Browse > Article
http://dx.doi.org/10.11614/KSL.2022.55.1.060

Ecological Network on Benthic Diatom in Estuary Environment by Bayesian Belief Network Modelling  

Kim, Keonhee (Zion E&S Co. Ltd., Research Institute)
Park, Chaehong (Human and Eco- Care Center, Sanghuh College of Life Sciences, Konkuk University)
Kim, Seung-hee (Department of Marine Sciences and Convergent Technology, Hanyang University)
Won, Doo-Hee (Doohee Institute of Ecological Research, Korea Ecosystem Service Inc.)
Lee, Kyung-Lak (Water Environmental Engineering Research Division, National Institute of Environmental Research)
Jeon, Jiyoung (Water Environmental Engineering Research Division, National Institute of Environmental Research)
Publication Information
Korean Journal of Ecology and Environment / v.55, no.1, 2022 , pp. 60-75 More about this Journal
Abstract
The Bayesian algorithm model is a model algorithm that calculates probabilities based on input data and is mainly used for complex disasters, water quality management, the ecological structure between living things or living-non-living factors. In this study, we analyzed the main factors affected Korean Estuary Trophic Diatom Index (KETDI) change based on the Bayesian network analysis using the diatom community and physicochemical factors in the domestic estuarine aquatic ecosystem. For Bayesian analysis, estuarine diatom habitat data and estuarine aquatic diatom health (2008~2019) data were used. Data were classified into habitat, physical, chemical, and biological factors. Each data was input to the Bayesian network model (GeNIE model) and performed estuary aquatic network analysis along with the nationwide and each coast. From 2008 to 2019, a total of 625 taxa of diatoms were identified, consisting of 2 orders, 5 suborders, 18 families, 141 genera, 595 species, 29 varieties, and 1 species. Nitzschia inconspicua had the highest cumulative cell density, followed by Nitzschia palea, Pseudostaurosira elliptica and Achnanthidium minutissimum. As a result of analyzing the ecological network of diatom health assessment in the estuary ecosystem using the Bayesian network model, the biological factor was the most sensitive factor influencing the health assessment score was. In contrast, the habitat and physicochemical factors had relatively low sensitivity. The most sensitive taxa of diatoms to the assessment of estuarine aquatic health were Nitzschia inconspicua, N. fonticola, Achnanthes convergens, and Pseudostaurosira elliptica. In addition, the ratio of industrial area and cattle shed near the habitat was sensitively linked to the health assessment. The major taxa sensitive to diatom health evaluation differed according to coast. Bayesian network analysis was useful to identify major variables including diatom taxa affecting aquatic health even in complex ecological structures such as estuary ecosystems. In addition, it is possible to identify the restoration target accurately when restoring the consequently damaged estuary aquatic ecosystem.
Keywords
bayesian belief network; estuary; diatom; ecological network; estuary trophic diatom index;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 McCormick, P.V. and R.J. Stevenson. 1998. Periphyton as a tool for ecological assessment and management in the Florida Everglades. Journal of Phycology 34(5): 726-733.   DOI
2 Hwang, S.-J., N.-Y. Kim, D.H. Won, K.K. An, J.K. Lee and C.S. Kim. 2006. Biological assessment of water quality by using epilithic diatoms in major river systems (Geum, Youngsan, Seomjin River), Korea. Journal of Korean Society on Water Environment 22(5): 784-795.
3 Suh, S.W., H.Y. Lee and S.C. Yoo. 2010. Simulation of Water Quality Changes in the Saemangeum Reservoir Induced by Dike Completion. Journal of Korean Society of Coastal and Ocean Engineers 22(4): 258-271.
4 Taylor, J.C., W.R. Harding and C. Archibald. 2007. An illustrated guide to some common diatom species from South Africa, Water Research Commission Pretoria.
5 Wang, P., H. Shen and P. Xie. 2012. Can hydrodynamics change phosphorus strategies of diatoms?-nutrient levels and diatom blooms in lotic and lentic ecosystems. Microbial ecology 63(2): 369-382.   DOI
6 Westen, C.-J.v. and R.J. Scheele. 1996. Characteristics of estuaries, Springer.
7 WFD. 2014. UKTAG River Assessment Method Macrophytes and Phytobenthos, Water Framework Directive.
8 Yang, J.-S., Y.-T. Kim and K.-W. Choi. 2004. The monitoring of biogeochemical interactions between sediment and water: a Mesocosm Study. Journal of the Korean Society of Oceanography 39(1): 107-118.
9 Yoo, J., J.-H. Ryu, J.-H. Lee and T.-W. Kim. 2021. Probabilistic assessment of causal relationship between drought and water quality management in the Nakdong River basin using the Bayesian network model. Journal of Korea Water Resources Association 54(10): 769-777.   DOI
10 Zheng, L., C. Chen and F.Y. Zhang. 2004. Development of water quality model in the Satilla River Estuary, Georgia. Ecological Modelling 178(3-4): 457-482.   DOI
11 Noh, B.-H. 2011. Development of estuarine wetland restoration and management program in Korea, Korea Environment Institute.
