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:
퐵푖 퐹푖 Ii = RBi＋RFi ；RBi = ；RFi= ∑ 퐵푖 ∑ 퐹푖
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 Season Abbrevia S S S S S S S S S S Su Au W Rhodophyta tion in DCA 1 2 3 4 5 6 7 8 9 pring mmer tumn inter Grateloupia filicina + + + ( Lamouroux) C．Agardh
Grateloupia divaricata Okamura + + +
Grateloupia livida (Harv.) + + + + + + + + + + + + + A1 Yamada Grateloupia lanceolata + + + + + + + + + A2 (Okamura) Kawaguchi Grateloupia catenata(Yendo) Li + + + et Ding Grateloupia ramosissima + + + Okamura
Grateloupia okamurae Yamada + + + +
Grateloupia turuturu Yamada + + + + + + + + + + + A3
Sinotubimorpha claviformis Li et + + + Ding
Corallina sessilis Yendo + + + + + + + + + + + + A4
PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 Corallina officinalis Linnaeus + + + +
Amphiroa zonata Yendo + + + +
Amphiroa ephedraea Decaisne + + + + + + + + + + + + A5
Callophyllis adhaerens Yamada + + + + + + + A6
Callophyllis adnata Okamura + + + + + + A7
Polysiphonia japonica Harvey + + + + +
Laurencia glandulifera Kütz. + + + + + + + + A8
Laurencia obtusa Yamada + + + + + A9
Laurencia pinnataYamada + + + + +
Laurencia composita Yamada + + + +
Chondria crassicaulis Harvey + + +
Ceramium japonicum Okamura + + + +
Erythroglossum pinnatum + + Okamura
Hypnea charoides J.Agardh + +
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. + + + + + + A10
Hypnea boergesenii Tanaka + + + + + + + + + + + + + A11
Hypnea cervicornis J. Agardh + + + + + + + + + + + + + A12
Gracilaria lemaneiformis(Bory) + + + + + Greville Gracilaria tenuistipitata Zhang + + + et Xia var. liui Zhang et Xia
Gracilaria chouae Zhang et Xia + +
Gracilaria textorii (Suring.) De + + + + + + + A13 Toni
Chondrus ocellatus Holmes + + + + + + A14
Pyropia suborbiculata Kjellman + + + + + A15
Porphyra haitanensis T. J. + + + + + A16 Chang et B. F. Zheng
Pyropia yezoensis Ueda + + + + + A17
Lomentaria hakodatensis Yendo + + + + A18
Lomentaria catenata Harvey + + + + + + + + + + A19
PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 Ganonema farinose + + + + + (Lamouroux) Fan et Wang
Chlorophyta
Ulva lactuca L. + + + + + + + + + + + + + A20
Ulva fasciata Delile + + + + + + + + + + A21
Ulva pertusa Kjellman + + + + + + + + + + + + A22
Ulva conglobata Kjellman + + + + + + + + + + A23
Chaetomorpha media (Ag.) + + + + + + + + + + A24 Kuetz.
Monostroma nitidum Wittr. + + +
Ulva linza L. + + + + + + + + + + + + + A25
Ulva flexuosa + +
Enteromorpha prolifera + +
Blidingia minima( Nägeli ex + + Kützing) Kylin Bryopsis pennata J.V. + + + + + + + A26 Lamouroux
PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 Bryopsis sp.J.V. Lamouroux + + + +
Bryopsis maxima Okamura + + + + + A27
Bryopsis corticulans Setch. + + +
Bryopsis plumosa ( Hudson) + + + + + + + + A28 C.Agardh
Codium fragile( Suringar) Hariot + + + + + A29
Cladophora stimpsonii Harvey + + + + + + + + + + + A30
Cladophora utriculosa Kütz. + + + + + + + + + + A31
Cladophora flexuosa (Müller) + + + + + + + + A32 Kuetzing
Chaetomorpha spiralis Okamura + + + + + + + + + + + + + A33
Chaetomorpha aerea (Dillw.) + + + + + Kütz.
