Workflow

Make the data set:

1. prac.R - Use to merge tree ring and forest inventory metadata; creates data set of trees stacked with growth year and corresponding ring width value.
2. new_rwl.R - Use if adding new ring width data from rwl files. Merge output with previous data set in AnnualizeDBH.R.
3. AnnualizeDBH.R - Make sure to merge new data. Back calculates DBH using ring width values.
4. MissingDBH.R - Other trees on plot are required for density calculations. Need to back calculate these as well. Use BAR from annualized data set to back calculate first by plot and species and then by species. Includes justification of method.
5. CCF.R - Compute crown competition factor on the plot (stand CCF) and subplot (PCCF) level.
6. BAL.R - Compute basal area of trees larger than the subject tree.
7. CR.R - Compute crown ratio using the Weibull distribution. FVS restricts crown ratio change to 1% (bound).
8. solrad.R - Compute single radiation parameter. There are two methods: Swift method and using the r package - solrad - to get direct radiation. The Swift method is not working, so we use the solrad package.
9. PRISM.R - Extract PRISM climate data for each tree. Total monthly precipitation and average monthly maximum and minimum temperature as well as 30 year climate normals were downloaded.
10. glmm_data.R - Join tree and climate data. Fix trees in which site species associated with site index (SICOND) doesn't match species code. Calculate seasonal climate variables for each species based on clim-growth.R results.

Make the models:

1. clim-growth.R - Use dendrochronolgy r packages - dplR and treeclim - to determine significant climate variables determining growth for each focal species. Input is data_all.Rdata from glmm_data.R.
2. glmm_df.R - Make data frame for Douglas fir growth model. Explore. Determine which climate variables to use in model selection.
3. Douglas fir.Rmd - Picks up where the Douglas fir script leaves off. Finish model building, selection and interpretation.
4. glmm_pp.R - Make data frame for ponderosa pine growth model. Explore. Determine which climate variables to use in model selection.
5. Ponderosa_pine.Rmd - Picks up where the ponderosa pine script leaves off. Finish model building, selection and interpretation.
6. glmm_es.R - Make data frame for Engelmann spruce growth model. Explore. Determine which climate variables to use in model selection.
7. E_spruce.Rmd - Picks up where the Englemann spruce script leaves off. Finish model building, selection and interpretation.

Assess the models:

1. validation.R -