Aquatic biodiversity in a pond on the airport landside areas through environmental DNA metabarcoding: Implementation for Aviation Security Management

##plugins.themes.bootstrap3.article.main##

DWI SENDI PRIYONO
AKBAR REZA
RURY EPRILURAHMAN
DONAN SATRIA YUDHA
FARADINA MUFTI
NOORMAN HENDRY FAUZY
RADEN BAMBANG TRIYONO
PANGGIH KURNIA ADHI

Abstract


Abstract. Priyono DS, Reza A, Eprilurahman R, Yudha DS, Mufti D, Fauzy NH, Triyono RB, Adhi PK2022Aquatic biodiversity in a pond on the airport landside areas through environmental DNA metabarcoding: Implementation for Aviation Security ManagementBiodiversitas 23: 3639-3646Environmental DNA (eDNA) has become a widely used tool for aquatic biodiversity monitoring, as well as for formulating effective landscape management strategies. Yogyakarta International Airport (YIA), Indonesia, has a green belt landscape located on the Indian Ocean coast. YIA's landscape biodiversity analysis is still unexplored. Herein, we first used high throughput sequencing DNA metabarcoding to identify and investigate aquatic biodiversity in a pond on the airport landside areas. The metabarcoding eDNA sequencing analysis yielded 224,737 raw reads from the metagenomics utilizing Illumina MiSeq sequencing. We identified 588 eukaryote species from 205 families and 300 genera. Actinopteri is the most dominant class with a diversity of 160 taxa, followed by Mammalia (88), Amphibia (60), and Chlorophyceae (25). At the order level, Anura has the highest order diversity (50), followed by Rodentia (31), Chiroptera (17), Eulipotyphla (16), Squamata (15), and Cypriniformes (14). We found that Plasmodium was the genus with the highest relative abundance in this pond (18,030 reads). Furthermore, the large variety of fish and other taxa in this pond may attract waterbirds, increasing the risk of bird strike. The abundance of Plasmodium sp. in this airport area is an important issue, especially regarding airport malaria risk. Integration of biodiversity monitoring using eDNA with aviation security management provides valuable information for the airport's wildlife hazard management plan. To prevent the recurrence of bird strikes and prevent airport malaria, aviation security strategies utilizing habitat management approaches are recommended.


