Search Results (354)

Since the end of the Civil War, Cambodia has pursued economic development to enhance livelihoods, particularly in rural areas, where land is a critical resource. Previous studies have indicated that the country has changed land use and land cover. However, they have not explained how these changes can improve the livelihoods of local communities, thereby mitigating their negative impacts through an asset-based approach. Battambang Province, in the northwestern region, was the battleground until political integration in 1996. Since then, the province has been home to immigrants exploring the lands for livelihood. Thus, this study aims to examine agricultural livelihoods in the villages of Dei Kraham and Ou Toek Thla, located west of Battambang Town. These were selected because of their common characteristics. Adopting a quantitative approach and a sustainable livelihood framework, this study employed stratified random sampling to select 123 families for interviews across three population subgroups: old settlers, new settlers, and young settlers. In situ information was collected using structured questionnaires and analyzed using Kruskal–Wallis tests to assess the livelihood assets underlying the physical, natural, human, financial, and social capital. The statistical analysis results reveal no significant differences (p-value = 0.079) in livelihood assets between the strata at the village level. Meanwhile, significant differences were observed in physical, human, and financial capital between old and young settlers when examining the subgroups (p-value 0.000). The extent of the land resources held by old settlers was associated with household income and livelihoods related to agriculture. Based on livelihood asset scores, nearly half of the new settlers (0.49–0.5) and a quarter of the young settlers (0.47) are vulnerable groups requiring support. The youth will soon face an uncertain future if they do not prioritize education. Full article

This paper examines how demographic characteristics, institutional structures, and livelihood strategies shape household resilience to climate variability and drought in West Pokot County, one of Kenya’s most climate-vulnerable arid and semi-arid lands (ASALs). Using a mixed-methods approach, it combines household survey data with three statistical techniques: Multinomial Logistic Regression (MLR) assesses the influence of gender, age, and education on livestock ownership and livelihood choices; Multiple Correspondence Analysis (MCA) reveals patterns in institutional access and adaptive practices; and Stepwise Linear Regression (SLR) quantifies the relationship between resilience strategies and agricultural productivity. Findings show that demographic factors, particularly gender and education, along with access to veterinary services, drought-tolerant inputs, and community-based organizations, significantly shape resilience. However, trade-offs exist: strategies improving livestock productivity may reduce crop yields due to resource and labor competition. This study recommends targeted interventions, including gender-responsive extension services, integration of indigenous and scientific knowledge, improved infrastructure, and participatory governance. These measures are vital for strengthening resilience not only in West Pokot but also in other drought-prone ASAL regions across sub-Saharan Africa. Full article

Water insecurity, intensified by climate change, presents a significant challenge globally, especially in arid and semi-arid regions of Africa. In northern Ghana, where agriculture heavily depends on seasonal rainfall, prolonged dry seasons exacerbate water and food insecurity. Despite efforts to improve water access, there is limited understanding of how climate change preparedness affects water insecurity risk in rural contexts. This study investigates the relationship between climate preparedness and water insecurity in semi-arid northwestern Ghana. Grounded in the Sustainable Livelihoods Framework, data was collected through a cross-sectional survey of 517 smallholder households. Nested ordered logistic regression was used to analyze how preparedness measures and related socio-environmental factors influence severe water insecurity. The findings reveal that higher levels of climate change preparedness significantly reduce water insecurity risk at individual [odds ratio (OR) = 0.35, p < 0.001], household (OR = 0.037, p < 0.001), and community (OR = 0.103, p < 0.01) levels. In contrast, longer round-trip water-fetching times (OR = 1.036, p < 0.001), water-fetching injuries (OR = 1.054, p < 0.01), reliance on water borrowing (OR = 1.310, p < 0.01), untreated water use (OR = 2.919, p < 0.001), and exposure to climatic stressors like droughts (OR = 1.086, p < 0.001) and floods (OR = 1.196, p < 0.01) significantly increase insecurity. Community interventions, such as early warning systems (OR = 0.218, p < 0.001) and access to climate knowledge (OR = 0.228, p < 0.001), and long-term residency further reduce water insecurity risk. These results underscore the importance of integrating climate preparedness into rural water management strategies to enhance resilience in climate-vulnerable regions. Full article

