The economic and ecological trade-offs of wetland conversion for development projects: the case of the Kampala–Mukono corridor

Wetland diminution for development projects (DPs) in the Kampala–Mukono Corridor (KMC) continues to pose threats to the socio-economic and ecological benefits of wetlands because decision-makers and wetland users at various levels often have insufficient knowledge of these benefits. This situation has resulted in unsustainable development decisions that accord little weight to wetlands and have allocated many of them to DPs. In order to inform decision making for optimal development in the KMC, the present study analysed the spatial and temporal wetland loss to DPs, estimated the economic value of the KMC wetlands, and assessed the environmental consequences of wetland conversion for DPs. Sets of ortho-rectified and cloud-free multi-temporal Landsat MSS (1974) and Landsat TM/ETM+ images (30m) for 1986, 2006, and 2013 were analysed in a spatial and temporal framework. The 79m Landsat image (MSS) of 1974 was resampled and later filtered with subsequent 30m images using a majority filter method. An unsupervised classification approach was employed to characterize the wetlands and associated DPs. The classified DPs and wetland cover types were validated by reference to topographical maps (sheets) of 1974 at a scale of 1:50,000 obtained from Uganda Lands and Surveys, apriori knowledge and Google earth images corresponding to the same spatial and temporal frames. The IDRISI Selva-based Markov Chain model was employed to model future wetland loss to DPs. The Total Economic Valuation Approach (TEV) was employed to quantify selected use values of wetland economic benefits using the market price, replacement cost and contingent valuation techniques. The ecological implications of wetland loss focused on soil organic carbon (SOC) and hydrological impacts in the KMC wetlands. The estimated SOC was assessed with climatic data in order to infer the implication of SOC loss for local climate variability. The manual wet chemistry/oxidation method by Walkley-Black (1934) was adopted to estimate SOC in various wetland cover types. Hydrological impact assessments focused on water quality analysis in various wetland cover types, with major parameters being total nitrogen (TN), total phosphorous (TP) total dissolved solids – (TDS) and total suspended sediments (TSS). Hydrologic flow data parameters across the different wetland cover types in the KMC focused on water level, speed, stream width, and bed load. Results from analysis of the spatial-temporal wetland change revealed that by 2013 the KMC wetlands had lost almost half (47%) of their 1974 areal coverage, with 56% of this loss resulting from conversion to DPs. It is projected that 26% of the KMC wetlands will be lost to more DPs by 2040. Wetland loss is attributed to intensified economic activity and preference of Kampala as an industrial zone, weakness in the previous spatial planning of Kampala, and the general lack of information flow to various institutions involved in the establishment of DPs. The KMC wetlands provide a flow of economic benefits at a minimum approximated value of US$3,418 / ha / per year. It is revealed that a great deal of these economic benefits (88$ 19,311,700 in the sampled wetlands, and projections of future wetland loss put the minimum economic loss at US$ 48,368,118 by 2040. Continuous degradation of these wetlands means serious economic costs to the government and local communities, as reflected in high replacement expenditures for wetland services, foregone incomes, subsistence livelihood support and alternative employment. The highest carbon (C) sinks were identified in forest swamps, palms, thickets and wetlands converted to agriculture, which accounted for 25% of the KMC wetlands by 2013, while the lowest total soil organic carbon (TSOC) range occurred in converted wetland cover types (converted wetlands to industrial and settlements) that occupied 47% of the study area. A general decrease in SOC sequestration from 1974 to 2013 across the KMC wetlands is identified, with the lowest C pool registered in 2013. The dwindling SOC banks are considered to be partly responsible for varying climate and related feedbacks on wetland benefits in the KMC. The hydrologic impacts of wetland loss are felt mainly in converted wetland cover types, in the form of compromised water quality, with increased nutrient pollution and TSS. These all create negative impacts on wetland hydrological services, particularly filtration, flood attenuation, recharge and discharge benefits, all of which have profound effects on biodiversity. There is an urgent need to reduce the scale of wetland diminution in the KMC. This will be achieved if mitigation and conservation measures are undertaken. Mitigation measures should include a revision of development plans, user sensitization on wetland economic values and enforcement of regulatory mechanisms. Conservation strategies should involve the use of economic incentives and disincentives which include: a revision of historic property rights to regulate wetland use, performance bonds or subsidies for environmentally friendly activities and taxes, fees or fines for unacceptable levels of degradation and tradable permits that utilise the concept of ‘wetland banks’ to ensure no further loss of the KMC wetlands to DPs. Future research should focus on modelling the response of wetland ecosystems to multiple threats and management interventions, and on a feasibility study of wetland restoration options and the implications for local people’s livelihoods in the KMC

