Review of Estimating Trophic Relationships by Quantitative Fatty Acid Signature Analysis

Abstract

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.

Validation of quantitative fatty acid signature analysis for estimating the diet composition of free-ranging killer whales

“…After choosing the best FA set, we ran multiple simulations using different sets of CCs. Each set of simulations was run using both the Kullback–Leibler (KL) distance 14 and the Aitchison distance 43 , as the literature has not yet settled on the best distance to use 44 . To evaluate which distance performed best, we determined how both scored in both the QFASA diagnostics (assumptions tests) and on the accuracy of the diet estimates relative to the true diet of the managed-care killer whales.…”

Trophic Transfer of Halogenated Organic Pollutants in a Wetland Food Web: Insights from Compound-Specific Nitrogen Isotope of Amino Acids and Food Source Analysis

“…66 Therefore, when using the TP mix model to quantify the TP of organisms in complex food webs, other research tools (e.g., field observations and stomach content analysis) are needed to assist in identifying a subset of the potential prey of consumers to improve the accuracy of the TP mix model. 67 ■ ASSOCIATED CONTENT * sı Supporting Information…”

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

“…For tissues such as blubber or adipose, which contain FAs that have accumulated over time, QFASA can provide an integrated record of dietary intake over a period of weeks to months (Budge et al, 2006) and has been used to estimate diets for a wide range of marine species (Zhang et al, 2020) including fish (Magnone et al, 2015), seabirds (Haynes et al, 2015;Iverson et al, 2007), pinnipeds (Beck et al, 2007;Bromaghin et al, 2013;Meynier et al, 2010), and polar bears (Galicia et al, 2016;Iverson et al, 2006;Thiemann et al, 2008).…”

“…Quantitative fatty acid signature analysis (QFASA, Iverson et al, 2004) is now a widely applied approach to estimating a predator's diet by comparing the FA profiles of metabolically active fat stores of predators with that of their potential prey, after taking into account modifications due to FA metabolism in the predator. For tissues such as blubber or adipose, which contain FAs that have accumulated over time, QFASA can provide an integrated record of dietary intake over a period of weeks to months (Budge et al, 2006) and has been used to estimate diets for a wide range of marine species (Zhang et al, 2020) including fish (Magnone et al, 2015), seabirds (Haynes et al, 2015; Iverson et al, 2007), pinnipeds (Beck et al, 2007; Bromaghin et al, 2013; Meynier et al, 2010), and polar bears (Galicia et al, 2016; Iverson et al, 2006; Thiemann et al, 2008). In cases where individual predators can be repeatedly sampled, diets estimated using QFASA provide an opportunity to examine temporal consistency over multiple time scales (e.g., Thiemann et al, 2011).…”