Markov Chain and  Cluster Model of  Green Algae Phytoplankton (Chlorophyceae) Diversity and Spatial Distribution Pattern along Stream, Water Quality, and Land Use Gradients in Krukut River, Jakarta City

Andriwibowo Andriwibowo; Adi  Basukriadi; Erwin  Nurdin; Amanda Zahra  Djuanda; Elizabeth  Adeline; Zeadora Abbya  Trisya

doi:10.5614/3bio.2022.4.2.2

Authors

Andriwibowo Andriwibowo Community Ecology and Environmental Biology, Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Indonesia https://orcid.org/0000-0001-7787-5735
Adi Basukriadi Community Ecology and Environmental Biology, Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Indonesia
Erwin Nurdin Community Ecology and Environmental Biology, Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Indonesia
Amanda Zahra Djuanda Community Ecology and Environmental Biology, Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Indonesia
Elizabeth Adeline Community Ecology and Environmental Biology, Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Indonesia
Zeadora Abbya Trisya Community Ecology and Environmental Biology, Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Indonesia https://orcid.org/0000-0001-9998-6962

DOI:

https://doi.org/10.5614/3bio.2022.4.2.2

Keywords:

distribution, Chlorophyceae, cluster, Markov chain, river

Abstract

Green algae phytoplankton (Chlorophyceae) have a wide aquatic distribution, including saltwater and freshwater environments. Compared to the ones living in saltwater, green algae diversity in freshwater ecosystems in rivers is influenced by stream gradients, water quality, and land uses. Meanwhile, in Jakarta, 17 rivers have the potential to provide a habitat for green algae communities. Due to anthropogenic activities, river streams have been affected by influences that may affect the water quality and green algae community along stream gradients. One of the critical rivers in Jakarta is the Krukut river, which has the most extended stream spanning over 40 km and downstream in Jakarta bay. This study aims to model the diversity and distribution pattern of green algae in the Krukut river from its upstream segment in Jakarta city, surrounded by settlements, to the downstream segments in Jakarta bay. The distribution model uses the Cluster Analysis and Markov Chain Model to elaborate the probabilities of green algae phytoplankton distribution in downstream, midstream, and upstream segments of the Krukut river. The results show that 7 species of Chlorophyceae have been recorded in the Krukut river. All species had a high likelihood of being found downstream, particularly Cosmarium sp., Eudorina sp., Spyrogyra sp., and Volvox sp. Regarding distribution, all phytoplankton species have a high probability (4%?31%) and tendency to be distributed from upstream and midstream to downstream rather than from downstream to midstream and upstream, with probability ranges of 2%?27%. The probability and tendency of phytoplankton distribution towards downstream directions avoiding upstream were related to the deteriorating water quality in the upstream, characterized by high turbidity, low dissolved oxygen, and more acidic water.

References

Domingues RB, Galv H. Phytoplankton and environmental variability in a dam regulated temperate estuary. Hydrobiologia. 2007. [cited 2021 November 2]; 586: 117?134. http://doi.org/10.1007/s10750-006-0567-4.

Khaqiqoh N, Purnomo PW, Hendrarto B. Pattern of phytoplankton communities change in the Banjir Kanal Barat River Semarang based on tide level. Diponegoro Journal Of Maquares. 2014. [cited 2021 November 2]; 3(2): 92-101.

Rosarina D, Rosanti D. Struktur komunitas plankton di Sungai Cisadane Kota Tangerang. Seminar Nasional Sains dan Teknologi Terapan. 2018. [cited 2021 November 2].

Hambali, R. Analisis hubungan bentuk das dengan debit banjir studi kasus: DAS Kali Pesanggrahan, DAS Kali Krukut, dan DAS Kali Cipinang. Faktor Exacta. 2017. [cited 2021 November 2]; 10(4). http://doi.org/10.30998/faktorexacta.v10i4.2244.

Pambudi A, Priambodo T, Noriko N, Basma. Keanekaragaman Fitoplankton Sungai Ciliwung Pasca Kegiatan Bersih Ciliwung. Jurnal Al-Azhar Indonesia Seri Sains Dan Teknologi. 2017. [cited 2021 November 2]; 3. 204. http://doi.org/10.36722/sst.v3i4.235.

