Multiscale analysis of factors affecting food security in China, 1980-2017

Research on the spatio-temporal coupling relationship between agricultural green development efficiency and food security system in China

Food security and agricultural green development are fundamental issues concerning the survival of mankind. To realize the coordinated development of them is of great significance to promote the green transformation of agriculture and ensure national food security. However, few studies have analyzed the coupling relationship between agricultural green development and food security. Therefore, this study complements the research on the coupling relationship between them. First, we use the agricultural panel data of 31 provinces in China from 2010 to 2021 to measure the agricultural green development efficiency and food security level by Super-SBM model and entropy weight method. Then, the coupling relationship and spatiotemporal evolution of the two are analyzed by coupling coordination degree model. The results show that, first of all, China's agricultural green development efficiency and food security level have improved overall, but there are regional differences. Secondly, the degree of coupling and coordination between the two is significantly improved, and most provinces develop from the break-in stage to the coordination stage, and the regional differences are relatively reduced. Finally, Beijing, Shanghai and other developed areas are mostly of the lagging food security type, Liaoning, Shandong and other major grain producing areas have reached a high degree of coordination, while Tibet, Qinghai and other western regions are still in the break-in stage. According to the development situation of different regions, corresponding suggestions are put forward. For regions with lagging food security type, the government should give full play to the application of science and technology in agriculture and promote green and low-carbon planting technologies. For regions with low coupling and coordination degree, the government should improve support policies and build a collaborative operation system, adjust planting structure to improve land utilization rate and food security level. Finally, the government should work together to build agricultural industrial parks and give full play to the leading role of competitive provinces to achieve common development.

Impact of aerosol concentration changes on carbon sequestration potential of rice in a temperate monsoon climate zone during the COVID-19: a case study on the Sanjiang Plain, China

The emission reduction of atmospheric pollutants during the COVID-19 caused the change in aerosol concentration. However, there is a lack of research on the impact of changes in aerosol concentration on carbon sequestration potential. To reveal the impact mechanism of aerosols on rice carbon sequestration, the spatial differentiation characteristics of aerosol optical depth (AOD), gross primary productivity (GPP), net primary productivity (NPP), leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FPAR), and meteorological factors were compared in the Sanjiang Plain. Pearson correlation analysis and geographic detector were used to analyze the main driving factors affecting the spatial heterogeneity of GPP and NPP. The study showed that the spatial distribution pattern of AOD in the rice-growing area during the epidemic was gradually decreasing from northeast to southwest with an overall decrease of 29.76%. Under the synergistic effect of multiple driving factors, both GPP and NPP increased by more than 5.0%, and the carbon sequestration capacity was improved. LAI and FPAR were the main driving factors for the spatial differentiation of rice GPP and NPP during the epidemic, followed by potential evapotranspiration and AOD. All interaction detection results showed a double-factor enhancement, which indicated that the effects of atmospheric environmental changes on rice primary productivity were the synergistic effect result of multiple factors, and AOD was the key factor that indirectly affected rice primary productivity. The synergistic effects between aerosol-radiation-meteorological factor-rice primary productivity in a typical temperate monsoon climate zone suitable for rice growth were studied, and the effects of changes in aerosol concentration on carbon sequestration potential were analyzed. The study can provide important references for the assessment of carbon sequestration potential in this climate zone.

The spatial effects of the household's food insecurity levels in Ethiopia: by ordinal geo-additive model

Background

Food insecurity and vulnerability in Ethiopia are historical problems due to natural- and human-made disasters, which affect a wide range of areas at a higher magnitude with adverse effects on the overall health of households. In Ethiopia, the problem is wider with higher magnitude. Moreover, this geographical distribution of this challenge remains unexplored regarding the effects of cultures and shocks, despite previous case studies suggesting the effects of shocks and other factors. Hence, this study aims to assess the geographic distribution of corrected-food insecurity levels (FCSL) across zones and explore the comprehensive effects of diverse factors on each level of a household's food insecurity.

