Forests

Research

15 pages, 5453 KiB

Open AccessArticle

Experimental Analysis on the Behaviors of a Laboratory Surface Fire Spreading across a Firebreak with Different Winds

by Hanwen Guo, Zhengyuan Yang, Ziqun Ye, Dong Xiang, Yunji Gao and Yuchun Zhang

Forests 2023, 14(12), 2455; https://doi.org/10.3390/f14122455 - 17 Dec 2023

Viewed by 871

In this work, a series of laboratory surface fire experiments were performed over a pine needle fuel bed to investigate the effectiveness of a firebreak and the behaviors of a surface fire across a firebreak. Seven wind velocities of 0~3.0 m/s and six [...] Read more.

In this work, a series of laboratory surface fire experiments were performed over a pine needle fuel bed to investigate the effectiveness of a firebreak and the behaviors of a surface fire across a firebreak. Seven wind velocities of 0~3.0 m/s and six firebreak widths of 10~35 cm are varied. The behaviors of a surface fire across the firebreak, the heat flux received by fuel surface and fuel temperature before and after the firebreak are analyzed and compared simultaneously. The main conclusions are as follows: the behaviors of a surface fire spreading across a firebreak under different wind velocities are classified into three categories—no ignition, ignition by flame contact and ignition by spot fires. When the wind velocity is not more than 1.0 m/s, the surface fire cannot successfully cross the firebreak; as wind velocity changes from 1.5 m/s to 2.5 m/s, the fuel after the firebreak can be ignited by flame contact for relatively narrow firebreak conditions; when the wind velocity increases to 3.0 m/s, the burning fuel can be blown away along the fuel bed, and the fuel behind the firebreak will be ignited by spot fire. A linear relationship between the threshold of firebreak width and the fireline intensity is obtained, and the linear fitting coefficient in this paper is larger than the results reported by Wilson (0.36). For no ignition conditions, the fuel temperature and the heat flux received by the fuel after firebreak are significantly lower than those before the firebreak, whereas their variations over time are similar to those before the firebreak for ignition conditions. Moreover, for no ignition conditions, the maximum fuel temperature and the heat flux after the firebreak increase with wind velocity, but decrease with firebreak width. Additionally, when the fuel temperature (253 °C) and the heat flux received by the fuel considering the radiation and convection (43 kW/m²) after firebreak exceed a threshold value, the surface fire can successfully cross the firebreak. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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20 pages, 4588 KiB

Open AccessArticle

Analysis of Wildfire Danger Level Using Logistic Regression Model in Sichuan Province, China

by Wanyu Peng, Yugui Wei, Guangsheng Chen, Guofan Lu, Qing Ye, Runping Ding, Peng Hu and Zhenyu Cheng

Forests 2023, 14(12), 2352; https://doi.org/10.3390/f14122352 - 29 Nov 2023

Viewed by 965

Abstract

Sichuan Province preserves numerous rare and ancient species of plants and animals, making it an important bio-genetic repository in China and even the world. However, this region is also vulnerable to fire disturbance due to the rich forest resources, complex topography, and dry [...] Read more.

Sichuan Province preserves numerous rare and ancient species of plants and animals, making it an important bio-genetic repository in China and even the world. However, this region is also vulnerable to fire disturbance due to the rich forest resources, complex topography, and dry climate, and thus has become one of main regions in China needing wildfire prevention. Analyzing the main driving factors influencing wildfire incidence can provide data and policy guidance for wildfire management in Sichuan Province. Here we analyzed the spatial and temporal distribution characteristics of wildfires in Sichuan Province based on the wildfire spot data during 2010–2019. Based on 14 input variables, including climate, vegetation, human factors, and topography, we applied the Pearson correlation analysis and Random Forest methods to investigate the most important factors in driving wildfire occurrence. Then, the Logistic model was further applied to predict wildfire occurrences. The results showed that: (1) The southwestern Sichuan Province is a high-incidence area for wildfires, and most fires occurred from January to June. (2) The most important factor affecting wildfire occurrence is monthly average temperature, followed by elevation, monthly precipitation, population density, Normalized Difference Vegetation Index (NDVI), NDVI in the previous month, and Road kernel density. (3) The Logistic wildfire prediction model yielded good performance, with the area under curve (AUC) values higher than 0.94, overall accuracy (OA) higher than 86%, true positive rate (TPR) values higher than 0.82, and threat score (TS) values higher than 0.71. The final selected prediction model has an AUC of 0.944, an OA of 87.28%, a TPR of 0.829, and a TS of 0.723. (4) The results of the prediction indicate that extremely high danger of wildfires (probability of fire occurrence higher than 0.8) is concentrated in the southwest, which accounted for about 1% of the area of the study region, specifically in Panzhihua and Liangshan. These findings demonstrated the effectiveness of the Logistic model in predicting forest fires in Sichuan Province, providing valuable insights regarding forest fire management and prevention efforts in this region. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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18 pages, 5724 KiB