12 Nam, K.-H. 2014. study on the compound-disaster risk assessment by utilizing the bayesian network, Graduate School, Inje University.
13 NIER. 1992. Standard methods for the examiantion of environmental pollution, Ministry of Environment.
14 NIER. 2019. Guidelines for aquatic ecosystem survey and health assessment methods (estuary), National Institute of Environmental Research.
15 Kobayasi, H., M. Idei, S. Mayama, T. Nagumo and K. Osada. 2006. H. Kobayasi's Atlas of Japanese Diatoms Based on Electron Microscopy. Uchidarokakuho, Tokyo, Japan, Japanese.
16 Frey, J.W., A.H. Bell, J.A. Hambrook Berkman and D.L. Lorenz. 2011. Assessment of nutrient enrichment by use of algal-, invertebrate-, and fish-community attributes in wadeable streams in ecoregions surrounding the Great Lakes, United States Geological Survery.
17 Kim, B. and S. Jung. 2007. Turbidity Problems in Streams and Reservoirs in Korea and Control Strategie. Nature Conservation 139: 1-7.
18 Kim, H.-K. 2022. Biological Water Quality Assessment Using the Epilithic Diatoms in Korean Estuary, Hanyang University.
19 Allan, J.D., M.M. Castillo and K.A. Capps. 2020. Stream ecology: structure and function of running waters, Springer Nature.
20 An, S., S. Lee and J. Choi. 2011. Classifications of Ecological Districts for Estuarine Ecosystem Restoration; Examples of Goseong Bay Estuaries, South sea, Korea. Journal of the Korean Society of Oceanography 16(2): 70-80.
21 APHA. 2005. Standard methods for the examination of water and wastewater, Federation, Water Environmental Aph Association.
22 Blinn, D.W. and P.C. Bailey. 2001. Land-use influence on stream water quality and diatom communities in Victoria, Australia: a response to secondary salinization. Hydrobiologia 466(1): 231-244.   DOI
23 Choi, J.-Y. 2006. Research and Research on Development of Comprehensive Water Environment Assessment Method (III) Korean Environment Institute National Institute of Environmental.
24 Noh, S., M. Byeon, M. Kim and J. Lee. 2009. Development of Biological Criteria for Water Quality Assessment using Benthic Diatoms. Journal of Korean Society on Water Quality 25(6): 879-885.
25 BERTRAND, J. 1992. Mouvement des diatomees. II: synthese des mouvements. Cryptogamie. Algologie 13(1): 49-71.
26 Besse-Lototskaya, A., P.F. Verdonschot, M. Coste and B. Van de Vijver. 2011. Evaluation of European diatom trophic indices. Ecological Indicators 11(2): 456-467.   DOI
27 Castillo, E., J.M. Gutierrez and A.S. Hadi. 2012. Expert systems and probabilistic network models, Springer Science & Business Media.
28 Krammer, K. 1985. Naviculaceae. Bibliotheca Diatomologica 9: 1-230.
29 Hwang, J.-S., Y.-K. Park and C.-H. Won. 2012. Runoff Characteristics of Non-Point Source Pollution in Lower Reaches of Livestock Area. Journal of Korean Society of Environmental Engineers 34(8): 557-565.   DOI
30 Kim, M. 2019. Analysis of the health status of the aquatic ecosystem in Chungbuk and environmental factors in the damaged section, Chungbuk Research Institute, Chungbuk Research Institute.
31 Wacker, A., V. Marzetz and E. Spijkerman. 2015. Interspecific competition in phytoplankton drives the availability of essential mineral and biochemical nutrients. Ecology 96(9): 2467-2477.   DOI
32 Shen, R., H. Ren, P. Yu, Q. You, W. Pang and Q. Wang. 2018. Benthic diatoms of the Ying River (Huaihe River Basin, China) and their application in water trophic status assessment. Water 10(8): 1013.   DOI
33 Park, K.-W., Y.-S. Kim, J.-W. Park, K.-H. Jeune and M.-K. Kim. 2011. Seasonal Variations of Water Environments and Benthic Diatom Communities in Streams across Byeonsan-Bando and Seonunsan Parklands in Jeollabukdo, Korea. Korean Journal of Limnology 44(2): 239-251.
34 Park, S.-J., D.-K. Lee, D.-K. Lee and D.-K. Lee. 2014. Risk Assessment of Potential Inundation Due to Sea Level Rise Using Bayesian Network. Journal of Korea Planning Association 49(2): 347-358.   DOI
35 Rimet, F. 2012. Diatoms: an ecoregional indicator of nutrients, organic matter and micropolluants pollution, Universit? de Grenoble.
36 Urrea Clos, G. 2010. Distribution of diatom communities in agricultural and mining watersheds of Southwest Spain, Universitat de Girona.
37 Krammer, K. and H. Lange-Bertalot. 1986. Naviculaceae: neue und wenig bekannte Taxa neue Kombinationen und Synonyme sowie Bemerkungen zu einigen Gattugen. Bibliotheca Diatomologica, Koeltz Scientific Books Berlin.
