U.S. Department of Commerce
Date of this Version
2006
Abstract
Standard laboratory toxicity tests assess the physiological responses of individual organisms to exposure to toxic substances under controlled conditions. Time and space restrictions often prevent the assessment of population-level responses to a toxic substance. Contaminants can affect various biological functions (e.g. growth, fecundity or behavior), which may alter different demographic traits, leading to population-level impacts. In this study,immune suppression, reproductive dysfunction and somatic growth impairment were examined using life history matrix models for coho salmon (Oncorhynchus kisutch), sockeye salmon (Oncorhynchus nerka) and chinook salmon (Oncorhynchus tshawytscha). Our intent was to gauge the relative magnitude of response to toxic effects among species and between life history stages, not provide a specific estimate of population growth rate or abundance. Effects due to immune suppression were modeled as reductions in age-specific survival. Toxic impacts on reproductive function were modeled as a 10% reduction in reproductive contribution for all reproductively mature age groups. Model runs that examined the effect of somatic growth reduction on population parameters incorporated both survival and reproductive impacts. All impacts were modeled as 10% reductions in the affected population demographic parameters. First-year survival and reproductive impacts produced similar population growth rates (λ), but resulted in different sensitivity and stable age distributions. Modeled somatic growth reduction produced additive effects on survival and reproduction. Toxic stressors producing similar changes in λ did not necessarily produce similar changes in the age distributions. Sensitivity and elasticity analyses demonstrated that changes to the first-year survival rate produced the greatest per-unit effect on λ for each species. Alteration in abundance of mature females also strongly influenced λ. Differences observed between species showed that the number of reproductive ages and time to reproductive maturity were important components for population-level responses. These results emphasize the importance of linking toxicity responses at low concentrations to the demographic traits they affect, and help to highlight the toxicity tests that are more suitable for assessing impacts on the focal species. Additionally, life history modeling is a useful tool for developing testable hypotheses regarding impacts on specific populations as well as for conducting comparisons between populations.
Comments
Published in Ecological Modelling 199 (2006) 240–252