Environmental Toxicology and Chemistry, Vol. 34, No. 8, pp. 1793–1798, 2015
# 2015 SETAC
Printed in the USA
Short Communication
DO WATER QUALITY CRITERIA BASED ON NONNATIVE SPECIES PROVIDE APPROPRIATE
PROTECTION FOR NATIVE SPECIES?
XIAOWEI JIN,*y ZIJIAN WANG,z YEYAO WANG,y YIBING LV,y KAIFENG RAO,z WEI JIN,x JOHN P. GIESY,k#yyzz§§
and KENNETH M. Y. LEUNGkk
yDepartment of Analytical Technique, China National Environmental Monitoring Center, Beijing, China
zState Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing,
China
xShijiazhuang Environmental Monitoring Center, Shijiazhuang, China
kDepartment of Veterinary Biomedical Sciences and Toxicology Centre, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
#State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, China
yyDepartment of Zoology and Center for Integrative Toxicology, Michigan State University, East Lansing, Michigan, USA
zzSchool of Biological Sciences, University of Hong Kong, Pokfulam, Hong Kong, China
xxDepartment of Biology and Chemistry and State Key Laboratory in Marine Pollution, City University of Hong Kong, Kowloon, Hong Kong, China
kkThe Swire Institute of Marine Science and School of Biological Sciences, The University of Hong Kong, Pokfulam, Hong Kong, China
(Submitted 20 January 2015; Returned for Revision 7 March 2015; Accepted 10 March 2015)
Abstract: The potential use of toxicity data for nonnative species to derive water quality criteria is controversial because it is sometimes
questioned whether criteria based on species from one geographical region provide appropriate protection for species in a different
region. However, this is an important concept for the development of Chinese water quality criteria or standards. Data were assembled on
38 chemicals for which values were available for both native and nonnative species. Sensitivities of these organisms were compared
based on the 5% hazardous concentration values and the species sensitivity distribution from a literature review. Results of the present
study’s analysis showed that there is approximately 74% certainty that use of nonnative species to generate water quality criteria would
be sufficiently protective of aquatic ecosystems in China. Without applying any assessment factor to the water quality criteria generated
from nonnative species, the uncertainty would be 26% when the native Chinese species might be under protection. Applying an
assessment factor of 10 would offer adequate protection to native Chinese species for approximately 90% of tested chemicals and thus
reduce the uncertainty from 26% to 10%. Environ Toxicol Chem 2015;34:1793–1798. © 2015 SETAC
Keywords: Water quality criteria
Chinese native species
Species sensitivity distribution
approach. The species sensitivity distribution approach uses a
statistical distribution estimated from a sample of toxicity data
and visualized as a cumulative distribution function. Species
sensitivity distributions are used to calculate the concentration
at which a specified proportion of species will be affected,
such as the hazardous concentration for 5% of species (HC5).
Species sensitivity distributions are dependent on available
data sets and can differ in type of distribution, taxonomic
diversity, and sample size. A substantial amount of toxicity
data from several taxonomic groups is required to obtain a
robust HC5 [3].
In the species sensitivity distribution, the probability of a
threshold for effect being exceeded during either acute or
chronic exposures is developed. For instance, in the species
sensitivity distribution approach, the probability of a particular
proportion of species being affected can be estimated. This
approach requires data on the concentration–response relationships for a relatively large number of species. As an example, if
data for only 2 species were available, each species would
represent 50% of the frequency distribution, and resolution or
prediction would be poor. As a rule of thumb, it is suggested that
to use the species sensitivity distribution approach, data for a
minimum of 20 species should be available [3,4]. In this case,
each species would represent 5% of the total, and the resolution
of the predictive power of the analysis would be 5%. The species
sensitivity distribution approach assumes that the species tested
represent a random selection of all the possible sensitivities. If,
for instance, the data available were for similar species with
similar sensitivities that did not represent the entire range of
METHODOLOGIES FOR DERIVING WATER QUALITY
CRITERIA
Water quality criteria are defined as levels of individual
characteristics or descriptions of conditions of a water body
that, if met, will generally protect the designated use(s) and
water quality standards. The methods to conduct these
assessments vary among jurisdictions but, in general, have
the same elements and suffer from the same limitations and
uncertainties. Probabilistic approaches have been used to
describe among-species variation in sensitivities [1]. Two
basic methods for derivation of water quality criteria are in use
or proposed for use throughout the world. These include the
assessment factor method and statistical extrapolation methods, such as the species sensitivity distribution approach.
