Comparative Abundance and Density of Oithona and Peridinium along Logolog River, an estuarine
environment traversing an Coal-Fired Power Plant Project
Introduction
This study covered assessment of the physico-chemical water parameters in relationship
with plankton count of Logolog River in Sual, Pangasinan. Logolog River is a small isolated stream
situated at western part of Pangasinan, stretching at 5.5 kilometers that drains in Lingayen Gulf.
The river runs in between of Brgy. Baybay Sur and Brgy. Pangascasan of Sual, Pangasinan;
whereas, distinctly, the Sual Coal Fire Power Plant can be located.
With little known information about this river, an
assessment was made that
encompassed the month of March for weekly recording of in-situ water parameters
(temperature, salinity, pH), collecting of water samples for lab analysis (BOD,TSS, Total and Fecal
Coliform), and counting plankton (specifically of genus Perdinium and Oithona) obtained from
horizontal tow to provide baseline information of the river’s water quality in terms of physical,
chemical, and biological scope.
Materials and Methods
In the said assessment, the study made used of several devices and equipment in
measurement and determination of water quality parameters. Sampling was made in three (3)
designated stations, comprising of Upstream, Midstream, and Downstream. All samples for each
station were replicated into three.
For determining onsite parameters, a water quality-checker probe was used to determine
temperature (C̊), salinity (ppt), and pH level. Nine (9) PET bottles, meanwhile, were used to collect
water samples from the river for laboratory analysis of BOD (mg/mL), Total Suspended Solids
(mg/L), Total and Fecal Coliform (MPN) in four consecutive weeks (1 month). Likewise, nine 250ml
PET bottles were used to contain water samples for plankon, whereas a plankton net (130µm)
was used in horizontal tow sampling. Plankton analysis, delimited to Peridinium and Oithona,
was done quantitatively because samples by genus were counted under a compound microscope
using a Sedgewick Rafter Counting Cell. Plankton analysis was performed at the Natural Food and
Biology laboratory at BFAR – NIFTDC.
The study was classified under non-experimental, exploratory type of research which
employed collection of ambient water quality parameters and were discussed in descriptive
approach.
Descriptive mean tables were carried out for the physico-chemical parameters
temperature, salinity, pH, Biochemical Oxygen Demand (BOD), Total and Fecal Coliform Load. For
plankton count, identified Peridinium and Oithina were only considered under the analysis.
Collectively, all parameters were enjoined in performing Pearson-R correlation and Regression
Analysis to determine significant relationship among them. Scatter plots were also made to
graphically illustrate fluctuation behavior of the two plankton genera with respect to ambient
parameters. Finally, Analysis of Variance for repeated measures (ANOVAR) was carried out to
determine significance of variations among the collected data derived from the conduct of the
study.
All statistical tests performed in the study were automatically run in the IBM SPSS Stat
Editor.
Stat Results and Discussions
Thirty-six (36) water samples were collected in one month, with breakdown of nine (9)
collected water samples per week. The descriptive statistic table was provided below to show the
frequency distribution, central tendency, and standard deviation.
Descriptive Statistics
Factors/
Paramaters
N
Minimu Maximu
m
m
Statisti Statistic Statistic
c
Sum
Mean
Statistic
Statistic
Std.
Deviation
Statistic
Skewness
Statisti
c
Std.
Error
Wk
36
1
4
90
2.50
1.134
.000
.393
Temp
36
26.70
35.20
1128.90
31.3583
2.50604
-.256
.393
Salnt
36
17.00
35.00
978.00
27.1667
5.65938
-.459
.393
pH
36
7.03
7.55
264.69
7.3525
.16031
-.474
.393
BOD
36
.09
4.72
40.99
1.1386
1.05750
1.328
.393
TCol
36
.00
110000.