Heterogeneity in Nutritional and Biochemical Composition of Cassava Varieties in Uganda

Cassava (Manihot esculenta Crantz) has been prioritized by the New Partnership for African Development to spur development in Africa. However, the nutritional and biochemical composition of the cassava diversity has not been adequately assessed to inform the various user needs.  Comparative analysis of macro, micro nutrients and biochemical composition of sixteen varieties of cassava in Uganda was undertaken following standard analytical techniques. Results showed significant differences in macro nutrients (p ≤0.000)  except carbohydrate, starch and amylose contents. With the exception of Calcium and Iron, the varieties were significantly different (p ≤0.000) in micronutrient composition.  The Cyanide and dry matter content were also significantly different (p ≤0.000) among the varieties. Overall, Mukibi, Juguja, Bao, Nigeria,  ranked highest in dry matter, cyanide, macro and micronutrients content, respectively. Therefore varieties differ in nutritional and biochemical composition; information crucial in the development of new varieities and deployment of cassava diversity in various  value chains

Implications of Soil Properties on Landslide Occurrence in Kigezi Highlands of South Western Uganda

Generally, soil characteristics have a significant influence on landslide occurrence. This issue has, however, not yet been adequately analysed in Kigezi highlands of South Western Uganda. In this study, soil properties such as dispersion, grain size distribution, Atterberg limits, shear strength and clay mineralogy were analysed to establish their contribution to the spatial distribution of landslides in Kigezi highlands. The results demonstrate that deep soil profiles ranging between 2.5 and 7 meters were dominated by clay-pans at a depth between 0.75 and 3 meters. Although the uppermost surface horizons of the soil profile are loamy sand, the clay content is more than 35% especially in the sub soil. This suggests that the soil materials are Vertic in nature. In addition, the upper soil layers predominantly contain quartz, while subsurface horizons have considerable amounts of illite as the dominant clay minerals, ranging from 43–47%. The average liquid limit and plasticity index was 58.43% and 33.3% respectively. Besides, high average computed weighted plasticity index (28.4%) and expansiveness (38.6%) were obtained. These soil characteristics have great implication on the timing and nature of landslide processes in the study area. A change in soil material due to varying moisture content is thought to be a major trigger of landslides in Kigezi highlands of South Western Uganda. This understanding of soil characteristics is a key step in mitigating landslide hazards in the area

Implications of Land Use and Cover Changes on Upper River Rwizi Macro-Watershed Health in South Western Uganda

The upper Rwizi river system in South Western Uganda has been severely degraded due to encroachment and unsustainable resource utilization. Little is, however, known about the link between the upper Rwizi macro-watershed health and land use/cover patterns from the spatiotemporal perspective. This study evaluated the relationship between spatiotemporal land use/ cover change and upper river Rwizi macro watershed health. Remotely sensed data was used to analyze the spatiotemporal land use and cover distribution for upper Rwizi macro watershed. The analysis was done using Landsat and Sentinel imagery datasets spanning 1990 to 2020 and 2016 to 2021 respectively. Field verification was undertaken to confirm the land use, cover types, and evaluate the implications of prevailing anthropogenic activities on the watershed health. The land use and cover characteristics in the upper Rwizi macro-watershed exhibits both highly spatial and temporal variations. By 1990, grassland as the dominant land use and cover type spanned 45% of the total study area followed by farmland at 30%. Forests, open water and settlements covered 12%, 10% and 3% respectively. Whereas grassland and forest cover has diminished drastically by 64% and 71% respectively, settlements and farmland have increased tremendously by 79% and 50% respectively between 1990 and 2020. The hillslope hydrological characteristics in the watershed are severely hampered due to increased human activities. It is, therefore, recommended that afforestation in the degraded areas be undertaken to restore the watershed health which could improve on hillslope hydrology

