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Data for Use in poscrptR Post-fire Conifer Regeneration Prediction Model

November 23, 2021

These data support poscrptR (Wright et al. 2021). poscrptR is a shiny app that predicts the probability of post-fire conifer regeneration for fire data supplied by the user. The predictive model was fit using presence/absence data collected in 4.4m radius plots (60 square meters). Please refer to Stewart et al. (2020) for more details concerning field data collection, the model fitting process, and limitations. Learn more about shiny apps at The app is designed to simplify the process of predicting post-fire conifer regeneration under different precipitation and seed production scenarios. The app requires the user to upload two input data sets: 1. a raster of Relativized differenced Normalized Burn Ratio (RdNBR), and 2. a .zip folder containing a fire perimeter shapefile. The app was designed to use Rapid Assessment of Vegetative Condition (RAVG) data inputs. The RAVG website ( has both RdNBR and fire perimeter data sets available for all fires with at least 1,000 acres of National Forest land from 2007 to the present. The fire perimeter must be a zipped shapefile (.zip file, include all shapefile components: .cpg, .dbf, .prj, .sbn, .sbx, .shp, and .shx). RdNBR must be 30m resolution, and both the RdNBR and fire perimeter must use the USA Contiguous Albers Equal Area Conic coordinate reference system (USGS version). RDNBR must be alligned (same origin) as RAVG raster data.

Stewart, J., van Mantgem, P., Young, D., Shive, K., Preisler, H., Das, A., Stephenson, N., Keeley, J., Safford, H., Welch, K., Thorne, J., 2020. Effects of postfire climate and seed availability on postfire conifer regeneration. Ecological Applications.

Wright, M.C., Stewart, J.E., van Mantgem, P.J., Young, D.J., Shive, K.L., Preisler, H.K., Das, A.J., Stephenson, N.L., Keeley, J.E., Safford, H.D., Welch, K.R., and Thorne, J.H. 2021. poscrptR. R package version 0.1.3.