MST-School of Architecture and the Built Environment

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    Settlement Schemes and Their Implication on Eastern Mau Watershed, Nakuru County, Kenya
    (Kenyatta University, 2022) Cherotich, Fredah; Sammy Letema
    Settlement schemes are aimed at settling landless people and those displaced by disasters to support socio-economic and environmental development of a country. Eastern Mau Forest Reserve is an important watershed that has settlement schemes established, which has led to encroachments and degradation of the watershed. This study, therefore, assessed the implications of human settlements on Eastern Mau watershed by examining the trends in land use/cover change, settlement schemes and river flows for four decades, from 1979 to 2020. Eastern Mau Forest Reserve is a major water tower therefore the large tracts of land that have been cleared coupled with the settlements in it is a worrying trend. It is essential to develop an approach that will aid in assessing land use land cover changes and effects on hydrological components at catchment level to aid in planning, use and management of resources. Primary data was collected from key informant interviews based on purposive sampling. Secondary data was derived from Landsat satellite images over a 10-year period and analysed using Maximum Likelihood Function from ArcGIS. Data on river flows from River Njoro was obtained from Water Resources Authority Office in Nakuru County for 1979-2020. Rainfall data for 1979-2020 was obtained from Kenya Meteorological Station, Nakuru Town. Time series analysis is used to understand the trend in river flows over time while Pearson correlation is used to determine relationship between farmlands and river flows. The results indicate a sharp decline in forest cover by 42.7% and an increase in farmlands by 41%. Dense vegetation and farmlands have an inverse relationship as an increase in farmlands lead to a decrease in forest cover and vice versa. People have settled beyond the established settlement schemes leading to encroachment and drying up of some rivers. There is also an increase in rainfall and river flows over the years, with monthly river flows increasing in peak flows and declining during low seasons. There is a positive correlation between farmlands and river flows between 1989 and 2020. Settlements affect land cover that in turn affects forests and impacts capacity of land to absorb rainfall water, which leads to higher runoff and subsequently higher flows. There is need for regeneration of encroached areas and defining boundary of Eastern Mau to allow initiatives and interventions that help with sustainable management of the watershed area.
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    Desert Locust (Schistocerca gregaria) Invasion Risk and Vegetation Damage in a Key Upsurge Area
    (MDPI, 2023-03) Mongare, Raphael; Abdel-Rahman, Elfatih M.; Mudereri, Bester Tawona; Kimathi, Emily; Onywere, Simon; Tonnang, Henri E. Z.
    In the recent past, the Horn of Africa witnessed an upsurge in the desert locust (Schistocerca gregaria) invasion. This has raised major concerns over the massive food insecurity, socioeconomic impacts, and livelihood losses caused by these recurring invasions. This study determined the potential vegetation damage due to desert locusts (DLs) and predicted the suitable habitat at high risk of invasion by the DLs using current and future climate change scenarios in Kenya. The normalized difference vegetation index (NDVI) for the period 2018–2020 was computed using multi-date Sentinel- 2 imagery in the Google Earth Engine platform. This was performed to assess the vegetation changes that occurred between May and July of the year 2020 when northern Kenya was the hotspot of the DL upsurge. The maximum entropy (MaxEnt) algorithm was used together with 646 DL occurrence records and six bioclimatic variables to predict DL habitat suitability. The current (2020) and two future climatic scenarios for the shared socioeconomic pathways SSP2-4.5 and SSP5-8.5 from the model for interdisciplinary research on climate (MIROC6) were utilized to predict the future potential distribution of DLs for the year 2030 (average for 2021–2040). Using Turkana County as a case, the NDVI analysis indicated the highest vegetation damage between May and July 2020. The MaxEnt model produced an area under the curve (AUC) value of 0.87 and a true skill statistic (TSS) of 0.61, while temperature seasonality (Bio4), mean diurnal range (Bio2), and precipitation of the warmest quarter (Bio18) were the most important bioclimatic variables in predicting the DL invasion suitability. Further analysis demonstrated that currently 27% of the total area in Turkana County is highly suitable for DL invasion, and the habitat coverage is predicted to potentially decrease to 20% in the future using the worst-case climate change scenario (SSP5-8.5). These results have demonstrated the potential of remotely sensed data to pinpoint the magnitude and location of vegetation damage caused by the DLs and the potential future risk of invasion in the region due to the available favorable vegetational and climatic conditions. This study provides a scalable approach as well as baseline information useful for surveillanc
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    Determinants of Spatial Distribution of Trees Outside Forests along Urban-Rural Gradients: A Review
    (Sustinere: Journal of Environment and Sustainability, 2024-05) Kariuki, Dorcas Wambui; Letema, Sammy C.; Opinde, Godwin O.
    Urbanization can create uncertainty for biodiversity.Understanding the spatial distribution of trees along urban-rural gradients is crucial for sustainable land management and the conservation of biological diversity. However, limited information is available on the factors influencing the distribution of trees outside forests along urban-rural transition gradients. This paper uses the Preferred Reporting items for Systematic Reviews and Meta-Analyses (PRISMA) to review how distance from urban centers, land use types, socio-economic disparities,and community attitudes and perceptions impact the spatial distribution of trees outside forests along urban-rural gradients. The review indicates that the species composition, diversity, density, and spatial arrangement of trees outside forests vary along the urban-rural gradient. The most commonly cited factors influencing this distribution are respondents' attitudes and perceptions of trees, socio-economic factors, and land use variations. Distance from the urban center was the least citedfactor. However, there is significant variation in how different factors impact this distribution from study to study. Therefore, further research is needed to better understand the factors driving changes in the diversity of trees outside forests in various urban-rural contexts and to determine whether variations exist across different settings.