---
title: "Montane Tree Species of the Tropical Andes"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{"Montane Tree Species of the Tropical Andes"}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

```{r setup}
library(mtsta)
```

- Summary of results of this regional Red List report:

```{r echo=FALSE}
summ_df <- tibble::tribble(
     ~Conservation.status, ~tag, ~Number.of.species,
  "Critically Endangered", "CR",                 1L,
             "Endangered", "EN",                42L,
             "Vulnerable", "VU",                27L,
        "Near Threatened", "NT",                20L,
          "Least Concern", "LC",                29L,
         "Data Deficient", "DD",                 8L,
          "Not Evaluated", "NE",                 0L
  )

summ_df |> 
  dplyr::select(1,3) |> 
  janitor::adorn_totals() |> 
  knitr::kable()
```

- Number of endemic tree species by country in the tropical Andes.

(Calderón et al. 2002; IUCN 2010; León-Yánez et al. 2011; León et al. 2006; Llamozas et al. 2003; Meneses and Beck 2005).


```{r summary_2, echo=FALSE, fig.align='center'}
summ_2 <- tibble::tribble(
               ~Country, ~CR,  ~EN,  ~VU, ~NT, ~LC, ~DD, ~Subtotal,  ~NE, ~Total,
              "Ecuador",  2L,  36L,  52L,  9L,  5L,  1L,      105L,  61L,   166L,
                 "Peru",  9L,  31L,  15L,  2L,  3L, 10L,       70L,  50L,   120L,
             "Colombia",  4L,   5L,   5L,  2L,  1L,  0L,       17L,  60L,    77L,
              "Bolivia",  0L,   5L,   1L,  0L,  0L,  1L,        7L,  94L,   101L,
            "Argentina",  0L,   0L,   0L,  0L,  0L,  0L,        0L,   3L,     3L,
            "Venezuela",  0L,   0L,   0L,  0L,  0L,  0L,        0L,   0L,     0L,
        "Total endemic", 15L,  77L,  73L, 13L,  9L, 12L,      199L, 268L,   467L,
  "Regional assessment",  1L,  42L,  27L, 20L, 29L,  8L,      127L,   0L,   127L,
          "Total Andes", 16L, 119L, 100L, 33L, 38L, 20L,      326L, 268L,   594L
  )

summ_2 |> 
  knitr::kable()
```


- Number of species per country that were evaluated

```{r echo=FALSE}
summarie_3 <- mtsta::mtsta_distribution |> 
  dplyr::select(accepted_name, distribution) |> 
  dplyr::mutate(distribution = dplyr::case_when(
    stringr::str_detect(distribution, "\\(Bolivia,\\) ") ~ stringr::str_remove(distribution, "\\(Bolivia,\\) "),
    stringr::str_detect(distribution, "\\(Colombia,\\) ") ~ stringr::str_remove(distribution, "\\(Colombia,\\) "),
    stringr::str_detect(distribution, "\\(Colombia\\) \\- ") ~ stringr::str_remove(distribution, "\\(Colombia\\) \\- "),
    stringr::str_detect(distribution, " \\- \\(Peru \\- Venezuela\\)") ~ stringr::str_remove(distribution, " \\- \\(Peru \\- Venezuela\\)"),
    TRUE ~ distribution
  )) |> 
  tidyr::separate_rows(distribution, sep = " - ") |> 
  dplyr::group_by(distribution) |> 
  dplyr::summarise(n_species = dplyr::n_distinct(accepted_name))
```

```{r echo=FALSE, fig.height=5, fig.width= 8}
summarie_3 |> 
  ggplot2::ggplot(ggplot2::aes(forcats::fct_reorder(distribution, n_species, .desc = TRUE),
                               n_species)) +
  ggplot2::geom_col() +
  ggplot2::labs(y = "Species per country",
                x = "Countries") +
  ggplot2::theme_bw()

```

The distribution of the 127 species across countries.