Daphnia — Daphnia • drc

Data are from a binary mixture experiment that was based on a fixed-ratio design involving 5 rays: the 2 rays for the pesticides prochloraz and alpha-cypermethrin and 3 mixture rays corresponding to virtual mixture proportions of 25:75, 50:50, and 75:25.

Usage

data(Daphnia)

Format

A data frame with 140 observations on the following 6 variables.

dose.a: Dose of alpha-cypermethrin (mu g/L)
dose.p: Dose of prochloraz (mu g/L)
dose: Total dose in the mixture (mu g/L)
mix.frac: Mixture fraction
total: Total number of Daphnia
immob48: Number of immobile Daphnia after 48 hours

Details

Synergistic and antagonistic effects of binary mixtures between a number of fungicides and the pyrethroid insecticide alpha-cypermethrin were investigated using a standard test system. Only data for the specific binary mixture of prochloraz and alpha-cypermethrin are provided. Data were obtained from a Daphnia acute immobilisation test where the test organisms were divided into groups of five, placed in containers, exposed to a dose (either a mixture dose or a dose from one of the two pesticides), and followed for 48h.

Source

Data were kindly provided by N. Cedergreen.

References

Noergaard KB and Cedergreen N, Pesticide cocktails can interact synergistically on aquatic crustaceans. Environ Sci Pollut Res 17: 957-967 (2010). https://doi.org/10.1007/s11356-009-0284-4

Examples

library(drc)

## Displaying the data
head(Daphnia)
#>   dose.a dose.p dose mix.frac total immob48
#> 1   1.50      0 1.50        0     5       5
#> 2   1.50      0 1.50        0     5       5
#> 3   1.50      0 1.50        0     5       4
#> 4   1.50      0 1.50        0     5       5
#> 5   0.75      0 0.75        0     5       5
#> 6   0.75      0 0.75        0     5       5

## Fitting a two-parameter log-logistic model for binomial response
## using mix.frac to model each mixture ray individually
Daphnia.m1 <- drm(immob48/total ~ dose, mix.frac, weights = total,
data = Daphnia, fct = LL.2(), type = "binomial")
summary(Daphnia.m1)
#> 
#> Model fitted: Log-logistic (ED50 as parameter) with lower limit at 0 and upper limit at 1 (2 parms)
#> 
#> Parameter estimates:
#> 
#>          Estimate Std. Error t-value   p-value    
#> b:0      -2.08226    0.35213 -5.9134 3.351e-09 ***
#> b:0.75   -7.47956    1.79255 -4.1726 3.012e-05 ***
#> b:0.5    -3.22760    0.60334 -5.3495 8.818e-08 ***
#> b:0.25   -3.00588    0.57382 -5.2384 1.620e-07 ***
#> b:1      -3.61417    0.72249 -5.0024 5.662e-07 ***
#> e:0       0.29705    0.03489  8.5139 < 2.2e-16 ***
#> e:0.75   98.81146    8.13182 12.1512 < 2.2e-16 ***
#> e:0.5   123.96886   12.82359  9.6672 < 2.2e-16 ***
#> e:0.25  280.08032   30.42243  9.2064 < 2.2e-16 ***
#> e:1    4941.86142  477.42984 10.3510 < 2.2e-16 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## Plotting the fitted curves for each mixture fraction
plot(Daphnia.m1, xlab = "Total dose (mu g/L)", ylab = "Proportion immobile",
ylim = c(0, 1), legendPos = c(3, 0.9))