Mixed-severity Wildfire Research Articles

Stream chemical response is mediated by hydrologic connectivity and fire severity in a Pacific Northwest forest

AbstractLarge‐scale wildfires are becoming increasingly common in the wet forests of the Pacific Northwest (USA), with predicted increases in fire prevalence under future climate scenarios. Wildfires can alter streamflow response to precipitation and mobilize water quality constituents, which pose a risk to aquatic ecosystems and downstream drinking water treatment. Research often focuses on the impacts of high‐severity wildfires, with stream biogeochemical responses to low‐ and mixed‐severity fires often understudied, particularly during seasonal shifts in hydrologic connectivity between hillslopes and streams. We studied the impacts of the 2020 Holiday Farm Fire at the HJ Andrews Experimental Forest where rare pre‐fire stream discharge and chemistry data allowed us to evaluate the influence of mixed‐severity fire on stream water quantity and quality. Our research design focused on two well‐studied watersheds with low and low‐moderate burn severity where we examined long‐term data (pre‐ and post‐fire), and instantaneous grab samples collected during four rain events occurring immediately following wildfire and a prolonged dry summer. We analysed the impact of these rain events, which represent the transition from low‐to‐high hydrologic connectivity of the subsurface to the stream, on stream discharge and chemistry behaviour. Long‐term data revealed total annual flows and mean flows remained fairly consistent post‐fire, while small increases in baseflow were observed in the low‐moderately burned watershed. Stream water concentrations of nitrate, phosphate and sulfate significantly increased following fire, with variance in concentration increasing with fire severity. Our end member mixing models suggested that during rain events, the watershed with low‐moderate severity fire had greater streamflow inputs from soil water and groundwater during times of low connectivity compared to the watershed with low severity fire. Finally, differences in fire severity impacts on concentration‐discharge relationships of biogenic solutes were most expressed under low catchment connectivity conditions. Our study provides insights into post‐wildfire impacts to stream water quality, with the goal of informing future research on stream chemistry responses to low, moderate and mixed severity wildfire.

Using Pre-Fire High Point Cloud Density LiDAR Data to Predict Fire Severity in Central Portugal

The wall-to-wall prediction of fuel structural characteristics conducive to high fire severity is essential to provide integrated insights for implementing pre-fire management strategies designed to mitigate the most harmful ecological effects of fire in fire-prone plant communities. Here, we evaluate the potential of high point cloud density LiDAR data from the Portuguese áGiLTerFoRus project to characterize pre-fire surface and canopy fuel structure and predict wildfire severity. The study area corresponds to a pilot LiDAR flight area of around 21,000 ha in central Portugal intersected by a mixed-severity wildfire that occurred one month after the LiDAR survey. Fire severity was assessed through the differenced Normalized Burn Ratio (dNBR) index computed from pre- and post-fire Sentinel-2A Level 2A scenes. In addition to continuous data, fire severity was also categorized (low or high) using appropriate dNBR thresholds for the plant communities in the study area. We computed several metrics related to the pre-fire distribution of surface and canopy fuels strata with a point cloud mean density of 10.9 m−2. The Random Forest (RF) algorithm was used to evaluate the capacity of the set of pre-fire LiDAR metrics to predict continuous and categorized fire severity. The accuracy of RF regression and classification model for continuous and categorized fire severity data, respectively, was remarkably high (pseudo-R2 = 0.57 and overall accuracy = 81%) considering that we only focused on variables related to fuel structure and loading. The pre-fire fuel metrics with the highest contribution to RF models were proxies for horizontal fuel continuity (fractional cover metric) and the distribution of fuel loads and canopy openness up to a 10 m height (density metrics), indicating increased fire severity with higher surface fuel load and higher horizontal and vertical fuel continuity. Results evidence that the technical specifications of LiDAR acquisitions framed within the áGiLTerFoRus project enable accurate fire severity predictions through point cloud data with high density.

