ResearchPad - wildfires Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Development and evaluation of habitat suitability models for nesting white-headed woodpecker (<i>Dryobates albolarvatus</i>) in burned forest]]> Salvage logging in burned forests can negatively affect habitat for white-headed woodpeckers (Dryobates albolarvatus), a species of conservation concern, but also meets socioeconomic demands for timber and human safety. Habitat suitability index (HSI) models can inform forest management activities to help meet habitat conservation objectives. Informing post-fire forest management, however, involves model application at new locations as wildfires occur, requiring evaluation of predictive performance across locations. We developed HSI models for white-headed woodpeckers using nest sites from two burned-forest locations in Oregon, the Toolbox (2002) and Canyon Creek (2015) fires. We measured predictive performance by developing one model at each of the two locations and quantifying discrimination of nest from reference sites at two other wildfire locations where the model had not been developed (either Toolbox or Canyon Creek, and the Barry Point Fire [2011]). We developed and evaluated Maxent models based on remotely sensed environmental metrics to support habitat mapping, and weighted logistic regression (WLR) models that combined remotely sensed and field-collected metrics to inform management prescriptions. Both Maxent and WLR models developed either at Canyon Creek or Toolbox performed adequately to inform management when applied at the alternate Toolbox or Canyon Creek location, respectively (area under the receiver-operating-characteristic curve [AUC] range = 0.61–0.72) but poorly when applied at Barry Point (AUC = 0.53–0.57). The final HSI models fitted to Toolbox and Canyon Creek data quantified suitable nesting habitat as severely burned or open sites adjacent to lower severity and closed canopy sites, where foraging presumably occurs. We suggest these models are applicable at locations similar to development locations but not at locations resembling Barry Point, which were characterized by more (pre-fire) canopy openings, larger diameter trees, less ponderosa pine (Pinus ponderosa), and more juniper (Juniperus occidentalis). Considering our results, we recommend caution when applying HSI models developed at individual wildfire locations to inform post-fire management at new locations without first evaluating predictive performance.

<![CDATA[Fire, CO2, and climate effects on modeled vegetation and carbon dynamics in western Oregon and Washington]]>

To develop effective long-term strategies, natural resource managers need to account for the projected effects of climate change as well as the uncertainty inherent in those projections. Vegetation models are one important source of projected climate effects. We explore results and associated uncertainties from the MC2 Dynamic Global Vegetation Model for the Pacific Northwest west of the Cascade crest. We compare model results for vegetation cover and carbon dynamics over the period 1895–2100 assuming: 1) unlimited wildfire ignitions versus stochastic ignitions, 2) no fire, and 3) a moderate CO2 fertilization effect versus no CO2 fertilization effect. Carbon stocks decline in all scenarios, except without fire and with a moderate CO2 fertilization effect. The greatest carbon stock loss, approximately 23% of historical levels, occurs with unlimited ignitions and no CO2 fertilization effect. With stochastic ignitions and a CO2 fertilization effect, carbon stocks are more stable than with unlimited ignitions. For all scenarios, the dominant vegetation type shifts from pure conifer to mixed forest, indicating that vegetation cover change is driven solely by climate and that significant mortality and vegetation shifts are likely through the 21st century regardless of fire regime changes.

<![CDATA[Bioclimatic modeling in the Last Glacial Maximum, Mid-Holocene and facing future climatic changes in the strawberry tree (Arbutus unedo L.)]]>

Increasing forest wildfires in Portugal remain a growing concern since forests in the Mediterranean region are vulnerable to recent global warming and reduction of precipitation. Therefore, a long-term negative effect is expected on the vegetation, with increasing drought and areas burnt by fires. The strawberry tree (Arbutus unedo L.) is particularly used in Portugal to produce a spirit by processing its fruits and is the main income for forestry owners. Other applications are possible due to the fruit and leaves’ anti-oxidant properties and bioactive compounds production, with a potential for clinical and food uses. It is a sclerophyllous plant, dry-adapted and fire resistant, enduring the Mediterranean climate, and recently considered as a possibility for afforestation, to intensify forest discontinuity where pines and eucalypts monoculture dominate the region. To improve our knowledge about the species’ spatial distribution we used 318 plots (the centroid of a 1 km2 square grid) measuring the species presence and nine environmental attributes. The seven bioclimatic variables most impacting on the species distribution and two topographic features, slope and altitude, were used. The past, current and future climate data were obtained through WorldClim. Finally, the vulnerability of the strawberry tree to the effects of global climate change was examined in the face of two emission scenarios (RCP 4.5 and 8.5), to predict distribution changes in the years 2050 and 2070, using a species distribution models (MaxEnt). The reduction of suitable habitat for this species is significant in the southern regions, considering the future scenarios of global warming. Central and northern mountainous regions are putative predicted refuges for this species. Forest policy and management should reflect the impact of climate change on the usable areas for forestry, particularly considering species adapted to the Mediterranean regions and wildfires, such as the strawberry tree. The distribution of the species in the Last Glacial Maximum (LGM) and Mid-Holocene (MH) agrees with previous genetic and paleontological studies in the region, which support putative refuges for the species. Two in the southern and coastal-central regions, since the LGM, and one in the east-central mountainous region, considered as cryptic refugia.

