Published March 28, 2022
| Version v1
Figure
Open
Fig. 1 in Analysis of biodiversity data suggests that mammal species are hidden in predictable places
Authors/Creators
- 1. Museum of Biological Diversity, The Ohio State University, Columbus, OH 43212 & Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43212
- 2. Department of Biology, Radford University, Radford, VA 24142
- 3. Department of Evolution, Ecology, and Organismal Biology, The Ohio State University, Columbus, OH 43212 & Department of Evolution, Ecology, and Organismal Biology, School of Environment and Natural Resources, Ohio Biodiversity Conservation Partnership, The Ohio State University, Columbus, OH 43210
Description
Fig. 1. Predictive modeling workflow. The framework proposed for identifying named mammal species that are likely to contain hidden diversity utilizes barcoding gene sequences and machine learning models built from environmental, geographic, climatic, taxonomic, and life history variables.
Notes
Published as part of Parsons, Danielle J., Pelletier, Tara A., Wieringa, Jamin G., Duckett, Drew J. & Carstens, Bryan C., 2022, Analysis of biodiversity data suggests that mammal species are hidden in predictable places, pp. 1-7 in Proceedings of the National Academy of Sciences 119 (14) on page 2, DOI: 10.1073/pnas.2103400119, http://zenodo.org/record/6448140
Files
figure.png
Files
(160.7 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:ee36c9cd7c916ba4975a6e65bf036448
|
160.7 kB | Preview Download |
Linked records
Additional details
Related works
- Is part of
- Journal article: 10.1073/pnas.2103400119 (DOI)
- Journal article: urn:lsid:plazi.org:pub:944FFFEDFFA2FFC2796F360E4568C62D (LSID)
- Journal article: https://zenodo.org/record/6448140 (URL)