Browsing by Author "Mgeni, Charles P"

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    African lion population estimates in Tanzania’s Ruaha national park
    (Scientific Research Publishing, 2022-02) Kimaro, Michael H; Mrosso, Hillary T; Chidodo, Simon J; Chilagane, Nyemo A; Msigwa, Fenrick F; Bulenga, George B; Kicheleri, Rose P; Mgeni, Charles P; Kangile, Rajabu J; Kimambo, Elisante A; Hughes, Courtney; Warbington, Camille; Mchaki, Helen; Mathayo, Daniel; Kiwango, Halima R
    Tanzania is considered a country with the largest number of African lions ( Panthera leo ). However, the continued absence of ecological population es- timates and understanding of the associated factors influencing lion distribu- tion hinders the development of conservation planning. This is particularly true in the Ruaha-Rungwa landscape, where it was estimated that more than 10% of the global lion population currently resides. By using a call-back sur- vey method, we aimed to provide population estimates (population size and density) of African lions in the Ruaha National Park, between wet (March 2019) and dry (October 2019) seasons. We also assessed the key factors that influenced the distribution of the observed lions towards call-back stations. Ferreira & Funston’s (2010) formula was used to calculate population size and in turn used to estimate density in the sampled area, while the Genera- lized Linear Model (GLMM) with zero-inflated Poisson error distribution was used to determine factors that influence the distribution of the observed lions to call-back stations. The population size we calculated for the sampled area of 3137.2 km 2 revealed 286 lions (95% CI, 236 - 335) during the wet season, and 196 lions (95% CI, 192 - 200) during the dry season. The density of lions was 9.1/100 km 2 during the wet season, and 6.3/100 km 2 during the dry sea- son. Distance to water source had a significant negative effect on the distribu- tion of the observed lions to the call-back stations, while habitat had a mar- ginal effect. Our findings show that, although lion population estimates were larger during the wet season than the dry season, the season had no effect on the distribution of the observed lions to call-back stations. We suggest that the proximity to water sources is important in study design. Further, we sug- gest that density and population size are useful indices in identifying conser- vation area priorities and lion coexistence strategies.
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    Dynamics of adjusted net National income per Capital and its determinants application of ARDL and vector error correction models to Sub-Saharan Africa
    (Eastern and Southern Africa Journal of Agricultural Economics & Development, 2025-03) Kadigi, Barthlomeow R; Sanga, Gody J; Mgeni, Charles P; Kadigi, Michael L
    Over the past few decades, the Sub-Saharan Africa (SSA) region has experienced a myriad of economic challenges, including highly dynamic trade trends, fluctuating commodity prices, stagnating capital accumulation trends, varying levels of foreign investment, and rapid population growth. These, coupled with the region's unique socio-economic landscape, necessitate a comprehensive understanding of how different variables interact to shape income outcomes. This paper employs the Autoregressive Distributed Lag (ARDL) and Vector Correction Models (VECM) to analyse the dynamics of Adjusted Net National Income Per Capita (ANNIPC). The results show complex interdependencies of capital formation, trade, inflation, and demographics indicating that increased gross capital formation and manageable inflation positively affect ANNIPC. This underscores the need for policymakers in SSA to prioritise capital investment strategies, such as infrastructure development and enhanced financial access, to spur sustainable economic growth. Additionally, improving export capacities and trade balances for elevating income levels and paying attention to population dynamics is essential. Similarly, integrating human capital enhancement through education and skills training into economic policies remains one of the important focal areas. We also found a quick adjustment to long-run equilibrium among variables that underscores the need for proactive policymaking to mitigate short-term economic shocks. A comprehensive approach, considering these interconnected factors, will be critical for SSA's governments to create a stable economic environment, ultimately fostering resilience and prosperity in the region.