##plugins.themes.bootstrap3.article.details##

References
Askling HH, Bruneel F, Burchard G, Castelli F, Chiodini PL, Grobusch MP, Lopez-Vélez R, Paul M, Petersen E, Popescu C. 2012. Management of imported malaria in Europe. Malar J 11(1):1–15.
Aylagas E, Borja A, Rodriguez-Ezpeleta N. 2014. Environmental status assessment using DNA metabarcoding: towards a genetics based marine biotic index (gAMBI). PLoS One 9(3):e90529.
Brown KM, Erwin RM, Richmond ME, Buckley PA, Tanacredi JT, Avrin D. 2001. Managing birds and controlling aircraft in the Kennedy Airport–Jamaica Bay Wildlife Refuge Complex: the need for hard data and soft opinions. Environ Manage 28(2):207–224.
Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. 2016. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods 13(7):581–583.
Cock PJA, Fields CJ, Goto N, Heuer ML, Rice PM. 2010. The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res 38(6):1767–1771.
Corlett RT. 2017. A bigger toolbox: biotechnology in biodiversity conservation. Trends Biotechnol 35(1):55–65.
Davenport J, Davenport JL. 2006. The ecology of transportation: managing mobility for the environment. Springer: 385.
DeVault TL, Blackwell BF, Seamans TW, Belant JL. 2016. Identification of off airport interspecific avian hazards to aircraft. J Wildl Manage 80(4):746–752.
Dolbeer RA, Begier MJ, Miller PR, Weller JR, Anderson AL. 2021. Wildlife Strikes to Civil Aircraft in the United States, 1990–2019. United States. Department of Transportation. Federal Aviation Administration
Edgar RC. 2010. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26(19):2460–2461.
Ficetola GF, Miaud C, Pompanon F, Taberlet P. 2008. Species detection using environmental DNA from water samples. Biol Lett 4(4):423–425.
Ficetola GF, Pansu J, Bonin A, Coissac E, Giguet?Covex C, De Barba M, Gielly L, Lopes CM, Boyer F, Pompanon F. 2015. Replication levels, false presences and the estimation of the presence/absence from eDNA metabarcoding data. Mol Ecol Resour 15(3):543–556.
Fu Q, Wang N, Shen M, Song N, Yan H. 2016. A study of the site selection of a civil airport based on the risk of bird strikes: The case of Dalian, China. J Air Transp Manag 54:17–30.
Geijzendorffer IR, Regan EC, Pereira HM, Brotons L, Brummitt N, Gavish Y, Haase P, Martin CS, Mihoub J, Secades C. 2016. Bridging the gap between biodiversity data and policy reporting needs: An Essential Biodiversity Variables perspective. J Appl Ecol 53(5):1341–1350.
Gold Z, Curd EE, Goodwin KD, Choi ES, Frable BW, Thompson AR, Walker Jr HJ, Burton RS, Kacev D, Martz LD. 2021. Improving metabarcoding taxonomic assignment: A case study of fishes in a large marine ecosystem. Mol Ecol Resour 21(7):2546–2564.
Goldberg CS, Turner CR, Deiner K, Klymus KE, Thomsen PF, Murphy MA, Spear SF, McKee A, Oyler?McCance SJ, Cornman RS. 2016. Critical considerations for the application of environmental DNA methods to detect aquatic species. Methods Ecol Evol 7(11):1299–1307.
Hebert PDN, Cywinska A, Ball SL, Jeremy R. 2003. Biological identifications through DNA barcodes. Proc Biol Sci 270:313–321. doi:10.1098/rspb.2002.2218.
Hebert PDN, Ratnasingham S, Jeremy R. 2003b. Barcoding animal life?: cytochrome c oxidase subunit 1 divergences among closely related species. figure 1:96–99. doi:10.1098/rsbl.2003.0025.
Ji Y, Ashton L, Pedley SM, Edwards DP, Tang Y, Nakamura A, Kitching R, Dolman PM, Woodcock P, Edwards FA. 2013. Reliable, verifiable and efficient monitoring of biodiversity via metabarcoding. Ecol Lett 16(10):1245–1257.
Katoh K, Misawa K, Kuma K, Miyata T. 2002. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res 30(14):3059–3066.
Kitowski I, Grzywaczewski G, Cwiklak J, Grzegorzewski M, Krop S. 2011. Falconer activities as a bird dispersal tool at Deblin Airfield (E Poland). Transp Res Part D Transp Environ 16(1):82–86.
Lahoz?Monfort JJ, Guillera?Arroita G, Wintle BA. 2014. Imperfect detection impacts the performance of species distribution models. Glob Ecol Biogeogr 23(4):504–515.
Leach E. 2013. Managing the bird strike risk of Nankeen Kestrels (Falco cenchroides) at Brisbane Airport: an ecological approach. BSc Hons thesis Griffith Univ Brisbane.
Leray M, Knowlton N. 2015. DNA barcoding and metabarcoding of standardized samples reveal patterns of marine benthic diversity. Proc Natl Acad Sci 112(7):2076–2081.
Leray M, Yang JY, Meyer CP, Mills SC, Agudelo N, Ranwez V, Boehm JT, Machida RJ. 2013. A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: Application for characterizing coral reef fish gut contents. Front Zool 10(1):1–14. doi:10.1186/1742-9994-10-34.
Liu Y, Hsiang MS, Zhou H, Wang W, Cao Y, Gosling RD, Cao J, Gao Q. 2014. Malaria in overseas labourers returning to China: an analysis of imported malaria in Jiangsu Province, 2001–2011. Malar J 13(1):1–9.
López?Delgado EO, Winemiller KO, Villa?Navarro FA. 2020. Local environmental factors influence beta?diversity patterns of tropical fish assemblages more than spatial factors. Ecology 101(2):e02940.
Lusina D, Legros F, Esteve V, Klerlein M, Giacomini T. 2000. Airport malaria: four new cases in suburban Paris during summer 1999. Eurosurveillance 5(7):76–80.
McDonald D, Price MN, Goodrich J, Nawrocki EP, DeSantis TZ, Probst A, Andersen GL, Knight R, Hugenholtz P. 2012. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J 6(3):610–618.
Neice AA, McRae SB. 2021. An eDNA diagnostic test to detect a rare, secretive marsh bird. Glob Ecol Conserv 27:e01529.
Ondov BD, Bergman NH, Phillippy AM. 2011. Interactive metagenomic visualization in a Web browser. BMC Bioinformatics 12(1):1–10.
Russo T, Maiello G, Talarico L, Baillie C, Colosimo G, D’Andrea L, Di Maio F, Fiorentino F, Franceschini S, Garofalo G. 2021. All is fish that comes to the net: metabarcoding for rapid fisheries catch assessment. Ecol Appl 31(2):e02273.
Taberlet P, Bonin A, Zinger L, Coissac E. 2018. Environmental DNA: For biodiversity research and monitoring. Oxford University Press.
Tatem AJ, Rogers DJ, Hay SI. 2006. Estimating the malaria risk of African mosquito movement by air travel. Malar J 5(1):1–8.
Thang HD, Elsas RM, Veenstra J. 2002. Airport malaria: report of a case and a brief review of the literature. Neth J Med 60(11):441–443.
Thomsen PF, Willerslev E. 2015. Environmental DNA–An emerging tool in conservation for monitoring past and present biodiversity. Biol Conserv 183:4–18.
Ushio M, Murata K, Sado T, Nishiumi I, Takeshita M, Iwasaki W, Miya M. 2018. Demonstration of the potential of environmental DNA as a tool for the detection of avian species. Sci Rep 8(1):1–10.
Valentini A, Taberlet P, Miaud C, Civade R, Herder J, Thomsen PF, Bellemain E, Besnard A, Coissac E, Boyer F, et al. 2016. Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. Mol Ecol 25(4):929–942. doi:10.1111/mec.13428.
Weber L. 2021. International Civil Aviation Organization (ICAO). Kluwer Law International BV.
Yudha DS, Priyono DS, Izzati R, Ardianto AS, Puradi A, Nainggolan N. 2021. Comparising DNA extraction from environmental DNA samples to reveal the diversity of freshwater metazoans. Biog J Ilm Biol 9(2):206–212.
Zhou Sheng, Li Z, Cotter C, Zheng C, Zhang Q, Li H, Zhou Shuisen, Zhou X, Yu H, Yang W. 2016. Trends of imported malaria in China 2010–2014: analysis of surveillance data. Malar J 15(1):1–8.

Most read articles by the same author(s)