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Special Issue "Managing Wildfires in Changing Climates: History, Current Practice, and Challenges"

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Ecology and Management".

Deadline for manuscript submissions: closed (20 June 2018)

Special Issue Editor

Guest Editor
Dr. Jesús San-Miguel-Ayanz

European Commission Joint Research Centre, Directorate E: Space, Security & Migration, Disaster Risk Management, Via Fermi 1, I-21027 Ispra, Italy
Website | E-Mail
Phone: +39 3481411403
Interests: Forest fire; Forest information and monitoring; Remote sensing

Special Issue Information

Dear Colleagues,

Fire has been integral agent of forest ecosystem dynamics in many climate-diverse regions of the world. These ecosystems were shaped according to the predominant fire regimes in the regions. Nowadays, climate change is affecting forest ecosystem dynamics, altering species succession and often making ecosystems more vulnerable to wildfires. Moreover, climate change has invoked changes in fire regimes, changing fire seasonality and altering fire size, intensity and frequency. Areas that were traditionally fire prone have experienced an increase of critical fire events that pose questions on traditional wildfire management practices. It is, thus, essential to define a new paradigm of wildfire dynamics at the global scale, taking into account the smooth effect of climate change but also the presence of critical climatic events such as heat weaves, droughts and persistent above-normal temperatures for continued periods. These effects are not only changing fire regimes but may be drivers of critical fires beyond the known fire reality. In this Special Issue, we encourage the submission of studies covering all fields of wildfire analysis, including wildfire management and monitoring systems, as well as new perspectives that may contribute to improving the knowledge and management of wildfires in a changing climate.

Dr. Jesús San-Miguel-Ayanz
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Wildfire
  • Climate Change
  • Fire Regimes
  • Fire Monitoring
  • Ecosystem Dynamics

Published Papers (6 papers)

