Vol.:(0123456789) Food Security (2024) 16:691–704 https://doi.org/10.1007/s12571-024-01444-1 ORIGINAL PAPER Addressing future food demand in The Gambia: can increased crop productivity and climate change adaptation close the supply–demand gap? Tony W. Carr1  · Felicity Addo2 · Amanda Palazzo2  · Petr Havlik2 · Katya Pérez‑Guzmán2 · Zakari Ali3  · Rosemary Green1,4 · Genevieve Hadida1 · Alcade C. Segnon5,6 · Robert Zougmoré5 · Pauline Scheelbeek1,4 Received: 14 June 2023 / Accepted: 6 March 2024 / Published online: 26 April 2024 © The Author(s) 2024 Abstract With rising demand for food and the threats posed by climate change, The Gambia faces significant challenges in ensuring sufficient and nutritious food for its population. To address these challenges, there is a need to increase domestic food produc- tion while limiting deforestation and land degradation. In this study, we modified the FABLE Calculator, a food and land-use system model, to focus on The Gambia to simulate scenarios for future food demand and increasing domestic food production. We considered the impacts of climate change on crops, the adoption of climate change adaptation techniques, as well as the potential of enhanced fertiliser use and irrigation to boost crop productivity, and assessed whether these measures would be sufficient to meet the projected increase in food demand. Our results indicate that domestic food production on existing cropland will not be sufficient to meet national food demand by 2050, leading to a significant supply–demand gap. How- ever, investments in fertiliser availability and the development of sustainable irrigation infrastructure, coupled with climate change adaptation strategies like the adoption of climate-resilient crop varieties and optimised planting dates, could halve this gap. Addressing the remaining gap will require additional strategies, such as increasing imports, expanding cropland, or prioritising the production of domestic food crops over export crops. Given the critical role imports play in The Gambia’s food supply, it is essential to ensure a robust flow of food imports by diversifying partners and addressing regional trade barriers. Our study highlights the urgent need for sustained investment and policy support to enhance domestic food produc- tion and food imports to secure sufficient and healthy food supplies amidst growing demand and climate change challenges. Keywords Food security · Food system model · Climate change adaptation · Crop productivity · Diets · Food imports 1 Introduction West Africa is facing significant challenges in guarantee- ing food security for its rapidly growing populations. The ever-increasing demand for food is accompanied by increas- ing vulnerability of food production due to environmental changes, particularly climate change, which is severely affecting the region (Trisos et al., 2022). Additionally, wide- spread land degradation, including depleted soil fertility, has reduced yields in agriculture (Stewart et al., 2020). The Gambia is facing particularly substantial food avail- ability issues as its agricultural sector has lower productiv- ity than other West African countries (World Bank, 2019). The Gambian agricultural sector is an important contributor to the country's economy and employs nearly half of the workforce (Cisse et al., 2021). Crop production accounts for the majority of agricultural GDP, with main crops including * Tony W. Carr tony.carr@lshtm.ac.uk 1 Department of Population Health, London School of Hygiene & Tropical Medicine, London, UK 2 International Institute for Applied Systems Analysis, Laxenburg, Austria 3 Nutrition & Planetary Health Theme, MRC Unit The Gambia at the London, School of Hygiene and Tropical Medicine, Banjul, The Gambia 4 Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK 5 International Center for Tropical Agriculture (CIAT), Dakar, Senegal 6 Faculty of Agronomic Sciences, University of Abomey-Calavi, Cotonou, Benin http://crossmark.crossref.org/dialog/?doi=10.1007/s12571-024-01444-1&domain=pdf http://orcid.org/0000-0002-1754-0842 http://orcid.org/0000-0001-8167-9403 http://orcid.org/0000-0002-8129-2230 692 T. W. Carr et al. groundnuts, millet, rice, maize, and sorghum. However, apart from groundnuts grown under resource-intensive conditions for the export market, most crops are produced through traditional rain-fed agriculture and subsistence farming, where farmers are often restricted by low soil fer- tility and limited access to inputs (World Bank, 2019). Agricultural production in The Gambia has seen consist- ent growth in recent decades. However, the increase has not been achieved from maximising productivity on existing cropland, but rather from expansion into conserved forests (World Bank, 2019). If current deforestation trends continue, The Gambia's forests could be completely depleted by 2050 (MECCNAR, 2021). This presents a challenge for the coun- try as it strives to balance its goals of preserving its forests, waters, wildlife, wetlands, and biodiversity with the need to increase food production (MECCNAR, 2021). The country's dependence on food imports is substan- tial, with only half of current food demand being met with domestic production (Cisse et al., 2021; MECCNAR, 2021). For instance, the country imports 83% of its rice, a staple food for most Gambian households (World Bank, 2019). The increasing demand for food has led to rising imports, mak- ing The Gambia vulnerable to external disruptions in food supply due to climate change or other shocks. Undernutrition continues to be a problem in The Gam- bia; however, diet-related non-communicable diseases (NCDs) have also emerged due to changes in diets and lifestyles with increasing incomes (Ali et al., 2023). A recent study found that the average Gambian diet has low adherence to global recommendations for healthy and sustainable diets, with a dominance of refined grains and added sugars exceeding guidelines, and low consumption of nutritionally important food groups, such as fruits and vegetables (Ali et al., 2022). To improve the nutritional status of the population, a National Nutrition Policy has been established, aiming to improve access to sufficient and healthy food (NaNA, 2021). To achieve The Gambia's nutrition policy objectives and maximise co-benefits for health, environmental sustain- ability and socio-economic development, a holistic under- standing of food system interactions is key. Integrated food system models can aid in linking The Gambia's food policy objectives by providing a broad overview of the food and land-use system and its interrelated components. These models simulate the complex interactions between system components impacting food supply and demand at national or regional levels, identifying trade-offs and synergies between different policy goals (Havlík et al., 2014; Valin et al., 2014; van Soest et al., 2019). Careful scenario analysis using integrated food system models can support informed decision-making, allowing policymakers to assess policy impacts on food security, nutrition, trade, and the environ- ment, before implementation (Palazzo et al., 2017). In this study, we aim to gain a better understanding of the future of The Gambia's food and land-use system and its impact on food availability by adapting the FABLE Cal- culator, a model developed by Mosnier et al., (2020, 2023) to represent the food system and its interactions with land- use and other sustainability indicators at the national level. Utilising scenarios co-developed with Gambian stakehold- ers and the integrated food system modelling approach, we project future food demand due to population growth and assess the feasibility of boosting domestic food production to decrease The Gambia's reliance on imports for its food sup- ply. This assessment considers the effects of climate change, climate change adaptation measures and improved access to fertiliser and irrigation on crop production. Our analysis provides valuable insights into the food system challenges faced by The Gambia and helps to determine priorities for ensuring a sufficient and nutritious food supply in the future. In addition, this study presents a nationally adapted inte- grated modelling framework that can be employed by other countries facing similar challenges in providing sufficient and healthy food to their populations. 2 Methods 2.1 The FABLE calculator The FABLE (Food, Agriculture, Biodiversity, Land-Use, and Energy) Calculator1 is an open-source Excel-based accounting model developed by Mosnier et al. (2020) to analyse the potential evolution of food and land-use sys- tems from 2000 to 2050 with the understanding that agri- culture plays the most significant role in land-use change. The model approximates the agricultural demand and supply from 2015 onward in five-year time steps, using historical FAOSTAT data (from 2000–2010) to calibrate the model. By combining various scenarios, the model simulates the potential future trajectories of food demand and land-use sectors, assessing their impacts on food security, production, trade, land use, land use change, greenhouse gas emissions, biodiversity, and water footprint. To assess future trajectories, the FABLE Calculator requires users to modify the drivers of system change, which are influenced by the choice and combination of model parameters and assumptions (i.e., scenarios). In this con- text, a user-defined combination of scenarios, representing a coherent and realistic development of the system along a specific trajectory defines a pathway. 