Single-point assessment factors are recognized as a conservative approach for dealing with uncertainty in assessing risks
posed by chemicals. Yet, current applications of safety factors
are based on policy rather than on empirical scientific
evidence, and they result in values that are protective but
not predictive [2]. The present study focuses on the derivation
of aquatic life criteria using the species sensitivity distribution
method because it can deliver greater statistical confidence to
the risk-assessment process compared with the single-point
* Address correspondence to jinxiaowei07@mails.ucas.ac.cn or
kmyleung@hku.hk.
Published online 12 March 2015 in Wiley Online Library
(wileyonlinelibrary.com).
DOI: 10.1002/etc.2985
1793
1794
Environ Toxicol Chem 34, 2015
X. Jin et al.
Figure 1. The distribution of the log-transformed ratio of hazardous concentration for 5% of species (HC5 ratio) between native and nonnative species in China
(open circles), The Netherlands (closed squares), Australia (triangles), and the Arctic (diamonds; i.e., Palearctic vs Nearctic species). Shaded area represents a
zone with the HC5 ratio varying from –2 to 2. Chemicals having 2 different HC5 ratios are in bold letters. 2,4-DCP ¼ 2,4-dichlorophenol; 2,4,6-TCP ¼ 2,4,6trichlorophenol.
possible sensitivities, then predicted probabilities would not be
accurate [5,6].
In natural ecosystems there are ranges of species, with
different natural histories and in different feeding guilds, that
might be differentially exposed or have different sensitivities to
stressors. It is impossible to test all of the species that make up
the biological community of an ecosystem. For this reason,
surrogate species are tested and then used as representatives of
sensitive species in the environment. In the semiprobabilistic
approach used by the US Environmental Protection Agency
(USEPA) to develop water quality criteria, sensitive species in
different families are selected to represent aquatic plants,
invertebrates, and vertebrates [7]. The USEPA guidelines state
that only aquatic species resident in North America can be used
as test species to derive the water quality criteria, such as the
criteria continuous concentration, for the protection of
freshwater and marine ecosystems [8–11]. In Australia, species
sensitivity distributions and protective concentrations for 95%
of local species are being used to derive water quality guidelines
for toxicants [12,13]. It is commonly thought that different
ecosystems contain different biological constituents and that a
concentration threshold that would be harmless in an ecosystem
might lead to irreversible toxic effects in others. The potential
use of toxicity data for nonnative species to derive water quality
criteria is controversial because it is sometimes questioned
whether criteria based on species from a geographical region
provide appropriate protection for species in a different
region [14]. This uncertainty could not be resolved previously,
in large part because of the paucity of toxicity data applicable for
local species. In particular, toxicity data, especially for chronic
effects on resident species in China, are sparse; and selection of
resident species for use in the development of aquatic life
criteria values is confounded by variations among ecosystems
throughout China. However, this is an important concept for the
development of Chinese water quality criteria or standards.
There might be differences between species in temperate
regions and those in tropical regions [15] or the Arctic and, of
course, between freshwater and marine environments [16]. In
fact, tropical species were found to be slightly more sensitive to
certain chemical substances than species from temperate
regions, so an application factor of 10 was suggested to ensure
protection of communities in tropical regions [15]. As a result of
conservation of biochemical and physiological mechanisms for
maintaining homeostasis in freshwater organisms, it is likely
that sensitivities of species within a particular class of organisms
would not vary significantly among countries within a climatic
region. Therefore, it is unlikely that there would be significant
differences between the overall sensitivities of organisms
between countries within the temperate zone.
