CC BY
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Protistology 8 (4), 178-188 (2014)
Protistology
Spatial and temporal variability of phytoplankton at Jukrim-ri, Tongyeong-si, Korea
Man Kyu Huh
Department of Molecular Biology, College of Natural Sciences, Dong-eui University 995Eomgwangno, Busanjin-gu, Busan 614-714, Korea
Summary
The study was described in the seasonal and spatial patterns of phytoplankton on the water surface and basal layer below the surface depths for seven stations at Jukrim-ri in Korea. Although this area was not wide, but the phytoplankton community was very diverse with 54 taxa identified, representing four classes. Diatoms (Bacillariophyceae) exhibited the greatest diversity with 38 taxa identified, followed by dinoflagellates (Dinophyceae, 12 taxa); Cryptophyceae with three taxa, and Eugenophyceae represented by a single taxon. Water surfaces were shown with the relative higher individual density or abundance across areas than those of basal layer. For the community as a whole, the values of fi-diversity for spatial variability were the lower than those of temporal variability. There was high taxonomic homogeneity of the phytoplankton community among four seasons. However, size distribution of abundance and biomass showed a statistically significant difference between south-north stations.
Key words: phytoplankton, size-frequency distribution, spatial patterns
Introduction
Phytoplankton inhabit most the upper sunlit layer of almost all oceans and bodies of fresh water. Despite their infinitely small size in comparison to other marine organisms, these tiny creatures occupy an immensely important ecological niche (Almandoz et al., 2011). Phytoplanktons are freely floating, often minute organisms that drift with water currents. They are agents for very important primary production of earth. Like land vegetation, phytoplankton uses carbon dioxide, releases oxygen, and converts minerals to a form animals can use. Thus, phytoplankton has a vastly significant role
to play not only in the marine food web of which they are part of, but also on a more global scale (Falkowski et al., 2003). Phytoplankton can be account for half of all photosynthetic activity on Earth (Falkowski et al., 2006; Stanca et al., 2003).
There are two kinds of ocean currents; surface currents which extend only a few feet below the surface and subsurface currents that run below the surface depths (McWilliams, 1996). Factors affecting the depth of the euphotic zone are the incidental angle of sunlight, the clarity of the atmosphere, and the turbidity of the water.
The spatial and seasonal changes of marine algae are important because they can produce a variety of
© 2014 The Author(s)
Protistology © 2014 Protozoological Society Affiliated with RAS
Protistology ■ 179
highly toxic compounds—marine biotoxins (Merritt and Cummins, 1996). These compounds, some of which can be released to the surrounding water while others are retained in the phytoplankton, can enter the food web and accumulate in fish and shellfish (Verlencar, 2004). In some cases higher in the food web, fish and shellfish can be affected by these potent compounds and made ill or even die. In virtually all cases, the marine biotoxins produced by these phytoplankton and zooplanktons (Lee et al., 2002).
Coastal lagoons have traditionally been considered as transitional systems between continental and marine domains (Bianchi, 1988; Perez-Ruzafa et al., 2008). These regions have some particular features, such as shallowness, relative isolation from the open sea, coastal barriers that maintain some communication channels or inlets, and the presence of boundaries with strong physical and ecological gradients (UNESCO, 1981).
I surveyed the some examples of phytoplankton in the surface and subsurface at Jukrim-ri, Georyu-meon, Tongyeong-si, Gyeongsangnam-do. Red tides usually occur along the south coasts near to this area in late summer and autumn (Son et al., 2011). Most red tides along the South Korea coast are caused by a group of phytoplankton known as dinoflagellates (Lee et al., 2002). Therefore, the present study aimed to examine the taxonomic structure of phytoplankton to provide preliminary information at Jukrim-ri which was characterized by tidal regimes ensuring high openness and low water turnover times at high tides. I describe more in details taxonomic composition of diatoms about spatial and temporal variability of phytoplankton.
Material and methods
Sampling of phytoplankton
Phytoplankton samplings were conducted at seven stations at Jukrim-ri, Georyu-meon, Tongyeong-si, Gyeongsangnam-do (Fig. 1). Sampling periods were 28 January, 14 April, 03 August, and 27 October 2013. Two step samples from the surface layer (1 m depth) to basal layer (20 m depth) were collected by 5 liter Niskin bottles and preserved with acidified Lugol solution.
