DOI: 10.5061/dryad.q83bk3jsg
title: Prey selection by Chordeiles minor (Common Nighthawks) does not reflect differences in prey availability between breeding and nonbreeding grounds

description: Predators may adjust their diets to match their energy needs and food
 availability, but these adjustments have not been explored for migratory
 aerial insectivores outside of the breeding grounds. We found that
 Chordeiles minor (the Common Nighthawk), a long-distance migrant and
 member of the rapidly declining aerial insectivore guild, exhibited
 similar levels of diet richness, diet diversity, and prey selectivity on
 the breeding and nonbreeding grounds, despite large differences in prey
 abundance. We examined the diets and prey communities of C. minor during
 two breeding seasons in Florida, USA, and two nonbreeding seasons in
 Corrientes Province, Argentina (2020–2022). We used DNA metabarcoding to
 identify insect prey in C. minor fecal samples, and we employed malaise
 and UV light traps to assess the abundance and composition of aerial
 insect prey communities. The abundance and richness of available prey were
 significantly higher on the nonbreeding grounds than on the breeding
 grounds. Even so, C. minor exhibited similar within-sample and
 within-population diet richness, Shannon and Simpson diversities, and prey
 preferences at both sites. Adults differed in their consumption of
 Lepidoptera between sites: adults on the nonbreeding grounds preferred
 Lepidoptera over all other orders, whereas adults on the breeding grounds
 consumed Lepidoptera less frequently than expected. We suggest that
 breeding adult C. minor may deliver Lepidoptera to their young
 instead of consuming these prey. At both sites, C. minor showed a
 preference for large-bodied, nutrient-rich prey, suggesting that these
 generalist predators exhibit less diet flexibility than previously thought
 and thus may be vulnerable to changes in prey communities at multiple
 points in the annual cycle.
description: # Prey selection by *Chordeiles minor* (Common Nighthawks) does not
 reflect differences in prey availability between breeding and nonbreeding
 grounds
 [https://doi.org/10.5061/dryad.q83bk3jsg](https://doi.org/10.5061/dryad.q83bk3jsg) ## Description of the data and file structure We examined the diets and prey communities of *C. minor* during two breeding seasons in Florida, USA, and two nonbreeding seasons in Corrientes Province, Argentina (2020–2022). We used DNA metabarcoding to identify insect prey in *C. minor* fecal samples, and we employed malaise and UV light traps to assess the abundance and composition of aerial insect prey communities. Demultiplexed sequences from fecal metabarcoding were processed in Qiime2, and analysis of diet diversity, prey selection, and insect community diversity was conducted in R using the scripts and data files contained in this directory. ### Files and variables #### File: prey-selection-data.zip **Description:** Directory for all analysis. All raw data can be found in the data/ folder, saved model outputs in models/, and output tables in output/. ### **Contents** #### data/ all_taxa.csv * (list of all insects detected in diet samples after filtering, given at the most precise level obtained via metabarcoding) - Missing data: NA = was not classified at this level * Columns * order: insect order ID * family: insect family ID * genus: insect genus ID * species: insect species ID bold-taxonomy.qza  * (sequence data classified using BOLD reference library) - Needs to be read into R using 'qiime2R' function; this produces a list of objects including version and format info. * Relevant sequence data is contained in [["data"]] - Columns * "Feature.ID": uniqe identifier for ASV * "Taxon": complete taxonomic assignment * "Confidence": percent match to reference (proportion) cust-taxonomy.qza * (sequence data classified using custom reference library) * Same structure as bold-taxonomy.qza ncbi-taxonomy.qza * (sequence data classified using NCBI reference library) * Same structure as bold-taxonomy.qza table-176-dada2.qza * (processed sequence table exported from qiime2) * Needs to be read into R using 