## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", eval = TRUE, warning = FALSE, fig.width = 7, fig.height = 4, fig.align='center' ) ## ----------------------------------------------------------------------------- # Load RuHere and terra library(RuHere) library(terra) # Loading the example data data("occurrences", package = "RuHere") ## ----set real directory, echo=FALSE------------------------------------------- dataset_dir <- system.file("extdata", "datasets", package = "RuHere") spp <- unique(occurrences$species) ## ----eval = FALSE------------------------------------------------------------- # # Define a directory for datasets (using a temporary one for this example) # # In a real project, use a persistent path # dataset_dir <- file.path(tempdir(), "datasets") # dir.create(dataset_dir, showWarnings = FALSE) ## ----eval = FALSE------------------------------------------------------------- # # Download WCVP # wcvp_here(data_dir = dataset_dir) # #> trying URL 'https://sftp.kew.org/pub/data-repositories/WCVP/wcvp.zip' # #> Content type 'application/zip' length 105093449 bytes (100.2 MB) # #> ================================================== # #> downloaded 100.2 MB # #> # #> trying URL 'https://zenodo.org/records/17455838/files/wgsrpd.gpkg?download=1' # #> Content type 'application/octet-stream' length 8581120 bytes (8.2 MB) # #> ================================================== # #> downloaded 8.2 MB # #> # #> Please don't forget to cite: # #> # #> Govaerts, R., Nic Lughadha, E. et al. The World Checklist of Vascular Plants, a continuously updated resource for exploring global # #> plant diversity. Sci Data, 8, 215 (2021). https://doi.org/10.1038/s41597-021-00997-6 ## ----eval = FALSE------------------------------------------------------------- # # Set species # spp <- unique(occurrences$species) # spp # #> [1] "Araucaria angustifolia" "Cyanocorax caeruleus" "Handroanthus serratifolius" # # # Download BIEN maps for your species # bien_here(data_dir = dataset_dir, species = spp) # #> species range_available # #> # #> 1: Araucaria angustifolia FALSE # #> 2: Cyanocorax caeruleus FALSE # #> 3: Handroanthus serratifolius TRUE ## ----eval = FALSE------------------------------------------------------------- # # Set your key (do this once) # set_iucn_credentials("YOUR_IUCN_KEY_HERE") ## ----eval = FALSE------------------------------------------------------------- # # Download data for specific species # iucn_here(data_dir = dataset_dir, species = spp) # #> trying URL 'https://zenodo.org/records/17455838/files/wgsrpd.gpkg?download=1' # #> Content type 'application/octet-stream' length 8581120 bytes (8.2 MB) # #> ================================================== # #> downloaded 8.2 MB ## ----eval = FALSE------------------------------------------------------------- # florabr_here(data_dir = dataset_dir, data_version = "latest") # #> Getting data from Flora e Funga do Brasil... # #> Data will be saved in /datasets/florabr # #> # #> Downloading version: 393.421 # #> # #> Merging data. Please wait a moment... # #> # #> Data downloaded and merged successfully. Final data saved in datasets/florabr/393.421/CompleteBrazilianFlora.rds # #> # #> Please don't forget to cite: # #> Trindade WCF (2024). “florabr: An R package to explore and spatialize species distribution using Flora e Funga do # #> Brasil.” Applications in Plant Sciences, e11616. doi:10.1002/aps3.11616 # >>>>>>> Stashed changes ## ----eval = FALSE------------------------------------------------------------- # faunabr_here(data_dir = dataset_dir) # #> Getting data from Taxonomic Catalog of the Brazilian Fauna ... # #> Downloading version: 1.45 # #> # #> Merging data. Please wait a moment... # #> # #> Data will be saved in /datasets/faunabr # #> Data downloaded and merged successfully. Final data saved in datasets/faunabr/1.45/CompleteBrazilianFauna.gz # # #> Please don't forget to cite: # # #> Trindade WCF (2025) faunabr: An R package to explore taxonomic data and map species distributions using the Catálogo Taxonômico da Fauna do Brasil. Zoologia 42: e25027. . ## ----eval = FALSE------------------------------------------------------------- # fs::dir_tree(dataset_dir) # #> datasets # #> ├── bien # #> │ └── Handroanthus_serratifolius.gpkg # #> ├── faunabr # #> │ └── 1.43 # #> │ └── CompleteBrazilianFauna.gz # #> ├── florabr # #> │ └── 393.420 # #> │ └── CompleteBrazilianFlora.rds # #> ├── iucn # #> │ └── iucn_distribution.gz # #> ├── wcvp # #> │ └── wcvp.gz # #> └── wgsrpd # #> └── wgsrpd.gpkg ## ----------------------------------------------------------------------------- # Check availability for our species avail <- available_datasets(data_dir = dataset_dir, species = spp) avail ## ----out.width = "80%"-------------------------------------------------------- # Get available ranges for species avail_ranges <- available_datasets(data_dir = dataset_dir, species = spp, return_distribution = TRUE) # Plot ranges of Araucaria ranges_araucaria <- avail_ranges$species_range$`Araucaria angustifolia` # Save current graphical parameters oldpar <- par(no.readonly = TRUE) # Set the plotting layout (1 row, 3 columns) par(mfrow = c(1, 3)) #Create grid plot(ranges_araucaria$florabr$states_biomes, main = "florabr") plot(ranges_araucaria$iucn, main = "IUCN") plot(ranges_araucaria$wcvp, main = "WCVP") # Restore original graphical parameters par(oldpar) ## ----------------------------------------------------------------------------- # Flag using WCVP-defined range occ <- flag_wcvp(data_dir = dataset_dir, #Directory where dataset was saved occ = occurrences) ## ----------------------------------------------------------------------------- # Number of records flagged (FALSE) for each species table(occ$species, occ$wcvp_flag) ## ----------------------------------------------------------------------------- # Flag using IUCN-defined range occ <- flag_iucn(data_dir = dataset_dir, #Directory where dataset was saved occ = occ) ## ----------------------------------------------------------------------------- # Number of records flagged (FALSE) for each species table(occ$species, occ$iucn_flag) ## ----------------------------------------------------------------------------- # Flag using BIEN-defined range occ <- flag_bien(data_dir = dataset_dir, #Directory where dataset was saved occ = occ) #> Checking the distribution from 1 of 3 species ## ----------------------------------------------------------------------------- # Number of records flagged (FALSE) for each species table(occ$species, occ$bien_flag) ## ----------------------------------------------------------------------------- # Flag using florabr-defined range occ <- flag_florabr(data_dir = dataset_dir, #Directory where dataset was saved occ = occ) ## ----------------------------------------------------------------------------- # Number of records flagged (FALSE) for each species table(occ$species, occ$florabr_flag) ## ----------------------------------------------------------------------------- # Flag using faunabr-defined range occ <- flag_faunabr(data_dir = dataset_dir, #Directory where dataset was saved occ = occ) ## ----------------------------------------------------------------------------- # Number of records flagged (FALSE) for each species table(occ$species, occ$faunabr_flag) ## ----eval=FALSE--------------------------------------------------------------- # # Interactive map with map_here() # map_here(occ, species = "Araucaria angustifolia", label = "record_id", cex = 4) ## ----show mapview, eval=T, echo=F, fig.align='center', out.width='80%'-------- knitr::include_graphics("vignettes_img/IMG03.jpeg") ## ----out.width = "80%"-------------------------------------------------------- ggmap_here(occ, species = "Araucaria angustifolia", facet_wrap = TRUE) ## ----------------------------------------------------------------------------- occ_cleaned <- remove_flagged(occ) ## ----------------------------------------------------------------------------- flag_summary <- summarize_flags(occ) ## ----------------------------------------------------------------------------- # Data.frame summarizing the number of records per flag flag_summary$df_summary ## ----out.width = "80%"-------------------------------------------------------- # Bar plot flag_summary$plot_summary