Relationship between vegetation cover types and soil organic carbon in the rangelands of Northern Kenya

Publication Type

Journal contribution (peer reviewed)

Authors

Kurgat B K, Golicha D, Giese M, Kuria S G and Asch F

Year of publication

2014

Published in

Livestock Research for Rural Development

Band/Volume

26/Article #162

Climate Change affect various sectors in Kenya, with the most vulnerable being agriculture, livestock, water, health, fisheries and tourism. Accurate estimates of soil organic carbon stocks (SOCS) in the rangelands are critical in developing strategies to help mitigate impacts of climate change. The study therefore, sought to establish the relationship between vegetation cover types and SOCS in northern rangelands of Kenya as an indirect method of estimating SOCS in the field. Landsat 5 Thematic Mapper satellite image was used to differentiate vegetation cover types and soil samples taken along the transect line laid at intervals of 50 m across each vegetation cover type. Colourimetric and core sampling methods were used to determine SOC concentrations and soil bulk densities, respectively. Analysis of variance and simple linear regression were used in the statistical analysis.

Four vegetation cover types indentified were: Acacia bush land (ABL), bare land (BRL), sparsely distributed acacia with bare ground (SAB), sparsely distributed acacia with forbs (SAF) and. The means of SOC for each vegetation cover were different. However, soil bulk densities under BRL and SAB were similar but different from that of ABL and SAF that were alike. Further, overall mean of SOCS was 6.76±2.85 t C ha^-1 for all the vegetation cover types. A positive relationship was established between the average mean values of both Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) when regressed with the average mean values of SOCS. The findings suggest that vegetation indices measured with GIS are good predictors of SOCS for the study region, with the potential for extrapolation to the arid and semi-arid areas to which this ecosystem belongs.