How Prescribed Burning Affects Surface Fine Fuel and Potential Fire Behavior in Pinus yunnanensis in China

Abstract

Forest fine fuels are a crucial component of surface fuels and play a key role in igniting forest fires. However, despite nearly 20 years of long-term prescribed burning management on Zhaobi Mountain in Xinping County, Yunnan Province, China, there remains a lack of specific quantification regarding the effectiveness of fine fuel management in Pinus yunnanensis forests. In this study, 10 m × 10 m sample plots were established on Zhaobi Mountain following one year of growth after prescribed burning. The plots were placed in a prescribed burning (PB) area and an unburned control (UB) area. We utilized indicators such as forest stand characteristics, fine fuel physicochemical properties, and potential fire behavior parameters for evaluation. The results indicate that prescribed burning at one-year intervals significantly affects stand characteristics, particularly in metrics such as crown base height, diameter breast height, and fuel load (p < 0.05). However, the physical and chemical properties of fine fuels did not show significant differences. Notably, the mean range of spread (RS) of PB fuels downhill was 43.3% lower than that of UB fuels, and the mean flaming height (FH) was 35.2% lower. The fire line intensity was <750 kW/m, categorizing it as a low-intensity fire. These findings provide data on the composition of fine fuels and the variables of fire behavior affected by prescribed burning, demonstrating that low-intensity prescribed burns can regulate fine fuels in the understory and maintain a stable regional fire risk level.

1. Introduction

Wildfires constitute a considerable disturbance element in forest ecosystems, causing a substantial amount of destruction and severely impacting forest structure and function. In recent years, large-scale wildfires have been witnessed globally, highlighting them as a key disaster and environmental issue for many countries [1]. The occurrence of forest fires is not a singular process; rather, it consists of several interrelated components influenced by various factors, including fuel types, meteorological conditions, and topographical features [2]. Forest fuels serve as a fundamental prerequisite for forest fires, with fine fuels comprising an essential part of surface fuels and acting as a critical factor in initiating forest fires [3]. The classification of surface fuels is primarily based on the three-level fuel classification method proposed by Burrows [4]. According to the Department for Environment and Water of South Australia [5], fine fuels include twigs, leaves, and weeds with a diameter of less than 0.64 cm and are commonly referred to as 1 h time-lag fuels. Statistics indicate that more than 59% of wildfires are initially spread by the burning of surface fine fuels.

The burning characteristics of forest fuels significantly influence the behavior of forest fires, impacting their occurrence, development, and spread. These characteristics are crucial for assessing fire risks [6]. Forest fuels can be categorized by their hazard level, including hazardous fuels, slow-burning fuels, and hard-to-ignite fuels. Surface fine fuels in forests, such as dry twigs and leaves, are classified as hazardous due to their low moisture content, low ignition point, and high burning rate, thus serving as ignition sources in forests [7]. From the physical and chemical properties of fuel, the flammability of fuel is positively correlated with crude fat content and a higher heating value (HHV) and negatively correlated with fuel moisture content (FMC) and ash content. Surface fires typically consume fine fuels, including loose needles, mosses, and herbaceous vegetation located at or close to the surface, primarily through flaming combustion. The spread of surface fires is often facilitated by the layer of grass or deadfall [8]. Therefore, studying the combustion characteristics of forest fine fuels can help regulate these fuels effectively and enhance forest fire prevention efforts.

Globally, prescribed burning has emerged as a vital management tool to reduce the likelihood of fires occurring, particularly in the context of increasing fire hazards due to climate change [9]. Prescribed burning involves the controlled, human-induced ignition of understory fuels in a planned and systematic manner [10] with specific fire management objectives. This practice reduces the likelihood of large wildfires and minimizes ecological damage [11]. Prescribed burning helps regulate fuel loads in forests [12] and effectively reduces the intensity of wildfires [13]. Additionally, it serves multiple purposes, including controlling pests [14], improving wildlife habitats [15,16], and acting as a crucial silvicultural method to promote forest growth [17]. Prescribed burning enhances the habitat environment of wild animals and the woodland landscape, fostering the growth of forest trees and altering the diversity of herbs and saplings beneath the forest canopy. Consequently, it improves the quality and quantity of food for certain animals. Additionally, this practice modifies the habitat conditions for wildlife, impacting the species composition and range of wild herbivores. When conducted under appropriate conditions, prescribed burning is a significant tool for managing forest ecosystems [18]. However, the impacts of prescribed burning on ecosystems and the climate could be intricate and involve potential hazards [19]. Researchers have focused on its ecological consequences, including the production of and temporal and spatial changes in airborne particulate pollutants [20], impacts on rainfall and water quality [21], effects on soil organic carbon and nutrients [22], and influences on the wider ecological environment and biodiversity [23,24].