Water bottles contain all but the rarest organisms in the water mass sampled and include the whole size spectrum from the largest entities (Tomas, 1997). Quantitative phytoplankton collections as required quantities of water were collected from the desired depth (Sournia, 1978).
Identification of phytoplankton
Identification of diatoms in water samples is usually best done by using phase contrast optics (Tomas, 1997; Sournia, 1978). Diatoms like Rhizosolenia with a pervalvar axis longer than the cell diameter or the apical axis turn girdle side upwards. Colony types like Chaetoceros, Fragilariopsis and Thalassiosira are normally seen in girdle view in a water mount. Diatoms like Thalassionema, Asterionellopsis and Pseudo-nitz.schia show either valve or girdle side. Cylindrical and discoid diatoms are readily recognized by the general circular outlines in valves view. When the cells are viewed properly the next step is to look for special features like setae in Chaetoceraceae, shape of linking processes in Skelotonema and in unpreserved material, organic threads from the valve in Thallassiosiraceae.
Frustular elements cleaned of organic material may also be oriented in various ways in a permanent mount (Tomas, 1997). Flattened valves with a low mantle will usually be seen in valve view (some Coscinodiscus spp., most Navicula spp.), while valves with a high mantle and protuberances may appear in girdle view (Eucampiaand Rhizosolenia). Lightly silicified bands shaped as those in Rhizosolenia and Stephanopyxis often lie with girdle side up.
Cell count
The enumeration of phytoplankton is done by various counting chambers, however, the most commonly used counting chamber is Sedgwick Rafter cell (Sournia, 1978). The counting cell is filled with the plankton sample and placed on the mechanical stage of the microscope. Then the counting cell is left for about half-an-hour for proper sedimentation. The organisms are then counted from one corner of the counting cell to the other.
Biotic indices
Shannon-Weaver index of diversity (Shannon and Weaver, 1963): the formula for calculating the Shannon diversity index (H’) is
H’ = - E pi ln pi
pi = the proportion of important value of the ith species (pi = ni / N, ni is the important value index of ith species and N is the important value index of all the species).
N1 = eH’
180 • Man Kyu Huh
Fig. 1 .The seven stations at Jukrim-ri, Georyu-meon, Tongyeong-si, Korea.
N2 = 1/X
Where X (Simpson’s index) for a sample is defined as
. = _ ni(ni-l)
X L N(N-1)
The species richness of phytoplankton was calculated by using the method, Margalefs indices (R1 and R2) of richness (Magurran, 1988).
E4 =
1/X
eH’
E4 =
1/X-1
eH’-1
В-diversity index was calculated using the method of Tuomisto (2010)
В = y/a
R1 =
R2 =
S-1
ln(«)
S
Vn
S is the total number of species in a community and n is the total number of individuals observed.
Evenness index was calculated using important value index of species (Pielou, 1966; Hill, 1973).
E1 =
H’
ВД
E2 =
eH’
T
E2 =
eH’-1
's-і
Here у is the total species diversity of a landscape, and a is the mean species diversity per habitat.
The homogeneity ofvariance or mean values to infer whether differences exist among the stations samples or seasons was tested. Namely, the tests (F, chi-square, etc.) of homogeneity used to make a conclusion about whether several stations have the same distribution (Zar, 1984).
Spatial correlation coefficients and cluster analysis
Cluster analysis was applied to generate dendrograms (group average method), based on the Jaccard distance matrixes among samples. Calculation of indices and cluster analysis were performed using Primer 6.1.9 software (Primer-E Ltd.). The correlation coefficient is calculated for estimates of the relationships between geographic distance and the phytoplankton community. Except where
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181
Table 1. The composition and biomass at water surface (unit: x100 cells/l).
