Jeffrey A. Wolf, Stephen P. Hubbell, Geoffrey A. Fricker, and Benjamin L. Turner. 2015. Geospatial observations on tropical forest surface soil chemistry. Ecology 96:2313.

Data Paper

Ecological Archives E096-204-D1.


Data Files


Jeffrey A. Wolf,1,4 Stephen P. Hubbell,1,2 Geoffrey A. Fricker,3 Benjamin L. Turner2

1 Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095, USA ([email protected], [email protected])

2 Smithsonian Tropical Research Institute, Apartado 0843-03092, Balboa, Ancon, Republic of Panama ([email protected])

3 Department of Geography, Bunche Hall, University of California, Los Angeles, CA 90095, USA ([email protected])

4 Corresponding author. E-mail: [email protected].

Data Files

corners.csv (MD5: 00b9af230a2cd73315d473083f6e7647)

soils.csv (MD5: d4deb84fa3a2300097efc07a7a42700c)

standards.csv (MD5: bdeb50c58864228f02b06be2971d11dc) (MD5: 30f8248abbe2851dd2b5763933ca6165)


At plot scales (<1 km²) used to study tropical forest plant communities the causes of spatial heterogeneity of soils are disputed. We collected, georeferenced, and chemically analyzed a large spatial sample of soil cores (n = 625 sites, 6.25 cm diameter 10 cm depth cores) on an approximately 28 m regular grid from the Barro Colorado Island (BCI) 50-ha (0.5 km²) forest dynamics plot (FDP), Republic of Panama (9.15 N, 79.8 W). Here we present these data for general use. We also present differential GPS measurements of the plot corners for the BCI 50-ha FDP, which aid in geospatial research in one of the most studied tropical forests. Further, we present a free open source command line software program written in Python that allows point data referenced to the plot coordinate system to be converted to a projected coordinate reference system for geospatial research. Together, the data sets allow for testing the drivers of soil heterogeneity in a tropical tree community using a wide variety of geospatial data sources.

Key words: Barro Colorado Island; biodiversity; biogeochemistry; Geographic Information Systems; nutrients; remote sensing; spatial projection; soil.