In Yunnan Province, China, prescribed burning exhibits distinctive regional characteristics. Unlike the prescribed burning management practices in Europe or the United States, which often have intervals of several years [25], such as the “10-year Wildfire Crisis Strategy” implemented in the Payette National Forest [26,27], some studies indicate a shorter burning cycle of approximately two years [28,29]. China places great emphasis on fire prevention in P. yunnanensis forests. In Xinping County, prescribed burning has been conducted almost annually for nearly 20 years as a policy measure to reduce fire risks in P. yunnanensis forests [30].

Pinus yunnanensis is a coniferous species unique to southwestern China and widely distributed in the region. This species demonstrates a significant degree of adaptability to fire, featuring highly flammable needles and typical serotiny traits. P. yunnanensis relies heavily on fire for seedling regeneration, with its thick bark providing protection from flames and, thus, allowing it to survive [31]. The abundance of cones remaining in the canopy, combined with the high flammability of its needles and low branch-to-ground height, renders these forests particularly vulnerable to fire; consequently, fires in these areas often escalate to high-intensity crown fires. This competitive advantage allows P. yunnanensis to thrive over other plant species in post-fire environments [32]. Seeds that survive in the canopy exhibit significant thermal shock responses; high temperatures and smoke effectively break seed dormancy, facilitating rapid regeneration after a fire and enabling P. yunnanensis to occupy advantageous ecological niches [33]. Thus, continuous fire disturbances may enhance the ecological dominance of P. yunnanensis, potentially increasing the frequency and severity of forest fires within its range [34]. The extensive distribution of P. yunnanensis across southwestern China indicates a high likelihood of potential forest fires in this region, emphasizing the species’ unique regional characteristics.

Currently, there is limited research on the effects of a long-term continuous forest fire disturbance. This study focuses on the fine fuels in P. yunnanensis forests one year after prescribed burning. Indicators such as forest stand characteristics, physicochemical properties of fine fuels, and parameters that indicate potential fire behavior were used for assessment. The objective was to investigate the effects of long-term continuous prescribed burning management on fine fuels in P. yunnanensis forests, serving as a foundational theory for subsequent research endeavors on the sustainable management of high-altitude forests and the development of effective prescribed burning policies.

2. Methods and Materials

2.1. Study Site and Experimental Design

The study area is situated in Xinping County, located in the southwestern region of central Yunnan Province (23°38′15″~24°26′05″ N, 101°16′30″~102°16′50″ E). The terrain is characterized by high elevation in the northwest and a gradual decline toward the southeast, predominantly comprising mountainous regions. This area spans approximately 4139.6 km², with mountainous terrain accounting for 98.03% of the total area. The landscape also features deep valleys, with elevations ranging from a maximum of 3165.9 m to a minimum of 422.0 m. The climate in Xinping County belongs to the temperate zone and is heavily influenced by altitude, which gives rise to three distinct climatic types: a high-temperature area in the river valley, a moderate-temperature area in the middle mountains, and a low-temperature area in the high mountains. The annual maximum temperature reaches 32.8 °C, while the minimum temperature can drop to 1.3 °C, resulting in an average annual temperature of 18.0 °C. The annual precipitation is approximately 869.0 mm, with an annual sunshine duration of 2838 h. The frost-free period lasts around 316 days [35]. Fires in Xinping County exhibit high seasonality, primarily occurring in winter and spring when conditions are drier and more conducive to fire. The fire prevention period in Xinping County runs from December to June of the following year, and the annual prescribed burning on Zhaobi Mountain basically starts in February [36].