Sirait M, Rahmatia F, Pattulloh P.. Comparison of diversity index and dominant index of phytoplankton at Ciliwung River Jakarta. Jurnal Kelautan: Indonesian Journal of Marine Science and Technology. 2018. [cited 2021 November 2]; 11. 75. http://doi.org/10.21107/jk.v11i1.3338.

Sidabutar T. The abundance of phytoplankton and its relationship to the N/P ratio in Jakarta Bay, Indonesia. Biodiversitas, Journal of Biological Diversity. 2016. [cited 2021 November 9]; 17: 673-678. http://doi.org/10.13057/biodiv/d170241.

Kalita J, Bhuyan, S.I., Das, R. An assessment of Green algae (Chlorophyceae) diversity in different habitats of RiBhoi, Meghalaya. The Pharma Innovation Journal. 2015. [cited 2021 November 2]; 4(2): 50-55.

Yamaji IE. Illustration of the Marine Plankton of Japan. Houkusho.Osaka, Japan.1966.

Omura T, Iwataki M, Valeriano B, Haruyoshi T, Fukuyo Y. Marine phytoplankton of the Western Pacific. Nippon Suisan Gakkaishi (Japanese Edition). 2013. [cited 2021 November 9]; 79: 486-488. http://doi.org/10.2331/suisan.79.486.

Lusher A, Tirelli V, O'Connor I, Officer R. Microplastics in Arctic polar waters: The first reported values of particles in surface and sub-surface samples. Scientific Reports. 2015. [cited 2021 November 2].

Su L, Sharp S, Pettigrove VJ, Craig NJ, Nan B, Du F, Shi H. Superimposed microplastic pollution in a coastal metropolis. Water Research. 2020. [cited 2021 November 9]; 168.

Free CM, Jensen OP, Mason SA, Eriksen M, Williamson NJ, Boldgiv B. High-levels of microplastic pollution in a large, remote, mountain lake. Marine Pollution Bulletin. 2014. [cited 2021 November 9]; 85(1): 156-163.

Tallei T, Sumarto S, Tallei V. Wild birds diversity in Mount Tumpa Forest Park, North Sulawesi, Indonesia. Bioscience Research. 2018. [cited 2021 November 9]; 15: 443-452.

Nijssen D, Rousseau R, Hecke PV. The Lorenz curve: a graphical representation of evenness. Coenoses. 1998. [cited 2021 November 9]; 13(1): 33?38.

Rousseau R, Van Hecke P, NIjssen D. The relationship between diversity profiles, evenness and species richness based on partial ordering. Environmental and Ecological Statistics. 1999. [cited 2021 November 9]; 6: 211?223. https://doi.org/10.1023/A:1009626406418.

Grubesic T, Murray A. Detecting hot spots using cluster analysis and GIS. 2001.

Aksoy E. Clustering with GIS: an attempt to classify Turkish District data. 2006.

Chan, K., Lenard, C., Mills, T. An introduction to Markov Chains. 2012. [cited 2021 December 23]. https://doi.org/10.13140/2.1.1833.8248.

Fukaya, K., Royle, J.A. Markov models for community dynamics allowing for observation error. Ecology. 2013. [cited 2021 December 23]; 94(12): 670?2677.

Hill, M., Witman, J., Caswell, H. Markov Chain Analysis of Succession in a Rocky Subtidal Community. The American Naturalist. 2004. [cited 2021 December 23]; 164: E46-61. https://doi.org/10.1086/422340.

Yudo S. Kondisi kualitas air Sungai Ciliwung di wilayah DKI Jakarta ditinjau dari paramater organik, amoniak,fosfat, deterjen dan bakteri coli. JAI. 2010. [cited 2021 December 23]; 6(1): 34-42.

