Suppr超能文献

将自然还给城市海洋的新兴解决方案。

Emerging Solutions to Return Nature to the Urban Ocean.

机构信息

Department of Biology, Chioggia Hydrobiological Station Umberto D'Ancona, University of Padova, 30015 Chioggia, Italy; email:

Department of Biological, Geological, and Environmental Sciences and Interdepartmental Research Center for Environmental Sciences, University of Bologna, UO CoNISMa, 48123 Ravenna, Italy.

出版信息

Ann Rev Mar Sci. 2021 Jan;13:445-477. doi: 10.1146/annurev-marine-032020-020015. Epub 2020 Aug 31.

Abstract

Urban and periurban ocean developments impact 1.5% of the global exclusive economic zones, and the demand for ocean space and resources is increasing. As we strive for a more sustainable future, it is imperative that we better design, manage, and conserve urban ocean spaces for both humans and nature. We identify three key objectives for more sustainable urban oceans: reduction of urban pressures, protection and restoration of ocean ecosystems, and support of critical ecosystem services. We describe an array of emerging evidence-based approaches, including greening grayinfrastructure, restoring habitats, and developing biotechnologies. We then explore new economic instruments and incentives for supporting these new approaches and evaluate their feasibility in delivering these objectives. Several of these tools have the potential to help bring nature back to the urban ocean while also addressing some of the critical needs of urban societies, such as climate adaptation, seafood production, clean water, and recreation, providing both human and environmental benefits in some of our most impacted ocean spaces.

摘要

城市和近岸海洋发展影响了全球专属经济区的 1.5%,对海洋空间和资源的需求正在增加。随着我们努力追求更可持续的未来,当务之急是更好地设计、管理和保护城市海洋空间,造福人类和自然。我们确定了更可持续的城市海洋的三个关键目标:减少城市压力、保护和恢复海洋生态系统以及支持关键生态系统服务。我们描述了一系列新兴的循证方法,包括绿化灰色基础设施、恢复栖息地和开发生物技术。然后,我们探讨了支持这些新方法的新经济手段和激励措施,并评估了它们在实现这些目标方面的可行性。其中一些工具有可能帮助将自然带回城市海洋,同时满足城市社会的一些关键需求,如气候适应、海鲜生产、清洁水和娱乐,在我们受影响最严重的一些海洋空间提供人类和环境的双重效益。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验