Breeding bird abundance and species diversity greatest in high-severity wildfire patches in central hardwood forests

In 2016, mixed-severity wildfires in the southern Appalachians created a gradient of forest structures not typical following prescribed burns, providing a unique opportunity to study temporally dynamic conditions and breeding bird response. We measured forest structure and breeding bird communities across a fire-severity gradient in 3 burned and 3 unburned watersheds for 5 years (Y1-Y5). We categorized plots as unburned (NB), low- (L), moderate- (M), or high-severity (H) using a composite fire-severity index. Tree mortality increased with fire-severity category (FSC) and over time; by Y5, 7 % of trees in NB, 11 % in L, 38 % in M, and 71 % in H had died. Shrub recovery was rapid and most pronounced in H, exceeding other FSCs (70 % vs 21 %–44 %) by Y5. Total bird abundance, species richness, and diversity increased over time in H (by Y3) and M (by Y4); by Y5, these metrics were highest in H and twice as high in H as in NB. Low-severity wildfires had no detectable effects on birds. Abundance of 7 species was greatest in higher-severity FSCs; 11 species did not differ among FSC, although ovenbirds (Seiurus aurocapilla) indicated a trend of lower abundance in H. No species was limited to NB, L, or M, whereas disturbance-dependent indigo bunting (Passerina cyanea), chestnut-sided warbler (Setophaga pensylvanica), and eastern towhee (Pipilo erythrophthalmus) were primarily associated with H. Increased richness and diversity were associated with heavy tree mortality and subsequent shrub recovery in H, accompanied by an influx of disturbance-dependent species and positive or neutral responses by most other species. Results highlight the interrelated roles of fire severity and time in driving forest structure and breeding bird response. Breeding birds responded to high-severity burns similarly to silvicultural treatments with heavy canopy reduction documented in other studies, offering possible alternatives when managing for breeding bird diversity in hardwood forests.

Influence of topography, vegetation, weather, and climate on Big-cone Douglas-Fir fire refugia and high fire-induced mortality after two large mixed-severity wildfires

Big-cone Douglas-Fir (Pseudotsuga macrocarpa, hereafter BCDF) is an endemic, fire-adapted conifer found throughout the mountains of southern California. Because recent large high intensity wildfires have resulted in loss of BCDF, understanding how environmental factors, such as topography, fuels, climate, and weather, impact BCDF survivorship is important for informing restoration and conservation efforts. Here, we used randomForest (RF) and accumulated local effects (ALE) plots to examine how environmental variables contribute to the occurrence of both fire refugia and high fire-induced mortality of BCDF stands during two large wildfires. Additionally, we explored how the influence of these variables changed between the use of two different response variables: (1) visually-assessed mortality evaluated through estimation of canopy survival using Google Earth imagery and (2) RdNBR. This comparison allows us to evaluate the potential that RdNBR overestimates BCDF mortality because it is highly indicative of understory conditions post-fire, rather than direct changes to BCDF trees. We found that pre-fire fuel was one of the most influential variables contributing to both fire refugia and high mortality; sparse and oak dominant understories contributed to fire refugia, while chaparral contributed to high mortality. We also found that the role of certain variables was not consistent across the two fires. For example, areas of the landscape with hotter temperature and higher vapor pressure deficit (VPD) during the fire experienced high BCDF mortality in the Zaca Fire, but had the inverse effect in the Thomas Fire. Lastly, we found that our two metrics of response resulted in significantly different classification of BCDF stands: RdNBR resulted in more stands being classified as high intensity and fewer low severity/unburned areas, supporting our concern that it can overestimate high severity impact in some ecosystems. However, the two model types resulted in relatively similar explanatory environmental variable selections, although different rankings.

Short-Term Recovery of the Aboveground Carbon Stock in Iberian Shrublands at the Extremes of an Environmental Gradient and as a Function of Burn Severity