<![CDATA[Mapping future fire probability under climate change: Does vegetation matter?]]>

Understanding where and how fire patterns may change is critical for management and policy decision-making. To map future fire patterns, statistical correlative models are typically developed, which associate observed fire locations with recent climate maps, and are then applied to maps of future climate projections. A potential source of uncertainty is the common omission of static or dynamic vegetation as predictor variables. We therefore assessed the sensitivity of future fire projections to different combinations of vegetation maps used as explanatory variables in a statistically based fire modeling framework. We compared models without vegetation to models that incorporated static vegetation maps and that included output from a dynamic vegetation model that imposed three scenarios of fire and one scenario of land use change. We mapped projected future probability of all and large fires (> = 40 ha) under two climate scenarios in a heterogeneous study area spanning a large elevational gradient in the Sierra Nevada, California, USA. Results showed high model sensitivity to the treatment of vegetation as a predictor variable, particularly for models of large fire probability and for models accounting for wildfire effects on vegetation, which lowered future fire probability. Some scenarios resulted in opposite directional trends in the extent and probability of future fire, which could have serious implications for policy and management resource allocation. Model sensitivity resulted from high relative importance of vegetation variables in the baseline models and from large predicted changes in vegetation, particularly when simulating wildfire. Although statistical fire models often omit vegetation due to uncertainty, model sensitivity demonstrated here suggests a need to account for that uncertainty. Coupling statistical and processed based models may be a promising approach to reflect a more plausible range of scenarios.

<![CDATA[The effectiveness of an on-line training program for improving knowledge of fire prevention and evacuation of healthcare workers: A randomized controlled trial]]>


Hospitals are vulnerable to fires and the evacuation process is challenging. However, face-to-face fire prevention and evacuation training may take healthcare workers’ time away from patient care; therefore, effective on-line training may be warranted. We carried out and examined the effectiveness of an on-line education and training of fire prevention and evacuation training for healthcare workers in China by a randomized controlled trial using convenience sampling from five public hospitals in China.


A total of 128 participants were recruited between December 2014 and March 2015. The authors built a webpage that included the informed consent statement, pre-test questionnaire, video training, and post-test questionnaire. After completing the pre-test questionnaire, participants were randomly assigned to watch the intervention video (basic response to a hospital fire) or the control video (introduction to volcanic disasters). A 45-item questionnaire on knowledge of fire prevention and evacuation was administered before and after the video watching. This questionnaire were further divided into two subscales (25-item generic knowledge of fire response and 20-item hospital-specific knowledge of fire prevention and evacuation). One point was awarded for each correct answer.


Half of the participants (n = 64, 50%) were randomized into the intervention group and the remaining 64 (50%) were randomized into the control group. For generic knowledge of fire prevention and evacuation, those in the intervention group improved significantly (from 16.16 to 20.44, P < 0.001) while the scores of those in the control group decreased significantly (from 15.27 to 13.70, P = 0.03). For hospital-specific knowledge of fire prevention and evacuation, those in the intervention group (from 10.75 to 11.33, P = 0.15) and the control group (from 10.38 to 10.16, P = 0.54) had insignificant change. For total score, those in the intervention group improved significantly (from 26.91 to 31.77, P < 0.001) while those in the control group decreased insignificantly (from 25.64 to 23.86, P = 0.07). After the intervention, the difference between the scores of the intervention group and the control group on all three knowledge areas of fire prevention and evacuation (generic, hospital-specific, and total) were significant (all Ps < 0.05).