WATER QUALITY CRITERIA TO PROTECT NATIVE SPECIES
IN CHINA
As China has developed economically and become more
industrialized, more attention has been paid to the development
of a system to protect the environment [17]. Previously, because
of a lack of resources, China often adopted water quality criteria
promulgated by other jurisdictions [18,19]. Historically, this
lack of data on toxicities of chemicals on Chinese species
pragmatically led to the use of toxicological data from foreign
toxicity databases of nonnative species (e.g., data extracted
from the USEPA’s ECOTOX database) to develop chemical
water quality criteria [18]. However, as environmental regulation and monitoring have become more sophisticated, the
adequacy of this approach has been questioned. The question
has been posed whether it would be more appropriate to develop
water quality criteria specific to the situation in China by
acquiring data on toxicity of chemicals to species native to
China. However, this uncertainty could not be resolved
previously, in large part because of the paucity of toxicity
data applicable for local species. For the more than 130
chemicals evaluated in the current Chinese Environmental
Quality Standards for Surface Water, and even more chemicals
needed to reestablish and revise their water quality criteria, data
are available for only few species indigenous to China.
Currently, the required resources, knowledge, and political
Australian vs non-Australian
Palearctic vs nearctic
Chinese vs non-Chinese
Taxonomic group
a
Ammonia
Phenola
4-Chlorophenol
Endosulfan
Lindane
Diazion
Fenitrothion
Chlorpyntos
Triclosan
Parathion
Nitrobenzene
Cadmium
Mercury
Arsenic (III)
a
Pentachlorophenol
2,4,6-Trichlorophenol
2,4-Dichlorophenol
Chemical
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Palearctic
Nearctic
Palearctic
Nearctic
Palearctic
Nearctic
Palearctic
Nearctic
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Species
17
71
8
6
9
28
13
17
10
36
7
14
6
11
13
6
14
15
13
21
12
60
14
16
47
33
49
50
20
13
32
38
12
12
Data number
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Data type
All
All
All
All
All
All
All
All
excl.
excl.
excl.
excl.
excl.
excl.
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
All
fish
fish
fish
fish
fish
fish
Taxonomic group
Log-Burr
Log-Burr
Log-Burr
Log-Burr
Log-Burr
Log-Burr
Log-Burr
Log-Burr
III
III
III
III
III
III
III
III
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-Burr III
Log-Burr III
Log-Burr III
Log-Burr III
Log-Burr III
Log-Burr III
Log-logistic
Log-logistic
Log-logistic
Log-logistic
Log-logistic
Log-logistic
Log-logistic
Log-logistic
Log-logistic
Log-logistic
Log-logistic
Log-logistic
Model fit
Table 1. Toxicity parameter of 38 chemicals for native and nonnative species
0.31
0.17
735
3018
8408
2177
96
93
0.09
0.15
0.9
1.6
0.36
0.37
2.07
1.47
1100
1060
790
720
35
57
264
335
3.52
8.69
4.39
2.0
8.86
13.59
0.22
0.02
33.48
48.46
HC5 (mg/L)
–0.51
–0.77
2.86
3.47
3.92
3.34
1.98
1.97
–1.04
–0.82
–0.05
0.20
–0.44
–0.43
0.31
0.17
3.04
3.02
2.89
2.85
1.54
1.75
2.42
2.52
0.54
0.94
0.64
0.30
0.95
1.13
–0.66
–1.69
1.52
1.68
Log HC5
0.97
0.26
4.11
0.55
0.71
1.03
1.78
1.67
1.45
0.09
1.53
0.45
2.47
1.27
1.63
0.91
0.96
Nonnative/native ratio
(continued)
[24]
[24]
[24]
[13]
[19]
[19]
[19]
[19]
[23]
[25]
[25]
[25]
[25]
[25]
[22]
[21]
[14]
Reference
Water quality criteria to protect native species in China
Environ Toxicol Chem 34, 2015
1795
Fenitrothion
Diazinon
Atrazine
Heptachlor
Methoxychlor
Azinphos-methyl
Endrin