00
724240. 20117.77 37808.100
00
78
73
1.950
.393
FCol
36
.00
1400.00
3940.00 109.4444 300.46578
3.215
.393
TSS
36
17.70
98.36
2256.73
62.6869
21.09815
-.439
.393
Oithona
36
0
56
284
7.89
14.577
1.985
.393
Peridinium
36
0
422
2709
75.25
118.725
1.914
.393
Valid N
(listwise)
36
Based on the table, the Logolog River had an average weekly temperature of 31.56C̊,
salinity of 27.17 ppt, pH of 7.35, BOD of 1.14 mg/L, Total Coliform of 20,117.78MPN, Fecal
Coliform of 109.44MPN, and TSS level of 62.69 mg/L. For the average plankton count, meanwhile,
the river had an average weekly abundance of 8 count/ml and 75 count/ml for Oithona and
Peridinium, respectively.
Correlation
Statistical correlations were carried to determine significant interaction of relationship
among variables considered in the study. The
Correlations
Wk
Pearson
Correlation
Salnt
Salnt
1 .590**
.160
.000
.350
pH
BOD
TCol
*
-.063
.449**
.165
.004
.714
.006
.336
.469*
FCol
TSS
Oith Peridin
ona ium
.728*
.251
.388*
.000 .140
.019
*
Sum of Squares
and Crossproducts
45.0 58.65 36.00
674150 1970.0 609.7 145. 1829.5
2.985 -2.655
00
0
0
.000
00
85 000
00
Covariance
1.28
1.676 1.029
6
.085
-.076
19261.
17.42 4.14
56.286
52.271
429
2
3
N
36
36
36
36
36
36
36
*
Pearson
.590
1 .423* .349*
.099
-.160
*
**
Correlation
.636
Sig. (2-tailed)
.000
.010 .037
.000
.566
.351
Sum of Squares
58.6 219.8 209.9
328250
and Cross4.906 58.97
4217.8
50
08
50
.667
products
7
33
1.67
9378.5
Covariance
6.280 5.999 .140 -1.685
120.51
6
90
0
N
36
36
36
36
36
36
36
*
Pearson
.517
.160 .423*
1
-.221
-.253
.033
*
Correlation
Sig. (2-tailed)
.350
.010
.001
.196
.137
.849
Sum of Squares
36.0 209.9 1121. 16.42
1963.3
and Cross46.23 189111
00
50
000
5
33
products
2 6.667
Tem
p
Wk
Sig. (2-tailed)
Temp
36
.785*
*
36
36
.229
-.171
.000 .180
.320
1453. 292.
1775.7
266 433
25
41.52 8.35
2
5 50.735
36
36
36
.047 .221 -.597**
.787 .196
.000
194.8 637.
14030.
58 667
500
pH
Covariance
N
36
36
36
*
Pearson
.469
.349* .517**
*
Correlation
Sig. (2-tailed)
.004
.037
.001
Sum of Squares
2.98
16.42
and Cross4.906
5
5
products
TCol
BOD
Covariance
.085
.140
.469
18.2
.469 -1.321 54031. 56.095 5.567
400.87
19
905
1
36
36
36
36
36 36
36
1
-.252
.080
.025
.185 .228
.138
.642
.886
.280 .180
.899 -1.495
.026
-.043
N
36
36
36
36
36
Pearson
-.063
-.221 -.252
1
**
Correlation
.636
Sig. (2-tailed)
.714
.000
.196 .138
Sum of Squares
- 39.14
and Cross2.65 58.97 46.23
1.495
0
products
5
7
2
Covariance
-.076 -1.685 -1.321 -.043 1.118
N
Pearson
Correlation
Sig. (2-tailed)
36
.449*
Sum of Squares
and Crossproducts
6741
32825
50.0
0.667
00
Covariance
FCol
1.02
32.02
5.999
9
9
N
Pearson
Correlation
Sig. (2-tailed)
Sum of Squares
and Crossproducts
36
36
36
36
*
.099
-.253
.080
.096
.006
.566
1926
9378.
1.42
590
9
36
36
-.176
.305
17021.
21.90 18.6
41.750
117.07
500
9 80
3
486.32
1.193 .626 .534 -3.345
9
36
36
36 36
36
.096
.338* -.279
.353*
.034
.578
.044 .099 .842
.035
134178 3756.2
1550.1
217.9 18.5
.989
72
43
50 36
3833.6 107.32
44.290
85
2 6.227 .530
36
36
36 36
36
1
.283 .341* .129
.137 .642
.578
.094 .042
500308 112677 9517
18911 1702 13417
36822. 955.55 878.4
16.66 1.500 8.989
222
6
56
7
142945
2719
486.3 3833.
