Spatially explicit forecasts of tree insect and disease incidence across North American forests under future climate scenarios

This repository contains the core analysis code and supporting data for the study 'Spatially explicit forecasts of tree insect and disease incidence across North American forests under future climate scenarios'. Using Bayesian hierarchical binomial regression fit to forest inventory records, we model the effects of contemporary and historical climate on forest insect and pathogen (FIP) incidence at the tree-population levels across plots, among tree species, and on individual FIP taxon, and project climate-driven shifts in incidence under SSP2-4.5, SSP3-7.0, and SSP5-8.5 climate scenarios. Files: data_pest_pathogen.csv — Tree-population-level FIP incidence and predictor data used to fit the models. dataNotes.csv — Description of variables. CoreCode.R — Core analysis code (model fitting and projection workflow). phylo_host.tree — Host tree phylogeny used to construct the phylogenetic covariance structure. climateProjection.tif — Historical, contemporary, and future (SSP scenario) climate layers. treeCover.tif — Global tree-cover layer used to restrict projections to forested land. treerange.shp (with .shx, .dbf, .cpg) — Tree species geographic ranges. pestRange.shp (with .shx, .dbf, .cpg) — FIP taxa geographic ranges.