Low Burn Severity Research Articles

EFFECTS OF DROUGHT AND FIRE ON NATIVE STIPA PULCHRA (POACEAE) RECOVERY IN SOUTHERN CALIFORNIA GRASSLANDS

Mediterranean-type climate California experiences both frequent wildfires and periodic drought. Climate change models predict increased severity of drought, and wildfire size and frequency, leading to concern about the ability of some plant species to recover to pre-fire conditions when wildfires and drought coincide. During exceptional drought, drought-adapted native vegetation, such as perennial native grassland, can experience substantial die-off. Here we use three post-fire case studies in southern California to assess the combined effects of fire and drought on the resilience of a native perennial bunchgrass, Stipa pulchra Hitchc. (Poaceae). We hypothesized that resilience to fire, assessed as post-fire survival, resprouting and fecundity (i.e., number of flowering plants and inflorescences), would decrease if the fire occurred during a drought. Unburned (control) sites had about double the survival and resprouting, and about three times the fecundity compared to moderate-severity burn sites. Resprouting and fecundity in the low-severity burn sites was about twice that of moderate-severity burn sites, and survival was five times higher. Responses to two springtime fires that occurred during drought were similar (average mortality 37%), in contrast to a fall fire with no drought (6%). We cannot separate the relative contribution of drought effects from those of the time of year (spring vs. fall), burn severity, and other site factors. However, moderate-severity burns, in combination with drought, decreased survival, resprouting, and fecundity of S. pulchra.

Water and elevation are more important than burn severity in predicting bat activity at multiple scales in a post-wildfire landscape.

Bats are among the most widespread mammals on Earth, and are subject to habitat change, loss, and other disturbances such as fire. Wildfire causes rapid changes in vegetation that affect habitat use. However, the spatial scale at which these changes affect bats depends on their use of habitat elements. Three years post wildfire, we assessed how burn severity, water, landform type, elevation, vegetation type, and roads affected use by bats of a forest landscape at multiple spatial scales. We deployed acoustic detectors at randomly selected locations within a 217,712 ha wildfire boundary in Arizona. We classified echolocation calls to species or group and calculated an activity index by adjusting the calls per hour. We conducted a multi-scale analysis of landscape structure and composition around each location from a 90 to 5760 m radius. No scale was selected preferentially by any species or group. Stream density and elevation range were more important predictors for species groups than burn severity. When burn severity was a predictor, agile species had higher activity in areas that were unburned or had low severity burn. A heterogeneous landscape composed of high, medium, and low burn severity patches within a forest altered by large wildfires provided habitat for different bat species, but water density and range in elevation were more important for predicting bat habitat use than fire severity in this arid landscape. More than one spatial scale, representing local to landscape levels, should be considered in managing habitat for bats. In arid areas, such as the western United States, maintaining reliable water sources is important for bats. Managing these factors at multiple spatial scales will benefit bat species with different wing morphologies, echolocation call types, and habitat selections.

120 Terahertz Spectral Imaging for Burn Depth Determination in an in Vivo Porcine Scald Model

Abstract Introduction Clinical evaluation of burns results in about 50–70% accuracy in predicting the final burn progression and healing outcome in partial thickness burns. Early and accurate assessment of burn wounds is critical for determining the course of clinical management. Terahertz (THz) spectral imaging is a promising biomedical imaging modality that has been used to quantitatively determine burn severity in acute rodent models. Here, we hypothesized that the new THz modality can determine burn depth and predict the wound healing outcome of injuries using a standardized porcine model. We developed a handheld THz instrument to obtain diagnostic images from large animal burns with varying severities. The results showed that the THz imaging can differentiate between different burn groups defined by injury depth on days 1–5 post-burn, and predict their ultimate outcome defined by reepithelialization during a 28-day study period (1-way ANOVA, p< 0.05). Methods Multiple 1 inch diameter standardized cutaneous burns were created (n = 20–24 per pig) in 3 anesthetized female domestic pigs (~32kg) using a circulating heated water in replicates. The temperatures were controlled and kept constant at 95 C degrees using thermosensors, while the duration of exposure was varied between 5, 15, or 25 seconds. Burns were covered with a topical antibiotic ointment and frequent dressing changes were performed for 4 weeks. Daily THz scans were obtained from each burn during the first week, corresponding to the peak of the anti-inflammatory response of the burns. After the initial 5 days, weekly scans were obtained until the ultimate healing outcome was determined by an experienced surgeon and a blinded histopathologist. Periodic punch biopsies were taken to determine burn depth, percentage burns reepithelialized within 21 days, and depth of scar at 28 days. Results Attached figures show representative daily visual and THz images of burns with the associated ROI. Bar plots show mean and standard deviation of spectral amplitude (SA) and spectral slope (SS). Low severity burns showed decreasing SA and increasing SS over time, whereas SS from 25 second burns remained negative and SA increased by day 4. Variation in SS suggests changes in density of skin structure as a result of scattering and changes in SA suggests variations in water content. Detailed statistical analysis is in attached table. Conclusions Using the novel handheld THz scanner, analysis of the spectral slopes signal showed the ability of the new Terahertz imaging modality in differentiating between different burn severities (p < 0.05) and evaluating burn progression. Applicability of Research to Practice THz modality can result in improvement in the accuracy of burn triage, which in turn can lead to better wound healing outcomes, reduction in length of hospital stay and improvement in overall recovery of the patients.

