Spatial analysis of tree species occurrence: an example of Mount Kenya region
Abstract
Ecologists often seek to predict species distributions of environmental
variables. Statistical models are useful for making predictions about occurrence of
species based on the variables derived from remote sensing or geographic
information system. We used five environmental variables from 265 plots sampled
on farms around Mount Kenya region and species inventories colleted for five
years (1999-2004) by ICRAF. We modeled the occurrence of the two species:
Croton megalocarpus and Cupressus lusitanica using logistic regression model and
then abundance was modeled by negative binomial model.
The aim of the study was to establish the relationship between the
environmental factors and occurrence/ abundance of the tree species on farm and
using R functions to map them.
"Generally all the variables did poorly in predicting the presence-absence
and abundance of the two species. The results suggested that the presence
absence for the two species w~spest explained by vegetation class only. For the
abundance, the results suggested that Croton megalocarpus abundance was best
explained by Vegetation class whereas Cupressus lusitanica abundance was best
explained by agro ecological zones. Moreover the findkigs of the study were that
occurrence and abundance of the two species were not affected by rainfall,
temperature and altitude. ·Sensitivity,.and specificity were affected by the species
occurrence and not the abundance.
Citation
M.Sc (Biometry)Sponsorhip
University of NairobiPublisher
School of Mathematics, University of Nairobi
Description
Master of Science Thesis