The degree to which burn severity influences the recovery of aboveground carbon density (ACD) of live pools in shrublands remains unclear. Multitemporal LiDAR data was used to evaluate ACD recovery three years after fire in shrubland ecosystems as a function of burn severity immediately after fire across an environmental and productivity gradient in the western Mediterranean Basin. Two large mixed-severity wildfires were assessed: an Atlantic site, dominated by resprouter shrubs and located at the most productive extreme of the gradient, and a Mediterranean site, dominated by obligate seeders and located at the less productive extreme. Initial assessment of burn severity was performed using the differenced Normalized Burn Ratio index computed from Landsat imagery. Thresholds for low and high burn severity categories were established using the Composite Burn Index (CBI). LiDAR canopy metrics were calibrated with field measurements of mean shrub height and cover at plot level in a post-fire situation. Pre-fire and post-fire ACD estimates, and their ratio (ACDr) to calculate carbon stock recovery, were computed from the predictions of LiDAR grid metrics at landscape level using shrubland allometric relationships. Overall, ACDr decreased both with high burn severity and low productivity, although the burn severity impact was not homogeneous within the gradient. In the Atlantic site, ACDr was similar under low and high burn severity, whereas it decreased with burn severity in the Mediterranean site. These results suggest that carbon cycling models could be biased by not accounting for both fire severity and species composition of shrublands under different environmental conditions.

Mixed-severity wildfire shapes habitat use of large herbivores and carnivores

Ecological disturbance is a driving force that structures ecosystems and shapes landscape pattern. Wildfire is a widespread form of ecological disturbance, and in some vegetation communities fires are increasing in extent and severity. Across the gradient of fire severity, fire can have both positive and negative effects on animals, where some species require mature climax vegetation conditions and other species select for early successional stages. However, further work is necessary to understand how large mammalian herbivore and carnivore populations respond to the gradient of fire severity. The overall objective of this research was to understand the relative roles of fire, landscape, and human factors across the gradient of fire severity on occupancy and/or relative habitat use of large herbivores (i.e., elk and mule deer) and carnivores (i.e., black bear, mountain lion, and gray wolf) seven years post fire. We predicted that animals would increase use of areas characterized by higher fire severity (moderate, moderate/high, or high fire severity) and heterogeneity, where food resources were expected to be greatest. In addition, road density could either increase or decrease animal use of areas, where some animals might increase use near roads due to increased forage along roadsides or decrease use due to higher human activity. Remote wildlife (RW) cameras sampled the gradient of fire severity seven years post a large mixed-severity wildfire (Wallow Fire, year 2011, 2,177 km2) in the White Mountains of Arizona, USA. We evaluated RW camera data using single-species occupancy and Royle-Nichols (relative habitat use) models. As predicted, large mammals (black bear, elk, mountain lion, mule deer, and wolves) exhibited high occupancy and/or habitat use in relation to higher levels of fire severity and/or fire heterogeneity, which was likely related to bottom-up factors related to increased food resources. Some species (black bear and elk) also exhibited relatively high use of unburned forest. Elk reduced use of areas with higher road density, likely to avoid human activity, whereas mule deer increased use of areas with high road density. Mixed-severity wildfire may provide important resources, including pulses of food in early successional forests. Thus, allowing fire-adapted forests to experience mixed-severity wildfire is predicted to benefit some large herbivore and carnivore populations. If high occupancy and/or habitat use by wildlife in areas experiencing higher fire severity and heterogeneity translates into increased populations of animals, wildfire might be beneficial to humans, focal wildlife populations, and fire-adapted ecosystems.

Influence of fuel structure derived from terrestrial laser scanning (TLS) on wildfire severity in logged forests

ContextLogging and wildfire can reduce the height of the forest canopy and the distance to the understorey vegetation below. These conditions may increase the likelihood of high severity wildfire (canopy scorch or consumption), which may explain the greater prevalence of high severity wildfire in some recently logged or burnt forests. However, the effects of these structural characteristics on wildfire severity have not clearly been demonstrated. ObjectivesWe aimed to assess how the structure of forests affected by logging and wildfire influence the probability of high severity wildfire. MethodsWe used terrestrial laser scanning to measure the connectivity of canopy and understorey vegetation in forests at various stages of recovery after logging and wildfire (approximately 0–80 years since disturbance). These sites were subsequently burnt by mixed severity wildfire during the 2019–20 ‘Black Summer’ fire season in south-eastern Australia. We assessed how these forest structure metrics affected the probability of high severity wildfire. ResultsThe probability of high severity fire decreased as the canopy base height increased, and the distance between the canopy base and understorey increased. High severity wildfire was less likely in forests with taller understoreys and greater canopy or understorey cover, but these effects were not considered causal. Fire weather was the strongest driver of wildfire severity, which was also affected by topography. ConclusionsThese findings demonstrate a link between forest structure characteristics, that are strongly shaped by antecedent logging and fire, and fire severity. They also indicate that vertical fuel structure should be incorporated into assessments of fire risk.