1 An Open-Source version of the FABLE Calculator can be down- loaded for free at https:// www. abstr act- lands capes. com/ fable- calcu lator https://www.abstract-landscapes.com/fable-calculator https://www.abstract-landscapes.com/fable-calculator 693Addressing future food demand in The Gambia: can increased crop... In the FABLE Calculator, users define 16 parameters with multiple alternative values to represent scenarios. Implementing future scenarios in the model involves parameter shifters, which use historical values or past trajectories to capture time-specific relative changes in a parameter's initial value, allowing it to vary over time. The model follows interconnected calculation steps, starting with estimating the agricultural food and non- food demand trajectory by 2050, modified by shifters reflecting population growth, GDP projections, diets, food waste, and biofuel demand. The model then consid- ers various constraints tied to agricultural productivity, post-harvest losses, trade policies (e.g., import reduc- tion and export quotas), and the availability and use of land. As a result of these assumed constraints, the model computes a feasible supply that is available for human consumption. The feasible supply might not align with the initially calculated supply target necessary to meet food demand when the constraints for expanding produc- tion are binding. This feasible supply calculation is a key model output as it helps identify potential gaps between food demand and supply. It also provides insights into how much additional food is needed through production increase or imports to bridge these gaps. As a critical component of the feasible supply, the feasi- ble domestic food production plays a significant role, which is influenced by agricultural productivity and land avail- ability. The model represents six land cover types and calcu- lates land-use changes based on afforestation, reforestation, agricultural land expansion, and protected areas. A feedback loop ensures land-use trajectory assumptions remain within feasible restrictions concerning available land. A main advantage of the FABLE model lies in its ability to address complex food and land-use system questions using a simplified setup. This user-friendly design enables researchers, policymakers, and stakeholders with diverse modeling exper- tise to operate the model using only basic Microsoft Excel knowledge and a moderate learning curve. Users can easily adapt the model by modifying scenarios, parameters, variables, and formulas. Its interactive interface supports transparent communication between modelers and stakeholders. Although the model is user-friendly and requires minimal modeling expertise, it is important to note that the FABLE Calculator is an accounting model rather than an optimisation model. Consequently, it does not consider price effects and market dynamics. The options for reducing agricultural GHG emissions in the model rely on decreasing production volumes and enhancing productivity, while more sophisticated mitiga- tion techniques, such as refined rice management or animal feed supplements, are not included in the model. A more detailed explanation of the model and its application in different studies is available in the supplementary information. 2.2 An empirical application to The Gambian food and land‑use system To analyse potential future pathways of the food and land- use system in The Gambia, we adapted the FABLE Cal- culator to better fit the country's context. We drew upon key parameters from previous FABLE modelling exercises (Mosnier et al., 2023) to inform the initial future scenar- ios for The Gambia's food and land-use system. To ensure the Gambia-specific parameter assumptions and scenario pathways were accurate and relevant for the Gambian food system, we organised a stakeholder workshop with over 30 participants, including technical experts, policymakers, researchers, farmer organisation representatives, and NGOs. During the workshop, stakeholders examined the model's calculation steps, data used, parameter assumptions, and sce- narios. They identified key drivers significantly influencing The Gambia's food and land-use system and collaborated in multidisciplinary breakout groups to co-develop and co- design realistic scenario pathways. Stakeholders reviewed initial model assumptions and results, providing feedback on drivers, relevant indicators, and additional national data and policy documents necessary for integrating these pathways into the FABLE Calculator. 2.3 Parameters of the FABLE Gambia model To estimate future domestic food demand in The Gambia, we used data on changes in population size and per capita food available for consumption. The latter is based on the current average daily per capita supply of different food groups, as documented in the FAO Balance sheets (FAO, 2023) (Fig. S1). Population projections consider alternative assumptions regarding future fertility, mortality, migra- tion, and educational transitions that correspond to the five shared socioeconomic pathways (SSPs) (KC and Lutz, 2017) (Fig. S2). For the baseline scenario, we selected the inter- mediate scenario (SSP-2), which assumes an annual popula- tion growth of 2.8%, in line with The Gambia's growth rates in the 2010s, ranging between 2.5% and 3% (World Bank, 2023). The range of five SSP scenarios was used to account for the uncertainty in food demand stemming from varying population growth projections. The future Gambian food supply scenarios were primar- ily determined by variations in domestic food production. This was influenced by scenarios considering the impacts of climate change and different field management practices on crop productivity. We applied these scenarios to the most widely grown and consumed crops in The Gambia, includ- ing rice, millet, maize, sorghum, groundnut, and cassava. Climate change scenarios, which account for the effects of temperature, rainfall, and other climate factors on crop yields, were derived from the Representative Concentration 694 T. W. Carr et al. Pathway (RCP) 2.6 and RCP 6.0 scenarios. Our analysis considered crop yield changes due to climate change with and without CO2 fertilisation using LPJmL vegetation model simulations (Schaphoff et al., 2018) from the ISIMIP data- base (Arneth et al., 2017) (Fig. S3). As no climate projec- tions were available for sorghum, we mapped the relative yield changes of millet, as it has similar biophysical and photosynthetic properties (Janssens et al., 2020). We considered three field management scenarios that affect crop yields: 1. Business as usual (BAU) scenario: This scenario assumes no significant changes in agricultural practices or technologies and was used as a reference for compari- son with other scenarios. 2. Climate change adaptation (CCA) scenarios: CCA prac- tices typically respond to shifts in precipitation and tem- perature to enhance productivity. These practices include shifting planting dates, changing crop varieties (e.g., drought-resistant crops), crop rotations, altering soil man- agement and fertilisation, and improving water manage- ment, among others (Segnon et al., 2021). The estimated impact of CCA practices on crop yields was based on a systematic review of climate change and adaptation strat- egies on major crops in West Africa (Carr et al., 2022), which showed that crop yields can increase by 13% on average by adopting techniques such as optimised planting dates, climate-resistant varieties, and increased fertiliser use under changing climate conditions. 3. Intensified nutrient and water management (Boost) sce- narios: We estimated the increase in crop yield resulting from improved access to irrigation and fertiliser based on simulated yield potentials achievable with reduced water and nutrient stress. This agricultural intensifica- tion scenario assumes that with better management, 75% of The Gambia's yield potential can be achieved, based on yield potentials calculated by Mueller et al. (2012). Achieving these yields would require increased irrigation and nutrient application across most of the country, bringing crop yields closer to the respective yield potentials achieved in the world's main agricul- tural areas. The yield potentials were used as a target for the year 2050, which would be gradually reached through a linear growth function in 5-year increments. If the historical maximum yield already exceeds 75% of the achievable yield potential, the historical yield was used as the intensification target (Fig. S4). To evaluate whether domestic crop production could meet the increasing food demand through productivity gains, we kept other factors affecting food supply con- stant from the baseline years 2000–2010, including crop- land area, livestock production productivity, food waste, post-harvest losses, and export quantities. Additionally, our model assumes a constant import share, meaning that imports will represent the same share of the domestic sup- ply in 2010 and in 2050. Table 1 summarises the param- eters relevant to the FABLE Gambia model. 