Prey selection by Chordeiles minor (Common Nighthawks) does not reflect differences in prey availability between breeding and nonbreeding grounds
Data files
Nov 27, 2024 version files 922.68 KB
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analysis-files.zip
916.15 KB
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README.md
6.54 KB
Abstract
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.
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
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(list of all insects detected in diet samples after filtering, given at the most precise level obtained via metabarcoding)
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Missing data: NA = was not classified at this level
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Columns
- order: insect order ID
- family: insect family ID
- genus: insect genus ID
- species: insect species ID
bold-taxonomy.qza
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(sequence data classified using BOLD reference library)
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Needs to be read into R using ‘qiime2R’ function; this produces a list of objects including version and format info.
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Relevant sequence data is contained in [[“data”]]
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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
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(sample metadata formatted for qiime2)
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Missing values: NA = not measured
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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
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(raw data for insect trap samples in Argentina)
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Missing values: NA = not measured
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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
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(raw data for insect trap samples in Florida)
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Missing values: NA = not measured
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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
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(prey selection econullnetr model output for Argentina UV trap data)
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data structure can be found in the the helpfile for generate_null_net()
coni_null_u_fl.rda
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(prey selection econullnetr model output for Florida UV trap data)
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data structure can be found in the helpfile for generate_null_net()
insect.dissim.arg.csv
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(insect community dissimilarity model output for Argentina)
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data structure can be found in the helpfile for iNEXT.beta3D()
insect.dissim.fl.csv
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(insect community dissimilarity model output for Florida)
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data structure can be found in the helpfile for iNEXT.beta3D()
insect.diversity.arg.csv
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(insect community diversity model output for Argentina)
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data structure can be found in the helpfile for iNEXT.beta3D()
insect.diversity.fl.csv
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(insect community diversity model output for Florida)
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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.