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Assessment of Tufted Puffin Fratercula cirrhata diet using DNA metabarcoding.
Citation
GOOD, T.P., SHELTON, A.O., WELLS, A.H., RAMÓN-LACA, A., GALLEGO, R., HODUM, P.J. & PEARSON, S.F. 2024. Assessment of Tufted Puffin Fratercula cirrhata diet using DNA metabarcoding..
Marine Ornithology 52: 235
- 245
http://doi.org/10.5038/2074-1235.52.2.1587
Received 01 December 2023, accepted 07 March 2024
Date Published: 2024/10/15
Date Online: 2024/09/15
Key words: metabarcoding, fecal DNA, Tufted Puffin, California Current
Abstract
Investigating trophic relationships can be critical for understanding relationships between marine predators and their prey. DNA analysis of feces is used increasingly as a non-invasive method to uncover seabird dietary patterns across space and time. Tufted Puffins Fratercula cirrhata are listed as Endangered in the state of Washington (WA), USA, and reduced prey availability is thought to be a key factor in the species' decline. Recent information on Tufted Puffin diet is lacking, and present opportunities for direct diet observation are limited. We conducted a pilot study to characterize Tufted Puffin diet on Destruction Island, WA, in 2019 using DNA metabarcoding of feces from burrow entrances and from soil in nesting chambers. Smelt (Osmeridae) and rockfish (Scorpaenidae) were detected in all fecal samples, along with a variety of other fish taxa, squid, crab, and shrimp. Smelt was detected in most soil samples, as were a variety of other fish, crustaceans, and terrestrial insects. While DNA metabarcoding detected several taxa also identified in Tufted Puffin bill-loads in 2019, fecal and soil samples detected multiple taxa not identified in bill-loads. It appears that Tufted Puffin diet can be characterized using DNA metabarcoding, provided that fecal samples are of sufficient quality and that contamination is minimized. Amplifying prey DNA from soil samples opens opportunities for sampling burrows after breeding, which would minimize disruptions to study colonies. Future strategies to characterize Tufted Puffin diet could combine direct observation and DNA metabarcoding methods where possible and could focus on the latter methods where observation is difficult. These non-destructive and non-disruptive methods hold promise for characterizing the diet of other burrow-nesting species of conservation concern.
References
AINLEY, D.G. & BOEKELHEIDE, R.J. (Eds.) 1990. Seabirds of the Farallon Islands: Ecology, Dynamics, and Structure of an Upwelling System Community. Palo Alto, USA: Stanford University Press.
BOGANTES, V.E., DARRAH, A.J., CALDWELL, M.F., FELLGREN, A.K., WHITAKER, J.M. & JANOSIK, A.M. 2024. Characterizing diet of the Least Tern Sternula antillarum using DNA metabarcoding. Marine Ornithology 52: in press.
BORSTAD, G., CRAWFORD, W., HIPFNER, J.M., THOMSON, R. & HYATT, K. 2011. Environmental control of the breeding success of Rhinoceros Auklets at Triangle Island, British Columbia. Marine Ecology Progress Series 424: 285-302. doi:10.3354/meps08950
BOWSER, A.K., DIAMOND, A.W. & ADDISON, J.A. 2013. From puffins to plankton: A DNA-based analysis of a seabird food chain in the northern Gulf of Maine. PLoS One 8: e83152. doi:10.1371/journal.pone.0083152
