344
Chiang Mai J. Sci. 2013; 40(3)
Chiang Mai J. Sci. 2013; 40(3) : 344-355
http://it.science.cmu.ac.th/ejournal/
Contributed Paper
Phytoplankton as a Bio-indicator of Water Quality in
the Freshwater Fishing Area of Pak Phanang River
Basin (Southern Thailand)
Amphorn Sakset [a] and Wanninee Chankaew [b]
[a] Surat Thani Inland Fisheries Development and Research Center, Thakham Sub-district, Punpin District,
Surat Thani 84130, Thailand.
[b] Department of Fishery, Faculty of Agriculture, Rajamangala University of Technology Srivijaya,
Nakhon Si Thammarat 80110, Thailand.
Author for correspondence; e-mail: [email protected], [email protected]
Received: 27 February 2012
Accepted: 7 November 2012
ABSTRACT
Phytoplankton in the freshwater fishing area of Pak Phanang River Basin (PPRB),
Nakhon Si Thammarat Province in southern Thailand was monitored at three different
habitat sites over three different seasons in 2006, in order to assess water quality condition
and suggest any fishery management measures. The water quality parameters still remained
suitability for inland fisheries. A total of 62 genera and an average density of 10,020
units L-1 of phytoplankton belonging to six divisions were identified. The third-most
abundant genera were Peridinium sp, Protoperidinium sp which most related to velocity
and Trachelomonas sp. which most related to ammonia nitrogen. Shannon-Wiener
diversity index showing that phytoplankton diversity was generally in medium level
and implied that water quality condition was moderately-polluted. Also, the AARL-PP
score assessed that the water quality condition in the area was considered meso-eutrophic
and moderately-polluted, but it was still suitable for aquatic animal growth and survival.
Furthermore, fishery management through water monitoring should be regularly
conducted. Restocking aquatic animals/fishes should be implemented at sites and times
with the best condition for survival.
Keywords: phytoplankton, bio-indicator, water quality, freshwater, Pak Phanang river
basin
1. INTRODUCTION
Phytoplankton has been long used as an
effective water bio-indicator [1-2] that is
sensitive to environmental changes [1]. Some
species thrive in highly eutrophic waters,
whereas some species are very sensitive to
environmental changes [1]. Rivers with
weak water currents always contain
phytoplankton in division Chlorophyta,
such as Pandorina and Eudorina, and in
division Euglenoplyta, such as Euglena and
Trachelomonas [3]. Melosira and Cyclotella
are usually found in clean water, whereas
Nitzschia, Microcystis and Aphanizomenon
are usually found in polluted waters [1].
Chiang Mai J. Sci. 2013; 40(3)
Chlamydomonas, Euglena, Scenedesmus [4]
and Microcystis [4-5] are indicators of
eutrophic waters. Aphanizomenon,
Microcystis and Ceratium are usually found
in high phosphate waters, while Anabaena
is found in waters with slight nitrogen
content [6]. Palmer [2] listed sixty genera
of plankton which are the most organic
pollution-tolerant. Euglena, Oscillatoria,
Chlamydomonas, Scenedesmus, Chlorella,
Nitzschia, Navicula, and Stigeoclonium are
the top eight genera which can indicate
organic pollution in the waters. Rott et al.
[7] used the Shannon diversity and evenness
indices of phytoplankton to assess water
conditions in tropical Asian water bodies.
They were classified as eutrophic level in
Thailand. Moreover, Peerapornpisal et al.
[8] developed a method to assess the water
quality in water bodies by using dominant
phytoplankton scoring system, i.e. AARLPP score which is a simple evaluation
method without chemical requirement.
The results were more than 90% consistent
with physical and chemical parameters.
Pak Phanang River Basin (PPRB) is
located along the southeastern seashore of
Thailand. Its area covers around 3,183 km2.
In 1995, the Uthokvibhajaprasid Sluice gate was
constructed on Pak Phanang River at Hu Long
Sub-District (about 6 km from the seashore),
Pak Phanang District, Nakhon Si Thammarat
Province as a Royal Initiative Project in an
effort to provide freshwater for agriculture
and household purposes, and to prevent
saltwater intrusion into agricultural areas [9].
