DOI: 10.5061/dryad.z08kprrj5
title: Data from: Tree functional traits across Caribbean island dry forests are remarkably similar

description: Delineation of potential dry forest and estimated actual dry forest on
 Caribbean islands. Potential dry forest is delineated based on CHELSA
 climate data (www.chelsa-climate.org) and the FAO definition of dry
 forest. Estimated actual dry forest is corrected for land cover using data
 from Hansen et al. (2022) https://doi.org/10.1088/1748-9326/ac46ec. Areas
 of potential dry forest, estimated actual dry forest, and area of built-up
 land covers are summarized by islands and joined to CHELSA bioclimatic
 variables for selected islands where data on functional traits are
 available. Trait values by sites are also included. The package consists
 of data outputs and R scripts to reproduce the data outputs from
 identified publicly available data sources.
description: Areas potentially supporting tropical dry forest in the Caribbean
 were delineated based on precipitation normals data from CHELSA and a
 climatically-based definition of tropical dry forest established by the
 Food and Agriculture Association of the United Nations (FAO): total annual
 precipitation 500 to 1500 mm, 5-8 mo &lt; 100 mm precipitation. Land
 cover data (2019 conditions) from Hansen et al. were used to constrain
 estimated actual dry forest based on the intersection of climate-based
 potential dry forest with forested land cover. To facilitate analysis with
 functional trait data obtained from forests on a subset of islands, data
 on the area of potential and estimated actual dry forest and forest and
 built land covers were summarized by island and associated with a standard
 suite of 19 bioclimate variables. R scripts showing and reproducing our
 detailed methods are provided with the repository.
description: Data processing and analysis was conducted in R version 4.2.1 in
 RStudio using the raster (v3.5.21), rgdal (v1.5.32), rgeos (v0.5.9), sf
 (v1.0.8), and fields (v13.3) packages.
description: ## README --- Delineation of potential dry forest and estimated actual dry
 forest on Caribbean islands. Potential dry forest is delineated based on
 CHELSA climate data and the FAO definition of dry forest. Estimated actual
 dry forest is corrected for land cover using data from Hansen et al.
 (2022) . Areas of
 potential dry forest, estimated actual dry forest, and area of built-up
 land covers are summarized by islands and joined to CHELSA bioclimatic
 variables for selected islands where data on functional traits are
 available. The package consists of data outputs and R scripts to reproduce
 the data outputs from identified publicly available data sources. ##
 Description of the data and file structure The data include raster image
 (GeoTIFF) files of potential and estimated actual dry forest, and a
 spreadsheet (.csv) of island and land cover areas joined to bioclimatic
 variables for a selection of islands where plant functional trait data
 were available. A spreadsheet (.csv) provides the locations where plant
 functional trait data were available. An additional spreadsheet (.csv)
 provides the species names and trait values used for calculations. A text
 file (.txt) of urls of CHELSA files to download supports an R script for
 downloading those data. potential_dryforest.tif: raster image in GeoTIFF
 format of potential dry forest. Delineated based on climate normals data
 from CHELSA using the FAO definition of total annual precipitation 500 to
 1500 mm, 5-8 mo &lt; 100 mm precipitation.
 potential_dryforest.tif.aux,xml: helper file for file 1.
 WestIndiesSDTF_locality.csv: spreadsheet of locations where functional
 trait data are available. Columns are as follows: country island
 archipelag long: longitude lat: latitude chelsa_dllist.txt: a text file of
 urls of files to download. Used by downloadCHELSA.R. traits_by_sites.csv:
 a spreadsheet of individual sites and their calculated functional richness
 (Fric), functional dispersion (FDis), wood density, specific leaf area,
 and seed mass. 'NA' indicates missing values. Columns are as
 follows: site FRic (functional richness) FDis (functional dispersion) wd
 (wood density, g cm^-2) sla (specific leaf area, cm^2 g^-1) sm (seed mass,
 mg) ## Sharing/Access information Data was derived from the following
 sources: CHELSA climate project: .
 Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza,
 R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at
 high resolution for the Earth land surface areas. *Scientific Data***.** 4
 170122. Brun, P., Zimmermann, N.E., Hari, C., Pellissier, L., Karger, D.
 (2022): Data from: CHELSA-BIOCLIM+ A novel set of global climate-related
 predictors at kilometre-resolution. *EnviDat.
 * Global land cover and land
 use 2019:
 ,
 . Hansen, M. C., Potapov,
 P. V., Pickens, A. H., Tyukavina, A., Hernandez-Serna, A., Zalles, V., ...
 & Kommareddy, A. (2022). Global land use extent and dispersion within
 natural land cover using Landsat data. *Environmental Research Letters*,
 *17*(3), 034050. ## Code/Software There are two R scripts provided that
 reproduce the data products in this repository: 1. downloadCHELSA.R:
 downloads selected precipitation normals and bioclimate variables from
 CHELSA. 2. delineateDryForest.R: performs data management, subsetting,
 summarization, and spatial analysis fuctions to produce the data outputs.
 These scripts were produced in R version 4.2.1 in RStudio using the raster
 (v3.5.21), rgdal (v1.5.32), rgeos (v0.5.9), sf (v1.0.8), and fields
 (v13.3) packages.