Investigation of bed and den site selection by American black bears (Ursus americanus) in a landscape impacted by forest restoration treatments and wildfires

The combined effects of long-term fire suppression, logging, and overgrazing have negatively impacted many southwestern U.S. forests, resulting in decreased habitat quality for wildlife, and more frequent and severe wildfires. In response, land management agencies are implementing large-scale forest restoration treatments, but data on how wildlife respond to restoration treatments and wildfires are often limited. We investigated bed and den site selection of American black bears (Ursus americanus) using GPS location data and a use/available study design to assess the influence of habitat characteristics, including wildfires, prescribed burns, and thinning treatments on bed and den site selection in the Jemez Mountains, New Mexico. The most supported models suggested that black bears were more likely to select bed sites with a combination of low horizontal visibility (β = −0.007, SE = 0.002; P = 0.002) and high stand basal area (β = 0.013, SE = 0.005; P = 0.004). The highest-ranking model for den site selection indicated that black bears were more likely to select den sites with low horizontal visibility (β = −0.0102, SE = 0.004; P = 0.006). Black bears used all disturbed sites to varying degrees (45% of study area), although 48% of bed sites were located in undisturbed habitat (55% of study area) while only 11% and 2% of bed sites were located in thinned and prescribed burn sites, respectively. Thirty-nine percent of bed sites were located in previous wildfire locations; however, 67% of these sites were in areas with low burn severity. Thirty-eight percent of den sites were located in previously disturbed habitat, 8 of these sites were burned by wildfires. In order to develop effective management plans for black bears, it is essential to understand responses to landscape-scale habitat disturbances due to wildfires and restoration activities, all of which are becoming more prevalent and widespread across southwestern forests. Accounting for the timing, size, and proximity of future restoration efforts would aid in mitigating potential short-term negative effects on black bears.

Still standing: Recent patterns of post-fire conifer refugia in ponderosa pine-dominated forests of the Colorado Front Range.

Forested fire refugia (trees that survive fires) are important disturbance legacies that provide seed sources for post-fire regeneration. Conifer regeneration has been limited following some recent western fires, particularly in ponderosa pine (Pinus ponderosa) forests. However, the extent, characteristics, and predictability of ponderosa pine fire refugia are largely unknown. Within 23 fires in ponderosa pine-dominated forests of the Colorado Front Range (1996–2013), we evaluated the spatial characteristics and predictability of refugia: first using Monitoring Trends in Burn Severity (MTBS) burn severity metrics, then using landscape variables (topography, weather, anthropogenic factors, and pre-fire forest cover). Using 1-m resolution aerial imagery, we created a binary variable of post-fire conifer presence (‘Conifer Refugia’) and absence (‘Conifer Absence’) within 30-m grid cells. We found that maximum patch size of Conifer Absence was positively correlated with fire size, and 38% of the burned area was ≥ 50m from a conifer seed source, revealing a management challenge as fire sizes increase with warming further limiting conifer recovery. In predicting Conifer Refugia with two MTBS-produced databases, thematic burn severity classes (TBSC) and continuous Relative differenced Normalized Burn Ratio (RdNBR) values, Conifer Absence was high in previously forested areas of Low and Moderate burn severity classes in TBSC. RdNBR more accurately identified post-fire conifer survivorship. In predicting Conifer Refugia with landscape variables, Conifer Refugia were less likely during burn days with high maximum temperatures: while Conifer Refugia were more likely on moister soils and closer to higher order streams, homes, and roads; and on less rugged, valley topography. Importantly, pre-fire forest canopy cover was not strongly associated with Conifer Refugia. This study further informs forest management by mapping post-fire patches lacking conifer seed sources, validating the use of RdNBR for fire refugia, and detecting abiotic and topographic variables that may promote conifer refugia.

