Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Stream fish assemblages and basin land cover in a river network.

Young-Seuk Park1, Gaël Grenouillet, Benjamin Esperance

  • 1Department of Biology, Kyung Hee University, Dongdaemun-gu, Seoul 130-701, Republic of Korea. parkys@khu.ac.kr

The Science of the Total Environment
|April 22, 2006
PubMed
Summary

Landscape features significantly influence stream fish assemblages in the Adour-Garonne basin. Artificial neural networks effectively predicted fish types based on land cover and basin characteristics.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Biological invasions disrupt the relationship between size spectrum and trophic interactions in freshwater fish communities.

The Journal of animal ecology·2026
Same author

Species range shifts often speed ahead of their modeled climatic niches.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Genetic Diversity Impacts Climate-Induced Species Range Shifts.

Ecology letters·2026
Same author

Increasing Functional or Phylogenetic Distance From Native Fish Communities Promotes Non-Native Fish Invasions in Global Rivers.

Global change biology·2026
Same author

Seasonal and Spatiotemporal Dynamics of Plankton Communities Using eDNA Metabarcoding in Singal Reservoir.

Environmental management·2026
Same author

Assessment of the ecological status of benthic macroinvertebrate communities in the intertidal flats of Lake Shihwa following tidal power plant operation.

Marine pollution bulletin·2025

Area of Science:

  • Ecology
  • Freshwater Biology
  • Geospatial Analysis

Background:

  • Understanding stream fish assemblage patterns is crucial for effective river management.
  • Landscape-scale features are known to influence aquatic ecosystems, but their specific impacts on fish assemblages require detailed investigation.

Purpose of the Study:

  • To characterize fish assemblages in the Adour-Garonne basin.
  • To identify the influence of landscape-scale features on stream fish assemblage patterns.
  • To compare the predictive power of artificial neural networks against traditional methods.

Main Methods:

  • Utilized self-organizing maps (SOM) to classify fish assemblages based on species composition.
  • Employed multilayer perceptron (MLP) and factorial discriminant analysis for predictive modeling.

Related Experiment Videos

  • Integrated topographical data (altitude, distance from source, basin area) and land cover data (agricultural, forest, urban) derived from GIS.

    • Main Results:

    • SOM successfully identified three distinct fish assemblage types.
    • MLP demonstrated superior prediction accuracy for assemblage types compared to discriminant analysis.
    • Agricultural land percentage and basin surface area were key drivers for assemblage types 1 and 2.
    • Distance from source was the most influential factor for assemblage type 3.

    Conclusions:

    • Landscape-scale features, particularly land cover and basin morphology, are significant determinants of stream fish assemblage structure.
    • Artificial neural networks, like MLP, offer a powerful tool for predicting fish assemblages based on environmental variables.
    • The findings provide valuable insights for ecological assessments and conservation strategies within river basins.