Wildfire may facilitate climate tracking of forest species moving upslope or north in latitude. For subalpine tree species, for which higher elevation habitat is limited, accelerated replacement by lower elevation montane tree species following fire may hasten their extinction risk. We used a dataset of post-fire tree regeneration spanning a broad geographic range to ask whether fire facilitated upslope movement of montane tree species at the montane-to-subalpine ecotone. We sampled tree seedling occurrence in 248 plots across a fire severity gradient (unburned to >90% basal area mortality) and spanning ~500 km of latitude in Mediterranean-type subalpine forest in California, USA. We used logistic regression to quantify differences in postfire regeneration between resident subalpine species and the seedling-only range (interpreted as climate-induced range extension) of montane species. We tested our assumption of increasing climatic suitability for montane species in subalpine forest using the predicted difference in habitat suitability at study plots between 1990 and 2030. We found that postfire regeneration of resident subalpine species was uncorrelated or weakly positively correlated with fire severity. Regeneration of montane species, however, was roughly four times greater in unburned relative to burned subalpine forest. Although our overall results contrast with theoretical predictions of disturbance-facilitated range shifts, we found opposing postfire regeneration responses for montane species with distinct regeneration niches. Recruitment of shade-tolerant red fir declined with fire severity and recruitment of shade-intolerant Jeffrey pine increased with fire severity. Predicted climatic suitability increased 5% for red fir and 34% for Jeffrey pine. Differing postfire responses in newly climatically available habitat indicate that wildfire disturbance may only facilitate range extensions for species whose preferred regeneration conditions align with increased light and/or other postfire landscape characteristics.

Methods may be found in linked publication Brodie et al., 2023.

Data are in .csv format and may be opened with any program designed to view tabular data such as Microsoft Excel or Google Sheets.