An on-line fire training program delivered via educational video can effectively improve healthcare workers’ knowledge of fire prevention and evacuation.

Trial registration NCT02438150

<![CDATA[PLoS Medicine Issue Image | Vol. 15(7) July 2018]]>

Climate change and health: Moving from theory to practice

July's issue of PLOS Medicine includes a special issue on climate change and health. Included in this exciting issue are papers focusing on heatwaves and mortality or morbidity; the impact of air conditioning on greenhouse gas emissions; wildfires and health impacts; health sector contributions to emissions; the effects of increased CO2 on crop nutrients; the occurrence of sewage in urban water supplies as a consequence of rainwater surge; and modelling studies focusing on dengue risk in small island states. The Guest Editors Jonathan Patz (Global Health Institute, University of Wisconsin-Madison) and Madeleine Thomson (International Research Institute for Climate and Society, Columbia University) discuss the papers in their Editorial and reveal how these papers provide an important and compelling advance to the field of climate change and health.

Image Credit: Akuppa John Wigham, Flickr; California National Guard, Flickr

<![CDATA[Fitting power-laws in empirical data with estimators that work for all exponents]]>

Most standard methods based on maximum likelihood (ML) estimates of power-law exponents can only be reliably used to identify exponents smaller than minus one. The argument that power laws are otherwise not normalizable, depends on the underlying sample space the data is drawn from, and is true only for sample spaces that are unbounded from above. Power-laws obtained from bounded sample spaces (as is the case for practically all data related problems) are always free of such limitations and maximum likelihood estimates can be obtained for arbitrary powers without restrictions. Here we first derive the appropriate ML estimator for arbitrary exponents of power-law distributions on bounded discrete sample spaces. We then show that an almost identical estimator also works perfectly for continuous data. We implemented this ML estimator and discuss its performance with previous attempts. We present a general recipe of how to use these estimators and present the associated computer codes.

<![CDATA[Historical Maps from Modern Images: Using Remote Sensing to Model and Map Century-Long Vegetation Change in a Fire-Prone Region]]>

Understanding the age structure of vegetation is important for effective land management, especially in fire-prone landscapes where the effects of fire can persist for decades and centuries. In many parts of the world, such information is limited due to an inability to map disturbance histories before the availability of satellite images (~1972). Here, we describe a method for creating a spatial model of the age structure of canopy species that established pre-1972. We built predictive neural network models based on remotely sensed data and ecological field survey data. These models determined the relationship between sites of known fire age and remotely sensed data. The predictive model was applied across a 104,000 km2 study region in semi-arid Australia to create a spatial model of vegetation age structure, which is primarily the result of stand-replacing fires which occurred before 1972. An assessment of the predictive capacity of the model using independent validation data showed a significant correlation (rs = 0.64) between predicted and known age at test sites. Application of the model provides valuable insights into the distribution of vegetation age-classes and fire history in the study region. This is a relatively straightforward method which uses widely available data sources that can be applied in other regions to predict age-class distribution beyond the limits imposed by satellite imagery.

<![CDATA[Accounting for Biomass Carbon Stock Change Due to Wildfire in Temperate Forest Landscapes in Australia]]>

Carbon stock change due to forest management and disturbance must be accounted for in UNFCCC national inventory reports and for signatories to the Kyoto Protocol. Impacts of disturbance on greenhouse gas (GHG) inventories are important for many countries with large forest estates prone to wildfires. Our objective was to measure changes in carbon stocks due to short-term combustion and to simulate longer-term carbon stock dynamics resulting from redistribution among biomass components following wildfire. We studied the impacts of a wildfire in 2009 that burnt temperate forest of tall, wet eucalypts in south-eastern Australia. Biomass combusted ranged from 40 to 58 tC ha−1, which represented 6–7% and 9–14% in low- and high-severity fire, respectively, of the pre-fire total biomass carbon stock. Pre-fire total stock ranged from 400 to 1040 tC ha−1 depending on forest age and disturbance history. An estimated 3.9 TgC was emitted from the 2009 fire within the forest region, representing 8.5% of total biomass carbon stock across the landscape. Carbon losses from combustion were large over hours to days during the wildfire, but from an ecosystem dynamics perspective, the proportion of total carbon stock combusted was relatively small. Furthermore, more than half the stock losses from combustion were derived from biomass components with short lifetimes. Most biomass remained on-site, although redistributed from living to dead components. Decomposition of these components and new regeneration constituted the greatest changes in carbon stocks over ensuing decades. A critical issue for carbon accounting policy arises because the timeframes of ecological processes of carbon stock change are longer than the periods for reporting GHG inventories for national emissions reductions targets. Carbon accounts should be comprehensive of all stock changes, but reporting against targets should be based on human-induced changes in carbon stocks to incentivise mitigation activities.

