Fire Ecology最新文献

{"title":"Using witness trees as pyro-indicators to depict past fire environments across the eastern United States","authors":"Gregory J. Nowacki, Melissa A. Thomas-Van Gundy","doi":"10.1186/s42408-024-00247-1","DOIUrl":"https://doi.org/10.1186/s42408-024-00247-1","url":null,"abstract":"Understanding past fire environments is vitally important for applying silvicultural treatments, which often include prescribed burning to restore fire-dependent ecosystems. We have developed a novel method by which witness trees can be used as pyro-indicators to map past fire environments. The stepwise process first involves partitioning witness trees into two classes, pyrophobic and pyrophilic, based on their known ecophysiological traits. Pyrophilic percentages are then calculated at survey corners by dividing the number of pyrophilic trees by the total number of trees. Next, statistical spatial interpolation is applied to this point-based data set to produce a continuous response surface of pyrophilic percentages. The resultant maps capture gradients of fire importance across the pre-European-settlement landscape, which can be coupled with historic fire regime maps, thus providing additional information for better understanding and explaining past fire environments. We have applied this technique to various available witness-tree databases across the eastern United States. This paper serves as a compendium of our collective work to date.","PeriodicalId":12273,"journal":{"name":"Fire Ecology","volume":"50 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139578064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Midwest prairie management practices benefit the non-target prairie crayfish","authors":"Caitlin C. Bloomer, Christopher M. Miller, Robert J. DiStefano, Christopher A. Taylor","doi":"10.1186/s42408-023-00243-x","DOIUrl":"https://doi.org/10.1186/s42408-023-00243-x","url":null,"abstract":"Prescribed burning is used to duplicate natural, pre-settlement prairie successional processes. It is an essential and commonly used tool to promote and protect biodiversity and enhance ecosystem function in tallgrass prairie remnants throughout the midwestern United States. The responses to prescribed burns vary widely among faunal groups. We conducted the first study into the response of the prairie crayfish (Procambarus gracilis Bundy) to periodic prescribed burns and other management activities in a tallgrass prairie in Northern Missouri. This species relies on natural and restored prairies across its broad distribution, but little is known on how to actively manage these populations. We found that the density of the prairie crayfish burrows did not vary in response to the burn regime; however, other management activities like the installation of artificial ponds for amphibians and reptiles were directly benefitting this species. Observations indicate that prairie crayfish may also show positive associations with warm-season grass stands and vegetation management should be further explored. The current prairie management practices for vegetation, quail, and herpetofauna are having beneficial or neutral effects on non-target taxa like the prairie crayfish. The value of crayfish and their burrows in prairies is well-established. Conservation biologists should continue to examine how burrowing crayfish are responding to management practices for other taxa to explicitly manage and promote these populations.","PeriodicalId":12273,"journal":{"name":"Fire Ecology","volume":"4 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139578067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guiding principles for transdisciplinary and transformative fire research","authors":"Kelsey Copes-Gerbitz, Ira J. Sutherland, Sarah Dickson-Hoyle, Jennifer N. Baron, Pablo Gonzalez-Moctezuma, Morgan A. Crowley, Katherine A. Kitchens, Tahia Devisscher, Judith Burr","doi":"10.1186/s42408-023-00244-w","DOIUrl":"https://doi.org/10.1186/s42408-023-00244-w","url":null,"abstract":"Managing landscape fire is a complex challenge because it is simultaneously necessary for, and increasingly poses a risk to, societies and ecosystems worldwide. This challenge underscores the need for transformative change in the way societies live with and manage fire. While researchers have the potential to act as agents of transformative change, in practice, the ability to affect change is often constrained by siloed and biased expertise, rigid decision-making institutions, and increasingly vulnerable social-ecological systems where urgent rather than long-term solutions are prioritized. Addressing these challenges requires more holistic and equitable approaches to fire research that promote new models of transdisciplinary thinking, collaboration, and practice. To advance transformative solutions to this complex fire challenge, we propose four principles for conducting transdisciplinary fire research: (1) embrace complexity, (2) promote diverse ways of knowing fire, (3) foster transformative learning, and (4) practice problem-centered research. These principles emerged from our experience as a group of early-career researchers who are embedded within and motivated by today’s complex fire challenge within British Columbia (BC), Canada. In