Quantitative Fatty Acid Signature Analysis Research Articles

Variation in the diet of beluga whales in response to changes in prey availability: insights on changes in the Beaufort Sea ecosystem

The eastern Beaufort Sea (EBS) beluga whaleDelphinapterus leucaspopulation has experienced a 20 yr decline in inferred growth rates of individuals, which is hypothesized to have resulted from changes in prey availability. We used fatty acid signatures and stable isotope ratios to reconstruct the proportional contributions of 14 prey species to the diets of 178 beluga whales from 2011 to 2014. Prey estimates using quantitative fatty acid signature analysis suggest that EBS beluga whales primarily consume Arctic codBoreogadus saida, a species highly sensitive to climate change. Prey estimates varied with year and sex and size class of the whales, with large males consuming the highest proportions of Arctic cod, and females consuming the highest proportions of capelinMallotus villosus. Estimated proportional contributions of Arctic cod to beluga diet decreased from 2011 to 2014, coinciding with an increase in capelin. Belugas consumed the highest proportions of capelin and the lowest proportions of cod in 2014, the same year in which body condition indices were lowest in the whales. We hypothesize that changing conditions in the Beaufort Sea ecosystem may result in a decreased consumption of Arctic cod by belugas and increased consumption of capelin, which may result in a decline in condition. This may predominately affect females and juveniles since they consume the highest proportions of capelin; however, long-term monitoring is needed for confirmation. Understanding inter-annual variation in prey, and the longer-term nutritional implications of shifting from an Arctic cod- to a capelin-dominated diet should be a priority for monitoring EBS predators.

Shifting systems: prerequisites for the application of quantitative fatty acid signature analysis in soil food webs

Quantitative fatty acid signature analysis (QFASA) is widely used to investigate trophic interactions in marine ecosystems, as nutritionally important ω3 long-chain polyunsaturated fatty acids at the food web base allow tracing of their trophic transfer in the food chain. By contrast, the basal resources in soil food webs comprise a wider array of trophic markers, including branched-chain, cyclopropane as well as several mono- and polyunsaturated fatty acids. These diverse markers allow distinguishing between the three dominant soil carbon and energy channels, the root, bacterial and fungal pathway. QFASA has not been applied yet to soil ecosystems owing to the lack of a priori data to fit the model. The present work investigates the transfer of absolute and relative trophic marker fatty acids into Collembola as dominant representatives of the soil mesofauna. Three different species were fed on a variety of single diets characteristic for the green and brown food chain. Calibration coefficients were calculated and diet estimation trials for mixed diet set-ups were performed, using a library comprising 50 different resources. However, estimation of Collembola diet was only partially successful, identifying the main components, but not the correct relative proportions. Adjustments by fat content or diet group exclusion did not improve the results. Nonetheless, this work provides, to our knowledge, a first comprehensive dataset to translate the application of QFASA from marine to soil ecosystems. This article is part of the theme issue 'The next horizons for lipids as 'trophic biomarkers': evidence and significance of consumer modification of dietary fatty acids'.

Fatty acid-based diet estimates suggest ringed seal remain the main prey of southern Beaufort Sea polar bears despite recent use of onshore food resources.

Polar bears (Ursus maritimus) from the southern Beaufort Sea (SB) subpopulation have traditionally fed predominantly upon ice‐seals; however, as the proportion of the subpopulation using onshore habitat has recently increased, foraging on land‐based resources, including remains of subsistence‐harvested bowhead whales (Balaena mysticetus) and colonial nesting seabirds has been observed. Adipose tissue samples were collected from this subpopulation during the springs of 2013–2016 and analyzed for fatty acid signatures. Diet estimates were generated for the proportional consumption of ringed seal (Pusa hispida), bearded seal (Erignathus barbatus), and beluga whale (Delphinapterus leucas), relative to onshore foods, including bowhead whale remains and seabird, as represented by black guillemot (Cepphus grylle mandtii) nestlings and eggs. Quantitative fatty acid signature analysis (QFASA) estimated that the ice‐obligate prey, ringed seal, remained the predominant prey species of SB polar bears (46.4 ± 1.8%), with much lower consumption of bearded seal (19.6 ± 2.0%), seabird (17.0 ± 1.2%), bowhead whale (15.0 ± 1.4%), and hardly any beluga whale (2.0 ± 0.5%). Adult and subadult females appeared to depend more on the traditional ringed seal prey than adult and subadult males. Diet estimates of SB polar bears showed significant interannual variability for all prey (F 12, 456 = 3.17, p < .001). Longer‐term estimates suggested that both types of onshore prey, bowhead whale remains and seabird, have represented a moderate proportion of the food resources used by SB polar bears since at least the start of the 21st Century.

