + + PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 A26 Bryopsis sp.J.V. Lamouroux Bryopsis maxima Okamura + + Bryopsis corticulans Setch. Bryopsis plumosa ( Hudson) C.Agardh + + + + + + Codium fragile( Suringar) Hariot + + + + Cladophora stimpsonii Harvey + + + + + Cladophora utriculosa Kütz. + + + + + + + + + + + + + + + Cladophora flexuosa (Müller) Kuetzing Chaetomorpha spiralis Okamura Chaetomorpha aerea (Dillw.) Kütz. + + + + + + + + + + + + + A27 + A28 A29 + + + + + + + + A31 + + + A32 + + + + + + + + + + + + + + + Phaeophyta Sargassum fusiforme( Harvey) + Setchell Sargassum thunbergii (Mertens ex Roth) Kuntze + PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 + + A30 A33 Sargassum horneri( Turner) C.Agardh Sargassum + + + + vachellianum lomentarius (Lyngbye) J. Agardh Endarachne binghamiae J. + Colpomenia sinuosa( Mertens ex (Holmes) Okamura + + + + + + Ectocarpus siliculosus (Dillwyn) + + + + + A36 + + Lyngbye + A34 A35 + J.V.Lamouroux Suringar + + Dictyota dichotoma (Hudson) Undaria pinnatifida( Harvey) + + + Roth) Derbes et Solier coriaceum + + + Agardh Pachydictyon + + Greville Scytosiphon + + + + + + + + + PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 + A37 Phaeophyta 16% Chlorophyta 30% Rhodophyta 54% Fig. 2 The composition of macro-algae flora in the mussels culture zones of Gouqi island 1.2 Spatiotemporal change of the macro-algae community The seasonal alternation of macro-algae species was significant throughout the year. There were 52 species in spring, 42 species in winter, 38 species in autumn, and 30 species in summer (Fig 3). Rhodophyta was the largest phylum; there were 30 species of Rhodophyta in spring, 28 species in winter, 20 species in autumn, 15 species in summer, which accounted for 57.69%, 66.67%, 52.63% and 50% of the total number of species in each season, respectively. Green algae were present during the four seasons. There were 16 species of green algae in autumn, 15 species in spring and summer, and only eight species in winter,. In the survey, brown algae were present only during spring, autumn, and winter. There were seven species of brown algae in spring, six in winter, and only two species in autumn. The species Gracilaria textorii (Suring.) De Toni, Grateloupia livida (Harv.) Yamada, Ulva lactuca L., Corallina sessilis Yendo and some Hypnea, and Laurencia et al. were present throughout the year (13 species in all), accounting for 18.57% of the total number of species (70 species in total). PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 Fig. 3 The macro-algae flora composition in different seasons There were significant differences in the species distribution in different stations (Fig.4). There was a lower number of species in external stations and a higher number of species in internal stations. There was a lower number of species in the west stations and a higher number species in the east stations. There were 43 macro-algae species in S1 station (61.43% of the 70 species recorded), 35 in S2 (54.29% of the 70 species recorded), 35 in S4 (50% of the 70 species recorded), 29 in S7 and S9 stations (41.43% of the 70 species recorded), 25 in S3 (35.71% of the 70 species recorded), 23 in S5 (32.86 of the 70 species recorded), 22 in S8 (31.43% of the 70 species recorded), and 18 in S9 (25.71% of the 70 species recorded). PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 The macro-algae biomass in different seasons 1.3 Dominant macro-algae species in the community and its spatiotemporal distribution The dominant species of the macro-algae community changed seasonally (Table 2). In spring the dominant species were red algae and brown algae, such as Undaria pinnatifida (Harvey), Sargassum horneri (Turner) C. Agardh, Grateloupia livida (Harv.) Yamada, Callophyllis adnate Okamura, Amphiroa ephedraea Decaisne. In summer, autumn, and winter the dominant species were red algae and green algae, such as G. livida (Harv.) Yamada, Hypnea boergesenii Tanaka, Amphiroa ephedraea Decaisne, Ulva pertusa Kjellman, Ulva lactuca L, Chaetomorpha spiralis Okamura. G. livida (Harv.) Yamada, and C. spiralis were the dominant species in the four seasons. Some macro-algae species had a wide distribution, appearing in the nine stations. Among these algae species were G. livida (Harv.) Yamada, Grateloupia turuturu Yamada, Corallina sessilis Yendo, H. boergesenii Tanaka, U. pinnatifida (Harvey), U. lactuca, C. spiralis, and others that were the dominant species in the mussel culture zones, with a total number of 10 species, accounting for 14.29% of the total of 70 species. PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 Table 2 Importance values of dominant