occfilt_select: Select filtered occurrences

In sjevelazco/flexsdm: Tools for Data Preparation, Fitting, Prediction, Evaluation, and Post-Processing of Species Distribution Models

Select filtered occurrences

Description

Select filtered occurrences based on number of records and spatial autocorrelation (see details)

Usage

occfilt_select(occ_list, x, y, env_layer, filter_prop = FALSE)

Arguments

occ_list	list. A list with filtered specie occurrences testing several values (see occfilt_env and occfilt_geo)
x	character. Column name with longitude data
y	character. Column name with latitude data
env_layer	SpatRaster. Raster variables that will be used to fit the model. Factor variables will be removed.
filter_prop	logical. If TRUE, the function will return a list with the filtered occurrences and a tibble with the spatial autocorrelation and number of occurrence values

Details

The function implement the approach used in Velazco et al. (2020) which consists in calculating for each filtered dataset:

• 1- the number of occurrence.

• 2- the spatial autocorrelation based on Morans'I for each variable

• 3- the mean spatial autocorrelation among variables

Then function will select those dataset with average spatial autocorrelation lower than the mean of all dataset, and from this subset will select the one with the highest number occurrences.

If use occfilt_select cite Velazco et al. (2020) as reference.

Value

If filter_prop = FALSE, a tibble with selected filtered occurrences. If filter_prop = TRUE, a list with following objects:

• A tibble with selected filtered occurrences

• A tibble with filter properties with columns:

  • filt_value: values used for filtering, the value with an asterisk will denote the one selected

  • n_records: number of occurrence

  • mean_autocorr: mean spatial autocorrelation.

  • the remaining columns have the spatial autocorrelation values for each variable.

References

• Velazco, S. J. E., Svenning, J-C., Ribeiro, B. R., & Laureto, L. M. O. (2020). On opportunities and threats to conserve the phylogenetic diversity of Neotropical palms. Diversity and Distributions, 27, 512–523. https://doi.org/10.1111/ddi.13215

See Also

occfilt_env, occfilt_geo

Examples

## Not run: 
require(terra)
require(dplyr)

# Environmental variables
somevar <- system.file("external/somevar.tif", package = "flexsdm")
somevar <- terra::rast(somevar)

plot(somevar)

# Species occurrences
data("spp")
spp
spp1 <- spp %>% dplyr::filter(species == "sp1", pr_ab == 1)

## %######################################################%##
####                  Cellsize method                   ####
## %######################################################%##
# Using cellsize method
filtered_occ <- occfilt_geo(
  data = spp1,
  x = "x",
  y = "y",
  env_layer = somevar,
  method = c("cellsize", factor = c(1, 4, 8, 12, 16, 20)),
  prj = crs(somevar)
)

filtered_occ

# Select filtered occurrences based on
# number of records and spatial autocorrelation
occ_selected <- occfilt_select(
  occ_list = filtered_occ,
  x = "x",
  y = "y",
  env_layer = somevar,
  filter_prop = FALSE
)
occ_selected

occ_selected <- occfilt_select(
  occ_list = filtered_occ,
  x = "x",
  y = "y",
  env_layer = somevar,
  filter_prop = TRUE
)
occ_selected$occ

occ_selected$filter_prop

## End(Not run)

sjevelazco/flexsdm documentation built on Feb. 28, 2025, 9:07 a.m.