2024/10/01 by Madeleine M. Ostwald, Víctor H. González, C. P. Chang +3 · 1 voice · 21 citations
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · #Biology #Computer science #Data science #Data sharing #Ecology #Insect and Arachnid Ecology and Behavior #Insect and Pesticide Research #Metadata #Plant and animal studies #Trait #World Wide Web
paper · pdf · doi:10.1002/ece3.70465
published in Ecology and Evolution 14(10), e70465 (Wiley)
openalex publication_date 2024/10/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Functional traits offer an informative framework for understanding ecosystem functioning and responses to global change. Trait data are abundant in the literature, yet many communities of practice lack data standards for trait measurement and data sharing, hindering data reuse that could reveal large-scale patterns in functional and evolutionary ecology. Here, we present a roadmap toward community data standards for trait-based research on bees, including a protocol for effective trait data sharing. We also review the state of bee functional trait research, highlighting common measurement approaches and knowledge gaps. These studies were overwhelmingly situated in agroecosystems and focused predominantly on morphological and behavioral traits, while phenological and physiological traits were infrequently measured. Studies investigating climate change effects were also uncommon. Along with our review, we present an aggregated morphological trait dataset compiled from our focal studies, representing more than 1600 bee species globally and serving as a template for standardized bee trait data presentation. We highlight obstacles to harmonizing this trait data, especially ambiguity in trait classes, methodology, and sampling metadata. Our framework for trait data sharing leverages common data standards to resolve these ambiguities and ensure interoperability between datasets, promoting accessibility and usability of trait data to advance bee ecological research.