World's Best Scientists 2026 revealed!
Young-Seuk Park

Young-Seuk Park

Award Badge
Ecology and Evolution
Korea
2026

D-Index & Metrics

Ecology and Evolution

D-Index
44
Citations
7305
World Ranking
5082
National Ranking
3

Young-Seuk Park publication distribution in Ecology and Evolution in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Ecology and Evolution in 2026. The highlighted bar marks where Young-Seuk Park sits on this spectrum.

37–41 publications: 2 scientists 42–46 publications: 9 scientists 47–51 publications: 10 scientists 52–56 publications: 31 scientists 57–61 publications: 56 scientists 62–66 publications: 91 scientists 67–71 publications: 92 scientists 72–76 publications: 127 scientists 77–81 publications: 173 scientists 82–86 publications: 236 scientists 87–91 publications: 227 scientists 92–96 publications: 240 scientists 97–101 publications: 333 scientists 102–106 publications: 280 scientists 107–111 publications: 300 scientists 112–116 publications: 285 scientists 117–121 publications: 305 scientists 122–126 publications: 287 scientists 127–131 publications: 278 scientists 132–136 publications: 289 scientists 137–141 publications: 273 scientists 142–146 publications: 262 scientists 147–151 publications: 246 scientists 152–156 publications: 235 scientists 157–161 publications: 205 scientists 162–166 publications: 199 scientists 167–171 publications: 174 scientists 172–176 publications: 164 scientists 177–181 publications: 173 scientists 182–186 publications: 189 scientists 187–191 publications: 170 scientists 192–196 publications: 139 scientists 197–201 publications: 128 scientists 202–206 publications: 117 scientists 207–211 publications: 115 scientists 212–216 publications: 107 scientists 217–221 publications: 124 scientists 222–226 publications: 81 scientists 227–231 publications: 82 scientists 232–236 publications: 85 scientists 237–241 publications: 75 scientists 242–246 publications: 66 scientists 247–251 publications: 81 scientists 252–256 publications: 69 scientists 257–261 publications: 70 scientists 262–266 publications: 55 scientists 267–271 publications: 64 scientists 272–276 publications: 49 scientists 277–281 publications: 48 scientists 282–286 publications: 44 scientists 287–291 publications: 45 scientists 292–296 publications: 36 scientists 297–301 publications: 39 scientists 302–306 publications: 38 scientists 307–311 publications: 30 scientists 312–316 publications: 34 scientists 317–321 publications: 25 scientists 322–326 publications: 22 scientists 327–331 publications: 28 scientists 332–336 publications: 30 scientists 337–341 publications: 22 scientists 342–346 publications: 30 scientists 347–351 publications: 26 scientists 352–356 publications: 22 scientists 357–361 publications: 29 scientists 362–366 publications: 21 scientists 367–371 publications: 12 scientists 372–376 publications: 18 scientists 377–381 publications: 17 scientists 382–386 publications: 13 scientists 387–391 publications: 21 scientists 392–396 publications: 13 scientists 397–401 publications: 10 scientists 402–406 publications: 15 scientists 407–411 publications: 8 scientists 412–416 publications: 9 scientists 417–421 publications: 8 scientists 422–426 publications: 4 scientists 427–431 publications: 10 scientists 432–436 publications: 10 scientists 437–441 publications: 5 scientists 442–446 publications: 4 scientists 447–451 publications: 10 scientists 452–456 publications: 2 scientists 457–461 publications: 4 scientists 462–466 publications: 7 scientists 467–471 publications: 7 scientists 472–476 publications: 6 scientists 477–481 publications: 6 scientists 482–486 publications: 3 scientists 487–491 publications: 3 scientists 492–496 publications: 4 scientists 497–501 publications: 4 scientists 502–506 publications: 8 scientists 507–511 publications: 5 scientists 512–516 publications: 4 scientists 517–521 publications: 5 scientists 522–526 publications: 4 scientists 527–530 publications: 5 scientists 531+ publications: 100 scientists
37 publications 531+

This scientist: 221 publications — 80th percentile

80% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 531 publications or more.

Young-Seuk Park D-index placement in Ecology and Evolution in 2026

The chart shows the D-index (discipline H-index) distribution of Ecology and Evolution scientists ranked by Research.com in 2026. The highlighted bar marks where Young-Seuk Park sits on this spectrum.