Blubber fatty acids reveal variation in the diet of male Australian fur seals

Top-order predators play an important role in the structure and function of marine ecosystems. Optimal foraging theory predicts that predators will utilise foraging strategies that maximise their net energetic intake, and consequently, individuals within a population may utilise alternate strategies to target different prey resources. The present study investigated variation within the diet of 41 male Australian fur seals (Arctocephalus pusillus doriferus) using quantitative fatty-acid signature analysis (QFASA) of blubber. The study was conducted during the pre-breeding seasons of 2012 and 2013 and the non-breeding seasons of 2013 and 2014 at a colony on Kanowna Island (39°10′S, 146°18′E) in northern Bass Strait, southeastern Australia. QFASA models revealed that while males consumed prey commonly reported within the diet of Australian fur seals, elasmobranchs were more important than previously reported. Prey composition also varied between males which may reflect individuals using different strategies to target different resources, which ultimately broadens the trophic niche of a species and reduces intra-specific competition. Furthermore, substantial temporal variation in male diet was apparent presumably reflecting variation in the distribution, availability, and abundance of prey resources within Bass Strait at the time of sampling. Given that the energetic content of prey is expected to differ between species, temporal variation in dietary composition presumably has important implications for the growth and reproductive success of males.

Diversity and specificity of lipid patterns in basal soil food web resources.

Soil food webs are important drivers for key ecological functions in terrestrial systems such as carbon and nutrient cycling. However, soil food web models generally lack quantitative data, mainly due to the shortage in high-throughput methods to describe energy flows. In marine environments, multivariate optimization models (Quantitative Fatty Acid Signature Analysis) and Bayesian approaches (source-tracking algorithm) were established to predict the proportion of predator diets using lipids as tracers. A premise for the application of such models to soil systems is to acquire the fatty acid pattern of a broad range of resources and to reveal potential overlap in their signatures. We present a comprehensive comparison of lipid pattern across widespread taxa of plants (leaves and roots, n = 48), algae (n = 59), fungi (n = 60), and bacteria (n = 62) as basal food web resources. Lipid profiles from microorganisms and algae were assessed from laboratory cultures, whereas plant tissue was derived from an arable field. A lipid library was constructed and multivariate data analyses (hierarchical clustering, nMDS) was used to assess the extent of separation in lipid pattern by species or resource type. The performance of the lipid library was tested by leave-one-prey-out (LOPO) analysis, giving the distinctiveness of the resource (prey) groups. Fungi and plant leaves were correctly assigned based on their lipid pattern with more than 98%, while plant roots and bacteria achieved 88 and 85%, respectively. However, algae were only correctly classified by 60%, pointing to a bias in the herbivore food chain. Fatty acids most important for separation of algae and plant leaves were of the omega 3 type, i.e. 16:3ω3 and 18:3ω3. In plant roots 18:1ω9 was most important, whereas bacteria were distinguished predominantly by methyl-branched fatty acids. Overall, the lipid pattern of major soil food web resources are sufficiently differentiated to allow for qualitative (biomarker) analyses as well as quantitative modelling, yet with precaution in the case of algae.

