Meta‐barcoding insights into the spatial and temporal dietary patterns of the threatened Asian Great Bustard (Otis tarda dybowskii) with potential implications for diverging migratory strategies

Abstract

Food resources are often not sufficient to satisfy the nutritional and energetic requirements during winter conditions at high latitudes. Dietary analysis is a prerequisite to fully understanding the feeding ecology of a species and the nature of trophic interactions. Previous dietary studies of Asian Great Bustard (Otis tarda dybowskii) relied on behavioral observations, resulting in categorization of diet limited to broad taxonomic groupings. Here, we applied a high‐throughput sequencing meta‐barcoding approach to quantify the diet of resident and migratory Asian Great Bustard in three wintering sites during early winter and late winter. We detected 57 unique plant taxa in the bustard diet, among which 15 species were confirmed by a local plant database we generated. Both agricultural and natural foods were detected, indicating a relatively broad dietary niche. Spatiotemporal dietary changes were discovered, revealing diet differences among wintering sites and a general shift toward lower plant diversity later in winter. For the nonmigratory population, we detected a significantly more diverse array of plant species in their diet. We hypothesize that dietary variation between resident and migratory populations could be involved in the recent transition to partial migration in this species, although climate change can not be excluded. Collectively, these results support protecting unharvested grain fields and naturally unplowed lands to help conserve and promote population growth of Asian Great Bustard.

Geography, seasonality, and host‐associated population structure influence the fecal microbiome of a genetically depauparate Arctic mammal

“…Microbiome studies of wild animals often use nonfresh fecal samples due to their noninvasive nature and inclusivity of the entire digestive tract (Li et al, ; Liu et al, ; Liu, Zhang, Zhang, Zhu, & Mao, ; Pope et al, ; Salgado‐Flores et al, ). Though contamination is a concern with nonfresh fecal samples, our study corroborates with findings from other muskox microbiome studies that used immediate fecal sampling (Andersen‐Ranberg et al, ; Ungerfeld et al, ).…”

Advancing the integration of multi‐marker metabarcoding data in dietary analysis of trophic generalists

“…This is highlighted by the detection of a range of animal and plant taxa that probably resulted from secondary ingestion or contamination, which may be a widespread problem in molecular analysis of trophic generalists, particularly when using small amplicons such as gh for plant trnL (Groom et al, 2017;Liu et al, 2018;Sullins et al, 2018) or generalist molecular markers (Bowser et al, 2013). This problem might be important, for instance, in conservation studies aiming to assess key trophic resources for a given species (Groom et al, 2017;Liu et al, 2018), in behavioural ecology research (Aizpurua et al, 2018;Quéméré et al, 2013), and even when reconstructing trophic networks from molecular data (Evans, Kitson, Lunt, Straw, & Pocock, 2016). To address this problem, visual analysis of a subset of samples would be desirable (Haarsma, Siepel, & Gravendeel, 2016), providing information on the range of taxa that are eaten, which could then be compared against the results of metabarcoding.…”

High‐resolution multi‐marker DNA metabarcoding reveals sexual dietary differentiation in a bird with minor dimorphism

“…The advent of high‐throughput DNA sequencing is making it possible to overcome the limitations of these methods, providing the ability to identify virtually all prey species consumed with unprecedent taxonomic resolution (Hope et al., 2014; Nielsen, Clare, Hayden, Brett, & Kratina, 2017; Razgour et al., 2011; Soininen et al., 2009). As a consequence, this approach has been increasingly used to describe the diets of a wide range of animals (Brown, Jarman, & Symondson, 2012; Kaunisto, Roslin, Sääksjärvi, & Vesterinen, 2017; Macías‐Hernández et al., 2018; Mata et al., 2016; Soininen et al., 2009), including birds (Coghlan et al., 2013; Deagle, Chiaradia, McInnes, & Jarman, 2010; Jedlicka, Vo, & Almeida, 2017; Liu et al., 2018; Sullins et al., 2018; Trevelline et al., 2018). The high taxonomic resolution provided by high‐throughput sequencing has already been used to describe sexual dietary differences that otherwise would be almost impossible to detect (Mata et al., 2016).…”