Levin, L. A. et al. The function of marine critical transition zones and the importance of sediment biodiversity. Ecosystems 4, 430–451 (2001).
Google Scholar
Wagner, G. M. & Sallema-Mtui, R. in Estuaries: A Lifeline of Ecosystem Services in the Western Indian Ocean Estuaries of the World (eds S. Diop, P. Scheren, & J. Machiwa) 183–207 (2016).
Brown, C. J. et al. The assessment of fishery status depends on fish habitats. Fish Fish. 20, 1–14 (2019).
Google Scholar
De La Morinière, E. C., Pollux, B., Nagelkerken, I. & Van der Velde, G. Post-settlement life cycle migration patterns and habitat preference of coral reef fish that use seagrass and mangrove habitats as nurseries. Estuar. Coast. Shelf Sci. 55, 309–321 (2002).
Google Scholar
Branton, M. & Richardson, J. S. Assessing the value of the umbrella-species concept for conservation planning with meta-analysis. Conserv. Biol. 25, 9–20 (2011).
Google Scholar
Dudgeon, D. et al. Freshwater biodiversity: Importance, threats, status and conservation challenges. Biol. Rev. 81, 163–182 (2006).
Google Scholar
Zainal Abidin, D. H. et al. DNA-based taxonomy of a mangrove-associated community of fishes in Southeast Asia. Sci. Rep. 11, 1–15. https://doi.org/10.1038/s41598-021-97324-1 (2021).
Google Scholar
Gauthier, G. et al. Long-term monitoring at multiple trophic levels suggests heterogeneity in responses to climate change in the Canadian Arctic tundra. Philos. Trans. Roy. Soc. B Biol. Sci. 368, 20120482 (2013).
Valentini, A. et al. Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. Mol. Ecol. 25, 929–942 (2016).
Google Scholar
Myers, N., Mittermeier, R. A., Mittermeier, C. G., Da Fonseca, G. A. & Kent, J. Biodiversity hotspots for conservation priorities. Nature 403, 853 (2000).
Google Scholar
Chong, V. C., Lee, P. K. & Lau, C. M. Diversity, extinction risk and conservation of Malaysian fishes. J. Fish Biol. 76, 2009–2066. https://doi.org/10.1111/j.1095-8649.2010.02685.x (2010).
Google Scholar
Zainal Abidin, D. H. et al. Ichthyofauna of Sungai Merbok Mangrove Forest Reserve, northwest Peninsular Malaysia, and its adjacent marine waters. Check List 17, 601–631. https://doi.org/10.15560/17.2.601 (2021).
Google Scholar
Ong, J. et al. in Hutan paya laut Merbok, Kedah: Pengurusan hutan, persekitaran fizikal dan kepelbagaian flora. Vol. 23 Siri kepelbagaian biologi hutan (ed Ku Aman KA Abd Rahim AR, Abu Hassan MN, Abdullah M, Nor Hazliza MB, Latiff A) 21–33 (Jabatan Perhutanan Semenanjung Malaysia, 2015).
Hookham, B., Shau-Hwai, A. T., Dayrat, B. & Hintz, W. A baseline measure of tree and gastropod biodiversity in replanted and natural mangrove stands in Malaysia: Langkawi Island and Sungai Merbok. Trop. Life Sci. Res. 25, 1 (2014).
Google Scholar
Jamaluddin, J. A. F. et al. DNA barcoding of shrimps from a mangrove biodiversity hotspot. Mitochondrial DNA Part A 30, 618–625. https://doi.org/10.1080/24701394.2019.1597073 (2019).
Google Scholar
Mansor, M., Mohammad-Zafrizal, M., Nur-Fadhilah, M., Khairun, Y. & Wan-Maznah, W. Temporal and spatial variations in fish assemblage structures in relation to the physicochemical parameters of the Merbok estuary, Kedah. J. Nat. Sci. Res. 2, 110–127 (2012).