Method

This study analyzes three-term household-based panel data for years 2012, 2014, and 2016 with a total sample size of 11505 covering the all regional states of the country. An extended additive model, with empirical Bayes estimation by modeling both structured spatial effects using Markov random field or tensor product and unstructured effects using Gaussian, was adopted to assess the spatial distribution of FCSL across zones and to further explore the comprehensive effect of geographic, environmental, and socioeconomic factors on the locally adjusted measure.

Result

Despite a chronological decline, a substantial portion of Ethiopian households remains food insecure (25%) and vulnerable (27.08%). The Markov random field (MRF) model is the best fit based on GVC, revealing that 90.04% of the total variation is explained by the spatial effects. Most of the northern and south-western areas and south-east and north-west areas are hot spot zones of food insecurity and vulnerability in the country. Moreover, factors such as education, urbanization, having a job, fertilizer usage in cropping, sanitation, and farming livestock and crops have a significant influence on reducing a household's probability of being at higher food insecurity levels (insecurity and vulnerability), whereas shocks occurrence and small land size ownership have worsened it.

Conclusion

Chronically food insecure zones showed a strong cluster in the northern and south-western areas of the country, even though higher levels of household food insecurity in Ethiopia have shown a declining trend over the years. Therefore, in these areas, interventions addressing spatial structure factors, particularly urbanization, education, early marriage control, and job creation, along with controlling conflict and drought effect by food aid and selected coping strategies, and performing integrated farming by conserving land and the environment of zones can help to reduce a household's probability of being at higher food insecurity levels.

Resilience of agricultural development in China's major grain-producing areas under the double security goals of "grain ecology"

The development of agriculture faces uncertainties due to global climate variability and the scarcity of agricultural resources. Enhancing agricultural development resilience is essential for improving agriculture's adaptability to the external environment and ensuring food security. It is imperative to prevent and control agricultural pollution as it worsens. Thus, enhancing the resilience of agricultural development requires balancing food security and ecological security. The present study constructs an evaluation system for agricultural development resilience in China with three levels: resistance, resilience, and reengineering ability. The agricultural development resilience of China's main grain-producing areas is evaluated using the entropy method, and regional differences are analyzed using kernel density estimation and the Theil index. The obstacle model was used to identify and analyze the obstacles that affect agricultural development's resilience to propose countermeasures. The results showed that (1) agricultural development resilience in China's main grain-producing areas has steadily increased from 0.317 to 0.427. The resilience of agrarian development in Heilongjiang, Shandong, and Henan provinces ranges from 0.473 to 0.575, which is far higher than the mean development level; (2) Regional differences in the main grain-producing areas are narrowing from 0.077 to 0.023; (3) The main grain-producing areas share common obstacle factors, emphasizing the critical role of technological innovation, investment, and machine-cultivated land resources in enhancing agricultural resilience against external risks. Paying attention to the amount of fertilizer usage is crucial to achieving ecological security goals.

Assessing food security performance from the One Health concept: an evaluation tool based on the Global One Health Index

BACKGROUND

Food systems instantiate the complex interdependencies across humans, physical environments, and other organisms. Applying One Health approaches for agri-food system transformation, which adopts integrated and unifying approaches to optimize the overall health of humans, animals, plants, and environments, is crucial to enhance the sustainability of food systems. This study develops a potential assessment tool, named the global One Health index-Food Security (GOHI-FS), aiming to evaluate food security performance across countries/territories from One Health perspective and identify relevant gaps that need to be improved for sustainable food systems.

METHODS

We comprehensively reviewed existing frameworks and elements of food security. The indicator framework of GOHI-FS was conceptualized following the structure-process-outcome model and confirmed by expert advisory. Publicly available data in 2020 was collected for each indicator. The weighting strategy was determined by the Fuzzy Analytical Hierarchy Process. The data for each indicator was normalized and aggregated by weighted arithmetic mean. Linear regressions were performed to evaluate the associations of GOHI-FS with health and social-economic indicators.

