42
This matrix shows that the highest oyster mortality was happened in the station 15. If we make a cluster 50 the similarity based on station in this
matrix, we will find 3 clusters, which are first group consist of station 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, and 14 smaller of mortality oysters, second group is
station 2, and last group is station 15. However, we can’t cluster oyster mortalities based on time month. The variance analysis of BSP adult as shown in table 7.
Table 7. Variance analysis of BSP
Source Sum of Squares
Df Mean Square
F-Ratio P-Value
month 0.0444764
7 0.00635377
1.46 0.1909
station 0.308727
14 0.0220519
5.07 0.0000
Residual 0.417884
96 0.00435296
Total corrected 0.775067
117
:very significant
Based on table 7, the statistical significance of each factor is different for each variable. Notice that the highest P-value is 0.4104, belonging to time. The P-
value is greater or equal to 0.05, that term is not statistically significant at the 95.0 confidence level. In contrary, P-value for station is inferior to 0.05, that
term means that the oyster mortalities are significant with the station.
4.3 Oyster’s mortality by predation
As we know BAP is oyster culture with all aspect of mortality predation, disease -virus or parasite- and others and BSP is oyster culture with disease and
others kind of mortality like sediment effect except predation with a number of dead oysters for predation and a percentage of mortality for diseases and others
causes. Logically, the dead oysters by predation would be : BAP-BSP explanation in the annex. The variance analysis of BAP-BSP in time and
station as shown in table 8.
Table 8. Variance analysis of BAP-BSP
Source Sum of Squares
Df Mean Square
F-Ratio P-Value
month 13940.9
7 1991.56
3.61 0.0017
station 60040.4
14 4288.6
7.77 0.0000
Residual 54124.0
98 552.286
Total corrected 128105.
119
:very significant
43
Based on table 8, the statistical significance of each factor is same. The number of dead oyster by predation is statistically significant at the 95.0 confidence level
in variables, time and station. 1. The effect of gastropods
Interaction between gastropods and number of dead oyster by predation BAP-BSP per month is not significant in 95 confidence level table 9.
Table 9. Variance analysis of BAP-BSP and gastropods
Source Sum of Squares
Df Mean Square
F-Ratio P-Value
Model 22123.5
15 1474.9
1.45 0.1373
Residual 105589.
104 1015.28
Total Corr. 127713.
119
The interaction between BAP-BSP and Ocinebrillus per month as showed in table 10.
Table 10. Variance analysis of BAP-BSP and Ocinebrillus
Source Sum of Squares
Df Mean Square
F-Ratio P-Value
Model 21113.0
15 1407.53
1.37 0.1744
Residual 106600.
104 1025.0
Total Corr. 127713.
119
Because the P-value in the ANOVA table is greater or equal to 0.05, there is not a statistically significant relationship between the variables at the 95.0 or higher
confidence level. Here, we can’t find interaction analysis of BAP-BSP and gastropod per
station, or compared BAP-BSP with Ocenebra and Ocinebrellus per station because all of the data were same or homogen. The number of gastropods can be
compared with the distinction of BAP and BAP-BSP each month Figure 27.
44
Month=May Month=September
Month=June Month=October
Month=July Month=November
Month = August Month = December
Figure 27. Interaction gastropods between BAP and BAP-BSP per month
45
As shows in figure 27, the interaction of gastropods between number of dead oysters BAP and BAP-BSP are variance in the time, like in November and
December, there aren’t significant interaction between gastropods and both of number dead oysters.
2. The effect of starfishes Interaction between gastropods and number of dead oysters by predation
BAP-BSP per month is significant in 95 confidence level table 11.
Table 11. Variance analysis between BAP-BSP and starfish
Source Sum of Squares
Df Mean Square
F-Ratio P-Value
Model 59534.2
15 3968.95
6.05 0.0000
Residual 68178.4
104 655.562
Total Corr. 127713.
119
:very significant
Figure 28 shows the interaction of starfish between number of dead oysters in BAP and BAP-BSP.
Figure 28. Interaction between starfishes BAP and BAP-BSP
Based in figure 28, the value of R-square near to 1, it mean that validity of this graphic is reliable. Each of starfish per month and station can eat 11 oysters in
BAP and 9 oysters in BAP-BSP. To further understand the role of Asterias and Marthasterias in oyster mortality in BAP-BSP table 12 and 13.
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Table 12. Variance analysis of Asterias and BAP-BSP per month
Source Sum of
Squares Df
Mean Square
F- Ratio
P-Value Model
54405.4 15
3627.02 5.12
0.0000 Residual
73699.9 104 708.653
Total Corr.
128105. 119
Table 13. Variance analysis of Marthasterias and BAP-BSP per month
Source Sum of
Squares Df
Mean Square
F- Ratio
P- Value
Model 44095.8
15 2939.72
3.64 0.0000
Residual 84009.5 104 807.784
Total Corr.
128105. 119
:very significant
Because the P-value in the ANOVA table is less than 0.05, there is a statistically significant effect between the variables at the 95.0 confidence level. The present
of Asterias rubens in the cage is low 2, but there is interaction Marthasterias glacialis between BAP and BAP-BSP Figure 29.
Figure 29.Interaction Marthasterias in BAP and BAP-BSP
As shows in this figure in each station and month, a Marthasterias glacialis consume 10,6 oysters in BAP and 8,9 oysters in BAP-BSP, and there is
interaction too between the presence of Asterias and Marthasterias in BAP and BAP-BSP Figure 30.
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Figure 30. Interaction between the presents of Asterias and Marthasterias in BAP and BAP-BSP
The presence of Asterias and Marthasterias have an impact with BAP and BAP- BSP. It means that if there were both starfishes in the cage at the same time and
same station, they consumed approximately 11 oysters in BAP and 10 oysters in BAP-BSP.
Remarks on the distinction of BAP and BAP-BSP. According to this results the number of dead oysters in BSP seems to be affected or controlled by the predation
not only by other kinds of mortalities.
4.4 Economic value on RISCO Project