Alshari, N. F. M. A. H. et al. Metabarcoding of Fish Larvae in the Merbok River reveals species diversity and distribution along its mangrove environment. Zool. Stud. 60, 60–76. https://doi.org/10.6620/ZS.2021 (2021).
Google Scholar
Deiner, K., Fronhofer, E. A., Mächler, E., Walser, J.-C. & Altermatt, F. Environmental DNA reveals that rivers are conveyer belts of biodiversity information. Nat. Commun. 7, 1–9 (2016).
Hupało, K. et al. An urban Blitz with a twist: Rapid biodiversity assessment using aquatic environmental DNA. Environ. DNA 3, 200–213 (2020).
Bohmann, K. et al. Environmental DNA for wildlife biology and biodiversity monitoring. Trends Ecol. Evol. 29, 358–367 (2014).
Google Scholar
Taberlet, P., Coissac, E., Hajibabaei, M. & Rieseberg, L. H. Environmental DNA. Mol. Ecol. 21, 1789–1793 (2012).
Google Scholar
Ahn, H. et al. Evaluation of fish biodiversity in estuaries using environmental DNA metabarcoding. PLoS ONE 15, e0231127 (2020).
Google Scholar
Polanco, F. A. et al. Detecting aquatic and terrestrial biodiversity in a tropical estuary using environmental DNA. Biotropica 53, 1606–1619 (2021).
Zhang, H., Yoshizawa, S., Iwasaki, W. & Xian, W. Seasonal fish assemblage structure using environmental DNA in the Yangtze Estuary and its adjacent waters. Front. Mar. Sci. 6, 515. https://doi.org/10.3389/fmars.2019.00515 (2019).
Google Scholar
Stat, M. et al. Ecosystem biomonitoring with eDNA: Metabarcoding across the tree of life in a tropical marine environment. Sci. Rep. 7, 1–11 (2017).
Google Scholar
West, K. et al. Large-scale eDNA metabarcoding survey reveals marine biogeographic break and transitions over tropical north-western Australia. Divers. Distrib. 27, 1942–1957 (2021).
Hallam, J., Clare, E. L., Jones, J. I. & Day, J. J. Biodiversity assessment across a dynamic riverine system: A comparison of eDNA metabarcoding versus traditional fish surveying methods. Environ. DNA 3, 1247–1266 (2021).
Seymour, M. et al. Environmental DNA provides higher resolution assessment of riverine biodiversity and ecosystem function via spatio-temporal nestedness and turnover partitioning. Commun. Biol. 4, 1–12 (2021).
Aglieri, G. et al. Environmental DNA effectively captures functional diversity of coastal fish communities. Mol. Ecol. 30, 3127–3139 (2021).
Google Scholar
Fujii, K. et al. Environmental DNA metabarcoding for fish community analysis in backwater lakes: A comparison of capture methods. PLoS ONE 14, e0210357 (2019).
Google Scholar
Lecaudey, L. A., Schletterer, M., Kuzovlev, V. V., Hahn, C. & Weiss, S. J. Fish diversity assessment in the headwaters of the Volga River using environmental DNA metabarcoding. Aquat. Conserv. Mar. Freshwat. Ecosyst. 29, 1785–1800 (2019).
Zou, K. et al. eDNA metabarcoding as a promising conservation tool for monitoring fish diversity in a coastal wetland of the Pearl River Estuary compared to bottom trawling. Sci. Total Environ. 702, 134704 (2020).
Google Scholar
Klymus, K. E., Marshall, N. T. & Stepien, C. A. Environmental DNA (eDNA) metabarcoding assays to detect invasive invertebrate species in the Great Lakes. PLoS ONE 12, 24. https://doi.org/10.1371/journal.pone.0177643 (2017).
Google Scholar
Wilson, C. et al. Tracking ghosts: Combined electrofishing and environmental DNA surveillance efforts for Asian carps in Ontario waters of Lake Erie. Manag. Biol. Invasion 5, 225–231. https://doi.org/10.3391/mbi.2014.5.3.05 (2014).
