Browsing by Author "Macharia, Joseph M."

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  • Publication
    Publication
    Homogeneous land-use sequences in heterogeneous small-scale systems of Central Kenya: Land-use categorization for enhanced greenhouse gas emission estimation
    (Elsevier, 2022) Mairura, Franklin S.; Musafiri, Collins M.; Kiboi, Milka N.; Macharia, Joseph M.; Ng'etich, Onesmus K.; Shisanya, Chris A.; Okeyo, Jeremiah M.; Okwuosa, Elizabeth A.; Ngetich, Felix K.
    The current understanding of the link between land management practices and GHG (greenhouse gas) emissions is limited in the small-scale farm sector of sub-Sahara regions due to insufficient or fragmented land-use data. Land-use categories recognized in the national GHG inventories in Kenya are coarse. Therefore, they do not adequately account for the diversity in small-scale land uses. Characterization of land-use and knowledge of key drivers of land-use change is necessary to improve national GHG inventories in the SSA (Sub-Sahara Africa) region. We implemented a cross-sectional survey to characterize land-use and determine factors which influenced changes in land use within small-scale farms of Tharaka-Nithi County, Kenya. We sampled 300 farmers using multistage sampling and collected crop sequence recall data at plot level for three years (seven seasons). We grouped crop sequences into clusters using the ‘TraMineR’ R package. We derived four clusters including banana, tea, and declining fallows (cluster 1, 19.2% of plots), cereal-legume systems (cluster 2, 55.1%), fodder (cluster 3, 11.7%) and coffee (cluster 4, 14.0%). We observed higher N application rates in perennial cropping systems, than in annual crops, including cereal-legume systems. We observed that farmers in higher potential agro-ecological zones, male-managed farms, with higher per capita land area, higher remittances and higher total house-hold incomes, were associated with a higher propensity to adjust crop enterprises, leading to more unstable land-use sequences. Contrariwise, farmers with higher education, credit access, secure land tenure, increasing slope, good soil fertility, and longer farming experiences recorded a lower propensity to adjust their land uses, resulting in more stable crop sequences. Farmer socio-demographic characteristics influenced land-use change, which is directly linked with soil GHG emissions. Our findings propose the adoption of Tier II GHG quantification approaches which disaggregate between annual and perennial crop enterprises. GHG emissions are likely to be more generalizable in stable perennial crop systems than annual systems. Thus, better disaggregation of GHG sampling in annual crop systems is needed due to high diversity in crop and soil fertility management, and the dynamic nature of C and N cycling in these systems.
  • Publication
    Publication
    Homogeneous land-use sequences in heterogeneous small-scale systems of Central Kenya: Land-use categorization for enhanced greenhouse gas emission estimation
    (Elsevier, 2022-02-09) Mairura, Franklin S.; Musafiri, Collins M.; Kiboi, Milka N.; Macharia, Joseph M.; Ng'etich, Onesmus K.; Shisanya, Chris A.; Okeyo, Jeremiah M.; Okwuosa, Elizabeth A.; Ngetich, Felix K.
    The current understanding of the link between land management practices and GHG (greenhouse gas) emissions is limited in the small-scale farm sector of sub-Sahara regions due to insufficient or fragmented land-use data. Land-use categories recognized in the national GHG inventories in Kenya are coarse. Therefore, they do not adequately account for the diversity in small-scale land uses. Characterization of land-use and knowledge of key drivers of land-use change is necessary to improve national GHG inventories in the SSA (Sub-Sahara Africa) region. We implemented a cross-sectional survey to characterize land-use and determine factors which influenced changes in land use within small-scale farms of Tharaka-Nithi County, Kenya. We sampled 300 farmers using multistage sampling and collected crop sequence recall data at plot level for three years (seven seasons). We grouped crop sequences into clusters using the ‘TraMineR’ R package. We derived four clusters including banana, tea, and declining fallows (cluster 1, 19.2% of plots), cereal-legume systems (cluster 2, 55.1%), fodder (cluster 3, 11.7%) and coffee (cluster 4, 14.0%). We observed higher N application rates in perennial cropping systems, than in annual crops, including cereal-legume systems. We observed that farmers in higher potential agro-ecological zones, male-managed farms, with higher per capita land area, higher remittances and higher total house-hold incomes, were associated with a higher propensity to adjust crop enterprises, leading to more unstable land-use sequences. Contrariwise, farmers with higher education, credit access, secure land tenure, increasing slope, good soil fertility, and longer farming experiences recorded a lower propensity to adjust their land uses, resulting in more stable crop sequences. Farmer socio-demographic characteristics influenced land-use change, which is directly linked with soil GHG emissions. Our findings propose the adoption of Tier II GHG quantification approaches which disaggregate between annual and perennial crop enterprises. GHG emissions are likely to be more generalizable in stable perennial crop systems than annual systems. Thus, better disaggregation of GHG sampling in annual crop systems is needed due to high diversity in crop and soil fertility management, and the dynamic nature of C and N cycling in these systems.
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    Publication
    Multi-influencing-factors’ evaluation for organic-based soil fertility technologies out-scaling in Upper Tana Catchment in Kenya
    (Scientific African, 2020) Nganga, Beatrice W.; Ng’etich, Onesmus K.; Macharia, Joseph M.; N. Milka Kiboi; Noah Adamtey; K. Felix Ngetich
    Low adoption of soil fertility technologies, partially attributed to low technology outscaling initiatives, is a critical hindrance to agricultural productivity enhancement of most smallholder farms in sub-Saharan Africa. Application of geospatial tools for spatial suitability evaluation of soil fertility management technologies can be a breakthrough in their promotion and out-scaling existing novel technological initiatives. The study objective was to develop a data-driven multi-influencing-factor (MIF) geospatial approach for out-scaling organic-resource based soil fertility management technologies. Using the developed geospatial approach, we delineated suitable zones for targeted out-scaling of organic resource technologies in the Upper Tana River (UTC) catchment in Kenya. We acquired multiple datasets from different sources and used them to prepare thematic layers. The factors used included rainfall, elevation, cattle density, bulk density, slope, soil pH, soil organic carbon, cation exchange capacity, drainage, and soil texture. The input layers were georeferenced, converted to raster formats, standardized to a range of 1 to 5, after which we generated the suitability map through a weighted overlay technique. The delineated suitability map showed that about 0.002% of UTR was least suitable, 4.7% marginally suitable, 38.5% moderately suitable, 34.7% medium-high suitable while 0.03% was highly suitable for organic resources out-scaling The results obtained indicate the potential of the geospatial approach as a scaling out methodology for organic-based soil fertility technologies. The suitability delineation established that Nyeri, Murang’a and Meru are the most suitable areas for the use of most organic resources in the Upper Tana catchment of the Central Highlands of Kenya. The suitability maps can inform policymakers, planners, and decision-makers in identifying the suitable sites for the use of organic-based soil fertility resources. Based on this study, we recommend the use of the developed a data-driven multi-influencing-factor (MIF) geospatial approach in the scaling out of the organic-based soil fertility technologies, not only in the study area but also other regions in sub-Saharan Africa