Open AccessArticle

Effects of Prescribed Burning on Surface Dead Fuel and Potential Fire Behavior in Pinus yunnanensis in Central Yunnan Province, China

by Jin Wang, Ruicheng Hong, Cheng Ma, Xilong Zhu, Shiying Xu, Yanping Tang, Xiaona Li, Xiangxiang Yan, Leiguang Wang and Qiuhua Wang

Forests 2023, 14(9), 1915; https://doi.org/10.3390/f14091915 - 20 Sep 2023

Cited by 1 | Viewed by 866

Abstract

Prescribed burning is a widely used fuel management employed technique to mitigate the risk of forest fires. The Pinus yunnanensis Franch. forest, which is frequently prone to forest fires in southwestern China, serves as a prime example for investigating the effects of prescribed [...] Read more.

Prescribed burning is a widely used fuel management employed technique to mitigate the risk of forest fires. The Pinus yunnanensis Franch. forest, which is frequently prone to forest fires in southwestern China, serves as a prime example for investigating the effects of prescribed burning on the flammability of surface dead fuel. This research aims to establish a scientific foundation for managing dead fuel in forests, as well as fire prevention and control strategies. Field data was collected from P. yunnanensis forests located in central Yunnan Province in 2021 and 2022. The study implemented a randomized complete block design with two blocks and three treatments: an unburned control (UB), one year after the prescribed burning (PB1a), and three years after the prescribed burning (PB3a). These treatments were evaluated based on three indices: surface dead-bed structure, physicochemical properties, and potential fire behavior parameters. To analyze the stand characteristics of the sample plots, a paired t-test was conducted. The results indicated no significant differences in the stand characteristics of P. yunnanensis following prescribed burning (p > 0.05). Prescribed burning led to a significant decrease in the average surface dead fuel load from 10.24 t/ha to 3.70 t/ha, representing a reduction of 63.87%. Additionally, the average fire−line intensity decreased from 454 kw/m to 190 kw/m, indicating a decrease of 58.15%. Despite prescribed burning, there were no significant changes observed in the physical and chemical properties of dead fuels (p > 0.05). However, the bed structure of dead fuels and fire behavior parameters exhibited a significant reduction compared with the control sample site. The findings of this study provide essential theoretical support for the scientific implementation of prescribed burning programs and the accurate evaluation of ecological and environmental effects post burning. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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18 pages, 33822 KiB

Open AccessArticle

Assessing the Use of Burn Ratios and Red-Edge Spectral Indices for Detecting Fire Effects in the Greater Yellowstone Ecosystem

by David M. Szpakowski, Jennifer L. R. Jensen, T. Edwin Chow and David R. Butler

Forests 2023, 14(7), 1508; https://doi.org/10.3390/f14071508 - 24 Jul 2023

Viewed by 949

Abstract

Burn severity is commonly assessed using Burn Ratios and field measurements to provide land managers with estimates of the degree of burning in an area. However, less commonly studied is the ability of spectral indices and Burn Ratios to estimate field-measured fire effects. [...] Read more.