321937
54031
2480.6
39.38
29
685
0.159
.905
35
4
36
36
36
36
36
36
.165
-.160
.033
.025
.338*
.283
.336
.351
.849
.886
.044
.094
1
.042
.807
112677
1970
1963. 41.75 3756.
315978 9354.
4217.
955.55
.000
333
0
272
8.889 639
833
6
.454
248
729
1.11
1
710
65.4
60
36
.091
.597
139
82.2
22
.323
.055
507660
40.000
145045
8.286
36
-.071
.681
88525.
000
TSS
Covariance
N
Pearson
Correlation
Sig. (2-tailed)
Sum of Squares
and Crossproducts
Oithona
Covariance
N
Pearson
Correlation
Sig. (2-tailed)
Sum of Squares
and Crossproducts
Covariance
Peridinium
N
Pearson
Correlation
56.2
56.09
107.3 321937 90279. 267.2
120.5
1.193
399. 2529.2
86
5
22 0.159
683
75
10
492
86
36
36
36
36
36
36
36
36 36
36
*
.728
.785**
.047 .185 -.279
.341*
.042
1 .230
.170
*
.000
.000
609. 1453.
785
266
17.4 41.52
22
2
36
36
.787
.280
.099
.042
.807
.178
.323
247
194.8 21.90
951787 9354.6 1557
14873.
217.9
3.66
58
9
8.456
39 9.616
428
50
8
271939 267.27 445.1 70.6 424.95
5.567 .626 -6.227
.384
5
32 76
5
36
36
36
36
36
36 36
36
.251
.229
.221
.228
.140
.180
.196
.180
.000
.305
145. 292.4
000
33
4.14
8.355
3
-.034
.129
-.091
.230
1
-.136
.842
.454
.597 .178
.430
743
637.6 18.68
248729
2473.
18.53
13982.
7.55 8228.0
67
0
1.111
668
6
222
6
00
18.21
71065.
70.67 212.
.534 -.530
399.49
235.08
9
460
6 502
2
6
36
36
36
36
36
36 36
36
-.176 .353*
.323
-.071 .170
1
**
.597
.136
36
36
.388*
-.171
Sig. (2-tailed)
.019
.320
Sum of Squares
and Crossproducts
1829
1550. 507660
1487 822 493350
1775. 14030 117.0
88525.
.500
143 40.000
3.428 8.00
.750
725
.500
73
000
0
Covariance
52.2
- 44.29 145045
424.9
14095.
50.73 400.8
2529.2
235.
71
3.345
0 8.286
55
736
5
71
86
086
N
36
36
36
36
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
.035
36
.055
36
.681
36
.323 .430
36
36
36
Week as correlated with independent variables
The factor “Week” has strong positive correlation with temperature (0.590), pH (0.469),
Total Coliform (0.449), and TSS (0.728) based on the table above. The positive correlation of week
with parameters temperature, pH, Total Coliform, and TSS had something to do with distinct
climate pattern in the Philippines since the month of March fall under typical dry season (MarchMay).
Dry seasons are characterized with increased ambient temperature and heat index.
According to Silent Gardens (2019), the month of March kicks off the warmest months in the
Philippines, characterized with hot and dry weather.
With direct relationship of Week and Temperature, the increasing of temperature has
influence with the increasing of pH level of the water. In contrast, Gillespie (2018) claims that
there is an inverse correlation with pure water’s temperature and pH; however, differences are
too small to be picked by basic pH testing method. With this, other confounding factors may have
influenced this strong correlation with pH and temperature.
Levels of Total Coliform (MPN) were observed to be increasing with respect to passing
weeks. The strong correlation of coliform load and week may be synonymous with the
temperature factor. According to LeChevallier (2003), coliform level is significantly higher when
water temperatures were above 15 °C. In addition, he claims that bacterial growth may be very
rapid at warmer climates, but microbial activity still depends on underlying environmental
system.
Water Temperature correlated with TSS, pH, BOD
The water temperature has strong correlation with TSS (.785), significant correlation with
salinity (.423), pH (.349), and a negative correlation with BOD (-.636).