Field-Validated Burn-Severity Mapping in North Patagonian Forests

Burn severity, which can be reliably estimated by validated spectral indices, is a key element for understanding ecosystem dynamics and informing management strategies. However, in North Patagonian forests, where wildfires are a major disturbance agent, studies aimed at the field validation of spectral indices of burn severity are scarce. The aim of this work was to develop a field validated methodology for burn-severity mapping by studying two large fires that burned in the summer of 2013–2014 in forests of Araucaria araucana and other tree species. We explored the relation between widely used spectral indices and a field burn-severity index, and we evaluated index performance by examining index sensitivity in discriminating burn-severity classes in different vegetation types. For those indices that proved to be suitable, we adjusted the class thresholds and constructed confusion matrices to assess their accuracy. Burn severity maps of the studied fires were generated using the two most accurate methods and were compared to evaluate their level of agreement. Our results confirm that reliable burn severity estimates can be derived from spectral indices for these forests. Two severity indices, the delta normalized burn ratio (dNBR) and delta normalized difference vegetation index (dNDVI), were highly related to the fire-induced changes observed in the field, but the strength of these associations varied across the five different vegetation types defined by tree heights and tree and tall shrub species regeneration strategies. The thresholds proposed in this study for these indices generated classifications with global accuracies of 82% and Kappa indices of 70%. Both the dNBR and dNDVI classification approaches were more accurate in detecting high severity, but to a lesser degree for detecting low severity burns. Moderate severity was poorly classified, with producer and user errors reaching 50%. These constraints, along with detected differences in separability, need to be considered when interpreting burn severity maps generated using these methods.

Predictive habitat suitability models for nesting woodpeckers following wildfire in the Sierra Nevada and Southern Cascades of California

AbstractWoodpeckers are often focal species for informing management of recently burned forests. Snags generated by wildfire provide key nesting and foraging resources for woodpeckers, and nest cavities excavated by woodpeckers are subsequently used by many other species. Habitat suitability models applicable in newly burned forest are important management tools for identifying areas likely to be used by nesting woodpeckers. Here we present and test predictive models for mapping woodpecker nest-site habitat across wildfire locations that can be used to inform post-fire planning and salvage logging decisions. From 2009 to 2016, we monitored 313 nest sites of 4 species—Black-backed Woodpecker (Picoides arcticus), Hairy Woodpecker (Dryobates villosus), White-headed Woodpecker (D. albolarvatus), and Northern Flicker (Colaptes auratus)—from 3 wildfires in the Northern Sierra Nevada and Southern Cascades 1–5 yr after fire. Using these data, we developed habitat suitability index models that compared nest vs. non-nest sites for each species using (1) exclusively remotely sensed covariates, and (2) combinations of remotely sensed and field-collected covariates. We emphasized predictive performance across wildfire locations when selecting models to retain generalizable habitat relationships useful for informing management in newly burned locations. We identified models for all 4 species with strong predictive performance across wildfire locations despite notable variation in conditions among locations, suggesting broad applicability to guide post-fire management in the Sierra Nevada region. Top models for nest-site selection underscored the importance of high burn severity at the local scale, lower burn severity at the 1-km scale, mid-sized nest-tree diameters, and nest trees with broken tops. Models restricted to remotely sensed covariates exhibited similar predictive performance as combination models and are valuable for mapping habitat across entire wildfire locations to help delineate project areas or habitat reserves. Combination models are especially relevant for design of silvicultural prescriptions.