Google Scholar
Alexander, J. B. et al. Development of a multi-assay approach for monitoring coral diversity using eDNA metabarcoding. Coral Reefs 39, 159–171. https://doi.org/10.1007/s00338-019-01875-9 (2020).
Google Scholar
Port, J. A. et al. Assessing vertebrate biodiversity in a kelp forest ecosystem using environmental DNA. Mol. Ecol. 25, 527–541. https://doi.org/10.1111/mec.13481 (2016).
Google Scholar
Fritts, A. K. et al. Development of a quantitative PCR method for screening ichthyoplankton samples for bigheaded carps. Biol. Invasions 21, 1143–1153 (2019).
Maruyama, A., Nakamura, K., Yamanaka, H., Kondoh, M. & Minamoto, T. The release rate of environmental DNA from juvenile and adult fish. PLoS ONE 9, e114639 (2014).
Google Scholar
Amberg, J. J., Merkes, C. M., Stott, W., Rees, C. B. & Erickson, R. A. Environmental DNA as a tool to help inform zebra mussel, Dreissena polymorpha, management in inland lakes. Manag. Biol. Invasion 10, 96 (2019).
Gu, Z., Gu, L., Eils, R., Schlesner, M. & Brors, B. Circlize implements and enhances circular visualization in R. Bioinformatics 30, 2811–2812. https://doi.org/10.1093/bioinformatics/btu393 (2014).
Google Scholar
Zainal Abidin, D. H. & Noor Adelyna, M. A. Environmental DNA (eDNA) Metabarcoding as a Sustainable Tool of Coastal Biodiversity Assessment in Universities as Living Labs for Sustainable Development 211–225 (Springer, 2020).
Sard, N. M. et al. Comparison of fish detections, community diversity, and relative abundance using environmental DNA metabarcoding and traditional gears. Environ. DNA 1, 368–384 (2019).
Hoffman, J. C., Kelly, J. R., Trebitz, A. S., Peterson, G. S. & West, C. W. Effort and potential efficiencies for aquatic non-native species early detection. Can. J. Fish. Aquat. Sci. 68, 2064–2079 (2011).
Yamamoto, S. et al. Environmental DNA metabarcoding reveals local fish communities in a species-rich coastal sea. Sci. Rep. 7, 1–12 (2017).
Whitfield, A. K. Fish species in estuaries—From partial association to complete dependency. J. Fish Biol. 97, 1262–1264 (2020).
Google Scholar
Carpenter, K. & Niem, V. The living marine resources of the Western Central Pacific. Volume 5. Bony Fishes Part 3 (Menidae to Pomacentridae). Vol. 5, 2791–3380 (Food and Agriculture Organization of the United Nations, 2001).
Carpenter, K. E. & Niem, V. FAO species identification guide for fishery purposes. The Living Marine Resources of the Western Central Pacific. Volume 6. Bony Fishes Part 4 (Labridae to Latimeriidae), Estuarine Crocodiles, Sea Turtles, Sea Snakes and Marine Mammals. Vol. 6, 3381–4218 (Food and Agriculture Organization of the United Nations, 2001).
Carpenter, K. E. & Niem, V. H. The living marine resources of the Western Central Pacific: Batoid fishes, chimaera and bony fishes part 1 (Elopidae to Linophrynidae). Vol. 3, 1397–2068 (Food and Agriculture Organization of the United Nations, 1999).
Carpenter, K. E. & Niem, V. H. The living marine resources of the Western Central Pacific. Volume 4. Bony Fishes Part 2 (Mugilidae to Carangidae). Vol. 4, 2069–2790 (Food and Agriculture Organization of the United Nations, 1999).
Benson, D. A. et al. GenBank. Nucleic Acids Res. 46, D41–D47 (2018).
Google Scholar
Pentinsaari, M., Ratnasingham, S., Miller, S. E. & Hebert, P. D. N. BOLD and GenBank revisited—Do identification errors arise in the lab or in the sequence libraries?. PLoS ONE 15, e0231814–e0231814. https://doi.org/10.1371/journal.pone.0231814 (2020).
