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et al. (2003b) used a multivariate model based on short-term biomarker measurements
to successfully predict population-level responses of
Daphnia magna
. These biomarkers
included activities of digestive enzymes, enzymes of intermediary metabolism, cellular
energy allocation, DNA damage, and antioxidative stress activity. Rose et al. (2003) mod-
eled the effects of PCB exposure on populations of fish, integrating experimental results
on fecundity, egg mortality, and larval behavior.
Such studies merit being developed because they not only link effects at different levels
of biological organization, but also link the results of laboratory experiments with field
studies. The experimental results are in effect being used to predict the order of mag-
nitude of the population effects in the field. This predicted response can be compared
against the variability in population abundance and population dynamics observed in
the field. The cumulative effect of multiple stressors can thus be investigated through the
modeling. Moreover, Rose et al. (2003) propose that their model can be used to simulate
the growth of fish populations with and without the effects of PCB exposure, or indeed in
the presence or absence of other stress factors such as increased fishing.
16.3.3 Regulatory Acceptability
Because it is difficult to study directly the fate of a population at a contaminated site, the
extrapolation from individual to population level in an ecological model appears an attrac-
tive substitute in order to meet the demands of regulatory bodies (Grimm et al. 2009; Preuss
et al. 2009; Galic et al. 2010; Hommen et al. 2010). However, the use of ecological models
to support regulatory risk assessments of contaminants is patchy, being rarely used, for
example, for pesticides (Schmolke et al. 2010). These authors reviewed relevant models
available in an assessment of their suitability for use in such regulatory risk assessments
and found that, in spite of meeting high scientific standards, most currently available eco-
logical models would need modifications before being considered suitable for regulatory
risk assessments. Similar conclusions have been reached by Galic et al. (2010) and Forbes
et al. (2011). Galic et al. (2010) highlighted the advantages of the use of ecological models
as the relatively straightforward integration of the sensitivity of species to chemicals, the
mode of action and fate in the environment of toxicants, life history traits of the species of
concern, and landscape features. These authors reviewed 148 publications in an attempt to
establish whether existing published ecological modeling studies have addressed (or have
the potential to address) the protection aims and requirements of the chemical directives
of the EU. Most models had been developed to establish population-level responses on
the basis of individual effects, but the lack of clarity about protection goals in legislative
documents made it impossible to establish a direct link between modeling studies and
protection goals (Galic et al. 2010).
Ecological risk assessments within regulatory frameworks are tailored to fit decision-
making needs, the quality of available data, and legally mandated protection goals (Kramer
et al. 2011). Although the protection and associated risk assessment for an individual
organism might be appropriate in the management of an endangered species, it is clear
from the above discussion that ecological risk assessments of environmental contaminants
need to address population-level effects. Population models, especially those informed by
AOPs, can be used to translate individual-level study results to population-level responses
(Kramer et al. 2011). The challenge is to effectively translate quantitative mechanistic AOP
data to higher-level responses meaningful to population modeling and realistic ecological
risk assessment; in this context, model validation is a critical requirement (Kramer et al.
2011), but a criterion rarely met (Schmolke et al. 2010).
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