this forum piece, we first describe the four principles and then apply the principles to two case studies: (1) BC, a settler-colonial context experiencing increased size, severity, and impacts of wildfires, and (2) our ECR discussion group, a space of collective learning and transformation. In doing so, we present a unique contribution that builds on existing efforts to develop more holistic fire research frameworks and demonstrates how application of these principles can promote transdisciplinary research and transformation towards coexistence with fire, from local to global scales. In this forum piece, we identify and apply four guiding principles for transdisciplinary fire research. Collectively, these principles can foster more inclusive applied fire research that matches the scope and scale of today’s fire challenge and promotes transformative change towards coexisting with fire.","PeriodicalId":12273,"journal":{"name":"Fire Ecology","volume":"4 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139578313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wildfire risk exploration: leveraging SHAP and TabNet for precise factor analysis","authors":"Faiza Qayyum, Harun Jamil, Tariq Alsboui, Mohammad Hijjawi","doi":"10.1186/s42408-023-00236-w","DOIUrl":"https://doi.org/10.1186/s42408-023-00236-w","url":null,"abstract":"Understanding the intricacies of wildfire impact across diverse geographical landscapes necessitates a nuanced comprehension of fire dynamics and areas of vulnerability, particularly in regions prone to high wildfire risks. Machine learning (ML) stands as a formidable ally in addressing the complexities associated with predicting and mapping these risks, offering advanced analytical capabilities. Nevertheless, the reliability of such ML approaches is heavily contingent on the integrity of data and the robustness of training protocols. The scientific community has raised concerns about the transparency and interpretability of ML models in the context of wildfire management, recognizing the need for these models to be both accurate and understandable. The often-opaque nature of complex ML algorithms can obscure the rationale behind their outputs, making it imperative to prioritize clarity and interpretability to ensure that model predictions are not only precise but also actionable. Furthermore, a thorough evaluation of model performance must account for multiple critical factors to ensure the utility and dependability of the results in practical wildfire suppression and management strategies. This study unveils a sophisticated spatial deep learning framework grounded in TabNet technology, tailored specifically for delineating areas susceptible to wildfires. To elucidate the predictive interplay between the model’s outputs and the contributing variables across a spectrum of inputs, we embark on an exhaustive analysis using SHapley Additive exPlanations (SHAP). This approach affords a granular understanding of how individual features sway the model’s predictions. Furthermore, the robustness of the predictive model is rigorously validated through 5-fold cross-validation techniques, ensuring the dependability of the findings. The research meticulously investigates the spatial heterogeneity of wildfire susceptibility within the designated study locale, unearthing pivotal insights into the nuanced fabric of fire risk that is distinctly local in nature. Utilizing SHapley Additive exPlanations (SHAP) visualizations, this research meticulously identifies key variables, quantifies their importance, and demystifies the decision-making mechanics of the model. Critical factors, including temperature, elevation, the Normalized Difference Vegetation Index (NDVI), aspect, and wind speed, are discerned to have significant sway over the predictions of wildfire susceptibility. The findings of this study accentuate the criticality of transparency in modeling, which facilitates a deeper understanding of wildfire risk factors. By shedding light on the significant predictors within the models, this work enhances our ability to interpret complex predictive models and drives forward the field of wildfire risk management, ultimately contributing to the development of more effective prevention and mitigation strategies.","PeriodicalId":12273,"journal":{"name":"Fire Ecology","volume":"58 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139578452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plant-plant interactions influence post-fire recovery depending on fire history and nurse growth form","authors":"Maral Bashirzadeh, Mehdi Abedi, Mohammad Farzam","doi":"10.1186/s42408-024-00246-2","DOIUrl":"https://doi.org/10.1186/s42408-024-00246-2","url":null,"abstract":"Plant-plant interactions are among the most important factors affecting the natural recovery of vegetation. While the impacts of nurse plants on species composition and biodiversity are well documented, the effects of different nurse’s growth forms on all biodiversity components including taxonomic, functional, and phylogenetic diversity have been less studied and compared, especially for their effects on different times after fire disturbance. This research was focused on comparing the effects of a perennial grass (Elymus