## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width = 7, fig.height = 6, dpi=100, out.width = "95%" ) ## ----results='hide', message=FALSE, warning=FALSE----------------------------- # Load packages library(kuenm2) library(terra) # Current directory getwd() # Define new directory #setwd("YOUR/DIRECTORY") # uncomment and modify if setting a new directory # Saving original plotting parameters original_par <- par(no.readonly = TRUE) ## ----create model_projections, warning=FALSE, results='hide'------------------ # Import calib_results_maxnet data("fitted_model_maxnet", package = "kuenm2") # Import path to raster files with future variables provided as example # The data is located in the "inst/extdata" folder. in_dir <- system.file("extdata", package = "kuenm2") # Import raster layers (same used to calibrate and fit final models) var <- rast(system.file("extdata", "Current_variables.tif", package = "kuenm2")) # Get soilType soiltype <- var$SoilType # Organize and structure WorldClim files # Create folder to save structured files out_dir_future <- file.path(tempdir(), "Future_raw") # Here, in a temporary directory # Organize organize_future_worldclim(input_dir = in_dir, # Path to the raw variables from WorldClim output_dir = out_dir_future, name_format = "bio_", # Name format static_variables = var$SoilType, # Static variables progress_bar = FALSE, overwrite = TRUE) # Create a "Current_raw" folder in a temporary directory # and copy the rawvariables there. out_dir_current <- file.path(tempdir(), "Current_raw") dir.create(out_dir_current, recursive = TRUE) # Save current variables in temporary directory terra::writeRaster(var, file.path(out_dir_current, "Variables.tif"), overwrite = TRUE) # Prepare projections using fitted models to check variables pr <- prepare_projection(models = fitted_model_maxnet, present_dir = out_dir_current, # Directory with present-day variables future_dir = out_dir_future, # Directory with future variables future_period = c("2041-2060", "2081-2100"), future_pscen = c("ssp126", "ssp585"), future_gcm = c("ACCESS-CM2", "MIROC6")) # Project selected models to multiple scenarios ## Create a folder to save projection results # Here, in a temporary directory out_dir <- file.path(tempdir(), "Projection_results/maxnet") dir.create(out_dir, recursive = TRUE) ## Project selected models to multiple scenarios p <- project_selected(models = fitted_model_maxnet, projection_data = pr, out_dir = out_dir, write_replicates = TRUE, progress_bar = FALSE, # Do not print progress bar overwrite = TRUE) ## ----compute variance--------------------------------------------------------- # Create a directory to save results v <- projection_variability(model_projections = p, write_files = TRUE, output_dir = out_dir, verbose = FALSE, overwrite = TRUE) ## ----plot variability present, fig.width = 7, fig.height = 4------------------ # Variability for the present terra::plot(v$Present, range = c(0, 0.15)) ## ----plot variability future-------------------------------------------------- # Variability for Future_2081-2100_ssp585 terra::plot(v$`Future_2081-2100_ssp585`, range = c(0, 0.1)) ## ----root_directory, eval = FALSE--------------------------------------------- # # See the folder where the results were saved # v$root_directory # #> [1] "Temp/Projection_results/maxnet/variance" ## ----import variability_projections------------------------------------------- # Importing results v_2041_2060_ssp126 <- import_results(projection = v, present = FALSE, # Do not import results from the present time future_period = "2041-2060", future_pscen = "ssp126") # Plot terra::plot(v_2041_2060_ssp126, range = c(0, 0.1)) ## ----save raster variability, eval = FALSE------------------------------------ # writeRaster(v$`Future_2081-2100_ssp585`, # file.path(out_dir, "Future_2081-2100_ssp585.tif")) ## ----read variability projection---------------------------------------------- v <- readRDS(file.path(out_dir, "variance/variability_projections.rds")) ## ----see maximum temp--------------------------------------------------------- max(fitted_model_maxnet$calibration_data$bio_1) ## ----Highlight non-analogous-------------------------------------------------- # Import variables from the 2081-2100 period (SSP585, GCM MIROC6) future_ACCESS_CM2 <- rast(file.path(out_dir_future, "2081-2100/ssp585/ACCESS-CM2/Variables.tif")) # Range of values in bio_1 terra::minmax(future_ACCESS_CM2$bio_1) # Plot terra::plot(future_ACCESS_CM2$bio_1, breaks = c(-Inf, 22.7, Inf)) # Highlight regions with values above 22.7ºC ## ----perform mop-------------------------------------------------------------- # Create