Risks of Toxic Contaminants to Exploited Fish Populations: Influence of Life History, Data Uncertainty and Exploitation Intensity

Abstract

We investigated three aspects of the use of toxicity test data for population‐level risk assessment: (a) the influence of life history characteristics on vulnerability to contaminant‐induced stress, (b) the importance of test data availability and (c) the influence of exploitation intensity. We quantified population‐level effects of chronic contaminant exposure by coupling standard toxicity test data to matrix‐type population models derived from long‐term field studies of the Gulf of Mexico menhaden (Brevoortia patronus) and Chesapeake Bay striped bass (Morone saxatilis) populations. We used statistical regressions to quantify the uncertainty inherent in using test data ranging from life cycle tests to quantitative structure‐activity relationships (QSARs) to estimate effects of contaminants on the survival and reproduction parameters of the population models. We found that because of differences in life history, menhaden and striped bass differ in terms of their capacity to sustain the same level of contaminant‐induced mortality. Changes in exploitation intensity affect the responses of both populations to the same level of additional contaminant‐induced mortality. However, the quantitative effects of both factors are negligible compared to the uncertainty introduced by estimating long‐term effects from short‐term tests or QSARs. Our results suggest that consideration of life history may be important primarily for site‐specific assessments. For screening‐level assessments, the substantial differences in uncertainty associated with different types of test data are of much greater concern.

Measuring pesticide ecological and health risks in West African agriculture to establish an enabling environment for sustainable intensification

“…Where appropriate, small sample approaches were used as described in Whiteside et al [59]. Second, all available MATC-estimating regressions from Suter et al [63] and Barnthouse et al [64] were run on the HC 5 value. The lowest MATC estimate obtained was retained.…”

Derivation of Population-Level Ecological Remedial Action Objectives: Tualatin River Case Study

“…As shown in Table 2, population-level RAOs are higher than either fish population EC 20 values (Barnthouse et al, 1990) or Tier II secondary chronic values (Suter and Tsao, 1996). The lower fish EC 20 values may be explained by resource exploitation stress having been included as a factor in their derivation, whereas stressors other than contaminants were not a factor in this analysis.…”

Axes of Extrapolation in Risk Assessment

“…Rodent testing is a standard approach for obtaining data relevant to human health risks (see Arnold et al 1990), and bioassays using surrogate test species are the norm in certain types of ecological risk assessment. Ideally, biological responses can be extrapolated between species or taxa with acceptable uncertainty (in the sense of Figure 2a; see Barnthouse et al 1990) for an example from Extrapolation in Risk Assessment ecological risk assessment), but more than likely, the degree of correlation between the responses of the two species falls off as taxonomic distance between the two increases (Barnthouse et al 1990;Suter 1993) (Figure 2b). Biological extrapolations also involve moving from one level to another in a nested organizational hierarchy that ranges in scale from biochemicals at one extreme to the total biosphere at the other (shown conceptually in Figure 3).…”