Search Data.gov
Found 232 dataset(s) matching "Vegetation diversity".
-
These data consist of environmental covariates, measured plot-level and tree characteristics for seven coniferous tree species across the southwestern United States. The objectives of the study...
-
This dataset represents the variety (count of unique classes within 1 ha) of vegetation communities, river channel and bare areas (often sand bars) mapped along the Colorado River bottomland from...
-
<p>This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets...
-
<p>This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets...
-
The data release presents observations of riparian vegetation, topography, soil characteristics, and ground cover in three river segments located above, below, and between the former Glines Canyon...
-
This dataset represents the variety (count of unique classes within 0.5 ha) of vegetation communities, river channel and bare areas (often sand bars) mapped along the Colorado River bottomland...
-
<p>Sweetpotato (<em>Ipomoea batatas</em>) plays a critical role in food security and is the most important root crop worldwide following potatoes and cassava. In the United States (US), it is...
-
The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al....
-
The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al....
-
The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al....
-
The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al....
-
The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al....
-
The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al....
-
The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al....
-
The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al....
-
The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al....
-
The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al....
-
The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al....
-
The Maxent modeling algorithm was used to build the species distribution model at 270 m spatial resolution using species occurrence points and environmental layers as predictors (Phillips et al....
