Published September 5, 2023 | Version v1

Unravelling bird nest arthropod community structure using metabarcoding

  • 1. University of Guelph, Guelph, Canada
  • 2. University of Guelph, Guelph, Canada|University of Innsbruck, Innsbruck, Austria

Description

Bird nests are fascinating microcosms harboring a wide range of arthropods parasitizing the nesting birds or feeding on prey remains, feces, and the nest material. Studies of these communities have been entirely based on emergence traps which collect live organisms out of the nests. The analysis of nest contents and environmental DNA (eDNA) via metabarcoding could expand our knowledge and identify prey, exuviae, and other animal remains in bird nests. Here, we investigated the potential of arthropod remains, nest dust, and feathers to better describe arthropod diversity accumulated in 20 bird nests collected in Guelph (Canada). We used subsampling strategies and tested two extraction approaches to investigate the distribution of DNA in nests, account for low-quality DNA, and the presence of inhibitory substances. In total, 103 taxa were detected via metabarcoding. Arthropod remains delivered the highest number of taxa (n = 67), followed by nest dust (n = 29). Extractions with the PowerSoil kit outperformed DNeasy extractions coupled with PowerClean Pro inhibitor removal. Per nest, on average 5.5% taxonomic overlap between arthropod remains of different size classes was detected and subsamples of nest dust extracted with the PowerSoil kit showed 47.3% taxonomic overlap indicating a heterogeneous eDNA distribution in nests. Most detected species were either feeding in the nest, i.e., herbivorous / predatory, or bird food. We also detected molecular traces of 25 bird species, whose feathers were likely used as nest material. Consequently, the metabarcoding of bird nest materials provides a more complete picture of nest communities, which can enable future studies on functional diversity and better comparisons between nesting species.

Files

MBMG_article_103279.pdf

Files (1.8 MB)

Name Size
md5:43b7ab48016f69f06cb35816407adbe3
1.8 MB Preview Download

System files (144.8 kB)

