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Forests
Special Issues
Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges
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Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges

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

Deadline for manuscript submissions: closed (30 April 2025) | Viewed by 8723

Special Issue Editors

Prof. Dr. Rafael Coll Delgado

E-Mail Website
Guest Editor
Center for Biological and Natural Sciences, Federal University of Acre, Rio Branco 69920-900, AC, Brazil
Interests: climate change; forest fires; forest soils; gross primary productivity; carbon emissions; deforestation; remote sensing and fire meteorology
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Marcos Gervásio Pereira

E-Mail Website
Guest Editor
Department of Soils, Federal Rural University of Rio de Janeiro (UFRRJ), Seropédica 23897-000, RJ, Brazil
Interests: climate change; forest fires; forest soils; gross primary productivity; carbon emissions; deforestation; remote sensing and fire meteorology

Special Issue Information

Dear Colleagues,

Climate change has become a central theme of global discussions on environmental issues, in an attempt to ensure that the agreements signed in the past to reduce global emissions of greenhouse gases can be fulfilled. In recent decades, catastrophes arising from anthropic actions and also resulting from natural processes that affect millions of people worldwide have been observed on all continents. Forest fires associated with anthropic issues and the increase in global temperature in recent decades have been the scene of several studies involving numerous researchers. Remote sensing has been gaining new ground and new applications in recent years, being able to generate climate data from natural spaces, such as forest area coverage or fire advances in certain regions. The understanding of the monitoring carried out by remote sensors allows the establishment of observations and accurate analysis of climatic data and natural phenomena. In view of the global panorama of combating climate change, and considering the vulnerability of forests, it is important to understand past events of deforestation and fire outbreaks to understand their effect on the carbon cycle and ecosystem services of the forest.

Submitted manuscripts must be original contributions, not previously published or submitted to other journals.

Prof. Dr. Rafael Coll Delgado
Prof. Dr. Marcos Gervásio Pereira
Guest Editors

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 submissions that pass pre-check are 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 2600 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

  • climate change
  • forest fires
  • forest soils
  • gross primary productivity
  • carbon emissions
  • deforestation
  • remote sensing
  • fire meteorology

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Published Papers (6 papers)

