Experimentally Derived δ13C and δ15N Discrimination Factors for Gray Wolves and the Impact of Prior Information in Bayesian Mixing Models

Stable isotope analysis of diet has become a common tool in conservation research. However, the multiple sources of uncertainty inherent in this analysis framework involve consequences that have not been thoroughly addressed. Uncertainty arises from the choice of trophic discrimination factors, and for Bayesian stable isotope mixing models (SIMMs), the specification of prior information; the combined effect of these aspects has not been explicitly tested. We used a captive feeding study of gray wolves (Canis lupus) to determine the first experimentally-derived trophic discrimination factors of C and N for this large carnivore of broad conservation interest. Using the estimated diet in our controlled system and data from a published study on wild wolves and their prey in Montana, USA, we then investigated the simultaneous effect of discrimination factors and prior information on diet reconstruction with Bayesian SIMMs. Discrimination factors for gray wolves and their prey were 1.97‰ for δ¹³C and 3.04‰ for δ¹⁵N. Specifying wolf discrimination factors, as opposed to the commonly used red fox (Vulpes vulpes) factors, made little practical difference to estimates of wolf diet, but prior information had a strong effect on bias, precision, and accuracy of posterior estimates. Without specifying prior information in our Bayesian SIMM, it was not possible to produce SIMM posteriors statistically similar to the estimated diet in our controlled study or the diet of wild wolves. Our study demonstrates the critical effect of prior information on estimates of animal diets using Bayesian SIMMs, and suggests species-specific trophic discrimination factors are of secondary importance. When using stable isotope analysis to inform conservation decisions researchers should understand the limits of their data. It may be difficult to obtain useful information from SIMMs if informative priors are omitted and species-specific discrimination factors are unavailable.     

Multiple species‐specific molecular markers using nanofluidic array as a tool to detect prey DNA from carnivore scats

Large carnivore feeding ecology plays a crucial role for management and conservation for predators and their prey. One of the keys to this kind of research is to identify the species composition in the predator diet, for example, prey determination from scat content. DNA‐based methods applied to detect prey in predators’ scats are viable alternatives to traditional macroscopic approaches, showing an increased reliability and higher prey detection rate. Here, we developed a molecular method for prey species identification in wolf (Canis lupus) scats using multiple species‐specific marker loci on the cytochrome b gene for 18 target species. The final panel consisted of 80 assays, with a minimum of four markers per target species, and that amplified specifically when using a high‐throughput Nanofluidic array technology (Fluidigm Inc.). As a practical example, we applied the method to identify target prey species DNA in 80 wolf scats collected in Sweden. Depending on the number of amplifying markers required to obtain a positive species call in a scat, the success in determining at least one prey species from the scats ranged from 44% to 92%. Although we highlight the need to evaluate the optimal number of markers for sensitive target species detection, the developed method is a fast and cost‐efficient tool for prey identification in wolf scats and it also has the potential to be further developed and applied to other areas and large carnivores as well.     

Can diet composition estimates using stable isotope analysis of feathers predict growth and condition in nestling mountain bluebirds (Sialia currucoides)?

Insectivorous birds breeding in seasonal environments provision their dependent young during periods when prey diversity and abundance vary. Consequently, the composition and nutritional value of diets parents feed to their offspring may differ within and among broods, potentially affecting the condition of nestlings. In a population of mountain bluebirds (Sialia currucoides), we used two methods to estimate diet composition for individual nestlings: direct observation of provisioning using video recordings at 5 and 9 days post‐hatch, and stable isotopes of the δ¹³C and δ¹⁵N in nestling feathers and prey followed by analysis with mixing models. We determined the macronutrient content (% fat and lean mass) and estimated the metabolized energy from each type of prey. We evaluated whether different methods of estimating diet composition would produce similar results, and whether the types of prey nestlings ate at one or both ages affected their morphology, growth rates, or blood ketone concentration. We found that bluebirds fed their young 5 main types of prey: beetles, cicadas, grasshoppers, insect larvae, and spiders. Both observational and mixing model estimates of diet composition indicated that larvae are traded off with grasshoppers and that fewer larvae are provided to nestlings as the season progresses. In evaluating how diet influences individual growth and condition, estimates from direct observations had greater explanatory power than those from mixing models, indicating that diets rich in the most energy‐dense prey (greatest fat content; cicadas and larvae) were associated with larger size and higher body condition, and faster rate of mass gain and growth of tarsus. Lower value prey had more limited, specific effects on nestlings, but may still be important dietary components. While isotopic methods produced estimates of diet composition that were generally informative, when applied to explain the growth and condition of nestlings they proved less useful.     