However, the dam has affected fishing areas
of the Pak Phanang River up to 100 km
upstream due to loss of tidal influences and
associated marine and brackish waters,
which has caused a decrease in fishery
produce and thus in income of local people
[10]. Before the dam construction, people
around this river gained benefit from the
345
influence of the tide in terms of brackish
and marine fishery production. However,
the tidal area has become a semi-lotic
freshwater area since the dam began
operating in 1999. Aquatic biodiversity and
fish production have been reduced. Some
fish species have disappeared, particularly
brackish and marine species. The dam has
reduced biodiversity and disturbed fish
breeding [11]. Water quality is also low as
the consequence of agricultural residue
accumulation [11]. So, direct and indirect
impacts of the dam have been affecting the
way of living of local people, especially
fishermen [12].
This paper illustrates the use of
phytoplankton as a bio-indicator to assess
water quality conditions and imply any fishery
management measures in the freshwater
fishing area of the Pak Phanang River Basin
which was seriously affected by the dam
construction.
2. MATERIALS AND METHODS
The study was conducted over three
seasons in three different ecosystems in the
freshwater fishing area, about 100 km
upstream of the dam site in 2006. The seasons
were covered dry season (February and
March), early rainy season (June and July), and
heavy rainy season (October and December).
During the study period, the sluice gates were
normally closed during the dry and rainy
seasons, and opened during the heavy rainy
season. The ecosystems were divided into
downstream site (nearby the dam), middlestream site (main tributary), and upstream
site (peat swamp) (Figure 1).
In each study site, water samples were
collected for measurements based on
APHA, AWWA and WPCP [1] at the
surface and 0.5-1 m above the ground with
three replications (left, middle, and right
side of the river). Water temperature was
346
Chiang Mai J. Sci. 2013; 40(3)
Figure 1. Survey sites of phytoplankton in the freshwater fishing area, PPRB, 2006
(S1 = Downstream site, S2 = Middle-stream site, and S3 = Upstream site).
measured with a thermometer. Water
transparency was measured with a blackwhite 20 cm diameter Secchi disk. Salinity
was measured with a salinometer.
Dissolved oxygen (DO) was measured by
DO meter. Ammonia nitrogen was
measured by Nessler Method. Nitrate
(NO-3-N) was measured by the Cadmium
Reduction Method. Orthophosphate (PO+4P) was measured by the Ascorbic Acid.
Velocity was measured by flow meter. Water
dept was measured by depth gauge.
Phytoplankton samples were collected
along with the water quality measurements
using by the Kemmerer water sampler. Water
samples were filtered through a plankton net
with pore size of 20 micron. Filtered samples
were preserved in 95% alcohol (equal volumes
of alcohol and water sample) with the
addition of 1 ml L-1 saturated copper sulfate
solution (CuSO4) to retain color [1]. The
samples were then transported to the
laboratory for identification of genera and
counting the number of phytoplankton units
of each genus by using a Sedgwick-Rafter
counting chamber under a compound
microscope following the methods in APHA,
AWWA and WPCP [1], Wongrat [13], and
Prescott [4].
Univariate analysis; mean and standard
deviation (SD) was applied to describe and
evaluate the variations of the water quality
parameters among sampling sites and seasons,
and derived values were compared with
standard values for fisheries in Thailand [1516], and compared with previous studies
before the dam construction (1996-1999) [17];
diversity indices including number of genera,
abundance, richness index, evenness index and
Shannon-Wiener’s diversity index (loge) were
used to assess diversity level of phytoplankton
and to see trends of change along with the
sections of the river and seasons, as well as
compared with previous studies before the
dam operation (1996-1999) [17]; one-way
analysis of variance (ANOVA) was performed
to determine significant differences in water
quality parameters and phytoplankton
abundance among sites and seasons. Multiple
comparisons using LSD test were performed
to identify significantly different means among
sites and seasons at the 0.05 level.
Multivariate indices analysis; cluster
and Ordination Multi-Dimensional Scaling
(MDS) analyses were used to classify
similarity of water quality parameters and
Chiang Mai J. Sci. 2013; 40(3)
phytoplankton communities among
seasons and sites. The cluster and MDS
analyses aimed to find groupings of
similarities of samples among different sites
and seasons such that samples within a
group are more similar to each other than
samples in different groups. The resulting
cluster was shown in a tree-like diagram
called dendrogram and MDS was shown
as a map. Both the dendrogram and map
were constructed based on standardized
Euclidean distances matrix for the water
variables and Bray-Curtis similarity matrix
(fourth root transformation) for
phytoplankton communities; a similarity
percentage-species contribution (SIMPER)
analysis was applied to test the water
parameters and genus affecting group
similarity, with Primer program Version
5 for Windows, based on Clark and
Warwick [14]; Canonical Correspondence
analysis (CCA) was carried out to assess the
relationship between 10 dominant genera
(96% of total abundance) and water quality
parameters by CANOCO version 4.5. The
result was showed by CCA map. In
addition, AARL-PP score was also used to
assess the mass of water quality based on
Peerapornpisal et al. [8].