CALLAHAN, B.J., MCMURDIE, P.J., ROSEN, M.J., HAN, A.W., JOHNSON, A.J.A. & HOLMES, S.P. 2016. DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods 13: 581-583. doi:10.1038/nmeth.3869
CARREIRO, A.R., BRIED, J., DEAKIN, Z., ET AL. 2021. First insights into the diet composition of Madeiran and Monteiro's Storm Petrels (Hydrobates castro and H. monteiroi) breeding in the Azores. Waterbirds 44: 300-307. doi:10.1675/063.044.0304
CAVALLO, C., CHIARADIA, A., DEAGLE, B.E., ET AL. 2018. Molecular analysis of predator scats reveals role of salps in temperate inshore food webs. Frontiers in Marine Science 5: 381. doi:10.3389/fmars.2018.00381
CAVALLO, C., CHIARADIA, A., DEAGLE, B.E., ET AL. 2020. Quantifying prey availability using the foraging plasticity of a marine predator, the Little Penguin. Functional Ecology 34: 1626-1639. doi:10.1111/1365-2435.13605
DALÉN, L., LAGERHOLM, V.K., NYLANDER, J.A.A., ET AL. 2017. Identifying bird remains using ancient DNA barcoding. Genes 8: 169. doi:10.3390/genes8060169
DAVIES, W.E., HIPFNER, J.M., HOBSON, K.A. & YDENBERG, R.C. 2009. Seabird seasonal trophodynamics: Isotopic patterns in a community of Pacific alcids. Marine Ecology Progress Series 382: 211-219. doi:10.3354/meps07997
DEAGLE, B.E., GALES, N.J., EVANS, K., ET AL. 2007. Studying seabird diet through genetic analysis of faeces: A case study on Macaroni Penguins (Eudyptes chrysolophus). PLoS One 2: e831. doi:10.1371/journal.pone.0000831
DÍAZ-ABAD, L., BACCO-MANNINA, N., MIGUEL MADEIRA, F., ET AL. 2022. eDNA metabarcoding for diet analyses of green sea turtles (Chelonia mydas). Marine Biology 169: 18. doi:10.1007/s00227-021-04002-x
FAYET, A.L., CLUCAS, G.V., ANKER-NILSSEN, T., SYPOSZ, M. & HANSEN, E.S. 2021. Local prey shortages drive foraging costs and breeding success in a declining seabird, the Atlantic Puffin. Journal of Animal Ecology 90: 1152-1164. doi:10.1111/1365-2656.13442
FORD, M.J., HEMPELMANN, J., HANSON, M.B., ET AL. 2016. Estimation of a Killer Whale (Orcinus orca) population's diet using sequencing analysis of DNA from feces. PLoS One 11: e0144956. doi:10.1371/journal.pone.0144956
FOUNTAIN, E.D., KULZER, P.J., GOLIGHTLY, R.T., ET AL. 2023. Characterizing the diet of a threatened seabird, the Marbled Murrelet Brachyramphus marmoratus, using high-throughput sequencing. Marine Ornithology 51: 145-155.
FROESE, R. & PAULY, D. (Eds). 2023. FishBase. World Wide Web electronic publication. www.fishbase.org, version (10/2023).
GALLEGO, R. 2021. Nextera_Dada2. Boston, USA: Free Software Foundation, Inc. Accessed at https://github.com/ramongallego/Nextera_Dada2 on 01 April 2022.]
GJERDRUM, C., VALLÉE, A.M.J., ST. CLAIR, C.C., BERTRAM, D.F., RYDER, J.L. & BLACKBURN, G.S. 2003. Tufted Puffin reproduction reveals ocean climate variability. Proceedings of the National Academy of Sciences 100: 9377-9382. doi:10.1073/pnas.1133383100
HANSON, T., PEARSON, S.F., HODUM, P. & STINSON, D.W. 2019. Tufted Puffin Recovery Plan and Periodic Status Review. Olympia, USA: Washington Department of Fish and Wildlife.
HANSON, T. & WILES, G.J. 2015. Washington State Status Report for the Tufted Puffin. Olympia, USA: Washington Department of Fish and Wildlife.
