From the stand scale to the landscape scale: predicting the spatial patterns of forest regeneration after disturbance. Issue 6 (9th July 2018) - Shive, Kristen L.; Preisler, Haiganoush K.; Welch, Kevin R.; Safford, Hugh D.; Butz, Ramona J.; O'Hara, Kevin L.; Stephens, Scott L.
Abstract: Shifting disturbance regimes can have cascading effects on many ecosystems processes. This is particularly true when the scale of the disturbance no longer matches the regeneration strategy of the dominant vegetation. In the yellow pine and mixed conifer forests of California, over a century of fire exclusion and the warming climate are increasing the incidence and extent of stand‐replacing wildfire; such changes in severity patterns are altering regeneration dynamics by dramatically increasing the distance from live tree seed sources. This has raised concerns about limitations to natural reforestation and the potential for conversion to non‐forested vegetation types, which in turn has implications for shifts in many ecological processes and ecosystem services. We used a California region‐wide data set with 1, 848 plots across 24 wildfires in yellow pine and mixed conifer forests to build a spatially explicit habitat suitability model for forecasting postfire forest regeneration. To model the effect of seed availability, the critical initial biological filter for regeneration, we used a novel approach to predicting spatial patterns of seed availability by estimating annual seed production from existing basal area and burn severity maps. The probability of observing any conifer seedling in a 60‐m 2 area (the field plot scale) was highly dependent on 30‐yr average annual precipitation, burn severity, and seed availability. We then used this model to predict regeneration probabilities across the entire extent of a "new" fire (the 2014 King Fire), which highlights the spatial variability inherent in postfire regeneration patterns. Such forecasts of postfire regeneration patterns are of importance to land managers and conservationists interested in maintaining forest cover on the landscape. Our tool can also help anticipate shifts in ecosystem properties, supporting researchers interested in investigating questions surrounding alternative stable states, and the interaction of altered disturbance regimes and the changing climate.