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Data from: Global plant ecology of tropical ultramafic ecosystems

Citation

Hulshof, Catherine et al. (2022), Data from: Global plant ecology of tropical ultramafic ecosystems, Dryad, Dataset, https://doi.org/10.5061/dryad.0zpc8670p

Abstract

This is a compiled geospatial dataset in ESRI polygon shapefile format of ultramafic soils of the neotropics showing the location of ultramafic soils in Guatemala, Cuba, Dominican Republic, Puerto Rico, Costa Rica, Colombia, Argentina, Chile, Venezuela, Ecuador, Brazil, Suriname, French Guiana, and Bolivia. The data are derived from seven geospatial datasets. Original datasets were subset to include only ultramafic areas, datasets were assigned a common projection (WGS84), attribute tables were reconciled to a common set of fields, and the datasets were combined.

The dataset includes three components: 1) a geospatial dataset in ESRI polygon shapefile format of ultramafic soils of the neotropics showing the location of ultramafic soils in Guatemala, Cuba, Dominican Republic, Puerto Rico, Costa Rica, Colombia, Argentina, Chile, Venezuela, Ecuador, Brazil, Suriname, French Guiana, and Bolivia. 2) A regional-specific bibliography for all tropical ultramafic regions discussed in the original manuscript (Garnica-Diaz et al. 2022), and 3) an updated list in .csv format of major ultramafic outcrops worldwide including their latitude and longitude coordinates. 

Methods

The geospatial data are derived from seven geospatial datasets. Original datasets were subset to include only ultramafic areas, datasets were assigned a common projection (WGS84), attribute tables were reconciled to a common set of fields, and the datasets were combined. 

The region-specific bibliography was compiled by regional experts and identified as key references for each region included in the original manuscript.

The list of major ultramafic outcrops worldwide was compiled through an extensive literature search including Brooks (1987); Roberts & Proctor (1992), and other published studies. For some locations, the landmark represents the closest named geographical location (e.g., province, municipality, etc.). 

Usage Notes

The contents of the compiled geospatial dataset are in ESRI shapefile format and thus have four components with extensions .shp, .shx, .prj, and .dbf. The .shp file contains the feature geometries, the .prj file contains the geographic coordinate system information (WGS 1984), and the .dbf file contains the attribute table. The README.txt file includes additional information for the geospatial database including data fields, and sources for each of the seven individual geospatial datasets. 

Funding

National Science Foundation, Award: NSF-MSB-ECA #1833358

National Science Foundation, Award: NSF-CAREER #2042453