Market is the structure for the development and delivery of innovations that are able to address environmental, societal, and economic challenges. The lack of enabling conditions for market development has resulted in low investment levels and economic stagnation, impacting livelihoods in Africa. Although there have been efforts to implement market-driven reforms, challenges such as inadequate policies, weak legal frameworks, transparency issues and bureaucratic inefficiencies pose significant risks for public and private investments and for their potential to reach the target beneficiaries. This situation also discourages development partners and businesses from investing in the region.Technical assistance is crucial to improve the investment climate. This paper presents a framework to help governments create a more conducive environment for agricultural market development and the private sector to navigate through the existing challenges. Traditional technical assistance practices have faced criticism for adopting a one-size-fits-all approach that overlooks local contexts. Recently, however, there has been a shift towards more context-based and adaptive assistance, which informs this framework. This framework emphasizes key elements that contribute to an enabling environment, including institutions, such as policies, regulations, and legal frameworks, as well as clear market and regulatory information that help reduce transaction costs. The framework is theoretically based on new institutional economics and political economy approaches. It focuses on assistance in three areas with three categories of delivery partners: policy support to governments, institutional capacity strengthening (especially of National Agricultural Research and Extension Systems) and (agri)business acceleration support to small- and medium-scale enterprises. Through such assistance, this framework seeks to help create an enabling environment for the delivery of innovations that offer solutions to emerging climate, societal and economic crises. These solutions, especially those developed and scaled by the private sector, are targeted toward recipients such as farmers (including women and the youth), marginalized groups, displaced communities, refugees and migrants. The framework utilizes value chain and market development as the primary delivery structures. This framework has guided several recent enabling environment assistance practices under CGIAR’s International Water Management Institute (IWMI). This paper explores these practices and positions CGIAR as a strong technical assistance partner. While this framework offers a systematic approach to analyzing the enabling environment, the technical assistance driven by this framework promotes collaboration and co-creation. It actively engages governments, national research and extension offices, farmers and other stakeholders in influencing policies and business transaction advisories that directly benefit them. Furthermore, it aims to strengthen their capacities to diagnose and overcome enabling environment challenges as they arise. By helping to create an enabling environment for the private sector—especially small- and medium-scale enterprises that innovate and scale—and derisking the investment climate, this framework seeks to strengthen agrifood market systems to foster food security and alleviate poverty.

This study explored the determinants of scientific attitude among undergraduate agriculture students in Telangana State of India, analyzing their attitude levels and demographic influences. A sample of 250 B.Sc. Agriculture students from Professor Jayashankar Telangana Agricultural University was surveyed using random sampling. Factor analysis, normal probability curve, and inferential analysis revealed that most students exhibited a moderate scientific attitude, with significant differences based on gender, age, and parental occupation. Male students and those below 19 showed higher engagement, while students from government-employed families had the highest scores. Findings suggested the need for targeted educational strategies, including curiosity-driven learning, hands-on experiments, gender equity, early exposure, and infrastructure upgrades, to enhance scientific attitudes in agricultural education.

Optimal water resource allocation in agricultural irrigation districts constitutes a core strategy for achieving coordinated regional water–food–ecosystem development. However, current studies rarely integrate inter-basin water diversion projects into the allocation, and the prolonged operation of diversion systems fails to adequately consider their ecological impacts in the irrigation districts. This study incorporates inter-basin water diversion into supply–demand dynamics and considers its influence on groundwater table changes in terrestrial ecological targets. Inexact two-stage stochastic programming (ITSP) was applied for optimal water allocation to address uncertainties from fluctuations in future water availability and interval ambiguity in socioeconomic information. Taking the densely populated agricultural irrigation district of Huaibei as a case study, we established a multi-stakeholder allocation model, considering the Yangtze-to-Huai water diversion project, to maximize comprehensive benefits under multiple scenarios of water availability for the years of 2030 and 2040. The results demonstrate that the district will face escalating water scarcity risks, with demand–supply gaps widening when available water resources decrease. The water redistribution in the second stage reduces scarcity-induced losses, achieving maximum comprehensive benefits. The water diversion project enhances supply capacity and boosts economic gains. The project can also decrease the fluctuation range of the total benefits by 5 × 10⁶ CNY (2030) and 3.4 × 10⁷ CNY (2040), compared with the scenario without the project. From 2030 to 2040, limited water resources will progressively shift toward sectors with higher economic output per unit water, squeezing agricultural allocations. Therefore, for irrigation districts in developing countries, maintaining a minimum guaranteed rate of agricultural water proves critical to safeguarding food security.