Burn severity is commonly assessed using Burn Ratios and field measurements to provide land managers with estimates of the degree of burning in an area. However, less commonly studied is the ability of spectral indices and Burn Ratios to estimate field-measured fire effects. Past research has shown low correlations between fire effects and Landsat-derived Burn Ratios, but with the launch of the Sentinel-2 constellation, more spectral bands with finer spatial resolutions have become available. This paper explores the use of several red-edge-based indices and Burn Ratios alongside more ‘traditional’ spectral indices for predicting fire effects, measured from the Maple and Berry fires in Wyoming, USA. The fire effects include ash depth, char depth, post-fire dead lodgepole pine (Pinus contorta; PICO) density/stumps, mean basal diameter, cone density on dead post-fire trees, coarse wood percent cover/volume/mass, percent cover of ghost logs and initial regeneration of post-fire PICO/aspen density. All-possible-models regression was used to determine the best models for estimating each fire effect. Models with satisfactory R² values were constructed for post-fire dead PICO stumps (0.663), coarse wood percent cover (0.691), coarse wood volume (0.833), coarse wood mass (0.838), ash depth (0.636) and percent cover of ghost logs (0.717). Red-edge-based indices were included in all of the satisfactory models, which shows that the red-edge bands may be useful for measuring fire effects. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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11 pages, 1288 KiB

Open AccessArticle

Evaluation of Litter Flammability from Dominated Artificial Forests in Southwestern China

by Shuting Li, Zihan Zhang, Jiangkun Zheng, Guirong Hou, Han Liu and Xinglei Cui

Forests 2023, 14(6), 1229; https://doi.org/10.3390/f14061229 - 14 Jun 2023

Cited by 1 | Viewed by 1061

Abstract

Southwestern China has a large area of artificial forests and has experienced massive environmental and social losses due to forest fires. Evaluating the flammability of fuels from dominated forests in this region can help assess the fire risk and predict potential fire behaviors [...] Read more.

Southwestern China has a large area of artificial forests and has experienced massive environmental and social losses due to forest fires. Evaluating the flammability of fuels from dominated forests in this region can help assess the fire risk and predict potential fire behaviors in these forests, thus guiding forest fire management. However, such studies have been scarcely reported in this region. In this study, the flammability of litter from nine forest types, which are common in southwestern China, was evaluated by measuring organic matter content, ignition point, and calorific value. All these flammability characteristics of fuels varied significantly across forest types. By using principal component analysis and K-means clustering, litters were classified into three groups: highly susceptible to ignition with low fire intensity (Pinus densata, Pinus densata-Populus simonii, Pinus yunnanensis, Larix gmelini, Pinus armandii), less susceptible to ignition with high fire intensity (Abies fabri-Populus simonii), and median ignitibility and fire intensity (Abies fabri, Abies fabri-Picea asperata, Platycladus orientalis). Our study can help predict the risk and intensity of fires in the studied forests and serve as a source of information for fire management in southwestern China. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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14 pages, 7085 KiB

Open AccessArticle

Examining and Reforming the Rothermel Surface Fire Spread Model under No-Wind and Zero-Slope Conditions for the Karst Ecosystems

by Yunlin Zhang and Lingling Tian

Forests 2023, 14(6), 1088; https://doi.org/10.3390/f14061088 - 24 May 2023

Cited by 2 | Viewed by 1160

Abstract

The Rothermel model, which has been widely used to predict the rate of forest fire spread, has errors that restrict its ability to reflect the actual rate of spread (ROS). In this study, the fuels from seven typical tree species in the Karst [...] Read more.

The Rothermel model, which has been widely used to predict the rate of forest fire spread, has errors that restrict its ability to reflect the actual rate of spread (ROS). In this study, the fuels from seven typical tree species in the Karst ecosystems in southern China were considered as the research objects. Through indoor burning simulation, three methods, namely directly using the Rothermel model, re-estimating the parameters of the Rothermel, and reforming the model, were evaluated for applicability in Karst ecosystems. We found that the direct use of the Rothermel model for predicting the ROS in the Karst ecosystems is not practical, and the relative error can be as high as 50%. However, no significant differences between the prediction effect of re-estimating the parameters of the Rothermel and the reformed model were found, but the reform model showed more evident advantages of being simpler, and the errors were lower. Our research proposes a new method that is more suitable for predicting the rate of forest fire spread of typical fuels in Karst ecosystems under flat and windless conditions, which is of great significance for further understanding and calculating the ROS of forest fires in the region. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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12 pages, 1625 KiB

Open AccessArticle

Improving the Combustion Factor to Estimate GHG Emissions Associated with Fire in Pinus radiata and Eucalyptus spp. Plantations in Chile

by Guillermo Federico Olmedo, Horacio Gilabert, Horacio Bown, Rebeca Sanhueza, Pía Silva, Carlos Jorquera-Stuardo and Francisco Sierra

Forests 2023, 14(2), 403; https://doi.org/10.3390/f14020403 - 16 Feb 2023

Viewed by 1635

Abstract

Forest plantations can substantially contribute to carbon sequestration and greenhouse gas (GHG) mitigation at the country and global scales. Forest fires (especially when combined with droughts) may remarkably reduce such carbon sequestration capability. The IPCC has global-scale estimates for such losses, but they [...] Read more.

