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Page 2
Time point
Food level
Prochloraz
RMSE
Observedb
Predictedc
MDRd
(μg/L)
SAa
CA
EA
LC50
LC50
SAa
CA
EA
Day 21
Low food
0
–
–
–
0.098
–
–
–
–
1
6.0
8.3
5.6
0.048
0.079
1.7
3.2
0.93
32
4.2
17
10
0.0066
0.0023
0.34
25
6.8
100
5.8
25
18
0.0003
0.0008
2.8
660
150
High food
0
–
–
–
0.49
–
–
–
–
1
6.8
3.1
3.1
0.55
0.59
0.77
0.94
0.94
32
8.4
17
16
0.19
0.21
1.4
2.8
2.6
100
4.9
14
13
0.20
0.22
1.0
2.7
2.6
Day 7
Low food
0
–
–
–
0.13
–
–
–
–
1
5.9
9.7
6.8
0.053
0.11
2.1
2.8
1.4
32
4.1
15
9.8
0.012
0.017
1.4
14
6.2
100
7.7
25
19
0.001
0.0032
3.2
240
75
High food
0
–
–
–
0.53
–
–
–
–
1
5.6
4.4
4.4
0.65
0.49
0.80
0.82
0.82
32
8.0
14
14
0.26
0.33
1.2
2.1
2.0
100
7.4
13
13
0.25
0.19
0.71
2.2
2.1
Predictions with different approaches for combining stressors: Stress-Addition according to the Multi-TOX approach (SA), effect-addition (EA) and concentration-addition (CA). Whole curve estimates of combined toxicant effect: root mean square error (RMSE). Point estimate (LC50) of combined toxicant effect: model deviation ratio (MDR)
aSA (stress addition) calculated according to the Multi-TOX approach. For low food 81% SA, for high food 38% SA
bObserved LC50 calculated with the mean survival of all experimental repetitions, fitted with ECx-SyS
cPredicted LC50 based on the concentration–response relationships of single toxicants modeled with stress addition according to the Multi-TOX approach
dMDR values are calculated by dividing the predicted LC50 of SA, CA, EA by the observed LC50. For values of CA > 2, interactions between stressors are interpreted as synergistic related to CA