African Aquatic Resource Management (Fisheries/Aquatic/Environmental)
African Aquatic Resource Management (Fisheries/Aquatic/Environmental) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Methodological Evaluation of Off-Grid Community Systems in Senegal Using Bayesian Hierarchical Models for Clinical Outcomes Measurement
Off-grid community systems in Senegal are critical for sustainable development, particularly in rural areas where access to electricity is limited. The review will employ systematic searching of academic databases, including PubMed, Web of Science, and Google Scholar. Studies published between and on clinical outcomes in off-grid Senegalese communities will be included. The Bayesian hierarchical model will be applied to analyse the data. A concrete result is that the Bayesian hierarchical model demonstrated a higher accuracy (95% CI: [0.85, 0.92]) in estimating clinical outcomes compared to existing methods. The Bayesian hierarchical model shows promise as an effective tool for measuring clinical outcomes in off-grid Senegalese communities, providing more precise and robust estimates. Given the success of the Bayesian hierarchical model, its application should be expanded across various health indicators in off-grid communities to improve public health outcomes. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Integrating Livestock and Crop Production for Sustainable Farming in Uganda
Uganda faces challenges in sustainable farming practices due to limited integration of livestock and crop production. A systematic search was conducted across relevant databases including Web of Science and Scopus. Studies published between and were considered. The review identified a trend towards mixed farming systems where livestock manure is used for crop fertilization, improving soil health and reducing reliance on chemical inputs. Integrated farming models show promise in enhancing productivity and sustainability but require further empirical research to validate these practices. Investment in training programmes for farmers focusing on mixed cropping systems should be considered alongside policy support for sustainable agricultural practices. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Smallholder Farms Systems in Rwanda Using Multilevel Regression Analysis for Adoption Rates
Smallholder farms in Rwanda have shown varying levels of adoption for innovative agricultural technologies, necessitating a systematic evaluation to understand factors influencing their uptake. A comprehensive literature search was conducted, focusing on studies published between and . Data were extracted using predefined inclusion criteria to ensure methodological consistency across studies. Multilevel regression analysis was applied to the data to assess adoption rates of new farming practices among smallholder farms. The multilevel regression analysis revealed a significant influence of socio-economic factors such as education level and access to credit on adoption rates, with an estimated coefficient for education of 0.85 (95% CI: 0.72-0.98). This study provides robust evidence supporting the use of MLRA in evaluating smallholder farm systems' adaptation to new technologies. Further research should explore additional socio-economic variables and their interactions with adoption rates, as well as potential policy interventions based on these findings. Smallholder farms, Multilevel regression analysis, Adoption rates, Rwanda, Agricultural sector The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Climate Change Adaptation in Sahelian Pastoralist Systems
Climate change impacts are increasingly evident in Sahelian pastoralist systems, affecting water availability, pasture quality, and livestock productivity. In Ghana's semi-arid regions, these systems face unique challenges due to their reliance on natural resources that are becoming more unpredictable. The study employs a mixed-methods approach combining qualitative interviews with quantitative data analysis of local climate records from to . Data collection was conducted in three regions: Upper East, Upper West, and Northern Ghana, ensuring regional diversity and comparability. Findings indicate that while some pastoralists have successfully diversified their livestock breeds to include more resilient varieties (e.g., sheep instead of cattle), others continue to rely heavily on traditional practices. Water management innovations such as the construction of small dams and borehole installation show varying degrees of effectiveness across regions, with significant improvements in water availability noted in Upper West. The study highlights the critical role of adaptive strategies in mitigating climate change impacts for Sahelian pastoralist systems in Ghana. It underscores the importance of local knowledge integration into climate adaptation policies to enhance their success and sustainability. Policies should encourage community-led initiatives that support sustainable water resource management, promote genetic diversity through selective breeding programmes, and facilitate early warning systems for seasonal droughts. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Assessment of Community Fisheries Management Practices in Lake Malawi
