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The standrecon R package was created to summarize
reference historical stand conditions by total basal area and tree
density using contemporary field data.
The package implements a workflow for forest stand reconstruction using tree mortality information derived from decay classes and species-specific growth rates, following approaches described in the forest ecology literature.
Data sets using standard species codes (such as PIPO or PSME) can use built-in bark correction equations; custom equations may be supplied for other species.
You can install standrecon from CRAN with
install.packages("standrecon")Alternatively, can install the development version of standrecon from GitHub with:
# install.packages("pak")
pak::pak("kriggithub/standrecon")The example below demonstrates how to reconstruct forest stand basal area and stem density at historical reference years using tree-level inventory data.
library(standrecon)
# Load example data included with the package
data(standrecon_example_data)
# Species-specific average radial growth (mm/year)
avg_inc <- c(
PIEN = 0.5,
ABBI = 0.3,
PIPO = 0.4
)
# Reconstruct stand conditions
out <- standrecon(
data = standrecon_example_data,
meas_year = 2025,
ref_year = c(1950, 1975),
avg_inc_vec = avg_inc,
plot_size = 1000
)
# View the first few rows of output (percentiles for sensitivity analysis)
head(out)
#> type year percentile species basal_area stem_density
#> 1 reconstructed 1950 0.25 ABBI 26.92181 530
#> 2 reconstructed 1950 0.25 PIEN 30.76367 730
#> 3 reconstructed 1950 0.25 PIPO 18.15475 310
#> 4 reconstructed 1950 0.50 ABBI 26.26240 520
#> 5 reconstructed 1950 0.50 PIEN 29.70578 730
#> 6 reconstructed 1950 0.50 PIPO 17.41799 310These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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