LAUSR

Context Post-fire tree mortality is a spatially structured process driven by interacting factors across multiple scales. However, empirical models of fire-caused tree mortality are generally not spatially explicit, do not differentiate among scales, and do not differentiate immediate from delayed mortality. Objectives We aimed to quantify cross-scale linkages between forest structure—including spatial patterns of trees—and the progression of mortality 1–4 years post-fire in terms of rates, causes, and underlying demography. Methods We used data from a long-term study site in the Sierra Nevada, California to build a post-fire tree mortality model predicted by lidar-measured estimates of structure. We calculated structural metrics at scales from individual trees to 90 × 90 m neighborhoods and combined them with metrics for topography, site water balance, and burn weather to predict immediate and delayed post-fire tree mortality. Results Mortality rates decreased while average diameter of newly killed trees increased each year post-fire. Burn weather predictors as well as interactive terms across scales improved model fit and parsimony. Including landscape-scale information improved finer-scale predictions but not vice versa. The amount of fuel, fuel configuration, and burning conditions predicted total mortality at broader scales while tree group-scale fuel connectivity, tree species fire tolerance, and local stresses predicted the fine-scale distribution, timing, and agents of mortality. Conclusions Landscape-scale conditions provide the template upon which finer-scale variation in post-fire tree mortality is arranged. Post-fire forest structure is associated with the etiologies of different mortality agents, and so landscape-level heterogeneity is a key part of ecosystem stability and resilience.