Detect and exploit hidden structure in fatty acid signature data

Measuring repeatability of compositional diet estimates: An example using quantitative fatty acid signature analysis

By measuring the temporal consistency, or repeatability, in the diets of predators, we can gain a better understanding of the degree of individual specialization in resource utilization and implications for predator-prey interactions, population dynamics, and food web structure. To measure repeatability, we require repeated diet estimates of individuals over time, such as those derived from quantitative fatty acid signature analysis (QFASA), a popular diet estimation technique. However, diet estimates are often lengthy compositional vectors with many zeros, as some prey will not be consumed by all individuals, precluding the use of previously proposed measures of repeatability. In this paper, we propose a novel approach for inferring repeatability for multivariate data and, in particular, compositional diet estimates. We extend the commonly used measure of repeatability for univariate data to the multivariate compositional setting by utilizing the mean squares obtained from a nonparametric multivariate analysis of variance, and an appropriate choice of statistical distance. Our measure and its extension are compatible with both balanced and unbalanced data sets. Associated confidence intervals via nonparametric bootstrapping are also developed for the case of QFASA diet estimates that incorporate both sampling error and measurement error, where the latter error arises because the diets of predators are estimated. Simulation study results suggest that for practical levels of repeatability, our methods yield confidence intervals with the desired coverage probability even when the sample size relative to the dimension of the data (i.e., number of prey species eaten) is small. We tested our methods using QFASA diet estimates for free-ranging Northwest Atlantic grey seals. Given the importance of understanding how predator diets vary over time and space, our method may find broad application to other compositional diet estimates, including those derived from the stomach or fecal contents, and stable isotope analyses.

Are tissue samples obtained via remote biopsy useful for fatty acid-based diet analyses in a free-ranging carnivore?

Fundamental knowledge on free-ranging animals has been obtained through capture-based studies; however, these may be logistically intensive, financially expensive, and potentially inconsistent with local cultural values. Genetic mark–recapture using remote tissue sampling has emerged as a less invasive alternative to capture-based population surveys but provides fewer opportunities to collect samples and measurements for broader ecological studies. We compared lipid content, fatty acid (FA) composition, and diet estimates from adipose tissue of polar bears (Ursus maritimus) obtained from two collection methods: remote biopsies (n = 138) sampled from helicopters and hunter-collected tissue (n = 499) from bears harvested in Davis Strait and Gulf of Boothia, Nunavut, 2010 – 2018. Lipid content of adipose tissue was lower in remote biopsies than harvest samples likely because remote biopsies removed only the outermost layer of subcutaneous tissue, rather than the more metabolically dynamic innermost tissue obtained from harvest samples. In contrast, FA composition was similar between the two collection methods with relatively small proportional differences in individual FAs. For diet estimates in Davis Strait, collection method was not a predictor of prey contribution to diet. In Gulf of Boothia, collection method was a predictor for some prey types, but the differences were relatively minor; the rank order of prey types was similar (e.g., ringed seal; Pusa hispida was consistently the primary prey in diets) and prey proportions differed by < 6% between the collection methods. Results from both methods showed that diets varied by geographic area, season, year, age class, and sex. Our study demonstrates that adipose tissue from remote biopsy provides reliable estimates of polar bear diet based on FA analysis and can be used to monitor underlying ecological changes in Arctic marine food webs.

Review of Estimating Trophic Relationships by Quantitative Fatty Acid Signature Analysis

The dynamic predator–prey relations in the food web are vital for understanding the function and structure of ecosystems. Dietary estimation is a research hotspot of quantitative ecology, providing key insights into predator–prey relationships. One of the most promising approaches is quantitative fatty acid signature analysis (QFASA), which is the first generation of statistical tools to estimate the quantitative trophic predator–prey relationships by comparing the fatty acid (FA) signatures among predators and their prey. QFASA has been continuously widely applied, refined and extended since its introduction. This article reviewed the research progress of QFASA from development and application. QFASA reflects the long-term diet of predator, and provides the quantitative dietary composition of predator, but it is sensitive to the metabolism of predator. The calibration coefficients (CCs) and the FA subset are two crucial parameters to explain the metabolism of predators, but the incorrect construction or improper use of CCs and the FA subset may cause bias in dietary estimation. Further study and refinement of the QFASA approach is needed to identify recommendations for which CCs and subsets of FA work best for different taxa and systems.