Forest plantations can substantially contribute to carbon sequestration and greenhouse gas (GHG) mitigation at the country and global scales. Forest fires (especially when combined with droughts) may remarkably reduce such carbon sequestration capability. The IPCC has global-scale estimates for such losses, but they can vary widely depending on crops, climate, topography, and management, among other factors. The IPCC defines a factor for biomass loss as a consequence of forest fires, expressed as a fraction of total biomass. This methodology implies using aggregated data and the default emission factor, which are only recommended for countries where wildfires are not a key category. In Chile, over the last decade, there have been between 5000 and 8000 wildfires annually (an average of 6398 for the period 2011–2020), burning an average of 122,328 hectares each year. Countries may progress in the refinement of such factors depending on the availability and reliability of local values. This paper aims at estimating

C_{f}

values for the main forest plantation species in Chile, Pinus radiata, Eucalyptus nitens, and Eucalyptus globulus, across different age-classes and forest fire severity. To achieve this aim, we assessed the biomass loss after forest fires for a stratified sample of forest plots for the season 2018–2019. We fitted a model to predict the amount of biomass loss during fires, and in this way, predict the emissions associated with wildfires. The model employs very simple predictive variables, age and species, because statistics for burnt areas in plantations are only provided by age-classes and species, without details about productivity or management. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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14 pages, 3193 KiB

Open AccessArticle

The Characteristics of Gas and Particulate Emissions from Smouldering Combustion in the Pinus pumila Forest of Huzhong National Nature Reserve of the Daxing’an Mountains

by Shuyuan Tang, Sainan Yin, Yanlong Shan, Bo Yu, Chenxi Cui and Lili Cao

Forests 2023, 14(2), 364; https://doi.org/10.3390/f14020364 - 11 Feb 2023

Cited by 1 | Viewed by 1449

Abstract

Smouldering combustion can emit a large amount of CO₂, CO and particulate matter (PM). Moisture content is an important factor of the emission characteristics. As the hot spot of forest smouldering combustion, the gas and particulate emissions of the Huzhong National [...] Read more.

Smouldering combustion can emit a large amount of CO₂, CO and particulate matter (PM). Moisture content is an important factor of the emission characteristics. As the hot spot of forest smouldering combustion, the gas and particulate emissions of the Huzhong National Nature Reserve with different moisture contents are discussed herein. The emission factors (EF) of CO₂ and CO were 100.71 ± 39.14 g/kg and 11.76 ± 3.89 g/kg, respectively. The EF of PM_2.5, PM₄ and PM₁₀ were 87.11 ± 19.47 g/kg, 353.37 ±159.25 g/kg and 602.59 ± 276.80 g/kg, respectively. PM_2.5 accounted for 16.59 ± 5.25% of the PM, and PM₄ and PM₁₀ were 54.03 ± 13.46% and 91.00 ± 10.81%, respectively. There was no significant difference in the EF of CO₂ and CO with different moisture contents, nor in the EF of PM_2.5, but there was a significant difference in the EF of PM₄ and PM₁₀ with different moisture contents. In addition, the peak of CO₂ and CO appeared at 2~3 h; the peak of PM_2.5 lagged behind that of PM₄ and PM₁₀. According to the regression analysis, experimental expressions were obtained for the modified combustion efficiency (MCE) and the EF of PM. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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17 pages, 3130 KiB

Open AccessArticle

Evaluations on the Consequences of Fire Suppression and the Ecological Effects of Fuel Treatment Scenarios in a Boreal Forest of the Great Xing’an Mountains, China

by Han He, Yu Chang, Zhihua Liu, Zaiping Xiong and Lujia Zhao

Forests 2023, 14(1), 85; https://doi.org/10.3390/f14010085 - 02 Jan 2023

Cited by 2 | Viewed by 1489

Abstract

With global warming, catastrophic forest fires have frequently occurred in recent years, posing a major threat to forest resources and people. How to reduce forest fire risk is a hot topic in forest management. Concerns regarding fire suppression and forest fuel treatments are [...] Read more.

