- Metric Name:  Natural Conifer Regeneration Probability

- Data Vintage:  2021

- Unit Of Measure: Probability, 0 to 1

This metric is intended to be used to identify areas where reforestation may be necessary if stakeholders want to reestablish coniferous forests following fire. Conifers in our region generally lack the capacity to resprout after fire and are thus dependent on seedling recruitment for regeneration. Under pre colonial fire regimes – of frequent, small, and typically lower severity fires – conifer seeds were generally able to travel the relatively short distances from live trees to burnt patches. In contrast, the recent emergence of large stand-replacing fires poses a significant challenge for conifer regeneration because long-distance seed dispersal events – needed to span the long distances between surviving trees and large burnt patches – are relatively rare. As a result, many areas formerly occupied by conifers may be poised for vegetation type conversion if conifers are not deliberately replanted.- Creation Method:  This metric is the modeled probability of natural conifer regeneration – within 4.4m radii (60 m2) circular plots, five years after fire – for fires occurring from 2012 to 2021. In areas that burned more than once, the probability of regeneration following the most recent fire is reported.

The predictive model was fit using data from 1,234 4.4m radius (60 m2) plots, spanning 19 wildfires, each measured five years after wildfire (Stewart et al. 2021). Predictor variables include seed availability, burn severity, postfire precipitation 1 – 5 water years following each fire, slope, and equinox solar insolation. Burn severity was derived from Landsat composite imagery using methods derived from Parks et al (2018). Topographically downscaled postfire precipitation data was used as available (i.e., up to the 2022 water-year) and assumed to be equivalent to historical mean conditions (1981 – 2010) for future or incomplete water-years (Daly et al. 1994). Species-specific seed availability was derived from available forest structure maps (2012-2017; Ohmann et al. 2011), allometric equations, a dispersal kernel, and a basal-area-loss-to-fire function (Stewart et al. 2021).

When available, average species-specific basal area up to 5 years following fire was used to estimate seed availability. When unavailable (i.e., for 2017-2021 fires), a composite of 2016 and 2017 structure maps were adjusted to account for the effects of subsequent fires. I.e., to avoid unreliable regions of the 2017 forest structure map – that were derived from summer composite imagery that spans a period both before, during, and after 2017 fires – the 2016 map (adjusted for 2017 fire effects) was used in these areas. Subsequent years were adjusted for the effects of wildfires that occurred from 2018 to 2021. For additional details see Stewart et al. (2021) or the Postfire Conifer Reforestation Planning Tool (accessed at: https://reforestationtools.org/postfire-conifer-reforestation-planning-tool/). Predictions were made using version 0.125 of the Postfire Conifer Reforestation Planning Tool.

--	Postfire regeneration and seed production data, Stewart et al. 2022

--	Monthly climate data, Daly et al 1994

--	Forest structure maps, Ohmann et al. 2011

--	National Elevation Dataset, USGS

--	Landsat 4-8, NASA

--	Fire History (2021), CAL FIRE

--	Postfire mortality data, Miller et al. 2009

- Credits:  Department of Plant Sciences, UC Davis
Department of Plant Sciences, UC Davis