Moving beyond noninformative priors: why and how to choose weakly informative priors in Bayesian analyses

Throughout the last two decades, Bayesian statistical methods have proliferated throughout ecology and evolution. Numerous previous references established both philosophical and computational guidelines for implementing Bayesian methods. However, protocols for incorporating prior information, the defining characteristic of Bayesian philosophy, are nearly nonexistent in the ecological literature. Here, I hope to encourage the use of weakly informative priors in ecology and evolution by providing a ‘consumer's guide’ to weakly informative priors. The first section outlines three reasons why ecologists should abandon noninformative priors: 1) common flat priors are not always noninformative, 2) noninformative priors provide the same result as simpler frequentist methods, and 3) noninformative priors suffer from the same high type I and type M error rates as frequentist methods. The second section provides a guide for implementing informative priors, wherein I detail convenient ‘reference’ prior distributions for common statistical models (i.e. regression, ANOVA, hierarchical models). I then use simulations to visually demonstrate how informative priors influence posterior parameter estimates. With the guidelines provided here, I hope to encourage the use of weakly informative priors for Bayesian analyses in ecology. Ecologists can and should debate the appropriate form of prior information, but should consider weakly informative priors as the new ‘default’ prior for any Bayesian model.     

A comparison and critique of different scat‐analysis methods for determining carnivore diet

• 1 For terrestrial carnivores, scat analysis is the technique most often used to determine diets. Various methods of interpreting scat‐analysis data exist; however, little is known about how the choice of method affects the results.
• 2 We reviewed 50 scat‐analysis papers to assess the range of methods currently used. Furthermore, we used a large data set from cape fox Vulpes chama and black‐backed jackal Canis mesomelas scats to compare 11 scat‐analysis methods. Techniques tested included five biomass calculation methods, four frequency of occurrence methods, one method that estimated volume in scats, and another that estimated mass of food items in scats.
• 3 Frequency of occurrence methods were used in 94% of reviewed papers, and in 50% of papers they were the sole methods used. However, we conclude that frequency of occurrence has the least ecological significance and results can be misleading. Although biomass calculations probably provide the best approximation to true diets, only 23% of reviewed papers used suitable biomass calculation methods when models were available for the study species.
• 4 Analysis of fox and jackal scats showed that there were significant differences among methods when calculating percent diet composition and niche breadth. Additionally, dietary overlap between species differed considerably among the methods (range of R₀ = 0.29–0.79). We conclude that the choice of method can have a significant impact on the results of dietary analysis, and can lead to very different conclusions about a species' ecology.
• 5 The best approximation of the true diet can be obtained by using a biomass calculation model that was developed for the same species, or for a closely related species with a similar food spectrum. When no such model is available, either the volume or mass of diet components in the scats should be used. To document rare food items, frequency of occurrence data could also be given.

     

Methods of estimating marine mammal diets: A review of validation experiments and sources of bias and uncertainty

Diet estimation in marine mammals relies on indirect methods including recovery of prey hard parts from stomachs and feces, quantitative fatty acid signature analysis (QFASA), stable isotope mixing models, and identification of prey DNA in stomach contents and feces. Experimental evidence (9 species/13 studies) shows that digestion strongly influences the proportion and size of otoliths that can be recovered in feces. Number correction factors (NCF) and digestion coefficients have been experimentally determined to reduce the biases in fecal analysis. Correction factors and coefficients have not been determined for diet estimated from stomach contents. QFASA estimates which prey species and amounts must have been eaten to account for the fatty acid composition of the predator. Experimental studies on mammals and seabirds (9 species/10 studies) indicate that accurate estimates of diet can be determined using QFASA. Stable isotope mixing models provide rather coarse taxonomic resolution of diet composition. Prey DNA analysis shows promise as a method to estimate the species composition of diet, but further development and testing is needed to validate its use. Obtaining a representative sample from marine mammal populations is a significant challenge. Therefore, the use of complementary methods is recommended to obtain the most informative results.     

