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Forests
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Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges—2nd...
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Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges—2nd Edition

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 (31 March 2026) | Viewed by 2814

Special Issue Editors

Prof. Dr. Rafael Coll Delgado

E-Mail Website
Guest Editor
Center for Biological and Natural Sciences, Federal University of Acre (UFAC), Rio Branco, Acre, 23897-000, Brazil
Interests: forest vulnerability; climate change; dendroclimatology; fire foci; modeling; remote sensing; soil carbon stocks; climate
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Marcos Gervásio Pereira

E-Mail Website
Guest Editor
Department of Soils of the Federal Rural University of Rio de Janeiro (UFRRJ), Seropédica 23897-000, RJ, Brazil
Interests: forest vulnerability; climate change; soil carbon stocks; climate; pedology; nutrient cycling; soil use and management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Climate change has become a central theme in global discussions on environmental issues as an effort to ensure that past agreements 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 applications in recent years, enabling the generation of climate data from natural spaces, such as forest area coverage or fire advances in specific regions. The understanding of monitoring carried out by remote sensors enables the establishment of observations and the accurate analysis of climatic data and natural phenomena. In light of the global effort to combat climate change and considering the vulnerability of forests, it is crucial to understand past events of deforestation and fire outbreaks to comprehend their impact on the carbon cycle and the ecosystem services of forests.

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 250 words) can be sent to the Editorial Office for assessment.

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 (3 papers)

