The effect of intervention in nickel concentrations on benthic macroinvertebrates: A case study of statistical causal inference in ecotoxicology

摘要

Field survey-based ecological risk assessments for trace metals are conducted to examine the necessity and/or effectiveness of management intervention, such as setting of environmental quality standards. Observational datasets often involve confounders that may bias estimation of the effects of intervention (e.g., reduction of trace-metal concentrations through regulation). The field of ecotoxicology lags behind some other research fields in understanding proper analytical procedures for causal inference from observational datasets; there are only a few field survey-based ecotoxicological studies that have explicitly controlled for confounders in their statistical analyses. In the present study, we estimated the effect of intervention in nickel concentrations on Ephemeroptera, Plecoptera, and Trichoptera richness in rivers in Japan. We also provide detailed explanations for the backgrounds of spurious associations derived from confounders and on proper analytical procedures for obtaining an unbiased estimate of the targeted intervention effect by using regression analysis. We constructed a multiple regression model based on a causal diagram for aquatic insects and environmental factors, and on "the backdoor criterion," that enabled us to determine the set of covariates required to obtain an unbiased estimate of the targeted intervention effect from regression coefficients. We found that management intervention in nickel concentrations may be ineffective compared to intervention in organic pollution, and that analysis ignoring the confounders overestimated the effect of intervention in nickel concentrations. Our results highlight the fact that confounders can lead to misjudging the necessity for management of anthropogenic chemical substances. Confounders should be explicitly specified and statistically controlled to achieve a comprehensive assessment of ecological risks for various substances. (C) 2020 The Authors. Published by Elsevier Ltd.