Predicting the effects of endocrine disrupting chemicals on healthy and disease impacted populations of perch (perca fluviatilis)
Authored by AR Brown, AM Riddle, IJ Winfield, JM Fletcher, JB James
Date Published: 2005
DOI: 10.1016/j.ecolmodel.2005.03.009
Sponsors:
United Kingdom Natural Environment Research Council (NERC)
Platforms:
No platforms listed
Model Documentation:
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Abstract
Long-term data from the perch population of the north basin of
Windermere, UK, were combined with effects data from laboratory toxicity
studies of survival, growth and reproduction in other species to assess
the likely impact on fish populations of different levels of exposure to
nonylphenol (NP) and ethinylestradiol (EE2). A multi-stage Delay
Differential Equation fish population model was used to simulate the
perch population during two periods when it showed contrasting
population structures (1968-1973 and 1983-1988) as the result of a
disease outbreak in 1976, and to extrapolate the effects of chemical
exposure to EE2 and NP observed in the laboratory to the environment. In
the absence of chemical exposure, model simulations predicted population
numbers (females) in line with those derived from field survey data.
Effects predictions were made for long-term exposure (20 years) to low
and high doses of EE2 (1 and 10 ng l(-1)) and NP (1 and 30 mu g l(-1)).
The sustained high-level exposure of EE2 had a high probability of
causing the extinction of a confined fish population such as that in
Windermere, however, such an exposure scenario is unlikely. Far greater
uncertainty surrounds the prediction of effects due to low-level
exposure of fish populations and even though effects may appear to be
significant in laboratory studies, such as fecundity lowered by 30\%, they may not necessarily translate into significant population effects
in the field. This is especially true if life-history data show high
natural variability in terms of individual vital rates. Our work
suggests that for a decline in the perch population numbers to be
significant in Windermere, it would have to be substantially more than
50\%. Our model predictions indicated that the post-disease population
was generally more vulnerable than the pre-disease population and had a
significantly greater probability of declining by 50\% following single
chemical exposure, but both populations were equally likely to decline
following multiple chemical exposure. Rate of population recovery was
shown to be a more sensitive measure in terms of differentiating the
effects of low and high chemical exposure as well as the vulnerability
of populations with contrasting structures, histories or levels of
background stress. (c) 2005 Elsevier B.V. All rights reserved.
Tags
Individual-based model
Pimephales-promelas
Fish populations
Life-history strategies
Pike esox-lucius
Juvenile rainbow-trout
Medaka oryzias-latipes
Environmental estrogens
Toxic contaminants
Synthetic estrogen