• Login
    • Login
    Advanced Search
    View Item 
    •   Maseno IR Home
    • Journal Articles
    • School of Environment & Earth Sciences
    • Department of Environmental Science
    • View Item
    •   Maseno IR Home
    • Journal Articles
    • School of Environment & Earth Sciences
    • Department of Environmental Science
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Modeling Vegetation Lifeforms Abundance based on Epigeal Termitaria Physiography and Altitude in Tropical Savannah of Katolo Sub-Location, Kisumu County

    Thumbnail
    View/Open
    Agano paper 2017 (1).pdf (914.2Kb)
    Publication Date
    2017
    Author
    Oindo, Boniface O
    Oluoch, Wyclife A
    Abuom, Paul
    Metadata
    Show full item record
    Abstract/Overview
    Termite mounds are major sites of functional heterogeneity in the tropical ecosystems globally; through their prodigious influence on vegetation and soil perturbation. They aid soil aeration, water infiltration and catabolism of vegetative matter into nutrient rich humus. There is no documentation of a model for prediction of vegetation lifeforms with respect to mound basal radii, heights and altitude. Objective of this study was therefore to develop a model for rapid prediction of vegetation lifeforms (trees, shrubs, lianas and grass) abundance based on physiography (basal radii and heights) and altitude of the termite mounds. Study population of the mounds was unknown. Cross sectional research design was used. Saturated sampling was done where sixty accessible termite mounds were studied. Both basal radii and heights of termite mounds were measured using 50 m tape measure or hand-held inclinometer. Altitude data were captured by hand-held Global Positioning System (GPS). Trees, shrubs and lianas were identified visually and counted on the mounds while grass abundance was estimated using 0.3 m by 0.3 m quadrat on every termitarium. Multiple Linear Regressions were done to model vegetation lifeforms abundance based on termite mound basal radius, height and altitude. Results indicated that predicted MLR significantly (p ≤ 0.05) predicted trees, shrubs and lianas but not grass abundance. Predicted trees abundance = −89.2587 + 10.46157 (radius (m)) − 4.96989 (height (m)) + 0.074074 (altitude (m)), predicted shrubs abundance = 19.26065 + 6.780626 (radius (m)) – 6.09157 (height (m)) − 0.00822 (altitude (m)) and predicted lianas abundance = −24.9345 + 5.881659 (radius (m)) − 0.68423 (height (m)) + 0.020729 (altitude (m)). This study demonstrated significant effect of termite How to cite this paper: Oluoch, W.A., Oindo, B.O. and Abuom, P. (2017) Modeling Vegetation Lifeforms Abundance based on Epigeal Termitaria Physiography and Altitude in Tropical Savannah of Katolo Sub-Location, Kisumu County. Journal of Geoscience and Environment Protection, 5, 22-31. https://doi.org/10.4236/gep.2017.510003 Received: September 7, 2017 Accepted: October 15, 2017 Published: October 18, 2017 Copyright © 2017 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access W. A. Oluoch et al. DOI: 10.4236/gep.2017.510003 23 Journal of Geoscience and Environment Protection mound physiography on vegetation lifeforms abundance as well as developed a model for rapid prediction of their abundance on termite mounds
    Permalink
    https://repository.maseno.ac.ke/handle/123456789/444
    Collections
    • Department of Environmental Science [110]

    Maseno University. All rights reserved | Copyright © 2022 
    Contact Us | Send Feedback

     

     

    Browse

    All of Maseno IRCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    Maseno University. All rights reserved | Copyright © 2022 
    Contact Us | Send Feedback