TDF_CAM: A method for estimating stable isotope trophic discrimination in wild populations

Area of Science:

• Ecology
• Wildlife Biology
• Isotope Ecology

Background:

• Stable isotope mixing models (SIMMs) are crucial for analyzing wild animal diets.
• Accurate trophic discrimination factors (TDFs) are essential for SIMMs but traditionally derived from time-consuming feeding trials.
• Existing TDF methods may not capture natural variability in wild populations.

Purpose of the Study:

• To present and evaluate TDF_CAM, an alternative method for estimating TDFs in wild populations.
• To assess the applicability of TDF_CAM using nest camera data as a high-precision dietary source.
• To compare the performance of Bayesian SIMMs (BSIMMs) using TDF_CAM against other TDFs.

Main Methods:

• Developed and applied the TDF_CAM approach using nest camera data and stable isotope (δ¹³C & δ¹⁵N) data from wild raptor nestlings.
• Formulated BSIMMs incorporating TDF_CAM-derived TDFs and compared model performance with alternative TDFs.
• Conducted sensitivity analyses to explore TDF_CAM variability and influencing factors.

Main Results:

• BSIMMs utilizing TDF_CAM consistently outperformed models with other TDFs across species and tissue types, yielding reliable diet composition estimates.
• TDF_CAM provided more accurate trophic discrimination estimates than controlled feeding studies, even with small sample sizes (n<10).
• Variability in TDF_CAM estimates was linked to analytical precision of dietary data and natural factors like nestling condition and diet composition.

Conclusions:

• TDF_CAM is an effective and accurate method for estimating trophic discrimination in wild animal populations.
• This approach is adaptable to any high-accuracy diet monitoring method contemporaneous with isotopic turnover.
• TDF_CAM offers a practical alternative to controlled feeding trials, enhancing ecological diet studies.