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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) δ¹³C 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 δ¹³C fingerprints travel through food webs unaltered. Numerous studies have used this approach to quantify energy flow and multichannel feeding in animals, but δ¹³C fingerprinting has never been experimentally tested in a vertebrate consumer.

We tested the efficacy of δ¹³C fingerprinting using captive deer micePeromyscus maniculatusraised on diets containing bacterial, fungal and plant protein, as well as a combination of all three sources. We measured the transfer of δ¹³C 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 δ¹³C source fingerprints previously used to estimate energy flow and multichannel feeding by consumers.

We found that EAA δ¹³C values exhibit significant isotopic (i.e. trophic) fractionation between consumer tissues and diets. Nevertheless, LDA revealed that δ¹³C 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 δ¹³C source fingerprints from published literature can lead to erroneous diet reconstruction.

We show that δ¹³C 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 δ¹³C 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.

 

Herbivory is a dominant feeding strategy among animals, yet herbivores are often protein limited. The gut microbiome is hypothesized to help maintain host protein balance by provisioning essential macromolecules, but this has never been tested in wild consumers. Using amino acid carbon (δ¹³C) and nitrogen (δ¹⁵N) isotope analysis, we estimated the proportional contributions of essential amino acids (AA_ESS) synthesized by gut microbes to five co‐occurring desert rodents representing herbivorous, omnivorous and insectivorous functional groups. We found that herbivorous rodents occupying lower trophic positions (Dipodomysspp.) routed a substantial proportion (~40%–50%) of their AA_ESSfrom gut microbes, while higher trophic level omnivores (Peromyscusspp.) and insectivores (Onychomys arenicola) obtained most of their AA_ESS(~58%) from plant‐based energy channels but still received ~20% of their AA_ESSfrom gut microbes. These findings empirically demonstrate that gut microbes play a key functional role in host protein metabolism in wild animals.

 

Biodiversity collections are experiencing a renaissance fueled by the intersection of informatics, emerging technologies, and the extended use and interpretation of specimens and archived databases. In this article, we explore the potential for transformative research in ecology integrating biodiversity collections, stable isotope analysis (SIA), and environmental informatics. Like genomic DNA, SIA provides a common currency interpreted in the context of biogeochemical principles. Integration of SIA data across collections allows for evaluation of long-term ecological change at local to continental scales. Challenges including the analysis of sparse samples, a lack of information about baseline isotopic composition, and the effects of preservation remain, but none of these challenges is insurmountable. The proposed research framework interfaces with existing databases and observatories to provide benchmarks for retrospective studies and ecological forecasting. Collections and SIA add historical context to fundamental questions in freshwater ecological research, reference points for ecosystem monitoring, and a means of quantitative assessment for ecosystem restoration.

 

Food web ecology has revolutionized our understanding of ecological processes, but the drivers of food web properties like trophic position (TP) and food chain length are notoriously enigmatic. In terrestrial ecosystems, above‐ and belowground systems were historically compartmentalized into “green” and “brown” food webs, but the coupling of these systems by animal consumers is increasingly recognized, with potential consequences for trophic structure. We used stable isotope analysis (δ¹³C, δ¹⁵N) of individual amino acids to trace the flow of essential biomolecules and jointly measure multichannel feeding, food web coupling, and TP in a guild of small mammals. We then tested the hypothesis that brown energy fluxes to aboveground consumers increase terrestrial food chain length via cryptic trophic transfers during microbial decomposition. We found that the average small mammal consumer acquired nearly 70% of their essential amino acids (69.0% ± 7.6%) from brown food webs, leading to significant increases in TP across species and functional groups. Fungi were the primary conduit of brown energy to aboveground consumers, providing nearly half the amino acid budget for small mammals on average (44.3% ± 12.0%). These findings illustrate the tightly coupled nature of green and brown food webs and show that microbially mediated energy flow ultimately regulates food web structure in aboveground consumers. Consequently, we propose that the integration of green and brown energy channels is a cryptic driver of food chain length in terrestrial ecosystems.