HART, C.J., KELLY, R.P. & PEARSON, S.F. 2018. Will the California Current lose its nesting Tufted Puffins? PeerJ 6: e4519. doi:10.7717/peerj.4519
JARMAN, S.N., MCINNES, J.C., FAUX, C., ET AL. 2013. Adélie Penguin population diet monitoring by analysis of food DNA in scats. PLoS One 8: e82227. doi:10.1371/journal.pone.0082227
JONES, T., DIVINE, L.M., RENNER, H., ET AL. 2019. Unusual mortality of Tufted Puffins (Fratercula cirrhata) in the eastern Bering Sea. PLoS One 14: e0216532. doi:10.1371/journal.pone.0216532
KELLY, R.P., CLOSEK, C.J., O'DONNELL, J.L., KRALJ, J.E., SHELTON, A.O. & SAMHOURI, J.F. 2017. Genetic and manual survey methods yield different and complementary views of an ecosystem. Frontiers in Marine Science 3: 283. doi:10.3389/fmars.2016.00283
KOMURA, T., ANDO, H., HORIKOSHI, K., SUZUKI, H. & ISAGI, Y. 2018. DNA barcoding reveals seasonal shifts in diet and consumption of deep-sea fishes in Wedge-tailed Shearwaters. PLoS One 13: e0195385. doi:10.1371/journal.pone.0195385
MAHÉ, F., ROGNES, T., QUINCE, C., DE VARGAS, C. & DUNTHORN, M. 2015. Swarm v2: Highly scalable and high-resolution amplicon clustering. PeerJ 3: e1420. doi:10.7717/peerj.1420
MCINNES, J.C., ALDERMAN, R., DEAGLE, B.E., LEA, M.-A. BEN RAYMOND, B., JARMAN, S.N. 2016a. Optimised scat collection protocols for dietary DNA metabarcoding in vertebrates. Methods in Ecology and Evolution 8: 192-202. doi:10.1111/2041-210X.12677
MCINNES, J.C., ALDERMAN, R., LEA, M.-A., ET AL. 2017a. High occurrence of jellyfish predation by Black-browed and Campbell albatross identified by DNA metabarcoding. Molecular Ecology 26: 4831-4845. doi:10.1111/mec.14245
MCINNES, J.C., BIRD, J.P., DEAGLE, B.E., POLANOWSKI, A.M. & SHAW, J.D. 2021. Using DNA metabarcoding to detect burrowing seabirds in a remote landscape. Conservation Science and Practice 3: e439. doi:10.1111/csp2.439
MCINNES, J.C., EMMERSON, L., SOUTHWELL, C., FAUX, C. & JARMAN, S.N. 2016b. Simultaneous DNA-based diet analysis of breeding, non-breeding and chick Adélie Penguins. Royal Society Open Science 3: 150443. doi:10.1098/rsos.150443
MCINNES, J.C., JARMAN, S.N., LEA, M.-A., ET AL. 2017b. DNA metabarcoding as a marine conservation and management tool: A circumpolar examination of fishery discards in the diet of threatened albatrosses. Frontiers in Marine Science 4: 277. doi:10.3389/fmars.2017.00277
MICHAUX, J., DYCK, M., BOAG, P., LOUGHEED, S. & VAN COEVERDEN DE GROOT, P. 2021. New insights on Polar Bear (Ursus maritimus) diet from faeces based on next-generation sequencing technologies. Arctic 74: 87-99. doi:10.14430/arctic72239
NAEF, T., BESNARD, A.-L., LEHNEN, L., PETIT, E.J., VAN SCHAIK, J. & PUECHMAILLE, S.J. 2023. How to quantify factors degrading DNA in the environment and predict degradation for effective sampling design. Environmental DNA 5: 403-416. doi:10.1002/edn3.414
NIMZ, I., RENSHAW, M.A., BACZENAS, J., VANDERLIP, C., HYRENBACH, K.D. & IACCHEI, M. 2022. MetaBARFcoding: DNA-barcoding of regurgitated prey yields insights into Christmas Shearwater (Puffinus nativitatis) foraging ecology at Hōlanikū (Kure Atoll), Hawai‘i. Environmental DNA 4: 254-268. doi:10.1002/edn3.263
NORDSTROM, B., MITCHELL, N., BYRNE, M. & JARMAN, S. 2022. A review of applications of environmental DNA for reptile conservation and management. Ecology and Evolution 12: e8995. doi:10.1002/ece3.8995
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: 620-628. doi:10.1111/j.1755-0998.2011.03001.x
OEHM, J., THALINGER, B., EISENKÖLBL, S. & TRAUGOTT, M. 2017. Diet analysis in piscivorous birds: what can the addition of molecular tools offer? Ecology and Evolution 7: 1984-1995. doi:10.1002/ece3.2790
