Comparison of mechanical sorting and DNA metabarcoding for diet analysis with fresh and degraded wolf scats

Abstract

Abstract DNA metabarcoding has become a powerful technique for identifying the species present in a bulk environmental sample. The application of DNA metabarcoding to wildlife diet analysis is a particularly promising tool for exploring trophic interactions. The extent to which molecular approaches agree with traditional approaches, and how this varies with the quality of field‐collected scats, is unknown. Here, we compare diets from wolf scats profiled using both mechanical sorting and metabarcoding of amplified vertebrate DNA sequences. Our objectives were to (1) compare findings from mechanical sorting and metabarcoding as a method of diet profiling and (2) use results to better understand diets of wolves on Prince of Wales Island, a population of conservation concern. We predicted metabarcoding would reveal both higher diversity of prey and identify rare species that are overlooked with mechanical sorting. We found that there was substantial overlap in the diets revealed using both methods, indicating that deer, beaver, and black bear were the primary prey species, but metabarcoding revealed a more diverse diet with greater occurrence of rare species. However, there was a large discrepancy in the occurrence of beaver in scats (52% and 25% from mechanical sorting and metabarcoding, respectively) explained by the high rate of false positives with mechanical sorting methods. While the number of wolf sequence reads for fresh scats was nearly eight times higher than in degraded scats, neither the number of prey sequence reads nor the quantity of DNA to be sequenced varied between fresh and degraded scats suggesting that metabarcoding is sensitive enough to determine prey assemblages in degraded scats. Even using scats from extremely wet conditions hostile to DNA preservation, we found that metabarcoding was more effective than mechanical sorting in describing diet.

Keywords

• Alaska
• Canis lupus
• diet analysis
• eDNA
• metabarcoding
• noninvasive sampling