Differences in the Suitable Distribution Area between Northern and Southern China Landscape Plants.

Climate change, a global biodiversity threat, largely influences the geographical distribution patterns of species. China is abundant in woody landscape plants. However, studies on the differences in the adaptive changes of plants under climate change between northern and southern China are unavailable. Therefore, herein, the MaxEnt model was used to predict changes in the suitable distribution area (SDA) and dominant environmental variables of 29 tree species under two climate change scenarios, the shared socioeconomic pathways (SSPs) 126 and 585, based on 29 woody plant species and 20 environmental variables in northern and southern China to assess the differences in the adaptive changes of plants between the two under climate change. Temperature factors dominated the SDA distribution of both northern and southern plants. Southern plants are often dominated by one climatic factor, whereas northern plants are influenced by a combination of climatic factors. Northern plants are under greater pressure from SDA change than southern plants, and their SDA shrinkage tendency is significantly higher. However, no significant difference was observed between northern and southern plants in SDA expansion, mean SDA elevation, and latitudinal change in the SDA mass center. Future climate change will drive northern and southern plants to migrate to higher latitudes rather than to higher elevations. Therefore, future climate change has varying effects on plant SDAs within China. The climate change intensity will drive northern landscape plants to experience greater SDA-change-related pressure than southern landscape plants. Therefore, northern landscape plants must be heavily monitored and protected.

Temporal and Spatial Heterogeneity of PM2.5 Related to Meteorological and Socioeconomic Factors across China during 2000-2018.

In recent years, air pollution caused by PM2.5 in China has become increasingly severe. This study applied a Bayesian space-time hierarchy model to reveal the spatiotemporal heterogeneity of the PM2.5 concentrations in China. In addition, the relationship between meteorological and socioeconomic factors and their interaction with PM2.5 during 2000-2018 was investigated based on the GeoDetector model. Results suggested that the concentration of PM2.5 across China first increased and then decreased between 2000 and 2018. Geographically, the North China Plain and the Yangtze River Delta were high PM2.5 pollution areas, while Northeast and Southwest China are regarded as low-risk areas for PM2.5 pollution. Meanwhile, in Northern and Southern China, the population density was the most important socioeconomic factor affecting PM2.5 with q values of 0.62 and 0.66, respectively; the main meteorological factors affecting PM2.5 were air temperature and vapor pressure, with q values of 0.64 and 0.68, respectively. These results are conducive to our in-depth understanding of the status of PM2.5 pollution in China and provide an important reference for the future direction of PM2.5 pollution control.

Spatiotemporal variations in the incidence of bacillary dysentery and long-term effects associated with meteorological and socioeconomic factors in China from 2013 to 2017.

Bacillary dysentery is a global public health problem that exhibits manifest spatiotemporal heterogeneity. However, long-term variations and regional determinant factors remain unclear. In this study, the Bayesian space-time hierarchy model was used to identify the long-term spatiotemporal heterogeneity of the incidence of bacillary dysentery and quantify the associations of meteorological factors with the incidence of bacillary dysentery in northern and southern China from 2013 to 2017. GeoDetector was used to quantify the determinant powers of socioeconomic factors in the two regions. The results showed that the incidence of bacillary dysentery peaked in summer (June to August), indicating temporal seasonality. Geographically, the hot spots (high-risk areas) were distributed in northwestern China (Xinjiang, Gansu, and Ningxia) and northern China (including Beijing, Tianjin, and Hebei), whereas the cold spots (low-risk areas) were concentrated in southeastern China (Jiangsu, Zhejiang, Fujian, and Guangdong). Moreover, significant regional differences were found among the meteorological and socioeconomic factors. Average temperature was the dominant meteorological factor in both northern and southern China. In northern and southern China, a 1 °C increase in the average temperature led to an increase of 1.01% and 4.26% in bacillary dysentery risk, respectively. The dominant socioeconomic factors in northern and southern China were per capita gross domestic product and the number of health technicians, with q statistic values of 0.81 and 0.49, respectively. These findings suggest that hot, moist, and overcrowded environments or poor health conditions increase the risk of bacillary dysentery. This study provides suggestions and serves as a basis for surveillance efforts. Further, the suggestions may aid in the control of bacillary dysentery and in the implementation of disease prevention policies.