Yudo S, Said N. Status kualitas air sungai Ciliwung di wilayah DKI Jakarta studi kasus : pemasangan stasiun online monitoring kualitas air di segmen Kelapa Dua ? Masjid Istiqlal. Jurnal Teknologi Lingkungan. 2018. [cited 2021 December 23]; 19. http://doi.org/10.29122/jtl.v19i1.2243.

Hendrawan D. Kualitas air sungai dan situ di DKI Jakarta. Seri Teknologi (Technology Series). 2010. [cited 2021 December 23]; 9(1). http://dx.doi.org/10.7454/mst.v9i1.315.

Anggeraeni RW, Rachma AJ, Ustati RT, Astuti IAD. Analisis kualitas air sungai Ciliwung ditinjau dari parameter pH dan kekeruhan air berbasis Logger Pro. Prosiding Seminar Nasional Sains. 2020. [cited 2021 December 23]; 1(1): 29-38.

Khalila S, Mahnashi M, Hussain M, Zafar N. Exploration and determination of algal role as Bioindicator to evaluate water quality ? Probing fresh water algae. Saudi Journal of Biological Sciences. 2021. [cited 2022 January 18]; 28(10): 5728-5737.

Huang C, Wang X, Yang H, Li Y, Wang Y, Chen X, Xu L. Satellite data regarding the eutrophication response to human activities in the plateau lake Dianchi in China from 1974 to 2009. Sci. Total Environ. 2014. [cited 2022 January 18]; 485:1-11.

Guedes A, Amaro H, Dias Pereira R, Malcata F. Effects of temperature and ph on growth and antioxidant content of the microalga Scenedesmus obliquus. Biotechnology Progress. 2011. [cited 2022 February 23]; 27: 1218-24. http://doi.org/10.1002/btpr.649.

Mofeed J. Effect of different concentrations of polluted water on growth and physiological parameters of two green algae Scenedesmus obliquus and Cosmarium leave. 2015.

Halder, N. Two algal species of Volvox L. with their taxonomy and ecology from West Bengal, India. Songklanakarin J. Sci. Technol. 2016. [cited 2022 February 23]; 38(4): 435-437.

Wang X, Zhang Y, Li C, Huang X, Li F, Wang X, Li G. Allelopathic effect of Oocystis borgei culture on Microcystis aeruginosa. Environ. Technol. 2020. [cited 2022 February 23]; 1-10.

Liu M, Huang XH, Li CL, Gu B. Study on the uptake of dissolved nitrogen by Oocystis borgei in prawn (Litopenaeus vannamei) aquaculture ponds and establishment of uptake model. Aquac. Int. 2020. [cited 2022 February 23]; 28: 1445-1458.

Na H, Jo S, Do J, Kim I, Yoon H. Production of algal biomass production and high-value compounds mediated by the interaction of microalgal Oocystis sp. KNUA044 and bacterium Sphingomonas KNU100. Journal of Microbiology and Biotechnology. 2020. [cited 2022 February 23]; 31(3): 387-397. http://doi.org/10.4014/jmb.2009.09055.

Newman J, Anderson NJ, Bennion H, Bowes MJ, Carvalho L. Eutrophication in rivers: an ecological perspective. 2005. [cited 2022 March 1]. http://doi.org/10.13140/2.1.3711.5208.

Yang X, Wu X, Hao H, He Z. Mechanisms and Assessment of Water Eutrophication. Journal of ZhejiangUniversity. Science. 2008. [cited 2022 March 1]; 9: 197-209. http://doi.org/10.1631/jzus.B0710626.

Liu M, Huang X, Zhang R, Li C, Gu B. Uptake of urea nitrogen by Oocystis borgei in prawn (Litopenaeus vannamei) aquaculture ponds. Bulletin of Environmental Contamination and Toxicology. 2018. [cited 2022 March 1]; 101. http://doi.org/10.1007/s00128-018-2450-1.

Liu M, Huang X, Li C, Gu B. Study on the uptake of dissolved nitrogen by Oocystis borgei in prawn (Litopenaeus vannamei) aquaculture ponds and establishment of uptake model. Aquaculture International. 2020. [cited 2022 March 1]; 28. http://doi.org/10.1007/s10499-020-00534-z.