Rise of water temperature may enhance the increase of water turbidity and suspended
solids in Logolog River. According to Kentucky Government (2018), though indirectly, the heat
absorbency of the particulate and suspended solids affects other water parameters such as
temperature and dissolved oxygen. Nevertheless, suspended solids interfere with oxygen and
nutrient dispersion to deeper layers of river.
Salinity and pH, meanwhile, are directly related with temperature. Increase of
temperature enhances the acidity of water as said by Clark (2019). On the other hand, salinity
can affect water temperature with reference to density of water (sciencelearn, 2017).
Water Salinity correlated with pH and Peridinium abundance
Water salinity of Logolog River is strongly correlated to pH and Peridinium abundance. A
strong positive correlation was established between water salinity and pH, obtaining a p value of
(0.517). This implies that, going downstream, as salinity of the river water increases, the pH also
increases. In contrast, a strong negative correlation was determined between water salinity and
Peridinium abundance, obtaining a p value of (-0.597). Meaning, the increase of water salinity,
going downstream, decreases the number of Peridinium found in the river.
Total Coliform Level correlated with TSS
Total Coliform level of the river water is slightly correlated with Total Suspended Solids
(0.341). Though slight correlation may be translated to small effect or interaction of two
independent factors, the increase of total suspended solids (TSS) derived from effluent discharge
may carry rich load of fecal coliform bacteria. Also, it can be noted around river’s geographical
premises the scattered residential communities and the operation of the Sual Coal Fire Plant ().
Fecal Coliform Level correlated with BOD
Correlation between Fecal coliform and BOD yields a p value of (.338). The Biochemical
Oxygen Demand aims to measure the degree of organic pollutants present in the water,
meanwhile, fecal coliform level tells the degree of bacterial contamination originated from
domestic wastewater discharge.
TSS Level correlated with Temperature
Strong positive correlation (.785) between TSS and Temperature was obtained in the
analysis, which suggests the significant influence of suspended solids to warming of water
temperature. In vice versa, fluctuation of water temperature may also exhibit hyperactivity of
some plankton organisms (algal bloom) which contributes to increase of TSS that can be
manifested in the river water’s turbidity.
Peridinium Count correlated with BOD
Peridinium and BOD were found to be slightly correlated at p value 0.353. This indicates
significant effect of BOD level to population of phytoplankton Peridinium, where increase of BOD
can affect the population of Peridinium.
However, in the compilation made by Novis (2016), Peridinium are classified under
indicator taxa for good water quality.
Oithona and Peridinium Abundance at different Stations
Average Abundance of Oithona in Three
Sampling Stations
25
20
15
OithUP
OithMD
10
OithDW
5
0
OithUP
OithMD
OithDW
The preceding graph presents the average abundance of Oithona (zooplankton) at three
different sampling stations.
Highest mean (18 counts) for Oithona abundance was obtained at downstream (OithDW)
of Logolog. The river’s midstream (OithMD) and upstream (OithUP), had an average mean count
of 3 and 2, respectively.
Based on graph, a pattern of linear relationship was established which implies that the
zooplankton genus Oithona is most abundant at downstream environment. As the sampling
station ascends, the count of zooplankton Oithona decreases subject to variation of water salinity
and temperature. According to Wang, et.al (2017), lower temperature and higher salinity in the
surface water signifies a positive indication for aggregation of the genus Oithona.
Average Abundance of Peridinium in Three
Sampling Stations
200
180
160
140
120
PeriUP
100
PeriMD
80
PeriDW
60
40
20
0
PeriUP
PeriMD
PeriDW
The preceding graph presents the average abundance of Peridinium (phytoplankton) at
three different sampling stations.
Highest mean (166 counts) for Peridinium abundance was obtained at downstream
(PeriUP) of Logolog. Meanwhile, the river’s midstream (PeriMD) and downstream (PeriDW), had
an average mean count of 23 and 7, respectively.
Phytoplankton Peridinium are mostly found in freshwater water bodies, though some
inhabit brackish environment (Rogers, 2013)
Regression Analysis
In this study, a regression analysis was employed to determine a good predicting factor
for the abundance of Peridinium (Phytoplankton) and Oithona (Zooplankton).