Postfire recruitment failure in Scots pine forests of southern Siberia

Wildfire disturbances effect changes in vegetation communities that in turn influence climate. Such changes in boreal forest ecosystems can persist over decadal time scales or longer. In the ecotone between boreal forest and steppe in the region southeast of Lake Baikal in southern Siberia, shifts between the two vegetation types may be precipitated by variations in site specific conditions, as well as disturbance characteristics such as fire frequency and severity. Warmer, drier conditions in the region have been associated with a decrease in fire return intervals and greater burn severity that may, in turn, drive conversion of forests to steppe vegetation at a greater rate than has occurred prior to the onset of warming and drying. Stand-replacing fires in Pinus sylvestris stands in southern Siberia may lead to recruitment failure postfire, particularly on southwest to west-facing slopes, which are more often dominated by grasses. This study uses a combination of field data and remotely sensed indices of vegetation and moisture to distinguish between recruitment pathways in southern Siberia, and to study the influence of factors related to soils, topography, fire severity and winter snow cover on these.We expected that recruitment success would be associated with lower burn severity (higher NBR), higher greenness (NDVI) and moisture (NDMI), and winter snow (NDSI) postfire. We also expected phenological characteristics to differ among recruitment paths. Prior to burning, our sites are broadly similar in terms of remotely sensed indices of moisture (NDMI), vegetation (NDVI), and winter fractional snow cover (NDSI), but recruitment failure sites are generally drier and less green postfire. Initial differences in greenness and moisture among sites characterized by abundant recruitment (AR), intermediate recruitment (IR) and recruitment failure (RF) become more pronounced over the initial decades postfire. The earliest separability of AR and RF sites using remotely sensed indices occurs in the winter months 3–4 years postfire, during which time NDSI is highest for AR sites and lowest for RF. Although seasonality was important with regard to distinguishing among AR, IR and RF index values, the timing of phenological events such as start and end of season did not differ significantly among the sites.

Spatiotemporal variability of fire characteristics affect animal responses in pyric landscapes

BackgroundBehavioral responses are the most immediate ways animals interact with their environment, and are primary mechanisms by which individuals mitigate mortality risk while ensuring reproductive success. In disturbance-driven landscapes, animals must adjust behaviors both spatially and temporally to maximize individual fitness. Prescribed fire is an important ecosystem driver in many coniferous forests, as fire cycles nutrients, creates spatially heterogeneous distributions in quantity and quality of forage and cover, and provides opportunities for fire-adapted taxa. Because fire immediately shifts resource distribution, and fire characteristics may drive behavioral responses to recent burns, we examined behavioral responses of 105 Global Positioning System (GPS)-tagged female eastern wild turkeys (Meleagris gallopavo silvestris Linnaeus, 1758) to fire application at three sites in southeastern United States. We used satellite-derived imagery to calculate burn severity and burn heterogeneity. We also calculated distance to adjacent unburned stands and time-since-fire at GPS locations of each turkey while inside burned stands. We used behavioral change point analyses to estimate behavioral state for turkeys using burned areas, and generalized linear mixed models to estimate how fire characteristics affected turkey behavior inside burned areas.ResultsTurkeys focused their use in less severely burned areas, and were less likely to use the interior of burned areas. Turkeys were more likely to forage and rest in less severely burned areas, suggesting that managers should apply prescribed fire frequently enough to promote low-severity burns. We found that, as distance to neighboring unburned areas increased, turkeys were more likely to walk through the interiors of recently burned areas, as opposed to resting or foraging in them, suggesting that the interiors of some burn units are less suitable habitat in the year that prescribed fire is applied. Our findings suggest that prescribed fire applied to ensure that interior areas of burned stands are <250 m from adjacent unburned stands or to stands shaped to maximize edge-to-area ratios likely create more suitable conditions for foraging and resting.ConclusionsThe application and spatial arrangement of prescribed fire, even in frequently burned areas, affect animal response and behaviors. Prescribed fire regimes should be created in recognition that sizes of burned stands and fire severity, along with determinants of fire severity (e.g., fuel loads, return intervals, timing), are important influences on animal behavior in frequent-fire-managed landscapes.