Species Season Total %
Jan Apr Aug Oct
Chrysophyceae
Dictyocha fibula 1 2 11 14 0.01
Dictyocha speculum 3 6 22 14 45 0.03
Octactis octonaria 1 1 0.00
Eugenophyceae
Eutreptiella gymnastica 6 123 44 2 175 0.10
Bacillariophyceae
Asterionellopsis glacialis 3 29 117 3 152 0.09
Bacteriastrum hyalinum 471 471 0.28
Chaetoceros affinis 3481 22 16 3519 2.07
Chaetoceros costatus 4 13 66 83 0.05
Chaetoceros compressus 64 5 69 0.04
Chaetoceros curvisetus 4933 7217 12150 7.14
Chaetoceros danicus 112 367 13321 3987 17787 10.45
Chaetoceros debilis 1230 587 26 1843 1.08
Chaetoceros decipiens 11327 5 19 11351 6.67
Chaetoceros didymus 205 3479 2648 3901 10233 6.01
Chaetoceros lorenzianus 23 16 74 55 168 0.10
Chaetoceros pendulus 43 106 8 6 163 0.10
Chaetoceros peruvianus 2 0.00
Chaetoceros pseudocrinitus 45 4561 310 168 5084 2.99
Coscinodiscus gigas 2 2 4 8 0.00
Coscinodiscus wailesii 17 17 0.01
Coscinodiscus asteromphalus 5 5 0.00
Dactyliosolen fragillisimus 34 55 9104 3648 12841 7.54
Dictylum brightwellii 7 4 11 0.01
Guinardia delicatula 88 104 6613 42 6847 4.02
Lauderia annulata 5 9 45 49 0.03
Leptocylindrus danicus 2106 7871 1244 2108 13329 7.83
Leptocylindrus minimus 62 24 43 31 160 0.09
Melosira juergensii 3 2 5 0.00
Melosira moniliformis 48 3 162 213 0.13
Nitzschia sigma 4 4 0.00
Paralia sulcata 22 18 6 2 48 0.03
Pleurosigma angulatum 5 3 13 52 73 0.04
Pseudo-nitzschia pungens 7025 10467 13120 5750 36347 21.39
Pseudo-nitzschia seriata 28 19 47 0.03
Rhizosolenia hebetata 16 16 0.01
Rhizosolenia setigera 1258 667 129 1684 3738 2.20
Skeletonema costatum 1698 4820 15025 10368 31911 18.74
Thalassiosira angulata 225 241 55 47 568 0.33
Thalassiosira rotula 45 22 67 0.04
Thalassiosira nordenskioeldii 9 9 0.01
Dinophyceae
Ceratium furca 24 25 4 53 0.03
Ceratium fusus 3 147 159 22 331 0.19
Ceratium trichoceros 3 3 0.00
Gyrodinium spirale 2 2 0.00
Katodinium glaucum 8 15 23 0.01
Protoperidinium bipes 1 1 0.00
Prorocentrum bronchi 34 103 137 0.08
Protoperidinium leonis 3 3 0.00
Protoperidinium pellucidum 4 9 13 0.01
Scrippsiella trochoidea 16 22 6 44 0.03
Total 16516 45849 67960 39918 170243 100
Species No. 29 33 40 34 50
182 • Man Kyu Huh
stated otherwise, statistical analyses were performed using the SPSS software (Release 21.0) (IBM Corp. Released, 2012).
Results
Composition and biomass of species
The phytoplankton community at Jukrim-ri on 2013 was identified with 54 taxa, representing four classes (Table 1). Diatoms (Bacillariophyceae) exhibited the greatest diversity with 38 taxa identified, followed by dinoflagellates (Dinophyceae, 12 taxa); Cryptophyceae with three taxa, and Eugenophyceae represented by a single taxon.
On January 2013, a total of 36 taxa were identified: Bacillariophyceae 26 taxa, Dinophyceae 6 taxa, three Cryptophyceae taxa, and one Eugeno-phyceae taxon. On April 2013, a total of 37 taxa were identified: Bacillariophyceae 27 taxa, Dino-phyceae 7 taxa, two Cryptophyceae taxa, and one Eugenophyceae taxon. On August, a total of 48 taxa were identified: Bacillariophyceae 32 taxa, Dinophyceae 10 taxa, one Cryptophyceae taxon, and one Eugenophyceae taxon. On October, a total of 38 taxa were identified: Bacillariophyceae 28 taxa, Dinophyceae 7 taxa, two Cryptophyceae taxa, and one Eugenophyceae taxon.