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Research

20 pages, 2430 KB  
Article
Real-Time IoT-Enabled Decision Support for Forest Supply Chains: An Optimization-Simulation Approach to Mitigating Wildfire Risk
by Reinaldo Gomes, Bernardine Chigozie Chidozie, João C. O. Matias and Ruxanda Godina Silva
Forests 2026, 17(2), 279; https://doi.org/10.3390/f17020279 - 19 Feb 2026
Viewed by 407
Abstract
Climate change has intensified wildfire risk, creating an urgent need for integrated, data-driven tools that connect forest operations with fuel-reduction strategies. This paper introduces a real-time IoT-enabled Decision Support System (DSS) that unifies wood traceability with optimization–simulation planning for biomass collection and processing. [...] Read more.
Climate change has intensified wildfire risk, creating an urgent need for integrated, data-driven tools that connect forest operations with fuel-reduction strategies. This paper introduces a real-time IoT-enabled Decision Support System (DSS) that unifies wood traceability with optimization–simulation planning for biomass collection and processing. The system captures detailed operational data from harvesting, transportation, and processing through IoT devices and industry formats, enabling the continuous monitoring of wood flows and precise estimation of biomass residues that directly contribute to wildfire fuel loads. The DSS transforms these real-time streams into actionable planning outputs through an optimization–simulation module that generates efficient biomass harvesting and processing schedules while evaluating their robustness under wildfire-related constraints. By linking wood traceability with biomass logistics, the system provides the missing operational bridge between forest management decisions and wildfire-risk mitigation. Results show that the DSS not only improves operational efficiency but also enhances resilience by supporting risk-aware planning, prioritizing high-exposure areas, and reducing the accumulation of hazardous biomass. These insights demonstrate how digital traceability and robust planning can work together to lower ignition potential while maintaining service levels and operational continuity. Overall, this work presents a practical and scalable solution that strengthens forest supply chain resilience and provides a new pathway for integrating wildfire-risk mitigation into everyday operational planning. Full article
(This article belongs to the Special Issue Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges—2nd Edition)
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24 pages, 2957 KB  
Article
Development of a PM2.5 Emission Factor Prediction Model for Shrubs in the Xiao Xing’an Mountains Based on Coupling Effects of Physical Factors
by Tianbao Zhang, Xiaoying Han, Haifeng Gao, Hui Huang, Zhiyuan Wu, Yu Gu, Bingbing Lu and Zhan Shu
Forests 2026, 17(2), 199; https://doi.org/10.3390/f17020199 - 2 Feb 2026
Viewed by 379
Abstract
Over recent years, the intensity of forest fires has escalated, with wildfire-emitted pollutants exerting substantial impacts on the environment, ecosystems, and human well-being. This study developed a robust predictive framework to quantify wildfire-induced PM2.5 emission factors (EFs) using seven shrub species—Corylus [...] Read more.
Over recent years, the intensity of forest fires has escalated, with wildfire-emitted pollutants exerting substantial impacts on the environment, ecosystems, and human well-being. This study developed a robust predictive framework to quantify wildfire-induced PM2.5 emission factors (EFs) using seven shrub species—Corylus mandshurica, Eleutherococcus senticosus, Philadelphus schrenkii, Sorbaria sorbifolia, Syringa reticulata, Spiraea salicifolia, and Lonicera maackii. These species represent ecological cornerstones of Northeast Asian forests and hold global relevance as widely introduced or invasive taxa in North America and Europe. The novelty of this research lies in the integration of traditional statistical inference with machine learning to resolve the complex coupling between fuel traits and emissions. We conducted 1134 laboratory-controlled burns in the Liangshui National Nature Reserve, evaluating two continuous and three categorical variables. Initial screening via Analysis of Variance (ANOVA) and stepwise linear regression (Step-AIC) identified the primary drivers of emissions and revealed that interspecific differences among the seven shrubs did not significantly affect the EF (p = 0.0635). To ensure statistical rigor, a log-transformation was applied to the EF data to correct for right-skewness and heteroscedasticity inherent in raw observations. Linear Mixed-effects Models (LMMs) and Gradient Boosting Machines (GBMs) were subsequently employed to quantify factor effects and capture potential nonlinearities. The LMM results consistently identified burning type and plant part as the dominant determinants: smoldering combustion and leaf components exerted strong positive effects on PM2.5 emissions compared to flaming and branch components. Fuel load was positively correlated with emissions, while moisture content showed a significant negative effect. Notably, the model identified a significant negative quadratic effect for moisture content, indicating a non-linear inhibitory trend as moisture increases. While interspecific differences among the seven shrubs did not significantly affect EFs suggesting that physical fuel traits exert a more consistent influence than species-specific genetic backgrounds, complex interactions were captured. These include a negative synergistic effect between leaves and smoldering, and a positive interaction between moisture content and leaves that significantly amplified emissions. This research bridges the gap between physical fuel traits and chemical smoke production, providing a high-resolution tool for refining global biomass burning emission inventories and assisting international forest management in similar temperate biomes. Full article
(This article belongs to the Special Issue Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges—2nd Edition)
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34 pages, 12347 KB  
Article
Fire Danger Climatology Using the Hot–Dry–Windy Index: Case Studies from Portugal
by Cristina Andrade and Lourdes Bugalho
Forests 2025, 16(9), 1417; https://doi.org/10.3390/f16091417 - 4 Sep 2025
Cited by 3 | Viewed by 1473
Abstract
Wildfires in Portugal have become increasingly frequent and severe, driven by a combination of fuel accumulation, extreme meteorological conditions, and topographic complexity. This study assesses the applicability of the Hot–Dry–Windy (HDW) index in characterizing fire-weather conditions during five major wildfires: Chamusca (2003), Pedrógão [...] Read more.
Wildfires in Portugal have become increasingly frequent and severe, driven by a combination of fuel accumulation, extreme meteorological conditions, and topographic complexity. This study assesses the applicability of the Hot–Dry–Windy (HDW) index in characterizing fire-weather conditions during five major wildfires: Chamusca (2003), Pedrógão Grande and Lousã (2017), Monchique (2018), and Covilhã (2022). HDW values were computed at sub-daily resolution and compared against a 1991–2020 climatology. This study also evaluates the HDW index as a high-resolution fire danger indicator in Portugal and compares it with the traditional FWI using percentile-based climatology. The findings indicate that during 12 and 15 UTC, HDW in the wildfires in Chamusca (2003) and Lousã (2017) exceeded 180–370 units, suggesting extreme air conditions driven by hot, dry, and windy weather patterns. These values denoted extremely flammable conditions since they were significantly higher than the 95th percentile. A distinct peak at 15 UTC for Pedrógão Grande (2017) topped 140 units (>P95), which is consistent with the ignition timing and a rapid beginning spread. A continuous HDW anomaly that peaked above 200 units between 2 August and 5 August preceded the Monchique (2018) event, suggesting extended heat stress and increased wind contribution. While not as severe as in previous instances, HDW at Covilhã (2022) was above the 75th percentile in the early afternoon (12–18 UTC). Results show that in all cases, HDW values exceeded the 90th and 95th percentiles during the hours of ignition and early fire spread, with the most critical anomalies occurring between 12 UTC and 18 UTC. Spatial analyses revealed regional-scale patterns of HDW exceedance, aligning with observed ignition zones. Comparisons with the Canadian Fire Weather Index (FWI) revealed that while the FWI captured seasonal fuel aridity, the HDW more effectively resolved short-term meteorological extremes, particularly wind and atmospheric dryness. The HDW index was found to identify high-risk conditions even when FWI values were moderate, highlighting its added diagnostic value. These results support the inclusion of HDW in operational fire danger rating systems for Portugal and other Mediterranean countries, where compound fire-weather extremes are becoming more frequent due to climate change. Full article
(This article belongs to the Special Issue Managing Forest Wildfires in Climate Changes: New Paradigms and Challenges—2nd Edition)
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