Description Usage Format See Also Examples
This is an example growth data frame formed from two census data frames which has been updated with spatial data. It starts from growth_ex.
1 |
A sf
spatial tibble
Tree identification number. This identifies an individual tree and can be used to connect trees between the two censuses.
Species of the individual
Code for additional information on the stem during the first census: M means the main stem of the individual tree and R means the stem was lost, but the tag was moved to another stem greater than DBH cutoff, this stands for resprout.
Diameter at breast height of the tree in cm at the first census
Diameter at breast height of the tree in cm at the second census
Average annual growth between the two censuses in cm per year
Codes at the second census
Point location of the individual
A boolean variable for whether the individual is in the buffer region or not
Which cross-validation fold the individual is in
Other example data objects:
blocks_ex
,
census_1_ex
,
census_2008_bw
,
census_2014_bw
,
census_2_ex
,
comp_bayes_lm_ex
,
focal_vs_comp_ex
,
growth_ex
,
growth_toy
,
species_bw
,
study_region_bw
,
study_region_ex
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | library(ggplot2)
library(dplyr)
library(sf)
comp_dist <- 1
ggplot() +
geom_sf(data = growth_spatial_ex, aes(col = buffer), size = 2)
ggplot() +
geom_sf(data = growth_spatial_ex, aes(col = foldID), size = 2)
# Create the focal versus comp data frame
focal_vs_comp_ex <- growth_spatial_ex %>%
mutate(basal_area = 0.0001 * pi * (dbh1 / 2)^2) %>%
create_focal_vs_comp(comp_dist, blocks = blocks_ex, id = "ID", comp_x_var = "basal_area")
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