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Research

31 pages, 32346 KiB  
Article
Wildfires During Early Summer in Greece (2024): Burn Severity and Land Use Dynamics Through Sentinel-2 Data
by Ignacio Castro-Melgar, Artemis Tsagkou, Maria Zacharopoulou, Eleftheria Basiou, Ioannis Athinelis, Efstratios-Aimilios Katris, Ioanna-Efstathia Kalavrezou and Issaak Parcharidis
Forests 2025, 16(2), 268; https://doi.org/10.3390/f16020268 - 4 Feb 2025
Viewed by 1976
Abstract
Wildfires are a recurrent and intensifying natural hazard in Mediterranean regions like Greece, driven by prolonged heatwaves, evolving climatic conditions, and human activities. This study leverages Sentinel-2 satellite imagery and Copernicus geospatial data to assess four early-season wildfire events during May and June [...] Read more.
Wildfires are a recurrent and intensifying natural hazard in Mediterranean regions like Greece, driven by prolonged heatwaves, evolving climatic conditions, and human activities. This study leverages Sentinel-2 satellite imagery and Copernicus geospatial data to assess four early-season wildfire events during May and June 2024, which collectively affected 43.44 km2. Burn severity, land cover, and tree cover density were analyzed to evaluate the spatial and environmental impacts of these fires. Validation against Copernicus Emergency Management Service (CEMS) data yielded an overall accuracy of 95.79%, confirming the reliability of the methodology. The Achaia-Ilia wildfire, spanning 40.55 km2, exhibited the highest severity, with 26.93% classified as moderate to high severity. Smaller fires, such as Katsimidi (0.66 km2) and Stamata (1.41 km2), revealed the influence of vegetation type and density on fire dynamics, with Stamata’s sparse tree cover mitigating fire spread. The findings highlight the utility of remote sensing technologies for wildfire monitoring, and underscore the need for tailored management strategies, from vegetation control to urban planning, to enhance ecosystem resilience and mitigate wildfire risks in Mediterranean landscapes. Full article
(This article belongs to the Special Issue Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges)
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19 pages, 8275 KiB  
Article
Tree Functional Traits’ Responses to Forest Edges and Fire in the Savanna Landscapes of Northern South America
by Dolors Armenteras-Pascual, Walter Garcia-Suabita, Arnold Sebastian Garcia-Samaca and Alejandra Reyes-Palacios
Forests 2025, 16(2), 208; https://doi.org/10.3390/f16020208 - 23 Jan 2025
Cited by 1 | Viewed by 759
Abstract
In the fire-prone tropical savanna landscapes of northern South America, forest edge effects significantly shape tree structural integrity and functional traits, with implications for ecosystem resilience, carbon storage, and biodiversity. This study examines how the edge effect, intensified by fire, affects species dominance, [...] Read more.
In the fire-prone tropical savanna landscapes of northern South America, forest edge effects significantly shape tree structural integrity and functional traits, with implications for ecosystem resilience, carbon storage, and biodiversity. This study examines how the edge effect, intensified by fire, affects species dominance, forest structure, and functional trait distributions in this region. Using non-metric multidimensional scaling (NMDS) and generalized additive mixed models (GAMMs), we analyzed changes in species abundance and structural variables (biomass, basal area, tree height, and wood density), as well as leaf (leaf thickness, leaf moisture, leaf dry matter content (LDMC), and specific leaf area (SLA)) and stem (bark and stem thickness and stem-specific density) traits across edge-to-interior gradients. The key findings indicate significant reductions in tree height (F = 19.27, p < 0.01), basal area (F = 6.52, p < 0.01), and biomass (F = 5.44, p < 0.01) near the edges. Leaf moisture (F = 11.8, p < 0.01) and specific leaf area (SLA, F = 7.02, p < 0.01) increased at the edges, reflecting microenvironmental gradients, with heightened fire sensitivity seen in traits like bark thickness (F = 11.88, p < 0.01). Fire-affected areas displayed intensified adaptive trait shifts, suggesting a compounded resilience but potential functional convergence, limiting adaptive capacity under climate stressors. These findings emphasize the ecological significance of edge–fire interactions, advocating conservation strategies to enhance structural and trait diversity for ecosystem stability. Our study underscores the need for targeted management to bolster resilience and biodiversity within these dynamic landscapes as climate pressures intensify. Full article
(This article belongs to the Special Issue Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges)
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26 pages, 9938 KiB  
Article
Correlating Fire Incidents with Meteorological Variables in Dry Temperate Forest
by Khurram Abbas, Ali Ahmed Souane, Hasham Ahmad, Francesca Suita, Zhan Shu, Hui Huang and Feng Wang
Forests 2025, 16(1), 122; https://doi.org/10.3390/f16010122 - 10 Jan 2025
Cited by 1 | Viewed by 801
Abstract
Forest fires pose a significant ecological threat, particularly in the Diamer District, Gilgit-Baltistan, Pakistan, where climatic factors combined with human activities have resulted in severe fire incidents. The present study sought to investigate the correlation between the incidence of forest fires and critical [...] Read more.
Forest fires pose a significant ecological threat, particularly in the Diamer District, Gilgit-Baltistan, Pakistan, where climatic factors combined with human activities have resulted in severe fire incidents. The present study sought to investigate the correlation between the incidence of forest fires and critical meteorological elements, including temperature, humidity, precipitation, and wind speed, over a period of 25 years, from 1998 to 2023. We analyzed 169 recorded fire events, collectively burning approximately 109,400 hectares of forest land. Employing sophisticated machine learning algorithms, Random Forest (RF), and Gradient Boosting Machine (GBM) revealed that temperature and relative humidity during the critical fire season, which spans May through July, are key factors influencing fire activity. Conversely, wind speed was found to have a negligible impact. The RF model demonstrated superior predictive accuracy compared to the GBM model, achieving an RMSE of 5803.69 and accounting for 49.47% of the variance in the burned area. This study presents a novel methodology for predictive fire risk modeling under climate change scenarios in the region, offering significant insights into fire management strategies. Our results underscore the necessity for real-time early warning systems and adaptive management strategies to mitigate the frequency and intensity of escalating forest fires driven by climate change. Full article
(This article belongs to the Special Issue Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges)
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25 pages, 8167 KiB  
Article
Utilizing Machine Learning and Geospatial Techniques to Evaluate Post-Fire Vegetation Recovery in Mediterranean Forest Ecosystem: Tenira, Algeria
by Ali Ahmed Souane, Abbas Khurram, Hui Huang, Zhan Shu, Shujie Feng, Benamar Belgherbi and Zhiyuan Wu
Forests 2025, 16(1), 53; https://doi.org/10.3390/f16010053 - 31 Dec 2024
Cited by 2 | Viewed by 992
Abstract
