Multiple environmental stressors lead to biodiversity loss.

Although cities are human-dominated systems, they provide habitat for many other species. Because of the lack of long-term observation data, it is challenging to assess the impacts of rapid urbanization on biodiversity in Global South countries. Using multisource data, we provided the first analysis of the impacts of urbanization on bird distribution at the continental scale and found that the distributional hot spots of threatened birds overlapped greatly with urbanized areas, with only 3.90% of the threatened birds’ preferred land cover type in urban built-up areas. Bird ranges are being reshaped differently because of their different adaptations to urbanization. While green infrastructure can improve local bird diversity, the homogeneous urban environment also leads to species compositions being more similar across regions. More attention should be paid to narrow-range species for the formulation of biodiversity conservation strategies, and conservation actions should be further coordinated among cities from a global perspective.

Economic growth is an integral part of the Sustainable Development Goals (SDGs), especially SDG 8. We combine 10 economic constraints and build a five-variable (structural vector autoregressive) SVAR model based on China’s time series data of 1978–2017. The empirical results show: (1) The Chinese government adopted different economic policies at different stages of reform and opening up; (2) From the impulse response results, China’s excessively high government debt ratio has begun to inhibit economic growth; (3) In terms of policy selection and coordination, the Chinese government mostly adopts a “discretion” adjustment strategy. In most cases, the fiscal and monetary policies were in the same direction, and the “double expansionary” and “double contractionary” policy coordination may become mainstream; (4) The results of variance decomposition showed that both fiscal and monetary policies can effectively regulate economic growth at the present stage, and the contribution rates of exogenous shocks to the prediction variance of economic growth rate were about 25%.

Shenzhen is a national sustainable development innovation demonstration zone, with the theme of innovation leading the sustainable development of megacities. This manuscript studies technological innovation, production efficiency, and sustainable development and explores the impact of their relationship on Shenzhen. The benchmark test shows a significant negative correlation between the inefficiency of production, labor levels, investment levels, technical levels, and socioeconomic status. From 2001 to 2019, the production efficiencies of 21 prefecture-level cities in Guangdong Province were used as the research object. The Cobb–Douglas production function conducted panel stochastic frontier analysis and TOBIT regression, and the conclusion was robust. The mechanism test found that the economic growth of Guangdong Province, including Shenzhen, is still dominated by labor and investment. Its production efficiency has been dramatically impacted after 2008, and the increase in production inefficiency may be affected by the crowding-out effect of a four-trillion investment. Finally, based on the Tobit regression, we found that the rise in the labor force, capital input, technological level, and socioeconomic development level could reduce Shenzhen’s production inefficiencies by 3.6%, 20.2%, 2.5%, and 4%, respectively. There is still a long way to achieve sustainable development; however, Shenzhen’s technological innovation and mega-city reform process will provide valuable insights for other regions.