Stable isotope fingerprinting traces essential amino acid assimilation and multichannel feeding in a vertebrate consumer

Abstract

Abstract Animals often consume resources from multiple energy channels, thereby connecting food webs and driving trophic structure. Such ‘multichannel feeding’ can dictate ecosystem function and stability, but tools to quantify this process are lacking. Stable isotope ‘fingerprints’ are unique patterns in essential amino acid (EAA) δ 13 C values that vary consistently between energy channels like primary production and detritus, and they have emerged as a tool to trace energy flow in wild systems. Because animals cannot synthesize EAAs de novo and must acquire them from dietary proteins, ecologists often assume δ 13 C fingerprints travel through food webs unaltered. Numerous studies have used this approach to quantify energy flow and multichannel feeding in animals, but δ 13 C fingerprinting has never been experimentally tested in a vertebrate consumer. We tested the efficacy of δ 13 C fingerprinting using captive deer mice Peromyscus maniculatus raised on diets containing bacterial, fungal and plant protein, as well as a combination of all three sources. We measured the transfer of δ 13 C fingerprints from diet to consumer liver, muscle and bone collagen, and we used linear discriminant analysis (LDA) and isotopic mixing models to estimate dietary proportions compared to known contributions. Lastly, we tested the use of published δ 13 C source fingerprints previously used to estimate energy flow and multichannel feeding by consumers. We found that EAA δ 13 C values exhibit significant isotopic (i.e. trophic) fractionation between consumer tissues and diets. Nevertheless, LDA revealed that δ 13 C fingerprints are consistently routed and assimilated into consumer tissues, regardless of isotopic incorporation rate. Isotopic mixing models accurately estimated the proportional diets of consumers, but all models overestimated plant‐based protein contributions, likely due to the digestive efficiencies of protein sources. Lastly, we found that δ 13 C source fingerprints from published literature can lead to erroneous diet reconstruction. We show that δ 13 C fingerprints accurately measure energy flow to vertebrate consumers across tissues with different isotopic incorporation rates, thereby enabling the estimation of multichannel feeding at various temporal scales. Our findings illustrate the power of δ 13 C fingerprinting for quantifying food web dynamics, but also reveal that careful selection of dietary source data is critical to the accuracy of this emerging technique.