'qiime2R' function; this produces a list of objects including version and format info. * Relevant sequence data is contained in [["data"]] * Each row represents a unique ASV detected in diet (row names correspond with Feature.ID in *_taxonomy.qza files. * Each column represents a unique fecal sample. Samples starting with "CONI_2" are from USA and "CONI_RSM" are from Argentina. qiime_metadata_coni.csv * (sample metadata formatted for qiime2) - Missing values: NA = not measured * Columns * sample-id: Unique sample ID * source: location of sample collection (Citrus = Citrus WMA, RSM = Reserva NRSM) * dry-mass: mass of completely dried fecal sample (g)  * quality-ng-ul: DNA quality before PCR1 (nanograms per microliter) * sample-num: sample number, if more than one sample per bird * clean: yes/no; whether the sample was collected from a clean surface (yes) or not clean surface (no) * collect-date: sample collection date (m-d-yyyy) * source-year: site and year of collection (1 = first year, 2 = second year) * collect-time: sample collection time (hh:mm) * x-decimal-degree: longitude of sample collection (DD) * y-decimal-degree: latitude of sample collection (DD) insect_data_arg_final.csv * (raw data for insect trap samples in Argentina) - Missing values: NA = not measured * Columns * date: collection date (m/d/yyyy) * year: collection year * trap_id: unique sampling event ID * trap_type: trap type used for collection Malaise (M) or UV light (U) * length: insect body length (mm) * order: insect order * family: insect family insect_data_fl_final.csv * (raw data for insect trap samples in Florida) - Missing values: NA = not measured * Columns * date: collection date (m/d/yyyy) * year: collection year * trap_id: unique sampling event ID * trap_type: trap type used for collection Malaise (M) or UV light (U) * length: insect body length (mm) * order: insect order * family: insect family #### models/ coni_null_m_arg.rda * (prey selection econullnetr model output for Argentina Malaise trap data) * data structure can be found in the the helpfile for generate_null_net() coni_null_m_fl.rda  * (prey selection econullnetr model output for Florida Malaise trap data) * data structure can be found in the the helpfile for generate_null_net() coni_null_u_arg.rda  * (prey selection econullnetr model output for Argentina UV trap data) - data structure can be found in the the helpfile for generate_null_net() coni_null_u_fl.rda  * (prey selection econullnetr model output for Florida UV trap data) - data structure can be found in the helpfile for generate_null_net() insect.dissim.arg.csv * (insect community dissimilarity model output for Argentina) - data structure can be found in the helpfile for iNEXT.beta3D() insect.dissim.fl.csv  * (insect community dissimilarity model output for Florida) - data structure can be found in the helpfile for iNEXT.beta3D() insect.diversity.arg.csv  * (insect community diversity model output for Argentina) - data structure can be found in the helpfile for iNEXT.beta3D() insect.diversity.fl.csv  * (insect community diversity model output for Florida) - data structure can be found in the helpfile for iNEXT.beta3D() #### output/ Empty directory to house output files from R scripts #### scripts/ R scripts should be run in order (from 1\_ to 3_) coni_qiime2_scripts.txt * (scripts for processing raw reads in qiime2) 1_coni_diet_sequence_processing.Rmd * (R script for processing sequence data exported from qiime2) 2_coni_diet_diversity.Rmd * (R script for diet diversity analysis) 3_prey_selection_diversity.Rmd * (R script for prey selection and prey diversity analysis) ## Code/software Qiime 2 2023.5 R 4.3.2 ## Access information Data for creating COI classifiers was derived from the following sources: O'Rourke, D. R., N. A. Bokulich, M. A. Jusino, M. D. MacManes, J. T. Foster (2020). A total crapshoot? Evaluating bioinformatic decisions in animal diet metabarcoding analyses. *Ecology and Evolution* 00: 1– 19. Robeson II, M. E., D. R. O’Rourke, B. D. Kaehler, M. Ziemski, M. R. Dillon, J. T. Foster, N. A Bokulich (2020). RESCRIPt: Reproducible sequence taxonomy reference database management for the masses. *bioRxiv* 10.05.326504.