Name Size
md5:b61f6b1911ec02ecc07ed8ce9776d6ed
144.8 kB Download

Linked records

Additional details

References

  • Baardsen LF, Matthysen E (2022) Changes in arthropod communities between breeding stages in nests of Great Tits. Journal of Field Ornithology 92(4): 518–531. https://doi.org/10.1111/jofo.12390
  • Baardsen LF, De Bruyn L, Adriaensen F, Elst J, Strubbe D, Heylen D, Matthysen E (2021) No overall effect of urbanization on nest-dwelling arthropods of great tits (Parus major). Urban Ecosystems 24(5): 959–972. https://doi.org/10.1007/s11252-020-01082-3
  • Barnes MA, Turner CR (2016) The ecology of environmental DNA and implications for conservation genetics. Conservation Genetics 17(1): 1–17. https://doi.org/10.1007/s10592-015-0775-4
  • Belles-Isles J-C, Picman J (1986) House Wren nest-destroying behavior. The Condor 88(2): 190–193. https://doi.org/10.2307/1368914
  • Brinck-Lindroth G, Smit FGAM (2007) The fleas (Siphonaptera) of Fennoscandia and Denmark. Fauna Entomologica Scandinavica Vol. 41. Brill Academic Publishers, Leiden & Boston, 196 pp. https://doi.org/10.1163/ej.9789004151512.i-188
  • Collias NE (1997) On the Origin and Evolution of Nest Building by Passerine Birds. The Condor 99(2): 253–270. https://doi.org/10.2307/1369932
  • Collias NE, Collias EC (1984) Nest building and bird behavior. Princeton University Press, Princeton, 358 pp. http://search.ebscohost.com/login.aspx?direct=true&AuthType=ip&db=e000xna&AN=791905&site=ehost-live&scope=site
  • Cornell Lab of Ornithology (2019a) All About Birds. Eastern Bluebird. Ithaca, New York, Cornell Lab of Ornithology. https://www.allaboutbirds.org/guide/Eastern_Bluebird/lifehistory
  • Cornell Lab of Ornithology (2019b) All About Birds. Eastern Phoebe. Ithaca, New York, Cornell Lab of Ornithology. https://www.allaboutbirds.org/guide/Eastern_Phoebe/overview
  • Creedy TJ, Ng WS, Vogler AP (2019) Toward accurate species-level metabarcoding of arthropod communities from the tropical forest canopy. Ecology and Evolution 9(6): 3105–3116. https://doi.org/10.1002/ece3.4839
  • deWaard JR, Ivanova NV, Hajibabaei M, Hebert PDN (2008) Assembling DNA barcodes. Analytical Protocols. Methods in Molecular Biology (Clifton, N.J. ) 410: 275–293. https://doi.org/10.1007/978-1-59745-548-0_15
  • Diaz-Real J, Serrano D, Piriz A, Jovani R (2015) NGS metabarcoding proves successful for quantitative assessment of symbiont abundance: The case of feather mites on birds. Experimental & Applied Acarology 67(2): 209–218. https://doi.org/10.1007/s10493-015-9944-x
  • Doña J, Proctor H, Serrano D, Johnson KP, Oploo AO, Huguet-Tapia JC, Ascunce MS, Jovani R (2019a) Feather mites play a role in cleaning host feathers: New insights from DNA metabarcoding and microscopy. Molecular Ecology 28(2): 203–218. https://doi.org/10.1111/mec.14581
  • Doña J, Serrano D, Mironov S, Montesinos-Navarro A, Jovani R (2019b) Unexpected bird–feather mite associations revealed by DNA metabarcoding uncovers a dynamic ecoevolutionary scenario. Molecular Ecology 28(2): 379–390. https://doi.org/10.1111/mec.14968
  • Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics (Oxford, England) 26(19): 2460–2461. https://doi.org/10.1093/bioinformatics/btq461
  • Edgar RC, Flyvbjerg H (2015) Error filtering, pair assembly and error correction for next-generation sequencing reads. Bioinformatics (Oxford, England) 31(21): 3476–3482. https://doi.org/10.1093/bioinformatics/btv401
  • Elbrecht V, Leese F (2015) Can DNA-Based Ecosystem Assessments Quantify Species Abundance? Testing Primer Bias and Biomass-Sequence Relationships with an Innovative Metabarcoding Protocol. PLoS ONE 10(7): 1–16. https://doi.org/10.1371/journal.pone.0130324
  • Elbrecht V, Leese F (2017) Validation and development of COI metabarcoding primers for freshwater macroinvertebrate bioassessment. Frontiers in Environmental Science 5: 1–11. https://doi.org/10.3389/fenvs.2017.00038
  • Elbrecht V, Steinke D (2018) Scaling up DNA metabarcoding for freshwater macrozoobenthos monitoring. Freshwater Biology 64(2): 380–387. https://doi.org/10.1111/fwb.13220
