Violent conflict exacerbated drought-related food insecurity between 2009 and 2019 in sub-Saharan Africa

Causal discovery reveals complex patterns of drought-induced displacement

The increasing frequency and severity of droughts present a significant risk to vulnerable regions of the globe, potentially leading to substantial human displacement in extreme situations. Drought-induced displacement is a complex and multifaceted issue that can perpetuate cycles of poverty, exacerbate food and water scarcity, and reinforce socio-economic inequalities. However, our understanding of human mobility in drought scenarios is currently limited, inhibiting accurate predictions and effective policy responses. Drought-induced displacement is driven by numerous factors and identifying its key drivers, causal-effect lags, and consequential effects is often challenging, typically relying on mechanistic models and qualitative assumptions. This paper presents a novel, data-driven methodology, grounded in causal discovery, to retrieve the drivers of drought-induced displacement within Somalia from 2016 to 2023. Our model exposes the intertwined vulnerabilities and the leading times that connect drought impacts, water and food security systems along with episodes of violent conflict, emphasizing that causal mechanisms change across districts. These findings pave the way for the development of algorithms with the ability to learn from human mobility data, enhancing anticipatory action, policy formulation, and humanitarian aid.

Future projection of droughts in Morocco and potential impact on agriculture

The present study evaluates the future drought hazard in Morocco using a Multi-Model Ensemble (MME) approach. First, the artificial neural network-based MME is constructed using the General Circulation Models (GCMs) from the Climate Models Intercomparison Project phase 6 (CMIP6) which are most successful in representing the historical temperature and precipitation values. Next, the future changes in the precipitation, Potential EvapoTranspiration (PET) calculated using temperatures data, aridity index, and drought indices calculated via the Standardized Precipitation Evapotranspiration Index (SPEI) values were projected for the historical period 1980-2014, near future 2025-2050, mid future 2051-2075, and far future 2076-2100. The obtained results indicate that there will be a decrease in values of the precipitation and an increase in values of the PET, leading to an increase in aridity risk for Morocco. The future projections using the SPEI results show that the average index values will mostly be in the drought zone, indicating that the drought severity will increase. The spatial analysis of SPEI values in different regions of Morocco demonstrates that the northern part of the country has relatively more drought occurrences, and drought severity tends to increase with each passing period. The study also reveals that drought severity will significantly increase after 2050 in the Shared Socio-economic Pathways 5-8.5 (SSP5-8.5) scenario. The research concludes that the increase in drought severity will significantly impact Morocco's water resources, agriculture and food security among others.

Insight into land cover dynamics and water challenges under anthropogenic and climatic changes in the eastern Nile Delta: Inference from remote sensing and GIS data

The destabilization of delta's worldwide due to climate change and human activities presents challenges in meeting the growing demands for freshwater and food. The Nile Delta in Egypt is a prime example of a vulnerable region facing various stressors. In order to preserve land and water resources, it is crucial to monitor the spatial and temporal changes in Land Use/Land Cover (LULC), shoreline, and Terrestrial Water Storage (TWS) in these vulnerable regions This study comprehensively investigates the dynamic changes in LULC and their associated water and soil responses in the Eastern Nile Delta under these combined impacts. To achieve this goal, a combination of remote sensing techniques utilizing Landsat (5, 8, and 9), and GRACE datasets, along with field observations and Geographic Information System (GIS) tools, was employed. Accordingly, shoreline changes show coastal erosion rates ranging from 5.28 to 34.92 m/year due to climate change-induced SLR, with continued inland movement predicted for the next 20 years. Moreover, the dynamic changes in urbanization and alterations in agricultural cover have considerable penalties for water demand. Analysis of GRACE data indicates a notable reduction in average TWS by 77.89 mm between 2002 and 2017, with an annual rate, estimated at -5.821 mm/year. Soil sampling in highly vulnerable areas confirms agricultural degradation attributed to elevated salinity levels, with EC values ranging from 3.60 to 190 ds/m. These finds provide valuable insights for stakeholders and policymakers, to make reliable strategies regarding water allocation, land use regulations, and climate change adaptation in the worldwide vulnerable deltas.