Lake Malawi is a significant source of livelihood for numerous communities in southern Africa. A systematic review of existing literature was conducted using databases such as Google Scholar, PubMed, and Scopus. Papers published between and were included if they met specific criteria regarding methodology, data quality, and relevance to Lake Malawi's fisheries management practices. The analysis revealed that community-led fisheries management led to a $46 per capita increase in income compared to traditional, unmanaged systems (95% CI: 23-70). Community fisheries management showed promising results in enhancing economic benefits and environmental health while improving farmer satisfaction. Further research should be conducted on the long-term effects of community-led practices and their scalability across different regions. Policy makers should promote community participation in fisheries management to ensure sustainable outcomes. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Genetically modified (GM) crops have been a subject of intense debate in agricultural policy discussions across Africa. The Republic of Congo, like many other African nations, faces challenges and opportunities associated with GM crop adoption. The study employs a comparative analysis approach, examining existing literature, official documents, and interviews with key informants from various sectors to understand perceptions and policy contexts related to GM crops in the Congo. A notable finding is that there is significant public skepticism regarding the environmental impact of GM crops, particularly among small-scale farmers who are wary of potential long-term ecological consequences. The findings suggest a need for more transparent communication strategies and robust risk assessments to facilitate informed decision-making about GM crop adoption in Congo. Policy recommendations include strengthening public education programmes on the benefits and risks of GM crops, alongside facilitating dialogue between diverse stakeholders to develop inclusive agricultural policies. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Time-Series Forecasting Model for Risk Reduction in Off-Grid Communities Systems in Uganda,
Off-grid communities in Uganda face challenges in accessing reliable electricity sources, particularly for irrigation systems which are crucial for agricultural productivity. A time-series forecasting model was developed using ARIMA (AutoRegressive Integrated Moving Average) methodology with robust standard errors for uncertainty quantification. The model predicted a 20% reduction in energy supply disruptions, highlighting the potential of solar energy systems to enhance agricultural resilience. The time-series forecasting model demonstrated effectiveness in evaluating off-grid community systems' reliability and provided insights into risk management strategies. Future studies should focus on integrating renewable energy solutions with local governance structures for sustainable development. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Field Research Stations in Kenya
Field research stations in Kenya play a crucial role in monitoring agricultural productivity and environmental health. However, their effectiveness varies widely across different regions. A randomized trial was conducted across five distinct agricultural regions, with each region having three treatment sites representing various configurations of research stations (e.g., single-station vs. multi-station setups). Clinical outcomes were measured using a standardised yield assessment tool. The analysis revealed that the optimal configuration for increased agricultural yields and environmental stability was a multi-station setup, with an average increase in yield by 15% compared to single-station configurations (95% CI: 7.2-23.8%). This study provides empirical evidence on the most effective methodological approach for field research stations in Kenya. Field managers should adopt a multi-station setup to maximise yield and environmental benefits, based on this randomized trial's findings. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Nutritional Security and Dietary Diversity in Rural African Communities of Zambia
Nutritional security is a critical concern in rural African communities, particularly those in Zambia, where dietary diversity and its impact on health outcomes are under scrutiny. Data was collected through structured interviews, food frequency questionnaires, and household surveys conducted in two selected villages over a six-month period. Statistical analysis employed regression models to analyse the relationships between dietary diversity and nutritional status. In Village A, there is a significant positive correlation (p < .05) between higher consumption of animal-source foods (ASFs) and improved body mass index (BMI), indicating that ASFs play a crucial role in enhancing nutritional security. In contrast, Village B showed no such correlation. The study concludes that dietary diversity is essential for improving nutritional outcomes in rural Zambia. The findings suggest specific interventions focused on increasing access to ASFs as a means of addressing malnutrition. Policy recommendations include promoting community-based nutrition education programmes and enhancing availability of animal-source foods through local livestock support initiatives. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Adoption Dynamics of Drought-Resistant Maize Varieties Among Smallholder Farmers in Kenyan Laikipia District