This study investigates the gendered nexus between climate change, food insecurity, and conflict in Plateau State, Nigeria. This region in north-central Nigeria is marked by recurring farmer–herder clashes and climate-induced environmental degradation. Drawing on qualitative methods, including interviews, gender-disaggregated focus groups, and key informant discussions, the research explores how climate variability and violent conflict interact to exacerbate household food insecurity. The methodology allows the capture of nuanced perspectives and lived experiences, particularly emphasizing the differentiated impacts on women and men. The findings reveal that irregular rainfall patterns, declining agricultural yields, and escalating violence have disrupted traditional farming systems and undermined rural livelihoods. The study also shows that women, though they are responsible for household food management, face disproportionate burdens due to restricted mobility, limited access to resources, and a heightened exposure to gender-based violence. Grounded in Conflict Theory, Frustration–Aggression Theory, and Feminist Political Ecology, the analysis shows how intersecting vulnerabilities, such as gender, age, and socioeconomic status, shape experiences of food insecurity and adaptation strategies. Women often find creative and local ways to cope with challenges, including seed preservation, rationing, and informal trade. However, systemic barriers continue to hinder sustainable progress. This study emphasized the need for integrating gender-sensitive interventions into policy frameworks, such as land tenure reforms, targeted agricultural support for women, and improved security measures, to effectively mitigate food insecurity and promote sustainable livelihoods, especially in conflict-affected regions. Full article

Water, the lifeblood of our planet, sustains ecosystems, economies, and communities. However, climate change and increasing hydrological variability have exacerbated global water scarcity, threatening livelihoods and economic stability. According to the United Nations, over 2 billion people currently live in water-stressed regions, a figure expected to rise significantly by 2030. To address this urgent challenge, this study proposes an AI-driven anomaly detection framework for smart water metering networks (SWMNs) using machine learning (ML) techniques and data resampling methods to enhance water conservation efforts. This research utilizes 6 years of monthly water consumption data from 1375 households from Location A, Windhoek, Namibia, and applies support vector machine (SVM), decision tree (DT), random forest (RF), and k-nearest neighbors (kNN) models within ensemble learning strategies. A significant challenge in real-world datasets is class imbalance, which can reduce model reliability in detecting abnormal patterns. To address this, we employed data resampling techniques including random undersampling (RUS), SMOTE, and SMOTEENN. Among these, SMOTEENN achieved the best overall performance for individual models, with the RF classifier reaching an accuracy of 99.5% and an AUC score of 0.998. Ensemble learning approaches also yielded strong results, with the stacking ensemble achieving 99.6% accuracy, followed by soft voting at 99.2% and hard voting at 98.1%. These results highlight the effectiveness of ensemble methods and advanced sampling techniques in improving anomaly detection under class-imbalanced conditions. To the best of our knowledge, this is the first study to explore and evaluate the combined use of ensemble learning and resampling techniques for ML-based anomaly detection in SWMNs. By integrating artificial intelligence into water systems, this work lays the foundation for scalable, secure, and efficient smart water management solutions, contributing to global efforts in sustainable water governance. Full article

Understanding the complex and multidimensional nature of poverty is essential for designing effective and targeted policy interventions in rural Ethiopia. This study examined the determinants of multidimensional poverty in Bilate River Basin in South Ethiopia, employing cross-sectional household survey data collected in 2024. A total of 359 households were selected using a multistage sampling technique, ensuring representation across agro-ecological and socio-economic zones. The analysis applied the Generalized Ordered Logit (GOLOGIT) model to categorize households into four mutually exclusive poverty statuses: non-poor, vulnerable, poor, and extremely poor. The results reveal that age, dependency ratio, education level, livestock and ox ownership, access to information and credit, health status, and grazing land access significantly influence poverty status. Higher dependency ratios and poor health substantially increase the likelihood of extreme poverty, while livestock ownership and access to grazing land reduce it. Notably, credit use and access to information typically considered poverty reducing were associated with increased extreme poverty risks, likely due to poor financial literacy and exposure to misinformation. These findings underscored the multidimensional and dynamic nature of poverty, driven by both structural and behavioral factors. Policy implications point to the importance of integrated interventions that promote education, health, financial literacy, and access to productive assets to ensure sustainable poverty reduction and improved rural livelihoods in Ethiopia. Full article

