Most toxicity data are developed for biological endpoints at the level of the individual organism, such as mortality, fecundity, or physiological responses. Suborganismal endpoints such as alterations in enzymatic expression are becoming more common with increased research into biomarkers that can measure changes in these pathways. Typical risk assessments ignore effects above the level of the organism, or only qualitatively discuss risks to populations and higher levels of organization. Ecotoxicological models are important tools for addressing these higher levels of organization in an ecological risk assessment.
Ignoring population-level or higher-level effects and focusing only on organism-level endpoints may over- or underestimate risks, leading to possible errors in environmental management decisions. Thus, ecological risk assessments should address ecologically relevant endpoints, such as population growth, population age/size structure, recruitment, biodiversity, ecosystem productivity, and indices oflandscape pattern. Ecological relevance is one aspect of ecological significance, which is a critical element of risk characterization in ecological risk assessment. Ecological significance is defined as the importance to population, community, or ecosystem responses (especially those that impact ecological structure and function). Several factors contribute to ecological significance, including the nature and magnitude of effects, the spatial and temporal extent of effects, and the recovery potential under partial or complete removal of a stressor.
For our purposes, an ecotoxicological model is a mathematical expression that can be used to describe or predict the effects of toxic chemicals on endpoints such as population abundance (or density), community species richness, productivity, or distributions of organisms. Ecotoxicological models are therefore useful in evaluations of the ecological significance of perturbations of organism-level endpoints, such as survivorship or fecundity.
Higher-level models may be used to evaluate chemicals and other factors (e.g., habitat, nutrient enrichment) that affect population abundance and distribution, biological community structure, and ecosystem processes. For example, several researchers have concluded that the growth rate parameter for a population integrates potentially complex interactions among life-history traits and thereby provides a more relevant measure of toxicant impacts than organism-level endpoints. Thus, these researchers favor using population models for ecological risk assessment. Others favor using ecosystem or higher-level models to interpret chemical exposure-response data for organismlevel endpoints in addressing more complex issues above the population level.
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