The independent variables: water temperature, salinity, pH, BOD, Total Coliform, Fecal
Coliform, and TSS were included for the regression analysis. Using the Stepwise Method of SPSS,
a good predicting factor for Peridinium and Oithona was identified from the pooled independent
factors.
Correlations
Peridin Temp Salnt
ium
pH
Peridinium
1.000 -.171 -.597 -.176
Temp
-.171 1.000
Salnt
Pearso
pH
n
Correla BOD
tion
TCol
FCol
.423
-.597
.423 1.000
-.176
.349
BOD
TCol
FCol
TSS
.353
.323 -.071
.170
.349 -.636
.099 -.160
.785
.517 -.221 -.253
.033
.047
.185
.517 1.000 -.252
.080
.025
.353 -.636 -.221 -.252 1.000
.096
.338 -.279
.323
.099 -.253
-.071 -.160
.080
.096 1.000
.283
.341
.033
.025
.338
.283 1.000
.042
TSS
.170
.785
.047
.185 -.279
.341
.042 1.000
Peridinium
Temp
.
.160
.160
.
.000
.005
.153
.019
.017
.000
.027
.283
.341
.176
.161
.000
Salnt
Sig. (1- pH
tailed) BOD
.000
.153
.017
.005
.019
.000
.
.001
.098
.001
.
.069
.098
.069
.
.069
.321
.289
.424
.443
.022
.394
.140
.050
TCol
FCol
TSS
.027
.341
.161
.283
.176
.000
.069
.424
.394
.321
.443
.140
.289
.022
.050
.
.047
.021
.047
.
.404
.021
.404
.
Peridinium
36
36
36
36
36
36
36
36
Temp
36
36
36
36
36
36
36
36
Salnt
36
36
36
36
36
36
36
36
pH
36
36
36
36
36
36
36
36
BOD
36
36
36
36
36
36
36
36
TCol
36
36
36
36
36
36
36
36
FCol
36
36
36
36
36
36
36
36
TSS
36
36
36
36
36
36
36
36
N
The Pearson-R correlation was initially carried out to determine statistical relationship of
the variables. Only variables tending to the abundance of Peridinium and Oithona (dependent
variables) were sorted by the regression analysis through Stepwise Method.
Variables Entered/Removeda
Model
Variables
Variables
Method
Entered
Removed
Stepwise
(Criteria:
Probability-ofF-to-enter <=
1
Salnt
.
.050,
Probability-ofF-to-remove
>= .100).
a. Dependent Variable: Peridinium
Based on applied Stepwise approach, the variable “Salinity” was found to be a potential
predicting factor of the Peridium abundance. However, the genus Oithona was found with no
potential predicting factor.
Abundance of Peridinium at Increasing Salinity Level
Perdinium Count
Peridinium
450
400
350
300
250
200
150
100
50
0
-50 0
Peridinium
Линейная
(Peridinium)
y = -12,516x + 415,27
R² = 0,3559
10
20
30
Salinity Level (ppt)
40
The preceding graph illustrates the inverse linear relationship of water salinity level to the
Peridinium abundance of the Logolog River. It can be visualized in the graph that the increasing
of water salinity (ppt) in the Logolog River can show decreasing abundance of Peridinium at
decreasing altitude.
With predicting formula y= -12.516x+415.27, the abundance of the phytoplankton
Peridinium can be mathematically projected at R2= 0.3559 (36%) level of reliability.
Analysis of Variance with Repeated Measures (ANOVAr)
Using the ANOVA for repeated measures (ANOVAr) in the SPSS, the Abundance of
phytoplankton Peridinium and zooplankton Oithona, sampled at four different time settings
(weekly), were analyzed separately. The ANOVAr determined the significant variations of withinsubject factor (time) at between-subject factor (abundance).
The test of variances derived from repetitive measures is hereby statistically translated as
follows:
Ho : p ≥ 0.05; null hypothesis
Ha : p < 0.05; alternative hypothesis
Accept Ho If calculated p value is greater than or equal to 0.05; this means that there are
no significant variations obtained from repeated sampling of Peridinium/ Oithona. However, if p
value falls below the α error of 0.05, Ho is rejected, and Ha is therefore accepted.
