Type:	Package
Title:	Euclidean Climatch Algorithm
Version:	1.0.2
Depends:	R (≥ 3.5.0)
Description:	An interface for performing climate matching using the Euclidean "Climatch" algorithm. Functions provide a vector of climatch scores (0-10) for each location (i.e., grid cell) within the recipient region, the percent of climatch scores >= a threshold value, and mean climatch score. Tools for parallelization and visualizations are also provided. Note that the floor function that rounds the climatch score down to the nearest integer has been removed in this implementation and the “Climatch” algorithm, also referred to as the “Climate” algorithm, is described in: Crombie, J., Brown, L., Lizzio, J., & Hood, G. (2008). “Climatch user manual”. The method for the percent score is described in: Howeth, J.G., Gantz, C.A., Angermeier, P.L., Frimpong, E.A., Hoff, M.H., Keller, R.P., Mandrak, N.E., Marchetti, M.P., Olden, J.D., Romagosa, C.M., and Lodge, D.M. (2016). <doi:10.1111/ddi.12391>.
BugReports:	https://github.com/JustinHubbard/Euclimatch/issues
License:	GPL (≥ 3)
Encoding:	UTF-8
Imports:	Rcpp (≥ 1.0-10), foreach, doParallel, RcppParallel, terra, RColorBrewer, grDevices
LinkingTo:	Rcpp
RoxygenNote:	7.2.3
NeedsCompilation:	yes
Packaged:	2024-10-03 14:54:25 UTC; justi
Author:	Justin A. G. Hubbard [aut, cre], D. Andrew R. Drake [aut], Nicholas E. Mandrak [aut]
Maintainer:	Justin A. G. Hubbard <justin.hubbard@mail.utoronto.ca>
Repository:	CRAN
Date/Publication:	2024-10-03 18:00:02 UTC

Run climatch in parallel

Description

Run climatch in parallel

Usage

climatch_par(recipient,

source,

globvar,

biovar = 1:length(globvar),

ncores,

type = "perc",

threshold = 6)

Arguments

Value

"perc" and "mean" returns data.frame of climatch within recipients (rows) for each source represented in columns, "vec" returns data.frame of climatch of a recipient (each column corresponds to grid cell), to sources (corresponding to rows)

Examples

# Dummy data
i1 <- data.frame("clim1" = 1:10, "clim2" = 9:18) # Fake source climate data
i <- list(i1, i1) # list the source dataframes
j1 <- data.frame("clim1" = 11:20, "clim2" = 16:25) # Fake recipient climate data
j <- list(j1, j1) # list the recipient dataframes
variance <- c(60, 80) # Fake global variance

# Climate matching
climatch_par(recipient = j, source = i, globvar = variance, ncores = 1, type = "vec")

Plot or Create SpatRaster of Climatch Data

Description

Create a plot or SpatRaster of climatch values within recipient region.

Usage

climatch_plot(climdat,
                     recipient,
                     source = NULL,
                     climatch = NULL,
                     provide_SpatRaster = FALSE,
                     xlim = terra::ext(recipient)[1:2],
                     ylim = terra::ext(recipient)[3:4],
                     plg = list(title = "Climatch", size=1),
                     xlab = expression(paste("Longitude (",degree,")")),
                     ylab = expression(paste("Latitude (",degree, ")")),
                     ...
                     )

Arguments

Value

A plot of the climatch within the recipient region. A SpatRater if provide_SpatRaster is TRUE.

Examples

r1 <- data.frame()
for(i in 1:100){r1 <- rbind(r1, runif(60))}
rclim1 <- terra::rast(as(r1, "matrix")) #Create the RasterLayer

# Dummy lon lat mimicking species occurrence records
spec_occ <- data.frame("lon" = 1:10, "lat" = 11:20)

# Create dummy polygons
x_coor <- c(1, 5,  10, 8, 3)
y_coor <- c(15, 20,  27, 30, 29)
dum_coor <- cbind(x_coor, y_coor)
dum_poly <- terra::vect(dum_coor, type = "polygon")

# Run and plot the climatch
climatch_plot(recipient = dum_poly, source = spec_occ, climdat = rclim1, xlab = "Lon", ylab = "Lat")

Climatch Summary Score

Description

A summarized climatch score within the recipient region to a source region. Provides the percentage of climate data points in the recipient region equal to or above a specified score (default is 6), or the mean climatch score across the whole recipient region. Note no floor function is used as in Crombie et al. (2008)

Usage

climatch_sum(recipient, source, globvar, type = "perc", threshold = 6)

Arguments

Value

A numeric value, vector or data.frame of the percentage of climatch scores within the recipient region(s) >= a threshold value, or the mean climatch score across the region(s).

References

Predicting invasiveness of species in trade: climate match, trophic guild and fecundity influence establishment and impact of non-native freshwater fishes"<doi:10.1111/ddi.12391>

Examples

i <- as.data.frame(matrix(runif(n=180, min=1, max=20), nrow=60)) # Fake source climate data
j <- as.data.frame(matrix(runif(n=300, min=10, max=40), nrow=100)) # Fake recipient data
variance <- c(600, 800, 450) # Fake global variance

climatch_sum(recipient = j, source = i, globvar = variance, type = "perc", threshold = 6)

Euclidean climatch scores

Description

Vector of the climatch scores within the recipient region

Usage

climatch_vec(recipient, source, globvar)

Arguments

Value

A vector of climatch scores corresponding to each grid cell within recipient region, i.e., each row in the recipient data.frame.

References

Crombie, J., Brown, L., Lizzio, J., & Hood, G. (2008). "Climatch user manual"

Examples

i <- as.data.frame(matrix(runif(n=180, min=1, max=20), nrow=60)) # Fake source climate data
j <- as.data.frame(matrix(runif(n=300, min=10, max=40), nrow=100)) # Fake recipient data
variance <- c(600, 800, 450) # Fake global variance

climatch_vec(recipient = j, source = i, globvar = variance)

Extract Climate Data

Description

Extracts climate data from several types of inputs.

Usage

extract_clim_data(climdat, locations, id = FALSE)

Arguments

Value

A data.frame or list of data.frames of the extracted climate data.

Examples

# Create fake climate data in as a SpatRaster object
r1 <- data.frame()
for(i in 1:100){r1 <- rbind(r1, runif(60))}
rclim1 <- terra::rast(as(r1, "matrix")) #Create the RasterLayer
rclim2 <- c(rclim1, rclim1) # Create the stack

# Dummy lon lat data i.e., species occurrences. Cols must be labelled "lon" and "lat"
# Cols must be labelled "lon" and "lat"
species.occurr <- data.frame("lon" = 1:10, "lat" = 11:20)

# Create dummy polygons
x.coor <- c(1, 5,  10, 8, 3)
y.coor <- c(15, 20,  27, 30, 29)
dummy_coordinates <- cbind(x.coor, y.coor)
dummy_polygon <- terra::vect(dummy_coordinates, type = "polygon")
dummy_polygon2 <- rbind(dummy_polygon, dummy_polygon)

# Extract the dummy data
# Extract dummy lon lat data
extract_clim_data(climdat = rclim2, locations = species.occurr)
# Extract dummy SpatVector with single polygon
extract_clim_data(climdat = rclim2, locations = dummy_polygon2)