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Near-global spawning strategies of large pelagic fish
Research Square, Vol.3 July 2024
Research Square Company
2024
Abstract
Knowledge of spawning strategies of large pelagic fish could provide insights into their underlying evolutionary drivers, but large-scale information on spawning is limited. Here we use a near-global larval dataset for 15 large pelagic fish to build habitat suitability models and use these as a proxy for spawning grounds.We found considerable consistency in spawning in time and space, with 10 taxa spawning in spring/summer and 11 taxa spawning off Northwest Australia. Considering the vast ocean area where these large pelagic fish could spawn, these results suggest that the evolutionary benefits of co-locating spawning in terms of advantageous larval conditionsoutweigh the benefits of segregated spawning in terms of reduced competition and lower larval predation. The knowledge that many large-pelagic fish taxa co-locate their spawning could inform marine management through fisheries measures to protect spawners, and the placement of marine protected areas.
Details
- Title
- Near-global spawning strategies of large pelagic fish
- Authors
- Kristine Camille V Buenafe (Corresponding Author) - The University of QueenslandSandra Neubert - Leipzig UniversityKylie Scales - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringDaniel Dunn - The University of QueenslandJason D Everett - The University of QueenslandJason Flower - University of California, Santa BarbaraIan Suthers - UNSW SydneyPablo Granado-Dieseldorff - Waitt FoundationAlvise Dabala - The University of QueenslandKris Jypson Esturas - The University of QueenslandJason Mercer - UNSW SydneyAnthony J Richardson - The University of Queensland
- Publication details
- Research Square, Vol.3 July 2024
- Publisher
- Research Square Company
- Date published
- 2024
- DOI
- 10.21203/rs.3.rs-4532139/v1
- ISSN
- 2693-5015
- Copyright note
- This work is licensed under a Creative Commons Attribution 4.0 International License.
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991051595402621
- Output Type
- Preprint
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