Document ID: chunk:federal_register_of_legislation:F2013C00288:reg:3:p11
Version: federal_register_of_legislation:F2013C00288
Segment Type: reg
Provision Reference: reg 3 (pt 11/21)
Character Range: 1373585–1376405

received considerable criticism from Calabrese and Baldwin (1993), Forbes and Forbes (1993), Schudoma (1994), and Smith and Cairns (1993), and some doubted whether the SSD methods were in fact better than the AF methods.

The key criticisms were:
    * whether ecosystems are sufficiently protected by protecting a given percentage of the species comprising that particular ecosystem
    * whether the distribution of species sensitivities in ecosystems is closely approximated by the distributions used in the various SSD methods
    * whether the SSD methods yield environmental quality guidelines that are conservative by nature.

A number of the other assumptions made by SSD methods were also attacked by these authors; however, these were assumptions made by all methods of deriving EQGs. There is considerable experimental support for the SSD methods (Emans et al. 1993; Okkerman et al. 1991, 1993). In addition, organisations such as the OECD compared both the SSD methods and AF methods and concluded by recommending the SSD methods (OECD 1995). An overview of the criticisms and support for the SSDs is provided in Warne (1996) and a more condensed version in Warne (1998). Several authors including Forbes and Calow (2002a) have now changed their position considerably and support SSDs while acknowledging their limitations. SSD methods are now well established and widely used in deriving EQGs and conducting ERAs. For example, SSD methods are the preferred method of deriving the EU soil and water quality guidelines (ECB 2003; EU 2006b).

A potential weakness of SSD methods, and indeed of all modelling methods, is that as the quantity of data used decreases the effect of the sample used increases dramatically. Initial studies by the Danish EPA (Pedersen et al. 1994) and the OECD (1995) indicated that WQGs derived using data sets containing less than five values were very dependent on the spread of the values, whereas for data sets containing five or more values this effect was markedly reduced. Subsequent more rigorous work by Newman et al. (2000), Forbes and Calow (2002b) and Wheeler et al. (2002) indicated that toxicity data for between 10 and 30 species was necessary for the resulting limit values to be stable irrespective of the sample. To calculate an HC5/PC95 value using empirical methods, at least 20 species are needed, and 100 species are needed for an HC1/PC99 value (Forbes & Calow 2002b). Using non-parametric methods, Newman et al. (2000) estimated for 30 toxicants that between 15 and 55 (median of 30) species per toxicant were needed, while Wheeler et al. (2002) estimated a minimum of 10 to 15 species per toxicant were needed. The decision by the regulating agency about the appropriate number of species is often arbitrary (Pennington 2003): US EPA requires at least eight