A regional stocktake of maize yield vulnerability to droughts in the Horn of Africa

Climate projections in sub-Saharan Africa predict increased frequency of droughts with parallel impacts on crop yield. The Horn of Africa is among the most vulnerable regions in Africa to these changes because agriculture in general and maize production in particularly is highly climate driven, and rain-fed. Current research approaches have mostly focused on the climatic and biophysical drivers of crop yield without including the socio-economic drivers of crop yield. This study fills this gap by investigating the vulnerability of maize yield in the Horn of Africa to climate and socio-economic indicators. The hypothesis is that there is an inverse relationship between vulnerability and adaptive capacity. The vulnerability index is a composite index that integrates sensitivity, exposure, and adaptive capacity sub-indices. Maize yield data to compute the sensitivity index were collected from FAOSTAT, precipitation data to compute the exposure index were collected from the Climate Research Unit (CRU), and the data for the proxies of adaptive capacity were collected from the readiness index database on figshare. From the results, Somalia records the highest vulnerability index of 1.15, followed by Ethiopia with a vulnerability index of 0.61. Kenya records the lowest vulnerability index of 0.33. Also, there is a positive relationship between the vulnerability, sensitivity, and the exposure indices and an inverse relationship between the vulnerability index and the adaptive capacity index. The high vulnerability index recorded in Somalia is accentuated by a low adaptive capacity index of 0.44 that is anchored on low literacy and high poverty rates. As Somalia records the lowest adaptive capacity index of 0.44, Ethiopia and Kenya record 0.91 and 0.99 respectively. This study has shown that to better understand vulnerability, a shift from the old paradigm that focuses on the climatic variables to integrating socio-economic variables or proxies of adaptive capacity which enhances our understanding of vulnerability. Though leveraging the benefits of climatic and non-climatic variables is important, the challenge so far has been on how to integrate these in the same model; a challenge this work has succinctly overcome by integrating adaptive capacity in the vulnerability equation.

Aeolian disaster risk evaluation in the African Sahel

The Sahel is facing a serious environmental crisis due to aeolian disaster that has seriously affected the local development and survival of residents. Thus, evaluating the aeolian disaster risk levels and their variation in the Sahel is important. This study established an optimal model by evaluating the applicability of different models in the aeolian disaster risk determination in the Sahel. Using this model, the spatiotemporal changes in the risk subsystem of aeolian disaster (hazard, sensitivity, vulnerability, and restorability) and the aeolian disaster risk in the Sahel from 2000 to 2020 were analyzed. Based on this analysis, the impact of climate change and human activities on the aeolian disaster risk in the Sahel was evaluated. Results revealed that the variable fuzzy recognition (VFR) based on the aeolian disaster risk index (ADRI) model had the highest accuracy, reaching 89.72 %. The middle of the Sahel, located in the desert-grassland transition zone, exhibited a high hazard, sensitivity, and vulnerability, rendering it highly susceptible to aeolian disaster. The proportion of areas with very low and very high aeolian disaster risk levels decreased from 2000 to 2020, while those with low and high levels increased, and the change in moderate risk level areas remained relatively stable. Areas of low, moderate, and high risk are more sensitive to climate change and human activities and are subjected to greater pressure for change. Human activities were the main factor for the change of ADRI in the Sahel, accounting for 69.74 and 58.19 % of the increased and decreased areas of ADRI, respectively. This study evaluated the level of aeolian disaster risk in the Sahel and identified the main driving factors, providing a reference for Sahel countries to better implement the Green Great Wall (GGW) program in Africa, thereby mitigating the adverse effects of aeolian disaster.