This study investigated post-fire vegetation recovery in Algeria’s Tenira forest using statistical traits (PCA), RFM, and LANDIS-II spatial analysis. The dataset included satellite imagery and environmental variables such as precipitation, temperature, slope, and elevation, spanning over a decade (2010–2020). Tenira forest is composed [...] Read more.
This study investigated post-fire vegetation recovery in Algeria’s Tenira forest using statistical traits (PCA), RFM, and LANDIS-II spatial analysis. The dataset included satellite imagery and environmental variables such as precipitation, temperature, slope, and elevation, spanning over a decade (2010–2020). Tenira forest is composed of Mediterranean species (36.5%); the biological types encountered are dominated by therophytes (39.19%). Ninety fire outbreaks were recorded, resulting in a loss of 1400.56 ha of surface area. Following the PCA results, precipitation, temperature, slope, and elevation were the main drivers of recovery (PC1 explained 43% alone, with the first five principal components accounting for 90% of observed variance, reflecting significant environmental gradients). Based on these components, an RFM predicted the post-fire recovery with an overall accuracy of 70.5% (Cost-Sensitive Accuracy), Quantity Disagreement of 3.1%, and Allocation Disagreement of 76%, highlighting spatial misallocation as the primary source of errors. The evaluation also identified PC4 (species richness) and PC3 (elevation) as significant predictors, collectively accounting for >50% of the variation in post-fire recovery. In the spatial analysis using LANDIS-II, the growth of vegetation, mainly in mid-altitude areas, was shown to be stronger, with the species consisting of those areas being more diverse. As a result, it demonstrated the connection between species richness and recovery capability. These findings can be useful in developing a management and development strategy, as well as proposing actions for species recovery after fire, such as the construction of firebreaks or the introduction of fireproof species, to make the forest more resistant to weather changes in Mediterranean ecosystems. Full article
(This article belongs to the Special Issue Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges)
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17 pages, 4439 KiB  
Communication
Functional Diversity of Soil Microorganisms in Taiga Forests in the Middle and Late Stages of Restoration after Forest Fires
by Zhichao Cheng, Mingliang Gao, Hong Pan, Xiaoyu Fu, Dan Wei, Xinming Lu, Song Wu and Libin Yang
Forests 2024, 15(7), 1220; https://doi.org/10.3390/f15071220 - 14 Jul 2024
Cited by 1 | Viewed by 1206
Abstract
Fire can significantly affect the structure and function of forest soil microorganisms. Therefore, it is important to study the effects of different fire intensities on soil microbial carbon source utilization capacity in cold-temperate larch forests to protect and utilize forest ecosystems. In this [...] Read more.
Fire can significantly affect the structure and function of forest soil microorganisms. Therefore, it is important to study the effects of different fire intensities on soil microbial carbon source utilization capacity in cold-temperate larch forests to protect and utilize forest ecosystems. In this study, we investigated the effects of different burning intensities on the carbon utilization capacity of soil microorganisms in fire sites from 2010 and 2000 using Biolog-Eco technology. Our findings revealed that (1) fire significantly increased soil pH, AN (available nitrogen), and AK (available potassium) (p < 0.05); (2) fire significantly increased the average color change rate (AWCD) of soil microorganisms (p < 0.05); (3) the Shannon index of soil microorganisms increased significantly, whereas the Simpson index and the McIntosh index decreased significantly after the fire—however, the McIntosh index in the 10M site was not altered; (4) the metabolic functions of soil microbial communities differed significantly among different fire intensities—MC (moisture content), TN (total nitrogen), and AK were the most influential soil environmental factors in the soil microbial community; and (5) mid-term fire restoration significantly increased microbial responses to carbohydrates, amino acids, esters, alcohols, amines, and acids, while late-fire burn sites significantly increased the microbial utilization intensity of amino acids, esters, and acids. In conclusion, fire significantly altered the functional diversity of soil microorganisms and microbial activities related to carbon source substrate utilization. Additionally, the ability of microorganisms to utilize a single carbon source substrate was also altered. Full article
(This article belongs to the Special Issue Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges)
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40 pages, 9776 KiB  
Article
Framework to Create Inventory Dataset for Disaster Behavior Analysis Using Google Earth Engine: A Case Study in Peninsular Malaysia for Historical Forest Fire Behavior Analysis
by Yee Jian Chew, Shih Yin Ooi, Ying Han Pang and Zheng You Lim
Forests 2024, 15(6), 923; https://doi.org/10.3390/f15060923 - 26 May 2024
Cited by 2 | Viewed by 1530
Abstract
This study developed a comprehensive framework using Google Earth Engine to efficiently generate a forest fire inventory dataset, which enhanced data accessibility without specialized knowledge or access to private datasets. The framework is applicable globally, and the datasets generated are freely accessible and [...] Read more.
This study developed a comprehensive framework using Google Earth Engine to efficiently generate a forest fire inventory dataset, which enhanced data accessibility without specialized knowledge or access to private datasets. The framework is applicable globally, and the datasets generated are freely accessible and shareable. By implementing the framework in Peninsular Malaysia, significant forest fire factors were successfully extracted, including the Keetch–Byram Drought Index (KBDI), soil moisture, temperature, windspeed, land surface temperature (LST), Palmer Drought Severity Index (PDSI), Normalized Vegetation Index (NDVI), landcover, and precipitation, among others. Additionally, this study also adopted large language models, specifically GPT-4 with the Noteable plugin, for preliminary data analysis to assess the dataset’s validity. Although the plugin effectively performed basic statistical analyses and visualizations, it demonstrated limitations, such as selectively dropping or choosing only relevant columns for tests and automatically modifying scales. These behaviors underscore the need for users to perform additional checks on the codes generated to ensure that they accurately reflect the intended analyses. The initial findings indicate that factors such as KBDI, LST, climate water deficit, and precipitation significantly impact forest fire occurrences in Peninsular Malaysia. Future research should explore extending the framework’s application to various regions and further refine it to accommodate a broader range of factors. Embracing and rigorously validating large language model technologies, alongside developing new tools and plugins, are essential for advancing the field of data analysis. Full article
(This article belongs to the Special Issue Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges)
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