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Characterizing diet of the Least Tern Sternula antillarum using DNA metabarcoding.
Citation
BOGANTES, V.E., DARRAH, A.J., FOLKERTS CALDWELL, M., FELLGREN, A.K., WHITAKER, J.M. & JANOSIK, A.M. 2024. Characterizing diet of the Least Tern Sternula antillarum using DNA metabarcoding. .
Marine Ornithology 52: 283
- 291
http://doi.org/10.5038/2074-1235.52.2.1594
Received 04 August 2023, accepted 29 February 2024
Date Published: 2024/10/15
Date Online: 2024/10/04
Key words: diet analysis, DNA metabarcoding, fecal samples, Least Terns, shore birds
Abstract
A complete picture of diet composition is an essential element to understanding the ecological role of organisms. Moreover, diet studies can serve as an important tool for monitoring species and changes to the food web. One method to provide resolution when studying the diet of avian species is DNA metabarcoding of fecal samples. As such, we used DNA analysis to determine the diet of the Least Tern Sternula antillarum and compare results with diet analysis based on composition of fish dropped within breeding colonies. Comparisons between adult and chick fecal samples were also made across three years and within three zones of sample collection. Results show differences in diet composition between the two methods as well as across zones and years. Significant differences between prey items of adults and chicks were also identified. Metabarcoding data indicate that Least Terns are consuming Lionfish Pterois spp. (most likely in larval stages), a prey item that had not been previously recorded for Least Terns, and that data obtained from dropped fish might not be representative of chick diet. Differences across years and zones are likely due to shifts in the abundance and availability of prey items.
References
ANDO, H., MUKAI, H., KOMURA, T., DEWI, T., ANDO, M. & ISAGI, Y. 2020. Methodological trends and perspectives of animal dietary studies by noninvasive fecal DNA metabarcoding. Environmental DNA 2: 391-406.
ARMSTRONG, B.N., CAMBAZOGLU, M.K. & WIGGERT, J.D. 2021. Modeling the impact of the 2019 Bonnet Carre Spillway opening and local river flooding on the Mississippi Sound. Paper presented at OCEANS 2021: San Diego - Porto, 20-23 September, San Diego, USA. doi:10.23919/OCEANS44145.2021.9705854
ATWOOD, J.L. & KELLY, P.R. 1984. Fish dropped on breeding colonies as indicators of Least Tern food habits. Wilson Bulletin 96: 34-47.
BOLYEN, E., RIDEOUT, J.R., DILLON, M.R., ET AL. 2019. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology 37: 852-857.
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.
CARREKER, R.G. 1985. Habitat Suitability Index Models: Least Tern. Report No. 82/10.103. Washington, DC: U.S. Fish Wildlife and Service (FWS/OBS).
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.
DEAGLE, B.E., THOMAS, A.C., MCINNES, J.C., ET AL. 2019. Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data? Molecular Ecology 28:391-406.
DRAHEIM, H.M., MILLER, M.P., BAIRD, P. & HAIG, S.M. 2010. Subspecific status and population genetic structure of Least Terns (Sternula antillarum) inferred by mitochondrial DNA control-region sequences and microsatellite DNA. The Auk 127: 807-819.
ESNAOLA, A., ARRIZABALAGA-ESCUDERO, A., GONZÁLEZ-ESTEBAN, J., ELOSEGI, A. & AIHARTZA, J. 2018. Determining diet from faeces: Selection of metabarcoding primers for the insectivore Pyrenean desman (Galemys pyrenaicus). PLoS One 13: e0208986
GAGLIO, D., COOK, T.R., CONNAN, M., RYAN, P.G. & SHERLEY, R.B. 2017. Dietary studies in birds: testing a non‐invasive method using digital photography in seabirds. Methods in Ecology and Evolution 8: 214-222.
GERWING, T.G., KIM, J.-H., HAMILTON, D.J., BARBEAU, M.A. & ADDISON, J.A. 2016. Diet reconstruction using next-generation sequencing increases the known ecosystem usage by a shorebird. The Auk 133: 168-177.
