This vignette shows you how to calculate abundance and basal area with the functions abundance(), basal_area(), and friends from the forestr package – let’s load it now:
# To install from a private repo, generate a personal access token (PAT) in
# https://github.com/settings/tokens and supply to this argument.
GITHUB_PAT <- "your token"
# install_github("forestgeo/forestr@iss49_demography", auth_token = GITHUB_PAT)
library(forestr)The function abundance() provides a quick way to calculate the abundance of alive stems of each species in each quadrat – that is what it does by default (see abundance()):
stem <- bci12s7mini
n <- abundance(stem)
head(n)
#> quadrat sp n
#> 1 0000 soroaf 1
#> 2 0002 hybapr 1
#> 3 0006 hybapr 2
#> 4 0009 faraoc 1
#> 5 0009 hybapr 1
#> 6 0020 tet2pa 1
# Of course you can change the defaults
head(abundance(stem, "sp", only_alive = FALSE))
#> sp n
#> 1 acaldi 27
#> 2 aegipa 1
#> 3 alchco 11
#> 4 alibed 3
#> 5 allops 1
#> 6 alsebl 36So you can get consistent output, abundance() always returns a dataframe. If what you want is a single number giving the total abundance of alive stems, then you can use abundance_tally().
abundance_tally(stem)
#> [1] 665
abundance_tally(stem, only_alive = FALSE)
#> [1] 2165
# This won't work
fails <- abundance(stem, group_by = NULL)
#> Error in group(x = x, group_by = group_by, only_alive = only_alive): group_by can't be NULL.In R there is always more than one way to get the same result. An alternative is to use dplyr, and instead of passing _“quoted grouping variables”__, you can pass bare grouping variables. No approach is good or bad – the most suitable one depends on the situation
# With forestr you can assign a string of variable names and pass use it later
quoted_vars <- c("quadrat", "sp")
with_forestr <- abundance(stem, quoted_vars))
# Compare
library(dplyr)
alive <- dplyr::filter(stem, status == "A")
# With dplyr you use bare variable names
with_dplyr <- dplyr::count(alive, quadrat, sp)
# You cant reuse grouping variables saved as strings
# (other tricks work but are beyond the scope of this tutorial)
fails <- dplyr::count(alive, quoted_vars)
# This also fails, not but trowing an error but by giving the wrong output
also_fails <- dplyr::count(alive, "quadrat", "sp")
# Whatever you choose, if you do it right you get the same results
alternatives <- list(with_forestr, with_dplyr)
lapply(alternatives, head)
is_var_identical <- function(x, y, var) {identical(x[["var"]], y[["var"]])}
is_var_identical(with_forestr, with_dplyr, "quadrat")
is_var_identical(with_forestr, with_dplyr, "sp")
is_var_identical(with_forestr, with_dplyr, "n")
#> Error: <text>:3:45: unexpected ')'
#> 2: quoted_vars <- c("quadrat", "sp")
#> 3: with_forestr <- abundance(stem, quoted_vars))
#> ^Compared to abundance(), basal_area() behaves very similarly: it provides a quick way to calculate the basal area of alive trees of each species within each quadrat:
stem <- bci12s7mini
ba <- basal_area(stem)
#> Units of returned values are the square of the input units.
head(ba)
#> quadrat sp basal_area
#> 1 0000 soroaf 2642
#> 2 0002 hybapr 95
#> 3 0006 hybapr 475
#> 4 0009 faraoc 1810
#> 5 0009 hybapr 0
#> 6 0020 tet2pa 3117
# Same but silent
silent <- suppressMessages(basal_area(stem))
head(silent)
#> quadrat sp basal_area
#> 1 0000 soroaf 2642
#> 2 0002 hybapr 95
#> 3 0006 hybapr 475
#> 4 0009 faraoc 1810
#> 5 0009 hybapr 0
#> 6 0020 tet2pa 3117Instead if you want the basal area of each individual stem, use basal_area_ind():
ba <- basal_area_ind(stem$dbh)
#> Units of returned values are the square of the input units.
head(ba)
#> [1] 407150 NA NA NA NA NA
# Why NAs?
head(stem$dbh)
#> [1] 720 NA NA NA NA NA
# because `dbh` is na in the data set