Document of bibliographic reference 406279

BibliographicReference record

Type

Bibliographic resource

Type of document

Journal article

BibLvlCode

AS

Title

Pathways for converting zooplankton traits to ecological insights are paved with findable, accessible, interoperable, and reusable (FAIR) data practices

Abstract

The use of trait-based approaches and trait data in zooplankton ecology is rapidly growing to better understand and predict the patterns of zooplankton distributions and their role in aquatic ecosystems and biogeochemical cycles. Although the number of zooplankton trait-based studies and available trait datasets is increasing, several challenges remain for the findability, accessibility, interoperability, and reusability (FAIR) in trait-based approaches that, if unaddressed, may stifle progress in this research area. Here, we review recent applications of trait-based approaches in zooplankton research and summarize the currently available trait data resources. To realize the potential of trait-based approaches to resolve ecological roles of zooplankton, datasets and approaches must adhere to FAIR principles. We provide recommendations and pathways forward to ensure FAIRness while highlighting the importance of collaborative efforts. These practical and easily implementable strategies will enhance the FAIRness of trait data, ultimately advancing zooplankton ecological research and connecting these findings to aquatic ecosystem functioning

Bibliographic citation

Titocci, Jessica; Pata, Patrick R; Durazzano, Tiziana; Ayata, Sakina-Dorothée; Clerc, Corentin; Cornils, Astrid; Duffy, Patrick; Greer, Adam T; Halsband, Claudia; Heneghan, Ryan F; Lacoursière-Roussel, Anaïs; Lombard, Fabien; Majaneva, Sanna; Pakhomov, Evgeny A; Reis, Carolina; Rist, Sinja; Rommel, Alix C M; Silva, Teresa; Stemmann, Lars; Ugwu, Kevin; Basset, Alberto; Rosati, Ilaria; Murphy, Kieran J; Hunt, Brian P V (2025). Pathways for converting zooplankton traits to ecological insights are paved with findable, accessible, interoperable, and reusable (FAIR) data practices. ICES J. Mar. Sci./J. Cons. int. Explor. Mer 82(2): fsaf017. https://dx.doi.org/10.1093/icesjms/fsaf017

Is peer reviewed

true

Access rights

open access

Is accessible for free

true