2.4 Considerations on fixed dietary scenario in food demand projections While our model accounts for population growth as a key determinant of future food demand, it assumes fixed dietary Table 1 Summary of parameters relevant to the FABLE Gambia model Parameter Options Description Population Annual population growth of 2.8% (SSP-2) Shared socioeconomic pathways (SSP) are used to estimate population growth based on future fertility, mortality, migration, education (KC and Lutz, 2017). The SSP-2 scenario served as a baseline, while the range from SSP-1 to SSP-5 captured various potential paths of population growth and associated changes in food demand Diet Current diet Current dietary patterns were derived from the average daily per capita supply of different food groups for the years 2000–2010, as recorded in the FAO Food Balance Sheets (FAO, 2023) Climate Change - RCP 2.6 - RCP 6.0 Changes in temperature, precipitation, and other climate factors were based on two Representative Concentration Pathway (RCP) scenarios, RCP 2.6 and RCP 6.0. Their effects on crop yields were simulated using LPJmL, with and without CO2 fertilisation (Schaphoff et al., 2018). The data was sourced from the ISIMIP database (Arneth et al., 2017) Field Management - BAU - CCA - Boost Field management scenarios assess the impact of various approaches to agricultural practices and technologies on crop yields. These scenarios include BAU, which assumed no significant changes in current practices; CCA, which explored the effects of climate change adaptation strat- egies informed by a systematic review (Carr et al., 2022); and Boost, which was based on yield potentials with intensified nutrient and water management, as calculated by Mueller et al. (2012) Other Constant from baseline Other factors include cropland area, import shares, export quantities, livestock productivity, food waste, and post-harvest losses. Values for these factors were taken from the years 2000–2010, as recorded in the FAO Food Balance Sheets (FAO, 2023) and previous FABLE modelling exer- cises (Mosnier et al., 2020, 2023) 695Addressing future food demand in The Gambia: can increased crop... patterns. This is a noteworthy simplification, as food demand is not only determined by population size, but also by dynamic dietary habits. These habits can be influenced by several socio- economic and cultural factors, including GDP, the degree of urbanisation, household characteristics, education levels and consumer preferences, each affecting the demand for certain types of food. The wide range of factors influencing dietary choices increases the complexity and uncertainty of scenarios for future food demand. Moreover, Ali et al. (2023) have shown that common socio-economic and cultural factors cannot explain the recent changes in diets across all food groups in The Gambia, thus highlighting the complexity involved in projecting future food demand. By focusing solely on the influence of population growth, we aim to provide a baseline scenario that illustrates the pressing challenges The Gambia will face even if dietary habits remain unchanged. 3 Results 3.1 Future food demand and requirements for production and imports in The Gambia Food demand in The Gambia is expected to increase under the baseline scenario by 54% by 2050, with variations rang- ing from 35 to 77%, depending on future population growth (i.e., SSP scenarios) (Fig. 1). The projected food demand growth is lower than the recorded historical growth, where between the 1990s and 2010s food demand in The Gambia grew by 106%, mainly due to population growth. During the same period, food production increased by 93%, and imports expanded by 160%. If this trend continues, rising food demand will be met with a greater increase in imports than in production. To meet the rising food demand in 2050, total domestic food production will need to increase accordingly. Assuming the area devoted to particular crops remains unchanged, the largest absolute increase in production will be for crops that are predominantly produced in The Gambia. This includes millet, groundnut, maize, and rice (Fig. 2(a)). Import volumes will also need to increase to meet the projected food demand. Assuming constant import shares for consumed products, the largest increase in import vol- umes in absolute terms is for historically high-imported food groups, such as rice, milk, and wheat (Fig. 2(b)). 3.2 Feasible food production under different climate change and crop productivity scenarios Through our analysis of future food demand, as presented in Section 3.1, we identified a supply target required to meet projected demand through an increase in domestic food production and imports. However, inherent constraints in production and trade, such as land availability, land-use poli- cies, and trade policies, can limit the feasible supply, causing it to fall short of the target. As food demand in The Gambia grows, primarily due to population increase, the gap between demand and feasible supply increases under the business-as-usual scenario. This divergence is influenced by changes in feasible domestic food production, which is itself influenced by the impact of climate change on crops and field management practices. Feasible domestic food production is projected to decrease due to climate change under the business-as-usual field man- agement (Fig. 3). By 2050, feasible food production is esti- mated to decrease by 3% under the RCP 2.6 scenario and 5% under the RCP 6.0 scenario. While the additional CO2 present in the atmosphere could have a so-called fertilisation effect on crop productivity and could potentially mitigate these declines, its impact is uncertain due to crop-specific variability and the difficulties in simulating this process. Accounting for this uncertainty, the impact could range from 1 to 5% under RCP 2.6 and from 2 to 8% under RCP 6.0. In terms of food production, the differential impact of varying climate change scenarios is relatively minor when compared to the changes brought by improved field manage- ment. Figure 4 illustrates the variation in feasible domestic food production over time and under different scenarios, with differences in bars representing projected production changes due to field management and error bars indicating Fig. 1 Food demand, food production and food imports in The Gam- bia as recorded by FAO (a) from 1980 to 2015 and projected using FABLE (b) from 2015 to 2050. Projected food production and food imports represent the target needed to meet food demand. Discrepan- cies between total food demand and the sum of production and import volumes arise due to factors such as exports, food waste and losses, unaccounted informal trade, stock variations, non-food uses and sta- tistical discrepancies in FAO Food Balance Sheets. The projections include an uncertainty range due to the different SSP population growth scenarios represented by the shading. The projected change in food demand, production target, and import target for all major food groups can be seen in Figs. S5 to S7 696 T. W. Carr et al. the different projected effects of climate change between the RCP 2.6 and RCP 6.0 scenarios. The primary driver of changes in feasible food production are improvements in field management practices leading to increased crop yields beyond those in the business-as-usual (BAU) field management scenario. Climate change adapta- tion techniques (CCA) contribute to a 7% increase in feasible production in 2030 and an 8% increase in 2050 compared to the BAU scenario. Intensified fertiliser application and irri- gation (Boost) results in a 21% production increase in 2030 and a 40% increase in 2050. Combining both approaches yields a 29% production increase in 2030 and a 51% increase in 2050. The larger combined effect occurs because CCA and Boost benefits are applied as multipliers in sequence, each increasing the already enhanced yields, rather than just adding the individual effects. The most notable improve- ments in feasible production are observed in crops with the highest current production levels, such as cereals (millet, rice, maize, sorghum) and groundnuts. Domestic food production, even under all options to increase productivity, falls short of meeting the 2050 food demand target, resulting in supply gaps for various food and feed products (Fig. 5). Under the BAU scenario, the food supply gap for all food groups combined is projected to be 361,000 tonnes (47%) by 2050. Increasing productiv- ity by adopting climate change adaptation and investing in agricultural intensification can help mitigate these supply gaps. Climate change adaptation practices can contribute Fig. 2 a Production growth required to meet food demand between 2020 and 2050 for the ten food products with the highest projected absolute increase. b Increase in imports required to meet food demand between 2020 and 2050 for the ten food products with the highest projected absolute increase Fig. 3 Feasible food production in The Gambia from 2010 to 2050 under business-as-usual field management under the RCP scenarios RCP 2.6 (a) and RCP 6.0 (b). Each trend line represents the average projected impact of climate change on food production. The shaded area indicates the uncertainty ranges due to the productivity effect of increased levels of CO2 (carbon fertilisation) 697Addressing future food demand in The Gambia: can increased crop... an additional 28,000 tonnes (4%) of food production, while agricultural intensification can provide 141,000 tonnes (18%) of extra production. Implementing both approaches can generate an additional 176,000 tonnes (23%) of food production, which can approximately halve the missing food supply by 2050. The projected gap between domestic demand and feasi- ble domestic supply will lead to an increasing deficit in the food available for consumption by 2050. Under current die- tary patterns, this would reduce the daily per capita calorie availability of 2553 by between 286 and 623 cal, depending on agricultural management practices (Fig. S9). To close the gap between food demand and supply, The Gambia would need to increase food imports, expand domestic cropland, or repurpose existing cropland from export-oriented crops to crops that serve domestic food consumption. To meet the required levels of food supply without increasing imports, total cropland area would need to increase by approximately 123% (431,000 ha) under the business-as-usual scenario and by about 56% (195.000 ha) under maximum crop productivity, compared to the baseline harvested area of 350,000 hectares (Fig. 6). Such land use alterations would affect deforestation, biodiversity, water resources, and greenhouse gas emissions. Our projections indicate that greenhouse gas emissions from crop produc- tion in 2050 could vary between 0.4 Mt CO2e under the business-as-usual scenario to 0.15 Mt CO2e under condi- tions of maximum crop productivity. 