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1-A comparison of statistical methods for deriving freshwater quality criteria for the
ENVIRONMENTAL QUALITY BENCHMARKS FOR PROTECTING AQUATIC ECOSYSTEMS
A comparison of statistical methods for deriving freshwater
quality criteria for the protection of aquatic organisms
Liqun Xing Hongling Liu Xiaowei Zhang Markus Hecker
John P. Giesy Hongxia Yu
Received: 6 August 2012 /Accepted: 2 January 2013 /Published online: 15 January 2013
# Springer-Verlag Berlin Heidelberg 2013
Abstract Species sensitivity distributions (SSDs) are in-
creasingly used in both ecological risk assessment and deriva-
tion of water quality criteria. However, there has been debate
about the choice of an appropriate approach for derivation of
water quality criteria based on SSDs because the various
methods can generate different values. The objective of this
study was to compare the differences among various methods.
Data sets of acute toxicities of 12 substances to aquatic organ-
isms, representing a range of classes with different modes of
action, were studied. Nine typical statistical approaches, in-
cluding parametric and nonparametric methods, were used to
construct SSDs for 12 chemicals. Water quality criteria,
expressed as hazardous concentration for 5 % of species
(HC5), were derived by use of several approaches. All
approaches produced comparable results, and the data gener-
ated by the different approaches were significantly correlated.
Variability among estimates of HC5 of all inclusive species
decreased with increasing sample size, and variability was
similar among the statistical methods applied. Of the statistical
methods selected, the bootstrap method represented the best-
fitting model for all chemicals, while log-triangle and Weibull
were the best models among the parametric methods evaluated.
The bootstrap method was the primary choice to derive water
quality criteria when data points are sufficient (more than 20).
If the available data are few, all other methods should be
constructed, and that which best describes the distribution of
the data was selected.
Key
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