RESULTS

The GOHI-FS includes 5 first-level indicators, 19 second-level indicators and 45 third-level indicators. There were 146 countries/territories enrolled for evaluation. The highest average score of first-level indicators was Nutrition (69.8) and the lowest was Government Support and Response (31.3). There was regional heterogeneity of GOHI-FS scores. Higher median scores with interquartile range (IQR) were shown in North America (median: 76.1, IQR: 75.5-76.7), followed by Europe and Central Asia (median: 66.9, IQR: 60.1-74.3), East Asia and the Pacific (median: 60.6, IQR: 55.5-68.7), Latin America and the Caribbean (median: 60.2, IQR: 57.8-65.0), Middle East and North Africa (median: 56.6, IQR: 52.0-62.8), South Asia (median: 51.1, IQR: 46.7-53.8), and sub-Saharan Africa (median: 41.4, IQR: 37.2-46.5). We also found significant associations between GOHI-FS and GDP per capita, socio-demographic index, health expenditure and life expectancy.

CONCLUSIONS

GOHI-FS is a potential assessment tool to understand the gaps in food security across countries/territories under the One Health concept. The pilot findings suggest notable gaps for sub-Saharan Africa in numerous aspects. Broad actions are needed globally to promote government support and response for food security.

The impacts of climatic conditions on cereal production: implications for food security in Africa

Climate change is a confounding factor that affects food security in several ways. Although the analyses of earlier studies in this area were largely non-technical, new analytical techniques have been developed to comprehensively evaluate climate change patterns and their implications for food security. In this study, we use recent developments in panel econometrics, which consider cross-sectional dependence and parameter heterogeneity, to examine the effects of climatic conditions on cereal farming in Africa from 1970Q1 to 2017Q4. The results show that rainfall positively affects cereal crops, although average temperatures are typically unfavourable. In the country-specific scenarios, we observed significant variations in the influence of climatic conditions on cereal production. The causality test results show a two-way causal relationship between climatic conditions-rainfall and temperature-and cereal production. It is suggested that African governments and non-governmental organisations support farmers' adaptation to climate change by implementing policies that prioritise farmers' capacity building and ensure that extension service officers engage with farmers intensively.

Characteristics, regional differences, and influencing factors of China's water-energy-food (W-E-F) pressure: evidence from Dagum Gini coefficient decomposition and PGTWR model

Water, energy, and food security are global concerning issues especially in China. To promote regional environmental management cooperation as well as find resource security influencing factor differences among regions, this paper calculates the water-energy-food (W-E-F) pressure, find W-E-F pressure's regional differences, and the influencing factors by Dagum Gini coefficient decomposition and geographically and temporally weighted regression model for panel data (PGTWR). First, the temporal trend of W-E-F pressure is decreasing and then increasing during 2003-2019; pressure in the eastern provinces is significantly higher than in other provinces and structurally energy pressure is the dominant resource pressure in W-E-F in most provinces. Besides, inter-regional differences are the main source of regional differences in China's W-E-F pressure, particularly for the inter-regional differences between eastern regions and other regions. In addition, there are obvious spatio-temporal heterogeneity effects of population density, per capita GDP, urbanization, energy intensity, effective irrigated area, and forest cover on W-E-F pressure. Balancing regional development gaps and developing differentiated resource pressure mitigation strategies based on the characteristics of different regional drivers are of great importance.