How Worried Are You about Food Fraud? A Preliminary Multi-Country Study among Consumers in Selected Sub-Saharan African Countries

Food fraud is an old, recurring, and global threat to public health. It poses a serious threat to food security in sub-Saharan Africa (SSA). Despite the prevalence of food fraud in SSA, little is known about how food fraud is viewed by consumers. This study aims to provide an overview of consumers' concerns about food fraud in SSA. A multi-country survey was conducted in October 2022-31 January 2023, and 838 valid responses were returned. To reduce the large and correlated dataset, Principal Component Analysis (PCA) was used. Five components were derived from PCA: (i) Staple foods; (ii) Premium food and drink products; (iii) Trust in reliable sources; (iv) Trust in less reliable sources; and (v) Trust in food vendors. The findings revealed Ghanaian (mean rank = 509.47) and Nigerian (mean rank = 454.82) consumers tended to score higher on the measure of food fraud concern suggesting that they were less confident in the safety and quality of the food they consume. Demographic characteristics including age, number of children, personal and family experience of food fraud and PCA components such as 'Staple foods', 'Trust in reliable sources', and 'Trust in food vendors' significantly predicted the model. This is the first preliminary study to provide empirical findings on consumers' concerns about food fraud in SSA. Practical and policy recommendations for the region are suggested. This includes (i) modelling the AfriFoodinTegrity in West Africa across other major regions such as Central, East, and Southern Africa; (ii) establish a regional sub-Saharan Africa Rapid Alert System for Food and Feed (SSA-RASFF) platform; and (iii) food safety and food fraud reports could be incorporated into SSA-RASFF portal for information sharing.

Diversifying agrifood systems to ensure global food security following the Russia–Ukraine crisis

The recent Russia–Ukraine conflict has raised significant concerns about global food security, leaving many countries with restricted access to imported staple food crops, particularly wheat and sunflower oil, sending food prices soaring with other adverse consequences in the food supply chain. This detrimental effect is particularly prominent for low-income countries relying on grain imports, with record-high food prices and inflation affecting their livelihoods. This review discusses the role of Russia and Ukraine in the global food system and the impact of the Russia–Ukraine conflict on food security. It also highlights how diversifying four areas of agrifood systems—markets, production, crops, and technology can contribute to achieving food supply chain resilience for future food security and sustainability.

Household behavior and vulnerability to acute malnutrition in Kenya

Anticipating those most at-risk of being acutely malnourished significantly shapes decisions that pertain to resource allocation and intervention in times of food crises. Yet, the assumption that household behavior in times of crisis is homogeneous-that households share the same capacity to adapt to external shocks-ostensibly prevails. This assumption fails to explain why, in a given geographical context, some households remain more vulnerable to acute malnutrition relative to others, and why a given risk factor may have a differential effect across households? In an effort to explore how variation in household behavior influences vulnerability to malnutrition, we use a unique household dataset that spans 23 Kenyan counties from 2016 to 2020 to seed, calibrate, and validate an evidence-driven computational model. We use the model to conduct a series of counterfactual experiments on the relationship between household adaptive capacity and vulnerability to acute malnutrition. Our findings suggest that households are differently impacted by given risk factors, with the most vulnerable households typically being the least adaptive. These findings further underscore the salience of household adaptive capacity, in particular, that adaption is less effective for economic vis-à-vis climate shocks. By making explicit the link between patterns of household behavior and vulnerability in the short- to medium-term, we underscore the need for famine early warning to better account for variation in household-level behavior.

Mean Temperature and Drought Projections in Central Africa: A Population-Based Study of Food Insecurity, Childhood Malnutrition and Mortality, and Infectious Disease

The Central African Region is an agricultural and fishing-based economy, with 40% of the population living in rural communities. The negative impacts of climate change have caused economic/health-related adverse impacts and food insecurity. This original article aims to research four key themes: (i) acute food insecurity (AFI); (ii) childhood malnutrition and mortality; (iii) infectious disease burden; and (iv) drought and mean temperature projections throughout the twenty-first century. Food insecurity was mapped in Central Africa based on the Integrated Food Security Phase Classification (IPC) for AFI. The global hunger index (GHI) was presented along with the proportion of children with undernourishment, stunting, wasting, and mortality. Data for infectious disease burden was computed by assessing the adjusted rate of change (AROC) of mortality due to diarrhea among children and the burden of death rates due to pneumonia across all age groups. Finally, the mean drought index was computed through the year 2100. This population-based study identifies high levels of hunger across a majority of the countries, with the mean drought index suggesting extreme ends of wet and dry days and an overall rise of 1-3 °C. This study is a source of evidence for stakeholders, policymakers, and the population residing in Central Africa.

