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Testing and applying a fish vitellogenesis model to evaluate laboratory and field biomarkers of endocrine disruption in Atlantic croaker (Micropogonias undulatus) exposed to hypoxia

Recently, hypoxia has been shown to act as an endocrine disruptor. We used a model of vitellogenesis in a female sciaenid fish to simulate the effects of hypoxia and to determine if reproductive impairment observed in field‐caught fish could be attributed to dissolved oxygen conditions at the sampling sites. The model is a set of coupled, ordinary differential equations that simulate major biochemical reactions from the secretion of gonadotropin to production of vitellogenin. Various intermediate variables in the model correspond to commonly measured biomarkers, and we assume a direct relationship between cumulative vitellogenin (VTG) and the gonadosomatic index (GSI). Model predictions were compared to results of laboratory studies that examined the effects of hypoxia on Atlantic croaker (Micropogonias undulatus) reproduction. When hypoxia was assumed to cause reduced gonadotropin and impaired aromatase activity, model predictions of VTG production were similar to laboratory‐measured reductions in GSI. The model was then applied to reproductive biomarkers measured in fish from normoxic and hypoxic locations in Pensacola Bay (FL, USA). We simulated the relationship between reduced estradiol‐17β and VTG production under hypoxia, and we compared these results with field data. Good agreement between field and simulation results suggested that croaker collected from hypoxic sites in October were exposed to hypoxic conditions for an extended period during gonadal recrudescence and that hypoxia was a dominant cause for the reduced GSIs. Monte Carlo uncertainty analyses suggested that the maximum rate of free testosterone production is the most sensitive parameter. Our simulations demonstrated that the model can be used identifying the mechanism underlying endocrine disruption and for interpreting field‐measured biomarkers in situations of multiple stressors.