Identifying Optimal Summer Microclimate for Conifer Seedlings in a Postfire Environment

Tree seedling and understory vegetation re-establishment following wildfires is fundamental to landscape recovery but highly variable, depending strongly on biophysical context at small spatial scales. Onsite regeneration surveys and monitoring have been traditionally viewed as a crucial part of sustainable forest management but can be extremely difficult and time-consuming. The objectives of this study were to use a combination of ground measurements and nonparametric hypothesis tests to quantify the ecological relationship between seedling abundance and microclimate by identifying optimal ranges of vapor pressure deficit (VPD) and sun for seedling abundance in postfire environments in the McKenzie River watershed in Oregon. We followed this effort by evaluating how wildfire severity alters these optimal conditions, informing concepts of conifer regeneration under shifting fire regimes in the Pacific Northwest. LOESS modeling, nonparametric statistics, and geospatial analysis quantified the top–down relationship between wildfire severity, site factors, and seedling abundance in our case study. Using LOESS models, optimal VPD ranges were found at 1.1–1.7 kPa and optimal sun ranges were found at 31.2%–47.8% (PAR). Kruskal–Wallis tests were used to compare differences in seedling abundance and optimal VPD and sun ranges (p = 0.027; p = 0.045). Their combined effect on seedling abundance was also evaluated using a Wilcoxon rank-sum test (p = 0.012). Fire severity was not significant to seedling abundance occurrence, but high-severity areas had a higher occurrence of optimal environments. However, given seed source availability, moderate-fire-severity events are still favored for predictable postfire regeneration. These results give insight into the resilience of ecosystems postfire and can be used to assess reforestation needs and monitor forest recovery. Measurements and resulting applications will benefit land managers serving as prefire data for when, inevitably, the next wildfire burns. These concepts can help repair the relationship between humans and wildland fire.