Estimating Population Abundance Of Seahorse In Sebong Bay, Bintan Island

Supradianto Nugroho; Nur Fadhilah; Tri Nur Sujatmiko

doi:10.15578/jkpt.v6i1.11159

Estimating Population Abundance Of Seahorse In Sebong Bay, Bintan Island

Supradianto Nugroho, Nur Fadhilah, Tri Nur Sujatmiko

Abstract

The decline in seahorse populations in the wild due to high fishing activity and habitat degradation prompted the inclusion of all seahorse species in Appendix II of CITES (Convention on International Trade in Endangered Species of Wild Fauna and Flora) in 2002. By being included in Appendix II of CITES, data and information on the abundance of seahorse populations become crucial as the basis for determining the quota for fishing and trade. Estimating population abundance of seahorse requires knowledge of habitat area, which can be modeled using the MaxEnt (maximum entropty). In this study, an estimation of the abundance of seahorses was carried out in the waters of Sebong Bay, Bintan Island. MaxEnt modeling was implemented with data on seahorse presence locations and environmental parameter maps consisting of chlorophyll-a as primary productivity parameter, benthic habitat as habitat type parameter, and dissolved oxygen, salinity, and pH as physiological parameters. From this model, the value of the area of suitable habitat for seahorses is 54,6 ha, while the density of seahorse in this area is 60 ind/ha, so it can be determined that the abundance of seahorses in the Sebong Bay is 3.276 individuals. Therefore, seahorse population in Sebong Bay is critically endangered since it is below the number of individuals that required to prevent the loss of quantitative genetic variation in a species.

Keywords

Seahorse abundance; habitat suitability; MaxEnt; Sebong Bay

Full Text:

PDF

References

al Aswant, I. (2016). Analisis Perbandingan Metode Interpolasi untuk Pemetaan pH Air pada Sumur Bor di Kabupaten Aceh Besar Berbasis SIG [Skripsi]. Universitas Syiah Kuala.

BPSPL Padang. (2020). Laporan Monitoring Kuda Laut di Pulau Bintan.

Buma, W. G., & Lee, S. il. (2020). Evaluation of Sentinel-2 and Landsat 8 images for estimating Chlorophyll-a concentrations in Lake Chad, Africa. Remote Sensing, 12(15). https://doi.org/10.3390/RS12152437

Foster A N, S. J., & Vincent, D. A. C. J. (2004). Life history and ecology of seahorses: implications for conservation and management. Journal of Fish Biology, 65, 1–61. https://doi.org/10.1111/j.1095-8649.2004.00429.x

Frankham, R. (1995). Effective population size/adult population size ratios in wildlife: A review. Genetical Research, 66(2), 95–107. https://doi.org/10.1017/S0016672300034455

Giles, B. G., Ky, T. S., Hoang, D. H., & Vincent, A. C. J. (2006). The catch and trade of seahorses in Vietnam. Biodiversity and Conservation, 15(8), 2497–2513. https://doi.org/10.1007/s10531-005-2432-6

Hafizt, M., Iswari, M. Y., & Prayudha, B. (2017). Kajian Metode Klasifikasi Citra Landsat-8 untuk Pemetaan Habitat Bentik di Kepulauan Padaido, Papua. Oseanologi Dan Limnologi Di Indonesia, 2(1), 1–13.

Jamieson, I. G., & Allendorf, F. W. (2012). How does the 50/500 rule apply to MVPs? Trends in Ecology and Evolution, 27(10), 578–584. https://doi.org/10.1016/j.tree.2012.07.001

Latifiana, K. (2018). Pemetaan Habitat Potensial Herpetofauna pada Daerah Terdampak Erupsi Gunung Merapi 2010. Seminar Nasional Geomatika, 497–510.

Lourie, S. A., Pollom, R. A., & Foster, S. J. (2016). A global revision of the Seahorses Hippocampus Rafinesque 1810 (Actinopterygii: Syngnathiformes): Taxonomy and biogeography with recommendations for further research. Zootaxa, 4146(1), 1–66. https://doi.org/10.11646/zootaxa.4146.1.1

Marini, Y., Emiyati, Hawariyah, S., & Hartuti, M. (2014). Perbandingan Metode Klasifikasi Supervised Maximum Likelihood dengan Klasifikasi Berbasis Objek untuk Inventarisasi Lahan Tambak di Kabupaten Maros. Seminar Nasional Penginderaan Jauh, 505–516.

Merow, C., Smith, M. J., & Silander, J. A. (2013). A practical guide to MaxEnt for modeling species’ distributions: What it does, and why inputs and settings matter. Ecography, 36(10), 1058–1069. https://doi.org/10.1111/j.1600-0587.2013.07872.x

Perera, N., Dahanayaka, D. D. G. L., & Udagedara, S. (2017). Habitat Preference and Population Structure of Two Data Deficient Seahorse (Syngnathidae) Species. OUSL Journal, 12(2), 75. https://doi.org/10.4038/ouslj.v12i2.7408

Phillips, S. J. (2017). A Brief Tutorial on Maxent (3.2.0). AT&T Labs-Research. http://biodiversityinformatics.amnh.org/open_source/maxent/.

Phillips, S. J., Anderson, R. P., Dudík, M., Schapire, R. E., & Blair, M. E. (2017). Opening the black box: an open-source release of Maxent. Ecography, 40(7), 887–893. https://doi.org/10.1111/ecog.03049

Pi, D. V. (2016). Applying species distribution models in conservation biology [Programa de Doctorat en Biodiversitat]. Universitat de Barcelona.

Putri, M. R. A., Suryandari, A., & Haryadi, J. (2019). Sumberdaya Kuda Laut (Hippocampus spp.) di Perairan Pulau Bintan, Teluk Lampung dan Pulau Tanakeke. Oseanologi Dan Limnologi Di Indonesia, 4(1), 27. https://doi.org/10.14203/oldi.2019.v4i1.194

Sampurno, R. M., & Thoriq, A. (2016). Klasifikasi Tutupan Lahan Menggunakan Citra Landsat 8 Operational Land Imager (OLI) di Kabupaten Sumedang. Teknotan, 10(2), 61–70.

Saraswati, S. A., & Pebriani, D. A. A. (2016). Monitoring Populasi Kuda Laut di Perairan Pantai Padang Bai, Karangasem Bali. Samakia, 7(2), 100–105.

Vincent, A. C. J., Foster, S. J., & Koldewey, H. J. (2011). Conservation and management of seahorses and other Syngnathidae. Journal of Fish Biology, 78(6), 1681–1724. https://doi.org/10.1111/j.1095-8649.2011.03003.x

Windyoningrum, A. (2013). Estimating Habitat Loss and Identifying Refugee Area for Javan Langur (Tracyphitecus auratus) as Impact of Merapi Eruption 2010 [Master Thesis]. Universitas Gadjah Mada.

Zeng, Q., Zhang, Y., Sun, G., Duo, H., Wen, L., & Lei, G. (2015). Using species distribution model to estimate the wintering population size of the endangered scaly-sided merganser in China. PLoS ONE, 10(2). https://doi.org/10.1371/journal.pone.0117307

Zhang, X. (2019). Conservation Prioritization and Ecology of Data-poor Marine Species under Human Pressures [Doctoral Thesis]. The University of British Columbia.

Zhang, X., & Vincent, A. C. J. (2018). Predicting distributions, habitat preferences and associated conservation implications for a genus of rare fishes, seahorses (Hippocampus spp.). Diversity and Distributions, 24(7), 1005–1017. https://doi.org/10.1111/ddi.12741

DOI: http://dx.doi.org/10.15578/jkpt.v6i1.11159