Improved estimates of certainty in stable-isotope-based methods for tracking migratory animals

Area of Science:

• Ecology
• Isotope Biogeochemistry
• Conservation Biology

Background:

• Stable-hydrogen isotopes (deltaD) are crucial for tracking migratory animal movements.
• Existing models often overlook errors in precipitation deltaD patterns and tissue measurements.
• This limits the certainty of assigning geographic origins for migratory species.

Purpose of the Study:

• To evaluate the impact of incorporating spatial and analytical errors into stable-hydrogen isotope (deltaD) assignment models.
• To assess how these errors influence the certainty of determining breeding origins for migratory birds.
• To explore the consequences of assignment uncertainty on predicting population dynamics.

Main Methods:

• Developed a stochastic extension to likelihood-based assignment tests.
• Incorporated spatial interpolation error for precipitation deltaD and analytical error for tissue deltaD measurements via simulation.
• Modeled the effect of winter habitat loss on population declines using error-influenced assignment distributions.

Main Results:

• Assignments incorporating errors showed variations up to 54% in regional proportions compared to error-free models.
• The inclusion of errors generated distributions of population change, including scenarios of no change or increase.
• Error modeling revealed potential challenges in the certainty of isotope-based connectivity data for population predictions.

Conclusions:

• Acknowledging and incorporating spatial and measurement errors in deltaD data is essential for robust inference.
• Improved accuracy in assigning migratory origins enhances predictions of population dynamics.
• Future studies should integrate these error sources for more reliable stable-isotope-based research on animal movement and connectivity.