Research priorities for global food security under extreme events

Extreme events, such as those caused by climate change, economic or geopolitical shocks, and pest or disease epidemics, threaten global food security. The complexity of causation, as well as the myriad ways that an event, or a sequence of events, creates cascading and systemic impacts, poses significant challenges to food systems research and policy alike. To identify priority food security risks and research opportunities, we asked experts from a range of fields and geographies to describe key threats to global food security over the next two decades and to suggest key research questions and gaps on this topic. Here, we present a prioritization of threats to global food security from extreme events, as well as emerging research questions that highlight the conceptual and practical challenges that exist in designing, adopting, and governing resilient food systems. We hope that these findings help in directing research funding and resources toward food system transformations needed to help society tackle major food system risks and food insecurity under extreme events.

Evaluation of Food Security Based on Remote Sensing Data—Taking Egypt as an Example

Egypt, a country with a harsh natural environment and rapid population growth, is facing difficulty in ensuring its national food security. A novel model developed for assessing food security in Egypt, which applies remote sensing techniques, is presented. By extracting the gray-level co-occurrence matrix (GLCM) mean texture features from Sentinel-1 and Landsat-7 images, the arable land used to grow grain crops was first classified and extracted using a support vector machine. In terms of the classified results, meteorological data, and normalized difference vegetation index (NDVI) data, the Carnegie–Ames–Stanford approach (CASA) model was adopted to compute the annual net primary production (NPP). Then, the NPP yield conversion formula was used to forecast the annual grain yield. Finally, a method for evaluating food security, which involves four dimensions, i.e., quantity security, economic security, quality security, and resource security, was established to evaluate food security in Egypt in 2010, 2015, and 2020. Based on the proposed model, a classification accuracy of the crop distribution map, which is above 82%, can be achieved. Moreover, the reliability of yield estimation is verified compared to the result estimated using statistics data provided by Food and Agriculture Organization (FAO). Our evaluation results show that food security in Egypt is declining, the quantity and quality security show large fluctuations, and economic and resource security are relatively stable. This model can satisfy the requirements for estimating grain yield at a wide scale and evaluating food security on a national level. It can be used to provide useful suggestions for governments regarding improving food security.

Water Resources in Africa under Global Change: Monitoring Surface Waters from Space

Abstract

The African continent hosts some of the largest freshwater systems worldwide, characterized by a large distribution and variability of surface waters that play a key role in the water, energy and carbon cycles and are of major importance to the global climate and water resources. Freshwater availability in Africa has now become of major concern under the combined effect of climate change, environmental alterations and anthropogenic pressure. However, the hydrology of the African river basins remains one of the least studied worldwide and a better monitoring and understanding of the hydrological processes across the continent become fundamental. Earth Observation, that offers a cost-effective means for monitoring the terrestrial water cycle, plays a major role in supporting surface hydrology investigations. Remote sensing advances are therefore a game changer to develop comprehensive observing systems to monitor Africa's land water and manage its water resources. Here, we review the achievements of more than three decades of advances using remote sensing to study surface waters in Africa, highlighting the current benefits and difficulties. We show how the availability of a large number of sensors and observations, coupled with models, offers new possibilities to monitor a continent with scarce gauged stations. In the context of upcoming satellite missions dedicated to surface hydrology, such as the Surface Water and Ocean Topography (SWOT), we discuss future opportunities and how the use of remote sensing could benefit scientific and societal applications, such as water resource management, flood risk prevention and environment monitoring under current global change.