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 Sargassum horneri( Turner) + + + + + + + + A34 C.Agardh Sargassum vachellianum + + Greville Scytosiphon lomentarius + + + (Lyngbye) J. Agardh Endarachne binghamiae J. + + + + A35 Agardh Colpomenia sinuosa( Mertens ex + + Roth) Derbes et Solier Pachydictyon coriaceum + + + + + A36 (Holmes) Okamura Dictyota dichotoma (Hudson） + + J.V.Lamouroux Ectocarpus siliculosus (Dillwyn) + + + Lyngbye Undaria pinnatifida( Harvey) + + + + + + + + + + + A37 Suringar
PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017
Phaeophyta 16%
Chlorophyta Rhodophyta 54% 30%
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 Important value Dominant species Spring Summer Autumn Winter Phaeophyta 1 Undaria pinnatifida 0.93 Sargassum horneri Rhodophyta Grateloupia livida 0.82 1.49 0.64 1.46 0.68 Grateloupia turuturu 0.92 0.94 0.7 Hypnea boergesenii 0.79 Callophyllis adnata 0.57 Corallina sessilis 0.55 1.01 0.95 Amphiroa ephedraea Chlorophyta
0.78 0.59 0.6 Ulva pertusa 0.98 0.91 Ulva lactuca 0.66 Ulva fasciata 1.34 Ulva linza Chaetomorpha spiralis 0.56 0.6 0.58 0.72 0.69 Cladophora stimpsonii Cladophora utriculosa 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 Biomass dominant species Spring Summer Autumn Winter Phaeophyta 6287.75 Sargassum horneri 4399.75 Undaria pinnatifida Rhodophyta 540.66 30.21 Grateloupia turuturu 251.51 264.85 Grateloupia livida Chlorophyta 49.86 75.42 Ulva lactuca 268.16 63.26 Ulva linza
PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 101.89 Cladophora utriculosa 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 Spring Summer Autumn Spring Station H' E J' H' E J' H' E J' H' E J'
PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.2738v1 | CC BY 4.0 Open Access | rec: 19 Jan 2017, publ: 19 Jan 2017 S1 1.55 1.43 0.4 2.65 1.37 0.84 3.38 3.06 0.78 2.09 2.75 0.5
S2 0.5 1.67 0.12 0.75 0.89 0.26 2.91 2.41 0.7 1.48 1.98 0.39
S3 1.09 0.91 0.34 2.91 1.78 0.84 3.05 2.33 0.74 1.79 1.17 0.57
S4 1.49 1.59 0.39 1.35 1.16 0.47 2.71 1.53 0.76 2.66 1.52 0.78
S5 2.1 1.26 0.58 1.28 0.72 0.64 1.94 1.32 0.6 2.32 1.36 0.71
S6 0.94 1.1 0.26 2.21 1.05 0.75 1.73 0.91 0.65 1.93 1.13 0.63
S7 1.05 0.97 0.33 2.65 1.26 0.87 1.67 1.14 0.54 1.43 0.82 0.54
S8 1.93 1.43 0.54 2.44 1.35 0.74 2.23 1.37 0.66 2.71 1.54 0.81
S9 0.38 1.07 0.11 2.78 1.45 0.83 2.05 1.31 0.63 1.94 0.82 0.75
Mean 1.23 1.27 0.34 2.11 1.23 0.69 2.41 1.71 0.67 2.04 1.45 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 macro-
algae to a certain extent.Salinity, light intensity, and the presence of other benthic macro-
invertebrates (Sala & Dayton, 2011; Wu et al., 2015) are likely to affect the structure of the macro-
algae 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. Human
disturbance is an important environmental factor affecting the algal communities. In this article,
we report that the variation of the macro-algae community in the mussel culture zones is the result
of mussel production activities and human disturbance. In the future, if we used the succession law
in the process of mussels breeding, the development of aquatic animals, within in a macro-algae
mariculture model, we would double the results with half the effort.
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