A comparison of diet estimates of captive beluga whales using fatty acid mixing models with their true diets

Beluga whales (Delphinapterus leucas) are sentinel species for Arctic environmental change; however, whether belugas are resilient to anticipated changes in prey dynamics remains uncertain, partly due to a lack of dietary information. Mixing models are promising tools to evaluate the diets of marine mammals, using dietary tracers such as fatty acid signatures. Additionally, captive feeding trials are useful to test the effectiveness of these tools for application to wild populations. In our study, we compared the ability of two models, quantitative fatty acid signature analysis in R (QFASAR) and Fatty Acid Source Tracking Algorithm in R (FASTAR) to reconstruct the diets of captive beluga whales that had been fed a long-term diet consisting mostly of Pacific herring (Clupea harengus pallasi), and in smaller proportions, capelin (Mallotus villosus) and squid (Doryteuthis opalescens). To account for fatty acid metabolism, we compared a suite of calibration coefficients derived from captive feeding trials of American mink (Mustela vison), harp seal (Pagophilus groenlandicus), harbour seal (Phoca vitulina richardsi), and grey seal (Halichoerus grypus) fed monotypic diets. For both methods, diets estimated using calibration coefficients derived from feeding trials of mink fed herring and/or seal oil were able to correctly identify herring as the dominant prey source of belugas. In addition, there was higher precision among diet estimates using these calibration coefficients in comparison to those generated using calibration coefficients derived from feeding trials of pinnipeds or mink fed poultry. QFASAR more accurately approximated the diet proportions of the whales than FASTAR, possibly because of the greater robustness to errors in the calibration coefficients. Based on QFASAR, diet estimates best reflect the whales' true dietary proportions consumed approximately two weeks to one month prior to sampling, similar to timeframes seen in previous studies of harbour seals. We recommend caution when using these models with prey that have high within-species variability in fatty acid signatures or small sample sizes, as well as prey with similar fatty acid signatures. The application of mixing models is promising to identify the prey of wild beluga whales and other marine mammals.

Fatty acids differentiate consumers despite variation within prey fatty acid profiles

Abstract Techniques that biochemically trace foraging habits of predators rely on the assumption that intra‐specific variation in prey species is smaller than variation among them. At the same time, these techniques often show that diets can induce drastic changes in the biochemical profiles of prey species, especially across different ecosystems. We tested if intra‐specific variation in fatty acid profiles of prey species added enough noise to confound quantitative fatty acid signature analysis (QFASA) using a controlled feeding experiment. Steelhead trout (Oncorhynchus mykiss) were fed either alewife (Alosa pseudoharengus) or round goby (Neogobius melanostomus) from either Lake Ontario or Cayuga Lake for a period of 8 weeks. Fatty acid profiles were significantly different between prey species and between lake of origin within each species. Differences in fatty acid profiles of steelhead trout strongly reflected prey species differences, whereas differences related to prey origin (lakes) were noted at a much lesser extent. QFASA performed remarkably well given the differences observed between the lakes prey originated from. Our results indicate that QFASA models for steelhead trout are probably not specific to one lake, and could provide estimates for other freshwater systems where alewife and round goby serve as the primary forage.

Energy-Rich Mesopelagic Fishes Revealed as a Critical Prey Resource for a Deep-Diving Predator Using Quantitative Fatty Acid Signature Analysis

Understanding the diet of deep-diving predators can provide essential insight to the trophic structure of the mesopelagic ecosystem. Comprehensive population-level diet estimates are exceptionally difficult to obtain for elusive marine predators due to the logistical challenges involved in observing their feeding behavior and collecting samples for traditional stomach content or fecal analyses. We used quantitative fatty acid signature analysis (QFASA) to estimate the diet composition of a wide-ranging mesopelagic predator, the northern elephant seal (Mirounga angustirostris), across five years. To implement QFASA, we first compiled a library of prey fatty acid profiles from the mesopelagic eastern North Pacific. Given the scarcity of a priori diet data for northern elephant seals, our prey library was necessarily large to encompass the range of potential prey in their foraging habitat. However, statistical constraints limit the number of prey species that can be included in the prey library to the number of dietary fatty acids in the analysis. Exceeding that limit could produce non-unique diet estimates (i.e. multiple diet estimates fit the data equally well). Consequently, we developed a novel ad-hoc method to identify which prey were unlikely to contribute to diet and could, therefore, be excluded from the final QFASA model. The model results suggest that seals predominantly consumed small mesopelagic fishes, including myctophids (lanternfishes) and bathylagids (deep sea smelts), while non-migrating mesopelagic squids comprised a third of their diet, substantially less than suggested by previous studies. Our results revealed that mesopelagic fishes, particularly energy-rich myctophids, were a critical prey resource, refuting the long-held view that elephant seals are squid specialists.

