Exploring global food security pattern from the perspective of spatio-temporal evolution

Abstract

Food security is the primary prerequisite for achieving other Millennium Development Goals (MDGs). Given that the MDG of "halving the proportion of hungers by 2015" was not realized as scheduled, it will be more pressing and challenging to reach the goal of zero hunger by 2030. So there is high urgency to find the pattern and mechanism of global food security from the perspective of spatio-temporal evolution. In this paper, based on the analysis of database by using a multi-index evaluation method and radar map area model, the global food security level for 172 countries from 2000 to 2014 were assessed; and then spatial autocorrelation analysis was conducted to depict the spatial patterns and changing characteristics of global food security; then, multi-nonlinear regression methods were employed to identify the factors affecting the food security patterns. The results show: 1) The global food security pattern can be summarized as "high-high aggregation, low-low aggregation". The most secure countries are mainly distributed in Western Europe, North America, Oceania and parts of East Asia. The least secure countries are mainly distributed in sub-Saharan Africa, South Asia and West Asia, and parts of Southeast Asia. 2) Europe and sub-Saharan Africa are hot and cold spots of the global food security pattern respectively, while in non-aggregation areas, Haiti, North Korea, Tajikistan and Afghanistan have long-historical food insecurity problems. 3) The pattern of global food security is generally stable, but the internal fluctuations in the extremely insecure groups were significant. The countries with the highest food insecurity are also the countries with the most fluctuated levels of food security. 4) The annual average temperature, per capita GDP, proportion of people accessible to clean water, political stability and non-violence levels are the main factors influencing the global food security pattern. Research shows that the status of global food security has improved since the year 2000, yet there are still many challenges such as unstable global food security and acute regional food security issues. It will be difficult to understand these differences from a single factor, especially the annual average temperature and annual precipitation. The abnormal performance of the above factors indicates that appropriate natural conditions alone do not absolutely guarantee food security,while the levels of agricultural development, the purchasing power of residents, regional accessibility, as well as political and economic stability have more direct influence.

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

“…In fact, the COVID-19 pandemic has further exacerbated world hunger (Laborde et al 2020 ; Zurayk 2020 ). Thus, food security will remain a global priority for decades to come (Conceição et al 2016 ; Sisha 2020 ) and a prerequisite for other Millennium Development Goals (Cai et al 2020 ).…”

COVID-19, Agriculture, and Food Security in Indonesia

“…Although food security is in a race against population growth, Grote (2014) and Goyal (2012) showed that population pressure, poverty, land degradation, and unstable environments had pushed food security further out of reach. This has been compounded by climate change and natural disasters (Cai et al, 2020). Douglas (2009) stated that agricultural development, people's purchase ability, regional accessibility, and social, psychological, behavioral, political, and economic stability are factors affecting food security.…”

An integrated assessment model for food security under climate change for South Asia

“…Further, it is found that decrease in cereal production not only increases the prices of cereal goods but also effect the consumption of individual households which is expected to decrease in all four countries (see Figure 7 ). This can be seen as that these South Asian countries can face more problems of food security, as they are already lagging in average yields and facing already a largely undernourished population ( Bandara and Cai, 2014 ; Cai et al., 2020 ). Further the loss of welfare is identified due to the climate change which is 49.224 billion US $ in India, 32.161 billion in Pakistan, 28.198 billion in Bangladesh, and 5.661 billion in Sri-Lanka (see Figure 8 ).…”

“…In IAM, climate was first integrated into the macro-economic model by representation of carbon dioxide concentrations in the classical model of the long-run growth ( Nordhaus 1975 , 1977 , 1992 ). This model consists of combined data on the growth of crops, usage of soil and some other economic models ( Mendelsohn et al., 2016 ; Prinn et al., 1999 ; Fujino et al., 2006 ; Cai et al., 2020 ; Müller et al., 2020 ; Meijl et al., 2020 ). The IAM developed a single entity by using the cause and effect of change in climate and by collecting the knowledge from different disciplines into a single entity and ultimately developing a network of information for developing policies ( Dinar and Mendelsohn, 2011 ; Vanschoenwinkel et al., 2020 ).…”