Mixed-Severity Wildfire as a Driver of Vegetation Change in an Arizona Madrean Sky Island System, USA

Fire is a powerful natural disturbance influencing vegetation patterns across landscapes. Recent transitions from mixed-species forests to post-fire shrublands after severe wildfire is an increasingly prevalent phenomenon in pine-oak and conifer forest ecosystems in southwestern North America. However, we know little about how variation in fire severity influences other common forest types in the region. In this study, we evaluated fire-induced changes in woody plant community composition and forest structure in Chiricahua Mountains in southeastern Arizona in the United States that hosts a diverse set of vegetation types. Cluster analysis of the pre-fire vegetation data identified three dominant pre-fire vegetation types including juniper woodland, piñon forest, and pine-oak forest. All vegetation types experienced significant tree mortality across a wide range of size classes and species, from forests to shrublands. The magnitude of change within sample plots varied with fire severity, which was mediated by topography. Significant shifts in dominance away from coniferous obligate seeder trees to resprouting hardwoods and other shrubs occurred across all vegetation types in response to the fire. Regeneration from seed can be episodic, but projected increases in aridity and fire frequency may promote continued dominance by hardwoods and fire- and drought-resistant shrub communities, which is a regional forest management concern as wildfire size and severity continue to increase throughout the southwestern USA.

Radiative transfer modeling to measure fire impact and forest engineering resilience at short-term

Forest managers demand reliable and cost-efficient methodologies to implement forest resilience concepts in post-fire decision-making at different spatio-temporal scales. In this paper, we developed a generalizable remote sensing-based tool to measure disturbance impact and engineering resilience at short-term in forest ecosystems affected by wildland fires. The case study was a mixed-severity wildfire that burned several shrubland (dominated by gorse, broom and heath) and tree forest (dominated by oak and pine) ecosystems. Specifically, we retrieved fractional vegetation cover (FVC) over a time-series of pre and post-fire Deimos-2 imagery (spatial resolution of 4 m) from a radiative transfer model (RTM) hybrid inversion approach (Gaussian processes regression algorithm learned from a simulation dataset generated using the PROSAIL-D model). Pre and post-fire FVC retrieval was validated with field data stratified by dominant ecosystem. High accuracy (>90%) and low error (<7%) were achieved in the retrieval over the time-series, despite the influence of background signal of soil and burned legacies. A random point sampling stratified by ecosystem and burn severity was used to extract validated FVC values for the time-series. A two-way repeated measures ANOVA was performed to evaluate the effect of burn severity along the time-series on FVC for each ecosystem. One-way repeated measures ANOVA and Tukey’s pairwise comparison test were applied to determine the earliest point in the time-series for which the FVC does not differ significantly from the pre-fire FVC. In tree forest ecosystems, the fire impact on FVC was stronger at high burn severity, being similar the impact on shrub ecosystems at medium and high burn severity. Engineering resilience was conditioned both by burn severity and species regenerative strategies. In ecosystems dominated by facultative or obligate seeders, pre-fire FVC was reached later across the time-series, compared to resprouter-dominated ecosystems. The RTM hybrid inversion tool has proved its reliability for assessing disturbance impact and ecosystem engineering resilience at short-term in heterogeneous fire-prone landscapes affected by mixed severity wildfires.

