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Create a speciation-area relationship plot (SpAR)

Source: R/create_spar.R
create_SpAR.Rd

Use segmented regression to create a speciation-area relationship plot. The X axis represents log(island area) and the Y axis represents log(speciation rate)

Usage

create_spar(occurrences, npsi = 1, visualize = FALSE)

create_SpAR(occurrences, npsi = 1, visualize = FALSE)

Arguments

occurrences

The dataframe output by one of ssarp's speciation methods (ssarp::estimate_bamm(), ssarp::estimate_dr(), ssarp::estimate_ms()), or if using a custom dataframe, ensure that it has the following columns: areas, rate

npsi

The maximum number of breakpoints to estimate for model selection. Default: 1

visualize

(boolean) Whether the plot should be displayed when the function is called. Default: FALSE

Value

A list of class SAR with 5 items including:

  • summary: the summary output

  • segObj or linObj: the regression object (segObj when segmented, linObj when linear)

  • aggDF: the aggregated dataframe used to create the plot

  • AICscores: the AIC scores generated during model selection

  • AllModels: a list of models created in model selection, labeled by number of breakpoints

Details

If the user would prefer to create their own plot of the ssarp::create_spar() output, the aggDF element of the returned list includes the raw points from the plot created here. They can be accessed as demonstrated in the Examples section.

More information about the three methods for estimating speciation rate included in ssarp can be found in ssarp's SpAR vignette.

Examples

# The GBIF key for the Anolis genus is 8782549
# Read in example dataset filtered from:
#  dat <- rgbif::occ_search(taxonKey = 8782549,
#                           hasCoordinate = TRUE,
#                           limit = 10000)
dat <- read.csv(system.file("extdata",
                            "ssarp_Example_Dat.csv",
                            package = "ssarp"))
land <- find_land(occurrences = dat)
areas <- find_areas(occs = land)
#> ℹ Recording island names...
#> ℹ Assembling island dictionary...
#> ℹ Adding areas to final dataframe...

# Read tree from Patton et al. (2021), trimmed to Caribbean species
tree <- ape::read.tree(system.file("extdata",
                                   "Patton_Anolis_Trimmed.tree",
                                   package = "ssarp"))

occ_speciation <- estimate_ms(tree = tree,
                              label_type = "epithet",
                              occurrences = areas)

seg <- create_spar(occurrences = occ_speciation,
                   npsi = 1,
                   visualize = FALSE)
plot(seg)

summary <- seg$summary
model_object <- seg$segObj
points <- seg$aggDF