The damage caused by landslides in socio-economic spheres within the Kigezi highlands of South Western Uganda

An assessment of the socio-economic implications of landslide occurrence in the Kigezi highlands of South Western Uganda was conducted. Landslide occurrence is on the increase and threatens community livelihoods in these highlands. Detailed field investigations were undertaken with the help of local communities between June 2018 and May 2020 to identify and map recent and visible landslide scars in Rukiga uplands of Kigezi highlands. In the course of field inventories, 85 visible landslide scars were identified and mapped using handheld GPS receivers to produce a landslide distribution map for the study area. A socio-economic analysis was conducted to establish the effects of landslide damage on people’s livelihoods as well as their existing coping and adaptation mechanisms. The assessment was administered through field observations and surveying, focus group discussions, key informants and household interviews as well as the use of Local Government Environmental Reports. The study established an increase in the spatial-temporal distribution of landslides over the Kigezi highlands in the past 40 years. The landslides have resulted in a reduction in the quality of land, loss of lives, destruction of transport infrastructures, settlements, farmlands, crops and other socio-economic infrastructures. Therefore, it is important to look for reliable and sustainable measures to prevent landslide hazards. Total landscape reforestation with deep-rooted trees can possibly reduce the landslide risk. It is also important to undertake policy implementation for preparedness and mitigation plans against landslides in this region and in the country at large. Proper soil and water conservation measures could help in enhancing soil strength against landslide hazards

Community Seedbanks in Uganda: Fostering Access to Genetic Diversity and Its Conservation

Community seedbanks promote conservation and the use of crop genetic diversity, as well as supporting farmer seed systems. This study analyses seed flow and access to crop genetic diversity over time in the Nakaseke, Rubaya, and Kibuga seedbanks of Uganda. The modes of operation of the banks were compared through scrutinizing records of crops and varieties being conserved, quantities of seed distributed, to whom, and quantities returned. The Nakaseke seed bank distributed the highest varietal diversity of common bean (Phaseolus vulgaris) and groundnuts (Arachis hypogaea L.), whereas the Rubaya seedbank distributed the highest quantity of common bean seed, followed by the Kibuga seedbank. There were no significant differences between the type of variety of seed, quantities of seed accessed, and seed returned to the seedbanks by women and men—except for the Nakaseke seedbank, where women returned significantly higher quantities of common bean seed. The Kibuga and Rubaya seedbanks dealt with individual farmers, whereas the Nakaseke seedbank dealt with individual farmers and groups. The extent to which core functions were achieved by a particular seedbank depended on the mode of operation, including actors, management, degree of development, socio-economic setting, among others. Further research is recommended to unpack these factors and come up with the most appropriate combinations for greater seedbank effectiveness

Community Seedbanks in Uganda: Fostering Access to Genetic Diversity and Its Conservation

Community seedbanks promote conservation and the use of crop genetic diversity, as well as supporting farmer seed systems. This study analyses seed flow and access to crop genetic diversity over time in the Nakaseke, Rubaya, and Kibuga seedbanks of Uganda. The modes of operation of the banks were compared through scrutinizing records of crops and varieties being conserved, quantities of seed distributed, to whom, and quantities returned. The Nakaseke seed bank distributed the highest varietal diversity of common bean (Phaseolus vulgaris) and groundnuts (Arachis hypogaea L.), whereas the Rubaya seedbank distributed the highest quantity of common bean seed, followed by the Kibuga seedbank. There were no significant differences between the type of variety of seed, quantities of seed accessed, and seed returned to the seedbanks by women and men—except for the Nakaseke seedbank, where women returned significantly higher quantities of common bean seed. The Kibuga and Rubaya seedbanks dealt with individual farmers, whereas the Nakaseke seedbank dealt with individual farmers and groups. The extent to which core functions were achieved by a particular seedbank depended on the mode of operation, including actors, management, degree of development, socio-economic setting, among others. Further research is recommended to unpack these factors and come up with the most appropriate combinations for greater seedbank effectiveness

Bayesian belief network modelling approach for predicting and ranking risk factors for malaria infections among children under 5 years in refugee settlements in Uganda