  • Elbrecht V, Peinert B, Leese F (2017a) Sorting things out: Assessing effects of unequal specimen biomass on DNA metabarcoding. Ecology and Evolution 7(17): 6918–6926. https://doi.org/10.1002/ece3.3192
  • Elbrecht V, Vamos EE, Meissner K, Aroviita J, Leese F (2017b) Assessing strengths and weaknesses of DNA metabarcoding-based macroinvertebrate identification for routine stream monitoring. Methods in Ecology and Evolution 8(10): 1265–1275. https://doi.org/10.1111/2041-210X.12789
  • Elbrecht V, Braukrnann TWA, Ivanova N, Prosser SWJ, Hajibabaei M, Wright M, Zakharov E, Hebert PDN, Steinke D (2019) Validation of COI metabarcoding primers for terrestrial arthropods. PeerJ 7: 1–23. https://doi.org/10.7717/peerj.7745
  • Elbrecht V, Bourlat SJ, Hörren T, Lindner A, Mordente A, Noll NW, Schäffler L, Sorg M, Zizka VMA (2021a) Pooling size sorted Malaise trap fractions to maximize taxon recovery with metabarcoding. PeerJ 9: 1–9. https://doi.org/10.7717/peerj.12177
  • Elbrecht V, Lindner A, Manerus L, Steinke D (2021b) A bright idea-metabarcoding arthropods from light fixtures. PeerJ 9: 1–13. https://doi.org/10.7717/peerj.11841
  • Foster NR, Martin B, Hoogewerff J, Aberle MG, de Caritat P, Roffey P, Edwards R, Malik A, Thwaites P, Waycott M, Young J (2023) The utility of dust for forensic intelligence: Exploring collection methods and detection limits for environmental DNA, elemental and mineralogical analyses of dust samples. Forensic Science International 344: 1–7. https://doi.org/10.1016/j.forsciint.2023.111599
  • Fryderyk S, Izdebska JN (2009) Birds as a living environment for parasitic arthropods. Katedra Zoologii Bezkręgowców, Uniwersytet Gdański, ul. Piłsudskiego 46: 81–378. https://www.academia.edu/63457779/Birds_as_a_living_environment_for_parasitic_arthropods
  • Gilbert G (2011) Community assembly of saprophagous arthropods of bird nest boxes. MSc Thesis, McGill University, Montreal, Canada. https://escholarship.mcgill.ca/concern/theses/gf06g310g
  • Gleason JE, Elbrecht V, Braukmann TWA, Hanner RH, Cottenie K (2021) Assessment of stream macroinvertebrate communities with eDNA is not congruent with tissue‐based metabarcoding. Molecular Ecology 30(13): 3239–3251. https://doi.org/10.1111/mec.15597
  • Guigueno MF, Sealy SG (2012) Nest sanitation in passerine birds: Implications for egg rejection in hosts of brood parasites. Journal of Ornithology 153(1): 35–52. https://doi.org/10.1007/s10336-011-0731-0
  • Healy SD, Morgan KV, Bailey IE (2015) Nest construction behaviour. In: Deeming DC, Reynolds SJ (Eds) Nests, eggs, and incubation: New ideas about avian reproduction. Oxford University Press, Oxford, 16–28. https://academic.oup.com/book/27880/chapter-abstract/203794482?redirectedFrom=fulltext&login=false
  • Hebert PDN, Cywinska A, Ball SL, DeWaard JR (2003) Biological identifications through DNA barcodes. Proceedings of the Royal Society B, Biological Sciences 270(1512): 313–321. https://doi.org/10.1098/rspb.2002.2218
  • Hernandez Triana LM, Prosser SW, Rodfriguez-Perez MA, Chaverri LG, Hebert PDN, Gregory TR (2014) Recovery of DNA barcodes from blackfly museum specimens (Diptera: Simuliidae) using primer sets that target a variety of sequence lengths. Molecular Ecology Resources 14(3): 508–518. https://doi.org/10.1111/1755-0998.12208
  • Hicks EA (1959) Check-list and bibliography on the occurrence of insects in birds' nests. Iowa State College Press, Ames, 681 pp. https://www.biodiversitylibrary.org/item/29868#page/7/mode/1up
  • Hicks EA (1962) Check-list and bibliography on the occurrence of insects in birds' nests. Supplement I. Iowa State College Journal of Science 36: 233–348.
  • Hicks EA (1971) Check-list and bilbiography on the occurrence of insects in birds' nests. Supplement 2. Iowa State Journal of Science 46: 123–338.
  • Ivanova NV, deWaard JR, Hebert PDN (2006) An inexpensive, automation-friendly protocol for recovering high-quality DNA. Molecular Ecology Notes 6: 998–1002. https://doi.org/10.1111/j.1471-8286.2006.01428.x