Post-hoc tests were also executed to further assess probability value of variations
obtained from the ANOVAr.
VARIATIONS FOR ABUNDANCE OF PERIDINIUM
The phytoplankton Peridinium was assigned for the analysis of variances from repeated
measures.
Levene's Test of Equality of Error Variancesa
F
df1
df2
Sig.
PAbd1
6.199
2
6
.035
PAbd2
11.754
2
6
.008
PAbd3
14.806
2
6
.005
PAbd4
5.287
2
6
.047
Tests the null hypothesis that the error variance of the dependent
variable is equal across groups.
a. Design: Intercept + Station
Within Subjects Design: PAbd
Test of homogeneity from the sampled genus Peridinium was carried out to ensure
measurement integrity, accuracy and sample distribution.
All considered factors of the study obtained statistically significant variations among the
between-subject factors.
Pairwise Comparisons
Measure: Abundance
(I) Station
(J) Station
Mean Difference
Std. Error
Sig.b
95% Confidence Interval for
Differenceb
(I-J)
Lower Bound
1
2
3
Upper Bound
2
179.917*
35.918
.002
92.028
267.805
3
180.500*
35.918
.002
92.611
268.389
1
-179.917*
35.918
.002
-267.805
-92.028
3
.583
35.918
.988
-87.305
88.472
1
-180.500*
35.918
.002
-268.389
-92.611
2
-.583
35.918
.988
-88.472
87.305
Based on estimated marginal means
*. The mean difference is significant at the .05 level.
b. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).
Rotational pairwise comparison was made
Univariate Tests
Measure: Abundance
Sum of Squares
df
Mean Square
Contrast
64950.597
2
32475.299
Error
11611.083
6
1935.181
F
Sig.
16.782
.003
The F tests the effect of Station. This test is based on the linearly independent pairwise
comparisons among the estimated marginal means.
Calculated p value is equal to .003, thereby rejecting the null and accept the alternative
hypothesis. This translates that the abundance of Peridinium, as scattered across the Logolog
River, have significant differences and variations.
Since Ho was already rejected, Ha shall now be assessed for possible remedial computation
obtained /desired from the value.
Post Hoc Tests
Station
Multiple Comparisons
Measure: Abundance
(I) Station
(J) Station
Mean
Std. Error
Sig.
Difference (I-J)
1
Tukey HSD
95% Confidence Interval
Lower Bound
Upper Bound
2
179.92*
35.918
.006
69.71
290.12
3
180.50*
35.918
.006
70.29
290.71
1
-179.92*
35.918
.006
-290.12
-69.71
3
.58
35.918
1.000
-109.62
110.79
1
-180.50*
35.918
.006
-290.71
-70.29
2
-.58
35.918
1.000
-110.79
109.62
2
179.92*
35.918
.002
92.03
267.81
2
3
LSD
1
3
180.50*
35.918
.002
92.61
268.39
1
-179.92*
35.918
.002
-267.81
-92.03
3
.58
35.918
.988
-87.31
88.47
1
-180.50*
35.918
.002
-268.39
-92.61
2
-.58
35.918
.988
-88.47
87.31
1
3
180.50*
35.918
.004
77.68
283.32
2
3
.58
35.918
1.000
-102.24
103.41
2
3
Dunnett t (2-sided)b
Based on observed means.
The error term is Mean Square(Error) = 1935.181.
*. The mean difference is significant at the .05 level.
b. Dunnett t-tests treat one group as a control, and compare all other groups against it.
Abundance
Station
N
Subset
1
Student-Newman-Keulsa,b,c
3
3
6.42
2
3
7.00
1
3
Sig.
Tukey HSDa,b,c
2
186.92
.988
3
3
6.42
2
3
7.00
1
3
Sig.
1.000
186.92
1.000
1.000
Means for groups in homogeneous subsets are displayed.
Based on observed means.
The error term is Mean Square(Error) = 1935.181.
a. Uses Harmonic Mean Sample Size = 3.000.
b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I
error levels are not guaranteed.
c. Alpha = .05.