Phytoplankton abundance on 2013 season of Jukrim-ri ranged from 1.0 x 102 to 58,210 x 102 cells/l for four seasons. Mean biomass per season was 5,087 x 102 cells/l with 54 taxa.
Composition of species at water surface
The phytoplankton community at basal layer on January was also very diverse (Table 1). On January 2013, a total of 29 taxa were identified at surface layer: Bacillariophyceae 21 taxa, Dinophyceae 4 taxa, three Cryptophyceae taxa, and one Eugeno-phyceae taxon. The most dominant species was Pseudo-nitzsehia pungens. The relative dominant species were Chaetoeeros affinis, Leptoeylindrus danicus, Rhizosolenia setigera, and Skeletonema eostatum at seven stations. Biomass of species at water surface on January was varied from 100 cells/l to 702,500 cells/l (Fig. 2).
On April 2013, a total of 33 taxa were identified: Bacillariophyceae 23 taxa, Dinophyceae 7 taxa, two Cryptophyceae taxa, and one Eugenophyceae taxon. The station B was characterized by high phytoplankton biomass. The relative dominant species were five diatoms taxa (Chaetoeeros decipiens, Chaetoeerospseudocrinitus, Leptoeylindrus danicus,
Pseudo-nitzschia pungens, and Skeletonema costa-tum) at seven stations.
On August, a total of 40 taxa were identified: Bacillariophyceae 32 taxa, Dinophyceae 6 taxa, one Cryptophyceae taxon, and one Eugenophyceae taxon. The relative dominant species were six diatoms taxa (Chaetoeeros curvisetus, Chaetoeeros danicus, Dactyliosolen fragillisimus, Guinardia delicatula, Pseudo-nitzschia pungens, and Skeletonema eostatum) at seven stations.
On October, a total of 34 taxa were identified: Bacillariophyceae 28 taxa, Dinophyceae 3 taxa, two Cryptophyceae taxa, and one Eugenophyceae taxon. The station B was characterized by high phytoplankton biomass and station G was lowest. The relative dominant species were six diatoms taxa (Chaetoeeros curvisetus, Chaetoeeros danicus, Chaetoeeros didymus, Dactyliosolen fragillisimus, Pseudo-nitzschia pungens, and Skeletonema costa-tum) at seven stations.
Composition of species at basal layer
A total of 43 taxa were identified at basal layer: Bacillariophyceae 31 taxa, Dinophyceae 9 taxa, two Cryptophyceae taxa, and one Eugenophyceae taxon. Diatoms and dinoflagellates were the most diverse groups. Centric and pennate diatoms accounted for the highest diversity among of them.
On January, a total of 25 taxa were identified: Bacillariophyceae 20 taxa, Dinophyceae 3 taxa, Cryptophyceae and Eugenophyceae, each of one taxon. The station C was characterized by high phytoplankton biomass. The most dominant species was Rhizosolenia setigera. Biomass of species at basal layer on January was varied from 100 cells/l to 69,700 cells/l (Fig. 2).
On April, a total of 28 taxa were identified: Bacillariophyceae 24 taxa, Dinophyceae 2 taxa, Cryptophyceae and Eugenophyceae, each of one taxon. The station C was characterized by high phytoplankton biomass. The relative dominant species were three Dinoflagellate taxa (Chaetoeeros danicus, Leptoeylindrus danicus, and Pseudo-nitzschia pungens) at seven stations.
On August, a total of 38 taxa were identified: Diatoms 28 taxa, Dinoflagellate 8 taxa, Cryptophy-ceae and Eugenophyceae, each of one taxon. The station A was characterized by high phytoplankton biomass. The relative dominant species were six diatoms taxa (Chaetoeeros curvisetus, Chaetoeeros danicus, Dactyliosolen fragillisimus, Leptoeylindrus danicus, Pseudo-nitzschia pungens, and Skeletonema eostatum).
Total Proportion biomass,
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Fig. 2. spatial variability of phytoplankton community. Upper dendrogram of the cluster analysis based on the dissimilarity among seven stations. Lower is the compositions of dominant species in different phytoplankton associations within area outlined by the cluster analysis.