30 D-Index: 95 scientists 31 D-Index: 123 scientists 32 D-Index: 191 scientists 33 D-Index: 245 scientists 34 D-Index: 252 scientists 35 D-Index: 244 scientists 36 D-Index: 249 scientists 37 D-Index: 244 scientists 38 D-Index: 254 scientists 39 D-Index: 254 scientists 40 D-Index: 280 scientists 41 D-Index: 274 scientists 42 D-Index: 266 scientists 43 D-Index: 233 scientists 44 D-Index: 248 scientists 45 D-Index: 208 scientists 46 D-Index: 201 scientists 47 D-Index: 213 scientists 48 D-Index: 207 scientists 49 D-Index: 172 scientists 50 D-Index: 209 scientists 51 D-Index: 199 scientists 52 D-Index: 153 scientists 53 D-Index: 169 scientists 54 D-Index: 163 scientists 55 D-Index: 148 scientists 56 D-Index: 120 scientists 57 D-Index: 146 scientists 58 D-Index: 137 scientists 59 D-Index: 140 scientists 60 D-Index: 104 scientists 61 D-Index: 119 scientists 62 D-Index: 118 scientists 63 D-Index: 99 scientists 64 D-Index: 77 scientists 65 D-Index: 100 scientists 66 D-Index: 86 scientists 67 D-Index: 83 scientists 68 D-Index: 75 scientists 69 D-Index: 94 scientists 70 D-Index: 57 scientists 71 D-Index: 68 scientists 72 D-Index: 59 scientists 73 D-Index: 63 scientists 74 D-Index: 66 scientists 75 D-Index: 60 scientists 76 D-Index: 42 scientists 77 D-Index: 49 scientists 78 D-Index: 39 scientists 79 D-Index: 37 scientists 80 D-Index: 43 scientists 81 D-Index: 41 scientists 82 D-Index: 45 scientists 83 D-Index: 34 scientists 84 D-Index: 40 scientists 85 D-Index: 35 scientists 86 D-Index: 55 scientists 87 D-Index: 24 scientists 88 D-Index: 24 scientists 89 D-Index: 30 scientists 90 D-Index: 23 scientists 91 D-Index: 25 scientists 92 D-Index: 27 scientists 93 D-Index: 27 scientists 94 D-Index: 13 scientists 95 D-Index: 23 scientists 96 D-Index: 12 scientists 97 D-Index: 14 scientists 98 D-Index: 19 scientists 99 D-Index: 16 scientists 100 D-Index: 14 scientists 101 D-Index: 5 scientists 102 D-Index: 21 scientists 103 D-Index: 16 scientists 104 D-Index: 10 scientists 105 D-Index: 7 scientists 106 D-Index: 7 scientists 107 D-Index: 7 scientists 108 D-Index: 6 scientists 109 D-Index: 9 scientists 110 D-Index: 11 scientists 111 D-Index: 12 scientists 112 D-Index: 9 scientists 113 D-Index: 7 scientists 114 D-Index: 3 scientists 115 D-Index: 8 scientists 116 D-Index: 5 scientists 117 D-Index: 11 scientists 118 D-Index: 4 scientists 119 D-Index: 2 scientists 120 D-Index: 5 scientists 121+ D-Index: 100 scientists
30 D-Index 121+

This scientist: 44 D-Index — 41st percentile

41% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 121 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Ecology and Evolution in Korea Leader Award
  • 2025 - Research.com Ecology and Evolution in Korea Leader Award

Overview

Young-Seuk Park is a researcher affiliated with Kyung Hee University in South Korea, primarily working in Environmental Science. The scientific contributions span multiple subfields, including Ecology, Nature and Landscape Conservation, Insect Science, Ecological Modeling, and Ecology, Evolution, Behavior and Systematics.

The research topics that Young-Seuk Park has focused on include:

  • Fish Ecology and Management Studies
  • Species Distribution and Climate Change
  • Environmental DNA in Biodiversity Studies
  • Aquatic Invertebrate Ecology and Behavior
  • Plant and animal studies
  • Freshwater macroinvertebrate diversity and ecology
  • Forest Insect Ecology and Management

Several recent publications illustrate the scope of work and areas of expertise:

  • "An interpretable machine learning method for supporting ecosystem management: Application to species distribution models of freshwater macroinvertebrates," 2021, Journal of Environmental Management
  • "Validity evaluation of a machine-learning model for chlorophyll a retrieval using Sentinel-2 from inland and coastal waters," 2022, Ecological Indicators
  • "Predicting the Global Distribution of Solenopsis geminata (Hymenoptera: Formicidae) under Climate Change Using the MaxEnt Model," 2021, Insects
  • "Predicting potential occurrence of pine wilt disease based on environmental factors in South Korea using machine learning algorithms," 2021, Ecological Informatics
  • "Key Determinants of Freshwater Gastropod Diversity and Distribution: The Implications for Conservation and Management," 2020, Water

Frequent coauthors collaborating with Young-Seuk Park include:

  • Dae-Seong Lee
  • Da-Yeong Lee
  • Ihn-Sil Kwak
  • Tae-Sung Kwon
  • Chang Woo Ji

Publication venues where Young-Seuk Park has contributed multiple works are centered around ecological and environmental journals, with a concentration in:

  • Korean Journal of Ecology and Environment
  • Global Ecology and Conservation
  • Forests
  • Ecological Informatics
  • Insects

Young-Seuk Park's research integrates ecological modeling and machine learning approaches to address environmental and conservation questions with an emphasis on biodiversity, species distribution, and ecosystem management.