Descriptive Statistics
Station
Mean
Std. Deviation
N
OAbd1
OAbd2
OAbd3
OAbd4
1
2.67
1.528
3
2
8.33
12.741
3
3
19.67
4.726
3
Total
10.22
10.146
9
1
1.33
1.155
3
2
7.33
5.774
3
3
28.67
6.110
3
Total
12.44
13.144
9
1
2.67
2.887
3
2
14.00
9.539
3
3
45.00
24.000
3
Total
20.56
23.001
9
1
3.00
5.196
3
2
16.33
8.083
3
3
56.00
21.071
3
Total
25.11
26.535
9
Multivariate Testsa
Effect
OAbd
Value
Hypothesis df
Error df
Sig.
Pillai's Trace
.733
3.661b
Wilks' Lambda
.267
3.661b
3.000
4.000
.121
Hotelling's Trace
2.746
3.661b
3.000
4.000
.121
Roy's Largest Root
2.746
3.661b
3.000
4.000
.121
.824
1.167
6.000
10.000
.395
.227
1.464b
6.000
8.000
.301
3.179
1.589
6.000
6.000
.294
3.107
5.178c
3.000
5.000
.054
Pillai's Trace
OAbd * Station
F
Wilks' Lambda
Hotelling's Trace
Roy's Largest Root
3.000
4.000
.121
a. Design: Intercept + Station
Within Subjects Design: OAbd
b. Exact statistic
c. The statistic is an upper bound on F that yields a lower bound on the significance level.
Mauchly's Test of Sphericitya
Measure: Abundance
Within Subjects Effect
Mauchly's W
df
Sig.
Epsilonb
OAbd
Approx. Chi-
Greenhouse-
Square
Geisser
.115
10.194
5
.075
Huynh-Feldt
.529
Lower-
.929
Tests the null hypothesis that the error covariance matrix of the orthonormalized transformed dependent variables is proportional to an i
matrix.
a. Design: Intercept + Station
Within Subjects Design: OAbd
b. May be used to adjust the degrees of freedom for the averaged tests of significance. Corrected tests are displayed in the Tests of Wit
Subjects Effects table.
Tests of Within-Subjects Effects
Measure: Abundance
Source
Type III Sum of
df
Mean Square
F
Sig.
Squares
OAbd
OAbd * Station
Error(OAbd)
Sphericity Assumed
1305.861
3
435.287
3.829
.028
Greenhouse-Geisser
1305.861
1.588
822.319
3.829
.067
Huynh-Feldt
1305.861
2.786
468.706
3.829
.032
Lower-bound
1305.861
1.000
1305.861
3.829
.098
Sphericity Assumed
1253.389
6
208.898
1.837
.148
Greenhouse-Geisser
1253.389
3.176
394.638
1.837
.206
Huynh-Feldt
1253.389
5.572
224.936
1.837
.155
Lower-bound
1253.389
2.000
626.694
1.837
.239
Sphericity Assumed
2046.500
18
113.694
Greenhouse-Geisser
2046.500
9.528
214.785
Huynh-Feldt
2046.500
16.717
122.423
Lower-bound
2046.500
6.000
341.083
Tests of Within-Subjects Contrasts
Measure: Abundance
Source
OAbd
Type III Sum of
df
Mean Square
F
Sig.
Squares
Linear
OAbd
OAbd * Station
1253.472
1
1253.472
12.549
.012
Quadratic
12.250
1
12.250
.078
.789
Cubic
40.139
1
40.139
.477
.516
Linear
1244.678
2
622.339
6.231
.034
Error(OAbd)
Quadratic
1.167
2
.583
.004
.996
Cubic
7.544
2
3.772
.045
.957
Linear
599.300
6
99.883
Quadratic
941.833
6
156.972
Cubic
505.367
6
84.228
Estimates
Measure: Abundance
Station
Mean
Std. Error
95% Confidence Interval
Lower Bound
Upper Bound
1
2.417
3.525
-6.210
11.043
2
11.500
3.525
2.874
20.126
3
37.333
3.525
28.707
45.960
Pairwise Comparisons
Measure: Abundance
(I) Station
(J) Station
Mean Difference
Std. Error
Sig.b
95% Confidence Interval for
Differenceb
(I-J)
Lower Bound
1
2
3
Upper Bound
2
-9.083
4.986
.118
-21.283
3.116
3
-34.917*
4.986
.000
-47.116
-22.717
1
9.083
4.986
.118
-3.116
21.283
3
-25.833*
4.986
.002
-38.033
-13.634
1
34.917*
4.986
.000
22.717
47.116
2
25.833*
4.986
.002
13.634
38.033
Based on estimated marginal means
*. The mean difference is significant at the .05 level.