<![CDATA[Modelling Carbon Emissions in Calluna vulgaris–Dominated Ecosystems when Prescribed Burning and Wildfires Interact]]>

A present challenge in fire ecology is to optimize management techniques so that ecological services are maximized and C emissions minimized. Here, we modeled the effects of different prescribed-burning rotation intervals and wildfires on carbon emissions (present and future) in British moorlands. Biomass-accumulation curves from four Calluna-dominated ecosystems along a north-south gradient in Great Britain were calculated and used within a matrix-model based on Markov Chains to calculate above-ground biomass-loads and annual C emissions under different prescribed-burning rotation intervals. Additionally, we assessed the interaction of these parameters with a decreasing wildfire return intervals. We observed that litter accumulation patterns varied between sites. Northern sites (colder and wetter) accumulated lower amounts of litter with time than southern sites (hotter and drier). The accumulation patterns of the living vegetation dominated by Calluna were determined by site-specific conditions. The optimal prescribed-burning rotation interval for minimizing annual carbon emissions also differed between sites: the optimal rotation interval for northern sites was between 30 and 50 years, whereas for southern sites a hump-backed relationship was found with the optimal interval either between 8 to 10 years or between 30 to 50 years. Increasing wildfire frequency interacted with prescribed-burning rotation intervals by both increasing C emissions and modifying the optimum prescribed-burning interval for minimum C emission. This highlights the importance of studying site-specific biomass accumulation patterns with respect to environmental conditions for identifying suitable fire-rotation intervals to minimize C emissions.

<![CDATA[Large Scale Anthropogenic Reduction of Forest Cover in Last Glacial Maximum Europe]]>

Reconstructions of the vegetation of Europe during the Last Glacial Maximum (LGM) are an enigma. Pollen-based analyses have suggested that Europe was largely covered by steppe and tundra, and forests persisted only in small refugia. Climate-vegetation model simulations on the other hand have consistently suggested that broad areas of Europe would have been suitable for forest, even in the depths of the last glaciation. Here we reconcile models with data by demonstrating that the highly mobile groups of hunter-gatherers that inhabited Europe at the LGM could have substantially reduced forest cover through the ignition of wildfires. Similar to hunter-gatherers of the more recent past, Upper Paleolithic humans were masters of the use of fire, and preferred inhabiting semi-open landscapes to facilitate foraging, hunting and travel. Incorporating human agency into a dynamic vegetation-fire model and simulating forest cover shows that even small increases in wildfire frequency over natural background levels resulted in large changes in the forested area of Europe, in part because trees were already stressed by low atmospheric CO2 concentrations and the cold, dry, and highly variable climate. Our results suggest that the impact of humans on the glacial landscape of Europe may be one of the earliest large-scale anthropogenic modifications of the earth system.

<![CDATA[Structure and Evolution of Mediterranean Forest Research: A Science Mapping Approach]]>

This study aims at conducting the first science mapping analysis of the Mediterranean forest research in order to elucidate its research structure and evolution. We applied a science mapping approach based on co-term and citation analyses to a set of scientific publications retrieved from the Elsevier’s Scopus database over the period 1980–2014. The Scopus search retrieved 2,698 research papers and reviews published by 159 peer-reviewed journals. The total number of publications was around 1% (N = 17) during the period 1980–1989 and they reached 3% (N = 69) in the time slice 1990–1994. Since 1995, the number of publications increased exponentially, thus reaching 55% (N = 1,476) during the period 2010–2014. Within the thirty-four years considered, the retrieved publications were published by 88 countries. Among them, Spain was the most productive country, publishing 44% (N = 1,178) of total publications followed by Italy (18%, N = 482) and France (12%, N = 336). These countries also host the ten most productive scientific institutions in terms of number of publications in Mediterranean forest subjects. Forest Ecology and Management and Annals of Forest Science were the most active journals in publishing research in Mediterranean forest. During the period 1980–1994, the research topics were poorly characterized, but they become better defined during the time slice 1995–1999. Since 2000s, the clusters become well defined by research topics. Current status of Mediterranean forest research (20092014) was represented by four clusters, in which different research topics such as biodiversity and conservation, land-use and degradation, climate change effects on ecophysiological responses and soil were identified. Basic research in Mediterranean forest ecosystems is mainly conducted by ecophysiological research. Applied research was mainly represented by land-use and degradation, biodiversity and conservation and fire research topics. The citation analyses revealed highly cited terms in the Mediterranean forest research as they were represented by fire, biodiversity, carbon sequestration, climate change and global warming. Finally, our analysis also revealed the multidisciplinary role of climate change research. This study provides a first holistic view of the Mediterranean forest research that could be useful for researchers and policy makers as they may evaluate and analyze its historical evolution, as well as its structure and scientific production. We concluded that Mediterranean forest research represents an active scientific field.