Short- and long-term effects of ponderosa pine fuel treatments intersected by the Egley Fire Complex, Oregon, USA

BackgroundFuel treatments are widely used to alter fuels in forested ecosystems to mitigate wildfire behavior and effects. However, few studies have examined long-term ecological effects of interacting fuel treatments (commercial harvests, pre-commercial thinnings, pile and burning, and prescribed fire) and wildfire. Using annually fitted Landsat satellite-derived Normalized Burn Ratio (NBR) curves and paired pre-fire treated and untreated field sites, we tested changes in the differenced NBR (dNBR) and years since treatment as predictors of biophysical attributes one and nine years after the 2007 Egley Fire Complex in Oregon, USA. We also assessed short- and long-term fuel treatment impacts on field-measured attributes one and nine years post fire.ResultsOne-year post-fire burn severity (dNBR) was lower in treated than in untreated sites across the Egley Fire Complex. Annual NBR trends showed that treated sites nearly recovered to pre-fire values four years post fire, while untreated sites had a slower recovery rate. Time since treatment and dNBR significantly predicted tree canopy and understory green vegetation cover in 2008, suggesting that tree canopy and understory vegetation cover increased in areas that were treated recently pre fire. Live tree density was more affected by severity than by pre-fire treatment in either year, as was dead tree density one year post fire. In 2008, neither treatment nor severity affected percent cover of functional groups (shrub, graminoid, forb, invasive, and moss–lichen–fungi); however, by 2016, shrub, graminoid, forb, and invasive cover were higher in high-severity burn sites than in low-severity burn sites. Total fuel loads nine years post fire were higher in untreated, high-severity burn sites than any other sites. Tree canopy cover and density of trees, saplings, and seedlings were lower nine years post fire than one year post fire across treatments and severity, whereas live and dead tree basal area, understory surface cover, and fuel loads increased.ConclusionsPre-fire fuel treatments effectively lowered the occurrence of high-severity wildfire, likely due to successful pre-fire tree and sapling density and surface fuels reduction. This study also quantified the changes in vegetation and fuels from one to nine years post fire. We suggest that low-severity wildfire can meet prescribed fire management objectives of lowering surface fuel accumulations while not increasing overstory tree mortality.

Improving burn severity retrieval by integrating tree canopy cover into radiative transfer model simulation

Burn severity mapping greatly informs fire management and can be used to predict post-fire vegetation recovery. Satellite remote sensing is a cost-effective method for estimating burn severity, providing a comprehensive spatially explicit view of whole landscapes. However, the proportion of tree canopy cover (TCC) affects the reflectance signal, obscuring background char and ash. Consequently, traditional optical satellite remote sensing methods that do not account for variation in TCC misclassify burn severity, especially in areas with extremely low or high TCC. In this study, TCC data served to parameterize and constrain the inversion of the Forest Reflectance and Transmittance (FRT) radiative transfer model (RTM) to alleviate spectral confusion when retrieving burn severity. The methodology was evaluated using field measurements of burn severity for a series of wildfires in the fire-prone tropical savannas of northern Australia and the western United States. Burn severity classes were used for Australia while the Composite Burn Index (CBI) for US. Reflectance data from Sentinel-2A Multi-Spectral Instrument (MSI) and Landsat-5 Thematic Mapper (TM) corresponding to post-fire field survey dates were used to retrieve burn severity using FRT RTM (with and without using TCC information in its parameterization and inversion) and two standard empirical burn indices, dNBR and RdNBR, for comparison. Using FRT RTM without TCC constraint produced an overestimation for low burn severity in regions with low TCC and an underestimation for moderate and high burn severity in regions with high TCC. Burn severity estimation accuracy significantly improved by integrating TCC in the parameterization and inversion of FRT RTM. The overall accuracy in northern Australia increased from 65% to 81%, and the kappa coefficient increased from 0.35 to 0.55. In the western United States, R2 between estimated and observed CBI, increased from 0.33 to 0.54, root mean square error (RMSE) reduced from 0.53 to 0.43, and in all instances, the method performed better than dNBR and RdNBR. The method used in this study achieved more accurate burn severity mapping, thus assisting land managers to better understand post-fire vegetation resilience and forest management.

