Computes a summary of species richness and endemism for each ecoregion in the Peruvian mammal backbone.
Usage
pm_ecoregion_summary(sort_by = c("code", "species", "endemic", "label"))Value
A tibble with one row per ecoregion and the following columns:
ecoregion_code– ecoregion abbreviation.ecoregion_label– ecoregion description in Spanish.n_species– total number of species recorded in the ecoregion.n_endemic– number of endemic species recorded in the ecoregion.pct_endemic– percentage of endemic species in the ecoregion.
Details
The summary is based on the long-format table
peru_mammals_ecoregions and joins metadata from
peru_mammals_ecoregions_meta and endemism information
from peru_mammals.
See also
pm_list_ecoregions() for ecoregion metadata,
pm_by_ecoregion() to list species by ecoregion.
Examples
# Get summary for all ecoregions (sorted by code)
pm_ecoregion_summary()
#> # A tibble: 10 × 5
#> ecoregion_code ecoregion_label n_species n_endemic pct_endemic
#> <chr> <chr> <int> <int> <dbl>
#> 1 BPP Bosque Pluvial del Pacífico 69 0 0
#> 2 BSE Bosque Seco Ecuatorial 81 4 4.9
#> 3 COS Costa 66 16 24.2
#> 4 OCE Oceánica 30 0 0
#> 5 PAR Páramo 26 4 15.4
#> 6 PUN Puna 71 14 19.7
#> 7 SB Selva Baja 320 18 5.6
#> 8 SP Sabana de Palmera 83 0 0
#> 9 VOC Vertiente Occidental 72 15 20.8
#> 10 YUN Yungas 256 48 18.8
# Sort by species richness
pm_ecoregion_summary(sort_by = "species")
#> # A tibble: 10 × 5
#> ecoregion_code ecoregion_label n_species n_endemic pct_endemic
#> <chr> <chr> <int> <int> <dbl>
#> 1 SB Selva Baja 320 18 5.6
#> 2 YUN Yungas 256 48 18.8
#> 3 SP Sabana de Palmera 83 0 0
#> 4 BSE Bosque Seco Ecuatorial 81 4 4.9
#> 5 VOC Vertiente Occidental 72 15 20.8
#> 6 PUN Puna 71 14 19.7
#> 7 BPP Bosque Pluvial del Pacífico 69 0 0
#> 8 COS Costa 66 16 24.2
#> 9 OCE Oceánica 30 0 0
#> 10 PAR Páramo 26 4 15.4
# Sort by number of endemic species
pm_ecoregion_summary(sort_by = "endemic")
#> # A tibble: 10 × 5
#> ecoregion_code ecoregion_label n_species n_endemic pct_endemic
#> <chr> <chr> <int> <int> <dbl>
#> 1 YUN Yungas 256 48 18.8
#> 2 SB Selva Baja 320 18 5.6
#> 3 COS Costa 66 16 24.2
#> 4 VOC Vertiente Occidental 72 15 20.8
#> 5 PUN Puna 71 14 19.7
#> 6 BSE Bosque Seco Ecuatorial 81 4 4.9
#> 7 PAR Páramo 26 4 15.4
#> 8 BPP Bosque Pluvial del Pacífico 69 0 0
#> 9 OCE Oceánica 30 0 0
#> 10 SP Sabana de Palmera 83 0 0
# Find ecoregion with highest species richness
eco_summary <- pm_ecoregion_summary(sort_by = "species")
eco_summary[1, ]
#> # A tibble: 1 × 5
#> ecoregion_code ecoregion_label n_species n_endemic pct_endemic
#> <chr> <chr> <int> <int> <dbl>
#> 1 SB Selva Baja 320 18 5.6
# Ecoregions with more than 100 species
eco_summary <- pm_ecoregion_summary()
subset(eco_summary, n_species > 100)
#> # A tibble: 2 × 5
#> ecoregion_code ecoregion_label n_species n_endemic pct_endemic
#> <chr> <chr> <int> <int> <dbl>
#> 1 SB Selva Baja 320 18 5.6
#> 2 YUN Yungas 256 48 18.8
# Compare richness between lowland and highland ecoregions
eco_summary <- pm_ecoregion_summary(sort_by = "species")
lowland <- eco_summary[eco_summary$ecoregion_code %in% c("SB", "SP"), ]
highland <- eco_summary[eco_summary$ecoregion_code %in% c("PUN", "PAR"), ]