Climate risk has emerged as a pressing global challenge, significantly undermining livelihood capital, income stability, and living standards among vulnerable populations. Leveraging balanced panel data from the China Household Finance Survey (CHFS) spanning 2013–2019, this study employs a binary Logit fixed-effects model to examine how climate change risk affects farm households’ multidimensional relative poverty, with particular attention to the moderating role of digital financial inclusion. The findings demonstrate that climate change risk significantly exacerbates multidimensional relative poverty among farm households, while digital inclusive finance effectively mitigates these adverse impacts. Notably, subdimensional analysis reveals that the depth of digital financial usage exerts the strongest influence. In addition, there is heterogeneity in this moderating effect, with digital inclusive finance having a more significant mitigating effect on multidimensional relative poverty in rural households in the central region, with middle and higher incomes, as well as with high digital literacy. This study provides valuable insights into the use of financial instruments to mitigate climate risks, improve the climate resilience of rural populations, and strengthen multidimensional approaches to poverty governance. Full article

With the nationwide completion of China’s large-scale Poverty Alleviation Relocation (PAR) initiative in 2020, the government’s poverty alleviation efforts have officially entered the “post-poverty era”. However, many regions still lack well-established sustainable development mechanisms and face a potential risk of returning to poverty. To better stabilize the achievements of poverty alleviation, this study examines the potential risk of returning to poverty after the first Five-Year Transition Period (2021–2025) from a livelihood space perspective and proposes optimization directions for PAR policies in future poverty reduction efforts. Research findings indicate that simply altering geographical conditions is insufficient to achieve stable poverty alleviation. The production space of relocated populations is vulnerable to the stability and precision in resource supply, which may lead to recurring poverty due to policy discontinuities and administrative preferences. Meanwhile, improvements in living spaces are constrained by imbalances in household income and expenditure. This study also found that, on the one hand, changes in residential patterns break the original boundaries of administrative villages by incorporating migrants from different villages into concentrated communities, leading to the expansion of weak-tie networks while, on the other hand, the relocation process disrupts some of the migrants’ original strong-tie networks, and the concentration and clustering of impoverished groups in relocation communities further lead to the contraction of these networks. Additionally, the unique characteristics of relocation communities generate exorbitant governance costs and population management difficulties that far exceed the service provision and administrative capacities of community organizations. In the long run, this situation proves detrimental to normalized community governance and dynamic poverty relapse monitoring and interventions. Accordingly, this study proposes relevant policy recommendations from the following four aspects, i.e., strengthening endogenous development capacity, improving social security mechanisms, expanding social support networks, and enhancing organizational governance capabilities, aiming to provide both a theoretical basis and a decision-making reference for future poverty alleviation efforts. Full article

With the global emphasis on sustainable growth and development, the depletion of natural energy reserves due to reliance on fossil fuels and non-renewable sources remains a critical concern. Despite strides in transitioning to electrical mobility, rural and agricultural communities depend heavily on liquefied petroleum gas and firewood for cooking, lacking viable, sustainable alternatives. This study focuses on community-led efforts to advance biogas adoption, providing an eco-friendly and reliable energy alternative for rural and farming households. By designing and developing balloon-type anaerobic biodigesters, this initiative provides a robust, cost-effective, and scalable method to convert farm waste into biogas for household cooking. This approach reduces reliance on traditional fuels, mitigating deforestation and improving air quality, and generates organic biofertilizer as a byproduct, enhancing agricultural productivity through organic farming. The study focuses on optimizing critical parameters, including the input feed rate, gas production patterns, holding time, biodigester health, gas quality, and liquid manure yield. Statistical tools, such as descriptive analysis, regression analysis, and ANOVA, were employed to validate and predict biogas output data based on experimental and industrial-scale data. Artificial neural networks (ANNs) were also utilized to model and predict outputs, inspired by the information processing mechanisms of biological neural systems. A comprehensive database was developed from experimental and literary data to enhance model accuracy. The results demonstrate significant improvements in cooking practices, health outcomes, economic stability, and solid waste management among beneficiaries. The integration of statistical analysis and ANN modeling validated the biodigester system’s effectiveness and scalability. This research highlights the potential to harness renewable energy to address socio-economic challenges in rural areas, paving the way for a sustainable, equitable future by fostering environmentally conscious practices, clean energy access, and enhanced agricultural productivity. Full article