The psychosocial complexities of acute burn patients in an Australian trauma hospital

IntroductionPsychosocial risk and protective factors specific to acute burn patients have been shown to impact on longer-term health outcomes. Yet the nature and impact of such factors throughout the acute hospital admission phase have not been extensively examined to date. This study analysed the psychosocial pre-admission, hospitalisation and discharge factors for a sample of burn patients at an Australian specialist acute burns unit (The Alfred) and the relationship with their admission length. MethodsA retrospective audit was undertaken of psychosocial factors documented in patient medical records, Victorian Adult Burns Service registry data, and social work files (January–December 2014). ResultsTwo hundred and forty-nine patients were identified, with a mean age of 42.83 years and a preponderance of men (73.9%). The majority (71%) had a low burn severity (<10%), and an average of eight psychosocial factors. Independent of the severity of the burn, two psychosocial domains were strongly predictive of length of stay — coping with treatment and discharge planning — along with pre-existing psychosocial factors and family support. ConclusionA diversity of psychosocial factors was identified, highlighting the clinical complexity of this patient group. Given three domains of admission-related psychosocial factors were predictive of the length of patient stay, more targeted psychosocial interventions in these areas may ensure patients and their families are supported more effectively throughout an admission, and length of stay costs may also be reduced.

Vegetation and Soil Fire Damage Analysis Based on Species Distribution Modeling Trained with Multispectral Satellite Data

Forest managers demand reliable tools to evaluate post-fire vegetation and soil damage. In this study, we quantify wildfire damage to vegetation and soil based on the analysis of burn severity, using multitemporal and multispectral satellite data and species distribution models, particularly maximum entropy (MaxEnt). We studied a mega-wildfire (9000 ha burned) in North-Western Spain, which occurred from 21 to 27 August 2017. Burn severity was measured in the field using the composite burn index (CBI). Burn severity of vegetation and soil layers (CBIveg and CBIsoil) was also differentiated. MaxEnt provided the relative contribution of each pre-fire and post-fire input variable on low, moderate and high burn severity levels, as well as on all severity levels combined (burned area). In addition, it built continuous suitability surfaces from which the burned surface area and burn severity maps were built. The burned area map achieved a high accuracy level (κ = 0.85), but slightly lower accuracy when differentiating the three burn severity classes (κ = 0.81). When the burn severity map was validated using field CBIveg and CBIsoil values we reached lower κ statistic values (0.76 and 0.63, respectively). This study revealed the effectiveness of the proposed multi-temporal MaxEnt based method to map fire damage accurately in Mediterranean ecosystems, providing key information to forest managers.

Traditional knowledge of fire use by the Confederated Tribes of Warm Springs in the eastside Cascades of Oregon

We examined traditional knowledge of fire use by the Ichishikin (Sahaptin), Kitsht Wasco (Wasco), and Numu (Northern Paiute) peoples (now Confederated Tribes of Warm Springs, CTWS) in the eastside Cascades of Oregon to generate insights for restoring conifer forest landscapes and enhancing culturally-valued resources. We examined qualitative and geospatial data derived from oral history interviews, participatory GIS focus groups, archival records, and historical forest surveys to characterize cultural fire regimes (CFRs) –an element of historical fire regimes– of moist mixed conifer (MMC), dry mixed conifer (DMC), and shrub-grassland (SG) zones. Our ethnohistorical evidence indicated a pronounced cultural fire regime in the MMC zone, but not in the two drier zones. The CFR of the MMC zone was characterized by frequent (few-year recurrence), low-severity burns distributed in a shifting pattern. This regime helped to maintain forest openings created by previous ignitions, resulting from lightning or possibly human-set, that had burned large areas. The CFR was influenced by the CTWS traditional knowledge system, which consisted of four elements: fire use and associated resource tending practices, tribal ecological principles, the seasonal round (the migratory pattern to fulfill resource needs), and culture. Thinleaf huckleberry (Vaccinium membranaceum), a cultural keystone species, occurs primarily in the MMC zone and was a principle focus of traditional fire use of the CTWS peoples. Fire was deployed to maintain shrub productivity and site access for harvesting. Cessation of fire use by ∼1940 has caused a decline in huckleberry productivity throughout much of the historical harvest zone. Our findings about CFR scale show how a nested, multi-level framework (patch- and landscape-levels) may be employed to reintroduce fire and thereby promote forest restoration and enhance culturally-valued resources. Our findings also highlight the utility of engaging the communities that hold traditional knowledge in the forest management and planning process.

