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2026 Vol.68, Issue 4 Preview Page
Predicting Fish Occurrence Probability in the Nakdong River Basin Using Species Distribution Models

종분포모델을 활용한 낙동강 유역의 어류 서식 확률 예측

Soyoung Wooa
,
Wonjin Kimb
,
Yongwon Kimc
,
Yonggwan Leed
,
Seongjoon Kime†
우 소영a
,
김 원진b
,
김 용원c
,
이 용관d
,
김 성준e†
aPostdoctoral Researcher, Department of Hydro Science and Engineering Research, Korea Institute of Civil Engineering and Building Technology
bPostdoctoral Researcher, Department of Hydro Science and Engineering Research, Korea Institute of Civil Engineering and Building Technology
cPh.D Student, Department of Civil, Environmental and Engineering, Graduate School, Konkuk University
dAssistant Professor, Asia Infrastructure Research Center, Konkuk University
eProfessor, Division of Civil and Environmental Engineering, College of Engineering, Konkuk University
† Corresponding author Tel.: +82-2-444-0186 E-mail: kimsj@konkuk.ac.kr
2026. pp. 61-73
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Abstract

In this study, Species Distribution Models (SDMs) were developed to predict the occurrence probability of six representative fish species in the Nakdong River Basin. Species occurrence data were obtained from biomonitoring survey, and environmental variables were constructed using hydrological and water quality data generated by the Soil and Water Assessment Tool (SWAT), considering not only basin characteristics but also various physical and chemical riverine conditions such as flow rate and water quality. The occurrence probability of each fish species was predicted by SDM based on Random Forest algorithm. The SDMs showed high predictive accuracy with values exceeding 0.899, and differences in occurrence probability of each species were observed depending on stream order and habitat preference. Furthermore, response curve showed the influence of environmental variable on species occurrence. These results represent an integrated analysis of factors affecting fish distribution across multiple spatial scales, from the watershed to individual stream reaches. This study provides a scientific foundation for conservation and restoration strategies in the Nakdong River Basin by applying SDMs to freshwater fish and identifying key environmental determinants of habitat suitability.

Keywords
Species distribution model
fish habitats
occurrence probability
environmental variables
response curve
References

REFERENCES

1
K. G. An and S. J. Lee, Korean Journal of Ecology and Environment, Ecological health assessments, conservation and management in Korea using fish MultiMetric model, 51(1); 86-95, (in Korean) (2018)10.11614/ksl.2018.51.1.086
2
J. G. Arnold, J. R. Williams, R. Srinivasan and K. W. King, SWAT manual, Texas. USDA Agricultural Research Service and Blackland Research Center. (1996)
3
L. Breiman, Machine Learning, Random forests, 45; 5-32 (2001)10.1023/a:1010933404324
4
D. Dudgeon, A. H. Arthington, M. O. Gessner, Z. I. Kawabata, D. J. Knowler, C. Lévêque and C. A. Sullivan, Biological Reviews, Freshwater biodiversity: Importance, threats, status and conservation challenges, 81(2); 163-182 (2006)10.1017/s1464793105006950
5
J. Elith and J. R. Leathwick, Annual Review of Ecology, Evolution, and Systematics, Species distribution models: Ecological explanation and prediction across space and time, 40; 677-697 (2009)10.1146/annurev.ecolsys.110308.120159
6
Z. Jin, D. Lee, E. Kim, J. Choi and Y. Jeon, Journal of Environmental Impact Assessment, Mapping mammalian species richness using a machine learning algorithm, 33(2); 53-63, (in Korean) (2024)10.14249/eia.2024.33.2.53
7
J. P. G. Jones, F. B. Andriahajaina and N. J. Hockley, Conservation Biology, A multidisciplinary approach to assessing the sustainability of freshwater crayfish harvesting in Madagascar, 19; 1863-1871 (2005)10.1111/j.1523-1739.2005.00269.x-i1
8
S. W. Jung, Y. H. Kim, J. H. Lee, D. G. Kim, M. K. Kim and H. M. Kim, Korean Journal of Environment and Ecology, Biodiversity changes and community characteristics of benthic macroinvertebrates in weir section of the Nakdong River, South Korea, 36(2); 150-164, (in Korean) (2022)10.13047/kjee.2022.36.2.150
9
J. R. Karr, Fisheries, Assessment of biotic integrity using fish communities, 6(6); 21-27 (1981)10.1577/1548-8446(1981)006<0021:aobiuf>2.0.co;2
10
D. J. Kim, Y. S. Kwon, N. Y. Han and D. H. Lee, Korean Journal of Environmental Biology, Trends identification of species distribution modeling study in Korea using text-mining technique, 41(4); 413-426, (in Korean) (2023)10.11626/KJEB.2023.41.4.413
11
T. G. Kim, D. Yang, Y. Cho, K. H. Song and J. G. Oh, Korean Journal of Ecology and Environment, Habitat distribution change prediction of Asiatic black bears (Ursus thibetanus) using Maxent modeling approach, 49(3); 197-207, (in Korean) (2016)10.11614/ksl.2016.49.3.197
12
X. Li and Y. Wang, Integrative Zoology, Applying various algorithms for species distribution modelling, 8(2); 124-135 (2013)10.1111/1749-4877.12000
13
C. D. McMahan, C. E. Fuentes-Montejo, L. Ginger, J. C. Carrasco, P. Chakrabarty and W. A. Matamoros, Scientific Reports, Climate change models predict decreases in the range of a microendemic freshwater fish in Honduras, 10; 12693 (2020)10.1038/s41598-020-69579-7
14
Millennium Ecosystem Assessment (MEA), Ecosystems and human well-being, Vol. 5, Washington, DC. Island Press. (2005)
15
National Institute of Environmental Research (NIER), Stream/River ecosystem survey and health assessment (Ⅷ); 693, Ministry of Environment/National Institute of Environmental Research. (2015)
16
J. Oh, S. Y. Kwon, A. R. Han and S. Hong, Ecology and Resilient Infrastructure, Application of big data-based feature selection methods for establishment of suitable species distribution models, 11(4); 229-243, (in Korean) (2024)10.17820/eri.2024.11.4.229
17
S. J. Phillips, R. P. Anderson and R. E. Schapire, Ecological Modelling, Maximum entropy modeling of species geographic distributions, 190(3–4); 231-259 (2006)10.1016/j.ecolmodel.2005.03.026
18
M. S. Shin, C. Seo, M. Lee, J. Y. Kim, J. Y. Jeon, P. Adhikari and S. B. Hong, Journal of Environmental Impact Assessment, Prediction of potential species richness of plants adaptable to climate change in the Korean Peninsula, 27(6); 562-581, (in Korean) (2018)10.14249/EIA.2018.27.6.562
19
A. N. Strahler, Eos, Transactions American Geophysical Union, Quantitative analysis of watershed geomorphology, 38(6); 913-920 (1957)10.1029/tr038i006p00913
Information
  • Publisher :The Korean Society of Agricultural Engineers
  • Publisher(Ko) :한국농공학회
  • Journal Title :Journal of Korean Society of Agricultural Engineers
  • Journal Title(Ko) :한국농공학회논문집
  • Volume : 68
  • No :4
  • Pages :61-73
  • Received Date : 2025-10-27
  • Revised Date : 2026-03-16
  • Accepted Date : 2026-05-06
  • DOI :https://doi.org/10.5389/KSAE.2026.68.4.061
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