 

Understanding physiological traits and ecological conditions that influence a species reliance on metabolic water is critical to creating accurate physiological models that can assess their ability to adapt to environmental perturbations (e.g., drought) that impact water availability. However, relatively few studies have examined variation in the sources of water animals use to maintain water balance, and even fewer have focused on the role of metabolic water. A key reason is methodological limitations. Here, we applied a new method that measures the triple oxygen isotopic composition of a single blood sample to estimate the contribution of metabolic water to the body water pool of three passerine species. This approach relies on Δ' 17 O, defined as the residual from the tight linear correlation that naturally exists between δ 17 O and δ 18 O values. Importantly, Δ'17O is relatively insensitive to key fractionation processes, such as Rayleigh distillation in the water cycle that have hindered previous isotope-based assessments of animal water balance. We evaluated the effects of changes in metabolic rate and water intake on Δ' 17 O values of captive rufous-collared sparrows ( Zonotrichia capensis ) and two invertivorous passerine species in the genus Cinclodes from the field. As predicted, colder acclimation temperatures induced increases in metabolic rate, decreases in water intake, and increases in the contribution of metabolic water to the body water pool of Z. capensis , causing a consistent change in Δ' 17 O. Measurement of Δ' 17 O also provides an estimate of the δ 18 O composition of ingested pre-formed (drinking/food) water. Estimated δ 18 O values of drinking/food water for captive Z. capensis were ~ −11‰, which is consistent with that of tap water in Santiago, Chile. In contrast, δ 18 O values of drinking/food water ingested by wild-caught Cinclodes were similar to that of seawater, which is consistent with their reliance on marine resources. Our results confirm the utility of this method for quantifying the relative contribution of metabolic versus pre-formed drinking/food water to the body water pool in birds. 

Biotic homogenization is a ubiquitous consequence of human disturbance. Through a mix of local extinctions and invasions, diverse communities of specialists are often replaced by or inundated with generalist species, resulting in uncertain consequences for ecological functions. While concern about biotic homogenization is growing, intraspecific variation and individual diet specialization (IS) have also emerged as key drivers of ecological functions. The niche variation hypothesis predicts that when a population is released from interspecific competition (ie “ecological release”), intraspecific competition will promote resource niche expansion and IS. It then follows that if biotic homogenization reduces taxonomic diversity andinterspecificcompetition,intraspecificcompetition within the remaining taxa should expand population resource niches and increase the prevalence of IS. Here, we integrate the rapidly growing fields of biotic homogenization and intraspecific variation and assess the potential for generalist species to compensate for multiple forms of biotic homogenization via adaptive foraging, resource niche expansion, and IS.

 

We designed novel field experimental infrastructure to resolve the relative importance of changes in the climate mean and variance in regulating the structure and function of dryland populations, communities, and ecosystem processes. The Mean - Variance Climate Experiment (MVE) adds three novel elements to prior designs that have manipulated interannual variance in climate in the field (Gherardi & Sala, 2013) by (i) determining interactive effects of mean and variance with a factorial design that crosses reduced mean with increased variance, (ii) studying multiple dryland biomes to compare their susceptibility to transition under interactive climate drivers, and (iii) adding stochasticity to our treatments to permit the antecedent effects that occur under natural climate variability. This new infrastructure enables direct experimental tests of the hypothesis that interactions between the mean and variance of precipitation will have larger ecological impacts than either the mean or variance in precipitation alone. A subset of plots have soil moisture and temperature sensors to evaluate treatment effectiveness by addressing, How do MVE manipulations alter the mean and variance in soil moisture and temperature? And How does micro-environmental variation among plots influence how treatments alter soil moisture profiles over three soil depths? This data package includes sensor data from the Mean - Variance Experiment in the Desert grassland ecosystem at the Sevilleta National Wildlife Refuge, Socorro, NM, which is dominated by the grass species Bouteloua eriopoda (black grama). 

We designed novel field experimental infrastructure to resolve the relative importance of changes in the climate mean and variance in regulating the structure and function of dryland populations, communities, and ecosystem processes. The Mean - Variance Experiment (MVE) adds three novel elements to prior designs that have manipulated interannual variance in climate in the field (Gherardi & Sala, 2013) by (i) determining interactive effects of mean and variance with a factorial design that crosses reduced mean with increased variance, (ii) studying multiple dryland biomes to compare their susceptibility to transition under interactive climate drivers, and (iii) adding stochasticity to our treatments to permit the antecedent effects that occur under natural climate variability. This new infrastructure enables direct experimental tests of the hypothesis that interactions between the mean and variance of precipitation will have larger ecological impacts than either the mean or variance in precipitation alone. A subset of plots have soil moisture and temperature sensors to evaluate treatment effectiveness by addressing, How do MVE manipulations alter the mean and variance in soil moisture and temperature? And How does micro-environmental variation among plots influence how treatments alter soil moisture profiles over three soil depths? This data package includes sensor data from the Mean x Variance experiment in the Plains grassland ecosystem at the Sevilleta National Wildlife Refuge, Socorro, NM, which is dominated by the grass species Bouteloua gracilis (blue grama).