R: Species Sensitivity Distribution (SSD) for endosulfan

endosulfan {fitdistrplus} | R Documentation

## Species Sensitivity Distribution (SSD) for endosulfan

### Description

Summary of 48- to 96-hour acute toxicity values (LC50 and EC50 values) for exposure of Australian an Non-Australian taxa to endosulfan.

### Usage

    data(endosulfan)

### Format

`endosulfan` is a data frame with 3 columns, named ATV for Acute Toxicity Value (geometric mean of LC50 ou EC50 values in micrograms per liter), Australian (coding for Australian or another origin) and group (arthropods, fish or non-arthropod invertebrates).

### Source

Hose, G.C., Van den Brink, P.J. 2004. Confirming the Species-Sensitivity Distribution Concept for Endosulfan Using Laboratory, Mesocosms, and Field Data. Archives of Environmental Contamination and Toxicology, 47, 511-520.

### Examples

    # (1) load of data
    #
    data(endosulfan)

    # (2) plot and description of data for non Australian fish in decimal logarithm
    #
    log10ATV <-log10(subset(endosulfan,(Australian == "no") & (group == "Fish"))$ATV)
    plotdist(log10ATV)
    descdist(log10ATV,boot=1000)

    # (3) fit of a normal and a logistic distribution to data in log10
    # (classical distributions used for SSD)
    # and visual comparison of the fits
    #
    fln <- fitdist(log10ATV,"norm")
    summary(fln)

    fll <- fitdist(log10ATV,"logis")
    summary(fll)

    cdfcomp(list(fln,fll),legendtext=c("normal","logistic"),
    xlab="log10ATV")

    denscomp(list(fln,fll),legendtext=c("normal","logistic"),
    xlab="log10ATV")

    qqcomp(list(fln,fll),legendtext=c("normal","logistic"))
    ppcomp(list(fln,fll),legendtext=c("normal","logistic"))

    gofstat(list(fln,fll), fitnames = c("lognormal", "loglogistic"))

    # (4) estimation of the 5 percent quantile value of
    # logistic fitted distribution (5 percent hazardous concentration  : HC5)
    # with its two-sided 95 percent confidence interval calculated by
    # parametric bootstrap
    # with a small number of iterations to satisfy CRAN running times constraint.
    # For practical applications, we recommend to use at least niter=501 or niter=1001.
    #
    # in log10(ATV)
    bll <- bootdist(fll,niter=101)
    HC5ll <- quantile(bll,probs = 0.05)
    # in ATV
    10^(HC5ll$quantiles)
    10^(HC5ll$quantCI)

    # (5) estimation of the 5 percent quantile value of
    # the fitted logistic distribution (5 percent hazardous concentration  : HC5)
    # with its one-sided 95 percent confidence interval (type "greater")
    # calculated by
    # nonparametric bootstrap
    # with a small number of iterations to satisfy CRAN running times constraint.
    # For practical applications, we recommend to use at least niter=501 or niter=1001.
    #
    # in log10(ATV)
    bllnonpar <- bootdist(fll,niter=101,bootmethod = "nonparam")
    HC5llgreater <- quantile(bllnonpar,probs = 0.05, CI.type="greater")
    # in ATV
    10^(HC5llgreater$quantiles)
    10^(HC5llgreater$quantCI)

    # (6) fit of a logistic distribution
    # by minimizing the modified Anderson-Darling AD2L distance
    # cf. ?mgedist for definition of this distance
    #

    fllAD2L <- fitdist(log10ATV,"logis",method="mge",gof="AD2L")
    summary(fllAD2L)
    plot(fllAD2L)

[Package fitdistrplus version 1.0-9 Index]