b. Adjustment for multiple comparisons: Least Significant Difference (equivalent to no adjustments).
Univariate Tests
Measure: Abundance
Sum of Squares
Contrast
Error
df
Mean Square
1969.042
2
984.521
223.708
6
37.285
F
26.405
Sig.
.001
The F tests the effect of Station. This test is based on the linearly independent pairwise
comparisons among the estimated marginal means.
Multivariate Tests
Value
Error df
3.000
4.000
.121
.267
3.661a
3.000
4.000
.121
2.746
3.661a
3.000
4.000
.121
2.746
3.661a
3.000
4.000
.121
Each F tests the multivariate effect of OAbd. These tests are based on the linearly
independent pairwise comparisons among the estimated marginal means.
a. Exact statistic
4. Station * OAbd
Measure: Abundance
Station
OAbd
Mean
Std. Error
95% Confidence Interval
Lower Bound
1
2
3
Sig.
.733
Wilks' lambda
Roy's largest root
Hypothesis df
3.661a
Pillai's trace
Hotelling's trace
F
Upper Bound
1
2.667
4.558
-8.487
13.820
2
1.333
2.828
-5.588
8.254
3
2.667
8.662
-18.529
23.863
4
3.000
7.720
-15.889
21.889
1
8.333
4.558
-2.820
19.487
2
7.333
2.828
.412
14.254
3
14.000
8.662
-7.196
35.196
4
16.333
7.720
-2.556
35.223
1
19.667
4.558
8.513
30.820
2
28.667
2.828
21.746
35.588
3
45.000
8.662
23.804
66.196
4
56.000
7.720
37.111
74.889
Summary and Conclusion
The Logolog River has an average temperature of 31.36˚C, average salinity of 27.17 ˚C,
average pH of 7.4, average Biochemical Oxygen Demand (BOD) of 1.14 mg/L, average Total
Coliform of 20,118 MPN, average Fecal Coliform of 109 MPN, and average Total Suspended Solids
(TSS) of 62.69 mg/L. Mean abundance of 8counts/station (zooplankton Oithona)
and 9
counts/station (phytoplankton Peridinium) was obtained along the stretch of the subject river.
Densest assemblage of Peridinium (166 countm/station) was obtained in the upstream
river section. In contrast, Oithona were (17 countm/station) found most abundant at downstream
of Logolog.
In application of Pearson-R analysis, it was revealed that there is strong positive
correlation (.785) between TSS and Temperature. This implies the significant influence of
suspended solids to warming of water temperature. In contrary, strong negative correlation (.636) was obtained between association of BOD and TSS, suggesting that as the TSS level
increases the BOD level decreases.
Out of correlated variables, regression analysis was also carried out to determine good
predicting factor/s for the plankton (Oithona and Peridinium) abundance. Derived from lengthy
calculations, only the water salinity was identified the potent predicting variable (y = -12.516x
+415.27;R² = 0.3559) of water salinity. Abundance of genus Oithona, on the other hand, obtained
no match of possible predicting variable.
Analysis of Variance for repeated measures (ANOVAr) was also performed thru SPSS as
means to validate if there is/ is no significant difference (0.003) among subjects. In application
of ANOVAr, the test revealed that the abundance of phytoplankton Peridinium, scattered at
three (3) river sections measured weekly in a month, are not statistically equal. Therefore, the
significant difference can support that the most abundant area for Peridinium are usually found
in the headwater of a stream. Meanwhile, the abundance of zooplankton Oithona obtained at
three river sections are statistically not equal with p value of (0.001).
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