GREEN, D.B., KLAGES, N.T.W., CRAWFORD, R.J.M., ET AL. 2015. Dietary change in Cape gannets reflects distributional and demographic shifts in two South African commercial fish stocks. ICES Journal of Marine Science 72: 771-781.
HARRIS, H.E., FOGG A.Q., ALLEN M.S., AHRENS R.N. M. & PATTERSON, W.F. 2020. Precipitous declines in northern Gulf of Mexico invasive lionfish populations following the emergence of an ulcerative skin disease. Scientific Reports 10: 1934.
HEBERT, C.E., WESELOH, D.V. C., IDRISSI, A., ET AL. 2008. Restoring piscivorous fish populations in the Laurentian Great Lakes causes seabird dietary change. Ecology 89: 891-897.
HOOVER, A., CHIAVERANO, L., DEARY A.L. & HERNANDEZ, F. 2022. Variation in larval Gulf menhaden diet, growth and condition during an atypical winter freshwater-discharge event in the northern Gulf of Mexico. Estuarine, Coastal and Shelf Science 265: 107692
JORDAN, M.J.R. 2005. Dietary analysis for mammals and birds: a review of field techniques and animal-management applications. International Zoo Yearbook 39: 108-116.
KIRSCH, E.M. & SIDLE, J.G. 1999. Status of the interior population of Least Tern. The Journal of Wildlife Management 63: 470-483.
MCINNES, J.C., ALDERMAN, R., LEA, M.-A., ET AL. 2017. High occurrence of jellyfish predation by black-browed and Campbell albatross identified by DNA metabarcoding. Molecular Ecology 26: 4831-4845.
MCINNES, J.C., EMMERSON, L., SOUTHWELL, C., FAUX, C. & JARMAN, S.N. 2016. Simultaneous DNA-based diet analysis of breeding, non-breeding and chick Adélie penguins. Royal Society Open Science 3: 150443.
MIYA, M., GOTOH, R.O. & SADO, T. 2020. MiFish metabarcoding: a high-throughput approach for simultaneous detection of multiple fish species from environmental DNA and other samples. Fisheries Science 86: 939-970.
MIYA, M., SATO, Y., FUKUNAGA, T., ET AL. 2015. MiFish, a set of universal PCR primers for metabarcoding environmental DNA from fishes: detection of more than 230 subtropical marine species. Royal Society Open Science 2: 150088.
O'CONNELL, M.T., CASHNER, R.C. & SCHIEBLE, C.S. 2004. Fish assemblage stability over fifty years in the Lake Pontchartrain Estuary; comparisons among habitats using canonical correspondence analysis. Estuaries 25: 807-817.
OKSANEN, J., BLANCHET, F.G., FRIENDLY, M., ET AL. 2020. vegan: Community Ecology Package. R package. Version 2.5-7. [Accessed online at https://CRAN.R-project.org/package=vegan on 01 Feb 2022.]
PANEK, M. 2021. Does habitat diversity modify the dietary and reproductive response to prey fluctuations in a generalist raptor predator, the Eurasian Buzzard Buteo buteo? Birds 2: 114-126.
RABALAIS, N.N., TURNER, R.E. & WISEMAN, W.J. JR. 2002. Gulf of Mexico hypoxia, a.k.a. “The dead zone.” Annual Review of Ecology and Systematics 33: 235-263.
SCHOFIELD, P.J. & FULLER, P. 2022. Fundulus grandis. Gainesville, USA: Nonindigenous Aquatic Species Database, U.S. Geological Survey. [Accessed at https://nas.er.usgs.gov/queries/factsheet.aspx?SpeciesID=687 on 05 May 2022.]
WILSON, E.C., HUBERT, W.A. & ANDERSON, S.H. 1993. Nesting and foraging of Least Terns on sand pits in central Nebraska. The Southwestern Naturalist 38: 9-14.