Fisheries Exploitation by Albatross Quantified With Lipid Analysis

Mortality from incidental bycatch in longline fishery operations is a global threat to seabird populations, and especially so for the albatross family (Diomedeidae) in which fifteen out of twenty-two species are threatened by extinction. Despite the risks, fisheries remain attractive to many species of seabird by providing access to high-energy foods in the form of discarded fish and offal, target fish, and baited hooks. Current policy regarding fisheries management is increasingly aimed at discard reform, exemplified by a discard ban initiated in the European Union Common Fisheries Policy in 2014. While there is global agreement in the importance of minimizing the waste inherent in bycatch and discards, there is also growing concern that there is also a need to understand the extent to which marine animals rely on fisheries-associated resources, especially at the colony and individual levels. We used a novel adaptation of quantitative fatty acid signature analysis (QFASA), to quantify fisheries-associated prey in the diet of two threatened North Pacific albatross species. Diet was estimated with QFASA using multiple lipid classes from stomach oil collected from breeding Laysan and black-footed albatrosses across multiple breeding seasons. Prey-specific error was estimated by comparing QFASA estimated diets from known “simulated” diets, which informed the level of precaution appropriate when interpreting model results. Fisheries-associated diet occurred in both albatross species across both the incubation and chick-brood stages; however, neither species relied on fisheries food as the dominant food source (consisting of <10 % of the total pooled proportional diet in each species). While total diet proportion was low, the incidence of fisheries-associated resources in albatross diets was highest in the 2009-2010 breeding season when there was a strong central Pacific El Nino. Additionally, the diets of a few individuals consisted almost entirely of fisheries-associated food, indicating that some birds might specialize on this foraging tactic. QFASA proved a tractable method for estimating the importance of fisheries-associated resources in albatross diet, and, as a tool, has the potential to enable long-term monitoring of diet and fisheries reliance of breeding colonies in the northwestern Hawaiian Islands.

High contributions of sea ice derived carbon in polar bear (Ursus maritimus) tissue.

Polar bears (Ursus maritimus) rely upon Arctic sea ice as a physical habitat. Consequently, conservation assessments of polar bears identify the ongoing reduction in sea ice to represent a significant threat to their survival. However, the additional role of sea ice as a potential, indirect, source of energy to bears has been overlooked. Here we used the highly branched isoprenoid lipid biomarker-based index (H-Print) approach in combination with quantitative fatty acid signature analysis to show that sympagic (sea ice-associated), rather than pelagic, carbon contributions dominated the marine component of polar bear diet (72–100%; 99% CI, n = 55), irrespective of differences in diet composition. The lowest mean estimates of sympagic carbon were found in Baffin Bay bears, which were also exposed to the most rapidly increasing open water season. Therefore, our data illustrate that for future Arctic ecosystems that are likely to be characterised by reduced sea ice cover, polar bears will not only be impacted by a change in their physical habitat, but also potentially in the supply of energy to the ecosystems upon which they depend. This data represents the first quantifiable baseline that is critical for the assessment of likely ongoing changes in energy supply to Arctic predators as we move into an increasingly uncertain future for polar ecosystems.

