EE2 impacts on zebrafish population dynamics extrapolated from organism-level endpoints using a DEB-IBM model
Résumé
Data used to estimate the likelihood of adverse ecological effects typically include responses of survival, growth, or reproduction of individuals measured after a specific exposure duration under constant laboratory conditions and in absence of ecological stress (e.g. predation and competition). These organism-level endpoints are far from the ecological features that the process aims to protect. Indeed, ecological risk assessment should protect the long-term persistence of populations of species in space and time under naturally varying field conditions and in the presence of other stressors (e.g. food limitation). In this context, population models can play an important role in bridging the gap between what is measured (organism-level endpoints) and what needs to be protected (population-level endpoints). Zebrafish (Danio rerio) is an attractive vertebrate model for investigating chemical ecotoxicity and to address the issues posed by Endocrine Disrupting Chemicals. Consequently, an individual-based model (IBM) of the population dynamics for zebrafish was developed in order to extrapolate from toxicity data measured on organism to biological levels relevant to support and enhance ecological risk assessment. The zebrafish population dynamics model was developed by coupling a DEB model with an IBM, and by integrating the main ecological factors (photoperiod, temperature, and food dynamics). The predictive capability of model was assessed with the 17a-ethinylestradiol (EE2). Indeed, abundant data was published on the EE2 impacts on organism-level endpoints and can be used to define the dose-response relationships integrated in our population model. In addition, at least one experiment was conducted at the population level with this compound [1] and could be used to test the predictions of our model. Two different cases were tested: (i) the exposure scenario conducted by Kidd et al. [1] and (ii) a discontinue exposure at different concentrations environmentally relevant. The exposure periods of the second scenario were defined using the sensitivity analysis of the model to define the worst case. Our model provided predictions comparable to the observations reported by Kidd et al. [1] notwithstanding the ecophysiology differences between the two species used. [1] Kidd KA, Blanchfield PJ, Mills KH, Palace VP, Evans RE, Lazorchak JM, Flick RW, 2007. Collapse of a fish population after exposure to a synthetic estrogen. Proc Nat Acad Sci USA 104:8897-8901.