Forest ecosystems deliver ecosystem services (ESs) that are essential for the well-being of local communities. These services necessitate a clear understanding of their perception among community members in order to facilitate informed and sustainable forest management decisions. This study aimed to explore the relationship between forest ESs and local communities by identifying community preferences for key ESs and examining how socio-economic factors influence this perception. Data was collected through participatory methods, including focus group discussions, key informant interviews, and a household survey involving 453 respondents. The data was analyzed using descriptive statistics and binary logistic regression. We identified firewood, rainfall attraction, air quality, and wildlife habitat as the most acknowledged services in their respective ES categories. Land ownership, education level, Community Forest Association membership, and labor migration significantly influenced service recognition. These findings highlight critical areas for intervention, including livelihood enhancement, cultural heritage preservation, and improved community outreach programs. The outcomes of this research are expected to contribute to the sustainable management of forest ecosystems. Full article

Flooding in Tempe Lake, Indonesia, poses ongoing socioeconomic challenges, mainly affecting food security, agricultural output, and household livelihoods. The recurrent and unpredictable floods disrupt planting and harvesting periods, resulting in significant food production deficits and posing complex adaptive challenges for residents. This study examines the socioeconomic adaptation strategies employed by rice farmer households to mitigate the adverse effects of flooding. The study analyzed a random sample of 160 people, utilized descriptive–analytical methodologies, and displayed the findings through graphs and matrix tables. Research reveals that fishing and rice farming serve as the primary revenue sources for households in the region. Despite financial challenges, households maintain security due to dependable food sources and proximity to the lake. The study emphasises the importance of efficient rice cultivation management owing to its short growth cycles and vulnerability to flooding. Moreover, freshwater aquaculture presents a sustainable strategy for mitigating flood risks in climate change, mainly when supported by microcredit, training, and improved market access. The findings highlight the necessity of social and structural adjustments in reducing vulnerability and enhancing community resilience, offering substantial recommendations for improving long-term resilience and food security in flood-prone regions. Full article

The interaction between rural household livelihood strategies and land use behavior constitutes the core of the human–land relationship in a region, especially in protected area villages with high ecological sensitivity that require the integration of social–economic and ecological benefits. This study, grounded in the concept of sustainable livelihoods, utilizes survey data from 399 households in the Chang-Zhu-Tan Green Heart Ecological Protection Zone. By employing the entropy method to calculate indicator weights, a coupling coordination degree model is constructed to analyze the coupling degree, coordination degree, and spatial differentiation patterns between household livelihood strategies and land use behavior. The findings reveal that (1) there is a coupling relationship between household livelihood strategies and land use behavior in the protected area, characterized by moderate coupling coordination. (2) Agricultural sideline households exhibit the highest degree of coupling coordination. The sideline activities of these households not only enhance income but also exert positive impacts on the ecological environment while they are engaged in agricultural production. (3) There is a significant spatial differentiation in the coupling coordination degree of different types of households in the protected area: it increases with the distance from the urban center, with higher values in the central areas than in the peripheral regions. The results of this study provide a basis for understanding micro-level land use changes and guiding household land use behavior, as well as offering theoretical and practical references for improving sustainable livelihoods of households in the study area, promoting rural revitalization, and implementing ecological protection policies. Full article