Histogram Matching of Sentinel-2 Spectral Information to Enhance Planetscope Imagery for Effective Wildfire Damage Assessment

In abrupt fire disturbances, high quality images suitable for wildfire damage assessment can be difficult to acquire. Quantifying wildfire burn area and severity are essential measures for quick short-term disaster response and efficient long-term disaster restoration. Planetscope (PS) imagery offers 3 m spatial and daily temporal resolution, which can overcome the spatio-temporal resolution tradeoff of conventional satellites, albeit at the cost of spectral resolution. This study investigated the potential of augmenting PS imagery by integrating the spectral information from Sentinel-2 (S2) differenced Normalized Burn Ratio (dNBR) to PS differenced Normalized Difference Vegetation Index (dNDVI) using histogram matching, specifically for wildfire burn area and severity assessment of the Okgye wildfire which occurred on April 4th, 2019. Due to the difficulty in acquiring reference data, the results of the study were compared to the wildfire burn area reported by Ministry of the Interior and Safety. The burn area estimates from this study demonstrated that the histogram-matched (HM) PS dNDVI image produced more accurate burn area estimates and more descriptive burn severity intervals in contrast to conventional methods using S2. The HM PS dNDVI image returned an error of only 0.691% whereas the S2 dNDVI and dNBR images overestimated the wildfire burn area by 5.32% and 106%, respectively. These improvements using PS were largely due to the higher spatial resolution, allowing for the detection of sparsely distributed patches of land and narrow roads, which were indistinguishable using S2 dNBR. In addition, the integration of spectral information from S2 in the PS image resolved saturation effects in areas of low and high burn severity.

Short communication: Surface charring from prescribed burning has minimal effects on soil bacterial community composition two weeks post-fire in jack pine barrens

Prescribed fire – the intentional use of fire to help achieve a land management goal – is becoming increasingly common as a land management practice. Soil physical, chemical, and biological properties can be affected by prescribed fires, but depend on the fire, soil type, residence time and frequency, and may not be changed substantially in low-severity burns. Here, we examined soil bacterial community composition immediately post-fire (15 days) in a sandy jack pine barrens soil in Wisconsin, USA. Soil bacterial communities clustered significantly by sample site (p < 0.001) and by soil horizon (p = 0.048), but not by whether or not soil samples were visibly burned. There were also no significant differences in total relative abundance at the phylum level in visibly burned vs. not visibly burned soils, and only two significant differences in abundance or variability of individual taxa. Soil properties remained unchanged post-fire and the fire was visibly patchy, suggesting that the low severity prescribed fire most likely had a minimal soil heating effect. Therefore, we suggest the minimal bacterial community composition shifts seen in this study were likely mediated more by plants than by direct heat-killing or changes to soil properties.

Burn severity analysis in Mediterranean forests using maximum entropy model trained with EO-1 Hyperion and LiDAR data

All ecosystems and in particular ecosystems in Mediterranean climates are affected by fires. Knowledge of the drivers that most influence burn severity patterns as well an accurate map of post-fire effects are key tools for forest managers in order to plan an adequate post-fire response. Remote sensing data are becoming an indispensable instrument to reach both objectives. This work explores the relative influence of pre-fire vegetation structure and topography on burn severity compared to the impact of post-fire damage level, and evaluates the utility of the Maximum Entropy (MaxEnt) classifier trained with post-fire EO-1 Hyperion data and pre-fire LiDAR to model three levels of burn severity at high accuracy. We analyzed a large fire in central-eastern Spain, which occurred on 16–19 June 2016 in a maquis shrubland and Pinus halepensis forested area. Post-fire hyperspectral Hyperion data were unmixed using Multiple Endmember Spectral Mixture Analysis (MESMA) and five fraction images were generated: char, green vegetation (GV), non-photosynthetic vegetation, soil (NPVS) and shade. Metrics associated with vegetation structure were calculated from pre-fire LiDAR. Post-fire MESMA char fraction image, pre-fire structural metrics and topographic variables acted as inputs to MaxEnt, which built a model and generated as output a suitability surface for each burn severity level. The percentage of contribution of the different biophysical variables to the MaxEnt model depended on the burn severity level (LiDAR-derived metrics had a greater contribution at the low burn severity level), but MaxEnt identified the char fraction image as the highest contributor to the model for all three burn severity levels. The present study demonstrates the validity of MaxEnt as one-class classifier to model burn severity accurately in Mediterranean countries, when trained with post-fire hyperspectral Hyperion data and pre-fire LiDAR.