Vegetation structure parameters determine high burn severity likelihood in different ecosystem types: A case study in a burned Mediterranean landscape

The design and implementation of pre-fire management strategies in heterogeneous landscapes requires the identification of the ecological conditions contributing to the most adverse effects of wildfires. This study evaluates which features of pre-fire vegetation structure, estimated through broadband land surface albedo and Light Detection and Ranging (LiDAR) data fusion, promote high wildfire damage across several fire-prone ecosystems dominated by either shrub (gorse, heath and broom) or tree species (Pyrenean oak and Scots pine). Topography features were also considered since they can assist in the identification of priority areas where vegetation structure needs to be managed. The case study was conducted within the scar of a mixed-severity wildfire that occurred in the Western Mediterranean Basin. Burn severity was estimated using the differenced Normalized Burn Ratio index computed from Sentinel-2 multispectral instrument (MSI) Level 2 A at 10 m of spatial resolution and validated in the field using the Composite Burn Index (CBI). Ordinal regression models were implemented to evaluate high burn severity outcome based on three groups of predictors: topography, pre-fire broadband land surface albedo computed from Sentinel-2 and pre-fire LiDAR metrics. Models were validated both by 10-fold cross-validation and external validation. High burn severity was largely ecosystem-dependent. In oak and pine forest ecosystems, severe damage was promoted by a high canopy volume (model accuracy = 79%) and a low canopy base height (accuracy = 82%), respectively. Land surface albedo, which is directly related to aboveground biomass and vegetation cover, outperformed LiDAR metrics to predict high burn severity in ecosystems with sparse vegetation. This is the case of gorse and broom shrub ecosystems (accuracy of 80% and 77%, respectively). The effect of topography was overwhelmed by that of the vegetation structure portion of the fire triangle behavior, except for heathlands, in which warm and steep slopes played a key role in high burn severity outcome together with horizontal and vertical fuel continuity (accuracy = 71%). The findings of this study support the fusion of LiDAR and satellite albedo data to assist forest managers in the development of ecosystem-specific management actions aimed at reducing wildfire damage and promote ecosystem resilience.

76-year decline and recovery of aspen mediated by contrasting fire regimes: Long-unburned, infrequent and frequent mixed-severity wildfire.

Quaking aspen (Populus tremuloides) is a valued, minor component on northeastern California landscapes. It provides a wide range of ecosystem services and has been in decline throughout the region for the last century. This decline may be explained partially by the lack of fire on the landscape due to heavier fire suppression, as aspen benefit from fire that eliminates conifer competition and stimulates reproduction through root suckering. However, there is little known about how aspen stand area changes in response to overlapping fire. Our study area in northeastern California on the Lassen, Modoc and Plumas National Forests has experienced recent large mixed-severity wildfires where aspen was present, providing an opportunity to study the re-introduction of fire. We observed two time periods; a 52-year absence of fire from 1941 to 1993 preceding a 24-year period of wildfire activity from 1993 to 2017. We utilized aerial photos and satellite imagery to delineate aspen stands and assess conifer cover percent. We chose aspen stands in areas where wildfires overlapped (twice-burned), where only a single wildfire burned, and areas that did not burn within the recent 24-year period. We observed these same stands within the first period of fire exclusion for comparison (i.e., 1941–1993). In the absence of fire, all aspen stand areas declined and all stands experienced increases in conifer composition. After wildfire, stands that burned experienced a release from conifer competition and increased in stand area. Stands that burned twice or at high severity experienced a larger removal of conifer competition than stands that burned once at low severity, promoting expansion of aspen stand area. Stands with less edge:area ratio also expanded in area more with fire present. Across both time periods, stand movement, where aspen stand footprints were mostly in new areas compared to footprints of previous years, was highest in smaller stands. In the fire exclusion period, smaller stands exhibited greater loss of area and changes in location (movement) than in the return of fire period, highlighting their vulnerability to loss via succession to conifers in the absence of disturbances that provide adequate growing space for aspen over time.

Changes in the Structure of Assemblages of Three Liolaemus lizards (Iguania, Liolaemidae) in a Protected Area of South-Central Chile Affected by a Mixed-Severity Wildfire

The use of space by sympatric lizards was assessed in a protected area in south central Chile that was affected by a wildfire three years prior. Through systematic monitoring in plots with varying degrees of severity, the abundance of species was counted in each treatment (low severity, medium severity, high severity and unburned control), and were, in turn, subdivided into different microhabitats (ground, trunks and trees). The microhabitats were differentiated by the level of damage suffered by the vegetation as a consequence of the wildfire. Of the three species recorded, it was observed that the presence of Liolaemus tenuis was linked to sites with less fire damage, disappearing in high severity sites. In contrast, L. pictus displayed a more generalist use of microhabitats, with its presence being similar in the different treatments. On the other hand, L. lemniscatus showed a predominant use of the ground, which became more evident in the most severe sites. The pattern found are discussed, as well the influence of fire in reshaping environments.