hispidens), a perennial herb (Phlomis cancellata), and a high shrub species (Lonicera nummulariifolia) on species composition and the biodiversity components, and how these impacts change across five sites with short-term (1 and 4 years sites), long-term (10 and 20 years sites) times since last fire and a control site where no fire was known in recorded history in semi-arid shrublands of Fereizi Chenaran located in Northeast of Iran. The changes of species composition and taxonomic, functional, and phylogenetic diversity were calculated with respect to the presence/absence of nurse’s growth forms, fire history, and their interactions. Nurse shrubs affected species composition and all biodiversity components, whereas all indices were reduced when considering Elymus grass as nurse plant. On the other hand, the herb Phlomis enhanced species composition and taxonomic diversity, while it had a negative effect on functional and phylogenetic diversity. Such specific effects of nurse types were mostly observed under long timescales (i.e., 10- and 20-year sites). Interestingly, the relative importance of nurse types and time since the last fire largely explained the variation of species composition and biodiversity components, with larger effects of nurse types on all biodiversity components. However, we found a significant contribution of fire explaining variation of species composition and phylogenetic diversity. These results indicated nurse plants can affect the post-fire recovery of vegetation by providing specific mechanisms controlling beneficiary relatedness depending on their growth forms and time scales since the last fire. Therefore, these findings suggest perennial plants in the form of nurse species as a useful factor to develop techniques of active restoration in burned ecosystems.","PeriodicalId":12273,"journal":{"name":"Fire Ecology","volume":"14 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139578445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shapley-based interpretation of deep learning models for wildfire spread rate prediction","authors":"Faiza Qayyum, Nagwan Abdel Samee, Maali Alabdulhafith, Ahmed Aziz, Mohammad Hijjawi","doi":"10.1186/s42408-023-00242-y","DOIUrl":"https://doi.org/10.1186/s42408-023-00242-y","url":null,"abstract":"Predicting wildfire progression is vital for countering its detrimental effects. While numerous studies over the years have delved into forecasting various elements of wildfires, many of these complex models are perceived as “black boxes”, making it challenging to produce transparent and easily interpretable outputs. Evaluating such models necessitates a thorough understanding of multiple pivotal factors that influence their performance. This study introduces a deep learning methodology based on transformer to determine wildfire susceptibility. To elucidate the connection between predictor variables and the model across diverse parameters, we employ SHapley Additive exPlanations (SHAP) for a detailed analysis. The model’s predictive robustness is further bolstered through various cross-validation techniques. Upon examining various wildfire spread rate prediction models, transformer stands out, outperforming its peers in terms of accuracy and reliability. Although the models demonstrated a high level of accuracy when applied to the development dataset, their performance deteriorated when evaluated against the separate evaluation dataset. Interestingly, certain models that showed the lowest errors during the development stage exhibited the highest errors in the subsequent evaluation phase. In addition, SHAP outcomes underscore the invaluable role of explainable AI in enriching our comprehension of wildfire spread rate prediction.","PeriodicalId":12273,"journal":{"name":"Fire Ecology","volume":"58 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139554550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cellular automata-based simulators for the design of prescribed fire plans: the case study of Liguria, Italy","authors":"Nicoló Perello, Andrea Trucchia, Francesco Baghino, Bushra Sanira Asif, Lola Palmieri, Nicola Rebora, Paolo Fiorucci","doi":"10.1186/s42408-023-00239-7","DOIUrl":"https://doi.org/10.1186/s42408-023-00239-7","url":null,"abstract":"Socio-economic changes in recent decades have resulted in an accumulation of fuel within Mediterranean forests, creating conditions conducive to potential catastrophic wildfires intensified by climate change. Consequently, several wildfire management systems have integrated prescribed fires as a proactive strategy for land management and wildfire risk reduction. The preparation of prescribed fires involves meticulous planning, entailing the identification of specific objectives, verification of prescriptions, and the definition of various scenarios. During the planning phase, simulation models offer a valuable decision-support tool for the qualitative and quantitative assessment of different scenarios. In this study, we harnessed the capabilities of the well-established wildfire simulation tool PROPAGATOR, to identify areas where prescribed fires can be performed, optimizing the wildfire risk mitigation and the costs. We selected a case study in the Liguria region, Italy, where the model