Carbaryl
Chlorpyrifos
Deltamethrin
Endosulfan
Pentachlorophenol
Cadmium
Phenol
Copper
Trichlorfon
Lindane
Malathion
DDT
Ammonium
Zinc
Chemical
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Native
Nonnative
Species
13
7
10
9
8
7
8
8
8
7
8
7
7
7
8
6
6
7
8
5
6
7
8
4
8
4
5
6
5
6
5
6
5
5
4
6
4
6
5
5
4
4
Data number
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Acute
Data type
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Fish
Taxonomic group
Model fit
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
Log-normal
707
288
218
100
1.99
1
10
141
10
10
39.81
79.43
30.20
39.81
5248
2041
10
257
19.95
10
1
0.1
1
3.98
1
3.98
1202
2951
0.60
0.20
0.1
1.99
10
10
3.98
4.07
13 182
5754
39.81
1148
257
1548
HC5 (mg/L)
2.85
2.46
2.34
2
0.3
0
1
2.15
1
1
1.6
1.9
1.48
1.6
3.72
3.31
1
2.41
1.3
1
0
–1
0
0.6
0
0.6
3.08
3.47
–0.22
–0.7
–1
0.3
1
1
0.6
0.61
4.12
3.76
1.6
3.06
2.41
3.19
Log HC5
6.03
28.84
0.44
1.02
1
19.95
0.33
2.45
3.98
3.98
0.1
0.50
25.7
0.39
1.32
1.99
1
14.1
0.50
0.46
0.41
Nonnative/native ratio
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
[26]
Reference
Environ Toxicol Chem 34, 2015
a
Because there are no fish data available for Australia, the taxonomic groups for Non-Australian exclude (excl.) fish data.
HC5 ¼ hazardous concentration for 5% of species; DDT ¼ Dichlorodiphenyltrichloroethane.
Netherlands vs non-Netherlands
Taxonomic group
Table 1. (Continued)
1796
X. Jin et al.
Water quality criteria to protect native species in China
will are available for China to develop its own water quality
criteria to protect a range of aquatic environments. For social
and political reasons, it might be preferable to use species
native to China that have been generated under conditions that
simulate the Chinese environment. However, it would take a
long time and a great expenditure of resources to collect
sufficient information, especially for probabilistic approaches,
to achieve this goal. Furthermore, standard testing protocols
have yet to be established for a range of surrogate species based
on species endemic to China. To develop these test protocols
would require a large investment simply to acquire information
on nutritional requirements and culturing conditions for species
to be used in standardized tests. Although this is feasible, it
might not be the most timely and efficient method or allocation
of resources and might unduly delay implementation of water
quality criteria.
COMPARISONS OF SENSITIVITIES BETWEEN NATIVE AND
NONNATIVE SPECIES
Comparisons of sensitivities between species native to China
and nonnative species can be made for only a few chemicals,
including 2,4-dichlorophenol, pentachlorophenol, and triclosan
[14,20–22]. When this comparison was made, there was no
significant difference between sensitivities of Chinese and nonChinese taxa. In Australia, sensitivities of Australian and nonAustralian organisms to endosulfan, ammonia, 4-chlorophenol,
and phenol, based on calculated HC5 values, were similar [13,23]. Similarly, among North American and European
taxa with different geographic distributions, sensitivities to a
range of toxicants have been shown to be similar. Moreover,
natural history, habitat type, and geographical distribution of the
species used to construct the species sensitivity distribution did
not have a significant influence on the assessment of hazard; but
the taxonomic composition of the species sensitivity distribution does have a significant effect on resulting estimates of the
HC5 [24].
