Primary tabs

Boise State University logo

Boise State University is a Carnegie-classified doctoral research university and our students have opportunities to work with talented and accomplished faculty on research, even as undergraduates. Our students go into the workforce better prepared, with expertise outside of their major by taking advantage of opportunities such as certificates in business anthropology, entrepreneurship, or cybersecurity.

Learn more at

Data Extent

Other Access

The information on this page (the dataset metadata) is also available in these formats.


via the DKAN API

Data from: Near-infrared spectroscopy aids ecological restoration by classifying variation of taxonomy and phenology of a native shrub

Plant communities are composed of complex phenotypes that not only differ among taxonomic groups and habitats but also change over time within a species. Restoration projects (e.g., translocations, reseeding) can introduce new functional variation in plants, which further diversifies phenotypes and complicates our ability to identify locally adaptive phenotypes for future restoration. Near-infrared spectroscopy (NIRS) offers one approach to detect the chemical phenotypes that differentiate plant species, populations, and phenological states of individual plants over time. We used sagebrush (Artemisia spp.) as a case study to test the accuracy by which NIRS can classify variation within taxonomy and phenology of a plant that is extensively managed and restored. Our results demonstrated that NIRS can accurately classify species of sagebrush within a study site (75-96%), populations of sagebrush within a subspecies (99%), annual phenology within a population (>99%), and seasonal phenology within individual plants (>97%). Low classification accuracy by NIRS in some sites may reflect heterogeneity associated with natural hybridization, translocation of non-local seed sources from past restoration, or complex gene-by-environment (GxE) interactions. Advances in our ability to detect and interpret spectral signals from plants may improve both the selection of seed sources for targeted conservation and the capacity to monitor long-term changes in vegetation.

Data Use
License: CC-BY 4.0
Recommended Citation: Robb, B., Olsoy, P., Mitchell, J., Caughlin, T. T., Delparte, D., Galla, S., Fremgen-Tarantino, M. R., Nobler, J. D., Rachlow, J., Shipley, L. A., & Sorensen Forbey, J. (2021). Data from: Near-infrared spectroscopy aids ecological restoration by classifying variation of taxonomy and phenology of a native shrub [Data set]. University of Idaho.

Release Date
Spatial / Geographical Coverage Area
POINT (-113.289869 44.699597)
POINT (-114.317528 43.242182)
POINT (-113.4 42.15)
POINT (-113.383333 42.95)
POLYGON ((-114.57313299179 42.021815832489, -114.57313299179 44.900738456164, -112.88635879755 44.900738456164, -112.88635879755 42.021815832489))
Spatial / Geographical Coverage Location
Idaho USA
Temporal Coverage
Tuesday, January 1, 2013 - 00:00 to Thursday, December 31, 2015 - 00:00
English (United States)
Brecken C. Robb, Peter J. Olsoy, Jessica J. Mitchell, T. Trevor Caughlin, Donna M. Delparte, Stephanie J. Galla, Marcella R. Fremgen-Tarantino, Jordan D. Nobler, Janet L. Rachlow, Lisa A. Shipley, Jennifer Sorenson Forbey
Contact Name
Jennifer Forbey
Contact Email
Public Access Level
Data available on:: 
Monday, January 3, 2022