is utilized operationally by the regional wildfire risk management system in emergency situations. Initially, we employed the propagation model to simulate a historical wildfire event, showcasing its potential as an emergency response tool. We focused on the most significant fire incident that occurred in the Liguria region in 2022. Subsequently, we employed PROPAGATOR to identify optimal areas for prescribed fires with the dual objectives of maximizing the mitigation of wildfire risk and minimizing treatment costs. The delineation of potential areas for prescribed fires has been established in accordance with regional regulations and expert-based insights. The methodology put forth in this study is capable of discerning the most suitable areas for the implementation of prescribed burns from a preselected set. A Monte Carlo simulation framework was employed to evaluate the efficacy of prescribed burns in mitigating the spread of wildfires. This assessment accounted for a variety of conditions, including fuel loads, ignition points, and meteorological patterns. The PROPAGATOR model was utilized to simulate the progression of wildfire spread. This study underscores the utility of PROPAGATOR in offering both quantitative and qualitative insights that can inform prescribed fire planning. Our methodology has been designed to involve active engagement with subject matter experts throughout the process, to develop scenarios grounded in their expert opinions. The ability to assess diverse scenarios and acquire quantitative information empowers decision-makers to make informed choices, thereby advancing safer and more efficient fire management practices.","PeriodicalId":12273,"journal":{"name":"Fire Ecology","volume":"20 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139517808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Air quality and health impacts of the 2020 wildfires in California","authors":"Marc Carreras-Sospedra, Shupeng Zhu, Michael MacKinnon, William Lassman, Jeffrey D. Mirocha, Michele Barbato, Donald Dabdub","doi":"10.1186/s42408-023-00234-y","DOIUrl":"https://doi.org/10.1186/s42408-023-00234-y","url":null,"abstract":"Wildfires in 2020 ravaged California to set the annual record of area burned to date. Clusters of wildfires in Northern California surrounded the Bay Area covering the skies with smoke and raising the air pollutant concentrations to hazardous levels. This study uses the Fire Inventory from the National Center for Atmospheric Research database and the Community Multiscale Air Quality model to estimate the effects of wildfire emissions on air quality during the period from August 16 to October 28 of 2020. In addition, low-cost sensor data for fine particulate matter (PM2.5) from the PurpleAir network is used to enhance modeled PM2.5 concentrations. The resulting impacts on ozone and PM2.5 are used to quantify the health impacts caused by wildfires using the Benefits Mapping and Analysis Program – Community Edition. Wildfire activity significantly increased direct PM2.5 emissions and emissions of PM2.5 and ozone precursors. Direct PM2.5 emissions surged up to 38 times compared to an average day. Modeling results indicated that wildfires alone led to a rise in ozone daily maximum 8-h average by up to 10 ppb and exceeded PM2.5 air quality standards in numerous locations by up to 10 times. While modeled PM2.5 concentrations were lower than measurements, correcting these with PurpleAir data improved the accuracy. The correction using PurpleAir data increased estimates of wildfire-induced mortality due to PM2.5 exposure by up to 16%. The increased hospital admissions and premature mortality attributed to wildfires were found to be comparable to the health impacts avoided by strategies aimed at meeting ozone and PM2.5 air quality standards. This suggests that widespread wildfire emissions can negate years of efforts dedicated to controlling air pollution. The integration of low-cost sensor data proved invaluable in refining the estimates of health impacts from PM2.5 resulting from wildfires.","PeriodicalId":12273,"journal":{"name":"Fire Ecology","volume":"10 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139509838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Fire severity influences large wood and stream ecosystem responses in western Oregon watersheds","authors":"Ashley A. Coble, Brooke E. Penaluna, Laura J. Six, Jake Verschuyl","doi":"10.1186/s42408-023-00240-0","DOIUrl":"https://doi.org/10.1186/s42408-023-00240-0","url":null,"abstract":"<p><b>Correction: Fire Ecol 19, 34 (2023)</b></p><p><b>https://doi.org/10.1186/s42408-023–00192-5</b></p><p>When analysing subsequent years of fish and amphibian data, the authors identified an error in some of the reach area calculations that affected vertebrate densities for some sites (density and biomass density for fish and amphibians). Specifically, the formula for reach area in some cells (5 sites) referenced wetted width from an adjacent site instead of the correct site. Because this error did not occur across all cells (sites) and because abundance data were not affected this calculation error was not readily apparent. This error affected densities for fish and amphibians at some sites, including 2 of the most severely burned sites, and therefore affects the individual fish and amphibian responses reported in Fig. 7 a, b. For consistency, Fig. 5 (PCA) has also been updated to reflect these changes.