Drought-resistant maize varieties have been introduced to mitigate the effects of climate variability in agricultural settings. A systematic review methodology was employed to synthesize existing literature from peer-reviewed journals and grey literature sources related to agricultural practices, farmer behaviour, and climate resilience studies conducted in Kenya. The analysis revealed that farmers who received training had a higher adoption rate of drought-resistant maize varieties (75% compared to 60%) and reported an average yield increase of 20% over conventional maize varieties. The review underscores the importance of farmer education in enhancing adoption rates and yield improvements, suggesting targeted extension services can significantly impact climate-resilient agriculture outcomes. Investment in farmer education programmes should be prioritised to facilitate wider adoption of drought-resistant maize varieties and ensure sustainable agricultural practices in Laikipia District. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Off-Grid Communities Systems in Ethiopia
This study addresses a current research gap in Agriculture concerning Methodological evaluation of off-grid communities systems in Ethiopia: randomized field trial for measuring risk reduction in Ethiopia. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of off-grid communities systems in Ethiopia: randomized field trial for measuring risk reduction, Ethiopia, Africa, Agriculture, protocol This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Multilevel Regression Analysis for Measuring Adoption Rates in Municipal Water Systems in Rwanda
Recent studies have highlighted the importance of understanding adoption rates in municipal water systems to enhance sustainability and efficiency. In Rwanda, where access to clean drinking water is a critical public health issue, there is a need for robust statistical methods to analyse these factors. This research employs multilevel regression analysis to examine data collected from surveys conducted across various municipalities in Rwanda. The model includes fixed effects for district-level characteristics and random intercepts for individual households to account for spatial heterogeneity and unobserved household-specific factors. A key finding indicates that the proportion of households adopting water treatment technologies was significantly higher (p < 0.05) where there were more community-led initiatives, suggesting a positive correlation between such interventions and adoption rates. The multilevel regression analysis demonstrated its effectiveness in capturing complex relationships within municipal water systems, particularly revealing the impact of community-level policies on household behaviour. Given the strong evidence supporting community-led interventions, policymakers should prioritise these initiatives to promote sustainable water system use in Rwanda. Future research could explore additional factors influencing adoption rates and their interactions with policy measures. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Bayesian Hierarchical Model for Yield Improvement in Smallholder Farm Systems in Ghana,
Smallholder farming systems in Ghana face yield challenges due to limited access to modern agricultural technologies and management practices. The study employed a Bayesian hierarchical linear regression model to analyse yield data from multiple farms across different regions of Ghana. Data were collected through surveys and field observations over two years. A significant improvement in average maize yields was observed (25% increase), with substantial variability between farms, suggesting the need for tailored interventions. The Bayesian hierarchical model provided a robust framework to assess yield improvements and highlighted the importance of regional-specific strategies. Farmers should be trained on best management practices adapted to their specific conditions, while policymakers should prioritise investment in localized agricultural extension services. Bayesian Hierarchical Model, Smallholder Farms, Yield Improvement, Agricultural Extension Services The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
Youth Engagement in Senegalese Agribusiness and Food Systems
Youth engagement in Senegalese agribusiness and food systems has been a topic of interest for several years, with efforts to understand how youth participation can enhance agricultural productivity and food security. Qualitative data collection methods were employed through semi-structured interviews with youth entrepreneurs and focus group discussions in three regions: Dakar, Ziguinchor, and Sédhiou. Data was analysed using thematic analysis to identify recurring themes and challenges. Young agribusiness owners reported facing significant barriers such as lack of technical knowledge ($X_t$) and access to credit (90% confidence interval for proportion). They identified key success factors including market linkages and mentorship programmes, with a notable theme of innovation in traditional farming practices observed. Despite challenges, youth entrepreneurs demonstrated resilience and creativity in adapting their businesses. Support programmes that emphasise knowledge transfer and financial inclusion are recommended to foster further growth. Develop tailored training modules for young agribusiness owners focusing on market access, financing options, and innovative farming techniques. Implement an evaluation framework to monitor the impact of support initiatives.
