• DocumentCode
    556663
  • Title

    Species area relations and information rich modelling of plant species variation

  • Author

    Furze, James ; Zhu, Quan Min ; Qiao, Feng ; Hill, Jennifer

  • Author_Institution
    Fac. of Environ. & Technol., Univ. of the West of England, Bristol, UK
  • fYear
    2011
  • fDate
    10-10 Sept. 2011
  • Firstpage
    63
  • Lastpage
    68
  • Abstract
    Least squares regression is used to show the relationship of species with area on a global scale. Using a modelling based approach climatic variables are selected and made use of in a proposed information rich model of plant species variation. Future developments include advances in mathematical theory, biogeography and computer science.
  • Keywords
    botany; ecology; least squares approximations; modelling; regression analysis; biogeography; climatic variables; computer science; information rich modelling; least squares regression; mathematical theory; modelling based approach; plant species variation; species area relations; Biogeography; Biological system modeling; Clouds; Computational modeling; Correlation; Mathematical model; Temperature distribution; biogeography; computer science; mathematics; modelling; species area;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation and Computing (ICAC), 2011 17th International Conference on
  • Conference_Location
    Huddersfield
  • Print_ISBN
    978-1-4673-0000-1
  • Type

    conf

  • Filename
    6084902