species in different seasons Dominant species Spring Important value Summer Autumn Winter Phaeophyta Undaria pinnatifida Sargassum horneri Rhodophyta Grateloupia livida Grateloupia turuturu Hypnea boergesenii Callophyllis adnata Corallina sessilis Amphiroa ephedraea Chlorophyta 1 0.93 Ulva pertusa Ulva lactuca Ulva fasciata Ulva linza Chaetomorpha spiralis Cladophora stimpsonii Cladophora utriculosa 0.78 0.82 1.49 0.92 0.64 0.68 0.94 1.46 0.7 0.79 0.55 0.56 1.01 0.59 0.98 0.6 0.57 0.95 0.6 0.91 0.66 1.34 0.58 0.72 0.69 1.13 1.4 Biomass characteristics of the macro-algae community The biomass of macro-algae community changed seasonally (Fig.5). The annual average macro-algae biomass was 3626.71 g•m−2. Biomass was highest in spring (12,599.35 g•m−2). There was a biomass decrease in summer (538.60 g•m−2, the nadir of the biomass throughout the year), resulting from a decline in U. pinnatifida (Harvey) Suringar and S. horneri (Turner) C. Agardh, due to higher temperatures. Macro-algae biomass was slightly higher in autumn (786.94 g• m−2) and winter (581.94 g• m−2). PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 Fig. 5 Total occurring macro-algae species numbers of different stations during the survey period Red algae and brown algae represented the major part of the macro-algae biomass (Table 3), which alternated in various seasons. Biomass in spring was mainly composed of brown algae; the biomass of S. horneri (Turner) C.Agardh and U. pinnatifida ( Harvey) Suringar was 6287.75 and 4399.75 g•m−2, respectively.Red algae represented the major part of the biomass in summer and winter; the biomass of G. livida (Harv). Yamada was 251.51 g•m−2 in summer, and 264.85 g•m-2 in winter.Green algae represented the major part of the biomass in autumn; the biomass of U. linza, L., Cladophora utriculosa Kütz, and Ulva fasciata Delile was 268.16 g•m−2, 268.16 g•m−2, and 268.16 g•m−2, respectively. Table3 Seasonal variation of biomass dominant species during the survey period (unit: g·m-2) Biomass dominant species Spring Biomass Summer Autumn Winter Phaeophyta Sargassum horneri 6287.75 Undaria pinnatifida 4399.75 Rhodophyta Grateloupia turuturu Grateloupia livida 540.66 30.21 251.51 264.85 49.86 75.42 Chlorophyta Ulva lactuca Ulva linza 268.16 63.26 PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 Cladophora utriculosa 101.89 Ulva fasciata 84.81 The annual average biomass of macro-algae was different at different stations (Fig. 6). The biomass was lower in external stations and higher in internal stations; biomass was higher in the west stations and lower in the east stations. The annual average biomass of S2 has highest (43,531.56 g•m−2), followed by S2 (19,692.38 g•m−2), S9 (16,653.79 g•m−2), S1 (15,633.33 g•m−2), S3 (10,194.18 g•m−2), S5 (7660.74 g•m−2), S7 (7012.49 g•m−2), S4 (6243.68 g•m−2), and S8 (3939.36 g•m−2). Fig. 6 Total macro-algae biomass of different stations during the survey period 1.5 Diversity characteristics of macro-algae community There were evident seasonal changes in the diversity index (H'), richness index (E) and evenness index (J') of the macro-algae community. The averages values of the diversity index (H'), richness index (E) and evenness index (J') were 1.95, 1.41, 0.58, respectively (Table 4).The diversity index (H ') was highest in autumn, followed by summer, spring, and winter. The richness index (E) was highest in spring, followed by winter, autumn, and summer. There were no significant differences in the evenness index (J') in summer, autumn, and winter; this index was lowest in spring. Table 4 The seasonal variation of Shanno-Wiener index (H’), Margelef index (E) and Pielou index (J’) of marco-algae communities in the mussels culture zones of Gouqi island Station Spring H' E Summer J' H' E Autumn J' H' E Spring J' H' E PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 J' S1 S2 S3 S4 S5 S6 S7 S8 S9 Mean 1.55 0.5 1.09 1.49 2.1 0.94 1.05 1.93 0.38 1.23 1.43 1.67 0.91 1.59 1.26 1.1 0.97 1.43 1.07 1.27 0.4 0.12 0.34 0.39 0.58 0.26 0.33 0.54 0.11 0.34 2.65 0.75 2.91 1.35 1.28 2.21 2.65 2.44 2.78 2.11 1.37 0.89 1.78 1.16 0.72 1.05 1.26 1.35 1.45 1.23 0.84 0.26 0.84 0.47 0.64 0.75 0.87 0.74 0.83 0.69 3.38 2.91 3.05 2.71 1.94 1.73 1.67 2.23 2.05 2.41 3.06 2.41 2.33 1.53 1.32 0.91 1.14 1.37 1.31 1.71 0.78 0.7 0.74 0.76 0.6 0.65 0.54 0.66 0.63 0.67 2.09 1.48 1.79 2.66 2.32 1.93 1.43 2.71 1.94 2.04 2.75 1.98 1.17 1.52 1.36 1.13 0.82 1.54 0.82 1.45 0.5 0.39 0.57 0.78 0.71 0.63 0.54 0.81 0.75 0.63 In spring, the diversity and evenness indexes were highest in S5, and the richness index was highest in S2. In summer, the diversity and richness indexes were highest in S3, and the evenness index was highest in S7. In autumn the diversity, evenness, and richness indexes were highest in S1. In winter, the diversity and evenness indexes were highest in S8, and the richness index was highest in S1. 