Nature‐based solutions to sea level rise and other climate change impacts on oceanic and coastal environments: a law and policy perspective.

  • Published In: Nordic Journal of Botany, 2023, v. 2023, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Doelle, Meinhard; Puthucherril, Tony George 3 of 3

Abstract

There are several nature‐based adaptation options available to coastal nations. In this paper, we offer a brief overview of these options and then focus on mangroves to consider how laws and policies can support nature‐based solutions and thereby contribute to more effective overall adaptation efforts. We first outline the concept of adaptation and its variants, thereby setting the context for this study. We then briefly explore the science relating to nature‐based adaptation. We analyze the international legal regime in place to protect mangrove ecosystems. Finally, we discuss the merits, the challenges, and strategies developed to surmount some of the challenges that coastal countries can face while implementing nature‐based adaptation options by utilizing Bangladesh's experience on mangrove conservation as a case study. Ultimately, we conclude that it may be necessary to implement both hard and nature‐based adaptation options and that an effective law and policy framework will be critical. It will also be important to look beyond physical coastal protection to augment coastal livelihoods and build resilient coastal communities with greater adaptive capacities. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Nordic Journal of Botany. 2023/01, Vol. 2023, Issue 1, p1
  • Document Type:Article
  • Subject Area:Earth and Atmospheric Sciences
  • Publication Date:2023
  • ISSN:0107-055X
  • DOI:10.1111/njb.03051
  • Accession Number:161524843
  • Copyright Statement:Copyright of Nordic Journal of Botany is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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