| Autor: |
Michelle Lawing, Edward Byrd Davis, Nathan S. Upham, Joaquín Arroyo-Cabrales, Samantha S. B. Hopkins, Brooks A. Kohli, John Deck, J. Alberto Cruz, Elizabeth J. Reitz, Ramona Walls, Michèle E. Morgan, Michelle S. Koo, Robert P. Guralnick, Laura Brenskelle, Bryan McLean, Amelisa Villseñor, Helena Machado, Raphael LaFrance, Denné Reed, Suzanne Pilaar-Birch, Arianne Boileau, Paul Barret, Kitty F. Emery, Laurel R Yohe, Maggie M. Hantak, Meghan A. Balk, Neeka Sewnath, Nicole R. Cannarozzi, Dana M. Reuter, Jessica L. Blois, Liliana M. Davanos, Noé U. de la Sancha, Samantha McCrane, Jessica N. King |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
SSRN Electronic Journal. |
| ISSN: |
1556-5068 |
| DOI: |
10.2139/ssrn.3783406 |
| Popis: |
Understanding variation of traits within and among species through time and across space is central to many questions in biology. Many resources have been developed to assemble trait data at the species level, but the underlying data and metadata about those trait measurements are often not reported, limiting broadest utility. Here we introduce FuTRES (Functional Trait Resource for Environmental Studies), a datastore and community resource for individual-level trait reporting that utilizes a strong semantic framework and best practices approach to overcome previous limitations. FuTRES already stores millions of trait measurements that span across multiple time scales, including zooarchaeological and paleobiological specimens, with a current focus on mammals. Two case studies showcase the promise of FuTRES. The first compares dynamically derived extant mammal species' body size estimates with summary values from other compilations, highlighting potential issues with simply reporting a single mean estimate. The second shows that FuTRES data improves 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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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