184 • Man Kyu Huh
On October, a total of 32 taxa were identified: Bacillariophyceae 24 taxa, Dinophyceae 5 taxa, two Cryptophyceae taxa, and one Eugenophyceae taxon. The station A was characterized by high phytoplankton biomass and station B was lowest. Skeletonema costatum was the most dominant species at seven stations. The relative dominant species were four diatoms taxa (Chaetoceros curvisetus, Chaetoceros danicus, Pseudo-nitz,schiapungens, and Skeletonema costatum).
Cluster analysis
Analysis of seasonal variability within the phytoplankton community was performed using the hierarchical clustering using the Jaccard Index of similarity. In the beginning of the year (January), all stations were more than 65% of similarity, as shown in Fig. 3. Water surface and basal layer showed a clear distinction excluding Stations B and C (data not shown). Stations A and B formed same clustered (cluster-1). They are mainly consisted of Pseudo-nitzschia pungens, Leptocylindrus danicus, and Skeletonema costatum which were dominant in cluster-1 on winter. In spring, the plankton community consisted mainly of Chaetoceros decipiens and Pseudo-nitzschia pungens (cluster-2). Relative remote stations (F and G) were characterized by low similarity between stations or two layers in depths and minimal values of species diversity and community evenness. In late autumn, the phytoplankton community consisted mainly of Chaetoceros curvisetus and Skeletonema costatum.
Spatial and temporal variability of phytoplankton
Water surfaces were shown with the relative high individual density or abundance across areas (Tables 1 and 2). However, Shannon-Weaver indices of diversity of water surfaces were similar to those of basal layers except January and October (Table
3). Richness indices were same trend. In addition, evenness indices ofbasal layers were similar to those of basal layers. Shannon-Weaver index of diversity also varied among the stations and season with 1.906 (January) and 2.038 (August).
Assessments ofthe seven spatial and four seasonal variability of the structure of the phytoplankton community were presented in Table 4. Although the numbers of species with absolute occurrence were existed in stations and season, mean paired similarity between both the species composition within stations and within seasons were high. For
Fig. 3. Simple linear regression in the phytoplankton community along a North-South longitude gradient. The vertical lines represent the SD.
the community as a whole, the values of B-diversity were the low (1.139 for water surface within seven stations and 1.109 for basal layer) or common (1.382 for water surface within four seasons and 1.431 for basal layer). The parameters paired similarity between season and stations testified (Table 5). There were high taxonomic homogeneity of the phytoplankton community in between four seasons and similar trends found in seasonal development of phytoplankton at depths ofsame stations. However, size distribution of abundance and biomass showed a statistically significant west-east different (p <0.05, Table 6).
In order to assess macro-scale spatial variability of the phytoplankton community at Jukrim-ri, I analyzed distributions of species richness and diversity of large taxonomic groups as well as phytoplankton composition along a longitudinal gradient. Fig. 3 showed the biomass plotted against longitude. Margalef’s index gradually decreased from south to north. This trend conformed to a linear regression model, which described 67% ofthe spatial variability for mean species biomass (r2 = 0.55).
Phytoplankton composition from western areas near inland was less diverse than that of southern sea. This decreasing trend was supported mainly by an increase of phytoplankton diversity. The mean number of species within the southern waters was 35 taxa and northern was 24. The portion of dinoflagellates in the phytoplankton decreased exponentially along the west-east gradient (Fig. 4). The diatom/dinoflagellate ratio was equal to 0.712 within western sea (Stations A, B, C); whereas it was reduced to 0.834 in middle waters, and even further to 1.014 in open sea.
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Table 2. The composition and biomass at basal layer (unit: cells/l).