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Research

Open AccessArticle Fire Management in Mount Kenya: A Case Study of Gathiuru Forest Station
Forests 2018, 9(8), 481; https://doi.org/10.3390/f9080481
Received: 11 June 2018 / Revised: 25 July 2018 / Accepted: 2 August 2018 / Published: 8 August 2018
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Abstract
This paper proposes an Integrated Fire Management (IFM) framework that can be used to support communities and resource managers in finding effective and efficient approaches to prevent damaging fires, as well as to maintain desirable fire regimes in Kenya. Designing and implementing an [...] Read more.
This paper proposes an Integrated Fire Management (IFM) framework that can be used to support communities and resource managers in finding effective and efficient approaches to prevent damaging fires, as well as to maintain desirable fire regimes in Kenya. Designing and implementing an IFM approach in Kenya calls for a systematic understanding of the various uses of fire and the underlying perceptions and traditional ecological knowledge of the local people. The proposed IFM framework allows different stakeholders to evaluate the risks posed by fires and balance them with their beneficial ecological and economic effects making it easier for them to develop effective fire management approaches. A case study of the proposed IFM framework was conducted in Gathiuru Forest, which that is part of the larger Mt. Kenya Forest Ecosystem. Focus group discussions were held with key resource persons, primary and secondary data on socio-economic activities was studied, fire and weather records were analysed and the current fire management plans were consulted. Questionnaires were used to assess how the IFM is implemented in the Gathiuru Forest Station. The results show that the proposed IFM framework is scalable and can be applied in places with fire-dependent ecosystems as well as in places with fire-sensitive ecosystems in Kenya. The effectiveness of the proposed IFM framework depends on the active participation, formulation and implementation of the IFM activities by the main stakeholder groups (Kenya Forest Service (KFS), Kenya Wildlife Service (KWS), and the Community Forest Associations (CFA). The proposed IFM framework helps in implementing cost-effective approaches to prevent damaging fires and maintain desirable fire regimes in Kenya. Full article
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Open AccessArticle Modeling Burned Areas in Indonesia: The FLAM Approach
Forests 2018, 9(7), 437; https://doi.org/10.3390/f9070437
Received: 20 June 2018 / Revised: 16 July 2018 / Accepted: 18 July 2018 / Published: 20 July 2018
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Abstract
Large-scale wildfires affect millions of hectares of land in Indonesia annually and produce severe smoke haze pollution and carbon emissions, with negative impacts on climate change, health, the economy and biodiversity. In this study, we apply a mechanistic fire model to estimate burned [...] Read more.
Large-scale wildfires affect millions of hectares of land in Indonesia annually and produce severe smoke haze pollution and carbon emissions, with negative impacts on climate change, health, the economy and biodiversity. In this study, we apply a mechanistic fire model to estimate burned area in Indonesia for the first time. We use the Wildfire Climate Impacts and Adaptation Model (FLAM) that operates with a daily time step on the grid cell of 0.25 arc degrees, the same spatio-temporal resolution as in the Global Fire Emissions Database v4 (GFED). GFED data accumulated from 2000–2009 are used for calibrating spatially-explicit suppression efficiency in FLAM. Very low suppression levels are found in peatland of Kalimantan and Sumatra, where individual fires can burn for very long periods of time despite extensive rains and fire-fighting attempts. For 2010–2016, we validate FLAM estimated burned area temporally and spatially using annual GFED observations. From the validation for burned areas aggregated over Indonesia, we obtain Pearson’s correlation coefficient separately for wildfires and peat fires, which equals 0.988 in both cases. Spatial correlation analysis shows that in areas where around 70% is burned, the correlation coefficients are above 0.6, and in those where 30% is burned, above 0.9. Full article
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Open AccessArticle Effect of Topography on Persistent Fire Refugia of the Canadian Rocky Mountains
Forests 2018, 9(6), 285; https://doi.org/10.3390/f9060285
Received: 4 April 2018 / Revised: 8 May 2018 / Accepted: 18 May 2018 / Published: 23 May 2018
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Abstract
Persistent fire refugia, which are forest stands that have survived multiple fires, play an important ecological role in the resilience of mountainous forest ecosystems following disturbances. The loss of numerous refugia patches to large, high-severity fires in recent years is prompting the need [...] Read more.
Persistent fire refugia, which are forest stands that have survived multiple fires, play an important ecological role in the resilience of mountainous forest ecosystems following disturbances. The loss of numerous refugia patches to large, high-severity fires in recent years is prompting the need to better understand drivers of fire refugia endurance. We investigate the role of topographic features on fire refugia survivorship based on pre-1950 fire regime conditions. Mapped refugia patches (n = 557) covering 28% of the forested landscape were used to develop three predictive models based on patch size (all sizes, <30 ha, <10 ha), as a function of explanatory variables describing several components of topography. Five topographic variables consistently favoured persistent fire refugia occurrence, though the ranking of explanatory variable importance varied among patch-size models. For the all-refugia model, elevation (23.7%), proportion of non-fuel at a 5000-m scale (20.3%), solar radiation (14.6%), Topographic Position Index at a 2000-m scale (10.1%), and distance from rivers (10.1%) were the top variables. The models’ predictive abilities were high, but decreased with larger patch sizes. We conclude that many suitable areas are currently unoccupied by fire refugia; that random elements affect their survivorship; and that additional environmental factors not considered in this study may contribute to their persistence. With changing climate and fire-regime conditions, careful fire and forest management considerations will be needed to limit future losses of persistent fire refugia forests. Full article
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Open AccessArticle Developing Models to Predict the Number of Fire Hotspots from an Accumulated Fuel Dryness Index by Vegetation Type and Region in Mexico
Forests 2018, 9(4), 190; https://doi.org/10.3390/f9040190
Received: 20 February 2018 / Revised: 24 March 2018 / Accepted: 29 March 2018 / Published: 7 April 2018
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Abstract
