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Although Brazil has one of the world's largest systems of protected areas, we do not know to what extent its marine protected areas (MPAs) are functioning as repositories of threatened species. Here we synthesized governmental and scientific information on the country's 75 federal MPAs to assess whether their size, age, protection group, visitation and management effectiveness affect the number of threatened animal species present within their boundaries. The MPAs harbored 133 threatened species, which corresponds to 78.2% of the 170 threatened marine animal species listed for the country. On average, there were 10.1 threatened species per MPA (varying from 1 to 48), but 13 MPAs did not report any. As expected, the number of threatened species was greater in no-take, larger, and older MPAs with management plan. The MPA effectiveness index averaged 0.55 (0.43–0.74), indicating moderate effectiveness for the entire federal system. The level of management effectiveness in 2022 and the visitation accumulated between 2012 and 2021 did not significantly affect the number of threatened species. Our results demonstrate that Brazilian MPAs do serve as repositories for threatened animal species, but reveal serious bottlenecks in the management of official databases, dissemination of information to society, and biodiversity inventory and monitoring. We recommend (i) improvements in working conditions for MPA officials; (ii) advances in data management and publicization; (iii) partnerships of MPA managers with universities, research institutions, and non-governmental organizations; and (iv) the development of a broad, long-term biodiversity monitoring program. [ABSTRACT FROM AUTHOR]

Green innovation solves the dilemma of economic growth, energy conservation, and ecological protection to achieve innovation-driven sustainable development. On this premise, it is reasonable to assess the performance of technology innovation for promoting green development. In this context, this study examines green innovation efficiency (GIE) and its influencing mechanisms in rapidly emerging BRICST economies (i.e., Brazil, Russia, India, China, South Africa, and Turkey) during 2000–2021 by adopting the novel super ray slack-based measure model with undesirable output and the dynamic panel data model. As a novelty, we have evaluated GIE by constructing a comprehensive input–output index system based on innovation, energy, economic, and environmental factors. The empirical result reveals an increasing wave-shaped trend of GIE fluctuating around 0.606, failing to be DEA-efficient where inefficient countries need to improve by at least 39.40% to become efficient. There is an emerging gap with individual differences among countries, which is highest in Brazil and lowest in India. Moreover, green technology development and environmental regulation are highly conductive to improve GIE. However, foreign direct investment and government support have a mere positive effect, while trade openness has an inhibitory impact on GIE. These results suggest that individual governments should support technical cooperative relationships to formulate stringent but distinct green innovation policies based on domestic conditions, improve innovation-driven technological development and environmental regulation, encourage adoption and utilization of energy-efficient and clean technologies, enhance sustainable foreign investment and governmental research and development funds, synchronize trade baskets to improve trade diversification, and strengthen absorptive capacity of domestic enterprises. [ABSTRACT FROM AUTHOR]