JOURNAL OF THE GEOGRAPHICAL ASSOCIATION OF TANZANIA

Is Convivial Conservation A Solution for Human-Wildlife Interactions Around Protected Areas?

Ruth Wairimu John — Mon, 30 Jun 2025 00:00:00 +0000

Conserving biodiversity requires resolving human-wildlife conflicts in protected areas. Conservation NGOs, community-based organisations, governments, development agencies, and donors have debated these strategies to anticipate fundamental changes. Humans' biggest challenge is co-existing with animals during biodiversity extinction, as wild animals kill humans annually, prompting retaliation. Balancing nature conservation and economic viability is threatening. Community-based conservation balances conservation with development. This article examines the shortcomings of human-wildlife conflict resolution methods using Selous Game Reserve in Tanzania as a case study. It expands on Buscher and Fletcher's "convivial conservation" proposal, which promotes fundamental equity, organisational transformation, and environmental justice to create a more equitable and sustainable global community (Buscher and Fletcher, 2019). Convivial conservation addresses social, cultural, ecological, and political-economic issues affecting humans and biodiversity. Community-based organisations around protected areas were supposed to benefit local communities, but they have distorted livelihoods, increased human-wildlife conflicts, and destabilised local resource institutions without compensation. Similarly, human-animal conflicts can have a substantial impact on poverty by increasing illegal activities. Political ecology perspectives and convivial conservation will be used to suggest methods for resolving human-wildlife conflicts. The analysis is based on empirical data from published studies and extensive field research conducted in the study area through interviews, surveys, group discussions, and direct observations using narratives and narration.

An Analysis of the Impacts of Climate Variability on Smallholder Farmers’ Livelihood Assets in the Kilimanjaro Region, Tanzania

Saumu Mwasha — Fri, 27 Jun 2025 00:00:00 +0000

Climate variability is emerging as a significant challenge that affects local livelihood in developing countries. This paper seeks to analyse the multifaceted ways that climate variability affects smallholder farmers’ livelihoods in Kilimanjaro region, across villages located in three agro-ecological zones. It analyses the impact of climate variability on livelihood assets and its implications on farmers’ ability to make a living. Data for this paper were collected through a rigorous process of homogenous focus group discussions, household surveys, and key informants’ interviews. These methods were carefully chosen to ensure validity and reliability of data. Qualitative data were analysed thematically while quantitative data analysis was carried out using Statistical Package for Social Sciences. The results indicate that the impact of climate variability on financial assets involve decrease in income and increase in farming costs. It also affects natural capital by diminishing the supply of surface water and thus limiting irrigation practices. The study also suggests that climate variability affects social capital by decreasing household and community support, primarily through poor harvests. The results further establish that climate variability through increase in temperature affects human health and reduces labour force due to the prevalence of malaria and climate-induced migration. More effective adaptation measures are recommended to increase farmers’ capacity to adapt to existing climate variability, and help them protect and improve their livelihood assets.

Land Use and Land Cover Change and Its Drivers in Lake Singida Catchment, Tanzania, East Africa

Juvenary Madyanga, Joel Nobert, Edmund Mabhuye — Mon, 30 Jun 2025 00:00:00 +0000

Lakes and their catchments provide essential resources and ecosystem services. However, these global resources are impacted by various anthropogenic activities that drive changes in land use and land cover. The study that generated data for this paper used Landsat TM (1991), ETM+ (2000, 2010), and OLI (2020) satellite imagery to examine land use and land cover change in the Lake Singida catchment. To identify drivers for change, we engaged 19 key informants, conducted surveys of 382 household heads, and reviewed secondary data, including meteorological records, population statistics, and the FAO/UNESCO soil database. We employed purposive sampling for key informants, and random sampling for household heads. Land use types were categorized using supervised classification with the maximum likelihood classifier in ArcMap 10.7. The qualitative data were analysed through content analysis in MAXQDA (version 20), while quantitative data were assessed using IBM SPSS Statistics (version 21) and Microsoft Excel, 2016. The results depict an increase in agricultural land, bare land, built-up area and water body features by 1%, 29%, 13%, and 2%, respectively; and a decrease of bushland and grassland by 7% and 40%, respectively. The key drivers of these changes include climate change, poor soil conditions, population growth, in-migration, land demand, mode of land ownership, land size, urbanization, livestock grazing, human-induced fires, grass-cutting, and traditional salt extraction. These results offer valuable insights into land use dynamics, and highlight the need for sustainable land use planning to conserve natural habitats in the Lake Singida catchment; hence informing broader environmental policy.

Drivers of Informal Settlement Growth and Land Use Change in Dar es Salaam: Insights from Remote Sensing and GIS (1995-2024)

Olipa Simon, Zakaria Robert Ngereja — Fri, 27 Jun 2025 00:00:00 +0000

Rapid urbanization presents critical challenges, particularly in managing the growth of informal settlements. Effective urban planning is essential to address this issue, yet it often falls short in rapidly growing cities like Dar es Salaam. This study aims to explore the drivers behind informal settlement expansion and assess the consequences of inadequate urban planning. This study integrates quantitative analysis using Landsat imagery and spatial analysis with ArcGIS Pro, alongside qualitative data from focus groups and interviews. Land cover changes from 1995 to 2024 were evaluated using supervised image classification, employing a machine learning random forest classifier in R to create land use/land cover classes. The analysis reveals significant changes in land use. Agricultural areas increased from 396.7 km² to 555.17 km², while built-up areas expanded from 72.55 km² to 403.44 km². In contrast, forest, bushland, and grassland areas declined significantly. Key drivers of informal settlement growth include financial constraints, political interference, formalization challenges, and poor coordination among stakeholders. Financial limitations impede comprehensive planning and infrastructure development, while political interference weakens land-use policies. Bureaucratic and financial barriers to formalization lead to unauthorized construction, and a lack of institutional coordination exacerbates fragmented planning and informal industrial growth. Addressing the rapid expansion of informal settlements requires financial investment, political commitment, improved coordination, and public awareness to support sustainable urban planning. The study presents a novel approach by integrating quantitative analysis using Landsat imagery and machine learning techniques with qualitative insights from focus groups and interviews, providing a comprehensive examination of both spatial and socio-political drivers of informal settlement expansion in Dar es Salaam, and offering a unique perspective on land use changes and urban planning challenges