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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/11384

Title: Spatial Binomial Generalized Linear Model of Tree Species Occurrence in Mt. Kenya Region
Authors: Owino, John
Adebanji, Atinuke
Ingwe, Marlyne
Njoroge, Julia
Keywords: Generalised linear models
Environmental and spatial variables
Occurrence prediction
Issue Date: 2009
Publisher: The East African Journal of Statistics
Citation: The East African Journal of Statistics, Volume2, Number 3, pp. xx-xx
Abstract: Predictive distribution models are important in studying the occurrence of species based on variables derived from remote sensing or Geographical Information System (GIS). This project investigates the hypothesis that environmental variables can be used to predict the occurrence of species.Spatial Binomial Generalized linear models were developed to predict the occurrence of Grevillea robusta, Croton megalocarpus and Carica papaya species in the Mt.Kenya region. Environmental and spatial variables from data sampled in a 265 plots based on vegetation survey carried out by ICRAF between 1999-2004 was used in the study. Results obtained showed that the model for vegetation class and agroecological zones predicted the occurrence of Grevillea robusta with a very small error. Although most levels for vegetation and agroecological zones were not significant, they explained most deviance for the three species. Altitude gave a good prediction for both Carica papaya and Croton megalocarpus, while rainfall predicted well the occurrence of Grevillea robusta.
Description: An article published in The East African Journal of Statistics, Volume2, Number 3, pp. xx-xx, 2009
URI: http://hdl.handle.net/123456789/11384
ISSN: 1811-7503
Appears in Collections:College of Science

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