Examining post-fire vegetation recovery with Landsat time series analysis in three western North American forest types

BackgroundFew studies have examined post-fire vegetation recovery in temperate forest ecosystems with Landsat time series analysis. We analyzed time series of Normalized Burn Ratio (NBR) derived from LandTrendr spectral-temporal segmentation fitting to examine post-fire NBR recovery for several wildfires that occurred in three different coniferous forest types in western North America during the years 2000 to 2007. We summarized NBR recovery trends, and investigated the influence of burn severity, post-fire climate, and topography on post-fire vegetation recovery via random forest (RF) analysis.ResultsNBR recovery across forest types averaged 30 to 44% five years post fire, 47 to 72% ten years post fire, and 54 to 77% 13 years post fire, and varied by time since fire, severity, and forest type. Recovery rates were generally greatest for several years following fire. Recovery in terms of percent NBR was often greater for higher-severity patches. Recovery rates varied between forest types, with conifer−oak−chaparral showing the greatest NBR recovery rates, mixed conifer showing intermediate rates, and ponderosa pine showing slowest rates. Between 1 and 28% of patches had recovered to pre-fire NBR levels 9 to 16 years after fire, with greater percentages of low-severity patches showing full NBR recovery.Precipitation decreased and temperatures generally remained the same or increased post fire. Pre-fire NBR and burn severity were important predictors of NBR recovery for all forest types, and explained 2 to 6% of the variation in post-fire NBR recovery. Post-fire climate anomalies were also important predictors of NBR recovery and explained an additional 30 to 41% of the variation in post-fire NBR recovery.ConclusionsLandsat time series analysis was a useful means of describing and analyzing post-fire vegetation recovery across mixed-severity wildfire extents. We demonstrated that a relationship exists between post-fire vegetation recovery and climate in temperate ecosystems of western North America. Our methods could be applied to other burned landscapes for which spatially explicit measurements of post-fire vegetation recovery are needed.

Relationships between Wildfire Burn Severity, Cavity-Nesting Bird Assemblages, and Habitat in an Eastern Ponderosa Pine Forest

Historically, eastern ponderosa pine (Pinus ponderosa) forests were described as sparse patches of old-growth trees maintained by frequent, low-severity fires; however, in recent decades, there have been a number of large mixed-severity wildfires throughout the range of these forests. Wildlife responses to severe fire disturbance in eastern ponderosa pine forests are not well understood. Our study investigates how cavity-nesting bird species in an eastern ponderosa pine forest are impacted by burn severity. The objectives of our study were to: (1) identify the community composition of cavity-nesting birds in a 27 y old burn of mixed severity, (2) assess how habitat variables important to cavity-nesting birds differ in the mixed-severity fire, and (3) determine what habitat variables best predict bird occurrence 27 y after mixed-severity fire. We surveyed 56 sites across four burn severity classes, ranging from unburned to severely burned forest, in the Pine Ridge region of Nebraska. We measured multiple habitat characteristics (tree and snag diameter at breast height (DBH), coarse woody debris (CWD), tree and snag density, shrub height, and shrub cover) in May–August 2016 and conducted bird count surveys between 25 May and 8 June 2016. Cavity-nesting bird species' occurrence varied among the burn severity variables. Burn severity class (unburned, low severity, moderate severity, high severity) was a significant predictor of habitat characteristics for cavity-nesting birds, including tree density, snag density, mean snag DBH, variance in DBH, and CWD, which also was the best indicator of cavity-nesting bird community composition. We report evidence that mixed-severity wildfires in eastern ponderosa pine forests create variation in habitat characteristics and cavity-nesting bird occurrence.

Mapping and exploring variation in post-fire vegetation recovery following mixed severity wildfire using airborne LiDAR.

