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Increasing fire severity and warmer, drier postfire conditions are making forests in the western United States (West) vulnerable to ecological transformation. Yet, the relative importance of and interactions between these drivers of forest change remain unresolved, particularly over upcoming decades. Here, we assess how the interactive impacts of changing climate and wildfire activity influenced conifer regeneration after 334 wildfires, using a dataset of postfire conifer regeneration from 10,230 field plots. Our findings highlight declining regeneration capacity across the West over the past four decades for the eight dominant conifer species studied. Postfire regeneration is sensitive to high-severity fire, which limits seed availability, and postfire climate, which influences seedling establishment. In the near-term, projected differences in recruitment probability between low- and high-severity fire scenarios were larger than projected climate change impacts for most species, suggesting that reductions in fire severity, and resultant impacts on seed availability, could partially offset expected climate-driven declines in postfire regeneration. Across 40 to 42% of the study area, we project postfire conifer regeneration to be likely following low-severity but not high-severity fire under future climate scenarios (2031 to 2050). However, increasingly warm, dry climate conditions are projected to eventually outweigh the influence of fire severity and seed availability. The percent of the study area considered unlikely to experience conifer regeneration, regardless of fire severity, increased from 5% in 1981 to 2000 to 26 to 31% by mid-century, highlighting a limited time window over which management actions that reduce fire severity may effectively support postfire conifer regeneration.

Wildfires and housing development have increased since the 1990s, presenting unique challenges for wildfire management. However, it is unclear how the relative influences of housing growth and changing wildfire occurrence have altered risk to homes, or the potential for wildfire to threaten homes. We used a random forests model to predict burn probability in relation to weather variables at 1‐km resolution and monthly intervals from 1990 through 2019 in the Southern Rocky Mountains ecoregion. We quantified risk by combining the predicted burn probabilities with decadal housing density. We then compared the predicted burn probabilities and risk across the study area with observed values and quantified trends. Finally, we evaluated how housing growth and changes in burn probability influenced risk individually and combined. Fires burned 9055 km2 and exposed more than 8500 homes from 1990 to 2019. Observed burned area increased 632% from the 1990s to the 2000s, which combined with housing growth, resulted in a 1342% increase in homes exposed. Increases continued in the 2010s but at lower rates; burned area by 65% and exposure by 32%. The random forests model had excellent fit and high correlation with observations (AUC = 0.88 and r = 0.9). Observed values were within the 95% uncertainty interval for all years except 2016 (burned area) and 2000 (exposure). However, our model overpredicted in years with low observed burned area and underpredicted in years with high observed burned area. Overpredictions in risk resulted in lower rates of change in predicted risk compared with change in observed exposure. Increases in risk between the 1990s and 2000s were primarily due to warmer and drier weather conditions and secondarily because of housing growth. However, increases between the 2000s and 2010s were primarily due to housing growth. Our modeling approach identifies spatial and temporal patterns of wildfire potential and risk, which is critical information to guide decision‐making. Because the drivers behind risk shift over time, strategies to mitigate risk may need to account for multiple drivers simultaneously. [ABSTRACT FROM AUTHOR]

Aim: Fine‐scale topography and canopy cover can play an important role in mediating effects of regional‐scale climate change on the below‐canopy environment in mountain forests. The aim of this study was to determine how below‐canopy temperatures in a high‐elevation Rocky Mountain forest have been affected by canopy change resulting from severe wildfire and spruce beetle outbreak within the last 10–15 years. Location: Eastern San Juan Mountains, Colorado, USA. Taxon: Picea engelmannii, Abies lasiocarpa, Dendroctonus rufipennis. Methods: We used a network of sensors to record temperatures for a full year in burned and beetle‐impacted areas. Using a Bayesian model that accounted for spatial structure in temperatures, we derived covariate parameters to determine the relative influence of topographic variables (elevation, aspect, slope, topographic position and solar radiation), live tree basal area and burned/unburned status on average daily maximum and minimum temperatures (Tmax, Tmin) in summer and winter. Results: Model parameters indicated that burned areas were warmer than unburned forest, with three of four average temperature variables (summer Tmax, winter Tmax, and winter Tmin) having >95% likelihood of a positive temperature difference in burned versus unburned locations. Mean temperature changes for these variables ranged from 0.41 to 0.74°C. Conversely, canopy loss in unburned, beetle‐killed forests did not meaningfully affect Tmax but resulted in slight cooling of Tmin. Modelled temperature changes resulting from 100% overstorey mortality were −1.29°C for summer Tmin (95% credible interval: −0.027 to −2.56°C) and −1.31°C for winter Tmin (95% credible interval: 0.17 to −2.79°C). Main Conclusions: Our results indicate that severe wildfire may exacerbate effects of climate change and increase the probability of ecosystem transitions. However, the effects of bark beetle outbreaks are more complex. Cooling of overnight minimum temperatures may counteract warming trends, but an increase in diurnal temperature ranges may have uncertain ecological consequences. [ABSTRACT FROM AUTHOR]