Gradients in richness and turnover of a forest passerine's diet prior to breeding: A mixed model approach applied to faecal metabarcoding data

Abstract

Rather little is known about the dietary richness and variation of generalist insectivorous species, including birds, due primarily to difficulties in prey identification. Using faecal metabarcoding, we provide the most comprehensive analysis of a passerine's diet to date, identifying the relative magnitudes of biogeographic, habitat and temporal trends in the richness and turnover in diet of Cyanistes caeruleus (blue tit) along a 39 site and 2° latitudinal transect in Scotland. Faecal samples were collected in 2014–2015 from adult birds roosting in nestboxes prior to nest building. DNA was extracted from 793 samples and we amplified COI and 16S minibarcodes. We identified 432 molecular operational taxonomic units that correspond to putative dietary items. Most dietary items were rare, with Lepidoptera being the most abundant and taxon‐rich prey order. Here, we present a statistical approach for estimation of gradients and intersample variation in taxonomic richness and turnover using a generalised linear mixed model. We discuss the merits of this approach over existing tools and present methods for model‐based estimation of repeatability, taxon richness and Jaccard indices. We found that dietary richness increases significantly as spring advances, but changes little with elevation, latitude or local tree composition. In comparison, dietary composition exhibits significant turnover along temporal and spatial gradients and among sites. Our study shows the promise of faecal metabarcoding for inferring the macroecology of food webs, but we also highlight the challenge posed by contamination and make recommendations of laboratory and statistical practices to minimise its impact on inference.

DNA metabarcoding reveals adaptive seasonal variation of individual trophic traits in a critically endangered fish

“…Indeed, Trophic Niche Variation (TNV) is driven, among other factors, by variation in ecological opportunity (i.e. the abundance and diversity of prey species) (Varpe & Fiksen, 2010;Shutt et al, 2020;Araújo et al, 2011), and the Optimal Foraging Theory predicts that when the availability of preferred prey species declines, previously disregarded or less preferred prey species will be incorporated into the diet, thus leading to trophic niche expansion at the population level (Perry & Pianka, 1997).…”

“…Empirical studies have confirmed that seasonality is a major source of trophic niche variation (e.g. Falke et al, 2020;Varpe & Fiksen, 2010;Shutt et al, 2020) that has implications for individual fitness (Durant et al, 2005;Hipfner, 2008) and affects the demography of populations (Miller-Rushing et al, 2010). In response to low resource availability, trophic niche expansion is predicted by the Optimal Foraging Theory (OFT; see Perry & Pianka 1997).…”

Diet induces parallel changes to the gut microbiota and problem solving performance in a wild bird

“…Microbiome analysis. Microbial DNA was extracted using the Qiagen QIAamp DNA Stool Kit, following the "Isolation of DNA from Stool for Pathogen Detection" protocol with modifications described in 73 to increase DNA yield and remove excess inhibitors expected to be present in the uric acid of bird faeces [but see 74 where they found no evidence of uric acid in faecal matter from a subset of avian species]. A 0.10-0.20 g aliquot of each faecal sample was added to the kit, alongside a negative control.…”

eDNA metabarcoding reveals a core and secondary diets of the greater horseshoe bat with strong spatio‐temporal plasticity

“…However, a suboptimal diet can have negative impacts on individual fitness (Sasakawa, 2009). Dietary plasticity, despite its potential ecological and evolutionary importance, remains scarcely addressed in the literature (Sousa et al., 2019; but see Shutt et al., 2020), potentially because dietary studies have long been constrained by methodological limits (e.g., low taxonomic level, nondetection of soft‐bodied prey, and limited number of processed samples; Nielsen et al., 2018). The development of molecular approaches for identifying prey DNA contained in feces, in particular environmental DNA (eDNA) metabarcoding, has overcome most of the limitations associated with traditional methods (Clare, 2014; Khanam et al., 2016).…”