4 Discussion 4.1 Summary of findings If recent trends continue, food demand in The Gambia will increase in the future to feed a growing population. To ensure that this growing demand can be met, it is crucial to imple- ment strategies aimed at increasing food supply, which include increasing domestic production, increasing imports (and/or reducing exports), or a combination of these approaches. In The Gambia, improving crop yields presents an oppor- tunity to bridge the demand–supply gap. Our results indicate that if domestic yields of the most consumed crops would Fig. 4 Feasible food production for domestic consumption and exports on current cropland under different crop productivity sce- narios in 2030 (a) and 2050 (b). Crop productivity scenarios include business-as-usual (BAU), climate change adaptation (CCA), agri- cultural intensification (Boost), and a combination of both (CCA & Boost). Error bars indicate the variation between food production simulated under the RCP2.6 scenario and simulated under the RCP 6.0 scenario. The dashed line represents the target of domestic food production required to meet food demand for both domestic con- sumption and exports. The coloured products include the most pro- duced food products in The Gambia. The projected changes in feasi- ble food production for all major food groups can be seen in Fig. S8 Fig. 5 a Shortfall of food supply for domestic consumption (%), expressed as the gap between the food production target to meet food demand and the feasible food production in 2030 and 2050 under the business-as-usual scenario. b Additional food production on current cropland (%) estimated under different scenarios to increase crop pro- ductivity, including climate change adaptation (CCA), agricultural intensification (Boost), and a combination of both (CCA & Boost) 698 T. W. Carr et al. reach their potential achievable levels, the projected food supply gap in 2050 could be halved. Whilst this is a promising improvement, additional meas- ures would be required in The Gambia to fully close the sup- ply gap, such as expanding existing agricultural land, repur- posing cropland used for producing export and cash crops to producing domestically consumed food, or modifying trade patterns (i.e., increasing imports and/or decreasing exports). Adopting climate change adaptation technologies has a limited impact on increasing yield potentials in The Gam- bia compared to boosting productivity. This is fundamental as the main determinants of low productivity are related to limited access to inputs and technology rather than climate- change-induced yield fluctuations. Nevertheless, climate change adaptation remains crucial for food security, as this helps mitigate the risk of major harvest failures resulting from extreme events such as droughts. Our findings echo previous studies that emphasised the importance of supporting domestic agricultural production in sub-Saharan Africa to increase self-sufficiency in food supply amid rising demand (De Graaff et al., 2011; Giller, 2020; Luan et al., 2013). 4.2 The role of diets in The Gambia's changing food demand Demand projections for specific food groups in The Gam- bia carry considerable uncertainty due to evolving dietary habits, which can be influenced by a variety of factors such as socio-economic changes and government policies (Ali et al., 2023). Currently, cereals like rice and wheat dominate food consumption, while healthier options such as fruits, vegetables, and nuts are not adequately consumed (Ali et al., 2022). To address unhealthy diets, the Gambian government pro- posed the Food-Based Dietary Guidelines (FBDG) to edu- cate the population on healthier eating habits. If healthier diets would be adopted, this would considerably shift the food demand projections and consequently the projected supply–demand gap. Specifically, the supply gap for cereals would decrease, while the gap for fruits, vegetables, pulses, nuts, and meat would increase. Beyond dietary guidelines, broader socio-economic indicators like GDP growth and urbanisation also have the potential to influence a shift in diets, likely leading to an increase in demand for animal-source foods in The Gambia (Ali et al., 2023). Gambian farmers and producers may face challenges from these changes, especially for fruits and vegetables. These healthier options typically require intensive use of resources such as fertiliser and water, advanced technology, and agricultural expertise. Currently, these resources are pre- dominantly allocated to cereal production. In addition, the supply chain for shifting to more fruits and vegetables would require investment in infrastructure for perishable food. Addressing the supply challenges will require strategies that improve trade flows and promote domestic production of nutrient-rich crops. Even without substantial changes in dietary patterns, major supply gaps are projected for the coming decades. The next section will discuss implications and potential solutions related to domestic production and international trade. 4.3 Policy and practice recommendations 4.3.1 Enhancing agricultural productivity in The Gambia The current agricultural productivity in The Gambia is signifi- cantly lower than that of neighbouring countries, with cereal yields 42% and 35% lower than in Senegal and the average for West Africa in the past decade, respectively (FAO, 2023). Among the cereals, rice has the greatest potential for yield improvement, with achievable regional average yields being up to five times greater than recent average Gambian yields. In addition, root and tuber crops such as cassava have enormous untapped potential to increase yields by five to ten times their current levels and have the added advantage of being highly resilient to climate change (Jarvis et al., 2012). A major barrier to higher crop production is the inad- equate access of farm households to inputs such as fertilis- ers, seeds, and extension services (Gajigo & Saine, 2011). Furthermore, poor land management practices and land degradation have contributed to declining soil fertility and Fig. 6 Change in the area of cultivated land required to meet food demand under different crop productivity scenarios from 2015–2050. Crop productivity scenarios include business-as-usual (BAU), climate change adaptation (CCA), agricultural intensification (Boost), and a combination of both (CCA & Boost). The dashed line represents the total area of The Gambia 699Addressing future food demand in The Gambia: can increased crop... crop productivity, as evidenced by regional satellite data (Mechiche-Alami & Abdi, 2020). Given the documented benefits of public agricultural spending for food security (Bambio et al., 2022), prior studies have recommended increasing agricultural investment in The Gambia (Belford et al., 2023; Fontan Sers & Mughal, 2020). Although the government subsidises a large proportion of the fertiliser used in the country, its usage remains lower than in neighbouring Senegal and the West African average (World Bank, 2019). The high costs of fertiliser contribute to this low usage, as it renders fertiliser inaccessible for smallholder farm- ers, even when it is available (Segnon et al., 2022a, b). Enhancing productivity requires increased access to inputs such as pesticides and fertilisers, advanced technologies like new seed varieties, and improved water management prac- tices (Government of The Gambia, 2019; World Bank, 2019). Investment in rice production has shown promising results for increasing productivity in The Gambia. For example, The Rice Value Chain Transformation Programme has increased access to improved seeds, fertilisers, and machinery, resulting in higher rice yields (Belford et al., 2023). However, increasing produc- tivity does not always require significant investments in new inputs or technology. Field trials of the System of Rice Inten- sification (SRI) have demonstrated that improved agricultural practices can boost productivity without relying solely on water and fertilisers (Ceesay, 2011). This underscores the impor- tance of providing farmers with information and resources to improve farming practices, in addition to investments in inputs and technology. Adopting innovative, land-efficient farming practices and the use of underutilised rural land can increase food pro- duction without the need for large-scale cropland expansion (Ali et al., 2022). Urban farming methods such as vertical farming allow for optimal use of space, while homestead farming enhances production even in confined spaces. Col- lective farming initiatives, such as community gardens, not only increase local production but also promote com- munity empowerment, with women playing a central role (Bizikova et al., 2020; Ebile et al., 2022). These approaches offer opportunities to increase the production of fruits and vegetables in particular. However, as fruits and vegetables are highly perishable, it is essential to invest in post-harvest infrastructure to reduce losses from storage and transport. Given The Gambia’s vulnerability to climate change impacts, scaling up adaptation practices in agriculture and food systems is key to increase resilience to climatic risks. Several field studies in The Gambia and West Africa have confirmed the positive impact of various climate-smart agriculture techniques in mitigating climate change effects (Segnon et al., 2022a, b; Zougmoré et al., 2014, 2018). Priority adaptation options, determined through evidence- based assessment and participatory processes (Segnon et al., 2022a, b), offer a strategic pathway for the expansion of these practices. For example, climate change-induced weather variability necessitates reliable weather information for agricultural plan- ning, helping farmers to make informed decisions and reduce risks associated with weather-related crop failures (MacCarthy et al., 2017; Segnon et al., 2022a, b). Additionally, cultivating crops better adapted to tropical climates can be a promising strategy for ensuring a stable future food supply. Duvallet et al. (2021) found that native crops like sorghum, millet, and tubers are more resilient to climate variability and have higher yields compared to rice in West Africa. By increasing the production of such local crops, The Gambia could secure a more stable, climate-resilient food supply. 