With global warming, catastrophic forest fires have frequently occurred in recent years, posing a major threat to forest resources and people. How to reduce forest fire risk is a hot topic in forest management. Concerns regarding fire suppression and forest fuel treatments are rising. Few studies have evaluated the ecological effects of fuel treatments. In this study, we used the LANDIS PRO model to simulate the consequences of fire suppression and the ecological effects of fuel treatments in a boreal forest of the Great Xing’an Mountains, China. Four simulation scenarios were designed, focusing on whether to conduct fuel treatments or not under two fire-control policies (current fire suppression policy and no fire suppression policy). Each scenario contains nine fuel treatment plans based on the combinations of different treatment methods (coarse woody debris reduction, prescribed burning, coarse woody debris reduction plus prescribed burning), treatment frequency (low, medium, and high), and treatment area (large, medium, and small). The ecological effects of the fuel treatments were evaluated according to the changes in fire regimes, species succession, and forest landscape patterns to find a forest fuel management plan that is suitable for the Great Xing’an Mountains. The results showed that long-term fire suppression increases fuel loads and the probability of high-intensity forest fires. The nine fuel management plans did not show significant differences in terms of species succession and forest landscape patterns while lowering forest fire intensity, and none of them were able to restore historical vegetation structure and composition. Our results consolidate the foundation for the practical performance of forest fuel treatments in fire-prone forest landscapes. We suggest a suitable fuel treatment plan for the Great Xing’an Mountains, with a low treatment frequency (20 years), large treatment area (10%), and coarse woody debris reduction, plus the prescribed burning measure. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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20 pages, 4114 KiB

Open AccessArticle

Forest Burned Area Detection Using a Novel Spectral Index Based on Multi-Objective Optimization

by Bo Wu, He Zheng, Zelong Xu, Zhiwei Wu and Yindi Zhao

Forests 2022, 13(11), 1787; https://doi.org/10.3390/f13111787 - 28 Oct 2022

Cited by 5 | Viewed by 1713

Abstract

Forest fires cause environmental and economic damage, destroy large areas of land and displace entire communities. Accurate extraction of fire-affected areas is of vital importance to support post-fire management strategies and account for the environmental impact of fires. In this paper, an analytical [...] Read more.

Forest fires cause environmental and economic damage, destroy large areas of land and displace entire communities. Accurate extraction of fire-affected areas is of vital importance to support post-fire management strategies and account for the environmental impact of fires. In this paper, an analytical burned area index, called ABAI, was proposed to map burned areas from the newly launched Sentinel-2 images. The innovation of this method is to separate the fire scars from other typical land covers by formulating different objective functions, which involved three main components: First, spectral differences between the burned land and other land covers were characterized by analyzing the spectral features of the existing burned area indices. Then, for each type of land cover, we formed an objective function by linear combination of bands with the values of band ratios. Second, all the objective functions and possible constraints were formulated as a multi-objective optimization problem, and then it was solved using a linear programming approach. Finally, the ABAI spectral index was achieved with the optimizing coefficients derived from the multi-objective problem. To validate the effectiveness of the proposed spectral index, three experimental datasets, clipped from Sentinel-2 images at different places, were tested and compared with baseline indices, such as normalized burned area (NBR) and burned area index (BAI) methods. Experimental results demonstrated that the injection of a green band to the spectral index has led to good applicability in burned area detection, where the ABAI can avoid most of the confusion presented by shadows or shallow water. Compared to other burned area indices, the proposed ABAI achieved the best classification accuracy, with the overall accuracy being over 90%. Visually, our approach significantly outperforms other spectral indexed methods, especially in confused areas covered by water bodies and shadows. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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17 pages, 7689 KiB

Open AccessArticle

How Environmental Factors Affect Forest Fire Occurrence in Yunnan Forest Region

by Zheng Zhu, Xiaofan Deng, Fan Zhao, Shiyou Li and Leiguang Wang

Forests 2022, 13(9), 1392; https://doi.org/10.3390/f13091392 - 31 Aug 2022

Cited by 7 | Viewed by 1773

Abstract

Forest fire is an ecosystem regulating factor and affects the stability, renewal, and succession of forest ecosystems. However, uncontrolled forest fires can be harmful to the forest ecosystem and to the public at large. Although Yunnan, China is regarded as a global hotspot [...] Read more.

