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Type Package Package spthin February 20, 2015 Title Functions for Spatial Thinning of Species Occurrence Records for Use in Ecological Models Version 0.1.0 Date 2014-11-16 Author Matthew E. Aiello-Lammens, Robert A. Boria, Aleksandar Radosavljevic, Bruno Vilela, and Robert P. Anderson Maintainer Matthew E. Aiello-Lammens <matt.lammens@gmail.com> spthin is a set of functions that can be used to spatially thin species occurrence data. The resulting thinned data can be used in ecological modeling, such as ecological niche modeling. Depends spam, grid, fields, knitr LazyData TRUE License GPL-3 VignetteBuilder knitr NeedsCompilation no Repository CRAN Date/Publication 2014-11-17 08:57:55 R topics documented: Heteromys_anomalus_South_America........................... 2 plotthin........................................... 2 summarythin........................................ 3 thin............................................. 3........................................ 4 Index 6 1

2 plotthin Heteromys_anomalus_South_America Occurrence record locations for Heteromys anomalus A dataset containing compiled occurrence record locations for Heteromys anomalus in northern coastal South America. These records have been examined to check for accurate species identification. Format A data frame with 201 rows and 4 variables Details SPEC. species name assigned to occurrence record LAT. decimal degree latitude value LONG. decimal degree longitude value REGION. region, or island, of occurrence plotthin Plot diagnosis for results of thin function Three plots (selected by which) are currently available: a plot of the number of repetitions versus the number of maximum records retained at each repetition ([1] observed values; [2] log transformed) and a histogram of the maximun records retained [3]. plotthin(thinned, which = c(1:3), ask = prod(par("mfcol")) < length(which) && dev.interactive(),...) thinned A list of data.frames returned by thin function. which if a subset of the plots is required, specify a subset of the numbers 1:3. ask logical; if TRUE, the user is asked before each plot, see par(ask=.).... other parameters to be passed through to plotting functions. See Also thin

summarythin 3 summarythin Summary method for results of thin function Summarize the results of thin function. summarythin(thinned, show = TRUE) thinned show A list of data.frames returned by thin function. logical; if TRUE,the summary values are printed at the console. Value Returns a list with the (1) maximun number of records, (2) number of data frames with maximun number of records and (3) a table with the number of data frames per number of records. See Also thin thin Spatially thin species occurence data thin returns spatially thinned species occurence data sets. A randomizaiton algorithm () is used to create data set in which all occurnece locations are at least thin.par distance apart. Spatial thinning helps to reduce the effect of uneven, or biased, species occurence collections on spatial model outcomes. thin(loc.data, lat.col = "LAT", long.col = "LONG", spec.col = "SPEC", thin.par, reps, locs.thinned.list.return = FALSE, write.files = TRUE, max.files = 5, out.dir, out.base = "thinned_data", write.log.file = TRUE, log.file = "spatial_thin_log.txt", verbose = TRUE)

4 Value loc.data lat.col long.col spec.col thin.par A data.frame of occurence locations. It can include several columnns, but must include at minimum a column of latitude and a column of longitude values Name of column of latitude values. Caps sensitive. Name of column of longitude values. Caps sensitive. Name of column of species name. Caps sensitive. Thinning parameter - the distance (in kilometers) that you want records to be separated by. reps The number of times to repete the thinning process. Given the random process of removing nearest-neighbors there should be rep number of different sets of coordinates. locs.thinned.list.return TRUE/FALSE - If true, the list of the data.frame of thinned locs resulting from each replication is returned (see Returns below). write.files max.files out.dir out.base TRUE/FALSE - If true, new *.csv files will be written with the thinned locs data The maximum number of *csv files to be written based on the thinned data Directory to write new *csv files to A file basename to give to the thinned datasets created write.log.file TRUE/FALSE create/append log file of thinning run log.file verbose Text log file TRUE/FALSE - If true, running details of the function are print at the console. locs.thinned.dfs A list of data.frames, each data.frame the spatially thinned locations of the algorithm for a single replication. This list will have reps elements. See Also Implements random spatial thinning algorithm implements a randomization approach to spatially thinning species occurence data. This function is the algorithm underlying the thin function. (rec.df.orig, thin.par, reps)

5 rec.df.orig thin.par reps A data frame of long/lat points for each presence record. The data.frame should be a two-column data frame, one column of long and one of lat Thinning parameter - the distance (in kilometers) that you want records to be separated by. The number of times to repete the thinning process. Given the random process of removing nearest-neighbors there should be rep number of different sets of coordinates. Value reduced.rec.dfs: A list object of length rep. Each list element is a different data.frame of spatially thinned presence records.

Index Topic datasets Heteromys_anomalus_South_America, 2 Heteromys_anomalus_South_America, 2 plotthin, 2 summarythin, 3 thin, 2, 3, 3, 4, 2 4, 4 6