Interdependence among subregional crop production affects global crop failure risk

Statistical emulators of maize, rice, soybean and wheat yields from global gridded crop models

Key sustainability challenges for the global phosphorus resource, their implications for global food security, and options for mitigation

This paper discusses the Slovak regional economy structural changes, development and factors of regional economic specialisation and geographic concentration of sectors with a focus on agriculture from 1995 to 2012. Specialization and sector geographic concentration were quantified by Herfindahl and Entropy indices. At the national level we found steadily growing share of crop production at the expense of animal production. Regional concentration of both, crop and animal production and animal production specialisation has been increasing. Spatial clusters of similar specialised regions were detected for crop production. Linear panel models were used to estimate the effect of selected factors on regional crop and animal production specialisation. The agricultural policy instruments, including the CAP had significant effect on regional crop and animal production specialisation patterns. Provision of the complementary national direct payments (CNDP) and investment support had positive effect on regional crop production diversification. Density of regional road network, average annual temperature in the growing season, average annual rainfall in the growing season and provision of the LFA payments had positive effect on both regional crop and animal production diversification.

Projections of thermal growing season indices over China under global warming of 1.5 °C and 2.0 °C

Rapid changing climate has increased the risk of natural hazards and threatened global and regional food security. Near real-time monitoring of crop response to agrometeorological hazards is fundamental to ensuring national and global food security. However, quantifying crop responses to a specific hazard in the natural environment is still quite challenging, especially over large areas, due to the lack of tools to separate the independent impact of the hazard on crops from other confounding factors. In this study, we present a general difference-in-differences (DID) framework to monitor crop response to agrometeorological hazards at near real-time using widely accessible remotely sensed vegetation indices (VIs). To demonstrate the effectiveness of the DID framework, we applied it in quantifying the dry-hot wind impact on winter wheat in northern China as a case study using the VIs calculated from the MODIS data. The monitoring results for three years with varying severity levels of dry-hot events (i.e., 2007, 2013, and 2014) demonstrated that the framework can effectively detect winter wheat growing areas affected by dry-hot wind hazards. The estimated damage shows a notable relationship (R2 = 0.903, p < 0.001) with the dry-hot wind intensity calculated from meteorological data, suggesting the effectiveness of the method when field data on a large scale is not available for direct validation. The main advantage of this method is that it can effectively isolate the impact of a specific hazard (i.e., dry-hot wind in the case study) from the mixed signals caused by other confounding factors. This general DID framework is very flexible and can be easily extended to other natural hazards and crop types with proper adjustment. Not only can this framework improve the crop yield forecast but also it can provide near real-time assessment for farmers to adapt their farming practice to mitigate impacts of agricultural hazards.

Crop production is responsible for most of humanity’s water consumption. In some regions, the consumption levels already exceed sustainable limits putting local water security and ecosystems at risk. Thus, one of the grand challenges of the next decades is to satisfy growing global crop demand while minimising water consumption.<br/>One way to assess the water consumption and productivity of a crop is to use the consumptive Water Footprint (WF). It measures green and blue water volumes consumed to produce a particular crop. Green water refers to the evapotranspiration of water from precipitation and blue water refers to the evapotranspiration from irrigation or shallow groundwater via capillary rise. The first comprehensive crop WF dataset was produced more than a decade ago and covered around 150 individual crops averaged for the year 2000. This dataset provided a basis for numerous studies on a wide range of topics, including agricultural water management, environmental economics, water footprint and life cycle assessments. Later, it was projected over the 1961–2016 period using a fast-track approach, which succeeded in providing historical coverage but also propagated the limitations and uncertainties from the original dataset.<br/>This thesis aims to produce and analyse a new WF dataset covering 175 individual crops over the 1990–2019 period. These new estimates are based on fresh simulations using state-of-the-art input data, methods, and a global gridded crop model. The latter is developed from FAO’s process-based crop model AquaCrop with additional implemented features, such as the ability to run at the 10 x 10 km scale, trace green and blue water fluxes in the soil, and simulate perennial crops. The accompanying analysis of spatial and temporal patterns provides new insights into the crop WF evolution over the last decades. For example, it demonstrates that most of the crops experienced large water-productivity gains as crop yields improved and cultivation centred around more productive areas. Also, it shows that these gains were insufficient to stop the global water consumption for crop production from increasing, mainly across the tropics. This raises multiple concerns regarding already existing (and expected in the future) environmental and socio-economic water-related issues. Therefore, more efforts should be dedicated towards more water-sustainable agrifood systems.

