Tanaka Yoshinari

For the ecological risk assessment, extrapolation from toxicological data obtained at the individual level into effects at the population level is required. We review the analytical methods for translating chronic toxicity data into the effect on propensity of populations (population growth rate or intrinsic rate of population increase). Actual ecotoxicological data have two major problems, i.e., 1) only a very small fraction of chemicals-species combinations has been examined for chronic toxicity, and 2) it is not feasible for many test species to execute the life-cycle test. As analytical methods in order to circumvent these limitations of data, we focus on the extrapolation method and the life history sensitivity analysis, and discuss these methods in the context of ecological risk assessment. The cxtrapolation method is to infer missing chronic toxicity data from regression of known chronic data to acute data, or from regression of chromic data between different species or life stages. From the inferred and the directly estimated chronic toxicity data, the effect of chemicals to population growth rate is estimated. The life history sensitivity analysis estimates the relative importance of life stages in terms of intrinsic rate of natural increase, and reduces the life table evaluation by excluding the unimportant life stages. These analytical methods that apply the ecological theory may be important for future ecotoxicological data analysis embedded in the ecological risk assessment.

Ecotoxicological data using life table evaluation are reviewed and analyzed with the power function model. Life table evaluation and population growth experiments are proposed as experimental procedures that provide demographic parameters (e.g. intrinsic rate of natural increase) relevant for calculating extinction risk due to pollutant exposure. Totally 47 concentration vs. intrinsic rate data sets were collected and analyzed with two indices in the power function model, α and β. The α-value is the concentration at which the intrinsic rate of increase drops off below zero due to exposure and the β-value represents curvature of the response. The α-values, which represent strength of ecological toxicity, are highly correlated with acute LC50s. It is indicated that the α-values are indirectly predictable from acute LC50s. Such statistical extrapolation may be useful for ecological risk assessment based on extinction probability of populations.