Improving the application of quantitative fatty acid signature analysis in soil food webs: The effects of diet fat content

Abstract

Quantitative fatty acid signature analysis (QFASA) as a biochemical tool to study the diet composition of predators is frequently used in marine ecology to infer trophic links in vertebrate consumers. However, the potential and challenges of this method in other ecosystems have only recently been studied. The application in soil ecosystems leads to hurdles not encountered in the marine, such as the low similarity of fatty acid signatures between resource and consumer. So far, diet estimation attempts have been semisuccessful, necessitating to adapt QFASA for use in soil food webs. Dietary fat content may play an important role, as it influences consumer metabolism, and thus calibration coefficients for fatty acid trophic transfer. A series of feeding trials with baker's yeast spiked with five different pure fatty acids at various concentrations was conducted with Collembola, and the changes in calibration coefficients were observed. From there, equations were gained through regression analysis and new sets of calibration coefficients were calculated. QFASA was applied on a range of basal resources and the results compared with previously defined calibration coefficients. Calibration coefficients changed with the proportion of fatty acids in the diet and differed between the three Collembolan species. The re-estimation of diets showed an improvement of model performance by the new calibration coefficients and indicated several modes of fatty acid assimilation. These greatly influence the outcome of diet estimation, for example, algal and bacterial diets are likely underestimated due to high metabolic turnover rates. The application of QFASA in soil ecosystems remains challenging. The variation in calibration coefficients and the resulting decrease in estimation deviation indicate the merit of calculating calibration coefficients from consumer signatures through linear or exponential equations. Ideally, the method should, when extended to the entire fatty acid signature, allow correct determination of consumer diets in soil food webs.

Keywords: Collembola; lipids; quantitative fatty acid signature analysis; soil food webs.

FIGURE 1

Nonmetric multidimensional scaling (nMDS) analysis of the fatty acid pattern of the experimental diets (upper left) and of the three Collembola consumers Protaphorura fimata, Folsomia candida, and Lepidocyrtus violaceus after 3 days of feeding. Shown are pure yeast and the designed diets containing additionally 5% (bright color), 10% (intermediate shade), and 15% (dark color) of the fatty acid 18:1ω9, 18:2ω6,9, a15:0, cy19:0, 16:1ω5, or 16:3ω3,6,9 as well as combinations with two and three different fatty acids

FIGURE 2

Nonmetric multidimensional scaling (nMDS) analysis of the fatty acid pattern of the experimental diets (upper left) and of the three Collembola consumers Protaphorura fimata, Folsomia candida, and Lepidocyrtus violaceus after 6 days of feeding. Shown are pure yeast and the designed diets containing additionally 5% (bright color), 10% (intermediate shade), and 15% (dark color) of the fatty acid 18:1ω9, 18:2ω6,9, a15:0, cy19:0, 16:1ω5, or 16:3ω3,6,9 as well as combinations with two and three different fatty acids

FIGURE 3

Incorporation of fatty acids (FA) supplemented in the designed experimental diets relative to a baseline signature (ΔFA). Shown are the changes in the fat concentrations in consumers when fed on diets containing 5% (bright color), 10% (intermediate shade), and 15% (dark color) of the fatty acid 18:1ω9, 18:2ω6,9, a15:0, cy19:0, 16:1ω5, or 16:3ω3,6,9 in relation to a pure yeast diet

FIGURE 4

Linear regression of fatty acid proportion [%] in the consumer signature and their respective calibration coefficients. Shown are the regressions for all fatty acids supplemented in the design diets—18:1ω9, 18:2ω6,9, a15:0, cy19:0, 16:1ω5, and 16:3ω3,6,9 fed to the Collembola Protaphorura fimata, Folsomia candida, and Lepidocyrtus violaceus

FIGURE 5

Regression of fatty acid proportion [%] in the consumer signature and their respective calibration coefficients for a combined dataset of the experiment presented in this study and feeding data of a prior, related publication (Kühn et al., 2020). Shown are the regressions for all fatty acids supplemented in the design diets—18:1ω9, 18:2ω6,9, a15:0, cy19:0, 16:1ω5, and 16:3ω3,6,9 fed to the Collembola Protaphorura fimata, Folsomia candida, and Lepidocyrtus violaceus