<![CDATA[Historical, Observed, and Modeled Wildfire Severity in Montane Forests of the Colorado Front Range]]>

Large recent fires in the western U.S. have contributed to a perception that fire exclusion has caused an unprecedented occurrence of uncharacteristically severe fires, particularly in lower elevation dry pine forests. In the absence of long-term fire severity records, it is unknown how short-term trends compare to fire severity prior to 20th century fire exclusion. This study compares historical (i.e. pre-1920) fire severity with observed modern fire severity and modeled potential fire behavior across 564,413 ha of montane forests of the Colorado Front Range. We used forest structure and tree-ring fire history to characterize fire severity at 232 sites and then modeled historical fire-severity across the entire study area using biophysical variables. Eighteen (7.8%) sites were characterized by low-severity fires and 214 (92.2%) by mixed-severity fires (i.e. including moderate- or high-severity fires). Difference in area of historical versus observed low-severity fire within nine recent (post-1999) large fire perimeters was greatest in lower montane forests. Only 16% of the study area recorded a shift from historical low severity to a higher potential for crown fire today. An historical fire regime of more frequent and low-severity fires at low elevations (<2260 m) supports a convergence of management goals of ecological restoration and fire hazard mitigation in those habitats. In contrast, at higher elevations mixed-severity fires were predominant historically and continue to be so today. Thinning treatments at higher elevations of the montane zone will not return the fire regime to an historic low-severity regime, and are of questionable effectiveness in preventing severe wildfires. Based on present-day fuels, predicted fire behavior under extreme fire weather continues to indicate a mixed-severity fire regime throughout most of the montane forest zone. Recent large wildfires in the Front Range are not fundamentally different from similar events that occurred historically under extreme weather conditions.

<![CDATA[Non-linear growth in tree ferns, Dicksonia antarctica and Cyathea australis]]>

Tree ferns are an important structural component of forests in many countries. However, because their regeneration is often unrelated to major disturbances, their age is often difficult to determine. In addition, rates of growth may not be uniform, which further complicates attempts to determine their age. In this study, we measured 5 years of growth of Cyathea australis and Dicksonia antarctica after a large wildfire in 2009 in south-eastern Australia. We found growth rates of these two species were unaffected by aspect and elevation but slope had a minor effect with D. antarctica growing 0.3mm faster for each additional degree of slope. Geographic location influenced growth in both species by up to 12 – 14mm/yr. The most consistent factor influencing growth rate, however, was initial height at the time of the 2009 fire; a finding consistent in both species and all geographic locations. For both tree fern species, individuals that were taller at the commencement of the study had greater overall growth for the duration of the study. This effect did not decrease even among the tallest tree ferns in our study (up to 6 metres tall). Overall, Cyathea australis averaged 73 (± 22)mm/year of growth (± 1SD), with the rate increasing 5mm/yr per metre of additional height. Dicksonia antarctica averaged 33 (± 13)mm/year, increasing by 6mm/yr/m. Growth rates dependent on initial height were unexpected and we discuss possible reasons for this finding. Variable growth rates also suggest that common age estimation methods of dividing height by average growth rate are likely to underestimate the age of short tree ferns, while overestimating the age of tall tree ferns, particularly if they have been subject to a fire.