Xinping County features a forest area of approximately 320,000 ha, resulting in a forest cover of 60.96%. The natural forest area comprises about 220,000 ha, while the artificial forest area, including aerially seeded forest, covers approximately 96,000 ha. P. yunnanensis is the primary coniferous species in this region, often forming pure forests that are predominantly single layered and established largely through aerial seeding. The undergrowth is composed primarily of shrubs, with notable species including Myrica nana A.Chev., Vaccinium duclouxii (H.Lév.) Hand.-Mazz., and Camellia reticulata Lindl. Herbaceous plants are relatively well developed, covering 30% to 50% of the ground, with an average height of around 40 cm. Grasses of the Poaceae family dominate the herbaceous layer, featuring species such as Rubia edgeworthii Hook.f., Eulalia brevifolia P.C.Keng, and Inula cappa (Buch.-Ham.) DC.

The primary objective of prescribed burning in this region is to mitigate the risk of high-intensity fires caused by the accumulation of ground fuels. As a policy initiative, Xinping County has implemented prescribed burning in P. yunnanensis forests for nearly 20 years. Notably, prescribed burning was halted in 2020 and 2021 due to concerns regarding air pollution. This study’s field survey was carried out in January 2024, before the scheduled prescribed burning for that year.

A contiguous area of pure P. yunnanensis forest was chosen as the location for conducting this study. Sample plots were divided into two groups: the prescribed burning (PB) area and the unburned (UB) area. Due to the presence of TV towers, prescribed burning is prohibited in the upper slope region. Similarly, the lower slope region, which borders villages and farmlands, is also restricted from burning. Consequently, prescribed burning is primarily conducted in the mid-slope region. To mitigate the impact of varying elevations on sampling locations, the sample plots we selected in the UB area exhibit an elevation difference within the range of 2040~2080 m and the sample plots we selected in the PB area exhibit an elevation variation ranging between 2030 m and 2100 m. Based on this arrangement, we conducted a study on the impact of prescribed burning on fine fuels. Thirty plots were randomly selected in the PB area for data collection, while ten control plots were chosen from the UB area that had not undergone any burning treatment (Figure 1). Each survey plot measured 10 m × 10 m. Detailed records of each plot’s geographical location, altitude, slope, aspect, and position were kept. The tally for all P. yunnanensis trees within the plot included height, crown base height, and diameter breast height (DBH), from which stand closure was estimated in order to calculate stand density (Figure 2a). Trees measuring ≥1 m in height and <10 cm in DBH were categorized as shrubs during sampling [37]. Additionally, five 1 m × 1 m quadrats were established diagonally within each sample plot (Figure 2b). Fuel was collected using the harvest method, weighed, and placed in plastic bags, and all fine fuels in the quadrats were transported to the laboratory for further analysis.

2.2. Description of the Surface Fine Fuel Structure in a Sample Plot

Figure 3 represents the vertical structure of the forest stand, which consists of three distinct layers: the fine fuel layer, the shrub layer, and the arboreal layer. In the pure P. yunnanensis forest of the study area, surface fuel types primarily include fallen leaves, herbs, ferns, and a limited number of shrubs. In the prescribed burning sample plots, the surface fuels consist mainly of P. yunnanensis litter, herbaceous litter, and dead ferns. These fuels are characterized by being discontinuous and unevenly distributed, resulting in a relatively low fuel load.

In contrast, the control plot exhibits a wider diversity of fuels, including significant quantities of P. yunnanensis litter (comprising dead branches and leaves) along with ferns, herbs, and shrubs. P. yunnanensis thrives in sparse conditions, allowing some light to penetrate the understory and promoting the growth of heliophilous plants. Ferns are frequently found in clumps and typically exhibit low moisture content and considerable height, especially after the fire prevention period.

Due to the periodic nature of prescribed burning, the importance and abundance of Quercus species in the burned areas are considerably lower compared with unburned areas. The undergrowth is sparse, with shrubs exhibiting reduced fire resistance; thus, prescribed burning at certain intensities suppresses shrub growth and deters their proliferation.

2.3. Sample Analysis

The experiments were performed in a laboratory under standard temperature and pressure conditions, yielding the subsequent results.