OOSTERBROEK, S., DOORENSPLEET, K., NIJLAND, R. & JANSEN, L. 2021. Decona: From demultiplexing to consensus for Nanopore amplicon data. ARPHA Conference Abstracts 4: e65029. doi:10.3897/aca.4.e65029
PEARSON, S.F., KEREN, I., HODUM, P.J., ET AL. 2023. Range-wide changes in the North American Tufted Puffin Fratercula cirrhata breeding population over 115 years. Bird Conservation International 33: e24. doi:10.1017/S0959270922000193
PIATT, J.F. & KITAYSKY, A.S. 2020. Tufted Puffin (Fratercula cirrhata), v. 1.0. In: BILLERMAN, S.M. (Ed.). Birds of the World. Ithaca, USA: Cornell Lab of Ornithology. doi:10.2173/bow.tufpuf.01
PONT, D., ROCLE, M., VALENTINI, A., ET AL. 2018. Environmental DNA reveals quantitative patterns of fish biodiversity in large rivers despite its downstream transportation. Scientific Reports 8: 10361. doi:10.1038/s41598-018-28424-8
PORT, J.A., O'DONNELL, J.L., ROMERO-MARACCINI, O.C., ET AL. 2016. Assessing vertebrate biodiversity in a kelp forest ecosystem using environmental DNA. Molecular Ecology 25: 527-541. doi:10.1111/mec.13481
ROGNES, T., FLOURI, T., NICHOLS, B., QUINCE, C. & MAHÉ, F. 2016. VSEARCH: A versatile open source tool for metagenomics. PeerJ 4: e2584. doi:10.7717/peerj.2584
SHELTON, A.O., GOLD, Z.J., JENSEN, A.J., ET AL. 2023. Toward quantitative metabarcoding. Ecology 104: e3906. doi:10.1002/ecy.3906
SIGSGAARD, E.E., NIELSEN, I.B., CARL, H., ET AL. 2017. Seawater environmental DNA reflects seasonality of a coastal fish community. Marine Biology 164: 128. doi:10.1007/s00227-017-3147-4
THALINGER, B., OEHM, J. & TRAUGOTT, M. 2022. Molecular methods to study Great Cormorant feeding ecology. Ardea 109: 537-547. doi:10.5253/arde.v109i2.a22
THOMAS, A.C., NELSON, B.W., LANCE, M.M., DEAGLE, B.E. & TRITES, A.W. 2017. Harbour seals target juvenile salmon of conservation concern. Canadian Journal of Fisheries and Aquatic Sciences 74: 907-921. doi:10.1139/cjfas-2015-0558
THOMSEN, P.F., MØLLER, P.R., SIGSGAARD, E.E., KNUDSEN, S.W., JØRGENSEN, O.A. & WILLERSLEV, E. 2016. Environmental DNA from seawater samples correlate with trawl catches of subarctic, deepwater fishes. PLoS One 11: e0165252. doi:10.1371/journal.pone.0165252
THOMSEN, P.F. & WILLERSLEV, E. 2015. Environmental DNA - An emerging tool in conservation for monitoring past and present biodiversity. Biological Conservation 183: 4-18. doi:10.1016/j.biocon.2014.11.019
TRUJILLO-GONZÁLEZ, A., LI, T., POTTS, J., ET AL. 2022. Can stomach content and microbiomes of tuna provide near real-time detection of ecosystem composition in the Pacific Ocean? Frontiers in Marine Science 9: 811532. doi:10.3389/fmars.2022.811532
USFWS (US FISH AND WILDLIFE SERVICE). 2020. Endangered and Threatened Wildlife and Plants; Eleven Species Not Warranted for Listing as Endangered or Threatened Species. 50 CFR, Part 17. Federal Register 85(233): 78029-78038. [Accessed at https://www.federalregister.gov/d/2020-26139.]
WAGNER, E.L., PEARSON, S.F., GOOD, T.P., HODUM, P.J., BUHLE, E.R. & SCHRIMPF, M.B. 2024. Resilience to a severe marine heatwave at two Pacific seabird colonies. Marine Ecology Progress Series 737: 101-120. doi:10.3354/meps14222
WEBER, E.D., AUTH, T.D., BAUMANN-PICKERING, S., ET AL. 2021. State of the California Current 2019-2020: Back to the future with marine heatwaves? Frontiers in Marine Science 8: 709454. doi:10.3389/fmars.2021.709454
WILLIAMS, C.T., IVERSON, S.J. & BUCK, C.L. 2008. Stable isotopes and fatty acid signatures reveal age- and stage-dependent foraging niches in Tufted Puffins. Marine Ecology Progress Series 363: 287-298. doi:10.3354/meps07477