Detect and exploit hidden structure in fatty acid signature data

AbstractEstimates of predator diet composition are essential to our understanding of their ecology. Although several methods of estimating diet are practiced, methods based on biomarkers have become increasingly common. Quantitative fatty acid signature analysis (QFASA) is a popular method that continues to be refined and extended. Quantitative fatty acid signature analysis is based on differences in the signatures of prey types, often species, which are recognized and designated by investigators. Similarly, predator signatures may be structured by known factors such as sex or age class, and the season or region of sample collection. The recognized structure in signature data inherently influences QFASA results in important and typically beneficial ways. However, predator and prey signatures may contain additional, hidden structure that investigators either choose not to incorporate into an analysis or of which they are unaware, being caused by unknown ecological mechanisms. Hidden structure also influences QFASA results, most often negatively. We developed a new method to explore signature data for hidden structure, called divisive magnetic clustering (DIMAC). Our DIMAC approach is based on the same distance measure used in diet estimation, closely linking methods of data exploration and parameter estimation, and it does not require data transformation or distributional assumptions, as do many multivariate ordination methods in common use. We investigated the potential benefits of the DIMAC method to detect and subsequently exploit hidden structure in signature data using two prey signature libraries with quite different characteristics. We found that the existence of hidden structure in prey signatures can increase the confusion between prey types and thereby reduce the accuracy and precision of QFASA diet estimates. Conversely, the detection and exploitation of hidden structure represent a potential opportunity to improve predator diet estimates and may lead to new insights into the ecology of either predator or prey. The DIMAC algorithm is implemented in the R diet estimation package qfasar.

Simultaneous estimation of diet composition and calibration coefficients with fatty acid signature data.

Knowledge of animal diets provides essential insights into their life history and ecology, although diet estimation is challenging and remains an active area of research. Quantitative fatty acid signature analysis (QFASA) has become a popular method of estimating diet composition, especially for marine species. A primary assumption of QFASA is that constants called calibration coefficients, which account for the differential metabolism of individual fatty acids, are known. In practice, however, calibration coefficients are not known, but rather have been estimated in feeding trials with captive animals of a limited number of model species. The impossibility of verifying the accuracy of feeding trial derived calibration coefficients to estimate the diets of wild animals is a foundational problem with QFASA that has generated considerable criticism. We present a new model that allows simultaneous estimation of diet composition and calibration coefficients based only on fatty acid signature samples from wild predators and potential prey. Our model performed almost flawlessly in four tests with constructed examples, estimating both diet proportions and calibration coefficients with essentially no error. We also applied the model to data from Chukchi Sea polar bears, obtaining diet estimates that were more diverse than estimates conditioned on feeding trial calibration coefficients. Our model avoids bias in diet estimates caused by conditioning on inaccurate calibration coefficients, invalidates the primary criticism of QFASA, eliminates the need to conduct feeding trials solely for diet estimation, and consequently expands the utility of fatty acid data to investigate aspects of ecology linked to animal diets.

Qfasar: quantitative fatty acid signature analysis with R

Summary Knowledge of predator diets provides essential insights into their ecology, yet diet estimation is challenging and remains an active area of research. Quantitative fatty acid signature analysis (QFASA) is a popular method of estimating diet composition that continues to be investigated and extended. However, software to implement QFASA has only recently become publicly available. I summarize a new R package, qfasar, for diet estimation using QFASA methods. The package also provides functionality to evaluate and potentially improve the performance of a library of prey signature data, compute goodness‐of‐fit diagnostics, and support simulation‐based research. Several procedures in the package have not previously been published. qfasar makes traditional and recently published QFASA diet estimation methods accessible to ecologists for the first time. Use of the package is illustrated with signature data from Chukchi Sea polar bears and potential prey species.

Evaluating quantitative fatty acid signature analysis (QFASA) in fish using controlled feeding experiments

Accurate diet estimation has long been a challenging issue for researchers investigating predators because of constraints associated with stomach content analyses. Fatty acid signature analysis offers an alternative avenue to study long-term diet trends in consumers. Despite the wealth of experiments involving fatty acids of fish and their diets, few have evaluated quantitative fatty acid signature analysis (QFASA) with fish consumers. To this end, we fed juvenile lake trout (Salvelinus namaycush), round goby (Neogobius melanostomus), and yellow perch (Perca flavescens) various invertebrate species and back-classified each predator to its respective prey using only fatty acids. Estimates were highly accurate when metabolism of diets was natively accounted for by using fatty acid profiles of predators fed known diets as the “prey library”. While highly accurate results were obtained, accounting for each predator–prey relationship limits the use of QFASA to predators that consume a limited number of species. We call for specific knowledge as to how fatty acid profiles reflect each predator–prey interaction before attempting to use fatty acids to quantify a consumer’s diet. Only after incorporating such data will QFASA provide an accurate view of individual’s diets when stomach content data are not available or are invalid.