Understanding the linkage between accumulated fuel dryness and temporal fire occurrence risk is key for improving decision-making in forest fire management, especially under growing conditions of vegetation stress associated with climate change. This study addresses the development of models to predict the number [...] Read more.
Understanding the linkage between accumulated fuel dryness and temporal fire occurrence risk is key for improving decision-making in forest fire management, especially under growing conditions of vegetation stress associated with climate change. This study addresses the development of models to predict the number of 10-day observed Moderate-Resolution Imaging Spectroradiometer (MODIS) active fire hotspots—expressed as a Fire Hotspot Density index (FHD)—from an Accumulated Fuel Dryness Index (AcFDI), for 17 main vegetation types and regions in Mexico, for the period 2011–2015. The AcFDI was calculated by applying vegetation-specific thresholds for fire occurrence to a satellite-based fuel dryness index (FDI), which was developed after the structure of the Fire Potential Index (FPI). Linear and non-linear models were tested for the prediction of FHD from FDI and AcFDI. Non-linear quantile regression models gave the best results for predicting FHD using AcFDI, together with auto-regression from previously observed hotspot density values. The predictions of 10-day observed FHD values were reasonably good with R2 values of 0.5 to 0.7 suggesting the potential to be used as an operational tool for predicting the expected number of fire hotspots by vegetation type and region in Mexico. The presented modeling strategy could be replicated for any fire danger index in any region, based on information from MODIS or other remote sensors. Full article
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Open AccessArticle Conditional Performance Evaluation: Using Wildfire Observations for Systematic Fire Simulator Development
Forests 2018, 9(4), 189; https://doi.org/10.3390/f9040189
Received: 2 February 2018 / Revised: 26 March 2018 / Accepted: 2 April 2018 / Published: 6 April 2018
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Abstract
Faster than real-time wildland fire simulators are being increasingly adopted by land managers to provide decision support for tactical wildfire management and assist with strategic risk planning. These simulators are typically based on simple forward rate-of-spread algorithms that were predominantly developed using observations [...] Read more.
Faster than real-time wildland fire simulators are being increasingly adopted by land managers to provide decision support for tactical wildfire management and assist with strategic risk planning. These simulators are typically based on simple forward rate-of-spread algorithms that were predominantly developed using observations of experimental fires. Given their operational use, it is important that fire simulators be assessed in terms of their performance for their intended use; predicting the spatial progression of wildfires. However, the conditions under which wildfires occur cannot be easily replicated experimentally. We describe and demonstrate a method for use in model development, whereby a dataset comprised of wildfire case-studies is used for evaluating the predictive performance of fire simulators. Two different versions of the model PHOENIX RapidFire were assessed, one incorporating a novel algorithm that accounts fine-scale spatial variation in landscape dryness. Evaluation was done by comparing simulator predictions against contemporaneous observations of 9 different wildfires that occurred in Australia. Performance was quantified using the sum of the Area Difference Indices—a measure of prediction overlap calculated for each prediction/observation pair. The two versions of the model performed similarly, with the newer version being marginally (but not statistically significantly) better when outcomes were summarised across all fires. Despite this, it did not perform better in all cases, with three of the 9 fires better predicted using the original model. Wildfire evaluation datasets were demonstrated to provide valuable feedback for model development, however the limited availability of data means power is lacking for detailed comparisons. With increasingly extreme weather conditions resulting from climate change, conditions under which wildfires occur are likely to continue to extend well beyond those under which fire models algorithms were developed. Consequently, the adoption of improved methods for collecting and utilising wildfire data is critical to ensure fire simulators retain relevance. Full article
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Open AccessArticle Differences in Human versus Lightning Fires between Urban and Rural Areas of the Boreal Forest in Interior Alaska
Forests 2017, 8(11), 422; https://doi.org/10.3390/f8110422
Received: 4 September 2017 / Revised: 17 October 2017 / Accepted: 31 October 2017 / Published: 4 November 2017
Cited by 1 | PDF Full-text (2446 KB) | HTML Full-text | XML Full-text
Abstract
In western North America, the carbon-rich boreal forest is experiencing warmer temperatures, drier conditions and larger and more frequent wildfires. However, the fire regime is also affected by direct human activities through suppression, ignition, and land use changes. Models are important predictive tools [...] Read more.
In western North America, the carbon-rich boreal forest is experiencing warmer temperatures, drier conditions and larger and more frequent wildfires. However, the fire regime is also affected by direct human activities through suppression, ignition, and land use changes. Models are important predictive tools for understanding future conditions but they are based on regional generalizations of wildfire behavior and weather that do not adequately account for the complexity of human–fire interactions. To achieve a better understanding of the intensity of human influence on fires in this sparsely populated area and to quantify differences between human and lightning fires, we analyzed fires by both ignition types in regard to human proximity in urban (the Fairbanks subregion) and rural areas of interior Alaska using spatial (Geographic Information Systems) and quantitative analysis methods. We found substantial differences in drivers of wildfire: while increases in fire ignitions and area burned were caused by lightning in rural interior Alaska, in the Fairbanks subregion these increases were due to human fires, especially in the wildland urban interface. Lightning fires are starting earlier and fires are burning longer, which is much more pronounced in the Fairbanks subregion than in rural areas. Human fires differed from lightning fires in several ways: they started closer to settlements and highways, burned for a shorter duration, were concentrated in the Fairbanks subregion, and often occurred outside the brief seasonal window for lightning fires. This study provides important insights that improve our understanding of the direct human influence on recently observed changes in wildfire regime with implications for both fire modeling and fire management. Full article
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