Postfire Spatial Conifer Restoration Planning Tool (POSCRPT) R package (and web version) 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 five years after wildfire, from 1,234 4.4m radius plots (60m2), spanning 19 wildfires in California. Please refer to Stewart et al. (2020) for more details.
The poscrptR tool is designed to simplify the process of predicting post-fire conifer regeneration under different precipitation and seed production scenarios. 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 app requires the user to upload two input data sets:
1) A raster of Relativized differenced Normalized Burn Ratio (RdNBR).
2) A .zip folder containing a fire perimeter shapefile.
The tool is a user interface for Postfire Spatial Conifer Restoration Planning Tool (POSCRPT) models developed by:
Stewart J.A.E., van Mantgem, P.J., Young, D.J.N., Shive, K.L., Preisler, H.K., Das, A.J., Stephenson, N.L., Keeley, J.E., Safford, H.D., Wright, M.C., Welch, K.R. & Thorne, J.H. (2020) Effects of postfire climate and seed availability on postfire conifer regeneration. Ecological applications, e2280.
The models developed by Stewart et al. (2020) were inspired by an earlier spatial model developed by Shive et al. (2018) and by analyses of sensitivity to postfire climate presented by Young et al. (2019).
Shive, K.L., Preisler, H.K., Welch, K.R., Safford, H.D., Butz, R.J., O’Hara, K.L. and Stephens, S.L., 2018. From the stand scale to the landscape scale: predicting the spatial patterns of forest regeneration after disturbance. Ecological Applications, 28(6), pp.1626-1639.
Young, D. J. N., C. M. Werner, K. R. Welch, T. P. Young, H. D. Safford, and A. M. Latimer. 2019. Post-fire forest regeneration shows limited climate tracking and potential for drought-induced type conversion. Ecology 100:e02571.
