Articles | Volume 18, issue 5
Ocean Sci., 18, 1477–1490, 2022
https://doi.org/10.5194/os-18-1477-2022
Ocean Sci., 18, 1477–1490, 2022
https://doi.org/10.5194/os-18-1477-2022
Research article
 | Highlight paper
20 Oct 2022
Research article  | Highlight paper | 20 Oct 2022

Detecting the most effective cleanup locations using network theory to reduce marine plastic debris: a case study in the Galapagos Marine Reserve

Stefanie L. Ypma et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2022-426', Noam Vogt-Vincent, 16 Jun 2022
  • RC1: 'Comment on egusphere-2022-426', Anonymous Referee #1, 01 Jul 2022
  • RC2: 'Comment on egusphere-2022-426', Anonymous Referee #2, 19 Jul 2022
  • RC3: 'Comment on egusphere-2022-426', Anonymous Referee #3, 04 Aug 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Stefanie Ypma on behalf of the Authors (30 Aug 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (31 Aug 2022) by Anne Marie Tréguier
RR by Anonymous Referee #2 (02 Sep 2022)
ED: Publish as is (04 Sep 2022) by Anne Marie Tréguier
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Executive editor
Marine plastics is a socially relevant topic that usually attracts public interest. It is especially relevant in the Galapagos which wants exceptional protection in view of its unique wildlife. The paper provides a methodology for effective management.
Short summary
In this research we aim to improve cleanup efforts on the Galapagos Islands of marine plastic debris when resources are limited and the distribution of the plastic on shorelines is unknown. Using a network that describes the flow of macroplastic between the islands we have identified the most efficient cleanup locations, quantified the impact of targeting these locations and showed that shorelines where the plastic is unlikely to leave are likely efficient cleanup locations.