From static to dynamic: Embracing dynamics in isotopic diet estimation

Area of Science:

• Ecology
• Ecological modeling
• Stable isotope analysis

Background:

• Isotopic mixing models are crucial for diet quantification in ecology.
• Static models assume stable isotopic systems, ignoring temporal dynamics.
• Temporal variations can introduce significant bias into diet estimates.

Purpose of the Study:

• To characterize bias in isotopic mixing models due to temporal dynamics.
• To develop a dynamic mixing model that accounts for these temporal effects.
• To evaluate strategies for mitigating bias in static models.

Main Methods:

• In silico experiments and computational modeling.
• Analysis of isotopic turnover rates and sampling frequency.
• Development and validation of a dynamic mixing model.

Main Results:

• Bias is strongly influenced by the interaction between isotopic turnover rate and sampling frequency.
• Consumer isotopic signature prior to dietary shifts and source signature fluctuations amplify bias.
• Previously recommended bias mitigation strategies were evaluated and refined.

Conclusions:

• Temporal dynamics significantly impact isotopic mixing model accuracy.
• The developed dynamic mixing model offers a robust and accurate approach for diet estimation.
• Guidelines for applying bias mitigation strategies in static models are provided.