Protocol for the Derivation of Environmental and Human ... - CCME

• the sensitivity of the test controls replicate number and replicate variability. High test variability can
lead to inaccurate estimation of these concentrations, and
• loss of information on the dose-response of the chemical to the test organism and variability of the
data set.
Therefore, NOEC and LOEC data can vary significantly from study to study given the same test
conditions and may not reflect the "true" concentration for these endpoints. Recently, alternative
methods to hypothesis-based NOECs and LOECs were proposed (e.g., Mayer, 1991; Bruce and
Versteeg, 1992; Hoekstra and van Ewijk, 1993). The essence of these methods is lowdose/concentration
interpolation based on calculated doses/concentrations on the response curve.
Therefore, for reasons above, LOEC data interpolated or extrapolated from the dose-response curve is
preferred, but since most soil toxicity data are not calculated using this method, arbitrary uncertainty
factors accommodate for the lack of confidence with using this data in guidelines derivation.
Model Uncertainty
Due to the restrictions on model input parameters, the error associated with the guidelines derivation
can only be qualitatively assessed. The primary concern here is the ability of the statistical model
employed to accurately predict the concentration at which no effects or low-level effects are observed.
This of course is subject to the overall error inherent in toxicity data used to derive the guideline, but
also to the error in model design. For instance, if a large proportion of NOEC and LOEC data are
used for derivation, the degree to which these data affect output is a function of the statistical design
used in the model.
Another source of model uncertainty has been termed "stochasticity of species sensitivity" (Suter, 1993).
That is, species sensitivity is assumed to be a stochastic variable and can be characterized by fitting an
empirical or probabilistic distribution of test endpoints for several species to determine guidelines. There
is also uncertainty about the true distribution of species sensitivity. Recently, the Netherlands (e.g.,
Kooijman, 1987; van Straalen and Denneman, 1989; Aldenberg and Slob, 1991) and Denmark
(Wagner and Lokke, 1991) have proposed statistical methods in an attempt to quantify the uncertainty
of the "true" stochastic multi-species sensitivity distribution. These methods, however, are relatively data
intensive and have not been rigorously applied to soil toxicity data.
Depending on the method employed for deriving environmental guidelines, test endpoints may be used
that are not considered concentrations that pose low-level effects to a species (i.e., LC 50 , EC 50 ). The
goal of guidelines derivation is to estimate a concentration at which no significant adverse effects are
observed in field populations (agricultural and residential/parkland) or significant low-level effects in field
populations (commercial and industrial land). Therefore, uncertainty arises from the need to extrapolate
from median lethal or effective concentrations to areas of the species sensitivity distribution required for
guidelines derivation. Uncertainty factors are generally used for this extrapolation.
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