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
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;
Conference_Titel :
Automation and Computing (ICAC), 2011 17th International Conference on
Conference_Location :
Huddersfield
Print_ISBN :
978-1-4673-0000-1