3. RESULTS AND DISCUSSION
The water quality variables relating to
phytoplankton, i.e. water temperature, water
transparency, DO, ammonia and NO-3-N, had
average values that were still in the standard
range for class 2 [16] and inland fisheries [1516], excepted PO+4-P, which was less than the
standard range. The salinity value was generally
suitable for freshwater phytoplankton genera.
Velocity was generally very slow, and water
dept of study area was shallow (Table 1).
After the dam began operating, the salinity
of upper dam area had decreased, and the
water became freshwater condition because
347
the dam blocked seawater moving up the river
(tidal water). The salinity decreasing related to
increase of phytoplankton density which also
led to transparency decrease. Also, ammonia
was higher than before the dam operation [17]
(Table 1) caused to phytoplankton increment.
The higher ammonia might be a result of
more sedimentation and nutrient loading
[18] in the area. However, the result of
ANOVA test showed that there was no
significant difference among sites (P>0.05)
in temperature, transparency, ammonia,
NO-3-N, PO+4-P, DO and velocity. In contrast,
salinity and water dept showed significant
difference (P<0.05) among sites. The result
of LSD test showed that the salinity had the
highest value at the down and middle stream
sites (P<0.05) where were occasionally
affected by sea water when opening the sluice.
The water dept had higher value at the
upstream (Table 1). In terms of season,
ANOVA showed that water depth was similar
(P>0.05) among seasons but there were
significant differences among seasons (P<0.01)
in temperature, transparency, ammonia,
NO-3-N, PO+4-P, DO, velocity, and salinity.
The LSD test (P<0.05) showed that velocity
had the highest values during the early rainy
season, while ammonia, NO-3-N and PO+4-P
showed highest concentration during the dry
season. The salinity, temperature and
transparency showed highest concentration
during the dry and early rainy seasons. DO
had the highest value during the early rainy
season which related to phytoplankton
abundance.
The results of cluster and MDS analyses
to test similarity of the water quality
parameters variations among seasons and sites
showed two groups by season over all sites;
1) dry season and early rainy seasons, and 2)
heavy rainy season (Figure 2). This suggests
the changes that they might be related to
precipitation and drainage of water gate. The
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Chiang Mai J. Sci. 2013; 40(3)
gate was normally closed during the dry
season and early rainy season to store
freshwater for irrigation and water supply, and
was opened in the heavy rainy season to
control flooding [9]. Also, the SIMPER
analysis showed that the transparency and
DO indicated similarity within the each
group at contributing greater than 5% of
the similarity. However, their values in first
group were higher than another.
Table 1. Variations of water quality in freshwater fishing area, PPRB, 2006 and comparison
of variables before damming and comparison with standard values for fisheries (* <0.5 ppt
= freshwater, 0.5-25 ppt = Brackish water; different superscripts in a column indicated significant
difference at P<0.05).
Parameters
Sites/seasons Dry season
Early rainy
season
Before the
Heavy rainy
dam
Mean + SD
season
operation
[17]
Temperature Downstream 29.70+0.37 29.62+0.49 28.62+0.51 29.24+0.69
Middle-stream 30.41+0.93 30.47+0.50 29.15+1.02 29.93+1.05
( )
Upstream
29.90+0.59 30.24+0.51 28.52+1.42 29.46+1.25
Mean + SD 30.00+0.71a 30.11+0.61a 28.76+1.06b 29.54+1.05 30.22+1.44
Transparency Downstream 71.50+28.75 72.90+34.54 37.25+14.63 58.27+30.17
Middle-stream 68.38+29.52 74.30+36.23 33.83+19.02 56.53+32.63
(cm.)
