Connectivity Inference

Connectivity Inference is a methodological framework within population connectivity research that identifies and quantifies the patterns of movement or gene flow among subpopulations by analyzing indirect genetic, demographic, or ecological data.

45

Publications

3.1K

Citations

212

Authors

126

Institutions

Publications per year

2017–2026

20

Authors

212

  1. DY
    Daniel Y. Takahashi

    Princeton University, United States

    3 publications · 201 citations

    3

    h-index

  2. KS
    Koichi Sameshima

    Universidade de São Paulo, Brazil

    3 publications · 201 citations

    3

    h-index

  3. LA
    Luiz Antonio Baccalá

    Universidade de São Paulo, Brazil

    2 publications · 88 citations

    2

    h-index

  4. SD
    Sven Dorkenwald

    Princeton University, United States

    2 publications · 176 citations

    2

    h-index

  5. PP
    Pablo Presa

    Universidade de Vigo, Spain

    2 publications · 46 citations

    2

    h-index

1–5 of 212

Venues

  1. Movement Ecology

    3 publications · 99 citations

    3

    h-index

  2. Nature Methods

    2 publications · 176 citations

    2

    h-index

  3. Landscape Ecology

    2 publications · 217 citations

    2

    h-index

  4. Fisheries Research

    2 publications · 56 citations

    2

    h-index

  5. Molecular Ecology Resources

    2 publications · 56 citations

    2

    h-index

1–5