Addressing future food demand in The Gambia: can increased crop productivity and climate change adaptation close the supply–demand gap?

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 production 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. However, 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 production and food imports to secure sufficient and healthy food supplies amidst growing demand and climate change challenges

Part-Time Farming and Scale Efficiency

While many studies have compared the technical effi-ciency of part-time and full-time farms, we add to the existing literature by extending this analysis to scale efficiency. Based on a sample of crop farms in Austria between 2010 and 2017, we find that part-time farms are more scale efficient when they are evaluated with respect to their production technology and the differ-ence in scale efficiency between part-time and full-time farms increases over time. Although we do not find any significant difference in technical efficiency, full-time farms have a higher technological change. Furthermore, an analysis of the determinants of scale efficiency confirms that factors facilitating farm growth also increase scale efficiency

Part-Time Farming and Scale Efficiency

While many studies have compared the technical effi-ciency of part-time and full-time farms, we add to the existing literature by extending this analysis to scale efficiency. Based on a sample of crop farms in Austria between 2010 and 2017, we find that part-time farms are more scale efficient when they are evaluated with respect to their production technology and the differ-ence in scale efficiency between part-time and full-time farms increases over time. Although we do not find any significant difference in technical efficiency, full-time farms have a higher technological change. Furthermore, an analysis of the determinants of scale efficiency confirms that factors facilitating farm growth also increase scale efficiency

Determinants of Persistent and Transient Technical Efficiency of Austrian Crop Farms

In the last two decades, the Common Agricultural Policy (CAP) of the European Union (EU) has experienced significant changes which has created a highly competitive market in which farmers operate. This is particularly challenging for countries with small-scaled agriculture like Austria, requiring farms to significantly improve technical efficiency in order to be competitive. In this paper, we apply a four-error component model to decompose technical efficiency into persistent inefficiency, which captures long run effects of farm management, and transient inefficiency, which accounts for how farms adjust to short run production shocks, while controlling for farm heterogeneity and a random error. We extend this model to include exogenous determinants for both types technical inefficiency. To do so, we estimate a translog stochastic production function for a panel of 231 Austrian crop farms for the period 2003-2016. We observe that though transient and persistent efficiency are similar on average, persistent efficiency is much more dispersed suggesting that persistent technical inefficiency poses a greater problem for Austrian crop farms than the transient component. Overall technical efficiency is estimated at 89%. Regarding persistent technical efficiency, we find that full time farms and medium to large scale farms are more efficient. However, we observe that older farmers and farms that employ a high proportion of family labour are less persistently efficient. With regards to transient technical efficiency, we find that farms that cultivate more on their own land are less transiently efficient compared to farms on rented land. Lastly, we observe that farm subsidies in general negatively affects both types of efficiency

Adaptation of the Wound Healing Questionnaire universal-reporter outcome measure for use in global surgery trials (TALON-1 study): mixed-methods study and Rasch analysis

BackgroundThe Bluebelle Wound Healing Questionnaire (WHQ) is a universal-reporter outcome measure developed in the UK for remote detection of surgical-site infection after abdominal surgery. This study aimed to explore cross-cultural equivalence, acceptability, and content validity of the WHQ for use across low- and middle-income countries, and to make recommendations for its adaptation.MethodsThis was a mixed-methods study within a trial (SWAT) embedded in an international randomized trial, conducted according to best practice guidelines, and co-produced with community and patient partners (TALON-1). Structured interviews and focus groups were used to gather data regarding cross-cultural, cross-contextual equivalence of the individual items and scale, and conduct a translatability assessment. Translation was completed into five languages in accordance with Mapi recommendations. Next, data from a prospective cohort (SWAT) were interpreted using Rasch analysis to explore scaling and measurement properties of the WHQ. Finally, qualitative and quantitative data were triangulated using a modified, exploratory, instrumental design model.ResultsIn the qualitative phase, 10 structured interviews and six focus groups took place with a total of 47 investigators across six countries. Themes related to comprehension, response mapping, retrieval, and judgement were identified with rich cross-cultural insights. In the quantitative phase, an exploratory Rasch model was fitted to data from 537 patients (369 excluding extremes). Owing to the number of extreme (floor) values, the overall level of power was low. The single WHQ scale satisfied tests of unidimensionality, indicating validity of the ordinal total WHQ score. There was significant overall model misfit of five items (5, 9, 14, 15, 16) and local dependency in 11 item pairs. The person separation index was estimated as 0.48 suggesting weak discrimination between classes, whereas Cronbach's α was high at 0.86. Triangulation of qualitative data with the Rasch analysis supported recommendations for cross-cultural adaptation of the WHQ items 1 (redness), 3 (clear fluid), 7 (deep wound opening), 10 (pain), 11 (fever), 15 (antibiotics), 16 (debridement), 18 (drainage), and 19 (reoperation). Changes to three item response categories (1, not at all; 2, a little; 3, a lot) were adopted for symptom items 1 to 10, and two categories (0, no; 1, yes) for item 11 (fever).ConclusionThis study made recommendations for cross-cultural adaptation of the WHQ for use in global surgical research and practice, using co-produced mixed-methods data from three continents. Translations are now available for implementation into remote wound assessment pathways