Installation will require the pre-release version of fgeo.abundance:
# install.packages("devtools")
devtools::install_github("forestgeo/fgeo.abundance@pre-release")Or simply install the development version of fgeo.abundance:
# install.packages("devtools")
devtools::install_github("forestgeo/fgeo.abundance")Or install all fgeo packages in one step by using the following link: (https://forestgeo.github.io/fgeo/index.html#installation)
For details on how to install packages from GitHub, visit the following website to review their article: (https://goo.gl/dQKEeg)
library(dplyr)
library(fgeo.tool)
library(fgeo.abundance)
If the trees HAVE buttresses your data may have multiple stems per treeid and even multiple measures per stemid.
# Trees with buttresses may have multiple measurements of a single stem.
# Main stems will always have highest `HOM`, then largest `DBH`.
vft <- tribble(
~CensusID, ~TreeID, ~StemID, ~DBH, ~HOM,
1, "1", "1.1", 88, 130,
1, "1", "1.1", 10, 160, # Main stem
1, "2", "2.1", 20, 130,
1, "2", "2.2", 30, 130, # Main stem
)
Fundamentally, abundance() counts the number of rows. All of these results are the same:
nrow(vft)
dplyr::count(vft)
dplyr::summarize(vft, n = n())
abundance(vft)
The result isn’t always likely what you expect, instead it would look more like:
summarize(vft, n = n_distinct(TreeID))
As shown above, you can get a correct result by combining summarize() and n_distinct() (from the dplyr package). The function abundance() on the other hand includes some useful additional features (see ?abundance()). This code more clearly conveys your intention, i.e. to calculate tree abundance by counting the number of main stems:
(main_stems <- pick_main_stem(vft))
abundance(main_stems)
If you have data from multiple censuses, you can compute by census (or any other group).
vft2 <- tibble::tribble(
~CensusID, ~TreeID, ~StemID, ~DBH, ~HOM,
1, "1", "1.1", 10, 130,
1, "1", "1.2", 20, 130, # Main stem
2, "1", "1.1", 12, 130,
2, "1", "1.2", 22, 130 # Main stem
)
by_census <- group_by(vft2, CensusID)
(main_stems_by_census <- pick_main_stem(by_census))
abundance(main_stems_by_census)
Often you will need to first subset data (e.g. by status or DBH) and then count.
over20 <- filter(main_stems_by_census, DBH > 20)
abundance(over20)
If trees have buttresses, you may need to pick the main stemid of each stem, so you don't count the same stem more than once.
vft3 <- tribble(
~CensusID, ~TreeID, ~StemID, ~DBH, ~HOM,
1, "1", "1.1", 88, 130,
1, "1", "1.1", 10, 160, # Main stem
1, "2", "2.1", 20, 130,
1, "2", "2.2", 30, 130, # Main stem
2, "1", "1.1", 98, 130,
2, "1", "1.1", 20, 160, # Main stem
2, "2", "2.1", 30, 130,
2, "2", "2.2", 40, 130, # Main stem
)
(main_stemids <- pick_main_stemid(vft3))
main_stemids
basal_area(main_stemids)
basal_area() also allows you to compute by groups.
by_census <- group_by(main_stemids, CensusID)
basal_area(by_census)
However if you want to compute on a subset of data, you need to first pick the data.
ten_to_twenty <- filter(by_census, DBH >= 10, DBH <= 20)
ba <- basal_area(ten_to_twenty)
ba
And if you need to convert units, you can do so after the fact with fgeo.tool::convert_unit_at().
convert_unit_at(ba, .at = "basal_area", from = "mm2", to = "hectare")
Example data.
vft <- example_byyr
vft
Abundance by year.
abundance_byyr(vft, DBH >= 10, DBH < 20)
abundance_byyr(vft, DBH >= 10)
Basal area by year.
basal <- basal_area_byyr(vft, DBH >= 10)
basal
# Convert units and standardize by plot size in hectares
years <- c("yr_2001", "yr_2002")
in_he <- convert_unit_at(basal, .at = years, from = "mm2", to = "hectare")
standardize_at(in_he, .at = years, denominator = 50)
To get started visit the following link: (https://forestgeo.github.io/fgeo/articles/fgeo.html)