How do carbon emissions, economic growth, population growth, trade openness and employment influence food security? Recent evidence from the East Africa

East Africa has a substantially greater rate of food insecurity than other regions of the world. Scenarios of climate change and other macroeconomic variables are important contributors to food insecurity in East Africa. Using data spanning from 1990 to 2020, this study looked into the influence of carbon dioxide (CO₂) emissions, economic growth, population growth, trade openness, and agricultural employment on food security in the East Africa. The fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models were used in this study. The heterogeneous panel cointegration test's findings indicated that the study variables have an equilibrium long-term connections. The estimation findings from the FMOLS and DOLS models showed that an increase in CO₂ emissions increases food security in the East Africa over the long term. According to other findings, long-term food security is positively impacted by economic expansion, population growth, trade openness, and employment in agriculture. However, trade openness has a detrimental long-lasting effect on food security. Future research directions, research limitations, and policy implications are discussed.

Spatiotemporal heterogeneity between agricultural carbon emission efficiency and food security in Henan, China

It is significant to investigate the coupling and coordination between agricultural carbon emission efficiency (ACEE) and food security and to achieve peak carbon dioxide emissions and carbon neutrality in agriculture as early as possible while ensuring national food security. The Super-SBM (slack-based model) and the comprehensive index method were used to measure the ACEE and food security level in Henan province from 2010 to 2020. The coupling coordination degree (CCD) and the relative state of ACEE and food security were analyzed using the coupling coordination degree model (CCDM) and the relative development degree model (RDDM). In addition, the interaction between ACEE and food security and the spatial-temporal heterogeneity were analyzed by combining with the geographically and temporally weighted regression (GTWR) model. The results showed that: Firstly, the overall level of ACEE was high, and the spatial heterogeneity of ACEE was significant. The spatial pattern of food security is relatively stable, with high levels in the south and low levels in the north. Secondly, The CCD between ACEE and food security in Henan province generally shows a decreasing trend. In the spatial dimension, the CCD between ACEE and food security in Henan province exhibits a spatial divergence characteristic of low in the center and high in the north and south, with significant regional variations. Finally, there is spatial and temporal heterogeneity between ACEE and food security. The regression coefficients differ significantly among different cities, the regression coefficients do not show a consistent positive or negative correlation, and the regression coefficients are distributed both positively and negatively. This study serves as a guide for achieving the goal of double carbon in agriculture and ensuring food security.

Spatial Differences of Nutrient Adequacy in Coastal Areas of China

Ensuring nutrient adequacy for all is a common goal of the international community, but spatial difference is one of the barriers to its development. Exploring nutrient adequacy in coastal areas of China can help regions where food production systems and economic development systems are under mutual stress to reduce nutritional disparities and improve nutrition levels. This paper used the transformation food-to-nutrient model to calculate nutrient production and nutrient consumption in 11 coastal provinces of China and analyzed their spatial patterns, after which spatial differences in nutrient adequacy (including energy, protein and fat) were analyzed. The results showed that nutrient production and nutrient consumption in coastal areas of China showed significant spatial differences, in which nutrient production was mainly concentrated in land food, and the three provinces of Shandong, Jiangsu and Hebei contributed more. Guangdong had the highest nutrient consumption; in contrast, Shanghai, Tianjin, and Hainan had the lowest consumption. Nutrient adequacy was not optimistic, with fat being particularly significant, and nutrient surplus quantity was mainly concentrated in Shandong and Jiangsu and nutrient deficiency quantity was mainly concentrated in Guangdong. Overall, the study area had adequate levels of protein and was deficient in energy and fat levels, with surplus or shortage of 2.41 million tonnes, 2620 billion kcal and 9.97 million tonnes, respectively.

