Diet tracing in ecology: Method comparison and selection

Abstract

Determining diet is a key prerequisite for understanding species interactions, food web structure and ecological dynamics. In recent years, there has been considerable development in both the methodology and application of novel and more traditional dietary tracing methods, yet there is no comprehensive synthesis that systematically and quantitatively compares the different approaches. Here we conceptualise diet tracing in ecology, provide recommendations for method selection, and illustrate the advantages of method integration. We summarise empirical evidence on how different methods quantify diet mixtures, by contrasting estimates of dietary proportions from multiple methods applied to the same consumer‐resource datasets, or from experimental studies with known diet compositions. Our data synthesis revealed an urgent need for more experiential comparisons among the dietary methods. The comparison of diet quantifications from field observations showed that different techniques aligned well in cases with less than six diet items, but diverged considerably when applied to more complex diet mixtures. Efforts are ongoing to further advance dietary estimation, including how reliably compound specific stable isotope analyses and fatty acid profiles can quantify more prey items than bulk stable isotope analyses. Similarly, DNA analyses, which can depict trophic interactions at a higher resolution than any other method, are generating new ways to better quantify diets and differentiate among life‐stages of prey. Such efforts, combined with more empirical testing of each dietary method and establishment of open data repositories for dietary data, promise to greatly advance community and ecosystem ecology.

Spatiotemporal and demographic variation in the diet of New Zealand lesser short‐tailed bats (Mystacina tuberculata)

“…All previous work analyzing M. tuberculata diet used visual inspection and morphological analysis of partially digested prey remains in feces (Arkins et al., 1999; Daniel, 1979). This technique has limitations as more hard‐bodied prey will be recognizable after digestion, leading to an over‐representation of these taxa compared to soft‐bodied prey (Nielsen, Clare, Hayden, Brett, & Kratina, 2017). Conversely, molecular analysis has been demonstrated to accurately identify hard‐bodied prey and small, soft‐bodied prey (Clare et al 2009), but may be biased by primer binding and available reference collections (Nielsen et al., 2017).…”

“…This technique has limitations as more hard‐bodied prey will be recognizable after digestion, leading to an over‐representation of these taxa compared to soft‐bodied prey (Nielsen, Clare, Hayden, Brett, & Kratina, 2017). Conversely, molecular analysis has been demonstrated to accurately identify hard‐bodied prey and small, soft‐bodied prey (Clare et al 2009), but may be biased by primer binding and available reference collections (Nielsen et al., 2017). As such, both methods should be seen as confirming the presence of dietary items with different and potentially complimentary approaches.…”

Metabolism and foraging strategies of mid‐latitude mesozooplankton during cyanobacterial blooms as revealed by fatty acids, amino acids, and their stable carbon isotopes

“…However, FA trophic markers are not taxonomic indicators at the phytoplankton species level because some FAs indicate multiple algae classes (e.g., EPA in diatoms and (dino-) flagellates, Dalsgaard et al., 2003). Lately, stable carbon isotope analysis (δ 13 C) of individual essential compounds has been used as an accurate tool to reconstruct phototrophic sources of FAs and AAs in food webs (Kohlbach et al, 2016;Larsen et al, 2013;McMahon, Fogel, Elsdon, & Thorrold, 2010;Nielsen, Clare, Hayden, Brett, & Kratina, 2018) and thus can complement studies on FA trophic markers. in the Baltic Sea, can still be synthesized de novo by zooplankton (Kattner & Hagen, 1998;Peters et al, 2006).…”

Use of compound‐specific nitrogen isotope analysis of amino acids in trophic ecology: assumptions, applications, and implications

“…2). Optical identification or DNA metabarcoding of stomach contents are the most straightforward approaches to unravel 'who eats who' in trophic networks (e.g., Kartzinel et al 2015;Nielsen et al 2018). In contrast, the TP value in the energy flow web instead indicates 'who assimilates who' and enables the estimation of the average number of times that the organic matter is transferred from basal resource(s) to the animal of interest (Post 2002).…”

“…2 are very low and prey organisms exhibit various TPs. The two approaches sometimes cause confusion by showing an inconsistent contribution of prey to the consumers, especially in complex food webs where consumers are supported by dozens of prey organisms (Nielsen et al 2018). Furthermore, most animals drastically shift food preferences during their lifespan ).…”