How to make rank abundance curve?

[_shy]

How would I go about making rank abundance curves to compare tree species from two different years? I dont have data to share here, but any general code guidance would be very helpful!

[williaml]

Hi, perhaps try goeveg::racurves().

R: Multiple rank-abundance curves (r-project.org)

[_shy]

@williaml thanks. I did see that in my search, but I am having a hard time interpreting what they are describing to make code out of it. Or rather I am not sure where to plug things in to compare the abundance of 15 species (the species are in one column) in two different years...

[williaml]

This is the example dataset that they use: R: Vegetation releves from Scheden (r-project.org)

Your species are in one column, but you could use something like dplyr::pivot_wider() to get them in to many columns so that they're in the same shape.

See also: R: Rank Abundance Curves (r-project.org)

[Matthias]

I was curious what a rank abundance curve is.
It may be of advantage to feed it in into a dedicated package, maybe you want to obtain some other parameters describing or differentiating the curves / populations (see: https://esajournals.onlinelibrary.wiley.com/doi/full/10.1002/ecs2.2881)
However the plot is quite simple, you just need the rank and the abundance (the counts?)

library(tidyverse)

# Calculate values based on the diamonds dataset
rank_abundance = diamonds %>% 
   # count
  count(cut, color, name = "abundance") %>%
   # add ranks within the readout groups (here: cut)
  group_by(cut) %>% 
  mutate(rank = rank(desc(abundance))) %>% 
   # add normalised abundance 
  mutate(norm_abundance = abundance / max(abundance))

# check the outcome
rank_abundance
# A tibble: 35 x 5
# Groups:   cut [5]
   cut   color abundance  rank norm_abundance
   <ord> <ord>     <int> <dbl>          <dbl>
 1 Fair  D           163     6          0.519
 2 Fair  E           224     4          0.713
 3 Fair  F           312     2          0.994
 4 Fair  G           314     1          1    
 5 Fair  H           303     3          0.965
 6 Fair  I           175     5          0.557
 7 Fair  J           119     7          0.379
 8 Good  D           662     5          0.710
 9 Good  E           933     1          1    
10 Good  F           909     2          0.974
# ... with 25 more rows

# plot with total abundance 
ggplot(rank_abundance,
       aes(x = rank,
           y = abundance)) + 
  geom_line() + 
  geom_point(aes(colour = color),
             size = 4) + 
  theme_bw() +
  facet_wrap(~ cut)

# plot with normalised abundance 
ggplot(rank_abundance,
      aes(x = rank,
          y = norm_abundance)) + 
 geom_line() + 
 geom_point(aes(colour = color),
            size = 4) + 
 theme_bw() +
 facet_wrap(~ cut)

# all in one  
ggplot(rank_abundance,
      aes(x = rank,
          y = abundance,
          colour = cut)) + 
 geom_line() + 
 geom_point(size = 7) +
 geom_text(aes(label = color),
            colour = "grey70",
            fontface = "bold") + 
 theme_bw()