<![CDATA[Post-Fire Recovery in Coastal Sage Scrub: Seed Rain and Community Trajectory]]>

Disturbance is a primary mechanism structuring ecological communities. However, human activity has the potential to alter the frequency and intensity of natural disturbance regimes, with subsequent effects on ecosystem processes. In Southern California, human development has led to increased fire frequency close to urban areas that can form a positive feedback with invasive plant spread. Understanding how abiotic and biotic factors structure post-fire plant communities is a critical component of post-fire management and restoration. In this study we considered a variety of mechanisms affecting post-fire vegetation recovery in Riversidean sage scrub. Comparing recently burned plots to unburned plots, we found that burning significantly reduced species richness and percent cover of exotic vegetation the first two years following a 100-hectare wildfire. Seed rain was higher in burned plots, with more native forb seeds, while unburned plots had more exotic grass seeds. Moreover, there were significant correlations between seed rain composition and plant cover composition the year prior and the year after. Collectively, this case study suggests that fire can alter community composition, but there was not compelling evidence of a vegetation-type conversion. Instead, the changes in the community composition were temporary and convergence in community composition was apparent within two years post-fire.

<![CDATA[Trace Elements in Stormflow, Ash, and Burned Soil following the 2009 Station Fire in Southern California]]>

Most research on the effects of wildfires on stream water quality has focused on suspended sediment and nutrients in streams and water bodies, and relatively little research has examined the effects of wildfires on trace elements. The purpose of this study was two-fold: 1) to determine the effect of the 2009 Station Fire in the Angeles National Forest northeast of Los Angeles, CA on trace element concentrations in streams, and 2) compare trace elements in post-fire stormflow water quality to criteria for aquatic life to determine if trace elements reached concentrations that can harm aquatic life. Pre-storm and stormflow water-quality samples were collected in streams located inside and outside of the burn area of the Station Fire. Ash and burned soil samples were collected from several locations within the perimeter of the Station Fire. Filtered concentrations of Fe, Mn, and Hg and total concentrations of most trace elements in storm samples were elevated as a result of the Station Fire. In contrast, filtered concentrations of Cu, Pb, Ni, and Se and total concentrations of Cu were elevated primarily due to storms and not the Station Fire. Total concentrations of Se and Zn were elevated as a result of both storms and the Station Fire. Suspended sediment in stormflows following the Station Fire was an important transport mechanism for trace elements. Cu, Pb, and Zn primarily originate from ash in the suspended sediment. Fe primarily originates from burned soil in the suspended sediment. As, Mn, and Ni originate from both ash and burned soil. Filtered concentrations of trace elements in stormwater samples affected by the Station Fire did not reach levels that were greater than criteria established for aquatic life. Total concentrations for Fe, Pb, Ni, and Zn were detected at concentrations above criteria established for aquatic life.

<![CDATA[Are Isolated Indigenous Populations Headed toward Extinction?]]>

At least 50 indigenous groups spread across lowland South America remain isolated and have only intermittent and mostly hostile interactions with the outside world. Except in emergency situations, the current policy of governments in Brazil, Colombia, and Peru towards isolated tribes is a “leave them alone” strategy, in which isolated groups are left uncontacted. However, these no-contact policies are based on the assumption that isolated populations are healthy and capable of persisting in the face of mounting external threats, and that they can maintain population viability in the long-term. Here, we test this assumption by tracking the sizes and movements of cleared horticultural areas made by 8 isolated groups over the last 10–14 years. We used deforestation data derived from remote sensing Landsat satellite sensors to identify clearings, and those were then validated and assessed with high-resolution imagery. We found only a single example of a relatively large and growing population (c. 50 cleared ha and 400 people), whereas all of the other 7 groups exhibited much smaller villages and gardens with no sizable growth through time. These results indicated that the smaller groups are critically endangered, and it prompts an urgent re-thinking of policies toward isolated populations, including plans for well-organized contacts that may help save lives and rescue isolated indigenous populations from imminent extinction.