European agriculture must transform to confront the many challenges it faces, yet there are different sets of values that may underpin future agricultural change. However, we currently lack thorough understanding of the implications of operationalising these plural values for European land systems. In this article, we apply the IPBES Nature Futures Framework to develop a set of three land-change scenario narratives—the Agricultural Futures Framework (AFF)—representing the diverse ways that humans value agricultural land systems: Land for Food and Land for Nature, Land as Culture, and Land for Society. We operationalise the AFF scenarios in the CLUMondo land-change model and simulate how these alternative value perspectives could reshape land systems in Europe by 2050, accounting for future demands for food production, carbon sequestration, nature restoration, and nitrogen emission reduction. We find that significant land-system reconfiguration would be needed to fulfil these multiple demands under all three scenarios, ranging from 18.8% to 37.1% of all European land, with multiple scenarios showing multifunctional pathways in Eastern Romania and Bulgaria, productivist pathways in Poland and Slovakia, and marginalisation/rewilding pathways in Central France and Northern Spain. However, the magnitude and spatial locations of change differ substantially across the prioritised value perspectives, suggesting that these may have large implications for future agricultural development. The AFF framework and our findings are useful for identifying opportunities to reconcile the divisions in values perspectives, and to prioritise interventions for agri-food transformations.

The connectivity of forest ecosystems is increasingly recognized as a key factor in evaluating the sustainability of forest management, with significant implications for biodiversity conservation. This study examines the impact of afforestation programs on forest evolution, fragmentation, and connectivity in León province, Spain, over the past 25 years (1996–2020). Three scenarios were modeled across two periods (1996–2006 and 2006–2020), integrating data from the national forest inventories (IFN2, IFN3, and IFN4) and afforestation program records provided by the Junta de Castilla y León. The evolution of connectivity “with” and “without” afforestation was analyzed using Graphab 2.6 and graph theory, and several connectivity metrics were calculated. The first period analyzed, influenced by the two initial afforestation programs, corresponded to the end of a forest expansion phase, followed by a decrease in tree cover. Despite this reduction, a net positive balance of up to 24% of all connectivity metrics (NC, PC, Flux, and ECA) was observed throughout the study period. Afforestation in mountain areas enhanced tree cover continuity, resulting in a more homogeneous but less diverse landscape. Conversely, afforestation in agricultural lands increased landscape heterogeneity, diversifying and extending the ecological network of connections. These programs have played a crucial role in shaping the landscape, influencing its diversity and the evolution of forest connectivity. Legislation grounded in technical and ecological principles should be prioritized as a strategic tool to address pressing land management challenges and preserve natural values.

The connectivity of forest ecosystems is increasingly recognized as a key factor in evaluating the sustainability of forest management, with significant implications for biodiversity conservation. This study examines the impact of afforestation programs on forest evolution, fragmentation, and connectivity in León province, Spain, over the past 25 years (1996–2020). Three scenarios were modeled across two periods (1996–2006 and 2006–2020), integrating data from the national forest inventories (IFN2, IFN3, and IFN4) and afforestation program records provided by the Junta de Castilla y León. The evolution of connectivity “with” and “without” afforestation was analyzed using Graphab 2.6 and graph theory, and several connectivity metrics were calculated. The first period analyzed, influenced by the two initial afforestation programs, corresponded to the end of a forest expansion phase, followed by a decrease in tree cover. Despite this reduction, a net positive balance of up to 24% of all connectivity metrics (NC, PC, Flux, and ECA) was observed throughout the study period. Afforestation in mountain areas enhanced tree cover continuity, resulting in a more homogeneous but less diverse landscape. Conversely, afforestation in agricultural lands increased landscape heterogeneity, diversifying and extending the ecological network of connections. These programs have played a crucial role in shaping the landscape, influencing its diversity and the evolution of forest connectivity. Legislation grounded in technical and ecological principles should be prioritized as a strategic tool to address pressing land management challenges and preserve natural values.