Species Season Total %
Jan Apr Aug Oct
Chrysophyceae
Dictyocha fibula 2 2 0.00
Dictyocha speculum 3 14 5 8 30 0.03
Eugenophyceae
Eutreptiella gymnastica 14 102 31 2 149 0.14
Bacillariophyceae
Asterionellopsis glacialis 12 25 784 16 837 0.80
Bacteriastrum hyalinum 338 338 0.32
Chaetoceros affinis 34 2 36 0.03
Chaetoceros costatus 22 14 36 0.03
Chaetoceros compressus 45 45 0.04
Chaetoceros curvisetus 3 629 7128 3012 10772 10.31
Chaetoceros danicus 45 7147 3685 4109 14986 14.35
Chaetoceros debilis 1167 254 1421 1.36
Chaetoceros decipiens 13 21 14 59 107 0.10
Chaetoceros didymus 106 895 1514 135 2650 2.54
Chaetoceros lorenzianus 18 14 8 40 0.04
Chaetoceros mitra 27 0 27 0.03
Chaetoceros pendulus 66 113 246 20 445 0.43
Chaetoceros pseudocrinitus 556 1244 18 1818 1.74
Coscinodiscus gigas 5 6890 0.01
Dactyliosolen fragillisimus 36 150 4571 2133 162 6.60
Dictylum brightwellii 142 3 17 0.16
Dictylum pumila 3 2 6 11 0.01
Guinardia delicatula 66 124 29 15 234 0.22
Lauderia annulata 44 47 91 0.09
Leptocylindrus danicus 1245 7800 4214 1365 14624 14.00
Melosira moniliformis 26 33 59 0.06
Nitzschia sigma 14 14 0.01
Paralia sulcata 29 24 65 118 0.11
Pleurosigma angulatum 6 11 2 23 42 0.04
Pseudo-nitzschia pungens 1017 6141 9237 3783 20178 19.32
Pseudo-nitzschia seriata 69 12 239 28 348 0.33
Rhizosolenia setigera 697 108 101 38 944 0.90
Skeletonema costatum 1315 2348 16147 16147 26299 25.18
Thalassiosira angulata 26 107 102 58 293 0.28
Thalassiosira rotula 12 3 103 7 125 0.12
Dinophyceae
Ceratium furca 16 11 27 0.03
Ceratium fusus 6 45 11 24 86 0.08
Gyrodinium spirale 3 3 0.00
Protoperidinium bipes 9 9 0.01
Prorocentrum bronchi 61 23 0.08
Prorocentrum dentatum 12 4 16 0.02
Prorocentrum minimum 2 8 5 15 0.01
Protoperidinium leonis 2 12 14 0.01
Protoperidinium pellucidum 14 5 3 22 0.02
Total 4838 27811 50336 21467 104452 100
Species No. 25 28 38 32 44
Discussion
Diatoms were dominated phytoplankton abundance numerically as well as in biomass, accounting for 88.6% of the latter depending on season. Phytoplankton concentrations, which were obtained in this study, were within the range of those reported previously (Al-Zaidan et al., 2006). Both
the spatial and temporal components contributed to the variability of the phytoplankton community at Jukrim-ri in Tongyeong-si. During the winter months, the northern area was characterized by the lowest concentrations of phytoplankton. It was strongly correlated with temperature from cold river introduction of inland, whereas the highest phytoplankton concentrations were observed
186 • Man Kyu Huh
Table 3. Biological diversity of phytoplankton at water surface (W.S.) and basal layer (B.L.).
Indices Season
Jan Apr Aug Oct
W.S. B.L. W.S. B.L. W.S. B.L. W.S. B.L.
Diversity
H' 1.680 2.132 1.989 1.808 2.032 2.044 2.083 1.803
N1 5.367 8.434 7.310 6.100 7.621 7.725 8.031 6.069
N2 3.870 5.003 5.870 4.566 6.284 5.583 6.514 5.023
Richness
R1 2.883 3.193 2.891 2.635 3.505 3.418 3.115 3.073
R2 0.226 0.583 0.154 0.167 0.153 0.169 0.170 0.206
Evenness
E1 0.499 0.662 0.569 0.543 0.551 0.562 0.591 0.520
E2 0.185 0.337 0.222 0.218 0.191 0.203 0.236 0.190
E3 0.156 0.310 0.197 0.189 0.170 0.182 0.213 0.164
E4 0.721 0.811 0.803 0.748 0.823 0.723 0.811 0.828
E5 0.657 0.784 0.772 0.699 0.797 0.681 0.784 0.794
in open sea. The minimum diversity level was associated with the winter months, whereas the maximum was in autumn (October). Phytoplankton species richness gradually increased eastward, with the lowest richness recorded in the waters closest to the coastal-side (Stations B, C, and D) and the highest towards the southern sea (Stations F, G). These east-west differences in the phytoplankton community have been reported for the Pacific (Magurran, 1988; Harrison et al., 1999; Shiomoto and Hashimoto, 2000). This east-west difference in the phytoplankton community may reflect heterogeneity in the grazing pressure of the zooplankton community (Mackas and Tsuda, 1999; Takahashi et al., 2008) or temperature and magnitude of the spring phytoplankton bloom (Tsuda et al., 2004). In addition, these north-south transects difference in the phytoplankton community has been reported abundance and biomass of mesozooplankton along in the North Pacific (Matsuno and Yamaguchi, 2010).
