Associated with the manuscript "Fusing tree-ring and forest inventory data to infer influences on tree growth" (Evans et al. 2017. Ecosphere ________), we publish R code to implement our statistical model in the public GitHub repository located at https://github.com/kholsinger/DBH. We point readers to a Readme.md file found in this repository, which contains the same information as follows here.

We describe four models reported in the manuscript: coupled vs. uncoupled, and 24 monthly climate variables vs. 4 seasonal climate variables as predictors (see Methods, Evans et al. 2017. Ecosphere ________). The workflow followed in our analysis is controlled by one of two R driver files, one each for the model with 24 monthly climate variables (gi-plus-dbh.R) vs. 4 seasonal climate variables (gi-plus-dbhSeas.R). These R driver files accomplish the following steps of the workflow

1. bring in data,
2. prepare those data in data objects for analysis,
3. set the stage for Stan model analysis,
4. fit a Stan model, and
5. save Stan model output.

The R driver files contain, at the top, several controls (TRUE/FALSE) on what will be done, including debugging, implementation of the coupled vs. uncoupled model, model comparison (i.e., between coupled vs. uncoupled model output), writing results to a text file, and saving Stan MCMC output. Regardless of these settings, execution of the R driver will source two data preparation scripts:

1. "prepare-data.R", which reads in tree-ring data (all .rwl files located in the folder plot-data) and climate covariate data (PRISM_MCN.txt and vpd_MCC_cru1901_1913.txt) and
2. "dbh-process-data.R", which reads in diameter data (MCNallDBH4.csv) and plot covariate data (MCNplotCovariatesNEW.csv). Note that the CRU VPD data actually includes the time series 1901-2013.

If coupled is TRUE and uncoupled is FALSE, the R driver file gi-plus-dbh.R will use "gi-plus-dbh.stan" for the Stan model file; if coupled is FALSE and uncoupled is TRUE, the R driver file gi-plus-dbh.R will use "gi-plus-dbh-uncoupled.stan" for the Stan model file. Similarly, if coupled is TRUE and uncoupled is FALSE, the R driver file gi-plus-dbhSeas.R (testing 4 seasonal climate predictors) will use "gi-plus-dbhM2.stan" for the Stan model file; if coupled is FALSE and uncoupled is TRUE, the R driver file gi-plus-dbhSeas.R will use "gi-plus-dbh-uncoupledM2.stan" for the Stan model file. Parallel models that test the effect of fire + thinning are found in the branch "Fire". Readers unfamiliar with Stan are encouraged to consult the Stan website http://mc-stan.org/ to get oriented to the basic structure and syntax of modeling in Stan. If write.results.file is set to TRUE in the R driver file, summary statistics of parameters monitored during Stan's MCMC simulation are appended to the model output file "results-gi-plus-dbh.txt". If save is TRUE, samples are saved from the MCMC chains in an Rsave file (named either "results-gi-pls-dbh.Rsave" or "results-gi-pls-dbh-uncoupled.Rsave"), according to MCMC settings specified at the top of the R driver file. If compare is TRUE, a comparison is made the MCMC samples in the coupled vs. uncoupled Rsave files (see the description of leave-one-out [LOO] cross-validation, under Model comparison in the Methods, Evans et al. 2017 Ecosphere __________). Results from that comparison are written to the file "model-comparison.txt".

Additional models explored are found in the repository, including gi-plus-dbhM2a.stan, gi-plus-dbhM2b.stan, gi-plus-dbhM2c.stan, gi-plus-dbhProfCurv.stan (testing the effect of the GIS-derived topographic variable profile curvature), and gi-plus-dbhTRMI.stan (testing the effect of a topographic relative moisture index at a variety of spatial scales; citation). Even more models considered but not reported in the manuscript are also found, including a model that estimates a single correlation between the parallel coefficients in the regressions of the two data types (rather than a single constant, alpha; gi-plus-dbh-correlated.stan), and one that estimates a correlation for each parallel coefficient (gi-plus-dbh-multi-correlated.stan). We also considered analyzing basal area increments rather than diameter/radial increments; functions for reconstructing past basal area are found in the R driver files, and models implementing analysis of basal area increments are found in the branch basal-area-increments. Readers interested in these alternative models are encouraged to contact M. E. K. Evans and/or K. E. Holsinger. Scripts for visualizing model output are found in the repository as well, including autocorrelation.R, bivariate.R, plot-mu-site.R, plot-results.R, and plot-site-effects.R. Additional scripts for making figures are available from M. E. K. Evans.