Canadians’ Perceptions of Food,Diet, and Health – A National Survey

Background

Poor nutrition is harmful to one’s health as it can lead to overweight and obesity and a number of chronic diseases. Understanding consumer perceptions toward diet and nutrition is critical to advancing nutrition-related population health interventions to address such issues. The purpose of this paper was to examine Canadians’ perceived health and diet status, compared to their actual health status, and general concern about their own diet and beliefs about health. Also analyzed were some of the perceived barriers to eating “healthy” foods, with a focus on the availability of “healthy” processed foods.

Methods

Two surveys were administered online to a group of Canadian panelists from all ten provinces during May 2010 to January 2011. Thirty thousand were invited; 6,665 completed the baseline survey and 5,494 completed the second survey. Panelists were selected to be nationally representative of the Canadian adult population by age, sex, province and education level, according to 2006 census data.

Results

Approximately one third of Canadians perceived their health or diet to be very good while very few Canadians perceived their health or diet to be very poor. While the majority of Canadians believed food and nutrition to be very important for improving one’s health, fewer Canadians were concerned about their own diets. The majority of Canadians reported difficulty finding “healthy” processed foods (low in salt and sugar and with sufficient vitamins and minerals). Many also reported difficulty finding healthy foods that are affordable.

Conclusion

Although consumers believe that nutrition is one of the most important factors for maintaining health, there are still a number of attitudinal and perceived environmental barriers to healthy eating.     

To Eat or Not To Eat? The Diet of the Endangered Iberian Wolf (Canis lupus signatus) in a Human-Dominated Landscape in Central Portugal

Livestock predation by large carnivores and their persecution by local communities are major conservation concerns. In order to prevent speculations and reduce conflicts, it is crucial to get detailed and accurate data on predators’ dietary ecology, which is particularly important in human dominated landscapes where livestock densities are high. This is the case of the endangered Iberian wolf in Portugal, an endemic subspecies of the Iberian Peninsula, which has seen its population distribution and abundance decline throughout the 20th century. Accordingly, the diet of the Iberian wolf was analyzed, using scat analysis, in a humanized landscape in central Portugal. From 2011 to 2014, a total of 295 wolf scats were collected from transects distributed throughout the study area, prospected on a monthly basis. Scat analysis indicated a high dependence of Iberian wolf on livestock. Domestic goat predominated the diet (62% of the scats), followed by cow (20%) and sheep (13%); the only wild ungulate present in the scat analysis was the wild boar (4% of the scats). Our results show that even though livestock constitute most part of wolves diet, different livestock species may represent different predation opportunities. We conclude that the high levels of livestock consumption may be a result of low diversity and density of wild ungulates that settles livestock as the only abundant prey for wolves. Our findings help on the understanding of the Iberian wolf feeding ecology and have implications for conflict management strategies. Finally, management implications are discussed and solutions are recommended.     

TDFCAM: A method for estimating stable isotope trophic discrimination in wild populations

1. Stable isotope mixing models (SIMMs) are widely used for characterizing wild animal diets. Such models rely upon using accurate trophic discrimination factors (TDFs) to account for the digestion, incorporation, and assimilation of food. Existing methods to calculate TDFs rely on controlled feeding trials that are time-consuming, often impractical for the study taxon, and may not reflect natural variability of TDFs present in wild populations.
2. We present TDF_CAM as an alternative approach to estimating TDFs in wild populations, by using high-precision diet estimates from a secondary methodological source—in this case nest cameras—in lieu of controlled feeding trials, and provide a framework for how and when it should be applied.
3. In this study, we evaluate the TDF_CAM approach in three datasets gathered on wild raptor nestlings (gyrfalcons Falco rusticolus; peregrine falcons Falco perigrinus; common buzzards Buteo buteo) comprising contemporaneous δ¹³C & δ¹⁵N stable isotope data and high-quality nest camera dietary data. We formulate Bayesian SIMMs (BSIMMs) incorporating TDFs from TDF_CAM and analyze their agreement with nest camera data, comparing model performance with those based on other relevant TDFs. Additionally, we perform sensitivity analyses to characterize TDF_CAM variability, and identify ecological and physiological factors contributing to that variability in wild populations.
4. Across species and tissue types, BSIMMs incorporating a TDF_CAM outperformed any other TDF tested, producing reliable population-level estimates of diet composition. We demonstrate that applying this approach even with a relatively low sample size (n < 10 individuals) produced more accurate estimates of trophic discrimination than a controlled feeding study conducted on the same species. Between-individual variability in TDF_CAM estimates for ∆¹³C & ∆¹⁵ N increased with analytical imprecision in the source dietary data (nest cameras) but was also explained by natural variables in the study population (e.g., nestling nutritional/growth status and dietary composition).
5. TDF_CAM is an effective method of estimating trophic discrimination in wild animal populations. Here, we use nest cameras as source dietary data, but this approach is applicable to any high-accuracy method of measuring diet, so long as diet can be monitored over an interval contemporaneous with a tissue's isotopic turnover rate.

