In this example we will explore two functions of this package that allow the users to crate species ranges based on trend surface analyses and ecological niche models.
With the rangemap_tsa generates a distributional range for a given species using a trend surface analysis. See the function’s help for more details.
# Data data("occ_f", package = "rangemap") # Defining parameters <- simple_wmap("simple", regions = "Cuba") CU # Now we can create the species range based a tsa # Remember, this is a statistical approach, it may take some time depending on the area <- rangemap_tsa(occurrences = occ_f, region_of_interest = CU, tsa_range cell_size = 2)
Now the figure of our results
The other one with the potential extent of occurrence, the species occurrences and other map details. But let’s first define the characteristics we want in the figure.
par(mar = rep(0, 4)) # optional, reduces the margins of the figure rangemap_plot(tsa_range, add_occurrences = TRUE, polygons = CU, range_color = NA) rangemap_plot(tsa_range, northarrow = TRUE, polygons = CU, legend = TRUE, legend_position = "bottomright")
The function rangemap_enm generates a distributional range for a given species using a continuous raster layer produced with an ecological niche modeling algorithm. See the function’s help for more details.
# parameters <- raster::raster(list.files(system.file("extdata", package = "rangemap"), sp_mod pattern = "sp_model", full.names = TRUE)) data("occ_train", package = "rangemap") <- 1 # threshold 1 to be used thresh <- 5 # threshold 2 to be used thresh1 <- 10 # threshold 3 to be used thresh2 <- TRUE save <- "test" name # Now we can create the species range from the models <- rangemap_enm(occurrences = occ_train, model_output = sp_mod, enm_range threshold_omission = thresh) <- rangemap_enm(occurrences = occ_train, model_output = sp_mod, enm_range1 threshold_omission = thresh1) <- rangemap_enm(occurrences = occ_train, model_output = sp_mod, enm_range2 threshold_omission = thresh2)
Seeing all species ranges based on enms
Using the rangemap_plot function we can produce a nice figure for each of the species ranges. Lets put all the figures together and compare them.
par(mar = rep(0, 4)) rangemap_plot(enm_range, add_occurrences = TRUE, range_color = NA) rangemap_plot(enm_range) rangemap_plot(enm_range1) rangemap_plot(enm_range2)