After generating the Area of Habitat data, we can import them.
# import the Area of Habitat data
@@ -274,7 +274,7 @@ Tutorial strip.text = element_text(color = "white"),
strip.background = element_rect(fill = "black", color = "black")
)
## |---------|---------|---------|---------|========================================= |---------|---------|---------|---------|========================================= ## |---------|---------|---------|---------|=========================================
# display maps
print(map)Can I use habitat classification data from other data sources?
-Yes, you can use habitat classification data from a variety of sources. For example, the habitat classification data could be derived from Copernicus Corine Land Cover, and MODIS Land Cover data (MCD12Q1)). To use such data, you will also need to develop a crosswalk table to specify which land cover (or habitat) classes correspond to which habitat classes as defined by the IUCN Red List Habitat Classification Scheme (e.g., see Tracewski et al. 2016; Lumbierres et al. 2021). After preparing the habitat classification data and the crosswalk table, they can be used to create Area of Habitat data (via create_spp_aoh_data()). For more information, see the Customization vignette.
Yes, you can use habitat classification data from a variety of sources. For example, the habitat classification data could be derived from Copernicus Corine Land Cover, and MODIS Land Cover data (MCD12Q1)). To use such data, you will also need to develop a crosswalk table to specify which land cover (or habitat) classes correspond to which habitat classes as defined by the IUCN Red List Habitat Classification Scheme (e.g., see Tracewski et al. 2016; Lumbierres et al. 2021). After preparing the habitat classification data and the crosswalk table, they can be used to create Area of Habitat data (via create_spp_aoh_data()). For more information, see the Customization vignette.
The output Area of Habitat data have different spatial extents, how can I combine them together?
diff --git a/docs/search.json b/docs/search.json index b64c14c..f9045d2 100644 --- a/docs/search.json +++ b/docs/search.json @@ -1 +1 @@ -[{"path":"https://prioritizr.github.io/aoh/articles/aoh.html","id":"introduction","dir":"Articles","previous_headings":"","what":"Introduction","title":"Getting started","text":"Area Habitat (AOH) maps aim delineate spatial distribution suitable habitat species (Brooks et al. 2019). used assess performance protected area systems, measure impacts threats biodiversity, identify priorities conservation actions (Tracewski et al. 2016; Rondinini et al. 2005; Durán et al. 2020). maps generally produced obtaining geographic range data species, removing areas contain suitable habitat occur outside known elevational limits species (Brooks et al. 2019). help make maps accessible, aoh R package provides routines automatically creating Area Habitat data based International Union Conservation Nature (IUCN) Red List Threatened Species. manually downloading species range data IUCN Red List, users can import (using read_spp_range_data()), prepare collate additional information subsequent processing (using create_spp_info_data()), create Area Habitat data (using create_spp_aoh_data()). Global elevation habitat classification data automatically downloaded (Robinson et al. 2014; Jung et al. 2020; Lumbierres et al. 2021), data species’ habitat preferences elevational limits obtained automatically using IUCN Red List API. Since accessing IUCN Red List requires token, users may need obtain token update R configuration recognize token (see README details).","code":""},{"path":"https://prioritizr.github.io/aoh/articles/aoh.html","id":"tutorial","dir":"Articles","previous_headings":"","what":"Tutorial","title":"Getting started","text":"provide tutorial using aoh R package. tutorial, generate Area Habitat data following Iberian species: Pyrenean brook salamander (Calotriton asper), Iberian frog (Rana iberica), western spadefoot toad (Pelobates cultripes), golden striped salamnader (Chioglossa lusitanica). start , load package. also load rappdirs R package cache data, terra ggplot2 R packages visualize results. Now import range data species. Although users typically obtain range data International Union Conservation Nature (IUCN) Red List Threatened Species, use built-species range data distributed package convenience. Please note data obtained IUCN Red List, manually generated using occurrence records Global Biodiversity Information Facility. Next, prepare range data generating Area Habitat data. procedure – addition repairing geometry issues spatial data – obtain information species’ habitat preferences elevational limits (via IUCN Red List Threatened Species). also specify folder cache downloaded data won’t need re-download subsequent runs. can now generate Area Habitat data species. default, data generated using elevation data derived Robinson et al. (2014) habitat data derived Lumbierres et al. (2021). Similar , also specify folder cache downloaded datasets won’t need re-downloaded subsequent runs. running code, see displayed message telling us certain habitat classes available (.e., \"7.1\", \"7.2\"). fine. error. reason see message although global habitat dataset contains majority IUCN habitat classes terrestrial environments, contain every single IUCN habitat class (see Lumbierres et al. 2021 details). Upon checking IUCN habitat classes, can see classes correspond artificial aquatic areas also caves subterranean environments. Although failing account habitats potentially issue, assume accounting species’ non-subterranean habitats sufficient describe spatial distribution (Ficetola et al. 2014). generating Area Habitat data, can import . can see Area Habitat data species stored separate spatial (raster) datasets different extents. Although useful drastically reduces total size data species, can make difficult work data multiple species. address , can use terra_combine() function automatically align combine spatial data species’ distributions single spatial dataset. Finally, let’s create maps compare range data Area habitat data. Although create maps manually (e.g., using ggplot2 R package), use plotting function distributed aoh R package convenience.","code":"# load packages library(aoh) library(terra) library(rappdirs) library(ggplot2) # find file path for data path <- system.file(\"extdata\", \"EXAMPLE_SPECIES.zip\", package = \"aoh\") # import data spp_range_data <- read_spp_range_data(path) # preview data print(spp_range_data) ## Simple feature collection with 4 features and 26 fields ## Geometry type: POLYGON ## Dimension: XY ## Bounding box: xmin: -9.479736 ymin: 36.59422 xmax: 3.302702 ymax: 43.76455 ## Geodetic CRS: WGS 84 ## # A tibble: 4 × 27 ## id_no binomial presence origin seasonal compiler yrcompiled citation ##