Abstract Background Malaria risk factors at household level are known to be complex, uncertain, stochastic, nonlinear, and multidimensional. The interplay among these factors, makes targeted interventions, and resource allocation for malaria control challenging. However, few studies have demonstrated malaria’s transmission complexity, control, and integrated modelling, with no available evidence on Uganda’s refugee settlements. Using the 2018–2019 Uganda’s Malaria Indicator Survey (UMIS) data, an alternative Bayesian belief network (BBN) modelling approach was used to analyse, predict, rank and illustrate the conceptual reasoning, and complex causal relationships among the risk factors for malaria infections among children under-five in refugee settlements of Uganda. Methods In the UMIS, household level information was obtained using standardized questionnaires, and a total of 675 children under 5 years were tested for malaria. From the dataset, a casefile containing malaria test results, demographic, social-economic and environmental information was created. The casefile was divided into a training (80%, n = 540) and testing (20%, n = 135) datasets. The training dataset was used to develop the BBN model following well established guidelines. The testing dataset was used to evaluate model performance. Results Model accuracy was 91.11% with an area under the receiver-operating characteristic curve of 0.95. The model’s spherical payoff was 0.91, with the logarithmic, and quadratic losses of 0.36, and 0.16 respectively, indicating a strong predictive, and classification ability of the model. The probability of refugee children testing positive, and negative for malaria was 48.1% and 51.9% respectively. The top ranked malaria risk factors based on the sensitivity analysis included: (1) age of child; (2) roof materials (i.e., thatch roofs); (3) wall materials (i.e., poles with mud and thatch walls); (4) whether children sleep under insecticide-treated nets; 5) type of toilet facility used (i.e., no toilet facility, and pit latrines with slabs); (6) walk time distance to water sources (between 0 and 10 min); (7) drinking water sources (i.e., open water sources, and piped water on premises). Conclusion Ranking, rather than the statistical significance of the malaria risk factors, is crucial as an approach to applied research, as it helps stakeholders determine how to allocate resources for targeted malaria interventions within the constraints of limited funding in the refugee settlements

Integrated modelling of the determinants of household food insecurity during the 2020–2021 COVID-19 lockdown in Uganda

Abstract Background The determinants of household food insecurity (HFI) do not act in isolation, and are known to be complex, stochastic, nonlinear, and multidimensional. Despite this being especially true in periods of shocks, studies that focus on integrated modelling of the HFI determinants during the COVID-19 lockdown are scarce, with no available evidence on Uganda. The main objective of this study was to develop Bayesian belief network (BBN) models to analyse, rank, and illustrate the conceptual reasoning, and complex causal relationships among the determinants of HFI during the COVID-19 lockdown. This study was based on seven rounds of Uganda’s High-Frequency Phone Surveys data sets collected during the lockdown. A total of 15,032 households, 17 independent determinants of HFI, and 8 food security indicators were used in this study. Metrics of sensitivity, and prediction performance were used to evaluate models’ accuracy. Results Eight BBN models were developed for each food insecurity indicator. The accuracy rates of the models ranged between 70.5% and 93.5%, with an average accuracy rate of 78.5%, indicating excellent predictive performance in identifying the determinants of HFI correctly. Our results revealed that approximately 42.2% of the sampled households (n = 15,032) in Uganda were worried about not having enough food. An estimated 25.2% of the respondents reported skipping a meal, while 32.1% reported consuming less food. Less than 20% of the households experienced food shortage, hunger, or having nothing to eat. Overall, 30.6% of the households were food insecure during the lockdown. The top five ranked determinants of HFI were identified as follows: (1) households’ inability to produce enough food; (2) households’ inability to buy food; (3) reduced household income; (4) limited cash assistance, and (5) households’ inability to stock adequate food supplies. Conclusions Ranking, rather than the statistical significance of the determinants of HFI, is crucial as an approach to applied research, as it helps stakeholders determine how to allocate resources for targeted interventions within the constraints of limited funding. These findings emphasize the importance of intervening on the most highly ranked determinants of HFI to enhance the resilience of local food systems, and households’ capacity to cope with recurring and unforeseen shocks