Populations of a cyprinid fish are self-sustaining despite widespread feminization of males
1 Biosciences, College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4QD, UK
2 Institute for the Environment, Brunel University, Uxbridge, Middlesex UB8 3PH, UK
3 Centre for Ecology and Hydrology, Oxfordshire OX10 8BB, UK
BMC Biology 2014, 12:1 doi:10.1186/1741-7007-12-1Published: 13 January 2014
Treated effluents from wastewater treatment works can comprise a large proportion of the flow of rivers in the developed world. Exposure to these effluents, or the steroidal estrogens they contain, feminizes wild male fish and can reduce their reproductive fitness. Long-term experimental exposures have resulted in skewed sex ratios, reproductive failures in breeding colonies, and population collapse. This suggests that environmental estrogens could threaten the sustainability of wild fish populations.
Here we tested this hypothesis by examining population genetic structures and effective population sizes (Ne) of wild roach (Rutilus rutilus L.) living in English rivers contaminated with estrogenic effluents. Ne was estimated from DNA microsatellite genotypes using approximate Bayesian computation and sibling assignment methods. We found no significant negative correlation between Ne and the predicted estrogen exposure at 28 sample sites. Furthermore, examination of the population genetic structure of roach in the region showed that some populations have been confined to stretches of river with a high proportion of estrogenic effluent for multiple generations and have survived, apparently without reliance on immigration of fish from less polluted sites.
These results demonstrate that roach populations living in some effluent-contaminated river stretches, where feminization is widespread, are self-sustaining. Although we found no evidence to suggest that exposure to estrogenic effluents is a significant driving factor in determining the size of roach breeding populations, a reduction in Ne of up to 65% is still possible for the most contaminated sites because of the wide confidence intervals associated with the statistical model.