Effects of fire and its severity on occupancy of bats in mixed pine-oak forests

Prescribed burning has become more common for the management of eastern forests in North America, so understanding if and how foraging bats respond to structural changes generated by fire is of increasing importance. Our objective was to investigate the effects of post-fire landscape conditions on the occurrence of foraging bats in mixed forests of the Cumberland Plateau physiographic region. We deployed Anabat II bat detectors in 164 paired burned and unburned forest sites for ≥2 nights from mid-May through August 2014 and 2015 to monitor bat foraging and commuting habitat use. We conducted vegetation surveys to quantify site-specific structural characteristics, which indicated that measures of structure were significantly lower in burned sites than unburned sites. We used Program Presence to test a priori hypotheses of species-specific probability of detection and site occupancy related to weather, burn history (i.e., site burned within the past 10 years or unburned), and site and landscape characteristics. Bats were detected at 94% of burned sites and 83% of unburned sites. Probability of detection was affected by weather conditions, vegetative structure, and burn history for most species. Occupancy for all species/species groups examined was positively associated with burning and generally associated with lower vegetative structure. Although burn severity did not affect most species groups, occupancy of Myotis species and tri-colored bats (Perimyotis subflavus) was lower in sites that received moderate severity burns than in sites that received low severity burns. Therefore, while prescribed fire may provide vegetative structure conducive to efficient foraging for all bats of the Cumberland Plateau, our results demonstrate that retaining some unburned forests while creating mosaics of lower and higher severity burns across the landscape will result in favorable foraging conditions for all resident bat species.

Severe wildfire exposes remnant peat carbon stocks to increased post-fire drying

The potential of high severity wildfires to increase global terrestrial carbon emissions and exacerbate future climatic warming is of international concern. Nowhere is this more prevalent than within high latitude regions where peatlands have, over millennia, accumulated legacy carbon stocks comparable to all human CO2 emissions since the beginning of the industrial revolution. Drying increases rates of peat decomposition and associated atmospheric and aquatic carbon emissions. The degree to which severe wildfires enhance drying under future climates and induce instability in peatland ecological communities and carbon stocks is unknown. Here we show that high burn severities increased post-fire evapotranspiration by 410% within a feather moss peatland by burning through the protective capping layer that restricts evaporative drying in response to low severity burns. High burn severities projected under future climates will therefore leave peatlands that dominate dry sub-humid regions across the boreal, on the edge of their climatic envelopes, more vulnerable to intense post-fire drying, inducing high rates of carbon loss to the atmosphere that amplify the direct combustion emissions.

Wildfire burned soil organic horizon contribution to runoff and infiltration in a Pinus pinaster forest soil

ABSTRACTThe immediate effects of a low soil burn severity wildfire on hydrological parameters and soil erosion were evaluated in a Pinus pinaster Ait. stand by means of rainfall simulations (140 mm h−1). The unburned forest soil was repellent at the mineral surface (100%) at the same degree as the burned ones. The diameter of soil aggregates and the particle size distribution did not differ between burned and unburned soils. The mean storage capacity of the unburned soil organic layer was 0.94–4.85 mm m−2 from the litter to the duff layers. The corresponding values for the capillary capacity were from 7.11 mm to 6.72 mm. In the burned plots, these figures were 1.42 mm m−2 for the mean storage capacity and 5.9 mm for the capillary capacity. The burned plots recorded significantly lower infiltration rates (29 mm h−1) and higher runoff (111 mm) and sediment yields (20.8 g m− 2) compared to the unburned controls. The characteristics of the soil organic layer significantly affected the infiltration rate and runoff volume. In a subsequent experiment, the remaining organic layer was completely removed and a new rainfall simulation was carried out. In unburned soils decreases in the infiltration rate and increases in the runoff volume were recorded with no significant changes in the sediment yields. In the burned plots, removal of the duff layer only led to a significant increase in soil erosion (20.8–51.4 g m−2). The above information could be used to help plan post-fire stabilization actions.