There is a public perception that large high-severity wildfires decrease biodiversity and increase fire hazard by homogenizing vegetation composition and increasing the cover of mid-story vegetation. But a growing literature suggests that vegetation responses are nuanced. LiDAR technology provides a promising remote sensing tool to test hypotheses about post-fire vegetation regrowth because vegetation cover can be quantified within different height strata at fine scales over large areas. We assess the usefulness of airborne LiDAR data for measuring post-fire mid-story vegetation regrowth over a range of spatial resolutions (10×10m, 30×30m, 50×50m, 100×100m cell size) and investigate the effect of fire severity on regrowth amount and spatial pattern following a mixed severity wildfire in Warrumbungle National Park, Australia. We predicted that recovery would be more vigorous in areas of high fire severity, because park managers observed dense post-fire regrowth in these areas. Moderate to strong positive associations were observed between LiDAR and field surveys of mid-story vegetation cover between 0.5-3.0m. Thus our LiDAR survey was an apt representation of on-ground vegetation cover. LiDAR-derived mid-story vegetation cover was 22-40% lower in areas of low and moderate than high fire severity. Linear mixed-effects models showed that fire severity was among the strongest biophysical predictors of mid-story vegetation cover irrespective of spatial resolution. However much of the variance associated with these models was unexplained, presumably because soil seed banks varied at finer scales than our LiDAR maps. Dense patches of mid-story vegetation regrowth were small (median size 0.01ha) and evenly distributed between areas of low, moderate and high fire severity, demonstrating that high-severity fires do not homogenize vegetation cover. Our results are relevant for ecosystem conservation and fire management because they: indicate that native vegetation are responsive and resilient to high-severity fire, and show the usefulness of remote sensing tools such as LiDAR to monitor post-fire vegetation recovery over large areasinsitu.

Resilience of California Black Oak Experiencing Frequent Fire: Regeneration Following Two Large Wildfires 12 Years Apart

Historically, oak woodlands in western North America were maintained by frequent fire that killed competing conifers. Today, these woodlands are often in decline as competition from conifers intensifies. Among oak species affected is the ecologically important California black oak (Quercus kelloggii Newberry). Within its range, large high-severity wildfires have become more common. We examined responses of black oak to two mixed-severity wildfires 12 years apart (2000 Storrie Fire and 2012 Chips Fire reburn). Regeneration was examined in relation to fire severity as measured by the Relative differenced Normalized Burn Ratio (RdNBR). We found that the RdNBR of the Storrie Fire was a useful predictor of the RdNBR of the Chips Fire reburn, suggesting that effects of the Storrie Fire on vegetation influenced fire behavior in the Chips reburn (t12 = 2.892, P = 0.014, n =14, r = 0.641). After experiencing a second top-kill (complete cambium mortality above the root collar) in the Chips reburn, 95 % (99 of 104) of black oak sprout clumps resprouted. Twelve years after the Storrie Fire, we found lower proportions of sprout clumps produced acorns in places where more overstory trees survived the fire (t5 = −3.023, P = 0.029, n = 7, r = 0.804). After both fires, the crown volume of entire sprout clumps was lower in areas of higher live overstory tree basal area (Storrie Fire: t5 = 2.527, P = 0.053, n = 7, r = 0.749; Chips reburn: t5 = −3.597, P = 0.016, n = 7, r = 0.849). Our finding that most black oak survived successive top-kill from repeat fire suggested that repeated high-severity or mixed-severity fire is not an immediate threat to black oak presence on the landscape. Our findings also suggest that, if high-severity fire is followed by historically normal fire return intervals, rapidly regenerating black oak may be favored over conifers and recover from decline.