Most of the time, marine waters are characteristically blue or green and reasonably clear. In the temperate waters of the northern latitudes, water is seldom as clear as seen in tropical areas, where visibility can exceed 50-75 feet (Verlencar, 2004). In temperate waters, the limits of visibility or murkiness are usually the result of algae in the water. However, in some unusual cases, a single microalgal species can increase in abundance until they dominate the microscopic plant community and reach such high concentrations that they discolor the water with their pigments, these “blooms” of algae are often referred to as a “Red tide”. Although referred to as Red tides, blooms are not only red, but can be brown, yellow, green, or milky in color (Son et
al., 2011). Adverse effects can likewise occur when algal cell concentrations are low and these cells are filtered from the water by shellfish such as clams, mussels, oysters, scallops, or small fish. Many animals at higher levels of the marine food chain are impacted by harmful algal blooms. Toxins can be transferred through successive levels of the food chain, sometimes having lethal effects.
Euglenophyceae (Eutreptiella gymnastiea) was found in the four stations on January and the all stations on April in this study (Tables 1 and 2) to be the major bloom formers (Son et al., 2011). Chaetoeeros curvisetus, Leptoeylindrus danicus, Skeletonema costatum, Pseudo-nitzschia pungens, Navicula spp. of Bacillariophyceae were also found in most stations and seasons to be the major bloom formers (Son et al., 2011). Ceratiumfurca, Ceratium fusus, Prorocentrum dentatum, Prorocentrum minimum, Scrippsiella trochoidea of Dinophyceae were found to be the major bloom formers.
Table 4. Space-time variability of the phytoplankton community structure.
Attributes of community structure Spatial variability (7 stations) Temporal variability (4 seasons)
Water surface Basal Layer Water urface Basal Layer
Mean number of species per sample 19 12 34 31
Number of species with absolute occurrence 5 2 12 8
Number of samples containing all species 5 2 19 18
Occurrence Index (P-diversity) 1. 139 1.109 1.382 1.431
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Fig. 4. Percentage contribution of phytoplankton groups to the total species richness plotted against geographical distances.
I expect that this work may provide valuable information of interest to later ecological studies. Definitive identification of the principal phytoplankton species assumes very importance also at the light of the potentially serious and harmful effects associated with bloom events.
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Table 6. Test of homogeneity of the phytoplankton community between the seven stations at Jukrim-ri. Upper diagonal is the degree of significant for p value and low diagonal is t value.
Station A B C D E F G
A _ p>0.05 p>0.05 p<0.01 p<0.01 p<0.01 p<0.01
B 0.023 - p>0.05 p<0.01 p<0.05 p<0.01 p<0.01
C 0.301 0.403 - p>0.05 p<0.05 p<0.01 p<0.01
D 3.237 3.119 0.940 - p>0.05 p<0.05 p>0.01
E 3.525 1.126 2.697 1.043 - p>0.05 p<0.05
F 3.640 3.203 3.552 2.890 1.915 - p>0.05
G 3.457 3.774 3.542 3.255 2.006 -0.089 -
188 • Man Kyu Huh
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Address for correspondence: Man Kyu Huh. Department ofMolecular Biology, College ofNatural Sciences, Dong-eui University 995 Eomgwangno, Busanjin-gu, Busan 614-714, Korea; e-mail: [email protected]
