JOURNAL ARTICLE

Climate-Change Impacts on Cephalopods: A Meta-Analysis.

  • Published In: Integrative & Comparative Biology, 2023, v. 63, n. 6. P. 1240 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Borges, Francisco O; Sampaio, Eduardo; Santos, Catarina P; Rosa, Rui 3 of 3

Abstract

This article focuses on the experimental impacts of marine climate change—specifically ocean warming (OW), ocean acidification (OA), and their interaction (OWA)—on cephalopods, a diverse class of marine mollusks including octopuses, squids, and cuttlefish. Through a meta-analysis of 47 peer-reviewed studies involving controlled laboratory exposures, the research finds that OW poses a significant and pervasive threat to cephalopods across taxonomic groups, life stages (especially early ontogeny), and biological functions, reducing survival and development times while increasing metabolic and cellular stress. OA effects are less pronounced and mostly limited to certain temperate species and life stages, with combined OW and OA exposures underrepresented but indicating potential synergistic negative impacts. The study highlights critical knowledge gaps, including a lack of research on ocean deoxygenation and multi-stressor interactions, and calls for expanded experimental efforts across more species, life stages, and climate regions to better understand cephalopods’ responses to future ocean conditions, which is essential for conservation and fisheries management.

Additional Information

  • Source:Integrative & Comparative Biology. 2023/12, Vol. 63, Issue 6, p1240
  • Document Type:Article
  • Subject Area:Agriculture and Agribusiness
  • Publication Date:2023
  • ISSN:1540-7063
  • DOI:10.1093/icb/icad102
  • Accession Number:174525812
  • Copyright Statement:Copyright of Integrative & Comparative Biology is the property of Oxford University Press / USA 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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