1.6 DCA sorting of the macro-algae community in the mussel culture zones DCA analysis was based on the total biomass of macro-algae in spring, summer, autumn, and winter (Fig. 7 and Fig. 8). For the convenience of drawing and data analysis, we retained only 38 species of macro-algae, the occurrence frequency of which was no less than 33.33% (A1–A37, Table 1). The distribution of S1–S9 stations changed along the axis1 and axis2 (Fig. 7). Stations S5, S3, S6, are far away from the dock and were distributed on the left side of the figure. Stations S1, S2, S4, S7 are near the dock, and were distributed on the right side of figure. The external stations S7, S8 were distributed on the upper part of the figure. Stations S1, S2, S3, and S4, within the mussel culture zones, were distributed in the lower part of the figure. We estimated that axis1 may represent human disturbances affecting the macro-algae community structure. The degree of disturbance increased gradually from left to right along the axis1. Waves and currents increased gradually along the axis2 from the bottom to the top; thus the axis2 may represent the size of the waves and currents affecting the macro-algae community structure. PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 Fig. 7 DCA plot of occurring species numbers of survey stations Fig. 8 DCA plot of occurring macro-algae species PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 The eigenvalues in the four axis of Fig 8 were 0.13, 0.07, 0.02, and 0.13. The eigenvalues of axis1 are the largest, which embody most of the ecological information. Gracilaria textorii (Suring.) De Toni (Fig8, A13), Laurencia obtusa Yamada (Fig 8, A9), A. ephedraea Decaisne) (Fig8, A5) and other warm temperature macro-algae that appeared in summer and autumn were distributed on the left side of the first axis. Laurencia glandulifera Kütz. (Fig 8, A8), Bryopsis pennata J.V. Lamouroux (Fig 8, A26), Bryopsis maxima Okamura (Fig 8, A27), Codium fragile (Suringar) Hariot (Fig 8, A29), Chondrus ocellatus Holmes (Fig 8, A14) and other macro-algae that appeared in spring and winter were distributed on the right side of the first axis. Endarachne binghamiae J. Agardh (Fig 8, A35), Pyropia suborbiculata Kjellman (Fig 8, A15), Porphyra haitanensis T. J. Chang et B. F. Sheng (Fig 8, A16) and other macro-algae that appeared in external stations were distributed on the upper part of the second axis. Hypnea chordacea Kütz. (Fig 8, A10), Pachydictyon coriaceum (Holmes) Okamura (Fig 8, A36), G. textorii (Suring.) De Toni (Fig 8, A13), C. ocellatus Holmes) (Fig 8, A14) and other macro-algae that appeared in internal stations were distributed on the bottom part of the second axis. We concluded that the first axis represents temperature as the main environmental factor affecting macro-algae distribution in Fig. 8, as water temperature decreases from left to right. The second axis represents the size of the waves and currents influencing macro-algae distribution, as the influence of waves decreases gradually from top to bottom. These conclusions were similar to those obtained from data in Fig.7 2Discussion 2.1 The composition and variation of the macro-algae community in the mussel culture zones of Gouqi island In 2007, Shou-Yu Zhang et al. (Zhang et al., 2008) investigated the macro-algae resources of Maan islands in Zhejiang province. Thirty species were identified, including 16 species of Rhodophyta, seven species of Chlorophyta, and eight species of Phaeophyta. In 2010, Lin et al. (2012) studied the variation in the macro-algae community structure in Shengsi islands. They collected 87 kinds of macro-algae in Gouqi island; 60 species belonged to Rhodophyta. In 2011, Zeng et al. (2013) investigated the intertidal benthic macro-algae resources of Gouqi island; 65 species were identified. In this survey, we identified 70 species, including 38 species of Rhodophyta, 21 species of Chlorophyta, and 11 species of Phaeophyta, similarly to the results of PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 Zenget al. (42 species of Rhodophyta, 11 species of Chlorophyta, 11 species of Phaeophyta, and one species of Cyanophyta). We did not find Lyngbya semiplena (C.Agardh) J.Agardh, Bangia fusco-purpurea (Dillwyn), Lyngbye,Pyropia dentata Kjellman, Gelidium divaricatum G. Martens, Gelidium amansiiv J.V.Lamouroux, Pterocladia tenuis Okamura et al. We newly found Grateloupia divaricata Okamura, G. livida (Harv.) Yamada, G. okamurae