An approach to measure distance between compositional diet estimates containing essential zeros

ABSTRACTFor many applications involving compositional data, it is necessary to establish a valid measure of distance, yet when essential zeros are present traditional distance measures are problematic. In quantitative fatty acid signature analysis (QFASA), compositional diet estimates are produced that often contain many zeros. In order to test for a difference in diet between two populations of predators using the QFASA diet estimates, a legitimate measure of distance for use in the test statistic is necessary. Since ecologists using QFASA must first select the potential species of prey in the predator's diet, the chosen measure of distance should be such that the distance between samples does not decrease as the number of species considered increases, a property known in general as subcompositional coherence. In this paper we compare three measures of distance for compositional data capable of handling zeros, but not satisfying some of the well-accepted principles of compositional data analysis. For compositional diet estimates, the most relevant of these is the property of subcompositionally coherence and we show that this property may be approximately satisfied. Based on the results of a simulation study and an application to real-life QFASA diet estimates of grey seals, we recommend the chi-square measure of distance.

Fatty‐acid profiles of juvenile lake trout reflect experimental diets consisting of natural prey

Summary It is relatively well‐known that fatty‐acid profiles of consumers reflect their diets. However, with fish, controlled studies that trace fatty‐acid profiles of natural prey into consumers are lacking. We asked whether lake trout (Salmonidae: Salvelinus namaycush) fatty‐acid profiles reflect diets at 4, 8 or 14 weeks after feeding began. We also evaluated if calibration coefficients were similar for each diet, a key assumption of quantitative fatty‐acid signature analysis (QFASA). In this study, juvenile lake trout were fed commercially available frozen diets of chironomids (Chironomidae: Chironomus spp.), copepods (Cyclopoida spp.), or Mysis (Mysidae: Mysis relicta) over a 14‐week period. Accurate classification of lake trout into a priori diet groups was attained after 8 weeks of feeding. Calibration coefficients were significantly different among diet groups, especially for lake trout that were fed chironomids, suggesting that diet‐specific modifications to fatty acids occurred. Chironomid‐fed lake trout grew significantly larger than others despite consuming prey that lacked long‐chain essential fatty acids. Furthermore, chironomid‐fed lake trout provide evidence for the conversion of 18:3n‐3 into longer chain n‐3 fatty acids. Our results call for additional studies to better understand how fatty acids reflect dietary origins prior to employing QFASA on wild freshwater fishes. QFASA could provide accurate diet estimates for freshwater fishes with low‐diversity diet compositions, if calibration coefficients for each predator–prey relationship are incorporated.

Should fatty acid signature proportions sum to 1 for diet estimation?

AbstractKnowledge of predator diets, including how diets might change through time or differ among predators, provides essential insights into their ecology. Diet estimation therefore remains an active area of research within quantitative ecology. Quantitative fatty acid signature analysis (QFASA) is an increasingly common method of diet estimation. QFASA is based on a data library of prey signatures, which are vectors of proportions summarizing the fatty acid composition of lipids, and diet is estimated as the mixture of prey signatures that most closely approximates a predator's signature. Diets are typically estimated using proportions from a subset of all fatty acids that are known to be solely or largely influenced by diet. Given the subset of fatty acids selected, the current practice is to scale their proportions to sum to 1.0. However, scaling signature proportions has the potential to distort the structural relationships within a prey library and between predators and prey. To investigate that possibility, we compared the practice of scaling proportions with two alternatives and found that the traditional scaling can meaningfully bias diet estimators under some conditions. Two aspects of the prey types that contributed to a predator's diet influenced the magnitude of the bias: the degree to which the sums of unscaled proportions differed among prey types and the identifiability of prey types within the prey library. We caution investigators against the routine scaling of signature proportions in QFASA.