Introduction: Water scarcity has become a global issue due to its direct relationship with food security. For this reason, the need for the long-term sustainable use of water necessitates the application of effective strategies. In this regard, strategic programs are utilized in water resource management and agricultural policies in order to increase self-sufficiency, to reduce the food gap, to decrease the cultivation of water based products, to maximize the economic value of water and to guarantee efficient allocation of resources among different activities in most parts of the world. The main objective of this study is to develop a decision support system to achieve the above-mentioned policies and strategies in the ten agricultural and ecological zones in the country according to the amount of virtual water for crop production. Data and Methods: The decision support system seeks to introduce an optimum pattern and to investigate the current status of water resources and determine the food gap and virtual economic value by means of a linear programming model. It intends also to determine the return on investment of crop production in each region. Our goal of this research is to maximize the value of virtual water with respect to land and availability of surface water and groundwater constraints. We also consider socio-economic constraints to ensure minimum and maximum area under cultivation in every region. In order to achieve accurate results, the social value of goods and inputs has been used in the model. In determining the social value of all goods and tradable inputs, prices of the border with a shadow exchange rate are used. Given the importance of addressing the amount of water used to produce goods, the virtual water content of products on maximizing the economic value of water is used in this study. Due to climatic conditions and consequently the performance of production in different regions, we use water requirement to crop yield ratio for every region for calculation of the virtual water content of a product. In this study, water valuation was based on value added inputs, while social values were used as criteria in its calculation. The data are gathered from the database of the Ministry of Agriculture, Ministry of Energy and the relevant agencies in the region. We used the 32.5 Edition of GAMS software to estimate the proposed model. Results: The results show the amount of water used by farmers to grow major crops in different regions in 1392, was 19 billion cubic meters. Central Zagros with 3.8 billion cubic meters and the Central dry zone with 1.2 billion cubic meters have respectively the largest and smallest water consumption. The results also showed the greatest change and lowest change in economic value of irrigation water related to wet wheat and wet cotton respectively. The regional view, the greatest and the lowest value of water refers respectively to the South Zagros region and the region of Khuzestan. Research results show that the pattern of demand reduces the food gap through increased cultivation of some strategic products. In order to reduce the food gap, one of the most important strategies is the increased cultivation of the wheat crop. Conclusion: This study provided a cultivating pattern in order to meet two important goals: cutting water consumption and reducing the food gap by increasing the cultivation of strategic crops such as wheat. In fact, by implementing appropriate Logistic policies, the government and politicians can achieve the aforementioned objectives by diversifying the current cultivation pattern in the desired region in compliance with environmental, economic and food security and health security considerations. The economic value of irrigation water and reduction of the area under cultivation is also a consequence of the proposed program. Instead of providing constant value in all regions of a country, providing an optimal cultivation pattern while considering the exact value of virtual water is a better policy. The proposed cropping pattern reduces Food gap and the area of water-based production cultivation and reduces water consumption, which can be used for producing strategic crops. The proposed cropping pattern increases the economic value of water by 20%. Indeed, it suggests that acreage crops such as wheat, pulses, and oil seeds are increased and rice and sugar beet cultivation is decreased. The main objective of the proposed cropping patterns to reduce the food gap and increase the welfare of consumers.

This comprehensive review delves into the intricate change of climate, assessing its profound impact on global food security and crop productivity. The examination addresses key questions, exploring the consequences of climate change on agriculture, with a specific focus on the challenges encountered in vulnerable regions such as sub-Saharan Africa and South Asia. Emphasizing the urgency of adaptive strategies for sustainable global agriculture, the review navigates through the complexities of mitigating climate-induced disruptions in crop growth patterns. Furthermore, it scrutinizes the implications of climate change on biodiversity, acknowledging the interconnectedness of ecological systems. Highlighting the imperative for innovation, the review underscores the pressing need for transformative farming methods to effectively tackle the multifaceted challenges posed by climate change. The emphasis is on ensuring the resilience of global agriculture in the face of climatic shifts. In conclusion, the review provides a compelling call to action, advocating for the prompt implementation of innovative farming practices to fortify the global agricultural sector against the evolving challenges brought about by climate change, fostering sustainability and adaptability.

Most of the world's food is produced in a handful of countries, the so-called breadbaskets of the world. Due to climate change, there is an increasing risk of crop failures, due to compounding hot and dry extremes. Furthermore, certain climate drivers – through teleconnections – have shown to lead to simultaneous crop failures around the globe. This highlights the importance to understand which climate processes drive global crop yield variability. Here we show global crop yield failures (Maize, Soya, Wheat, Rice, and combined) are associated with La Nina-like sea surface temperature (SST) anomalies, using Archetype Analysis. The adverse crop-yield archetypes show simultaneous hot-dry-surface imprints across the world, highlighting these high risk crop failure scenarios are driven by climate extremes. Our results demonstrate the importance in understanding the climate drivers of global crop production, and highlights the deep uncertainty associated with a changing climate. The response of ENSO due to anthropogenic activities is not yet fully understood and climate models often inaccurately reproduce the observed La Nina trends. Thus the fact that our results indicate that simultaneous crop failures are linked to La Nina like SSTs, highlights the deep uncertainty we currently face regarding food security in the future.