4.3.2 Enhancing food supply in The Gambia through trade Enhancing agricultural productivity in The Gambia was pro- jected to reduce The Gambia’s dependence on food imports in our model. However, as results show, the growing demand could not be fully met with increasing domestic production, thus an increase in food imports would likely be necessary. Currently, the most consumed cereals in the Gambia (largely rice and wheat) are supplied mostly through imports, while the consumption of locally produced non-import-reliant foods, like millet, has declined. A shift to more diverse diets could result in greater reliance on imports for a number of food groups that are currently not produced in sufficient quantities domestically, like fruits and vegetables. Opening up trade can enhance dietary diversity by mak- ing a more diverse range of food groups available, thus contributing to improved diet quality (Dithmer & Abdulai, 2017; Kinnunen et al., 2020). Trade plays an important role in ensuring consistent access to food by fostering better con- nections between food-deficit regions and those with sur- pluses (Janssens et al., 2020). Ensuring smooth trade flows, particularly for perishable foods, is therefore essential for building a resilient food system. However, import-dependent countries like The Gambia must be prepared for potential disruptions in international trade due to tariffs, trade restrictions, or global events. Recent examples include the 2007–2008 global food crisis, the COVID-19 pan- demic, and the war in Ukraine, a major exporter of agricultural products (Ali et al., 2020; FAO, 2022; Janssens et al., 2020; Sperling et al., 2022). Climate change could also contribute to future shocks in food trade, highlighting the importance of considering the climate resilience of trading partners (Gaupp et al., 2020; Hadida et al., 2022). Diversifying trade partners can spread the risk of supply disruptions and allows for more flexible adjustments in case of climate shocks or export dif- ficulties in a specific country or region. 700 T. W. Carr et al. Additionally, enhancing regional trade can reduce reli- ance on global market fluctuations and help mitigate food supply risks. Geographically closer trade partners offer reduced transportation time and costs, ensuring that fresher products can reach consumers quickly, which is vital for perishable items. Initiatives like the African Continental Free Trade Agreement could help to integrate Africa's food markets by promoting policy harmonisation, trade barrier reduction, and smooth cross-border movement of goods, which can contribute to stable prices and consistent access to various food items (Morsy et al., 2021). To improve trade within the Economic Community of West African States (ECOWAS) region and maxim- ise its positive impact on The Gambia's access to food, it is essential to address several trade barriers. Currently, barriers such as inadequate funding on both soft (e.g., inspectors, customs digitisation) and hard infrastructure (e.g., roads, ports), and informal cross-border food trade undermine trade competitiveness and revenue collec- tion (Kareem & Wieck, 2021). Intra-African trade is low compared to other continents, and trade between regional economic communities remains limited (Janssens et al., 2022). Although The Gambia has regional trade partners like Senegal, its largest trade partners are currently in South America, Europe, and Asia (Hadida et al., 2022). Overcoming these barriers and strengthening regional trade relationships could contribute to a more coherent and resilient food supply in future. 4.4 Opportunities and limitations in modelling future food supply and demand in The Gambia Our analysis of future food supply and demand scenarios in The Gambia made use of the compatibility of FABLE with common food system databases to mitigate low local data availability. Yet, the complexity of food systems and limited data introduce some limitations. Data mainly stems from FAO food balance sheets, known for potential inaccuracies such as underrepresentation of fruit and vegetable consumption (Ali et al., 2022; Del Gobbo et al., 2015). These may lead to inaccuracies in demand pro- jections. Moreover, changes in future diets were not con- sidered in our projections. In addition, our study does not consider subnational differences in population growth and diets. A regional analysis may reveal significant disparities in food availability, reflecting increased undernutrition in rural areas (Government of The Gambia, 2019). Incomplete trade data due to informal trade, scarce livestock and fish- eries data, and unavailable food waste or post-harvest loss data, further restrict model comprehensiveness. Diverse field management in The Gambia contributes to variable future crop productivity potentials, which are compounded by regional differences in farming techniques and adoption of climate change adaptation methods. To address this, we applied business-as-usual and two further scenarios assuming widespread climate change adaptation and agricultural intensification. Although not exhaustive, this approach captures a broad range of potential productiv- ity outcomes. Despite its limitations, this study’s modelling framework provides essential insights into The Gambia’s various future food supply and demand scenarios. Additionally, it offers a foundation for further research into the feasibility of healthy dietary targets and associated food availability. 5 Conclusion Our analysis of different future food demand and supply scenarios in The Gambia reveals that the country's food security faces ongoing challenges. The projected increase in food demand will likely lead to a growing reliance on imports, particularly if healthier and more diverse diets are adopted in the future. Nonetheless, The Gambia has signifi- cant potential to improve agricultural productivity, closing the considerable gap between actual and achievable yields. To boost agricultural productivity in The Gambia, rec- ommendations include targeted investments in research to increase yields and the implementation of subsidy pro- grammes to facilitate smallholder farmers' access to key inputs such as fertilisers and seeds. Alongside this, the development of sustainable irrigation infrastructure and the cultivation of unused rural land can enrich the food supply. Expanding agricultural extension services can facilitate the spread of innovative farming practices that make efficient use of land. It is also important to allocate resources to modern post-harvest infrastructures to minimise food loss, especially for perishable products. Developing climate- adapted agricultural techniques, tailored to the local condi- tions through evidence-based assessment and participatory processes, can help farmers adapt to climate variability. In addition, improved weather forecasting services could miti- gate the risks of weather-related crop failures. In terms of trade, diversification of trading partners can reduce risks related to supply chain disruptions and market volatility. In addition, strengthening regional trade within ECOWAS can reduce exposure to global market volatility, lower transport costs and ensure faster access to fresh pro- duce. This requires addressing deficiencies in soft and hard infrastructure as well as informal cross-border food trade to improve trade competitiveness and revenue collection. These general policy starting points serve as a basis for more detailed future research on policy implications. Addi- tionally, investigating the feasibility of the strategies we have outlined to improve agricultural productivity could provide 701Addressing future food demand in The Gambia: can increased crop... key insights into increasing The Gambia's food supply. Given the dynamic and multi-layered nature of food systems, ongoing research is essential to fully understand the feasibil- ity and variability of food supply and demand in the country. Our modelling framework, based on open-access data and scenarios, provides a starting point for much needed future research on food security in The Gambia and other countries facing similar challenges. Supplementary Information The online version contains supplemen- tary material available at https:// doi. org/ 10. 