a folder to save MOP results out_dir_mop <- file.path(tempdir(), "MOPresults") dir.create(out_dir_mop, recursive = TRUE) # Run MOP kmop <- projection_mop(data = fitted_model_maxnet, projection_data = pr, subset_variables = TRUE, calculate_distance = TRUE, out_dir = out_dir_mop, type = "detailed", overwrite = TRUE, progress_bar = FALSE) ## ----import mop, warning=FALSE------------------------------------------------ # Import results from MOP runs mop_ssp585_2100 <- import_results(projection = kmop, future_period = "2081-2100", future_pscen = "ssp585") # See types of results names(mop_ssp585_2100) ## ----plot distance------------------------------------------------------------ terra::plot(mop_ssp585_2100$distances) ## ----plot basic--------------------------------------------------------------- terra::plot(mop_ssp585_2100$basic) ## ----plot simple-------------------------------------------------------------- terra::plot(mop_ssp585_2100$simple) ## ----plot towards end--------------------------------------------------------- # Non-analogous conditions towards high values in the ACCESS-CM2 scenario terra::plot(mop_ssp585_2100$towards_high_end$`Future_2081-2100_ssp585_ACCESS-CM2`) # Non-analogous conditions towards low values in the MIROC6 scenario terra::plot(mop_ssp585_2100$towards_low_end$`Future_2081-2100_ssp585_ACCESS-CM2`, main = names(mop_ssp585_2100$towards_low_end$`Future_2081-2100_ssp585_ACCESS-CM2`)) ## ----plot towars combined----------------------------------------------------- # Variables with conditions above training range terra::plot(mop_ssp585_2100$towards_high_combined) # Variables with conditions below training range terra::plot(mop_ssp585_2100$towards_low_combined) ## ----mop zero----------------------------------------------------------------- # Create a folder to save MOP results, now assigning 0 to cells within the range out_dir_mop_zero <- file.path(tempdir(), "MOPresults_zero") dir.create(out_dir_mop_zero, recursive = TRUE) # Run MOP kmop_zero <- projection_mop(data = fitted_model_maxnet, projection_data = pr, subset_variables = TRUE, na_in_range = FALSE, # Assign 0 to cells within range calculate_distance = TRUE, out_dir = out_dir_mop_zero, type = "detailed", overwrite = TRUE, progress_bar = FALSE) ## ----check difference zero mop, fig.width = 7, fig.height = 4----------------- # Import MOP for the scenario ssp585 in 2081-2100 mop_ssp585_2100_zero <- import_results(projection = kmop_zero, future_period = "2081-2100", future_pscen = "ssp585") # Compare with the MOP that assigns NA to cells within the calibration range # Simple MOP terra::plot(c(mop_ssp585_2100$simple$`Future_2081-2100_ssp585_ACCESS-CM2`, mop_ssp585_2100_zero$simple$`Future_2081-2100_ssp585_ACCESS-CM2`), main = c("Within range as NA", "Within range as 0")) # Detailed MOP terra::plot(c(mop_ssp585_2100$towards_high_combined$`Future_2081-2100_ssp585_ACCESS-CM2`, mop_ssp585_2100_zero$towards_high_combined$`Future_2081-2100_ssp585_ACCESS-CM2`), main = c("Within range as NA", "Within range as 0"), plg=list(cex=0.6)) ## ----plot towards high values------------------------------------------------- # Non-analogous conditions towards high values in the ACCESS-CM2 scenario terra::plot(mop_ssp585_2100$towards_high_combined$`Future_2081-2100_ssp585_ACCESS-CM2`) ## ----response curves towards high, fig.height=3.8----------------------------- # Plotting response curves to check extrapolation towards the high end of variables par(mfrow = c(1,3)) # Set plot grid response_curve(models = fitted_model_maxnet, variable = "bio_1", new_data = future_ACCESS_CM2) response_curve(models = fitted_model_maxnet, variable = "bio_12", new_data = future_ACCESS_CM2) response_curve(models = fitted_model_maxnet, variable = "bio_15", new_data = future_ACCESS_CM2) ## ----plot towards low values, fig.width = 7, fig.height = 4------------------- # Non-analogous conditions towards low values in the ACCESS-CM2 scenario par(mfrow = c(1, 2)) # Set grid terra::plot(mop_ssp585_2100$towards_low_combined$`Future_2081-2100_ssp585_ACCESS-CM2`) ## It's bio 7. Plot response curve: response_curve(models = fitted_model_maxnet, variable = "bio_7", new_data = future_ACCESS_CM2) ## ----par_reset---------------------------------------------------------------- # Reset plotting parameters par(original_par) ## ----save mop rds------------------------------------------------------------- # Check for RDS files in the directory where we saved the MOP results list.files(path = out_dir_mop, pattern = "rds") # Import the mop_projections file kmop <- readRDS(file.path(out_dir_mop, "mop_projections.rds"))