The Socio-Economic and Environmental Variables Associated with Hotspots of Infrastructure Expansion in South America

How do intrinsic and extrinsic causes interact in the extinction vulnerability of South American savanna shrub and tree species?

Although a growing body of literature recognises the importance of rarity for biodiversity conservation, it is unclear how the interaction of different forms of rarity, extrinsic causes of extinction, and protection affect species' vulnerability. Here we addressed the extinction vulnerability of 2203 shrub and tree species of the South American savanna (SAS). For this, species were attributed a form of rarity, a synergistic risk index (SRI), and a protection index (PI). The SRI combines three extrinsic causes of extinction (climate hazard, fire frequency, and human footprint). The PI is the ratio between the number of a species occurrences within protected areas and the total number of occurrences in the SAS. By combining the SRI and PI, we classified common and rare species into five vulnerability classes. Some regions of the SAS show high values of climate hazard, fire frequency, human footprint, and SRI. Each extrinsic cause of extinction is differently distributed across the SAS and shows no or low spatial congruence with the SRI. Many species show a low ratio of occurrences within PAs, which in combination with high SRI results in high vulnerability to extinction. Surprisingly, the number of common species in the higher vulnerability classes is higher than of rare species. Common and rare species in different vulnerability classes occur in somewhat different locations across the SAS and mainly constitute spatially incongruent centres with high species richness. Given our results, we propose that strategies for the effective conservation of SAS species are challenging and must be carefully designed.

Coupling Coordination Relationship and Driving Mechanism between Urbanization and Ecosystem Service Value in Large Regions: A Case Study of Urban Agglomeration in Yellow River Basin, China

Mastering the coupling and coordination relationship and driving mechanism of urbanization and ecosystem service value (ESV) is of great significance to ecological protection and regional sustainable development. In this paper, the coupling coordination model, geographic detector and GWR model are used to analyze the spatio-temporal coupling interaction between urbanization and ESV and the spatial differentiation characteristics of influencing factors from 1995 to 2018. The results of the study are as follows: (1) During the study period, cities in the Yellow River Basin experienced accelerated urban expansion, and the ESV of forests, water and wetlands increased, which offset the reduction in ESV due to the expansion of construction land and farmland and grassland. (2) The degree of coupling and coordination between the two gradually improved, but the overall situation showed a low-level coupling and coordination process. Mild coupling coordination gradually increased, reaching an increase of 38.10%; severe imbalance types tended to disappear, decreasing by 52.38%, and coupling subtypes developed from lagging urbanization to ESV backward types. The high-value areas of the coupling coordination degree are distributed in the high-value areas of ESV in the north of the upper reaches, and the low-value areas are distributed in the cities of Henan and Shandong with high urbanization levels in the downstream and most resource-based cities in the middle reaches. (3) In addition, the spatial intensity of the effect of each dominant factor on the degree of coupling coordination is different. Economic growth, technological development, environmental regulations and the proportion of forest land have positive and belt-shaped alienation characteristics for the coupling and coordination of the two, and infrastructure and temperature show negative driving characteristics. Therefore, the coupling and coordination relationship between ESV and urbanization should be clarified to help future urban planning. On the basis of determining the regional environmental carrying capacity and the adjustment direction of the rational planning of land resources, the impact of urban barriers formed by administrative boundaries and natural geographical conditions on the development of urban agglomerations should be broken to achieve the overall high-quality and coordinated development of the basin.

CRISPR Genome Editing Technology: A Powerful Tool Applied to Developing Agribusiness

The natural increase of the world's population implies boosting agricultural demand. In the current non-optimistic global scenario, where adverse climate changes come associated with substantial population growth, the main challenge in agribusiness is food security. Recently, the CRISPR/Cas system has emerged as a friendly gene editing biotechnological tool, enabling a precise manipulation of genomes and enhancement of desirable traits in several organisms. This review highlights the CRISPR/Cas system as a paramount tool for the improvement of agribusiness products and brings up-to-date findings showing its potential applications in improving agricultural-related traits in major plant crops and farm animals, all representing economic-relevant commodities responsible for feeding the world. Several applied pieces of research have successfully demonstrated the CRISPR/Cas ability in boosting interesting traits in agribusiness products, including animal productivity and welfare, crop yield growth, and seed quality, reflecting positive impacts in both socioeconomics and human health aspects. Hence, the CRISPR/Cas system has revolutionized bioscience and biotechnology, and its concrete application in agribusiness goods is on the horizon.

Exploring the Dynamic Spatio-Temporal Correlations between PM2.5 Emissions from Different Sources and Urban Expansion in Beijing-Tianjin-Hebei Region

Due to rapid urbanization globally more people live in urban areas and, simultaneously, more people are exposed to the threat of environmental pollution. Taking PM2.5 emission data as the intermediate link to explore the correlation between corresponding sectors behind various PM2.5 emission sources and urban expansion in the process of urbanization, and formulating effective policies, have become major issues. In this paper, based on long temporal coverage and high-quality nighttime light data seen from the top of the atmosphere and recently compiled PM2.5 emissions data from different sources (transportation, residential and commercial, industry, energy production, deforestation and wildfire, and agriculture), we built an advanced Bayesian spatio-temporal autoregressive model and a local regression model to quantitatively analyze the correlation between PM2.5 emissions from different sources and urban expansion in the Beijing-Tianjin-Hebei region. Our results suggest that the overall urban expansion in the study area maintained gradual growth from 1995 to 2014, with the fastest growth rate during 2005 to 2010; the urban expansion maintained a significant positive correlation with PM2.5 emissions from transportation, energy production, and industry; different anti-haze policies should be designated according to respective local conditions in Beijing, Tianjin, and Hebei provinces; and during the period of rapid urban expansion (2005-2010), the spatial correlations between PM2.5 emissions from different sources and urban expansion also changed, with the biggest change coming from the PM2.5 emissions from the transport sector.