1007/ s12571- 024- 01444-1. Acknowledgements This study was developed as part of the Food system Adaptation in Changing Environments in Africa (FACE- Africa) project, which was funded by the Wellcome Trust (grant no. 216021/Z/19/Z) under the Wellcome Climate Change and Health Award Scheme. ACS and RBZ acknowledge financial supports by the Accelerating Impacts of CGIAR Climate Research for Africa (AIC- CRA) project, funded by a grant from the International Development Association (IDA) of the World Bank. We would like to express our gratitude to the participants of the stakeholder workshop for their invaluable insights and to Sulayman M’boob of Kombo Farms for his significant contributions to stakeholder engagement. We also extend our appreciation to Aline Mosnier and the FABLE team for providing the initial data for the Gambia version of the FABLE Calculator, which greatly facilitated our research. We would also like to thank the two anonymous reviewers who helped to improve this study. Funding Funding was provided by Wellcome Trust (grant no. 216021/Z/19/Z) and the International Development Association (IDA) of the World Bank (Accelerating Impacts of CGIAR Climate Research for Africa (AICCRA) project). Data and tool availability The results that support the findings of the study are provided in the manuscript and supplementary material. Sce- nario results for all scenarios are made accessible online via a Rshiny app: https:// gambia. shiny apps. io/ FABLE- Gambia/. Additional data and code are available upon reasonable request from the corresponding authors. Source data are provided with this paper. Declarations Conflict of interest The authors do not have any competing interests to declare. Open Access This article is licensed under a Creative Commons Attri- bution 4.0 International License, which permits use, sharing, adapta- tion, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. References Ali, Z., Green, R., Zougmoré, R. B., Mkuhlani, S., Palazzo, A., Prentice, A. M., Haines, A., Dangour, A. D., & Scheelbeek, P. F. D. (2020). Long-term impact of West African food system responses to COVID-19. Nature Food, 1(12), 768–770. https:// doi. org/ 10. 1038/ s43016- 020- 00191-8 Ali, Z., Scheelbeek, P. F. D., Dalzell, S., Hadida, G., Segnon, A. C., & M’boob, S., Prentice, A. M., & Green, R. (2023). Socio-economic and food system drivers of nutrition and health transitions in The Gambia from 1990 to 2017. Global Food Security, 37, 100695. https:// doi. org/ 10. 1016/j. gfs. 2023. 100695 Ali, Z., Scheelbeek, P. F. D., Felix, J., Jallow, B., Palazzo, A., Segnon, A. C., Havlík, P., Prentice, A. M., & Green, R. (2022). Adherence to EAT-Lancet dietary recommendations for health and sustain- ability in the Gambia. Environmental Research Letters, 17(10), 104043. https:// doi. org/ 10. 1088/ 1748- 9326/ ac9326 Arneth, A., Balkovic, J., Ciais, P., de Wit, A., Deryng, D., Elliott, J., Folberth, C., Glotter, M., Iizumi, T., Izaurralde, R. C., Jones, A. D., Khabarov, N., Lawrence, P., Liu, W., Mitter, H., Müller, C., Olin, S., Pugh, T. A. M., Reddy, A. D., … Büchner, M. (2017). ISIMIP2a Simulation Data from Agricultural Sector. GFZ Data Services. https:// doi. org/ 10. 5880/ PIK. 2017. 006 Bambio, Y., Deb, A., & Kazianga, H. (2022). Exposure to agricultural technologies and adoption: The West Africa agricultural produc- tivity program in Ghana, Senegal and Mali. Food Policy, 113, 102288. https:// doi. org/ 10. 1016/j. foodp ol. 2022. 102288 Belford, C., Huang, D., Ahmed, Y. N., Ceesay, E., & Sanyang, L. (2023). An economic assessment of the impact of climate change on the Gambia’s agriculture sector: A CGE approach. Interna- tional Journal of Climate Change Strategies and Management, 15(3), 322–352. https:// doi. org/ 10. 1108/ IJCCSM- 01- 2022- 0003 Bizikova, L., Nkonya, E., Minah, M., Hanisch, M., Turaga, R. M. R., Speranza, C. I., Karthikeyan, M., Tang, L., Ghezzi-Kopel, K., Kelly, J., Celestin, A. C., & Timmers, B. (2020). A scoping review of the contributions of farmers’ organizations to smallholder agri- culture. Nature Food, 1(10), 620–630. https:// doi. org/ 10. 1038/ s43016- 020- 00164-x Carr, T. W., Mkuhlani, S., Segnon, A. C., Ali, Z., Zougmoré, R., Dangour, A. D., Green, R., & Scheelbeek, P. (2022). Climate change impacts and adaptation strategies for crops in West Africa: a systematic review. Environmental Research Letters, 17(5), 053001. https:// doi. org/ 10. 1088/ 1748- 9326/ ac61c8 Ceesay, M. (2011). An opportunity for increasing factor productiv- ity for rice cultivation in The Gambia through SRI. Paddy and Water Environment, 9(1), 129–135. https:// doi. org/ 10. 1007/ s10333- 010- 0235-1 Cisse, I. T., Sienta, H., Woldeyes, A., & Thierry, B. (2021). The Future of Agriculture in The Gambia: 2030–2063—Case study: Chal- lenges and opportunities for IFAD-funded projects. IFAD Gambia Team under the direction of IFAD West Africa Hub. De Graaff, J., Kessler, A., & Nibbering, J. W. (2011). Agriculture and food security in selected countries in Sub-Saharan Africa: Diver- sity in trends and opportunities. Food Security, 3(2), 195–213. https:// doi. org/ 10. 1007/ s12571- 011- 0125-4 Del Gobbo, L. C., Khatibzadeh, S., Imamura, F., Micha, R., Shi, P., Smith, M., Myers, S. S., & Mozaffarian, D. (2015). Assessing global dietary habits: A comparison of national estimatesfrom the FAO and the Global Dietary Database. The American Journal of Clinical Nutri- tion, 101(5), 1038–1046. https:// doi. org/ 10. 3945/ ajcn. 114. 087403 Dithmer, J., & Abdulai, A. (2017). Does trade openness contribute to food security? A dynamic panel analysis. Food Policy, 69, 218– 230. https:// doi. org/ 10. 1016/j. foodp ol. 2017. 04. 008 Duvallet, M., Dumas, P., Makowski, D., Boé, J., Del Villar, P. M., & Ben-Ari, T. (2021). Rice yield stability compared to major food https://doi.org/10.1007/s12571-024-01444-1 https://gambia.shinyapps.io/FABLE-Gambia/ http://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1038/s43016-020-00191-8 https://doi.org/10.1038/s43016-020-00191-8 https://doi.org/10.1016/j.gfs.2023.100695 https://doi.org/10.1088/1748-9326/ac9326 https://doi.org/10.5880/PIK.2017.006 https://doi.org/10.1016/j.foodpol.2022.102288 https://doi.org/10.1108/IJCCSM-01-2022-0003 https://doi.org/10.1038/s43016-020-00164-x https://doi.org/10.1038/s43016-020-00164-x https://doi.org/10.1088/1748-9326/ac61c8 https://doi.org/10.1088/1748-9326/ac61c8 https://doi.org/10.1007/s10333-010-0235-1 https://doi.org/10.1007/s10333-010-0235-1 https://doi.org/10.1007/s12571-011-0125-4 https://doi.org/10.3945/ajcn.114.087403 https://doi.org/10.1016/j.foodpol.2017.04.008 702 T. W. Carr et al. crops in West Africa. Environmental Research Letters, 16(12), 124005. https:// doi. org/ 10. 1088/ 1748- 9326/ ac343a Ebile, P. A., Phelan, L., & Wünsche, J. N. (2022). The role of home gardens in empowering minority women and improving food and nutrition insecurity: A case of Mbororo community in Cameroon’s Northwest region. Agroecology and Sustainable Food Systems, 46(7), 1002–1024. https:// doi. org/ 10. 1080/ 21683 565. 2022. 20803 13 FAO. (2022). Impact of the Ukraine-Russia conflict on global food security and related matters under the mandate of the Food and Agriculture Organization of the United Nations (FAO). FAO Council, 169th Session. www. fao. org/3/ ni734 en/ ni734 en. pdf FAO. (2023). FAOSTAT . https:// www. fao. org/ faost at/ en/# home Fontan Sers, C., & Mughal, M. (2020). Covid-19 outbreak and the need for rice self-sufficiency in West Africa. World Development, 135, 105071. https:// doi. org/ 10. 1016/j. world dev. 2020. 105071 Gajigo, O., & Saine, A. (2011). The effects of government policies on cereal consumption pattern change in the Gambia. Review of African Political Economy, 38(130), 517–536. https:// doi. org/ 10. 1080/ 03056 244. 2011. 633826 Gaupp, F., Hall, J., Hochrainer-Stigler, S., & Dadson, S. (2020). Changing risks of simultaneous global breadbasket failure. Nature Climate Change, 10(1), 1. https:// doi. org/ 10. 1038/ s41558- 019- 0600-z Giller, K. E. (2020). The Food Security Conundrum of sub-Saharan Africa. Global Food Security, 26, 100431. https:// doi. org/ 10. 1016/j. gfs. 2020. 100431 Government of The Gambia. (2019). Second Generation National Agri- cultural Investment Plan-Food and Nutrition Security (GNAIP II-FNS). Government of The Gambia. Hadida, G., Ali, Z., Kastner, T., Carr, T. W., Prentice, A. M., Green, R., & Scheelbeek, P. (2022). Changes in Climate Vulnerability and Projected Water Stress of The Gambia’s Food Supply Between 1988 and 2018: Trading With Trade-Offs. Frontiers in Public Health, 10, 786071. https:// doi. org/ 10. 3389/ fpubh. 2022. 786071 Havlík, P., Valin, H., Herrero, M., Obersteiner, M., Schmid, E., Rufino, M. C., Mosnier, A., Thornton, P. K., Böttcher, H., Conant, R. T., Frank, S., Fritz, S., Fuss, S., Kraxner, F., & Notenbaert, A. (2014). Climate change mitigation through livestock system transitions. Proceedings of the National Academy of Sciences, 111(10), 3709– 3714. https:// doi. org/ 10. 1073/ pnas. 13080 44111 Janssens, C., Havlík, P., Boere, E., Palazzo, A., Mosnier, A., Leclère, D., Balkovič, J., & Maertens, M. (2022). A sustainable future for Africa through continental free trade and agricultural devel- opment. Nature Food, 3(8), 608–618. https:// doi. org/ 10. 1038/ s43016- 022- 00572-1 Janssens, C., Havlík, P., Krisztin, T., Baker, J., Frank, S., Hasegawa, T., Leclère, D., Ohrel, S., Ragnauth, S., Schmid, E., Valin, H., Van Lipzig, N., & Maertens, M. (2020). Global hunger and climate change adaptation through international trade. Nature Climate Change, 10(9), 829–835. https:// doi. org/ 10. 1038/ s41558- 020- 0847-4 Jarvis, A., Ramirez-Villegas, J., Herrera Campo, B. V., & Navarro- Racines, C. (2012). Is Cassava the Answer to African Climate Change Adaptation? Tropical Plant Biology, 5(1), 9–29. https:// doi. org/ 10. 