The apportionment of dietary diversity in wildlife

Evaluating species’ roles in food webs is critical for advancing ecological theories on competition, coexistence, and biodiversity, but complicated by pronounced dietary variability within species and overlap across species. We combined dietary DNA metabarcoding, GPS tracking, and a machine-learning algorithm to cluster and compare dietary profiles within and among five migratory large-herbivore species from Yellowstone National Park. Interspecific niche partitioning was weak, but statistically significant (PERMANOVA: pseudo-F4,498 = 14.7, R2 = 0.11, P ≤ 0.001), such that some diet profiles from different species were as similar as those from within one species. Instead of affirming species’ identity as a primary determinant of diet composition, we found three statistically different clusters of diet profiles—one concentrated on graminoids and forbs, another on forbs and deciduous shrubs, and a third on gymnosperms—each including samples from all herbivore species. Clusters did not refl..., We obtained high-resolution diet profiles from fecal samples associated with GPS-collared individuals from five large-herbivore species that migrated over a ~100-km2 area. We processed a total of 697 samples from Yellowstone (inclusive of the 503 samples in this dataset and 194 separate samples from a different sampling scheme) with 38 total extraction blanks to monitor for laboratory cross-contamination. To identify dietary DNA sequences with the plant trnL-P6 marker using an Illumina MiSeq, we developed two reference libraries. The ‘local’ library comprised 334 unique trnL-P6 sequences from 882 vouchered specimens representing 75 plant families. We also built a global library using all trnL-P6 sequences available from ENA in EMBL-EBI using obitools v1.2.13. The global library was built using 26,101 unique trnL-P6 sequences obtained from 223,916 accessions representing at least 641 plant families.
To ensure that both per-base and per-sequence quality scores exceeded Q20, we first ..., # The apportionment of dietary diversity in wildlife

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**Local reference library files:**\
This dataset includes the specimen data (bold-specimendata-DS-YNPBP-R3.csv) and *trn*L input fasta (bold-trnL-DS-YNPBP-R3.fas) file that were used to create the local DNA reference library for Yellowstone National Park, as well as the output fasta (YNPP6_completeDB_20241108.fasta) for the complete local reference library (generated from obitools_step2_local_reference_library_2025.Rmd).

Both the input and and output files for the local reference library are in FASTA format where a sequence begins with a single-line description (specimen ID and plant taxonomy), followed by lines of sequence data for that taxon.

All columns in bold-specimendata-DS-YNPBP-R3.csv are outlined below (cells where information wasn't recorded for a specimen are labeled with 'n/a'):

* Sample ID = internal identifier for the sample being sequenced
* Project Code = unique identifier for the data project
* Process ID = ...,