Food Security: 3D Dynamic Display and Early Warning Platform Construction and Security Strategy

Since it affects a nation's economy and people's wellbeing, food security is a crucial national security requirement. In order to realize multi-angle grain data presentation and analysis and achieve the goal of deep mining, we propose a 3D dynamic visualization analysis method of multidimensional agricultural spatial-temporal data based on the self-organizing map. This method realizes the multi-angle display and analysis of grain data and achieves the purpose of deep mining. With the outbreak of COVID-19, the global food security situation is not optimistic, so it is necessary to use the food security early warning system to solve the food security issue. Machine learning has emerged widely in recent years and has been applied in various fields. Therefore, it is an excellent way to solve food security to apply the model in machine learning to construct a food security early warning system. Afterward, a food security early warning platform is developed with a support vector regression (SVR) model to ensure food security. Finally, we analyze China's medium and long-term food security policy in line with modernization objectives. The experimental results show that the food security early warning platform based on the SVR model from 2007 to 2016 is effective compared with the actual situation every year. Through analyses, we should improve the stability, reliability, and sustainability of food supply, firmly hold the food security initiative, and construct a national food security guarantee system matching the goal of modernization.

Spatiotemporal Evolution of Cultivated Land Non-Agriculturalization and Its Drivers in Typical Areas of Southwest China from 2000 to 2020

Cultivated land resources are crucial to food security and economic development. Exploring the spatiotemporal pattern of cultivated land non-agriculturalization and its drivers is a prerequisite for cultivated land conservation. This paper used GlobeLand30 data to reveal the spatial and temporal pattern, the shift of the gravity center and the drivers of cultivated land non-agriculturalization by employing spatial analysis, gravity center model and the geographical detector model. The results show a dramatic increase in the non-agriculturalization of cultivated land in the period of 2010–2020 compared to 2000–2010. Spatially, the cultivated land non-agriculturalization mainly occurred in areas with high urbanization levels, such as eastern Sichuan Province and western Chongqing Municipality, while the cultivated land non-agriculturalization in other areas was small-scale and spatially scattered. Furthermore, the speed of cultivated land non-agriculturalization showed spatial unevenness, and the gravity center of cultivated land non-agriculturalization shifted towards the northeast at a distance of 123.21 km. The cultivated land non-agriculturalization was affected by GDP per capita, population density, GDP per unit of land and total retail sales of social consumer goods. The key drivers for the cultivated land non-agriculturalization in the study area were the continuous expansion of urban space and the large-scale cultivation of economic fruit trees. The government should promote small-scale machinery suitable for agricultural cultivation in the mountainous and hilly areas of Southwest China, and appropriately develop economic fruit groves and livestock farming to reduce the phenomenon of cultivated land non-foodization.

New Insight into the Coupled Grain–Disaster–Economy System Based on a Multilayer Network: An Empirical Study in China

Natural disasters occur frequently causing huge economic losses and reduced grain production. Therefore, it is important to thoroughly explore the spatial correlations between grain, disaster, and the economy. Based on inter-provincial panel data in China in 2019, this study integrates complex network and co-occurrence theory into a coupled grain–disaster–economy (GDE) multilayer network, which provides a new perspective to further explore the spatial correlation between these three systems. We identify the spatial coupled characteristics of the GDE multilayer network using three aspects: degree, centrality, and community detection. The research results show the following: (1) Provinces in the major grain-producing regions have a stronger role in allocating and controlling grain resources, and the correlation between grain and disasters in these provinces is stronger and more prone to disasters. Whereas provinces in the Beijing–Tianjin–Hebei economic zone, and the Yangtze River Delta and Pearl River Delta economic zones, such as Beijing, Tianjin, Jiangsu, Shanghai, and Zhejiang, have a high level of economic development, thereby a stronger ability to allocate economic resources. (2) The economic subsystem assumes a more important, central role compared with the grain and disaster subsystems in the formation and development of the coupled GDE multilayer network, with a stronger coordination for the co-development between the complex grain, disaster, and economy systems in the nodal provinces of the network. (3) The community modularity of the coupled GDE multilayer network is significantly higher than that of the three single-layer networks, indicating a more reasonable community division after coupling the three subsystems. The identification of the spatial characteristics of GDE using multilayer network analysis offers a new perspective on taking various measures to improve the joint sustainable development of grain, disaster, and the economy in different regions of China according to local conditions.