Google Scholar
Ardura, A., Planes, S. & Garcia-Vazquez, E. Applications of DNA barcoding to fish landings: Authentication and diversity assessment. Zookeys 365, 49–65. https://doi.org/10.3897/zookeys.365.6409 (2013).
Google Scholar
ZainalAbidin, D. H. et al. Population genetics of the black scar oyster, Crassostrea iredalei: Repercussion of anthropogenic interference. Mitochondrial DNA Part A 27, 647–658 (2016).
Google Scholar
Kelly, R. P. et al. Genetic and manual survey methods yield different and complementary views of an ecosystem. Front. Mar. Sci. 3, 283 (2017).
Ratnasingham, S. & Hebert, P. D. BOLD: The barcode of life data system (http://www.barcodinglife.org). Mol. Ecol. Notes 7, 355–364 (2007).
Google Scholar
Barnes, M. A. & Turner, C. R. The ecology of environmental DNA and implications for conservation genetics. Conserv. Genet. 17, 1–17. https://doi.org/10.1007/s10592-015-0775-4 (2016).
Google Scholar
Vasconcelos, R. P. et al. Global patterns and predictors of fish species richness in estuaries. J. Anim. Ecol. 84, 1331–1341 (2015).
Google Scholar
Shah, A. S. R. M., Hashim, Z. H. & Sah, S. A. M. Freshwater fishes of Gunung Jerai, Kedah Darul Aman: A preliminary study. Trop. Life Sci. Res. 20, 59 (2009).
Google Scholar
Md. Zain, K. et al. Fish diversity along streams in Ulu Muda Forest Reserve, Kedah, Peninsular Malaysia. Malayan Nat. J. 73, 349–361 (2021).
Thomsen, P. F. et al. Monitoring endangered freshwater biodiversity using environmental DNA. Mol. Ecol. 21, 2565–2573 (2012).
Google Scholar
Wang, S. et al. Methodology of fish eDNA and its applications in ecology and environment. Sci. Total Environ. 755, 142622. https://doi.org/10.1016/j.scitotenv.2020.142622 (2021).
Google Scholar
Deiner, K. et al. Environmental DNA metabarcoding: Transforming how we survey animal and plant communities. Mol. Ecol. 26, 5872–5895 (2017).
Google Scholar
Southeast Asian Fisheries Development Centre (SEAFDEC). Status and trends of sharks fisheries in South East Asia in Malaysia Shark Fisheries (Fisheries and Resources Monitoring System (FIRMS), Rome, 2004).
Zhang, S., Zhao, J. & Yao, M. A comprehensive and comparative evaluation of primers for metabarcoding eDNA from fish. Methods Ecol. Evol. 11, 1609–1625 (2020).
Google Scholar
Doi, H. et al. Environmental DNA analysis for estimating the abundance and biomass of stream fish. Freshw. Biol. 62, 30–39 (2017).
Google Scholar
Hayami, K. et al. Effects of sampling seasons and locations on fish environmental DNA metabarcoding in dam reservoirs. Ecol. Evol. 10, 5354–5367 (2020).
Google Scholar
Collins, R. A. et al. Persistence of environmental DNA in marine systems. Commun. Biol. https://doi.org/10.1038/s42003-018-0192-6 (2018).
Google Scholar
Morey, K. C., Bartley, T. J. & Hanner, R. H. Validating environmental DNA metabarcoding for marine fishes in diverse ecosystems using a public aquarium. Environ. DNA 2, 330–342 (2020).
Shaw, J. L. et al. Comparison of environmental DNA metabarcoding and conventional fish survey methods in a river system. Biol. Cons. 197, 131–138 (2016).
Siegenthaler, A. et al. Metabarcoding of shrimp stomach content: Harnessing a natural sampler for fish biodiversity monitoring. Mol. Ecol. Resour. 19, 206–220. https://doi.org/10.1111/1755-0998.12956 (2019).