</p><figure><figcaption><b data-test=\"figure-caption-text\">Fig. 5</b></figcaption><picture><source srcset=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs42408-023-00240-0/MediaObjects/42408_2023_240_Fig1_HTML.png?as=webp\" type=\"image/webp\"/><img alt=\"figure 1\" aria-describedby=\"Fig1\" height=\"1604\" loading=\"lazy\" src=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs42408-023-00240-0/MediaObjects/42408_2023_240_Fig1_HTML.png\" width=\"685\"/></picture><p>Principal components analysis (PCA) and relationships of axes with fire severity and pre-fire stand age. <b>a</b> PCA with scores and loadings of physical, chemical, biological, and watershed characteristics. <b>b</b> Principal component 1 (PC1) varied as a function of fire severity as RAVG mean. <b>c</b> Principal component 2 (PC2) varied as a function of pre-fire stand age</p><span>Full size image</span><svg aria-hidden=\"true\" focusable=\"false\" height=\"16\" role=\"img\" width=\"16\"><use xlink:href=\"#icon-eds-i-chevron-right-small\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"></use></svg></figure><p>This correction affects only the fish and amphibian density and biomass density results (Fig. 5, Fig. 7 panel a and b), with minimal edits to the text. However, this small adjustment does not affect the overall conclusions or interpretation of the article, which focuses on the response of in-stream large wood and riparian coarse wood to wildfire.</p><figure><figcaption><b data-test=\"figure-caption-text\">Fig. 7</b></figcaption><picture><source srcset=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs42408-023-00240-0/MediaObjects/42408_2023_240_Fig2_HTML.png?as=webp\" type=\"image/webp\"/><img alt=\"figure 2\" aria-describedby=\"Fig2\" height=\"551\" loading=\"lazy\" src=\"//media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs42408-023-00240-0/MediaObjects/42408_2023_240_Fig2_HTML.png\" width=\"685\"/></picture><p>Biological responses that varied as a function of fire severity (RAVG). Biological responses included: <b>a</b> fish densit","PeriodicalId":12273,"journal":{"name":"Fire Ecology","volume":"4 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139496593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prescribed burning mitigates the severity of subsequent wildfires in Mediterranean shrublands","authors":"José Manuel Fernández-Guisuraga, Paulo M. Fernandes","doi":"10.1186/s42408-023-00233-z","DOIUrl":"https://doi.org/10.1186/s42408-023-00233-z","url":null,"abstract":"Prescribed burning (PB) is becoming relevant in fuel reduction and thus fire hazard abatement in fire-prone ecosystems of southern Europe. Yet, empirical evidence on the effectiveness of this practice to mitigate wildfire severity in Mediterranean shrublands is non-existent, despite being the focus of PB efforts in this region. Here, we intended to quantify the protective effect of PB treatment units (2005–2021) to subsequent wildfire severity in shrublands across mainland Portugal, as well as the relative contribution and complex interactions between drivers of wildfire severity in PB-treated areas and untreated neighboring counterparts through Random Forest regression. We leveraged cloud-computing remote sensing data processing in Google Earth Engine to estimate fire severity (PB and wildfire) as the Relativized Burn Ratio (RBR) using Landsat data catalog. PB treatment was particularly effective at mitigating wildfire severity at the first PB-wildfire encounter in shrublands, with a mean reduction of around 24% in RBR units. Fuel age (i.e., time since prescribed burning) in PB-wildfire intersection areas overwhelmed to a large extent the effect of fire weather, burning probability, and PB severity. The mitigating effect of PB on wildfire severity persisted for a fuel age of around 5 years. However, this effect decreased with increasingly adverse fire weather conditions, such that variation in wildfire severity was somewhat insensitive to fuel age under extreme fire weather. Similarly, the lowest wildfire severity experienced in sites with high burning probability, along with the interaction effect observed between burning probability and fuel age, suggest that repeated PB treatments may be useful in controlling fuel accumulation and mitigating wildfire severity. The relative contribution of fire weather in explaining wildfire severity was exceedingly high in untreated areas, doubling that of the other variables in the model in the absence of PB treatment variables. Our results suggest that the implementation of PB treatments at intervals of less than 5 years is of paramount importance to control fuel build-up and fire hazard under extreme fire weather in productive Mediterranean shrublands. Further research on this topic is warranted in other shrublands worldwide, namely in Mediterranean-type climate regions.","PeriodicalId":12273,"journal":{"name":"Fire Ecology","volume":"2 1","pages":""},"PeriodicalIF":5.1,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139481245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}