     

The diets of polar cod (Boreogadus saida) from August 2008 in the US Beaufort Sea

Polar cod (Boreogadus saida) play an integral part in the Arctic ecosystems linking the upper and lower trophic levels. Though their estimated biomass is considerable, recent knowledge of their diets in the US Beaufort Sea is sparse. Collections of polar cod from the US Beaufort Sea were made during August 2008 using demersal and pelagic trawls. Polar cod diet composition was quantified as percent prey weight, percent prey count, and frequency of occurrence of prey. The diet composition between the demersal- and pelagic-captured cod showed differences in all these categories. Polar cod captured in the demersal nets primarily fed on fish (by weight), and pelagic cod primarily fed on copepods (frequency of occurrence) and euphausiids (by weight). In general, these dominant preys are different than what has been reported in other studies describing polar cod diets.     

Improving the Network Scale-Up Estimator: Incorporating Means of Sums,Recursive Back Estimation,and Sampling Weights

Researchers interested in studying populations that are difficult to reach through traditional survey methods can now draw on a range of methods to access these populations. Yet many of these methods are more expensive and difficult to implement than studies using conventional sampling frames and trusted sampling methods. The network scale-up method (NSUM) provides a middle ground for researchers who wish to estimate the size of a hidden population, but lack the resources to conduct a more specialized hidden population study. Through this method it is possible to generate population estimates for a wide variety of groups that are perhaps unwilling to self-identify as such (for example, users of illegal drugs or other stigmatized populations) via traditional survey tools such as telephone or mail surveys—by asking a representative sample to estimate the number of people they know who are members of such a “hidden” subpopulation. The original estimator is formulated to minimize the weight a single scaling variable can exert upon the estimates. We argue that this introduces hidden and difficult to predict biases, and instead propose a series of methodological advances on the traditional scale-up estimation procedure, including a new estimator. Additionally, we formalize the incorporation of sample weights into the network scale-up estimation process, and propose a recursive process of back estimation “trimming” to identify and remove poorly performing predictors from the estimation process. To demonstrate these suggestions we use data from a network scale-up mail survey conducted in Nebraska during 2014. We find that using the new estimator and recursive trimming process provides more accurate estimates, especially when used in conjunction with sampling weights.     

A Comparison of Methods for Analyzing Viral Load Data in Studies of HIV Patients

HIV RNA viral load (VL) is a pivotal outcome variable in studies of HIV infected persons. We propose and investigate two frameworks for analyzing VL: (1) a single-measure VL (SMVL) per participant and (2) repeated measures of VL (RMVL) per participant. We compared these frameworks using a cohort of 720 HIV patients in care (4,679 post-enrollment VL measurements). The SMVL framework analyzes a single VL per participant, generally captured within a “window” of time. We analyzed three SMVL methods where the VL binary outcome is defined as suppressed or not suppressed. The omit-participant method uses a 8-month “window” (-6/+2 months) around month 24 to select the participant’s VL closest to month 24 and removes participants from the analysis without a VL in the “window”. The set-to-failure method expands on the omit-participant method by including participants without a VL within the “window” and analyzes them as not suppressed. The closest-VL method analyzes each participant’s VL measurement closest to month 24. We investigated two RMVL methods: (1) repeat-binary classifies each VL measurement as suppressed or not suppressed and estimates the proportion of participants suppressed at month 24, and (2) repeat-continuous analyzes VL as a continuous variable to estimate the change in VL across time, and geometric mean (GM) VL and proportion of participants virally suppressed at month 24. Results indicated the RMVL methods have more precision than the SMVL methods, as evidenced by narrower confidence intervals for estimates of proportion suppressed and risk ratios (RR) comparing demographic strata. The repeat-continuous method had the most precision and provides more information than other considered methods. We generally recommend using the RMVL framework when there are repeated VL measurements per participant because it utilizes all available VL data, provides additional information, has more statistical power, and avoids the subjectivity of defining a “window.”     

