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Forest degradation impact on soil physico-chemical properties and bacteria community structure in Mount Kenya forest ecosystem

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dc.contributor.author Koech, Jebet Truphena
dc.date.accessioned 2025-12-04T13:31:36Z
dc.date.available 2025-12-04T13:31:36Z
dc.date.issued 2025
dc.identifier.uri http://ir.mu.ac.ke:8080/jspui/handle/123456789/10006
dc.description.abstract The Mount Kenya forest ecosystem has experienced notable degradation in recent years largely due to uncontrolled anthropogenic land use activities such as deforestation, overgrazing and improper land management, and whose impact on soil microbial communities has not been fully elucidated. Hence, this study aimed to assess the effects of forest degradation on soil bio-physico-chemical properties within the Mt. Kenya Forest. The specific objectives were to: Assess the effects of forest degradation on selected soil physical properties; Analyze the effect of forest degradation on soil chemical properties; and evaluate the influence of forest degradation on soil bacteria community structure. Two contrasting and non overlapping forest patches –undisturbed and degraded– were selected, and a 100×100 m plot established in each patch. Six sampling locations, with a spacing of 18 m between points, were established diagonally across each plot. To account for microvariability at each sampling location, sterile soil auger was used to collect soil samples in three replicates –one at the center and two others 1 m to the left and right. A total of 36 soil samples were transported in cool boxes and refrigerated prior to laboratory analysis. The dry combustion and core ring methods were used to assess the soil physical properties of organic matter and bulk density, respectively. Calcium, potassium and magnesium chemical properties were extracted using ammonium acetate and quantified by atomic absorption spectroscopy, while soil pH was measured in situ using a pH meter. Soil microbial abundance was determined using the pour plate method, while bacterial isolates were characterized based on morphological, biochemical, and molecular traits. Molecular identification involved DNA extraction, sequencing and BLAST analysis using MEGA X and NCBI GenBank. Data were analyzed using analysis of variance in SAS version 9.4, with LSD for post hoc comparisons. Results showed that undisturbed patch had significantly higher (P<0.05) soil organic matter, bulk density, calcium and potassium levels, but supported significantly lower (62.5±27.83; F1, 94=139.10; P<0.0001) mean bacteria colony-forming units (CFUs) when compared to degraded patch with 152.74±48.74 CFUs (F1, 94=139.10; P<0.0001), whose soil pH was more alkaline. Molecular analysis based on16SrRNA gene sequences showed distinct clustering of bacterial isolates with bootrap support values ranging from 69% to 100% with known strains in GenBank. Dominant bacterial isolates in undisturbed forest included Bacillus aerius, Pseudochrobactrum saccharolyticum, Brucella pseudogrignonensis, Brevundimonas diminuta, Delftia tsuruhatensis, Stenotrophomonas maltophilia, and Pseudomonas fluorescens, while degraded patch yielded Vagococcus fluvialis, Achromobacter xylosoxidans, Cupriavidus sp., and Ochrobactrum sp., thus indicating that forest land use degradation can affect soil bacterial communities through modifying soil physical parameters, nutritional conditions, and biological interactions. In conclusion, this study shows that forest land use changes can drastically alter the number of soil bacterial communities through modifying soil physical parameters, nutritional conditions, and biological interactions. This study recommends continuous monitoring of soil bio-physico-chemical properties that serve as indicators of forest soil health, and incorporating findings into forest management and restoration plans. en_US
dc.language.iso en en_US
dc.publisher Moi Univerisity en_US
dc.subject Forest degradation en_US
dc.subject Impact en_US
dc.title Forest degradation impact on soil physico-chemical properties and bacteria community structure in Mount Kenya forest ecosystem en_US
dc.type Thesis en_US


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