2018
DOI: 10.1007/s00442-018-4136-0
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DNA metabarcoding of nestling feces reveals provisioning of aquatic prey and resource partitioning among Neotropical migratory songbirds in a riparian habitat

Abstract: Riparian habitats are characterized by substantial flows of emergent aquatic insects that cross the stream-forest interface and provide an important source of prey for insectivorous birds. The increased availability of prey arising from aquatic subsidies attracts high densities of Neotropical migratory songbirds that are thought to exploit emergent aquatic insects as a nestling food resource; however, the prey preferences and diets of birds in these communities are only broadly understood. In this study, we ut… Show more

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Cited by 50 publications
(50 citation statements)
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“…Metabarcoding studies that focus on patterns in taxon richness commonly apply a two‐step analysis, first using rarefaction to quantify diversity at a focal sampling level and then using a statistical model to examine variation in taxon richness among samples (Quéméré et al, 2013). Studies interested in how taxonomic composition varies among samples have tended to rely on pairwise metrics, such as the Jaccard index, and nonparametric methods, such as PERMANOVA and the Mantel test (Alberdi, Aizpurua, Gilbert, & Bohmann, 2018; Mata et al, 2019; Trevelline, Nuttle, Hoenig, et al, 2018). Generalised linear mixed models (GLMMs) and their extensions provide a method for including structure in the data collection and multiple predictors into an analysis (Warton et al, 2015), but few studies have utilised them in diet metabarcoding to date (for exceptions see Mata et al, 2019; Nichols, Åkesson, & Kjellander, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…Metabarcoding studies that focus on patterns in taxon richness commonly apply a two‐step analysis, first using rarefaction to quantify diversity at a focal sampling level and then using a statistical model to examine variation in taxon richness among samples (Quéméré et al, 2013). Studies interested in how taxonomic composition varies among samples have tended to rely on pairwise metrics, such as the Jaccard index, and nonparametric methods, such as PERMANOVA and the Mantel test (Alberdi, Aizpurua, Gilbert, & Bohmann, 2018; Mata et al, 2019; Trevelline, Nuttle, Hoenig, et al, 2018). Generalised linear mixed models (GLMMs) and their extensions provide a method for including structure in the data collection and multiple predictors into an analysis (Warton et al, 2015), but few studies have utilised them in diet metabarcoding to date (for exceptions see Mata et al, 2019; Nichols, Åkesson, & Kjellander, 2016).…”
Section: Introductionmentioning
confidence: 99%
“…This single marker approach has been widely used in many studies (Gordon et al, ; McClenaghan, Nol, & Kerr, ; Moran, Prosser, & Moran, ), but it may produce significant biases due to differential primer affinity for different taxa. For instance, although ZBJ is often used as a ‘universal’ marker for arthropods (Crisol‐Martínez, Moreno‐Moyano, Wormington, Brown, & Stanley, ; Jedlicka, Vo, & Almeida, ; Trevelline, Latta, Marshall, Nuttle, & Porter, ; Trevelline et al, ), it may have strong positive or negative bias depending on the taxa (Clarke, Soubrier, Weyrich, & Cooper, ; Piñol, Mir, Gomez‐Polo, & Agustí, ). The challenge is even worse in the case of omnivorous diets, because the variety of taxonomic clades consumed cannot be analysed using a single marker (De Barba et al, ; Taberlet et al, ).…”
Section: Introductionmentioning
confidence: 99%
“…Diet studies are critical to the understanding of species interactions, trophic structures, and trophic dynamics (Nielsen, Clare, Hayden, Brett, & Kratina, ). They have been applied to a vast set of issues in ecology, evolution, and conservation, such as predator/prey interactions and habitat use (Corse et al, ; Sánchez‐Hernández, ), trophic niche partitioning (Kartzinel et al, ; Trevelline et al, ), and the delineation of habitats for guiding species conservation (Quéméré et al, ), management (Chivers et al, ), and habitat restoration (Motte & Libois, ). Diet studies have also proved critical in interfacing agriculture and ecology by assessing the effects of agricultural practices or policies on the trophic behaviors of species (Llaneza & López‐Bao, ; Mollot et al, ) and by evaluating the ecosystem services of wild species, such as in the control of crop pests (Aizpurua et al, ; McCracken et al, ).…”
Section: Introductionmentioning
confidence: 99%