Understanding vegetation heterogeneity dynamics is crucial for assessing ecosystem resilience, biodiversity patterns, and the impacts of environmental changes on landscape functions. While previous studies primarily focused on NDVI pixel trends, shifts in landscape heterogeneity have often been overlooked. To address this gap, our study evaluated the effectiveness of continuous metrics in capturing vegetation dynamics over time, emphasizing their utility in short-term trend analysis. The study area, located in Iran, encompasses a mix of urban and agricultural landscapes dominated by farming-related vegetation. Using 11 Landsat 8 OLI images from 2013 to 2023, we calculated NDVI to analyze vegetation trends and heterogeneity dynamics. We applied three categories of continuous metrics: texture-based metrics (dissimilarity, entropy, and homogeneity), spatial autocorrelation indices (Getis and Moran), and surface metrics (Sa, Sku, and Ssk) to assess vegetation heterogeneity. By generating slope maps through linear regression, we identified significant trends in NDVI and correlated them with the slope maps of the continuous metrics to determine their effectiveness in capturing vegetation dynamics. Our findings revealed that Moran’s Index exhibited the highest positive correlation (0.63) with NDVI trends, followed by Getis (0.49), indicating strong spatial clustering in areas with increasing NDVI. Texture-based metrics, particularly dissimilarity (0.45) and entropy (0.28), also correlated positively with NDVI dynamics, reflecting increased variability and heterogeneity in vegetation composition. In contrast, negative correlations were observed with metrics such as homogeneity (−0.41), Sku (−0.12), and Ssk (−0.24), indicating that increasing NDVI trends were associated with reduced uniformity and surface dominance. Our analysis underscores the complementary roles of these metrics, with spatial autocorrelation metrics excelling in capturing clustering patterns and texture-based metrics highlighting value variability within clusters. By demonstrating the utility of spatial autocorrelation and texture-based metrics in capturing heterogeneity trends, our findings offer valuable tools for land management and conservation planning.

Sri Lanka Government’s ambitious decision to ban synthetic agrochemicals, including chemical fertilizers (and pesticides), in April 2021 made it the first nation in the world to embark on a full-scale transition to – as the Government called it—organic farming, and address concerns about human health and the environment. Previous policies had envisioned a gradual shift, but the sudden ban caught agriculture off guard. Declining foreign exchange reserves to import chemical fertilizers and coinciding peak fertilizer prices appeared to support the timing of the move. However, the ensuing rush for organic fertilizers failed to meet the national demand, resulting in severe losses in rice and export-oriented plantation crops. Facing decreasing yields and food insecurity, the government lifted the ban in November 2021. The events raised critical questions about the necessity and feasibility of such a drastic transition and alternative ways. To explore the general feasibility of transitioning toward organic fertilizers, this study considered the actual and potential availability of biomass to “replace” chemical fertilizers at the national scale as was envisioned by the Government. The analysis focused on the four main national crops and showed that in none of the selected scenarios, Sri Lanka’s actual and potentially available organic fertilizer could supply rice- and plantation-based agrosystems with sufficient nitrogen, not to mention other crops or nutrients. The Government will in every scenario, including one that assumes a stepwise transition, remain compelled to spend significantly on importing organic fertilizer to maintain the required crop yields, which would cost the Government more foreign currency than purchasing chemical fertilizer. Even more costly is purchasing rice to close the national production gap, as Sri Lanka eventually did at the end of its nationwide experiment, which resulted in major food security concerns.

Quantifying the thresholds and processes of drought propagation is of great significance for early drought warning and ecosystem management. Our understanding of their spatial patterns and driving mechanism remains unclear. In this study, based on Copula functions, we quantified the thresholds and process of meteorological drought to agricultural drought in an alpine-oasis-desert inland river basin of China for the period of 1980–2020. Furthermore, the main factors driving drought propagation were identified using the Random Forest model. The results showed that: (1) significant spatial heterogeneity exists in the propagation of meteorological to agricultural drought, with longer propagation time and higher propagation risk in the upstream; (2) from upstream to downstream, the percentile-based average cumulative precipitation deficit threshold for triggering agricultural drought ranged from 18.5 % to 45.0 % under moderate probability conditions (greater than 0.6); (3) the response of agricultural drought to meteorological drought was characterized by intensity amplification and duration attenuation in the upstream, while the opposite occurred downstream. This response is mainly driven by the interactions of actual evapotranspiration (ETa) and vapor pressure deficit (VPD). Specifically, ETa and VPD contributed 15.7 %–54.8 % and 8.7 %–39.5 %, respectively. Additionally, irrigation also plays an important role in drought propagation, contributing 6.5 %–9.6 %. This study provides important implications and valuable insights for understanding the mechanisms of agricultural drought formation. Furthermore, the results can provide scientific guidance for watershed water allocation, drought preparedness and risk management.