Best Publications

  • Applications of artificial neural networks for patterning and predicting aquatic insect species richness in running waters

    Young-Seuk Park;Régis Céréghino;Arthur Compin;Sovan Lek

  • Patternizing communities by using an artificial neural network

    Tae-Soo Chon;Young Seuk Park;Kyong Hi Moon;Eui Young Cha

  • Conservation Strategies for Endemic Fish Species Threatened by the Three Gorges Dam

    Young-Seuk Park;Jianbo Chang;Sovan Lek;Wenxuan Cao

  • Biological early warning system based on the responses of aquatic organisms to disturbances: a review.

    Mi-Jung Bae;Young-Seuk Park

  • Review of the Self-Organizing Map (SOM) approach in water resources: Commentary

    R. Céréghino;Y. S. Park

  • Artificial Neural Networks: Multilayer Perceptron for Ecological Modeling

    Y.-S. Park;S. Lek

  • Hierarchical community classification and assessment of aquatic ecosystems using artificial neural networks.

    Young-Seuk Park;Tae-Soo Chon;Inn-Sil Kwak;Sovan Lek

  • Application of a self-organizing map to select representative species in multivariate analysis: A case study determining diatom distribution patterns across France

    Young-Seuk Park;Juliette Tison;Sovan Lek;Jean-Luc Giraudel

  • Typology of diatom communities and the influence of hydro-ecoregions: a study on the French hydrosystem scale.

    J. Tison;Y.-S. Park;M. Coste;J.G. Wasson

  • Water quality assessment using diatom assemblages and advanced modelling techniques

    Muriel Gevrey;Frédéric Rimet;Young Seuk Park;Jean‐Luc Giraudel

  • Characterizing effects of landscape and morphometric factors on water quality of reservoirs using a self-organizing map

    Young-Seuk Park;Yong-Su Kwon;Soon-Jin Hwang;Sangkyu Park

  • Relationships between stream macroinvertebrates and environmental variables at multiple spatial scales

    Fengqing Li;Namil Chung;Mi-Jung Bae;Yong-Su Kwon

  • Spatial and temporal patterns of benthic invertebrate communities in an intermittent river (North Africa)

    A. Arab;S. Lek;A. Lounaci;Y. S. Park

  • Predicting the species richness of aquatic insects in streams using a limited number of environmental variables

    Régis Céréghino;Young-Seuk Park;Arthur Compin;Sovan Lek

  • Patterning and predicting aquatic macroinvertebrate diversities using artificial neural network.

    Young-Seuk Park;Piet F.M Verdonschot;Tae-Soo Chon;Sovan Lek

  • An interpretable machine learning method for supporting ecosystem management: Application to species distribution models of freshwater macroinvertebrates.

    YoonKyung Cha;Jihoon Shin;ByeongGeon Go;Dae-Seong Lee

  • Modelling Community Structure in Freshwater Ecosystems

    Sovan Lek;Michele Scardi;P. F. M. Verdonschot;J.-P. Descy

  • Impact of Urban Pollution from the Hanoi Area on Benthic Diatom Communities Collected from the Red, Nhue and Tolich Rivers (Vietnam)

    Thi Thuy Duong;Thi Thuy Duong;Michel Coste;Agnès Feurtet-Mazel;Dinh Kim Dang

  • Modelling the factors that influence fish guilds composition using a back-propagation network: Assessment of metrics for indices of biotic integrity

    Alonso Aguilar Ibarra;Muriel Gevrey;Young Seuk Park;Puy Lim

  • Determining temporal pattern of community dynamics by using unsupervised learning algorithms

    Tae-Soo Chon;Young-Seuk Park;June Ho Park

  • Implementation of artificial neural networks in patterning and prediction of exergy in response to temporal dynamics of benthic macroinvertebrate communities in streams

    Young-Seuk Park;Inn-Sil Kwak;Tae-Soo Chon;Jwa-Kwan Kim

Frequent Co-Authors

Sovan Lek
Sovan Lek Paul Sabatier University
Piet F. M. Verdonschot
Piet F. M. Verdonschot Wageningen University & Research
Michel Coste
Michel Coste University of Rennes
Luc Ector
Luc Ector Luxembourg Institute of Science and Technology
Régis Céréghino
Régis Céréghino Paul Sabatier University
Frédéric Rimet
Frédéric Rimet Université Savoie Mont Blanc
Peter Goethals
Peter Goethals Ghent University
Michele Scardi
Michele Scardi University of Rome Tor Vergata
Sébastien Brosse
Sébastien Brosse Paul Sabatier University
Pieter Boets
Pieter Boets Ghent University

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