Vegetation structure and composition in the Sheeprock and East Tintic Mountains, Utah
dataset
posted on 2024-09-12, 20:06authored byErica Fleishman
These data document vegetation structure (tree, shrub, and ground cover) and composition of trees and shrubs (in most cases, ground cover is differentiated by functional group but not by species) in canyons and nearby areas in two mountain ranges in the eastern Great Basin: the Sheeprock Mountains (Tooele County) and East Tintic Mountains (Tooele and Utah counties), Utah. Vegetation data were collected in 2016 and 2017 at 96 locations where annual point-counts of breeding birds were conducted. The year in which vegetation structure and composition was measured differed among locations; vegetation structure and composition were measured once at each location. Data were collected to examine relations between abundance, occupancy, and detection probability of breeding birds and vegetation covariates. Data also may be used to train and validate models of vegetation (e.g., presence of riparian vegetation, potential changes in distribution of dominant species) that are based all or in part on remotely sensed data. Additionally, data may be used to examine responses of vegetation to fire, vegetation treatments, or other land uses. These data serve as environmental covariates for Fleishman 2019 (https://doi.org/10.2737/RDS-2019-0017). Vegetation data were collected at all locations where birds were sampled. Spatial data attributes in the breeding-bird data publication and this data publication (range, canyon or area, year, UTMx, UTMy) are the same and can be linked in a relational database or lookup table.
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:
Fleishman, Erica. 2019. Vegetation structure and composition in the Sheeprock and East Tintic Mountains, Utah. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2019-0019