TY - JOUR
T1 - A solution to the challenges of interdisciplinary aggregation and use of specimen-level trait data
AU - Balk, Meghan A.
AU - Deck, John
AU - Emery, Kitty F.
AU - Walls, Ramona L.
AU - Reuter, Dana
AU - LaFrance, Raphael
AU - Arroyo-Cabrales, Joaquín
AU - Barrett, Paul
AU - Blois, Jessica
AU - Boileau, Arianne
AU - Brenskelle, Laura
AU - Cannarozzi, Nicole R.
AU - Cruz, J. Alberto
AU - Dávalos, Liliana M.
AU - de la Sancha, Noé U.
AU - Gyawali, Prasiddhi
AU - Hantak, Maggie M.
AU - Hopkins, Samantha
AU - Kohli, Brooks
AU - King, Jessica N.
AU - Koo, Michelle S.
AU - Lawing, A. Michelle
AU - Machado, Helena
AU - McCrane, Samantha M.
AU - McLean, Bryan
AU - Morgan, Michèle E.
AU - Pilaar Birch, Suzanne
AU - Reed, Denne
AU - Reitz, Elizabeth J.
AU - Sewnath, Neeka
AU - Upham, Nathan S.
AU - Villaseñor, Amelia
AU - Yohe, Laurel
AU - Davis, Edward B.
AU - Guralnick, Robert P.
N1 - Publisher Copyright:
© 2022 The Authors
PY - 2022/10/21
Y1 - 2022/10/21
N2 - 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.
AB - 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.
KW - Animals
KW - Biological database
KW - Evolutionary history
KW - Ornithology
KW - Paleobiology
KW - Phylogenetics
KW - Systematics
UR - http://www.scopus.com/inward/record.url?scp=85139322881&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85139322881&partnerID=8YFLogxK
U2 - 10.1016/j.isci.2022.105101
DO - 10.1016/j.isci.2022.105101
M3 - Article
C2 - 36212022
SN - 2589-0042
VL - 25
JO - iScience
JF - iScience
IS - 10
M1 - 105101
ER -