Upstream
61.88+20.34 63.40+9.85 33.75+7.28 51.13+18.75
Mean + SD 67.25+24.36a 70.20+27.73a 34.94+13.70b55.31+27.38 84.40+46.20
Downstream 0.31+0.13
0.12+0.03
0.32+0.16 0.25+0.15
Ammonia
Middle-stream 0.36+0.16
0.08+0.02
0.27+0.10 0.23+0.15
nitrogen
Upstream
0.51+0.24
0.22+0.33
0.23+0.06 0.30+0.26
(mg L-1)
Mean + SD 0.39+0.20a 0.14+0.20b 0.27+0.12c 0.26+0.19 0.10+0.12
0.03+0.03
0.14+0.06 0.12+0.11
Downstream 0.21+0.16
NO-3-N
0.13+0.15
0.13+0.04 0.15+0.12
Middle-stream 0.20+0.16
(mg L-1)
Upstream
0.22+0.18
0.08+0.07
0.10+0.03 0.12+0.11
Mean + SD 0.21+0.16a 0.08+0.10b 0.12+0.05b 0.13+0.11 0.23+0.18
Downstream 0.022+0.003 0.002+0.001 0.002+0.000 0.009+0.002
PO+4-P
Middle-stream 0.018+0.004 0.002+0.001 0.002+0.000 0.007+0.002
(mg L-1)
Upstream
0.022+0.012 0.002+0.000 0.002+0.000 0.009+0.005
Mean + SD 0.021+0.007a 0.002+0.001b 0.002+0.000b0.008+0.004 0.018+0.010
Salinity (ppt) Downstream 1.00+1.07 0.50+0.53 0.00+0.00 0.40+0.70a
Middle-stream 0.63+0.52 0.40+0.52 0.00+0.00 0.30+0.47a
Upstream
0.00+0.00 0.00+0.00 0.00+0.00 0.00+0.00b
Mean + SD 0.54+0.78a 0.30+0.47a 0.00+0.00b 0.25+0.53 4.90+5.86
Downstream 8.56+4.93
9.93+2.07
5.83+1.34 7.92+3.35
DO
Middle-stream 8.00+4.26
8.09+4.56
5.75+2.11 7.13+3.72
(mg L-1)
Upstream
5.29+2.05
6.35+1.29
7.81+2.03 6.65+2.05
Mean + SD 7.28+4.04ab 8.12+3.24 a 6.46+2.05b 7.23+3.13 3.1+0.7
2.1+0.5
2.7+0.6ab
Water depth Downstream 2.9+0.6
Middle-stream 2.2+0.9
1.8+0.7
1.5+0.4
1.8+0.7b
(m)
Upstream
3.5+0.5
3.9+3.4
3.0+1.6
3.5+1.8a
Mean + SD 2.9+0.8
2.9+2.1
2.2+1.1
2.7+1.3
Downstream 0.01+0.01 0.18+0.07 0.04+0.03 0.08+0.04 Water
Middle-stream 0.06+0.04 0.17+0.07 0.08+0.06 0.10+0.06
velocity
0.01+0.00 0.03+0.03 0.11+0.05 0.05+0.03
Upstream
(m s-1)
Mean + SD 0.03+0.03a 0.14+0.09b 0.07+0.05a 0.08+0.06
Standard
for
fisheries
25-32 [15]
30-60 [15]
0.5 [16]
5.0 [16]
0.1-0.2[23]
<0.5* [23]
> 6.0 [16]
-
-
Chiang Mai J. Sci. 2013; 40(3)
349
Figure 2. Normalized Euclidean cluster diagram and MDS of environmental similarity in the
freshwater fishing area, PPRB, 2006 (T1 = Dry season, T2 = Early rainy season, T3 = Heavy
rainy season, S1 = Downstream site, S2 = Middle-stream site, and S3 = Upstream site).
Sixty-two genera of the phytoplankton
belonging to six divisions were found,
having an average density of 10,020 units
L-1. The third-most abundant genera were
Peridinium,
Protoperidinium and
Trachelomonas (Table 2). These genera
usually dominate in nutrient rich waters
[19]. As of this study, all of them were
present at the midstream site during the
early rainy season (closed period). The
dominant genera seem changed before
damming in 1996-1999 which were
Chaetoceros,
Peridinium
and
Trichodesmium [17]. The number of genera
was high at the upstream site during early
rainy season (42) whereas the number of
individuals was high at the midstream site
during early rainy season (55,021
individuals L-1) (Table 2) because of the
abundance of some genera, especially
Peridinium sp. and Protoperidinium sp.