Simulating realistic predator signatures in quantitative fatty acid signature analysis

Diet estimation is an important field within quantitative ecology, providing critical insights into many aspects of ecology and community dynamics. Quantitative fatty acid signature analysis (QFASA) is a prominent method of diet estimation, particularly for marine mammal and bird species. Investigators using QFASA commonly use computer simulation to evaluate statistical characteristics of diet estimators for the populations they study. Similar computer simulations have been used to explore and compare the performance of different variations of the original QFASA diet estimator. In both cases, computer simulations involve bootstrap sampling prey signature data to construct pseudo-predator signatures with known properties. However, bootstrap sample sizes have been selected arbitrarily and pseudo-predator signatures therefore may not have realistic properties. I develop an algorithm to objectively establish bootstrap sample sizes that generates pseudo-predator signatures with realistic properties, thereby enhancing the utility of computer simulation for assessing QFASA estimator performance. The algorithm also appears to be computationally efficient, resulting in bootstrap sample sizes that are smaller than those commonly used. I illustrate the algorithm with an example using data from Chukchi Sea polar bears (Ursus maritimus) and their marine mammal prey. The concepts underlying the approach may have value in other areas of quantitative ecology in which bootstrap samples are post-processed prior to their use.

Assessing the robustness of quantitative fatty acid signature analysis to assumption violations

Summary Knowledge of animal diets can provide important insights into life history and ecology, relationships among species in a community and potential response to ecosystem change or perturbation. Quantitative fatty acid signature analysis (QFASA) is a method of estimating diets from data on the composition, or signature, of fatty acids stored in adipose tissue. Given data on signatures of potential prey, a predator diet is estimated by minimizing the distance between its signature and a mixture of prey signatures. Calibration coefficients, constants derived from feeding trials, are used to account for differential metabolism of individual fatty acids. QFASA has been widely applied since its introduction and several variants of the original estimator have appeared in the literature. However, work to compare the statistical properties of QFASA estimators has been limited. One important characteristic of an estimator is its robustness to violations of model assumptions. The primary assumptions of QFASA are that prey signature data contain representatives of all prey types consumed and the calibration coefficients are known without error. We investigated the robustness of two QFASA estimators to a range of violations of these assumptions using computer simulation and recorded the resulting bias in diet estimates. We found that the Aitchison distance measure was most robust to errors in the calibration coefficients. Conversely, the Kullback–Leibler distance measure was most robust to the consumption of prey without representation in the prey signature data. In most QFASA applications, investigators will generally have some knowledge of the prey available to predators and be able to assess the completeness of prey signature data and sample additional prey as necessary. Conversely, because calibration coefficients are derived from feeding trials with captive animals and their values may be sensitive to consumer physiology and nutritional status, their applicability to free‐ranging animals is difficult to establish. We therefore recommend that investigators first make any improvements to the prey signature data that seem warranted and then base estimation on the Aitchison distance measure, as it appears to minimize risk from violations of the assumption that is most difficult to verify.

Characterization of polar bear (Ursus maritimus) diets in the Canadian High Arctic

Climate-driven changes in the quality and availability of sea ice habitat (e.g., spatial extent, thickness, and duration of open water) are expected to affect Arctic species primarily through altered foraging opportunities. However, trophic interactions in Arctic marine systems are often poorly understood, especially in remote high-latitude regions. We used quantitative fatty acid signature analysis to examine the diets of 198 polar bears (Ursus maritimus) harvested between 2010 and 2012 in the subpopulations of Baffin Bay, Gulf of Boothia, and Lancaster Sound. The objective was to characterize diet composition and identify ecological factors supporting the high density of polar bears in these regions. Polar bears across the study area fed primarily on ringed seals (Pusa hispida, 41-56 %), although bearded seals (Erignathus barbatus, 11-24 %) and beluga whales (Delphinapterus leucas, 15-19 %) were also important prey. Harp seals (Pagophilus groenlandi- cus) were a major food source in Baffin Bay. Dietary diversity was greatest in Baffin Bay, perhaps because marine mammals were attracted to the nutrient-rich waters in and downstream from the North Water Polynya. For- aging patterns differed across age and sex classes of polar bear. In Baffin Bay, adult females had high levels of bearded seal in their diet, whereas adult males and sub- adults consumed high levels of harp seal. Seasonal varia- tion in polar bear foraging was related to known migration patterns of marine mammals. Our results add to existing evidence that polar bears in these three separate subpopu- lations have a shared conservation status.