Google Scholar
Stoeckle, M. Y., Das Mishu, M. & Charlop-Powers, Z. Improved environmental DNA reference library detects overlooked marine fishes in New Jersey, United States. Front. Mar. Sci. 7, 226 (2020).
Collins, R. A. et al. Non-specific amplification compromises environmental DNA metabarcoding with COI. Methods Ecol. Evol. 10, 1985–2001 (2019).
Hebert, P. D., Ratnasingham, S. & De Waard, J. R. Barcoding animal life: Cytochrome c oxidase subunit 1 divergences among closely related species. Proc. Roy. Soc. Lond. Ser. B Biol. Sci. 270, S96–S99 (2003).
Google Scholar
Miya, M. et al. MiFish, a set of universal PCR primers for metabarcoding environmental DNA from fishes: Detection of more than 230 subtropical marine species. Roy. Soc. Open Sci. 2, 150088 (2015).
Google Scholar
Mariani, S., Baillie, C., Colosimo, G. & Riesgo, A. Sponges as natural environmental DNA samplers. Curr. Biol. 29, R401–R402 (2019).
Google Scholar
Bylemans, J., Gleeson, D. M., Duncan, R. P., Hardy, C. M. & Furlan, E. M. A performance evaluation of targeted eDNA and eDNA metabarcoding analyses for freshwater fishes. Environ. DNA 1, 402–414 (2019).
Chin, A. T. et al. Beta diversity changes in estuarine fish communities due to environmental change. Mar. Ecol. Prog. Ser. 603, 161–173 (2018).
Google Scholar
Sloterdijk, H. et al. Composition and structure of the larval fish community related to environmental parameters in a tropical estuary impacted by climate change. Estuar. Coast. Shelf Sci. 197, 10–26 (2017).
Google Scholar
Malaysian Meteorological Department. Tinjauan Cuaca bagi Tempoh November 2017 hingga April 2018. National Climate Centre: Ministry of Science, Technology and Innovation. Retrieved on February 1st, 2018, from https://www.met.gov.my/iklim/ramalanbermusim/ (2017).
Leray, M. et al. 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, 34 (2013).
Google Scholar
Geller, J., Meyer, C., Parker, M. & Hawk, H. Redesign of PCR primers for mitochondrial cytochrome c oxidase subunit I for marine invertebrates and application in all-taxa biotic surveys. Mol. Ecol. Resour. 13, 851–861 (2013).
Google Scholar
Illumina. 16S Metagenomic Sequencing Library Preparation. https://support.illumina.com/documents/documentation/chemistry_documentation/16s/16s-metagenomic-library-prep-guide-15044223-b.pdf 1–28 (2013).
Andrews, S. FastQC: A Quality Control Tool for High Throughput Sequence Data. (Babraham Bioinformatics (Babraham Institute, 2010).
Ewels, P., Magnusson, M., Lundin, S. & Käller, M. MultiQC: Summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32, 3047–3048 (2016).
Google Scholar
Edgar, R. C. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998 (2013).
Google Scholar
Andruszkiewicz, E. A. et al. Biomonitoring of marine vertebrates in Monterey Bay using eDNA metabarcoding. PLoS ONE 12, e0176343 (2017).
Google Scholar
Goldberg, C. S. et al. Critical considerations for the application of environmental DNA methods to detect aquatic species. Methods Ecol. Evol. 7, 1299–1307 (2016).
Fricke, R., Eschmeyer, W. N. & Van der Laan, R. Eschmeyer’s Catalog of Fishes: Genera, species, references. http://www.calacademy.org/scientists/catalog-of-fishes-family-group-names/ (2021).
Ebert, D. A. & Fowler, S. Sharks of the World (Princeton University Press, 2013).
R Core Team. RStudio: integrated development for R. RStudio, Inc., Boston, MA URL http://www.rstudio.com42, 14 (2015).
McMurdie, P. J. & Holmes, S. Phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).
Google Scholar
Oksanen, J. et al. Package ‘vegan’. Commun. Ecol. Pack. 2, 1–295 (2013).
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2016).
Google Scholar
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