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forestecology (version 0.2.0)

Fitting and Assessing Neighborhood Models of the Effect of Interspecific Competition on the Growth of Trees

Description

Code for fitting and assessing models for the growth of trees. In particular for the Bayesian neighborhood competition linear regression model of Allen (2020): methods for model fitting and generating fitted/predicted values, evaluating the effect of competitor species identity using permutation tests, and evaluating model performance using spatial cross-validation.

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Install

install.packages('forestecology')

Monthly Downloads

259

Version

0.2.0

License

MIT + file LICENSE

Issues

4

Pull Requests

0

Stars

12

Forks

2

Maintainer

Albert Y Kim

Last Published

October 2nd, 2021

Functions in forestecology (0.2.0)

census_2008_bw

Michigan Big Woods research plot data
compute_buffer_region

Compute buffer to a region.
autoplot.comp_bayes_lm

Plot Bayesian model parameters
comp_bayes_lm

Fit Bayesian competition model
add_buffer_variable

Identify trees in the buffer region
census_2014_bw

Michigan Big Woods research plot data
blocks_ex

Example cross validation grid
census_1_ex

Example input census data for package use
comp_bayes_lm_ex

Example bayesian competition model fit
compute_growth

Compute growth of trees
census_2_ex

Example input census data for package use
forestecology

forestecology package
predict.comp_bayes_lm

Make predictions based on fitted Bayesian model
focal_vs_comp_ex

Example focal versus comp data frame
reexports

Objects exported from other packages
%>%

Pipe operator
growth_toy

Example input data for create_focal_vs_comp()
growth_ex

Example growth data frame for small example
growth_spatial_ex

Example growth data frame with spatial data for small example
create_bayes_lm_data

Create input data frame for Bayesian regression
create_focal_vs_comp

Create focal versus competitor trees data frame
species_bw

Phylogenic groupings and trait based clustering of various tree species
run_cv

Run the bayesian model with spatial cross validation
study_region_ex

Study region for example data
focal_vs_comp_distance

Return all pairwise distances between two data frames of trees
study_region_bw

Bigwoods forest study region boundary