University of Lorraine, INRA, Research Unit Animal and Functionalities of Animal Products (URAFPA), 54000, Nancy, France.
INRA - AgroParisTech - U. Lorraine, UMR 1434 SILVA. Centre de recherche Grand Est-Nancy, 54113, Champenoux, France.
Sci Data. 2019 Dec 3;6(1):301. doi: 10.1038/s41597-019-0307-z.
Functional traits can be valuable pieces of information for aquaculture research and management. Although fish traits have been the focus of an abundant research, trait datasets for these organisms are difficult to access and often unpractical to achieve meta-analyses without a time-consuming extensive review. Already available large-scale compilations include trait information for many fish species but not as detailed as required for aquaculture purpose. Here, we introduce the TOFF (i.e. Traits OF Fish), a database focusing on fish functional traits that aims at bringing together behavioral, morphological, phenological, and physiological traits always coupled to environmental measurement context into a single open-source access repository. TOFF hosts data from published field and experimental studies. Here, we release data for 228 traits for 174 species extracted from 165 publications and present a collaborative platform. We ultimately aim at providing an inclusive and accessible data resource to facilitate advances in aquaculture development.
功能特征可以为水产养殖研究和管理提供有价值的信息。尽管鱼类特征一直是大量研究的重点，但这些生物的特征数据集很难获取，如果没有耗时的广泛审查，通常很难进行元分析。已经有许多大规模的综合数据集包括了许多鱼类的特征信息，但对于水产养殖目的来说，这些信息不够详细。在这里，我们引入了 TOFF（即鱼类特征），这是一个专注于鱼类功能特征的数据库，旨在将行为、形态、物候和生理特征与环境测量背景结合到一个单一的开源访问存储库中。TOFF 包含来自已发表的野外和实验研究的数据。在这里，我们发布了从 165 篇出版物中提取的 174 个物种的 228 个特征的数据，并展示了一个协作平台。我们的最终目标是提供一个包容性和可访问的数据资源，以促进水产养殖的发展。
