A Hybrid Individual-Based and Food Web-Ecosystem Modeling Approach for Assessing Ecological Risks to the Topeka...

Area of Science:

• Environmental toxicology
• Ecotoxicology
• Aquatic ecology

Background:

• Atrazine is a widely used herbicide with potential ecological impacts.
• The endangered Topeka shiner (Notropis topeka) is a sensitive indicator species for aquatic ecosystem health.
• Understanding atrazine's effects on aquatic food webs is crucial for conservation efforts.

Purpose of the Study:

• To characterize potential ecological risks of atrazine to the Topeka shiner population and its food web.
• To develop and apply a hybrid ecological model integrating bioenergetics and aquatic system dynamics.
• To assess risks under various atrazine exposure scenarios, including monitored and elevated concentrations.

Main Methods:

• A hybrid model combining a Topeka shiner individual-based bioenergetics population model (TS-IBM) and a comprehensive aquatic system model (CASM_TS) was utilized.
• Exposure-response functions were derived from published atrazine toxicity data (EC50s, NOECs) for algae.
• Simulations assessed Topeka shiner population dynamics and food web interactions under different atrazine concentrations and toxicity scenarios.

Main Results:

• No discernible food web effects on Topeka shiner populations were observed at monitored atrazine concentrations or constant exposures of 10 µg/L.
• Magnified monitored concentrations and higher constant atrazine exposures (≥50 µg/L) resulted in greater modeled indirect effects on Topeka shiners.
• The model indicated that indirect effects on prey were more sensitive to atrazine than direct effects on the fish.

Conclusions:

• The hybrid model provides a transparent and adaptable framework for assessing ecological risks of environmental stressors like atrazine.
• Atrazine poses minimal direct food web risk to Topeka shiners at typical environmental concentrations, but indirect effects warrant consideration at higher levels.
• The model's adaptability allows for application to other species and ecosystems, enhancing ecological risk assessment capabilities.