Forest fire is an ecosystem regulating factor and affects the stability, renewal, and succession of forest ecosystems. However, uncontrolled forest fires can be harmful to the forest ecosystem and to the public at large. Although Yunnan, China is regarded as a global hotspot for forest fires, a general lack of understanding prevails there regarding the mechanisms and interactions that cause forest fires. A logistic regression model based on fire points in Yunnan detected by satellite in 2005–2019 was used to estimate how environmental factors in local areas affect forest fire events. The results show that meteorology is the dominant cause of the frequent forest fires in the area. Other factors of secondary importance are the daily minimum relative humidity and the daily maximum temperature. When using the logistic regression model based on the data of fire points in Yunnan over the period 2005–2019, the key threshold for the daily minimum relative humidity is 28.07% ± 11.85% and the daily maximum temperature is 21.23 ± 11.15 °C for a forest fire probability of 50%. In annual and monthly dynamic trends, the daily minimum relative humidity also plays a dominant role in which combustible substance load remains relatively stable from January to March, and the impact on forest fire becomes greater in April, May, and June, which plays a secondary role compared with the interannual climate. The maximum daily temperature ranks third in importance for forest fires. At the county level, minimum relative humidity and maximum temperature are the top two factors influencing forest fires, respectively. Meanwhile, the differences in forest fire points between counties correspond to the pathways of the two monsoons. This study applies quantitative expressions to reveal the important environmental factors and mechanisms that cause forest fires. The results provide a reference for monitoring and predicting forest fires. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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14 pages, 2020 KiB

Open AccessArticle

Emissions Released by Forest Fuel in the Daxing’an Mountains, China

by Heng Zhang, Hui Li, Xinyuan Liu, Yunjia Ma, Qing Zhou, Rula Sa and Qiuliang Zhang

Forests 2022, 13(8), 1220; https://doi.org/10.3390/f13081220 - 02 Aug 2022

Cited by 1 | Viewed by 1497

Abstract

The large amounts of emissions released by forest fires have a significant impact on the atmospheric environment, ecosystems, and human health. Revealing the main components of emissions released by forest fuel under different combustion states is of great importance to evaluate the impact [...] Read more.

The large amounts of emissions released by forest fires have a significant impact on the atmospheric environment, ecosystems, and human health. Revealing the main components of emissions released by forest fuel under different combustion states is of great importance to evaluate the impact of forest fires on the ecological environment. Here, a self-designed biomass combustion system was used to simulate the combustion of different parts (i.e., branch, trunk, and bark) of five tree species and branches, and three layers of surface dead fuel (i.e., litter layer, semi-humus layer, and humus layer) of three shrub species, in the Daxing’an Mountains, Inner Mongolia. The emission characteristics of the main gas pollutants (i.e., CO, CO₂, HC, and NO_x) and PM₂.₅ released under the two combustion states of smoldering and flaming, along with the correlation ratio among emission factors, were measured. The results show that the average amounts of emissions released by different trees and the three layers of surface dead fuel from a smoldering state are higher than those from the flaming state, while shrub combustion shows the opposite. The emissions released by trees, shrubs, and surface dead fuel from the flaming state are ordered from high to low as follows: CO₂ > CO > HC > NO_x > PM_2.5; and from the smoldering state as CO₂ > CO > HC > PM_2.5 > NO_x, indicating that the primary emissions under both conditions are mainly due to CO₂, CO, and HC, while the emissions of NO_x and PM_2.5 are dependent on the combustion state—flaming promotes the emission of NO_x, while smoldering promotes the emission of PM_2.5. The average emissions of PM_2.5 from the branches, bark, and trunks of Quercus mongolica are significantly higher than those of the other four tree species in the smoldering state, and the emissions of PM_2.5 from the five tree species are ordered as follows: bark > branch > trunk. This study will help to further understand the impact of forest fires on the atmospheric environment and ecosystems in Northern China. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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16 pages, 2376 KiB