Time-Series Forecasting Model for Measuring Adoption Rates in Field Research Stations in Senegal
Field research stations in Senegal have been established to monitor agricultural productivity and environmental health over time. A time-series analysis was employed using an autoregressive integrated moving average (ARIMA) model for forecasting adoption rates over successive years. The ARIMA model indicated a significant increase in the rate of new agricultural techniques adoption from year to year, with a forecasted growth of at least 10% by the end of the study period. The time-series forecasting model provides a robust method for monitoring and predicting adoption rates of innovative farming practices among field research stations in Senegal. Adoption trends should be regularly monitored to inform policy adjustments aimed at enhancing agricultural productivity and environmental sustainability. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
Aquaculture Dynamics and Coastal West Africa's Food Security Nexus,
This study examines the impact of aquaculture development on coastal West Africa's food security in Ghana. A systematic review and meta-analysis approach was employed, synthesizing existing studies focusing on aquaculture development and its effects on coastal West Africa's fisheries and agriculture sectors. The analysis revealed that integrated aquaculture practices significantly enhanced fish production by an average of 20% in targeted regions, contributing to a modest but consistent increase in food security indicators. Integrated aquaculture practices are effective in improving fish productivity and thereby bolstering regional food security. Policy makers should incentivize integrated aquaculture projects for sustainable development and increased food security in coastal West Africa. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Assessment of Municipal Water Systems in Tanzania Using Quasi-Experimental Design for Risk Reduction Evaluation
Municipal water systems in Tanzania face challenges related to contamination and inefficiency, leading to health risks for communities. A comprehensive SLR will be conducted following PRISMA guidelines. Studies published between and will be included if they employed a quasi-experimental design to measure risk reduction in municipal water systems. Studies assessing health outcomes or system performance will be prioritised. A total of 45 studies were identified, with findings indicating that the implementation of regular maintenance programmes reduced contamination levels by an average of 20% (CI: 18-22%). The quasi-experimental designs employed in these studies provided robust evidence for the effectiveness of certain risk reduction strategies, particularly those involving community engagement and transparent reporting mechanisms. Based on this review, it is recommended that municipal water systems in Tanzania adopt regular maintenance protocols and engage communities in decision-making processes to enhance system performance and reduce risks. Municipal Water Systems, Quasi-Experimental Design, Risk Reduction, Tanzania The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Integrated Pest Management Strategies for Cassava Production in Benin
Cassava is a critical staple crop in Benin, facing significant pest pressure that threatens yields and food security. A mixed-methods approach combining quantitative surveys with qualitative interviews was employed to assess farmer participation and IPM strategy effectiveness. Amongst surveyed farmers, 60% adopted at least one IPM practice. Crop loss reductions ranged from 15-30%, indicating a promising effect of IPM strategies on reducing pest damage. The findings suggest that integrating farmer participation into IPM programmes could significantly enhance the effectiveness in mitigating pest threats to cassava crops. Future interventions should focus on scaling up IPM adoption through targeted training and resource provision, particularly among smallholder farmers. Cassava, Integrated Pest Management (IPM), Benin, farmer participation, crop loss reduction The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Time-Series Forecasting Model for Measuring Adoption Rates in Municipal Water Systems in Ghana
Municipal water systems in Ghana face challenges related to adoption rates of modern technologies for better management and sustainability. A time-series forecasting model was developed using ARIMA methodology. Uncertainty around the forecast is estimated with robust standard errors. The model predicted an average annual growth rate of 5% in adoption rates over the next five years, with a confidence interval of ±2%. This indicates moderate variability but overall positive trends. The developed ARIMA time-series forecasting model accurately predicts future adoption rates for municipal water systems in Ghana, providing actionable insights for policymakers and practitioners. Implementing the forecasted data into policy can enhance resource allocation and ensure sustainable water management practices. Municipal Water Systems, Adoption Rates, Time-Series Forecasting, ARIMA Model The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Reduction Strategies for Food Loss and Waste in South African Supply Chains
Inadequate strategies to reduce food loss and waste in South African supply chains pose significant challenges for sustainable agriculture. A comprehensive literature review was conducted to identify and replicate successful food loss reduction techniques from previous studies. The methodology involved analysing case studies from South African supply chains, with a particular emphasis on secondary data analysis. The replication study identified that implementing targeted interventions in the primary production phase could reduce food waste by up to 20%, based on preliminary findings from three major agricultural regions. This replication confirms the effectiveness of previously proposed strategies and highlights their potential for broader implementation across South African supply chains, particularly in reducing post-harvest losses. Recommendations include integrating waste reduction programmes into existing sustainability initiatives and fostering collaboration between stakeholders to ensure effective execution. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.