To further verify the similarity in chemical sensitivity
between native and nonnative species, we performed a metaanalysis for 38 cases for which the HC5 values of the chemicals
are available for both counterparts. The data set includes 9
chemicals for Chinese versus non-Chinese species, 4 chemicals
for Palearctic versus Nearctic species, 4 chemicals for
Australian versus non-Australian species, and 21 chemicals
for Netherlands versus non-Netherlands fish species. The
sensitivities of these organisms are compared based on the
ratio between the HC5 value of nonnative species and that of
native species generated from species sensitivity distributions
(i.e., if the ratio is <1, then nonnative species are more sensitive,
and vice versa). The results are summarized in Figure 1, and the
raw data and sources of information are provided in Table 1.
Assuming that there is an equal sensitivity when the HC5 ratio is
between –2 and 2 (i.e., differences within a factor of 2), 19 out
of the 38 cases (50.0%) will have an equal sensitivity between
native and nonnative species (Figure 1). Among the 38 cases,
native species are more sensitive to the chemicals for 10 cases
(26.3% when the HC5 ratio is 2), whereas nonnative
species are more sensitive to the chemicals for 9 cases
(23.7% when the HC5 ratio is –2). For chemicals being
tested twice with 2 different systems (i.e., phenol, cadmium,
ammonia, pentachlorophenol, and lindane), there are obvious
differences between the 2 HC5 ratios (Figure 1). Such results
suggest that the relative sensitivity between native and
nonnative species can be both chemical- and region-specific.
Environ Toxicol Chem 34, 2015
1797
The combined percentage would be 73.7% for encompassing
cases from those having an equal sensitivity to those in which
nonnative species are more sensitive. By extrapolating this
figure, there is approximately 74% certainty that using nonnative
species to generate water quality criteria would be protective of
Chinese aquatic systems. Without applying any assessment
factor to the water quality criteria generated from nonnative
species, the uncertainty would be approximately 26% when the
native Chinese species are under protection. Applying an
assessment factor of 10 will offer adequate protection to native
Chinese species for approximately 90% of tested chemicals
(Figure 1) and thus reduce the uncertainty from 26% to 10%.
It is important to sound a note of caution that there are some
intrinsic uncertainties for the above meta-analysis. For instance,
it is often the case that there are fewer data with a lower
taxonomic diversity in the toxicity data set for native species,
and this might lead to potential errors and bias in the comparison
as a result of the presence of more sensitive or nonsensitive taxa.
Although it is ideal to derive water quality criteria based on
native Chinese species, the process will be lengthy (i.e., several
years) to develop standardized tests and generate high-quality
data with native species before the generation of ecologically
sound water quality criteria. We strongly advocate the use of
surrogate data from other countries to formulate a set of
interim water quality criteria for managing water quality in
China as a means to provide some degree of protection to aquatic
ecosystems during this time gap. Based on the above metaanalysis, it is also feasible to apply an assessment factor (e.g.,
2–10) to account for the uncertainty of such extrapolations.
As a matter of fact, the problem of a lack of toxicity data for
native species exists not only in China but also in other countries
and regions such as Australia, Japan, Korea, South Africa, and
Southeast Asia. Some guiding principles for the developmental
process of a water quality criteria system are therefore urgently
needed with consideration of its reality, practicality, and
constraints such as those described herein. We hope that this
commentary will trigger more food for thought.
Acknowledgment—X. Jin and K.M.Y. Leung contributed equally to the
present study. The present study was financially supported by National
Natural Science Foundation of China (21307165) and the National
Major S&T Program for Water Pollution Control and Treatment
(2013ZX07502001). J.P. Giesy was supported by the 2012 program High
Level Foreign Experts (GDW20123200120) funded by the State Administration of Foreign Experts Affairs, People’s Republic of China, to Nanjing
University and the Einstein Professor Program of the Chinese Academy of
Sciences. J.P. Giesy was also supported by the Canada Research Chair
program, a visiting distinguished professorship in the Department of
Biology and Chemistry and State Key Laboratory in Marine Pollution, City
University of Hong Kong.
Data availability—The data, associated metadata, and calculation tools for
the present study are available. Please contact the corresponding author
(jinxiaowei07@mails.ucas.ac.cn).
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