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While one has yet to be built in China, a rice supply flow network would provide essential information for stabilizing and optimizing food distribution and ensuring food security. Moreover, it is unclear how socioeconomic and natural environmental factors affect the rice supply flow. In this study, 35,768 random samples from the rice sales market were collected to build the rice flow network of China. The rice supply patterns at a regional and provincial level were revealed by the rice flow network. At the regional level, Northeast, Central, and East China are the main rice source areas, supplying almost all of China. At the provincial level, economically developed megacities, such as Beijing and Shanghai, and provinces with low temperatures like Tibet and Qinghai, rely heavily on imported rice. Determinant analysis shows that the rice supply patterns are mainly attributable to the cultivated area, primary industry employees, the permanent population, and tertiary industry proportion. These factors explain 75%, 59%, 48%, and 31%, respectively, of the rice supply spatial patterns. Furthermore, the interactions of cultivated area and temperature, cultivated area and primary industry proportion, and cultivated area and precipitation can explain 94%, 91%, and 89%, respectively, of the rice supply patterns. These findings reveal China's rice supply patterns and their determinants in recent years, providing essential information for optimizing the layout of rice production and ensuring food security in the future scenarios of climate change and socioeconomic development. [Display omitted] [ABSTRACT FROM AUTHOR]

Understanding the spatiotemporal trends of temperature in the context of global warming is significant for public health. Although many studies have examined changes in temperature and the impacts on human health over the past few decades in many regions, they have often been carried out in data-rich regions and have rarely considered acclimatization explicitly. The most frequent temperature (MFT) indicator provides us with the ability to solve this problem. MFT is defined as the longest period of temperature throughout the year to which a human is exposed and therefore acclimates. In this study, we propose a new method to estimate the number of heat exposure days from the perspective of temperature distribution and MFT, based on the daily mean temperature readings of 2142 weather stations in eight major climate zones in China over the past 20 years. This method can be used to calculate the number of heat exposure days in terms of heat-related mortality risk without the need for mortality data. We estimated the distribution and changes of annual mean temperature (AMT), minimum mortality temperature (MMT), and the number of heat exposure days in different climate zones in China. The AMT, MMT, and number of heat exposure days vary considerably across China. They all tend to decrease gradually from low to high latitudes. Heat exposure days are closely related to the risk of heat-related mortality. In addition, we utilized multiple linear regression (MLR) to analyze the association between the risk of heat-related mortality and the city and its climatic characteristics. Results showed that the number of heat exposure days, GDP per capita, urban population ratio, proportion of elderly population, and climate zone were found to modify the estimate on heat effect, with an R2 of 0.71. These findings will be helpful for the creation of public policies protecting against high-temperature-induced mortalities. [ABSTRACT FROM AUTHOR]