A solution to the challenges of interdisciplinary aggregation and use of specimen-level trait data
Understanding variation of traits within and among species through time and across space is central to many questions in biology. Many resources assemble species-level trait data, but the data and metadata underlying those trait measurements are often not reported. Here, we introduce FuTRES (Functio...
Gespeichert in:
Veröffentlicht in: | iScience 2022-10, Vol.25 (10), p.105101-105101, Article 105101 |
---|---|
Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Understanding variation of traits within and among species through time and across space is central to many questions in biology. Many resources assemble species-level trait data, but the data and metadata underlying those trait measurements are often not reported. Here, we introduce FuTRES (Functional Trait Resource for Environmental Studies; pronounced few-tress), an online datastore and community resource for individual-level trait reporting that utilizes a semantic framework. FuTRES already stores millions of trait measurements for paleobiological, zooarchaeological, and modern specimens, with a current focus on mammals. We compare dynamically derived extant mammal species' body size measurements in FuTRES with summary values from other compilations, highlighting potential issues with simply reporting a single mean estimate. We then show that individual-level data improve estimates of body mass—including uncertainty—for zooarchaeological specimens. FuTRES facilitates trait data integration and discoverability, accelerating new research agendas, especially scaling from intra- to interspecific trait variability.
[Display omitted]
•Functional Trait Resource for Environmental Studies (FuTRES; few-tress)•Individual-level trait datastore for paleo-, zooarcheological, and modern specimens•Millions of individual-level trait data records already available for mammals•Semantic framework for enhanced interoperability, R package for access, and APIas
Ornithology; Animals; Systematics; Evolutionary history; Phylogenetics; Biological database; Paleobiology. |
---|---|
ISSN: | 2589-0042 2589-0042 |
DOI: | 10.1016/j.isci.2022.105101 |