However, the ANOVA showed that there
was no significant difference in abundance
of phytoplankton among sites at P>0.05,
but there were significant differences in
abundance among seasons at P < 0.05, and
LSD test showed that the highest
abundance were during the early rainy
season (P<0.05) (Table 2). The evenness
and Shannon-Wiener diversity indices in
Table 2 were high during almost all seasons
and sites except for the early rainy season
at the downstream site where a lower
number of genera (21) were observed, also
dominated by a few genera i.e. Peridinium
sp., Protoperidinium sp. and Trachelomonas
sp. (Table 2).
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Chiang Mai J. Sci. 2013; 40(3)
Table 2. Divisions, genera and average density (units L-1) of phytoplankton in the freshwater
fishing area, PPRB, 2006 (T1 = Dry season, T2 = Early rainy season, T3 = Heavy rainy season,
S1 = Downstream site, S2 = Middle-stream site, and S3 = Upstream site).
Genera
Bacillariophyta
Chaetoceros sp.
Cyclotella sp.
Diatoma sp.
Fragilaria sp.
Navicula sp.
Nitzschia sp.
Pinnularia sp.
Surirella sp.
Tabellaria sp.
Abundance
No. of genera (total)
Chlorophyta
Actinastrum sp.
Ankistrodesmus sp.
Bambusina sp.
Closterium sp.
Coelastrum sp.
Cosmarium sp.
Crucigenia sp.
Desmidium sp.
Euastrum sp.
Eudorina sp.
Dictyosphaerium sp.
Gonatozygon sp.
Gonium sp.
Hyalotheca sp.
Kirchneriella sp.
Micrasterias sp.
Mougeotia sp.
Nephrocytium sp.
Oocystis sp.
Pandorina sp.
Pediastrum sp.
Pleodorina sp.
Pleurotaenium sp.
Scenedesmus sp.
Selenastrum sp.
Spondylosium sp.
Staurastrum sp.
Staurodesmus sp.
Tetraedron sp.
Triploceras sp.
Volvox sp.
Xanthidium sp.
Zygnema sp.
Abundance
No. of genera (total)
T1S1
0
0
0
0
0
5
0
0
2
7
2
26
11
0
0
0
4
28
0
0
32
0
0
0
1
0
0
0
0
0
18
20
12
0
14
5
0
9
0
6
0
0
1
0
187
14
T1S2
2
20
0
0
0
6
0
0
0
28
3
9
21
0
3
0
28
1
3
0
29
2
0
1
0
0
0
0
0
0
12
21
0
0
23
1
0
30
0
6
0
0
27
0
214
16
T1S3
T2S1
T2S2
0
3
0
0
0
26
0
0
0
29
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1
0
2
2
0
5
0
6
6
3
181
3
0
38
11
0
3
4
0
3
0
0
0
10
6
0
6
4
6
0
12
0
1
0
0
3
1
314
20
103
5
0
0
39
0
23
0
0
1
0
0
0
0
0
0
0
2
0
2
35
0
0
229
0
0
0
0
0
0
0
0
0
439
9
181
8
0
2
40
0
59
0
0
18
0
0
0
0
0
0
0
6
0
6
44
0
0
459
0
0
2
0
0
0
16
1
0
842
13
T2S3
T3S1
T3S2
T3S3 Average
0
1
0
0
0
5
0
1
0
7
3
0
0
1
0
2
2
1
1
2
9
6
0
0
1
0
0
3
0
2
1
7
5
0
1
3
2
1
8
0
1
5
21
7
5
49
2
8
132
26
20
1
2
42
0
0
0
9
12
1
0
32
0
7
67
0
2
67
5
0
17
2
8
1
0
2
0
519
24
8
0
0
2
4
3
1
0
0
9
0
0
0
0
0
0
0
0
0
6
23
1
1
49
0
0
2
1
2
0
0
0
0
112
14
3
0
0
4
5
1
1
0
0
6
0
0
0
0
1
0
0
1
1
7
11
0
0
32
0
0
2
1
0
0
3
1
0
80
16
2
3
0
11
2
10
2
1
4
14
0
1
0
2
3
1
3
1
1
7
14
0
4
14
0
1
7
1
2
0
1
2
0
114
26
0
3
1
0
0
6
0
1
1
12
9
37
11
0
4
25
8
35
1
1
21
1
0
0
2
2
1
0
5
0
8
27
1
1
99
2
0
9
1
3
0
2
4
0
311
25
Chiang Mai J. Sci. 2013; 40(3)
351
Table 2. Continued
Genera
T1S1
Chrysophyta
Dinobryon sp.