Information-Driven Active Audio-Visual Source Localization

We present a system for sensorimotor audio-visual source localization on a mobile robot. We utilize a particle filter for the combination of audio-visual information and for the temporal integration of consecutive measurements. Although the system only measures the current direction of the source, the position of the source can be estimated because the robot is able to move and can therefore obtain measurements from different directions. These actions by the robot successively reduce uncertainty about the source’s position. An information gain mechanism is used for selecting the most informative actions in order to minimize the number of actions required to achieve accurate and precise position estimates in azimuth and distance. We show that this mechanism is an efficient solution to the action selection problem for source localization, and that it is able to produce precise position estimates despite simplified unisensory preprocessing. Because of the robot’s mobility, this approach is suitable for use in complex and cluttered environments. We present qualitative and quantitative results of the system’s performance and discuss possible areas of application.     

Selfie and the City: A World-Wide,Large, and Ecologically Valid Database Reveals a Two-Pronged Side Bias in Na?ve Self-Portraits

Self-portraits are more likely to show the artist’s right than left cheek. This phenomenon may have a psychobiological basis: Self-portraitists often copy their subject from mirrors and, if they prefer to present their left cheek (more expressive due to right-lateralization of emotions) to the mirror, this would result in a right-cheek bias in the painting. We tested this hypothesis using SelfieCity (3200 selfies posted on Instagram from December 4 through 12, 2013 from New York, Sao Paulo, Berlin, Moskow, and Bangkok), which includes two selfie-taking styles: a “standard” (photograph of selfie-taker) and a “mirror” (photograph of mirror reflection of selfie-taker) style. We show that the first style reveals a left cheek bias, whereas the second reveals a right cheek bias. Thus side biases observed in a world-wide, large, and ecologically valid database of naïve self-portraits provide strong support for a role of psychobiological factors in the artistic composition of self-portraits.     

The Independent Evolution Method Is Not a Viable Phylogenetic Comparative Method

Phylogenetic comparative methods (PCMs) use data on species traits and phylogenetic relationships to shed light on evolutionary questions. Recently, Smaers and Vinicius suggested a new PCM, Independent Evolution (IE), which purportedly employs a novel model of evolution based on Felsenstein’s Adaptive Peak Model. The authors found that IE improves upon previous PCMs by producing more accurate estimates of ancestral states, as well as separate estimates of evolutionary rates for each branch of a phylogenetic tree. Here, we document substantial theoretical and computational issues with IE. When data are simulated under a simple Brownian motion model of evolution, IE produces severely biased estimates of ancestral states and changes along individual branches. We show that these branch-specific changes are essentially ancestor-descendant or “directional” contrasts, and draw parallels between IE and previous PCMs such as “minimum evolution”. Additionally, while comparisons of branch-specific changes between variables have been interpreted as reflecting the relative strength of selection on those traits, we demonstrate through simulations that regressing IE estimated branch-specific changes against one another gives a biased estimate of the scaling relationship between these variables, and provides no advantages or insights beyond established PCMs such as phylogenetically independent contrasts. In light of our findings, we discuss the results of previous papers that employed IE. We conclude that Independent Evolution is not a viable PCM, and should not be used in comparative analyses.     

