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Abstract Identifying the composition of avian diets is a critical step in characterizing the roles of birds within ecosystems. However, because birds are a diverse taxonomic group with equally diverse dietary habits, gaining an accurate and thorough understanding of avian diet can be difficult. In addition to overcoming the inherent difficulties of studying birds, the field is advancing rapidly, and researchers are challenged with a myriad of methods to study avian diet, a task that has only become more difficult with the introduction of laboratory techniques to dietary studies. Because methodology drives inference, it is important that researchers are aware of the capabilities and limitations of each method to ensure the results of their study are interpreted correctly. However, few reviews exist which detail each of the traditional and laboratory techniques used in dietary studies, with even fewer framing these methods through a bird-specific lens. Here, we discuss the strengths and limitations of morphological prey identification, DNA-based techniques, stable isotope analysis, and the tracing of dietary biomolecules throughout food webs. We identify areas of improvement for each method, provide instances in which the combination of techniques can yield the most comprehensive findings, introduce potential avenues for combining results from each technique within a unified framework, and present recommendations for the future focus of avian dietary research. 

Abstract Determining how pollinators visit plants vs. how they carry and transfer pollen is an ongoing project in pollination ecology. The current tools for identifying the pollens that bees carry have different strengths and weaknesses when used for ecological inference. In this study we use three methods to better understand a system of congeneric, coflowering plants in the genusClarkiaand their bee pollinators: observations of plant–pollinator contact in the field, and two different molecular methods to estimate the relative abundance of eachClarkiapollen in samples collected from pollinators. We use these methods to investigate if observations of plant–pollinator contact in the field correspond to the pollen bees carry; if individual bees carryClarkiapollens in predictable ways, based on previous knowledge of their foraging behaviors; and how the three approaches differ for understanding plant–pollinator interactions. We find that observations of plant–pollinator contact are generally predictive of the pollens that bees carry while foraging, and network topologies using the three different methods are statistically indistinguishable from each other. Results from molecular pollen analysis also show that while bees can carry multiple species ofClarkiaat the same time, they often carry one species of pollen. Our work contributes to the growing body of literature aimed at resolving how pollinators use floral resources. We suggest our novel relative amplicon quantification method as another tool in the developing molecular ecology and pollination biology toolbox. 

Abstract Identifying genetic conservation units (CUs) in threatened species is critical for the preservation of adaptive capacity and evolutionary potential in the face of climate change. However, delineating CUs in highly mobile species remains a challenge due to high rates of gene flow and genetic signatures of isolation by distance. Even when CUs are delineated in highly mobile species, the CUs often lack key biological information about what populations have the most conservation need to guide management decisions. Here we implement a framework for CU identification in the Canada Warbler (Cardellina canadensis), a migratory bird species of conservation concern, and then integrate demographic modelling and genomic offset to guide conservation decisions. We find that patterns of whole genome genetic variation in this highly mobile species are primarily driven by putative adaptive variation. Identification of CUs across the breeding range revealed that Canada Warblers fall into two evolutionarily significant units (ESU), and three putative adaptive units (AUs) in the South, East, and Northwest. Quantification of genomic offset, a metric of genetic changes necessary to maintain current gene–environment relationships, revealed significant spatial variation in climate vulnerability, with the Northwestern AU being identified as the most vulnerable to future climate change. Alternatively, quantification of past population trends within each AU revealed the steepest population declines have occurred within the Eastern AU. Overall, we illustrate that genomics‐informed CUs provide a strong foundation for identifying current and future regional threats that can be used to inform management strategies for a highly mobile species in a rapidly changing world.