5
Abundance
5
No. of genera (total)
1
Cyanophyta
Anabaena sp.
10
Chroococcus sp.
71
Dimorphococcus sp.
0
Merismopedia sp.
0
Microcystis sp.
4
Oscillatoria sp.
0
Spirulina sp.
39
Abundance
124
No. of genera (total)
4
Euglenophyta
Euglena sp.
311
Euglepha sp.
0
Lepocinclis sp.
0
Phacus sp.
189
Strombomonas sp.
4
Trachelomonas sp.
1,392
Abundance
1,896
No. of genera (total)
4
Phyrrophyta
Ceratium sp.
34
Dinophysis sp.
0
Noctiluca sp.
127
Peridinium sp.
12
Prorocentrum sp.
0
Protoperidinium sp.
376
No.of abundance
549
No. of genera (total)
4
Grand total of
2,765
abundance
Grand total of
29
genera (total)
Species richness index 3.53
0.54
Evenness index
S h a n n o n - W i e n e r 1.82
diversity index
T1S2
T1S3
T2S1
T2S2
T2S3
T3S1
T3S2
T3S3 Average
6
6
1
0
0
0
0
0
0
12
12
1
14
14
1
6
6
1
5
5
1
10
10
1
6
6
1
14
24
0
0
24
0
12
74
4
1
47
0
0
0
6
0
54
3
6
0
0
0
30
779
110
925
4
0
14
0
0
46
1,574
728
2,362
4
0
66
0
1
9
8
1
85
5
0
0
0
0
5
34
14
53
3
0
3
0
0
0
17
23
43
3
2
4
1
0
0
6
4
17
5
4
25
0
0
13
269
103
414
5
165
0
0
92
5
994
1,256
4
49
0
0
61
0
743
853
3
28
0
0
30
0
1,094
1,152
3
207
0
0
515
0
10,297
11,019
3
98
28
924
172
0
1,297
2,519
5
83
11
0
165
2
1,074
1,335
5
419
10
0
375
0
1,883
2,687
4
111
27
2
61
4
824
1,029
6
163
8
103
184
2
2,177
2,637
6
7
5
38
0
0
0
164
853
0
25
358 12,796
0
0
0
444
0
1,140
640 1,216 13,974
4
3
3
2,217 2,464 16,492
276
2
0
21,920
0
18,584
40,782
4
55,021
4
0
0
895
0
0
899
2
4,041
107
0
0
597
0
0
704
2
2,210
54
0
0
715
0
0
769
2
3,583
9
0
0
162
1
35
207
4
1,386
59
0
127
4,164
0
2,287
6,637
6
10,020
33
31
21
27
42
31
30
49
62
4.15
0.57
1.98
3.84
0.53
1.82
2.06
0.30
0.92
2.38
0.42
1.39
4.94
0.54
2.00
3.90
0.46
1.58
3.54
0.42
1.43
6.64
0.44
1.72
3.83
0.47
1.63
Phytoplankton abundance was at 4,464
individuals L-1 in 1996-1999 [17] and 10,020
individuals L-1 in this study. The species
richness index was 3.99 in 1996-1999 [17]
and 3.89 in this study. The evenness index
was 0.42 in 1996-1999 [17] and 0.47 in our
study. The Shannon-Wiener diversity
index was 1.47 in 1996-1999 [17] and 1.63
in this study, showing tends to increase
after dam construction. Considering the
diversity levels in the water bodies, Begon
et al. [20] stated that the evenness index
ranges between 0.0 and 1.0, with 1.0
representing a situation in which all species
are equally abundant, and the ShannonWiener’s diversity index value was generally
between 1.5 and 3.5, where a high value
indicates high species diversity. So, in this
study, the diversity indices indicated that
the phytoplankton had medium
352
distribution and diversity. Also, based on
the diversity index implied that the water
quality condition in the area was
moderately-polluted [21], and still suitable
for aquatic animal growth and survival [22].
