Bulk tissue versus amino acid carbon stable isotopes to reveal the diet and basal resource use of an invasive rodent

Stable isotope analysis is widely used to reconstruct food webs, characterize trophic relationships, and estimate dietary composition. However, bulk tissue stable isotope analysis (BSIA) can yield diffuse or imprecise estimates when dietary sources are isotopically similar. We compared carbon stable isotope analysis of amino acids (δ13C-EAA values) with BSIA (δ13C and δ15N values) to estimate diet composition and basal resource use of non-native, invasive house mice (Mus musculus) on Sand Island, part of a remote atoll in the north Pacific Ocean. We aimed to assess whether δ13C-EAA values could improve source differentiation and yield more precise diet estimates and to evaluate whether δ13C-EAA fingerprints could provide insight into the origin and use of basal resources by mice.
We applied a Bayesian mixing model using δ13C-EAA values from a subset of 10 mice and associated diet items, with sample selection guided by existing BSIA and next-generation sequencing datasets. Diet estimates..., , # Bulk tissue versus amino acid carbon stable isotopes to reveal the diet and basal resource use of an invasive rodent

Dataset DOI: [10.5061/dryad.4f4qrfjqg](10.5061/dryad.4f4qrfjqg)

## Description of the data and file structure

For this study, we used existing samples of house mouse hair and known diet items (including plants, arthropods, and mōlī feathers) from Sand Island of Kuaihelani, collected between April 2018 to November 2021 (Holthuijzen et al. 2023). Hair and fecal samples were obtained from 318 mice captured via a series of traplines across four main habitat types, set approximately every eight weeks. Our experimental design allowed us to account for differences in food source composition, availability, and accessibility throughout the island. All samples were dried and homogenized before analysis; samples were processed for carbon isotope analysis of amino acids at the Stable Isotope Facility at the University of California, Davis.

### Files and variables

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