1007/ s12042- 012- 9096-7 Kareem, O. I., & Wieck, C. (2021). Mapping agricultural trade within the ECOWAS: Structure and flow of agricultural products, bar- riers to trade, financing gaps and policy options. A research pro- ject in cooperation with GIZ on behalf of BMZ, Hohenheimer Agrarökonomische Arbeitsberichte. https:// nbn- resol ving. de/ urn: nbn: de: bsz: 100- opus- 19876 KC, S., & Lutz, W. (2017). The human core of the shared socioeco- nomic pathways: Population scenarios by age, sex and level of education for all countries to 2100. Global Environmental Change, 42, 181–192. https:// doi. org/ 10. 1016/j. gloen vcha. 2014. 06. 004 Kinnunen, P., Guillaume, J. H. A., Taka, M., D’Odorico, P., Siebert, S., Puma, M. J., Jalava, M., & Kummu, M. (2020). Local food crop pro- duction can fulfil demand for less than one-third of the population. Nature Food, 1(4), 4. https:// doi. org/ 10. 1038/ s43016- 020- 0060-7 Luan, Y., Cui, X., & Ferrat, M. (2013). Historical trends of food self- sufficiency in Africa. Food Security, 5(3), 393–405. https:// doi. org/ 10. 1007/ s12571- 013- 0260-1 MacCarthy, D. S., Adiku, S. G. K., Freduah, B. S., Gbefo, F., & Kamara, A. Y. (2017). Using CERES-Maize and ENSO as decision support tools to evaluate climate-sensitive farm management practices for maize production in the Northern Regions of Ghana. Frontiers in Plant Science. https:// doi. org/ 10. 3389/ fpls. 2017. 00031 MECCNAR. (2021). The Gambia 2050 Climate Vision. The Gambian Ministry of Environment Climate Change and Natural Resources (MECCNAR). Government of The Gambia. Mechiche-Alami, A., & Abdi, A. M. (2020). Agricultural produc- tivity in relation to climate and cropland management in West Africa. Scientific Reports, 10(1), 3393. https:// doi. org/ 10. 1038/ s41598- 020- 59943-y Morsy, H., Salami, A., & Mukasa, A. N. (2021). Opportunities amid COVID-19: Advancing intra-African food integration. World Devel- opment, 139, 105308. https:// doi. org/ 10. 1016/j. world dev. 2020. 105308 Mosnier, A., Penescu, L., Pérez-Guzmán, K., Steinhauser, J., Thom- son, M., Douzal, C., & Poncet, J. (2020). FABLE Calculator 2020 update. International Institute for Applied Systems Anal- ysis (IIASA) and Sustainable Development Solutions Network (SDSN), Laxenburg, Austria. https:// doi. org/ 10. 22022/ ESM/ 12- 2020. 16934 Mosnier, A., Schmidt-Traub, G., Obersteiner, M., Jones, S., Javalera- Rincon, V., DeClerck, F., Thomson, M., Sperling, F., Harrison, P., Pérez-Guzmán, K., McCord, G. C., Navarro-Garcia, J., Marcos- Martinez, R., Wu, G. C., Poncet, J., Douzal, C., Steinhauser, J., Monjeau, A., Frank, F., & Wang, X. (2023). How can diverse national food and land-use priorities be reconciled with global sustainability targets? Lessons from the FABLE initiative. Sustainability Science, 18(1), 335–345. https:// doi. org/ 10. 1007/ s11625- 022- 01227-7 Mueller, N. D., Gerber, J. S., Johnston, M., Ray, D. K., Ramankutty, N., & Foley, J. A. (2012). Closing yield gaps through nutrient and water management. Nature, 490(7419), 254–257. https:// doi. org/ 10. 1038/ natur e11420 NaNA. (2021). National Nutrition Policy (2021 – 2025). National Nutrition Agency (NaNA). Government of The Gambia. Palazzo, A., Vervoort, J. M., Mason-D’Croz, D., Rutting, L., Havlík, P., Islam, S., Bayala, J., Valin, H., Kadi Kadi, H. A., Thornton, P., & Zougmore, R. (2017). Linking regional stakeholder scenarios and shared socioeconomic pathways: Quantified West African food and climate futures in a global context. Global Environmental Change, 45, 227–242. https:// doi. org/ 10. 1016/j. gloen vcha. 2016. 12. 002 Schaphoff, S., Von Bloh, W., Rammig, A., Thonicke, K., Biemans, H., For- kel, M., Gerten, D., Heinke, J., Jägermeyr, J., Knauer, J., Langerwisch, F., Lucht, W., Müller, C., Rolinski, S., & Waha, K. (2018). LPJmL4 – a dynamic global vegetation model with managed land – Part 1: Model description. Geoscientific Model Development, 11(4), 1343–1375. https:// doi. org/ 10. 5194/ gmd- 11- 1343- 2018 Segnon, A. C., Zougmoré, R. B., & Houessionon, P. (2021). Technolo- gies and practices for agriculture and food system adaptation to climate change in The Gambia. CCAFS Working Paper no. 344. Wageningen, the Netherlands: CGIAR Research Program on Cli- mate Change, Agriculture and Food Security (CCAFS). Segnon, A. C., Zougmoré, R. B., Green, R., Ali, Z., Carr, T. W., Houessionon, P., & M’boobScheelbeek, S. P. S. D. (2022a). Climate change adaptation options to inform planning of agriculture and food systems in The Gambia: A systematic approach for stocktaking. Frontiers in Sustainable Food Systems, 6, 834867. https:// doi. org/ 10. 3389/ fsufs. 2022. 834867 https://doi.org/10.1088/1748-9326/ac343a https://doi.org/10.1080/21683565.2022.2080313 http://www.fao.org/3/ni734en/ni734en.pdf https://www.fao.org/faostat/en/#home https://doi.org/10.1016/j.worlddev.2020.105071 https://doi.org/10.1080/03056244.2011.633826 https://doi.org/10.1080/03056244.2011.633826 https://doi.org/10.1038/s41558-019-0600-z https://doi.org/10.1038/s41558-019-0600-z https://doi.org/10.1016/j.gfs.2020.100431 https://doi.org/10.1016/j.gfs.2020.100431 https://doi.org/10.3389/fpubh.2022.786071 https://doi.org/10.1073/pnas.1308044111 https://doi.org/10.1038/s43016-022-00572-1 https://doi.org/10.1038/s43016-022-00572-1 https://doi.org/10.1038/s41558-020-0847-4 https://doi.org/10.1038/s41558-020-0847-4 https://doi.org/10.1007/s12042-012-9096-7 https://doi.org/10.1007/s12042-012-9096-7 https://nbn-resolving.de/urn:nbn:de:bsz:100-opus-19876 https://nbn-resolving.de/urn:nbn:de:bsz:100-opus-19876 https://doi.org/10.1016/j.gloenvcha.2014.06.004 https://doi.org/10.1016/j.gloenvcha.2014.06.004 https://doi.org/10.1038/s43016-020-0060-7 https://doi.org/10.1007/s12571-013-0260-1 https://doi.org/10.1007/s12571-013-0260-1 https://doi.org/10.3389/fpls.2017.00031 https://doi.org/10.1038/s41598-020-59943-y https://doi.org/10.1038/s41598-020-59943-y https://doi.org/10.1016/j.worlddev.2020.105308 https://doi.org/10.22022/ESM/12-2020.16934 https://doi.org/10.22022/ESM/12-2020.16934 https://doi.org/10.1007/s11625-022-01227-7 https://doi.org/10.1038/nature11420 https://doi.org/10.1038/nature11420 https://doi.org/10.1016/j.gloenvcha.2016.12.002 https://doi.org/10.5194/gmd-11-1343-2018 https://doi.org/10.3389/fsufs.2022.834867 https://doi.org/10.3389/fsufs.2022.834867 703Addressing future food demand in The Gambia: can increased crop... Segnon, A. C., Zougmoré, R. B., & M’Boob, S. (2022b). Priority adaptation options for agriculture and food systems in The Gam- bia. https:// cgspa ce. cgiar. org/ handle/ 10568/ 126094 Sperling, F., Havlik, P., Denis, M., Valin, H., Palazzo, A., Gaupp, F., & Visconti, P. (2022). Toward resilient food systems after COVID- 19. Current Research in Environmental Sustainability, 4, 100110. https:// doi. org/ 10. 1016/j. crsust. 2021. 100110 Stewart, Z. P., Pierzynski, G. M., Middendorf, B. J., & Prasad, P. V. V. (2020). Approaches to improve soil fertility in sub-Saharan Africa. Journal of Experimental Botany, 71(2), 632–641. https:// doi. org/ 10. 1093/ jxb/ erz446 Trisos, C. H., Adelekan, I. O., Totin, E., Ayanlade, A., Efitre, J., Gemeda, A., Kalaba, K., Lennard, C., Masao, C., Mgaya, Y., Ngaruiya, G., Olago, D., Simpson, N. P., & Zakieldeen, S. (2022). Africa. In H.-O. Pörtner, D. C. Roberts, M. Tignor, E. S. Poloczanska, K. Mintenbeck, A. Alegría, M. Craig, S. Langsdorf, S. Löschke, V. Möller, A. Okem, & B. Rama (Eds.), Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 1285–1455). Cam- bridge University Press. https:// doi. org/ 10. 1017/ 97810 09325 844. 011 Valin, H., Sands, R. D., van der Mensbrugghe, D., Nelson, G. C., Ahammad, H., Blanc, E., Bodirsky, B., Fujimori, S., Hasegawa, T., Havlik, P., Heyhoe, E., Kyle, P., Mason-D’Croz, D., Paltsev, S., Rolinski, S., Tabeau, A., van Meijl, H., von Lampe, M., & Willenbockel, D. (2014). The future of food demand: Understanding differences in global economic models. Agricultural Economics, 45(1), 51–67. https:// doi. org/ 10. 1111/ agec. 12089 van Soest, H. L., van Vuuren, D. P., Hilaire, J., Minx, J. C., Harmsen, M. J. H. M., Krey, V., Popp, A., Riahi, K., & Luderer, G. (2019). Analysing interactions among Sustainable Development Goals with Integrated Assessment Models. Global Transitions, 1, 210–225. https:// doi. org/ 10. 1016/j. glt. 2019. 10. 004 World Bank. (2019). The Gambia agriculture engagement note: Fos- tering agriculture-led inclusive growth. © World Bank. https:// docum ents1. world bank. org/ curat ed/ en/ 81469 15604 11931 505/ pdf/ The- Gambia- Agric ulture- Engag ement- Note- Foste ring- Agric ulture- Led- Inclu sive- Growth. pdf World Bank. (2023). Population growth (annual %)—The Gambia. https:// data. world bank. org/ indic ator/ SP. POP. GROW? end= 2021& locat ions= GM& start= 1961& view= chart Zougmoré, R., Jalloh, A., & Tioro, A. (2014). Climate-smart soil water and nutrient management options in semiarid West Africa: A review of evidence and analysis of stone bunds and zaï techniques. Agriculture & Food Security, 3(1), 16. https:// doi. org/ 10. 1186/ 2048- 7010-3- 16 Zougmoré, R. B., Partey, S. T., Ouédraogo, M., Torquebiau, E., & Campbell, B. M. (2018). Facing climate variability in sub-Saharan Africa: Analysis of climate-smart agriculture oppor tuni t ies to manage climate-related risks. Cahiers Agricultures, 27(3), 3. https:// doi. org/ 10. 