Critical summer foraging tradeoffs in a subarctic ungulate

Summer diets are crucial for large herbivores in the subarctic and are affected by weather, harassment from insects and a variety of environmental changes linked to climate. Yet, understanding foraging behavior and diet of large herbivores is challenging in the subarctic because of their remote ranges. We used GPS video‐camera collars to observe behaviors and summer diets of the migratory Fortymile Caribou Herd (Rangifer tarandus granti) across Alaska, USA and the Yukon, Canada. First, we characterized caribou behavior. Second, we tested if videos could be used to quantify changes in the probability of eating events. Third, we estimated summer diets at the finest taxonomic resolution possible through videos. Finally, we compared summer diet estimates from video collars to microhistological analysis of fecal pellets. We classified 18,134 videos from 30 female caribou over two summers (2018 and 2019). Caribou behaviors included eating (mean = 43.5%), ruminating (25.6%), travelling (14.0%), stationary awake (11.3%) and napping (5.1%). Eating was restricted by insect harassment. We classified forage(s) consumed in 5,549 videos where diet composition (monthly) highlighted a strong tradeoff between lichens and shrubs; shrubs dominated diets in June and July when lichen use declined. We identified 63 species, 70 genus and 33 family groups of summer forages from videos. After adjusting for digestibility, monthly estimates of diet composition were strongly correlated at the scale of the forage functional type (i.e., forage groups composed of forbs, graminoids, mosses, shrubs and lichens; r = 0.79, p < .01). Using video collars, we identified (1) a pronounced tradeoff in summer foraging between lichens and shrubs and (2) the costs of insect harassment on eating. Understanding caribou foraging ecology is needed to plan for their long‐term conservation across the circumpolar north, and video collars can provide a powerful approach across remote regions.     

ABO Genotype, ‘Blood-Type’ Diet and Cardiometabolic Risk Factors

Background

The ‘Blood-Type’ diet advises individuals to eat according to their ABO blood group to improve their health and decrease risk of chronic diseases such as cardiovascular disease. However, the association between blood type-based dietary patterns and health outcomes has not been examined. The objective of this study was to determine the association between ‘blood-type’ diets and biomarkers of cardiometabolic health and whether an individual''s ABO genotype modifies any associations.

Methods

Subjects (n = 1,455) were participants of the Toronto Nutrigenomics and Health study. Dietary intake was assessed using a one-month, 196-item food frequency questionnaire and a diet score was calculated to determine relative adherence to each of the four ‘Blood-Type’ diets. ABO blood group was determined by genotyping rs8176719 and rs8176746 in the ABO gene. ANCOVA, with age, sex, ethnicity, and energy intake as covariates, was used to compare cardiometabolic biomarkers across tertiles of each ‘Blood-Type’ diet score.

Results

Adherence to the Type-A diet was associated with lower BMI, waist circumference, blood pressure, serum cholesterol, triglycerides, insulin, HOMA-IR and HOMA-Beta (P<0.05). Adherence to the Type-AB diet was also associated with lower levels of these biomarkers (P<0.05), except for BMI and waist circumference. Adherence to the Type-O diet was associated with lower triglycerides (P<0.0001). Matching the ‘Blood-Type’ diets with the corresponding blood group did not change the effect size of any of these associations. No significant association was found for the Type-B diet.

Conclusions

Adherence to certain ‘Blood-Type’ diets is associated with favorable effects on some cardiometabolic risk factors, but these associations were independent of an individual''s ABO genotype, so the findings do not support the ‘Blood-Type’ diet hypothesis.     

Dietary effects on pelage emissivity in mammals: Implications for infrared thermography

Infrared thermography is becoming popular to measure animal surface temperature non-invasively. However, its application in quantitative mammal research is restricted by a paucity of pelage emissivity measurements, which are necessary to acquire accurate temperature readings. Furthermore, the factors influencing pelage emissivity remain largely unknown. We therefore examined the putative links between diet (fat content), hair length, hair diameter, and pelage emissivity in laboratory mice. Individuals maintained on high-fat diets had higher pelage emissivity values than those on standard diets, which may be due to fur being oily and/or the fact that the fur clumped together, exposing the skin underneath. Alternatively, the chemical composition of the fur of individuals on a high-fat diet may vary from those on a standard diet. We found no significant relationships between various hair metrics and emissivity. This study highlights that aspects of an animal's life history (e.g. age, sex, diet) may contribute to the emissivity of its pelage. As such, a single emissivity value may be inappropriate for use in infrared thermography across all species or individuals; other aspects of an animal's biology, which may affect emissivity, should also be considered. Best practice should involve measuring emissivity for every individual animal used in thermography studies.