Yamada, Corallina officinalis Linnaeus, Callophyllis adhaerens Yamada and Erythroglossum pinnatum Okamura et al. G. divaricata Okamura and E. pinnatum Okamura were not reported in a previous study of the algae community in Shengsi. In our survey Rhodophyta was the most abundant genera (38 species in total; accounting for 54.29% of the total species) followed by Chlorophyta and Phaeophyta (which had the lowest percentage). The biomass of Phaeophyta was large, and was mainly represented by U. pinnatifida (Harvey) and S. horneri (Turner) C. Agardh. Previous studies have shown that the macro-algae community attached to the floating balls will experience a succession process developing from junior to senior, after the floating balls were installed. In the early stages, when the floating balls were installed, pioneer Chlorophyta species in attached first in the succession, followed by Rhodophyta. The appearance and abundance of Phaeophyta is representative of the maturity of the macro-algae communities; the abundant attachment of Phaeophyta signals that the algae community had reached a stable stage (Sousa, 1979). Fishermen harvest and breed the young mussels in summer and autumn. Therefore the macro-algae community experiences the strongest human disturbances in summer and autumn. It is much harder for macro-algae communities to complete the succession to form a climax community. So the species of Rhodophyta and Chlorophyta at the early stage of succession highly represented in the macro-algae community (Orfanidis et al., 2001). The human disturbance was weaker in winter and spring, which is a vigorous growth period of macro-algae. The biomass of U. pinnatifida (Harvey) and S. horneri (Turner) C. Agardh was 6287.75 and 4399.75 g•m−2 in spring, respectively. This shows that the algal community had reached maturity after growing during winter and spring (Chang et al., 2002; Oyamada et al., 2008). 2.2 Analysis of the relationship of macro-algae species, biomass production and diversity index in the mussel culture zones Macro-algae species and biomass distribution in different stations show opposite patterns. PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 There was a lower number of species in external stations and a higher number of species in internal stations. There was a lower number of species in the west stations and a higher number species in the east stations. Conversely, the biomass was lower in external stations and higher in internal stations; biomass was higher in the west stations and lower in the east stations. S1 station had the most species, but the biomass was not the highest at this location. A previous study confirmed that external disturbances affect the species diversity of plant communities (Connell, 1978). Becausethe S1 station is near the dock, it experienced much more human disturbance than other stations. This caused that most of the macro-algae species in the community of S1 station pioneer species. The number of species in S2 station was lower than that of S1. S2 is far away from the dock, received weaker human disturbance, and had the highest biomass, which is consistent with the results of DCA analysis. Because the S1, S4 and S7 stations are near the dock, the effect of human disturbance is stronger, so they have a larger number of species (larger than the S3, S6 and S9 stations combined) but low biomass. S5 station is in the center of mussel culture zones, so the effect of human disturbance is smallest, and the biomass is also significantly higher than that of S8 station. The number of macro-algae species was highest in spring and lower in winter > autumn > and summer. The diversity index (H') in different seasons was highest in autumn and lower in summer > winter > and spring. The richness index (E) in different seasons was highest in autumn and lower in winter > spring > and summer. There were no significant differences in the evenness index (J ') in summer, autumn, and winter; this index was lowest in spring. The evenness index and the number of rare species in a community have a large effect on diversity index H'. In our study the number of macro-algae species and the diversity index did not match perfectly. That is because that the biomass of U. pinnatifida (Harvey) and S. horneri (Turner) C. Agardh was dominant in spring, which results in decreased community evenness and consequently a lower diversity index than in the other three seasons (Schneider, 2010). The seasonal distribution of the rare species (species with a relative occurrence frequency lower than 33.33% and with lower biomass) is: 20 species in spring, 18 species in winter, 13 species in autumn, nine