1051/ cagri/ 20180 19 Tony W. Carr Dr Tony Carr is a Research Fellow at the London School of Hygiene & Tropical Medicine (LSHTM). His research focuses on the links between agriculture, the environment, and health. Prior to joining LSHTM, he completed his PhD at Uni- versity College London on the impacts of soil degradation and climate change on global cereal production. Felicity Addo Dr Felicity Addo is a research scholar at the International Institute for Applied Systems Analy- sis. Her current scientific interests include examining food security pathways in developing countries and micro-econometric modelling of agri- cultural production systems applied to i) farm efficiency, competitiveness, and performance, ii) agricultural policies and iii) farmers’ input use, costs, and investment decisions. Currently, she contributes to multiple projects in the EU and Africa. Amanda Palazzo Amanda Palazzo (Research Scholar at the Inter- national Institute for Applied Systems Analysis (IIASA)) is one of the main developers of the partial- equilibrium model Global Biosphere Management Model (GLOBIOM). Her main topics of research concern participatory approaches to develop and model plausible regional future scenarios of food security and agri- cultural development, the representa- tion of the water-energy-land nexus in economic modelling including impacts of climate change and growing secto- ral demands (agriculture, domestic, energy, and environment), and assess- ing the impacts of investments in irrigation infrastructure. She has also worked extensively in stakeholder engagement to link qualitative and quantitative scenarios and modelling tools. Petr Havlik Dr Petr Havlik (Deputy Program Director, Ecosystem Services and Management, IIASA) oversees the use of EPIC and GLOBIOM models developed at IIASA to fit the data specific to The Gambia. He coordinates the instituteʼs contributions to global land use related foresight and assessment activities with European Commission funded research projects, and with interna- tional agencies such as the Food and Agriculture Organization of the United Nations (FAO), the Organisation for Economic Co-operation and Develop- ment (OECD), and the World Bank. At the national level, Havlik coordi- nates the contribution to policies and regulatory processes in, among others, China, the European Union, Indonesia, and the USA. While working at IIASA, he also held a three-year joint position with the International Livestock Research Institute (ILRI). Katya Pérez‑Guzmán Dr Katya Perez Guzman is a research scholar the IIASA Strategic Initiatives Program. Her main interest is to develop and promote quantitative scientific instruments to inform public policy on climate change in Mexico. Perez Guzman supported https://cgspace.cgiar.org/handle/10568/126094 https://doi.org/10.1016/j.crsust.2021.100110 https://doi.org/10.1093/jxb/erz446 https://doi.org/10.1093/jxb/erz446 https://doi.org/10.1017/9781009325844.011 https://doi.org/10.1111/agec.12089 https://doi.org/10.1016/j.glt.2019.10.004 https://doi.org/10.1016/j.glt.2019.10.004 https://documents1.worldbank.org/curated/en/814691560411931505/pdf/The-Gambia-Agriculture-Engagement-Note-Fostering-Agriculture-Led-Inclusive-Growth.pdf https://documents1.worldbank.org/curated/en/814691560411931505/pdf/The-Gambia-Agriculture-Engagement-Note-Fostering-Agriculture-Led-Inclusive-Growth.pdf https://documents1.worldbank.org/curated/en/814691560411931505/pdf/The-Gambia-Agriculture-Engagement-Note-Fostering-Agriculture-Led-Inclusive-Growth.pdf https://documents1.worldbank.org/curated/en/814691560411931505/pdf/The-Gambia-Agriculture-Engagement-Note-Fostering-Agriculture-Led-Inclusive-Growth.pdf https://data.worldbank.org/indicator/SP.POP.GROW?end=2021&locations=GM&start=1961&view=chart https://data.worldbank.org/indicator/SP.POP.GROW?end=2021&locations=GM&start=1961&view=chart https://doi.org/10.1186/2048-7010-3-16 https://doi.org/10.1186/2048-7010-3-16 https://doi.org/10.1051/cagri/2018019 https://doi.org/10.1051/cagri/2018019 704 T. W. Carr et al. the IIASA Food, Agriculture, Biodi- versity, Land, and Energy (FABLE) project from 2019–2021, as part of the larger Food and Land Use Coali- tion (FOLU) initiative. This crystal- lized her experience within a global consortium of climate change policy and research network, where she helps stakeholders to model, analyze, and better understand the different future policy scenarios of land use, food, and agriculture systems. Her main responsibility was supporting capacity building and the development of the FABLE calculator, an Excel based model that performs integrated analysis of the nexus between land use, food, and agriculture systems, with inclusion of biodiversity, climate change, and water criteria. Zakari Ali Dr Zakari Ali is a Research fellow at the MRC Unit The Gam- bia at the London School of Hygiene & Tropical Medicine (LSHTM) based in The Gambia – working on the FACE- Africa project. Zakari’s research focuses on mapping the Gambian food system and its adaptations to climate change using existing secondary data sources. He works closely with the Gambian food system stakeholders including government ministries and departments, NGOs, researchers, local farmers and climate interest groups to co-create evidence that is locally relevant for policy and adaptation to climate change. Zakari has MSc in Nutrition for Global Health from LSHTM and previously worked for two years as a Research Assistant in Ghana with the University for Devel- opment Studies where he worked on maternal, child and adolescent nutri- tion research. Rosemary Green Dr Rosie Green is a Professor in Sustainability, Nutri- tion and Health at the London School of Hygiene & Tropical Medicine. The focus of her work is on the links between nutrition, environment and health, particularly identifying dietary changes that would be positive for human health and the planet. She is a co-PI on the FACE-Africa and Path- finder projects, and also works on the Sustainable and Healthy Food Systems (SHEFS) project, the AMPHoRA pro- ject exploring air pollution from agri- culture in the UK and the South Asia Nitrogen Hub investigating health impacts of reducing nitrogen pollution from agriculture. Genevieve Hadida Genevieve Hadida joined the London School of Hygiene & Tropical Medicine as a Research Assistant in 2021, having completed an MSc in Nutrition for Global Health at the school. Her research interests lie at the intersection of food systems, nutrition and sustainability. Her work has focused on analysing The Gambia’s trade of crops, particularly the climate vulnerability of its imports. Alcade C. Segnon Dr Alcade Segnon is a Postdoctoral Scientist at the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), based at ICRISAT in Bamako, Mali. Alcade’s research interest is the intersec- tion of climate change adaptation, agro- biodiversity and traditional knowledge systems; and agroecosystem sustainabil- ity. He is particularly interested in how and to what extent agrobiodiversity and knowledge that local people share on it can be used to improve smallholders' livelihoods and resilience to environmental change. Alcade’s research also includes assessing adaptation effectiveness to inform policy decision making across scales. Dr Segnon is involved in the Global Adaptation Mapping Initiative (GAMI) and is a Contributing Author of the IPCC’s sixth Assessment Report, WGII. Robert Zougmoré As the CCAFS Africa Program leader since 2010, I have been defining and overseeing strategic directions for CCAFS research in the region and therefore, coordinating actions that lead to coherent implementation of the regional activities from the participating CGIAR Centres and other regional and national partners. One of my major tasks is to communicating regional research outputs and strategy through innovative means. Under my leader- ship, CCAFS action research was conducted at all levels in a way to generate scientific information that inform top-down and bottom-up decision-making processes on climate change, agriculture and food security. Pauline Scheelbeek Dr Pauline Scheelbeek is an Associate Professor in nutritional and environmental epidemiology at the London School of Hygiene & Tropical Medicine. Pauline’s research focusses on quan- tifying the impact of changing environments on agriculture, food avail- ability and quality, nutrition, and health. Currently she is the health lead for the multi-country Sustainable and Health Food Systems (SHEFS) project and leads (together with Dr Rosemary Green) the Food system Adaptations in Changing Environments in Africa (FACE-Africa) project in the Gambia. In this context she models future food systems for the UK, South Africa and India under several climate change and adaptation scenarios. Pauline is an active STEM ambassador and frequently organ- ises public engagement activities for school aged children in the UK and sub-Saharan Africa around environment, nutrition and health issues. Addressing future food demand in The Gambia: can increased crop productivity and climate change adaptation close the supply–demand gap? Abstract 1 Introduction 2 Methods 2.1 The FABLE calculator 2.2 An empirical application to The Gambian food and land-use system 2.3 Parameters of the FABLE Gambia model 2.4 Considerations on fixed dietary scenario in food demand projections 3 Results 3.1 Future food demand and requirements for production and imports in The Gambia 3.2 Feasible food production under different climate change and crop productivity scenarios 4 Discussion 4.1 Summary of findings 4.2 The role of diets in The Gambia's changing food demand 4.3 Policy and practice recommendations 4.3.1 Enhancing agricultural productivity in The Gambia 4.3.2 Enhancing food supply in The Gambia through trade 4.4 Opportunities and limitations in modelling future food supply and demand in The Gambia 5 Conclusion Acknowledgements References