Climate change, famine, and low-income communities challenge Sustainable Development Goals

Chapter 4 - Spatial analysis, geospatial data and land-change models for modelling agricultural land changes

An integrated research approach to ensure sustainable rice yield increase of a crop grown by 25% of the world's farmers in 10% of cropland is essential for global food security. Rice, being a global staple crop, feeds about 56% of the world population and sustains 40% of the world's poor. At ~ $200 billion, it also accounts for 13% of the annual crop value. With hunger and malnutrition rampant among the poor, rice research for development is unique in global food and nutrition security. A systems-based, sustainable increase in rice quantity and quality is imperative for environmental and biodiversity benefits. Upstream 'discovery' through biotechnology, midstream 'development' through breeding and agronomy, downstream 'dissemination and deployment' must be 'demand-driven' for 'distinct socio-economic transformational impacts'. Local agro-ecology and livelihood nexus must drive the research agenda for targeted benefits. This necessitates sustained long-term investments by government, non-government and private sectors to secure the future food, nutrition, environment, prosperity and equity status.

Through a brief review of the literature in which the concept of food security has developed since the first use of the term in 1974, this paper suggests that the ‘food security’ appearing extensively in governmental, official and academic analysis is a social construct that acts to conceal the reality of corporate food production mechanisms dominating global food systems. Since the date of the first World Food Summit in Rome in 1996, representations of both food security and insecurity have increasingly become a meme, a vehicle for conveying and performing a set of socio‐cultural beliefs relating to a neoliberal view of global food production that excludes the biopolitics of corporate, systemic global food production. The analysis focuses particularly on a range of forms of waste produced by global food systems, to suggest that in a world over‐producing food of which over a third is wasted and in which waste has become a mechanism for profit, no presentation of food security that fails to take into account this systemic reality can produce valid or effective policy. The food security meme that has evolved over nearly 40 years portrays at best a partial analysis, which as a consequence continues to proffer a range of market‐based solutions, ignoring issues of dominance and control. In considering the memetic representation of food security, the paper also examines briefly the biopolitics presented by corporate systems of dominance and control in global food production, as well as the systems of waste (vastogenic systems) that they produce. In conclusion, the development of what are effectively empires of waste has fuelled an urgent need for a radical re‐think of food security issues, based on proposals for food regime and food systems analysis that have begun to emerge in the literature.

The global food and water security scenario in the twenty-first century will be an extraordinarily complex one. The population of the world will continue to balloon and reach 9.7 billion by 2050 and nearly 11-12 billion by 2100 [1]. In addition, global daily average calorie consumption is expected to rise from 2789 kcal/person/day in the year 2000 to 3130 kcal/person/day by the year 2050 [2]. These consumption figures may rise even higher if traditionally low meat consuming nations start increasing meat consumption enabled by economic growth. Food habits of people are diversifying considerably (e.g., rice, wheat, or maize only to a mix of rice, wheat, maize, pulses, fruits, and vegetables). At the same time, about 30 to 50% of the food produced globally is wasted [3]. Added to all these already daunting needs are the food security challenges from the COVID-19 pandemic, the Russia-Ukraine conflict, and related supply-chain disruptions. COVID-19 lockdowns and wars are heavily impacting food production and trade mechanisms for all leading cropland countries. Additionally, global food and water security challenges are tightly intertwined. In a changing climate, the quantity and quality of surface and ground water are decreasing. Demands for agricultural and alternative uses (e.g., industrial, ecological) of water are simultaneously increasing. Adding to this complexity, urban migration and climate change related precipitation extremes necessitate new infrastructure to maintain water availability for new cropland. Thus, 30m (field scale where 1 pixel = 0.09 hectares) cropland products, including their intensity and irrigation status, are needed to monitor change and aid decision-making for issues of global food and water security. Thereby, ensuring food and water security for ~9.7 billion people by the year 2050 and ~11 billion people by the year 2100 sustainably will require a paradigm shift on how our land and water are used for food production, referred to as the evergreen revolution, where food security is sustained and assured in the years ahead without significant disruption [4]. Recent research [5] has indicated that the global agricultural land and water in the 21st century will be in a constant state of flux [6] requiring us to understand, model, map, and monitor these changes over space and time rapidly, routinely, and accurately year after year. This challenge invariably calls for very comprehensive global food security-support analysis data (GFSAD) products at fine spatial resolution representing field-scale (30m or better) routinely and accurately covering the entire Earth.

Food and water security: Analysis of integrated modeling platforms