species in summer. Rare species were mostly observed in spring and winter, which is why the resulting diversity index was lower in spring and winter. Fishermen harvest and breed young mussels in summer and autumn; therefore the macro-algae community has the strongest PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 human disturbance in these seasons. The community succession of mussel culture zones begin in summer. Summer is at the early stage of the succession. Because of high temperatures and strong and frequent human disturbance, the macro-algae species number and richness index of the community were the lowest. In autumn the temperature drops, which is suitable for macro-algae growth; this is the most thriving period of the succession. The number of algae species increased so the richness index is the highest, but the human disturbance is still strong. In winter water temperature continues to drop and human disturbances decrease. The algae community begins to develop rapidly, the succession level improves gradually, and the diversity index and richness become higher. After the growth in winter, a relatively stable macro-algae community with many species has been formed in spring, which is at a later stage of the succession, in which and U. pinnatifida (Harvey) and S. horneri (Turner) C. Agardh are dominant. So the diversity index and evennes are lowest in spring because at this time U. pinnatifida (Harvey) and S. horneri (Turner) C. Agardh are dominant. In summer, the mature macro-algae community is altered, returning back into the early stage of the succession. As the seasons change, the algae community constantly repeats the succession process: from junior to senior, from simple to complex, from fluctuant to the stable. The analysis each index of the different geographical position shows that, due to the stronger human disturbance factor in the S1, S2, S7, and S8 stations the diversity index higher. The nutrients at S5 station were high (Wang et al., 2015), so the diversity index is also higher. 2.3The influence of environmental factors on variations of macro-algae community Previous research shows that water temperature (Davision, 1991) and nutrient content (Zou & Xia, 2011) have an important influence on the growth and distribution of macro-algae. The average water temperature (18.23°C) in spring is suitable for growth, so that the number of algae species and biomass are at the highest levels. The number of algae species and biomass are lowest in summer. Seawater temperature decreased in autumn, so the number of algae species and biomass increase. Algae species are more abundant in winter than in autumn; most of these species are rare (they have low occurrence frequency and low biomass) so that the total biomass decreases. The average macro-algae biomass in summer is significantly lower than in the spring. This phenomenon may be due to the higher average temperature of seawater in summer (26.34°C), PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 which causes that a large number of macro-algae (especially U. pinnatifida (Harvey) Suringar and S. horneri (Turner) C.Agardh) declines, accounting for a large reduction of the total biomass in summer. Previous studies have shown that in summer the concentration of inorganic nitrogen and phosphate are 56.36 +2.98 μmol/L and 0.22 + 0.06 μmol/L, respectively. These concentrations reached a severe eutrophication level in the mussel culture zones (Wang et al., 2015). The tolerance of perennial macro-algae to pollution is low (Fletcher, 1996). A high concentration of nutrient is also one of the factors that lead to a dramatic decrease in macro-algae biomass levels. In our study, Since June, a large number of skeleton shrimp (Caprellidae sp.), gammarids (Gammaridea sp.), and other fouling organisms appeared in the mussel culture zones; their numbers reached a peak in August. These organisms compete with macro-algae for attaching to the substratum, which is also one of the causes of biomass decline. Harvesting, breeding of the young mussels, and other production activities in summer also affect the distribution of the macroalgae to a certain extent.Salinity, light intensity, and the presence of other benthic macroinvertebrates (Sala & Dayton, 2011; Wu et al., 2015) are likely to affect the structure of the macroalgae community. 3. Conclusions Survey results show that the macro-algae community composition in the mussel culture zones in Gouqi Island is diverse with evident seasonal changes. Temperature is the primary environmental factor temperature affecting the distribution of macro-algae community. 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