  • Kassambara A (2020) ggpubr: "ggplot2" Based Publication Ready Plots. [Available from:] https://CRAN.R-project.org/package=ggpubr
  • Krehenwinkel H, Fong M, Kennedy S, Huang EG, Noriyuki S, Cayetano L, Gillespie R (2018) The effect of DNA degradation bias in passive sampling devices on metabarcoding studies of arthropod communities and their associated microbiota. PLoS ONE 13(1): 1–14. https://doi.org/10.1371/journal.pone.0189188
  • Krehenwinkel H, Weber S, Künzel S, Kennedy SR (2022) The bug in a teacup—Monitoring arthropod–plant associations with environmental DNA from dried plant material. Biology Letters 18(6): 1–5. https://doi.org/10.1098/rsbl.2022.0091
  • Lennartz C, Kurucar J, Coppola S, Crager J, Bobrow J, Bortolin L, Comolli J (2021) Geographic source estimation using airborne plant environmental DNA in dust. Scientific Reports 11(1): 1–12. https://doi.org/10.1038/s41598-021-95702-3
  • Levesque-Beaudin V, Sinclair BJ, Marshall SA, Lauff RF (2020) Diptera communities of raptor (Aves) nests in Nova Scotia, Canada. Canadian Entomologist 152(3): 1–13. https://doi.org/10.4039/tce.2020.26
  • Lynggaard C, Bertelsen MF, Jensen CV, Johnson MS, Frøslev TG, Olsen MT, Bohmann K (2022) Airborne environmental DNA for terrestrial vertebrate community monitoring. Current Biology 32(3): 701–707. https://doi.org/10.1016/j.cub.2021.12.014
  • Madden AA, Barberán A, Bertone MA, Menninger HL, Dunn RR, Fierer N (2016) The diversity of arthropods in homes across the United States as determined by environmental DNA analyses. Molecular Ecology 25(24): 6214–6224. https://doi.org/10.1111/mec.13900
  • Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. Journal 17(1): 10–12. https://doi.org/10.14806/ej.17.1.200
  • Matange K, Tuck JM, Keung AJ (2021) DNA stability: A central design consideration for DNA data storage systems. Nature Communications 12(1): 1–9. https://doi.org/10.1038/s41467-021-21587-5
  • McCabe RA (1965) Nest Construction by House Wrens. The Condor 67(3): 229–234. https://doi.org/10.2307/1365401
  • McInnes JC, Bird JP, Deagle BE, Polanowski AM, Shaw JD (2021) Using DNA metabarcoding to detect burrowing seabirds in a remote landscape. Conservation Science and Practice 3(7): 1–6. https://doi.org/10.1111/csp2.439
  • Mennerat A, Perret P, Lambrechts MM (2009) Local Individual Preferences for Nest Materials in a Passerine Bird. PLoS ONE 4(4): 1–6. https://doi.org/10.1371/journal.pone.0005104
  • Messing J (1993) M13 cloning vehicles. In: Griffin HG, Griffin AM (Eds) DNA Sequencing Protocols. Methods in Molecular Biology, Humana Press (Clifton, N.J.) vol. 23, 9–22. https://doi.org/10.1385/0-89603-248-5:9
  • Oehm J, Juen A, Nagiller K, Neuhauser S, Traugott M (2011) Molecular scatology: How to improve prey DNA detection success in avian faeces? Molecular Ecology Resources 11(4): 620–628. https://doi.org/10.1111/j.1755-0998.2011.03001.x
  • Opel KL, Chung D, McCord BR (2010) A study of PCR inhibition mechanisms using real time PCR. Journal of Forensic Sciences 55(1): 25–33. https://doi.org/10.1111/j.1556-4029.2009.01245.x
  • Pfenninger M, Nowak C, Kley C, Steinke D, Streit B (2007) Utility of DNA taxonomy and barcoding for the inference of larval community structure in morphologically cryptic Chironomus (Diptera) species. Molecular Ecology 16(9): 1957–1968. https://doi.org/10.1111/j.1365-294X.2006.03136.x
  • Pribil S, Picman J (1991) Why House Wrens destroy clutches of other birds: A support for the nest site competition hypothesis. The Condor 93(1): 184–185. https://doi.org/10.2307/1368624
  • Prosser SWJ, deWaard JR, Miller SE, Hebert PDN (2016) DNA barcodes from century-old type specimens using next-generation sequencing. Molecular Ecology Resources 16(2): 487–497. https://doi.org/10.1111/1755-0998.12474
  • R Core Team (2021) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. [Available from:] https://www.R-project.org/