38 Kim, B.-H., D.-H. Won and Y.-J. Kim. 2012. Spring Bloom of Skeletonema costatum and Lake Trophic Status in the Hwajinpo Lagoon, South Korea. Korean Journal of Limonology 45(3): 329-339.
39 Shin, Y.-S. and B.-B. Yoon. 2011. Change in taxonomic composition of phytoplankton and environmental factors after construction of dike in Yeongsan River estuary. Korean Journal of Environmental Biology 29(3): 212-224.
40 Stancheva, R., N. Kristan, W. Kristan and R.G. Sheath. 2020. Diatom genus Planothidium(Bacillariophyta) from streams and rivers in California, USA: diversity, distribution and autecology. Phytotaxa 470(1): 1-30~31-30.   DOI
41 Won, D.H. 2012. A study on the selection of an estuary for pilot restoration to improve the health of the aquatic ecosystem, Ministry of Environment, Doohee Ecology Research center.
42 Yoo, K. 2007. Changes in topography after the construction of the estuary in Koreas estuary, Kyujanggak Institute for Korean studies, National University of Seoul.
43 Rho, P. and C.-H. Lee. 2014. Spatial Distribution and Temporal Variation of Estuarine Wetlands by Estuary Type. Journal of the Korean Geographical Society 49(3): 321-338.
44 Manoylov, K.M. 2009. Intra-and interspecific competition for nutrients and light in diatom cultures. Journal of Freshwater Ecology 24(1): 145-157.   DOI
45 Watanabe, T., K. Asai, T. Ohtsuka, A. Tuji and A. Houki. 2005. Picture book and ecology of the freshwater diatoms. 784pp. Uchida Rokakuho, Tokyo.
46 Lane, C.M. 2005. The use of diatoms as biological indicators of water quality, and for environmental reconstruction, in south-east Tasmania, Australia, University of Tasmania.
47 Lee, K.-H., B.-H. Rho, H.-J. Cho and C.-H. Lee. 2011. Estuary Classification Based on the Characteristics of Geomorphological Features, Natural Habitat Distributions and Land Uses. Journal of the Korean Society of Oceanography 16(2): 53-69.
48 Lee, S.-W., G. Joo, G. Ahn and H.-Y. Lee. 2009. Aquatic Ecosystem Health Survey and Assessment, National Institute of Environmental Research, Ministry of Environment.
49 Liew, J., T. Jardine, R. Lim, J. Kwik, H. Tan, Z. Kho and D. Yeo. 2018. Bottom-up influences on tropical freshwater food web structure support the "environmental filtering" hypothesis. Limnology and Oceanography 63(5): 1877-1890.   DOI
50 Lim, R., J. Liew, J. Kwik and D. Yeo. 2018. Predicting food web responses to biomanipulation using Bayesian Belief Network: Assessment of accuracy and applicability using in-situ exclosure experiments. Ecological Modelling 384: 308-315.   DOI
51 MOE. 2017. Operation plan of water environment monitoring network, Ministry of Environment.
52 MOE. 2020. Aquatic ecosystem health survey statistical information report, Ministry of Environment.
53 Roubeix, V. and M. Coste. 2017. A case of close interspecific interactions between diatoms: selective attachment on a benthic motile species. Aquatic Microbial Ecology 80(1): 55-59.   DOI
54 Shim, Y. 2016. Legal Policy Problems for the Restoration and Sustainable Management of Estuary - Focused on the Law and Policy Case Study concerning the Estuary Restoration and Management in the U.S. -. Journal of Law and Politics Research 16(3): 373-406.   DOI
55 Champ, C.W. and D.K. Shepherd. 2007. Encyclopedia of statistics in quality and reliability.
56 Coste, M. and H. Ayphassorho. 1991. Etude de la qualite des eaux du bassin Artois-Picardie a Iaide des communautes de diatomees benthiques: application des indices diatomiques, irstea.
57 Kelly, M. and B.A. Whitton. 1995. The trophic diatom index: a new index for monitoring eutrophication in rivers. Journal of Applied Phycology 7(4): 433-444.   DOI
58 Ewe, S.M., E.E. Gaiser, D.L. Childers, D. Iwaniec, V.H. Rivera-Monroy and R.R. Twilley. 2006. Spatial and temporal patterns of aboveground net primary productivity (ANPP) along two freshwater-estuarine transects in the Florida Coastal Everglades. Hydrobiologia 569(1): 459-474.   DOI
59 Gaiser, E. 2009. Periphyton as an indicator of restoration in the Florida Everglades. Ecological Indicators 9(6): S37-S45.   DOI
60 Gleick, P. 2001. Safeguarding our water-making every drop count, beitberl.ac.il, Scientific American.
61 Lange-Bertalot, H. 2001. Navicula sensu stricto 10 genera separated from Navicula sensu lato Frustulia, Diatoms of Europe. Diatoms of the European Inland Waters and Comparable Habitats 2: 526.