Skip to main content
Dryad logo

Ecological specialization and niche overlap of subterranean rodents inferred from DNA metabarcoding diet analysis

Citation

Lopes, Carla Martins et al. (2020), Ecological specialization and niche overlap of subterranean rodents inferred from DNA metabarcoding diet analysis, Dryad, Dataset, https://doi.org/10.5061/dryad.c866t1g49

Abstract

Knowledge of how animal species use food resources available in the environment increases our understanding of ecological processes. However, obtaining this information using traditional methods is a hard task for species feeding on a large variety of food items in highly diverse environments. We amplified the DNA of plants for 306 scat and 40 soil samples, and applied an eDNA metabarcoding approach to investigate food preferences, degree of diet specialization and diet overlap of seven herbivore rodent species of the Ctenomys genus distributed in southern and midwestern Brazil. The metabarcoding approach revealed that species consume more than 60% of the plant families recovered in soil samples, indicating generalist feeding habits of ctenomyids. The Poaceae family was the most common food resource retrieved in scats of all species as well in soil samples. Niche overlap analysis indicated high overlap in the plant families and Molecular Operational Taxonomic Units consumed, mainly among the southern species. Interspecific difference in diet composition was influenced, among other factors, by the availability of resources in the environment. In addition, our results provide support for the hypothesis that the allopatric distributions of ctenomyids allow them to exploit the same range of resources when available, possibly because of the absence of interspecific competition.

Usage Notes

The GMW_consensus_sequences_fastq.zip files contain unfiltered sequencing data (i.e. consensus sequences not assigned to the original samples), from fecal, soil, and positive and negative control samples. Each .fastq file correspond to a different sequencing library.

Ngsfilter.txt files contain information to distinguish between sequences from different PCR products pooled in the same sequencing library.