Preparation of data for model projections

This function prepared data for model projections to multiple scenarios, storing the paths to the rasters representing each scenario.

Usage

prepare_projection(models = NULL, variable_names = NULL, present_dir = NULL,
                   past_dir = NULL, past_period = NULL, past_gcm = NULL,
                   future_dir = NULL, future_period = NULL,
                   future_pscen = NULL, future_gcm = NULL,
                   write_file = FALSE, filename = NULL,
                   raster_pattern = ".tif*")

Arguments

models: an object of class fitted_models returned by the fit_selected() function. Default is NULL.
variable_names: (character) names of the variables used to fit the model or do the PCA in the prepare_data() function. Only applicable if models argument is not provided. Default is NULL.
present_dir: (character) path to the folder containing variables that represent the current scenario for projection. Default is NULL.
past_dir: (character) path to the folder containing subfolders with v ariables representing past scenarios for projection. Default is NULL.
past_period: (character) names of the subfolders within past_dir, representing specific time periods (e.g., 'LGM' or 'MID').
past_gcm: (character) names of the subfolders within past_period folders, representing specific General Circulation Models (GCMs).
future_dir: (character) path to the folder containing subfolders with variables representing future scenarios for projection. Default is NULL.
future_period: (character) names of the subfolders within future_dir, representing specific time periods (e.g., '2041-2060' or '2081-2100'). Default is NULL.
future_pscen: (character) names of the subfolders within future_period, representing specific emission scenarios (e.g., 'ssp126' or 'ssp585'). Default is NULL.
future_gcm: (character) names of the subfolders within future_pscen folders, representing specific General Circulation Models (GCMs). Default is NULL.
write_file: (logical) whether to write the object containing the paths to the structured folders. This object is required for projecting models across multiple scenarios using the project_selected() function. Default is FALSE.
filename: (character) the path or name of the folder where the object will be saved. This is only applicable if write_file = TRUE. Default is NULL.
raster_pattern: (character) pattern used to identify the format of raster files within the folders. Default is ".tif*".

Value

An object of class prepared_projection containing the following elements:

Present, Past, and Future: paths to the variables structured in subfolders.
Raster_pattern: the pattern used to identify the format of raster files within the folders.
PCA: if a principal component analysis (PCA) was performed on the set of variables with prepare_data(), a list with class "prcomp" will be returned. See ?stats::prcomp() for details.
variables: names of the raw predictos variables used to project.

Examples

# Import example of fitted_models (output of fit_selected())
data("fitted_model_maxnet", package = "kuenm2")

# Organize and structure future climate variables from WorldClim
# Import the current variables used to fit the model.
# In this case, SoilType will be treated as a static variable (constant
# across future scenarios).
var <- terra::rast(system.file("extdata", "Current_variables.tif",
                               package = "kuenm2"))

# Create a "Current_raw" folder in a temporary directory and copy the raw
# variables there.
out_dir_current <- file.path(tempdir(), "Current_raw")
dir.create(out_dir_current, recursive = TRUE)

# Save current variables in temporary directory
terra::writeRaster(var, file.path(out_dir_current, "Variables.tif"))

# Set the input directory containing the raw future climate variables.
# For this example, the data is located in the "inst/extdata" folder.
in_dir <- system.file("extdata", package = "kuenm2")

# Create a "Future_raw" folder in a temporary directory and copy the raw
# variables there.
out_dir_future <- file.path(tempdir(), "Future_raw")

# Organize and rename the future climate data, structuring it by year and GCM.
# The 'SoilType' variable will be appended as a static variable in each scenario.
# The files will be renamed following the "bio_" format
organize_future_worldclim(input_dir = in_dir,
                          output_dir = out_dir_future,
                          name_format = "bio_", variables = NULL,
                          fixed_variables = var$SoilType, mask = NULL,
                          overwrite = TRUE)
#> 
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#> 
#> Variables successfully organized in directory:
#> /tmp/RtmppZ1hZC/Future_raw

# Prepare projections using fitted models to check variables
pr <- prepare_projection(models = fitted_model_maxnet,
                         present_dir = out_dir_current,
                         past_dir = NULL,
                         past_period = NULL,
                         past_gcm = NULL,
                         future_dir = out_dir_future,
                         future_period = c("2041-2060", "2081-2100"),
                         future_pscen = c("ssp126", "ssp585"),
                         future_gcm = c("ACCESS-CM2", "MIROC6"),
                         write_file = FALSE,
                         filename = NULL,
                         raster_pattern = ".tif*")
pr
#> projection_data object summary
#> =============================
#> Variables prepared to project models for Present and Future 
#> Future projections contain the following periods, scenarios and GCMs:
#>   - Periods: 2041-2060 | 2081-2100 
#>   - Scenarios: ssp126 | ssp585 
#>   - GCMs: ACCESS-CM2 | MIROC6 
#> All variables are located in the following root directory:
#> /tmp/RtmppZ1hZC

# Prepare projections using variables names
pr_b <- prepare_projection(models = NULL,
                           variable_names = c("bio_1", "bio_7", "bio_12"),
                           present_dir = out_dir_current,
                           past_dir = NULL,
                           past_period = NULL,
                           past_gcm = NULL,
                           future_dir = out_dir_future,
                           future_period = c("2041-2060", "2081-2100"),
                           future_pscen = c("ssp126", "ssp585"),
                           future_gcm = c("ACCESS-CM2", "MIROC6"),
                           write_file = FALSE,
                           filename = NULL,
                           raster_pattern = ".tif*")
pr_b
#> projection_data object summary
#> =============================
#> Variables prepared to project models for Present and Future 
#> Future projections contain the following periods, scenarios and GCMs:
#>   - Periods: 2041-2060 | 2081-2100 
#>   - Scenarios: ssp126 | ssp585 
#>   - GCMs: ACCESS-CM2 | MIROC6 
#> All variables are located in the following root directory:
#> /tmp/RtmppZ1hZC

Usage

Arguments

Value

See also

Examples