A Multidimensional Matrix Model for Predicting the Effects of Male-Biased Sex Ratios on Fish Populations

Area of Science:

• Environmental Toxicology
• Ecology
• Population Dynamics

Background:

• Exposure to endocrine-active substances during sexual differentiation can alter fish sex ratios.
• The long-term population consequences of skewed sex ratios depend on species life history and bias direction.

Purpose of the Study:

• To develop a novel multidimensional, density-dependent matrix model for evaluating the population-level effects of biased sex ratios in fish.
• To link chemical stressors affecting sex ratios to population status and adverse outcomes.
• To demonstrate the model's utility using fathead minnow exposed to the aromatase inhibitor prochloraz.

Main Methods:

• Developed a multidimensional, density-dependent matrix model analyzing age- and sex-structured populations over time.
• Applied the model to fathead minnow (Pimephales promelas) exposed to prochloraz during sexual differentiation.
• Simulated realistic exposure scenarios including concurrent exposure of adult and early life stages.

Main Results:

• The model quantitatively evaluated the impact of biased sex ratios on population size, sex composition, and recruitment.
• Demonstrated how prochloraz exposure during development and to adults affects population trajectories.
• Showcased the integration of chemical effects across different life stages and pathways.

Conclusions:

• Multidimensional matrix population models are valuable tools for ecological risk assessment.
• The model integrates individual-level chemical effects with population-level outcomes, even with varied exposure pathways.
• This approach links chemical stressors to population status and potential adverse effects in fish.