The cluster and MDS analyses divided
the phytoplankton distribution into three
groups by season. The first was during the
dry season at all sites. The second was during
the early rainy season at the upstream site and
during the heavy rainy season at all sites. The
third group was during the early season at the
downstream and the middle-stream sites
(Figure 3). The genera that indicated the
similarity within each group at contributing
greater than 5% of the similarity were
Trachelomonas (Tra.), Noctiluca (Noc.), Euglena
(Eug.), Phacus (Pha.), Chroococcus (Chro.) and
Eudorina (Eudo.) in the first group; Trachelomonas,
Euglena, Phacus, Peridinium (Per.) and Scenedesmus
Chiang Mai J. Sci. 2013; 40(3)
(Sce.) in the second group; and
Trachelomonas, Peridinium, Scenedesmus,
Protpperidinium (Protoper.), Oscillatoria
(Oscil.), Spirulina (Spiru) and Actinastrum
(Acti.) in the third group (Figure 3).
According to the result, some genera, such
as Noctiluca, which can live in saltwater
disappeared during the rainy seasons. The
density of other genera such as Trachelomonas
sp., Peridinium and Protoperidinium increased
during rainy seasons (Table 2). The change
might be a result of rainfall and nutrient loads
more suitable for these genera. Trachelomonas
sp. thrives in waters rich in nitrogenous
nutrients while Peridinium sp. and Protoperidinium
sp. prefer waters rich in organic nutrients [13].
Also, the result of AARL-PP score showed
that Peridinium was predominant in this area
(42% of total density), indicating that the
trophic level in freshwater fishing area of
Figure 3. Bray-Curtis cluster diagram and MDS of phytoplankton similarity in the freshwater
fishing area, PPRB, 2006 (T1 = Dry season, T2 = Early rainy season, T3 = Heavy rainy season,
S1 = Downstream site, S2 = Middle-stream site, and S3 = Upstream site).
Chiang Mai J. Sci. 2013; 40(3)
PPRB was meso-eutrophic and the water
quality condition was moderately-polluted.
The triplot of 10 dominant genera and
water quality parameters provided by CCA
is shown in Figure 4. Genera are expressed as
arrows. The length of an arrow indicates the
importance of this factor. Each arrow
determines a direction or axis in the diagram,
obtained by extending the arrow in both
directions. The projection of a genus on this
axis shows its preference for high or low
values of this factor [25]. Thus, the results
indicated that change in water dept and
nutrients were an important characteristic
driving genus composition. Lepocinclis sp was
dominated by deepest water dept at T2S3.
Phacus sp, Euglena sp, Trachelomonas sp and
Scenedesmus sp were dominated by shallower
water dept and higher ammonia at T1S1,
T3S1, T3S2 and T3S3. Genus composition
at T2S1 and T2S2, which the study area
353
were characterized by higher temperature,
transparency, DO and velocity with slightly
salt water, was dominated by Peridinium sp,
Protoperidinium sp, Oscillatoria sp and Spirulina
sp. At the T1S2 and T1S3 which the nutrients
were higher, dominant genus was Noctiluca sp.
Furthermore, in terms of fishery
managements in order to maintain
environment and stocks, regular monitoring
of pollution should be conducted around the
year. Restocking of native species should be
taken at sites and seasonal times most critical
for the survival of ecosystems. For example,
restocking of Macrobrachium. rosenbergii which
prefers slightly saline water should be done at
downstream sites, regardless of the season,
since these areas are frequently affected by sea
water influx, and this species favors the
resulting slightly brackish water. Restocking of
herbivorous species such as Barbodes gonionotus
which is a freshwater species and feeds on
Figure 4. Relationship between 10 dominant genera and water quality parameters in the
in the freshwater fishing area, PPRB, 2006 (T1 = Dry season, T2 = Early rainy season,
T3 = Heavy rainy season, S1 = lower part of the river sampling site, S2 = middle part
of the river sampling site and S3 = upper part of the river sampling site).
354
phytoplankton would be best conducted
at middle stream sites during the early
rainy season which offers plenty of
phytoplankton serving as natural food.
In conclusion, phytoplankton diversity
in the freshwater fishing area of PPRB
could be considered at medium level. The
water condition was meso-eutrophic and
moderately-polluted, but is still suitable for
aquatic animal growth and survival.
However, water quality/environment
should be continuously monitored. Finally,
restocking aquatic animals/fishes should be
conducted in appropriate sites/times of
each species for better survival.
ACKNOWLEDGEMENTS
This research proposal was been
recommended by a special committee of The
Research and Development Project of Pak
Phanang River Basin. Funding for the field
research was provided by the Thailand
Research Fund (TRF). Special thanks go to
the all people from the Pak Phanang River
Basin who shared their ideas, experience
and knowledge.
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