Article Highlights

The hydrology of African surface water is of global importance, yet it remains poorly monitored and understoodComprehensive review of remote sensing and modeling advances to monitor Africa's surface water and water resourcesFuture opportunities with upcoming satellite missions and to translate scientific advances into societal applications.

Food security and emerging infectious disease: risk assessment and risk management

Climate change, emerging infectious diseases (EIDs) and food security create a dangerous nexus. Habitat interfaces, assumed to be efficient buffers, are being disrupted by human activities which in turn accelerate the movement of pathogens. EIDs threaten directly and indirectly availability and access to nutritious food, affecting global security and human health. In the next 70 years, food-secure and food-insecure countries will face EIDs driving increasingly unsustainable costs of production, predicted to exceed national and global gross domestic products. Our modern challenge is to transform this business as usual and embrace an alternative vision of the biosphere formalized in the Stockholm paradigm (SP). First, a pathogen-centric focus shifts our vision of risk space, determining how pathogens circulate in realized and potential fitness space. Risk space and pathogen exchange are always heightened at habitat interfaces. Second, apply the document-assess-monitor-act (DAMA) protocol developing strategic data for EID risk, to be translated, synthesized and broadcast as actionable information. Risk management is realized through targeted interventions focused around information exchanged among a community of scientists, policy practitioners of food and public health security and local populations. Ultimately, SP and DAMA protect human rights, supporting food security, access to nutritious food, health interventions and environmental integrity.

Protective Pathways: Connecting Environmental and Human Security at Local and Landscape Level with NLP and Geospatial Analysis of a Novel Database of 1500 Project Evaluations

Localized actionable evidence for addressing threats to the environment and human security lacks a comprehensive conceptual frame that incorporates challenges associated with active conflicts. Protective pathways linking previously disciplinarily-divided literatures on environmental security, human security and resilience in a coherent conceptual frame that identifies key relationships is used to analyze a novel, unstructured data set of Global Environment Fund (GEF) programmatic documents. Sub-national geospatial analysis of GEF documentation relating to projects in Africa finds 73% of districts with GEF land degradation projects were co-located with active conflict events. This study utilizes Natural Language Processing on a unique data set of 1500 GEF evaluations to identify text entities associated with conflict. Additional project case studies explore the sequence and relationships of environmental and human security concepts that lead to project success or failure. Differences between biodiversity and climate change projects are discussed but political crisis, poverty and disaster emerged as the most frequently extracted entities associated with conflict in environmental protection projects. Insecurity weakened institutions and fractured communities leading both directly and indirectly to conflict-related damage to environmental programming and desired outcomes. Simple causal explanations found to be inconsistent in previous large-scale statistical associations also inadequately describe dynamics and relationships found in the extracted text entities or case summaries. Emergent protective pathways that emphasized poverty and conflict reduction facilitated by institutional strengthening and inclusion present promising possibilities. Future research with innovative machine learning and other techniques of working with unstructured data may provide additional evidence for implementing actions that address climate change and environmental degradation while strengthening resilience and human security. Resilient, participatory and polycentric governance is key to foster this process.

Unlocking the Potential of Fish to Improve Food and Nutrition Security in Sub-Saharan Africa

Approximately one-third of the global population suffering from chronic hunger are in sub-Saharan Africa (SSA). In addition to high prevalence of chronic hunger, millions of people suffer from micronutrient deficiencies. Meanwhile, there is growing consensus across scientific disciplines concurring that fish plays a crucial role in improving food and nutrition security. Therefore, the present review aims to demonstrate the role of fish and the whole fisheries sector towards securing food and nutrition security in SSA by summarizing the existing literature. Fish is a treasure store of animal protein and essential micronutrients such as zinc, iodine, calcium, and vitamins, which are essential in human nutrition and have proven to help reduce the risks of both malnutrition and non-communicable diseases. Policymakers, development agencies, and society should recognize the role that the fisheries sector can play in combatting hunger and undernutrition, especially for the poor and marginalized people in SSA.