Environmental Engineering Reference
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that incorporated laboratory, semifield and field studies to determine relationships
among effects linked to biomarkers, behavior, reproduction, and biomonitoring.
The authors found they could extrapolate from biochemical effects to population
level effects, but they could not statistically link population and community level
responses to chemical, limnological, and geomorphological field data. The causal
relationship between environmental conditions and effects could not be established.
In addition, several of the enzyme induction responses were not useful indicators
of exposure or effects (Triebskorn et al. 2003).
In a thorough review of fish bioaccumulation and biomarkers, Van Der Oost et al.
(2003) reported that predicting the extent to which biochemical alterations in a
population may influence the health of the population or ecosystem, is difficult.
Moreover, they discuss several cases in which fish diseases have been linked to
pollutant exposure, and exposure was linked to biomarker response, but they
concluded the discussion with further comments about the difficulty of correlating
biomarker responses to higher-level responses.
In a study of the effects of atrazine and its degradation products on routine
swimming, antipredator responses, resting respiration, and growth in red drum
larvae, Del Carmen Alvarez and Fuiman (2005) saw significant effects on swim-
ming behaviors and growth. They also found higher rates of predator-prey interactions.
However, the only quantitative prediction they made about population effects
resulted from reduced growth rates. The authors postulated that increased metabolic
rates, resulting from higher swimming rates, may lead to starvation, but no quanti-
tative link was established.
Others have struggled to understand the significance (to populations, communities or
ecosystems) of biomarkers observed in individuals. Olsen et al. (2001) found natural
variability as high as twofold in acetylcholinesterase and glutathione S -transferase levels
in Chironomus riparius Meigen larvae exposed at 13 uncontaminated sites. Such varia-
bility, in the absence of toxicants, suggests that it is difficult to discern toxicant effects by
monitoring activity levels of these enzymes. In a later study, Crane et al. (2002) deter-
mined that acetylcholinesterase inhibition in C. riparius is a good predictor of demo-
graphically important effects (e.g., reproduction), caused by exposure to the insecticide
pirimiphos methyl. In the same study, Crane et al. (2002) found that pirimiphos methyl
had no effect on glutathione S -transferase activity. Callaghan et al. (2002) similarly found
that acetylcholinesterase activity in C. riparius was a robust and specific biomarker for
exposure to organophosphate pesticides, and was unaffected by temperature variation. In
contrast, glutathione S -transferase activity was neither robust nor specific, with induction
occurring at low temperature and in response to pesticide exposure. Enzyme induction
was not linked to demographic effects in the study by Callaghan et al. (2002). In a field
study of the effects of bleached kraft mill effluents on fish, Kleopper-Sams and Owens
(1993) found that induction of P450 enzymes was a good biomarker for exposure, but
provided no predictive power for individual health or population level effects.
De Coen and Janssen (2003) have proposed a model for predicting population-
level effects based on biomarker responses in Daphnia magna . By measuring
digestive and metabolic enzyme activities, cellular energy allocation, DNA dam-
age, and antioxidative stress activity, they used a multivariate partial least squares
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