Historical Northern spotted owl habitat and old-growth dry forests maintained by mixed-severity wildfires

Reconstructing historical habitat could help reverse declining animal populations, but detailed, spatially comprehensive data are rare. For example, habitat for the federally threatened Northern spotted owl (NSO; Strix occidentalis caurina) was thought historically rare because low-severity fires kept forests open and habitat restricted to fire refugia, but spatial historical data are lacking. Here I use public land-surveys to spatially reconstruct NSO habitat and old-growth forests in dry forests in Oregon’s Eastern Cascades in the late-1800s. I used reconstructions of forest structure across about 280,000 ha, including 9,605 tree records and 2,180 section-line descriptions. I was able to reconstruct likely NSO nest trees, nest stands, and foraging and roosting habitat, based on modern NSO habitat studies. Historical nest stands, including sufficient nest trees, were predicted across 22–39 % and foraging and roosting habitat across 11–68 % of the study area, thus neither were rare. More habitat than expected occurred in forests with preceding mixed-severity fires. Early post-fire succession produced foraging and roosting habitat. Mid- to late-succession produced nesting habitat. Late-succession after high-severity fires can also provide NSO habitat. Old-growth forests, covering 76 % of study-area forests, also likely link to preceding mixed-severity fires. Mixed- and high-severity fires strongly shaped historical dry forests and produced important components of historical NSO habitat. Focus on short-term loss of nest sites and territories to these fires is mis-directed. Fuel treatments to reduce these natural fires, if successful, would reduce future habitat of the NSO in dry forests.

Effects of wildfire on a pine stand in the Bohemian Switzerland National Park

The pine stand in the Havran&amp;iacute; Sk&amp;aacute;la locality in the Bohemian Switzerland National Park was affected by an extensive mixed-severity wildfire in summer 2006. The fire severity, fire type and fire extent were assessed by various fire severity measures collected in the field (mean bole char height on stems on sample plots, content of oxidizable C and total N at a soil depth of 0&amp;ndash;5 cm), as well as by classification and filtering of green canopy cover from time series of aerial photographs acquired before the fire (2005), soon after the fire (2006) and one year after the fire (2007). The specific image analyses made it possible to uncover the spatial and temporal pattern of the stand defoliation. The central part of the site was mainly affected by the crown fire and thus defoliated substantially right during the fire. On the contrary, the peripheral part of the site was mostly affected by low-severity ground fire and therefore defoliated progressively one year later. All the fire severity measures used were well related. &amp;nbsp;

Canopy damage to conifer plantations within a large mixed-severity wildfire varies with stand age

The 2002 Biscuit Fire burned at mixed-severities encompassing over 200,000 ha of publicly owned forestland, including more than 8300 ha of conifer plantations. We used pre- and post-fire digital aerial photography to examine how the level of canopy damage varied within these plantations in relation to topography, weather, vegetation-cover, and management history, with an emphasis on the age of the plantation. We examined 198 plantations that varied widely in age (5–47 years), size (1.25–47 ha), and landscape context. The average level of canopy damage within the plantations was 77%. Based on Random Forest variable importance values, plantation age was the best predictor of canopy damage. Average annual precipitation, elevation and topographic position were ranked second, third, and fourth, respectively. A model selection procedure, using geo-statistical regression models and Akaike’s information criterion, corroborated the importance of plantation age relative to the other predictors tested and also suggested that the influence of age varied over time. The top ranked regression model indicated that the level of canopy damage reached its maximum around age 15 and stayed relatively high until age 25 before declining.

Growth Response of Pinus ponderosa following a Mixed-Severity Wildfire in the Black Hills, South Dakota

Abstract In late summer 2000 the Jasper Fire burned ∼34,000 ha of ponderosa pine forest in the Black Hills of South Dakota. Although regarded as a catastrophic event, the Jasper Fire left a mosaic of fire severity across the landscape, with live trees present in areas burned under low andmoderate fire severity. In October 2005, we cored 96 trees from unburned, low-severity, and moderate-severity stands and assessed whether tree growth differed among fire severity classes during the 5 years postfire. We observed no differences in basal area increment (BAI) 10 years prefireamong fire severities with BAI averaging 9.6 cm2 per year. Despite severe drought conditions, BAI in moderate severity sites 2 years postfire was 58% greater than in unburned and low-severity stands. Although significant, this growth increase was short-lived. Three, 4, and 5 yearspostfire, no differences in growth among unburned, low-severity, and moderate-severity sites were detected, as BAI averaged 8.3, 7.5, and 7.0 cm2, respectively. The lack of a consistent and prolonged growth response suggests that the Jasper Fire did not result in any short-termchanges in growth patterns. Data extending beyond 5 years postfire are required to infer potential long-term changes in tree growth and productivity.