A solution to the challenges of interdisciplinary aggregation and use of specimen-level trait data
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Author
Balk, M.A.Deck, J.
Emery, K.F.
Walls, R.L.
Reuter, D.
LaFrance, R.
Arroyo-Cabrales, J.
Barrett, P.
Blois, J.
Boileau, A.
Brenskelle, L.
Cannarozzi, N.R.
Cruz, J.A.
Dávalos, L.M.
de la Sancha, N.U.
Gyawali, P.
Hantak, M.M.
Hopkins, S.
Kohli, B.
King, J.N.
Koo, M.S.
Lawing, A.M.
Machado, H.
McCrane, S.M.
McLean, B.
Morgan, M.E.
Pilaar Birch, S.
Reed, D.
Reitz, E.J.
Sewnath, N.
Upham, N.S.
Villaseñor, A.
Yohe, L.
Davis, E.B.
Guralnick, R.P.
Affiliation
BIO5 Institute, University of ArizonaCollege of Science, University of Arizona
Issue Date
2022Keywords
AnimalsBiological database
Evolutionary history
Ornithology
Paleobiology
Phylogenetics
Systematics
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Elsevier Inc.Citation
Balk, M. A., Deck, J., Emery, K. F., Walls, R. L., Reuter, D., LaFrance, R., Arroyo-Cabrales, J., Barrett, P., Blois, J., Boileau, A., Brenskelle, L., Cannarozzi, N. R., Cruz, J. A., Dávalos, L. M., de la Sancha, N. U., Gyawali, P., Hantak, M. M., Hopkins, S., Kohli, B., … Guralnick, R. P. (2022). A solution to the challenges of interdisciplinary aggregation and use of specimen-level trait data. IScience, 25(10).Journal
iScienceRights
Copyright © 2022 The Authors. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
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. © 2022 The AuthorsNote
Open access journalISSN
2589-0042Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1016/j.isci.2022.105101
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Except where otherwise noted, this item's license is described as Copyright © 2022 The Authors. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).