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Tropical forest permanent plot in Barro Colorado Island (Panama)

Source of data

Vegetation and environmental data: Condit et al. (2002)1)

Soil chemistry data: Soil maps of Barro Colorado Island 50ha plot

Description of the dataset

Map of Barro Colorado Island in Panama (source: CTFS website)

Data from 50 ha permanent plot, established by Smithsonian Tropical Research Institute and Princeton University to study the dynamics of tropical forest vegetation. The available dataset contains 50 1-ha plots, which align with each other. In each plot were recorded numbers of individuals of all forest species (only individuals with DBH > 10 cm are available in this dataset) and several environmental variables (see the table below).

Soil chemical analyses are also publicly available for BCI plot. Original soil data have a form of soil maps, which have been created from 300 collected and analysed soil samples by kriging and can be accessed here; spreadsheet dataset, created as kriged estimates for 20×20 m plots, is available here. For purpose of this example data, the soil data from 20×20 m plots were lumped into 1-ha plots to make it compatible with the vegetation dataset.


Barro Colorado is an island in the lake Gatun in central Panama. Since 1923, the island is a place of intensive scientific research focused on ecology of lowland tropical forest, and from the floristic point of view it's perhaps the most explored tropical area (of similar size) in the world. The studied 50-ha permanent plot is surveyed periodically since 1980.

The file with coordinates, which can be opened in Google Earth: bci.kml2) (source:

Photograph of Barro Colorado Island (author: Christian Ziegler/S.T.R.I., source: The New York Times).

Environmental variables

Variables available in BCI.env dataset (originally from BiodiversityR library, Kindt & Coe 2005). Note that original variables, which have been in BCI.env dataset in earlier versions of BiodiversityR library (Precipitation, Elevation, and Geology) and which were based on data published in Condit et al. (2002) were removed (they have been, so as so, of minor use, since they lack the resolution) and replaced by new topographical variables from De Caceres et al. (2012).

Name of variableDescription
UTM.EWlongitude [m]
UTM.NSlatitude [m]
elevationmean of the elevation values of the four cell corners [m]
convexconvexity - mean elevation of the target cell minus the mean elevation of the eight surrounding cells
slopemean angular deviation from horizontal of each of the four triangular planes formed by connecting three of its corners
aspectEWdeviation of aspect from east-west direction, calculated as sin (aspect)
aspectNSdeviation of aspect from north-south direction, calculated as cos (aspect)

Variables available in soil dataset (BCI.soil):

Name of variableDescription
x, y Relative coordinates of the plots [m]
Al, B, Ca, Cu, Fe, K, Mg, Mn, P, Zn, N, N(min), pH Measured soil chemistry variables3)
Map of elevation of the 50ha forest dynamics plot. Note that data for this map have higher resolution than the elevation data in the BCI.env dataset. Source: CTFS website.

Soil map for pH. Note that the resolution of this map is 20×20 m, although the resolution 100×100 m is used for further analyses.

Soil map for nitrogen. Note that the resolution of this map is 20×20 m, although the resolution 100×100 m is used for further analyses.

Spatial distribution of individual subplots (numbers 1, 2, ..., 50 represent the row in the species composition and environmental table).

Data for download

File name File type Description
bci.soil.txt tab-delimited txt file Soil data (originates from CTFR website, for purpose of analysis presented here rearranged using this script)

Script for direct import of data into R

# you will need library (vegan) - you can install it using following:
# install.packages ('vegan')
library (vegan)
data (BCI)
BCI.env <- read.delim ('', row.names = 1)
BCI.soil <- read.delim ('')

Note: The script for the preparation of soil data and drawing soil maps can be found here.


  • Condit, R, Pitman, N, Leigh, E.G., Chave, J., Terborgh, J., Foster, R.B., Nunez, P., Aguilar, S., Valencia, R., Villa, G., Muller-Landau, H.C., Losos, E. & Hubbell, S.P. (2002) Beta-diversity in tropical forest trees. Science 295: 666-669 pdf and Supplemental Table 1 - data in xls format
  • De Caceres, M., Legendre, P., Valencia R., Cao M., Chang L.-W., Chuyong G., Condit R., Hao Z., Hsieh, C.-F., Hubbell, S., Kenfack, D., Ma, K., Mi, X., Supardi Noor N., Kassim, A. R., Ren, H., Su, S.-H., Sun, I-F., Thomas, D., Ye, W. & He., F. (2012). The variation of tree beta diversity across a global network of forest plots. Global Ecology and Biogeography 21: 1191-1202 www
  • John, R., Dalling, J.W., Harms, K.E., Yavitt, J.B., Stallard, R.F., Mirabello, M., Hubbell, S.P., Valencia, R., Navarrete, H., Vallejo, M. & Foster, R.B. (2007) Soil nutrients influence spatial distributions of tropical tree species. PNAS 104: 864-869 pdf
  • Kindt, R. & Coe, R. (2005) Tree diversity analysis: A manual and software for common statistical methods for ecological and biodiversity studies.
  • Pyke, C.R., Condit, R., Aguilar, S. & Lao, S. (2001) Floristic composition across a climatic gradient in a neotropical lowland forest. Journal of Vegetation Science 12: 553-566 pdf

Note: access to the whole dataset could be applied using online form on website of Smithsonian Tropical Research Institute or National Center for Ecological Analysis and Synthesis.

part of freely available data included in libraries vegan and BiodiversityR
you need Google Earth installed on your computer to open this file
for details regarding soil chemistry analysis see protocol used for the sampling of the BCI plot
en/data/bci.txt · Last modified: 2022/03/31 21:20 by David Zelený

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