[Dataset:] Barro Colorado Forest Census Plot Data (Version 2012)

Abstract:

The 50-hectare plot at Barro Colorado Island, Panama, is a 1000 meter by 500
meter rectangle of forest inside of which all woody trees and shrubs with
stems at least 1 cm in stem diameter have been censused. Every individual tree
in the 50 hectares was permanently numbered with an aluminum tag in 1982, and
every individual has been revisited six times since (in 1985, 1990, 1995,
2000, 2005, and 2010). In each census, every tree was measured, mapped and
identified to species. Details of the census method are presented in Condit
(Tropical forest census plots: Methods and results from Barro Colorado Island,
Panama and a comparison with other plots; Springer-Verlag, 1998), and a
description of the seven-census results in Condit, Chisholm, and Hubbell
(Thirty years of forest census at Barro Colorado and the Importance of
Immigration in maintaining diversity; PLoS ONE, 7:e49826, 2012).

Description:

CITATION TO DATABASE: Condit, R., Lao, S., Pérez, R., Dolins, S.B., Foster,
R.B. Hubbell, S.P. 2012. Barro Colorado Forest Census Plot Data, 2012 Version.
DOI http://dx.doi.org/10.5479/data.bci.20130603

CO-AUTHORS: Stephen Hubbell and Richard Condit have been principal
investigators of the project for over 30 years. They are fully responsible for
the field methods and data quality. As such, both request that data users
contact them and invite them to be co-authors on publications relying on the
data. More recent versions of the data, often with important updates, can be
requested directly from R. Condit ([e-mail]).

ACKNOWLEDGMENTS: The following should be acknowledged in publications for
contributions to the 50-ha plot project: R. Foster as plot founder and the
first botanist able to identify so many trees in a diverse forest; R. Pérez
and S. Aguilar for species identification; S. Lao for data management; S.
Dolins for database design; plus hundreds of field workers for the census
work, now over 2 million tree measurements; the National Science Foundation,
Smithsonian Tropical Research Institute, and MacArthur Foundation for the bulk
of the financial support.

File 1. RoutputFull.pdf: Detailed documentation of the 'full' tables in Rdata
format (File 5).

File 2. RoutputStem.pdf: Detailed documentation of the 'stem' tables in Rdata
format (File 7).

File 3. ViewFullTable.zip: A zip archive with a single ascii text file named
ViewFullTable.txt holding a table with all census data from the BCI 50-ha
plot. Each row is a single measurement of a single stem, with columns
indicating the census, date, species name, plus tree and stem identifiers; all
seven censuses are included. A full description of all columns in the table
can be found at http://dx.doi.org/10.5479/data.bci.20130604 (ViewFullTable,
pp. 21-22 of the pdf).

File 4. ViewTax.txt: An ascii text table with information on all tree species
recorded in the 50-ha plot. There are columns with taxonomics names (family,
genus, species, and subspecies), plus the taxonomic authority. The column
'Mnemonic' gives a shortened code identifying each species, a code used in the
R tables (Files 5, 7). The column 'IDLevel' indicates the depth to which the
species is identified: if IDLevel='species', it is a fully identified, but if
IDLevel='genus', the genus is known but not the species. IDLevel can also be
'family', or 'none' in case the species is not even known to family.

File 5. bci.full.Rdata31Aug2012.zip: A zip archive holding seven R Analytical
Tables, versions of the BCI 50 ha plot census data in R format. These are
designed for data analysis. There are seven files, one for each of the 7
censuses: 'bci.full1.rdata' for the first census through 'bci.full7.rdata' for
the seventh census. Each of the seven files is a table having one record per
individual tree, and each includes a record for every tree found over the
entire seven censuses (i.e. whether or not they were observed alive in the
given census, there is a record). Detailed documentation of these tables is
given in RoutputFull.pdf (File 1).

File 6. bci.spptable.rdata: A list of the 1064 species found across all tree
plots and inventories in Panama, in R format. This is a superset of species
found in the BCI censuses: every BCI species is included, plus additional
species never observed at BCI. The column 'sp' in this table is a code
identifying the species in the R census tables (File 5, 7), and matching
'mnemomic' in ViewFullTable (File 3).

File 7. bci.stem.Rdata31Aug2012.zip: A zip archive holding seven R Analytical
Tables, versions of the BCI 50 ha plot census data in R format. These are
designed for data analysis. There are seven files, one for each of the 7
censuses: 'bci.stem1.rdata' for the first census through 'bci.stem7.rdata' for
the seventh census. Each of the seven files is a table having one record per
individual stem, necessary because some individual trees have more than one
stem. Each includes a record for every stem found over the entire seven
censuses (i.e. whether or not they were observed alive in the given census,
there is a record). Detailed documentation of these tables is given in
RoutputStem.pdf (File 2).

File 8. TSMAttributes.txt: An ascii text table giving full descriptions of
measurement codes, which are also referred to as TSMCodes. These short codes
are used in the column 'code' in R tables and in the column 'ListOfTSM' in
ViewFullTable.txt, in both cases with individual codes separated by commas.

File 9. bci_31August2012_mysql.zip: A zip archive holding one file, 'bci.sql',
which is a mysqldump of the complete MySQL database (version 5.0.95,
http://www.mysql.com) created 31 August 2012. The database includes data
collected from seven censuses of the BCI 50 ha plot plus censuses of many
additional plots elsewhere in Panama, plus transects where only species
identifications were collected and trees were not tagged nor measurements
made. Detailed documentation of all tables within the database can be found at
(http://dx.doi.org/10.5479/data.bci.20130604). This version of the data is
intended for experienced SQL users; for most, the R Analytical Tables in
Rtables.zip are more useful.