<![CDATA[Impacts of Short-Rotation Early-Growing Season Prescribed Fire on a Ground Nesting Bird in the Central Hardwoods Region of North America]]>

Landscape-scale short-rotation early-growing season prescribed fire, hereafter prescribed fire, in upland hardwood forests represents a recent shift in management strategies across eastern upland forests. Not only does this strategy depart from dormant season to growing season prescriptions, but the strategy also moves from stand-scale to landscape-scale implementation (>1,000 ha). This being so, agencies are making considerable commitments in terms of time and resources to this management strategy, but the effects on wildlife in upland forests, especially those dominated by hardwood canopy species, are relatively unknown. We initiated our study to assess whether this management strategy affects eastern wild turkey reproductive ecology on the Ozark-St. Francis National Forest. We marked 67 wild turkey hens with Global Positioning System (GPS) Platform Transmitting Terminals in 2012 and 2013 to document exposure to prescribed fire, and estimate daily nest survival, nest success, and nest-site selection. We estimated these reproductive parameters in forest units managed with prescribed fire (treated) and units absent of prescribed fire (untreated). Of 60 initial nest attempts monitored, none were destroyed or exposed to prescribed fire because a majority of fires occurred early than a majority of the nesting activity. We found nest success was greater in untreated units than treated units (36.4% versus 14.6%). We did not find any habitat characteristic differences between successful and unsuccessful nest-sites. We found that nest-site selection criteria differed between treated and untreated units. Visual concealment and woody ground cover were common selection criteria in both treated and untreated units. However, in treated units wild turkey selected nest-sites with fewer small shrubs (<5 cm ground diameter) and large trees (>20 cm DBH) but not in untreated units. In untreated units wild turkey selected nest-sites with more large shrubs (≥5cm ground diameter) but did not select for small shrubs or large trees. Our findings suggest that wild turkey have not benefited from the reintroduction of prescribed fire to the WRERA.

<![CDATA[Network analysis of wildfire transmission and implications for risk governance]]>

We characterized wildfire transmission and exposure within a matrix of large land tenures (federal, state, and private) surrounding 56 communities within a 3.3 million ha fire prone region of central Oregon US. Wildfire simulation and network analysis were used to quantify the exchange of fire among land tenures and communities and analyze the relative contributions of human versus natural ignitions to wildfire exposure. Among the land tenures examined, the area burned by incoming fires averaged 57% of the total burned area. Community exposure from incoming fires ignited on surrounding land tenures accounted for 67% of the total area burned. The number of land tenures contributing wildfire to individual communities and surrounding wildland urban interface (WUI) varied from 3 to 20. Community firesheds, i.e. the area where ignitions can spawn fires that can burn into the WUI, covered 40% of the landscape, and were 5.5 times larger than the combined area of the community core and WUI. For the major land tenures within the study area, the amount of incoming versus outgoing fire was relatively constant, with some exceptions. The study provides a multi-scale characterization of wildfire networks within a large, mixed tenure and fire prone landscape, and illustrates the connectivity of risk between communities and the surrounding wildlands. We use the findings to discuss how scale mismatches in local wildfire governance result from disconnected planning systems and disparate fire management objectives among the large landowners (federal, state, private) and local communities. Local and regional risk planning processes can adopt our concepts and methods to better define and map the scale of wildfire risk from large fire events and incorporate wildfire network and connectivity concepts into risk assessments.

<![CDATA[Multitemporal Modelling of Socio-Economic Wildfire Drivers in Central Spain between the 1980s and the 2000s: Comparing Generalized Linear Models to Machine Learning Algorithms]]>

The socio-economic factors are of key importance during all phases of wildfire management that include prevention, suppression and restoration. However, modeling these factors, at the proper spatial and temporal scale to understand fire regimes is still challenging. This study analyses socio-economic drivers of wildfire occurrence in central Spain. This site represents a good example of how human activities play a key role over wildfires in the European Mediterranean basin. Generalized Linear Models (GLM) and machine learning Maximum Entropy models (Maxent) predicted wildfire occurrence in the 1980s and also in the 2000s to identify changes between each period in the socio-economic drivers affecting wildfire occurrence. GLM base their estimation on wildfire presence-absence observations whereas Maxent on wildfire presence-only. According to indicators like sensitivity or commission error Maxent outperformed GLM in both periods. It achieved a sensitivity of 38.9% and a commission error of 43.9% for the 1980s, and 67.3% and 17.9% for the 2000s. Instead, GLM obtained 23.33, 64.97, 9.41 and 18.34%, respectively. However GLM performed steadier than Maxent in terms of the overall fit. Both models explained wildfires from predictors such as population density and Wildland Urban Interface (WUI), but differed in their relative contribution. As a result of the urban sprawl and an abandonment of rural areas, predictors like WUI and distance to roads increased their contribution to both models in the 2000s, whereas Forest-Grassland Interface (FGI) influence decreased. This study demonstrates that human component can be modelled with a spatio-temporal dimension to integrate it into wildfire risk assessment.