Outbreaks of aggressive bark beetle species cause widespread tree mortality, affecting timber production, wildlife habitat, wildfire, forest composition and structure, biogeochemical cycling, and biogeophysical processes. As a result, agencies responsible for forest management in the United States and British Columbia conduct aerial surveys to map these forest disturbances. Here we combined aerial surveys from British Columbia (2001–2010) and the western conterminous United States (1997–2010), produced 1‐km²grids of the area of crown mortality from bark beetle attack, and analyzed spatial and temporal patterns. We converted aerial‐survey polygon data for each combination of host type and bark beetle species available in the western United States, and for each bark beetle species available in British Columbia. We converted affected area (which includes live and killed trees) to mortality area (crown area of killed trees) using species‐specific crown diameters and the number (U.S.) or percentage (British Columbia) of killed trees. In the United States we also produced an upper estimate of mortality area by forcing the mortality area to match that from high‐resolution imagery in Idaho, Colorado, and New Mexico. Resulting adjustment factors of 3.7–20.9 illustrate the underestimate of mortality by the U.S. aerial surveys. The upper estimate, which we suggest is more realistic, better matched the spatial patterns and severity of the British Columbia mortality area. Cumulative mortality area from all bark beetles was 5.46 Mha in British Columbia in 2001–2010 and 0.47–5.37 Mha (lower and upper estimate) in the western conterminous United States during 1997–2010. We note that we report year of detection here; studies that consider year of tree mortality should shift the time series back one year. We conclude by discussing uses and limitations of these data in ecological studies, including uncertainties associated with assumptions in the methods, lack of complete coverage by surveys, and the subjective nature of the survey databases.

Fire refugia are landscape elements that remain unburned or minimally affected by fire, thereby supporting postfire ecosystem function, biodiversity, and resilience to disturbances. Although fire refugia have been studied across continents, scales, and affected taxa, they have not been characterized systematically over space and time, which is crucial for understanding their role in facilitating resilience in the context of global change. We identify four dichotomies that delineate an overarching conceptual framework of fire refugia: unburned versus lower severity, species-specific versus landscape-process characteristics, predictable versus stochastic, and ephemeral versus persistent. We outline the principal concepts underlying the ecological function of fire refugia and describe both the role of fire refugia and uncertainties regarding their persistence under global change. An improved understanding of fire refugia is crucial to conservation given the role that humans play in shaping disturbance regimes across landscapes.

Wildfire behavior depends on the type, quantity, and condition of fuels, and the effect that bark beetle outbreaks have on fuels is a topic of current research and debate. Remote sensing can provide estimates of fuels across landscapes, although few studies have estimated surface fuels from remote sensing data. Here we predicted and mapped field-measured canopy and surface fuels from light detection and ranging (lidar) and Landsat time series explanatory variables via random forest (RF) modeling across a coniferous montane forest in Colorado, USA, which was affected by mountain pine beetles (Dendroctonus ponderosae Hopkins) approximately six years prior. We examined relationships between mapped fuels and the severity of tree mortality with correlation tests. RF models explained 59%, 48%, 35%, and 70% of the variation in available canopy fuel, canopy bulk density, canopy base height, and canopy height, respectively (percent root-mean-square error (%RMSE) = 12–54%). Surface fuels were predicted less accurately, with models explaining 24%, 28%, 32%, and 30% of the variation in litter and duff, 1 to 100-h, 1000-h, and total surface fuels, respectively (%RMSE = 37–98%). Fuel metrics were negatively correlated with the severity of tree mortality, except canopy base height, which increased with greater tree mortality. Our results showed how bark beetle-caused tree mortality significantly reduced canopy fuels in our study area. We demonstrated that lidar and Landsat time series data contain substantial information about canopy and surface fuels and can be used for large-scale efforts to monitor and map fuel loads for fire behavior modeling at a landscape scale.

A warming climate, fire exclusion, and land cover changes are altering the conditions that produced historical fire regimes and facilitating increased recent wildfire activity in the northwestern United States. Understanding the impacts of changing fire regimes on forest recruitment and succession, species distributions, carbon cycling, and ecosystem services is critical, but challenging across broad spatial scales. One important and understudied aspect of fire regimes is the unburned area within fire perimeters; these areas can function as fire refugia across the landscape during and after wildfire by providing habitat and seed sources. With increasing fire activity, there is speculation that fire intensity and combustion completeness are also increasing, which we hypothesized would yield smaller unburned proportions and changes in fire refugia patterns. We sought to determine (1) whether the unburned proportion of wildfires decreased across the northwestern United States from 1984 to 2014 and (2) whether patterns of unburned patches were significantly different across ecoregions, land cover type, and land ownership. We utilized a Landsat‐derived geospatial database of unburned islands within 2298 fires across the inland northwestern USA (including eastern Washington, eastern Oregon, and Idaho) from 1984 to 2014. We evaluated patterns of the total unburned proportion and spatial patterns of unburned patches of the fires across different ecoregions, land cover types, and land ownership. We found that unburned area proportion exhibited no change over the three decades, suggesting that recent trends in area burned and overall severity have not affected fire refugia, important to post‐fire ecosystem recovery. There were ecoregional differences in mean unburned proportion, patch area, and patch density, suggesting influences of vegetation and topography on the formation of unburned area. These foundation findings suggest that complex drivers control unburned island formation, and yield insights to locate potential important fire refugia across the inland northwest.

Extensive bark beetle outbreaks have recently occurred in western North American forests, resulting in overstory tree mortality across millions of hectares. Annual aerial surveys are currently used to operationally monitor bark beetle induced tree mortality, though this method is subjective and can exclude some forest areas. Daily Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data offer a potential alternative means to develop regional tree mortality maps. Accurate methods using such data could aid natural resource managers in surveys of forests with frequent overstory mortality, helping to prioritize forest treatment and restoration activities. This paper discusses a study to test the potential of using MODIS data to detect tree mortality. We developed and tested an approach to use 250-m resolution MODIS Normalized Difference Vegetation Index (NDVI) data products collected during a mountain pine beetle (MPB) outbreak and related tree mortality event in the northern Rocky Mountains of Colorado, USA. The 94 km² study area is predominantly lodgepole pine forest with most of the MPB-caused mortality occurring between 2003 and 2008. We used a 2.4-m forest conditions map from 2008 aerial multispectral imagery to calculate percentage of mortality within 240-m pixels for use as reference data. Using either daily or 16-day products, MODIS NDVI change products were calculated for 2008 versus either 2000 or 2003 baselines. MODIS change products were used as predictors in linear regression analysis to assess correlation between MODIS data and the aerial percent forest mortality map. Depending on the MODIS product, linear regression analyses yielded r² values ranging from 0.362 to 0.544 without outliers removed and from 0.406 to 0.570 with extreme outliers removed. Daily MODIS NDVI products from 2003 and 2008 were used with exponential regression to improve the r² to 0.593. The project showed some MODIS NDVI data potential for mapping percent tree mortality in forests subjected to regional bark beetle outbreaks and severe drought.