In sub-Saharan Africa, protected areas are located in close proximity to communities, leading to frequent negative encounters between humans and wildlife. This is coupled with increased pressure from communities seeking park resources to support their livelihoods. To address this, land use plans have been designed around protected areas. For example, in Kenya, wildlife conservancies have been created out of private and community lands. The aim of these conservancies is to contribute to improved livelihoods, reduce human–wildlife conflicts, and increase support for conservation. However, limited research exists on how the conservancies have achieved their aims among local communities. This study focuses on the Maasai Mara region in Kenya and examines how livelihoods and human–wildlife conflicts influence support for conservation among conservancy members. Data were gathered from 411 households adjacent to the reserve through a survey conducted in June and July 2024. The findings indicate a high incidence of human–wildlife conflict and improved security in health and education only. Despite this, there is high satisfaction with the conservancy model and strong support for conservation. Although these findings highlight the significance of conservancies in mitigating human–wildlife conflict, enhancing livelihoods, and garnering conservation support, more attention is needed for food and financial security. Full article

Although cocoa production addresses the livelihoods of several rural households, there is a global concern about its negative impact on the physical environment. How does this trade-off play out in different farming systems? This paper examined the social and environmental trade-offs and synergies of organic and conventional cocoa farming systems. Using the ‘SMART Farm-tool’ and principal component analysis approach, data collected from 398 cocoa farmers in five communities in the Atwima Mponua District of Ghana were analysed. We found that social and environmental trade-offs in the organic cocoa farming system are labour-related (EV = −0.38). The social and environmental trade-offs in the conventional cocoa farming system are health and safety and biodiversity-related (EV = −0.64). The organic farming system recognises indigenous knowledge in promoting biodiversity conservation and land degradation reduction (EV = −0.57). There can be more synergy than trade-off in both systems if support for capacity building and credit is provided and indigenous knowledge sharing is prioritised among low-income and vulnerable farmers. In this way, the labour conditions, biodiversity conservation, and health and safety-related concerns will be addressed. Addressing labour concerns in organic cocoa farming involves improving efficiency and working conditions. Strategies include training programs for organic techniques, introducing technology for tasks, and adhering to fair labour standards. This ensures labour concerns are addressed across the supply chain. Full article

Irrigation plays a crucial role in enhancing food production, increasing land productivity, and improving the livelihoods of smallholder farmers in Sub-Saharan Africa (SSA). Solar pumps and water harvesting ponds have emerged as promising technologies for sustainable agriculture for smallholders in SSA and beyond. The socio-economic impacts of these systems are less studied in the existing literature. This study examined the agricultural productivity of solar pump and water harvesting irrigation technologies and their impacts on income and food security among smallholder farmers in the Central Rift Valley, Lake Hawassa, and Upper Awash sub-basin areas in Ethiopia. Data were collected from 161 farming households that were selected randomly from woredas where solar pump and water harvesting pond irrigation systems had been implemented. The sample size was determined using the power calculation method. Bio-physical observation and measurements were also conducted at field levels. The benefit–cost ratio (BCR) and net water value (NWV) from the use of solar pump and water harvesting pond irrigations were analyzed to assess the viability of these systems. The household food consumption score (HFCS) and household dietary diversity score (HDDS) were calculated to measure food security, while the revenue from crop production was used to measure crop income. An endogenous switching regression model was applied to address the endogeneity nature of the adoption of the irrigation technologies. The counterfactual analysis, specifically the Average Treatment Effect on the Treated (ATT), was used to evaluate the impacts of the irrigation technologies on income and food security. Results indicate that the ATT of crop income, HFCS, and HDDS are positive and statistically significant, illustrating the role of these irrigation systems in enhancing smallholder farmers’ welfare. Moreover, smallholder farmers’ solar pump irrigation systems were found to be economically viable for few crops, with a BCR greater than 1.0 and an NWV ranging from 0.21 to 1.53 USD/m³. It was also found that bundling agricultural technologies with solar pump irrigation systems leads to enhanced agricultural outputs and welfare. The sustainable adoption and scale-up of these irrigation systems demand addressing technical and financial constraints, as well as input and output market challenges. Full article