Goodluck Peter Massawe

Understanding the geographic distribution of mammal species is essential for informed conservation planning, maintaining local ecosystem stability, and addressing research gaps, particularly in data-deficient regions. This study investigated the distribution and richness of 20 mammal species within Nyerere National Park (NNP), a large and understudied protected area in Southern Tanzania. We applied species distribution models (SDMs) using presence data collected through ground surveys between 2022 and 2024, combined with environmental variables derived from remote sensing, including land surface temperature, vegetation indices, soil moisture, elevation, and proximity to water sources and human infrastructure. Models were constructed using the Maximum Entropy (MaxEnt) algorithm, and performance was evaluated using the Area Under the Curve (AUC) metric, yielding high accuracy ranging from 0.81 to 0.97. Temperature (32.3%) and vegetation indices (23.4%) emerged as the most influential predictors of species distributions, followed by elevation (21.7%) and proximity to water (14.5%). Species richness, estimated using a stacked SDM approach, was highest in the northern and riparian zones of the park, identifying potential biodiversity hotspots. This study presents the first fine-scale SDMs for mammal species in Nyerere National Park, offering a valuable ecological baseline to support conservation planning and promote sustainable ecotourism development in Tanzania’s southern protected areas.

Understanding community attitudes towards urban forests is of great importance since these attitudes are inherently linked to the long-term sustainability of urban forests management and conservation. We analysed the attitudes of the local community towards the Njiro forest (Arusha, Tanzania) which is managed and used as an experimental beekeeping area by TAWIRI (Tanzania Wildlife Research Institute). Data collection was done between September-October 2018 involving a sample of 163 randomly selected respondents. A semi-structured questionnaire was used to collect the data. Quantitative data were analysed through Statistical Packages for Social Sciences (SPSS). Chi-square tests and contingency tables were used to determine whether there was a significant difference between the expected frequencies and the observed frequencies in one or more categories. Possible influences coming from sociological and demographic factors such as age, gender, education level, occupation were assessed. The majority of the respondents declared to gain ecological benefits from the forest. A significantly larger group of older respondents in comparison with the younger ones (p<0.05) declared to face problems coming from the forest (stray dogs, robbers, illegal waste disposal). Males showed to be more interested in practising beekeeping than females (p<0.05). Respondents with a primary education level were more prone to express agreement with the adopted management strategies in comparison with respondents with higher education (p<0.001). In conclusion, the great majority of respondents declared to support the conservation of Njiro forest, however, employed respondents and females were more positive regarding the hypothesis of abolishing the forest (p<0.05). In order to improve management strategies and support the long-term conservation of the forest, respondents recommended strengthening the protection of the forest by fencing it, providing environmental education to the surrounding community, reinforcing the cooperation with the local community and planting new trees to improve the health of the forest ecosystem.