Theory I: Ecological niches and geographic distributions

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  • Опубликовано: 27 окт 2024

Комментарии • 11

  • @space-time-somdeep
    @space-time-somdeep 8 месяцев назад

    Fascinating topic.. specially seeing from a remote sensing and gis prospective

  • @thananhkhotathoom1460
    @thananhkhotathoom1460 3 года назад +2

    Great! I learned a lots from the lectures

  • @israelgz5358
    @israelgz5358 8 лет назад +2

    Thanks a lot for this course, it´s fantastic!

  • @ellalewis8098
    @ellalewis8098 2 года назад

    very useful, thank you!! lovely illustrations

  • @gebrehiwotgebreab5780
    @gebrehiwotgebreab5780 6 лет назад +2

    Thank you for your lecture. I have one question how can we eliminate multicollinearity in the environmental variable.

  • @otienoachieng7129
    @otienoachieng7129 7 лет назад

    Many thanks for this. Its really been helpful.

  • @RafikGARNI
    @RafikGARNI 8 лет назад

    Thank's a million

  • @JackWiizard
    @JackWiizard 8 лет назад

    That's great, thanks!

  • @milamanic8307
    @milamanic8307 8 лет назад

    Great :D

  • @gebrehiwotgebreab5780
    @gebrehiwotgebreab5780 5 лет назад

    Thank you for your lecture. I have one question how can we eliminate multicollinearity in the environmental variable.

    • @wyclifeoluoch9376
      @wyclifeoluoch9376 5 лет назад +1

      First, run Pearson correlation within all your independent variables and, ideally, any two variables with r > 0.8, you should drop one. To decide on which one to drop, check their contribution/importance in explaining the distribution of your species (easy to do in MaxEnt) and drop the less important one.