  • Ritter CD, Häggqvist S, Karlsson D, Sääksjärvi IE, Muasya AM, Nilsson RH, Antonelli A (2019) Biodiversity assessments in the 21st century: The potential of insect traps to complement environmental samples for estimating eukaryotic and prokaryotic diversity using high-throughput DNA metabarcoding. Trends in DNA Barcoding and Metabarcoding 01(3): 147–159. https://doi.org/10.1139/gen-2018-0096
  • Ruppert KM, Kline RJ, Rahman MS (2019) Past, present, and future perspectives of environmental DNA (eDNA) metabarcoding: A systematic review in methods, monitoring, and applications of global eDNA. Global Ecology and Conservation 17: 1–29. https://doi.org/10.1016/j.gecco.2019.e00547
  • Rytkönen S, Vesterinen EJ, Westerduin C, Leviäkangas T, Vatka E, Mutanen M, Välimäki P, Hukkanen M, Suokas M, Orell M (2019) From feces to data: A metabarcoding method for analyzing consumed and available prey in a bird-insect food web. Ecology and Evolution 9(1): 631–639. https://doi.org/10.1002/ece3.4787
  • Sabrosky CW, Bennett GF, Whitworth TL (2011) Bird blow flies (Protocalliphora) in North America (Diptera: Calliphoridae), with notes on the Palearctic species. Smithsonian Institution Press, Washington, D.C./London, 312 pp. https://doi.org/10.5962/bhl.title.46311
  • Sidstedt M, Rådström P, Hedman J (2020) PCR inhibition in qPCR, dPCR and MPS—Mechanisms and solutions. Analytical and Bioanalytical Chemistry 412(9): 2009–2023. https://doi.org/10.1007/s00216-020-02490-2
  • Sinclair CS, Gresens SE (2008) Discrimination of Cricotopus species (Diptera: Chironomidae) by DNA barcoding. Bulletin of Entomological Research 98(6): 555–563. https://doi.org/10.1017/S0007485308005865
  • Slowikowski K (2021) ggrepel: Automatically Position Non-Overlapping Text Labels with "ggplot2". [Available from:] https://CRAN.R-project.org/package=ggrepel
  • Smith TB, Marra PP, Webster MS, Lovette I, Gibbs HL, Holmes RT, Hobson KA, Rohwer S (2003) A call for feather sampling. The Auk 120(1): 218–221. https://doi.org/10.1642/0004-8038(2003)120[0218:ACFFS]2.0.CO;2
  • Steinke D, Braukmann TW, Manerus L, Woodhouse A, Elbrecht V (2021) Effects of Malaise trap spacing on species richness and composition of terrestrial arthropod bulk samples. Metabarcoding and Metagenomics 5: 43–50. https://doi.org/10.3897/mbmg.5.59201
  • Steinke D, DeWaard SL, Sones JE, Ivanova N, Prosser SWJ, Perez K, Braukmann TWA, Milton M, Zakharov E, DeWaard JR, Ratnasingham S, Hebert PDN (2022) Message in a Bottle-Metabarcoding enables biodiversity comparisons across ecoregions. GigaScience 11: 1–11. https://doi.org/10.1093/gigascience/giac040
  • Sutlović D, Definis Gojanović M, Andelinović S, Gugić D, Primorac D (2005) Taq polymerase reverses inhibition of quantitative real time polymerase chain reaction by humic acid. Croatian Medical Journal 46(4): 556–562. https://pubmed.ncbi.nlm.nih.gov/16100758/
  • Thalinger B, Oehm J, Obwexer A, Traugott M (2017) The influence of meal size on prey DNA detectability in piscivorous birds. Molecular Ecology Resources 17(6): e174–e186. https://doi.org/10.1111/1755-0998.12706
  • Townsend M, Waring P (2018) Concise guide to the moths of Great Britain and Ireland. Bloomsbury USA, 175 pp.
  • Tripet F, Richner H (1997) The coevolutionary potential of a "generalist" parasite, the hen flea Ceratophyllus gallinae. Parasitology 115(4): 419–427. https://doi.org/10.1017/S0031182097001467
  • Volpe NL, Thalinger B, Vilacoba E, Braukmann TWA, Di Giacomo AS, Berkunsky I, Lijtmaer DA, Steinke D, Kopuchian C (2022) Diet composition of reintroduced Red-and-Green Macaws reflects gradual adaptation to life in the wild. Ornithological Applications 124(1): 1–16. https://doi.org/10.1093/ornithapp/duab059
  • Wickham H (2016) ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag, New York. [Available from:] https://ggplot2.tidyverse.org
  • Wickham H, François R, Henry L, Müller K (2022) dplyr: A Grammar of Data Manipulation. [Available from:] https://CRAN.R-project.org/package=dplyr
  • Woodroffe GE (1953) An ecological study of the insects and mites in the nests of certain birds in Britain. Bulletin of Entomological Research 44(4): 739–772. https://doi.org/10.1017/S0007485300024706