Open AccessArticle

The Effects of Fire Disturbance on Litter Decomposition and C:N:P Stoichiometry in a Larix gmelinii Forest Ecosystem of Boreal China

by Fei Li, Zhe Shi, Bingqing Zhao, Gong Jinhua Bono, Long Sun and Tongxin Hu

Forests 2022, 13(7), 1029; https://doi.org/10.3390/f13071029 - 30 Jun 2022

Viewed by 2216

Abstract

Fire disturbance can affect the function of the boreal forest ecosystem through litter decomposition and nutrient element return. In this study, we selected the Larix gmelinii forest, a typical forest ecosystem in boreal China, to explore the effect of different years (3 years, [...] Read more.

Fire disturbance can affect the function of the boreal forest ecosystem through litter decomposition and nutrient element return. In this study, we selected the Larix gmelinii forest, a typical forest ecosystem in boreal China, to explore the effect of different years (3 years, 9 years, 28 years) after high burn severity fire disturbance on the decomposition rate (k) of leaf litter and the Carbon:Nitrogen:Phosphorus (C:N:P) stoichiometry characteristics. Our results indicated that compared with the unburned control stands, the k increased by 91–109% within 9 years after fire disturbance, but 28 years after fire disturbance the decomposition rate of the upper litter decreased by 45% compared with the unburned control stands. After fire disturbance, litter decomposition in boreal forests can be promoted in the short term (e.g., 9 years after a fire) and inhibited in the long term (e.g., 28 years after a fire). Changes in litter nutrient elements caused by the effect of fire disturbance on litter decomposition and on the C, N, and C:N of litter were the main litter stoichiometry factors for litter decomposition 28 years after fire disturbance. The findings of this research characterize the long-term dynamic change of litter decomposition in the boreal forest ecosystem, providing data and theoretical support for further exploring the relationship between fire and litter decomposition. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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23 pages, 5775 KiB

Open AccessArticle

Analysis of Factors Related to Forest Fires in Different Forest Ecosystems in China

by Zechuan Wu, Mingze Li, Bin Wang, Yuping Tian, Ying Quan and Jianyang Liu

Forests 2022, 13(7), 1021; https://doi.org/10.3390/f13071021 - 29 Jun 2022

Cited by 12 | Viewed by 2077

Abstract

Forests are the largest terrestrial ecosystem with major benefits in three areas: economy, ecology, and society. However, the frequent occurrence of forest fires has seriously affected the structure and function of forests. To provide a strong scientific basis for forest fire prevention and [...] Read more.

Forests are the largest terrestrial ecosystem with major benefits in three areas: economy, ecology, and society. However, the frequent occurrence of forest fires has seriously affected the structure and function of forests. To provide a strong scientific basis for forest fire prevention and control, Ripley’s K(d) function and the LightGBM algorithm were used to determine the spatial pattern of forest fires in four different provinces (Heilongjiang, Jilin, Liaoning, Hebei) in China from 2019 to 2021 and the impact of driving factors on different ecosystems. In addition, this study also identified fire hotspots in the four provinces based on kernel density estimation (KDE). An artificial neural network model (ANN) was created to predict the probability of occurrence of forest fires in the study area. The results showed that the forest fires were spatially clustered, but the variable importance of different factors varied widely among the different forest ecosystems. Forest fires in Heilongjiang and Liaoning Provinces were mainly caused by human-driven factors. For Jilin, meteorological factors were important in the occurrence of fires. Topographic and vegetation factors exhibited the greatest importance in Hebei Province. The selected driving factors were input to the ANN model to predict the probability of fire occurrence in the four provinces. The ANN model accurately captured 93.17%, 90.28%, 83.16%, and 89.18% of the historical forest fires in Heilongjiang, Jilin, Liaoning, and Hebei Provinces; Precision, Recall, and F-measure based on the full dataset are 0.87, 0.88, and 0.87, respectively. The results of this study indicated that there were differences in the driving factors of fire in different forest ecosystems. Different fire management policies must be formulated in response to this spatial heterogeneity. Full article

(This article belongs to the Special Issue Fire Ecology and Management in Forest)

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