2.3.1. Determination of FMC

The moisture content of combustible materials indicates the amount of water present per unit mass of the material and is a critical factor in fire behavior. Moisture content influences the rate at which combustible materials reach their ignition point and the amount of heat released during combustion. It plays a significant role in the initiation and development of fire, including the range of spread and fire intensity, making it a key indicator of ease of ignition [38]. To achieve complete drying, the collected samples were placed in an electric thermostatic drying oven and dried at 105 °C until a constant weight was attained. The fine fuel moisture content (FFMC) of each fuel type was determined by measuring the change in mass using an electronic balance. The formula for calculating FFMC is as follows:

$$\mathrm{F}\mathrm{M}\mathrm{C}={\displaystyle \frac{m_1-m_2}{m_2}}\times 100\%$$

(1)

where m₁ is the fresh weight (g) and m₂ is the weight after drying (g).

2.3.2. Determination of Ash Content

Ash content refers to the amount of mineral remnant remaining after the complete combustion of fuel, primarily comprising silica, non-oxidized silica, and other minerals. Ash acts as a barrier to flaming combustion; thus, a higher ash content correlates with lower combustibility. The high-temperature dry ash method was employed for analyzing the samples. A 2 g dry sample was weighed and the crucible holding the sample was subsequently heated in a muffle furnace at 800 °C for 12 h [39]. After cooling, the weight was re-measured and recorded, with two replicate tests conducted for each sample.

$$\mathrm{A}\mathrm{s}\mathrm{h}={\displaystyle \frac{m_4-m_3}{m_5-m_3}}\times 100\%$$

(2)

where m₃ is the weight of the crucible (g); m₄ is the mass of the sample and crucible after ashing (g); and m₅ is the total mass of the sample and crucible before ashing (g).

2.3.3. Determination of Crude Fat Content

Crude fat content is an important indicator of fuel flammability, with higher crude fat content in different fine fuels corresponding to increased flammability. Soxhlet extraction is a continuous solvent extraction method that utilizes solvents at ambient pressure and boiling temperature for the selective extraction of target compounds from solid compounds. The filter paper and sample were dried for 12 h in an electric thermostatic drying oven at 105 °C. The sample was then ground in a mill and sieved. The dried filter paper was packaged and sealed, and its weight was recorded along with that of the sample. Petroleum ether was added to the extraction flask of the Soxhlet extractor to immerse the sample fully. The condensate flow was activated, and the sample was placed in a water bath at a constant temperature of 80 °C for 8 h. After removal, the sample was allowed to evaporate in a ventilated area, followed by drying in an electric thermostatic drying oven at 105 °C, after which the weight was recorded [40]. The formula for calculating crude fat content is as follows:

$$\mathrm{C}\mathrm{r}\mathrm{u}\mathrm{d}\mathrm{e} \mathrm{F}\mathrm{a}\mathrm{t}={\displaystyle \frac{m_8-m_7}{m_8-m_6}}\times 100\%$$

(3)

where m₆ is the weight of the filter paper (g), m₇ is the weight of the filter paper and sample after Soxhlet extraction (g), and m₈ is the weight of the filter paper and sample after drying (g).

2.3.4. Determination of HHV

HHV is defined as the heat energy totally emitted during the full combustion of a unit mass of fuel at 25 °C and 101 kPa. This value is typically measured using an oxygen bomb calorimeter. To prepare the sample, it is dried for 12 h in an electric thermostatic drying oven at 105 °C, then crushed in a mill and sieved. The HHV of the sample is subsequently measured using an XRY-1C microcomputer oxygen bomb calorimeter (Changji Instruments, Shanghai, China). Each sample is tested in duplicate to ensure accuracy.

$$\mathrm{H}\mathrm{H}\mathrm{V}=\mathrm{K}{\displaystyle \frac{\left[\left({\mathrm{T}}_1-{\mathrm{T}}_2\right)+∆\mathrm{T}\right]}{\mathrm{M}}}$$

(4)

where HHV is the higher heating value (kJ/kg); K denotes the water equivalent (kJ/°C); T₁ denotes the temperature of the sample before ignition (°C); T₂ denotes the temperature of the sample after ignition (°C); ∆T denotes the temperature correction value (°C); and M denotes the sample mass (g).

2.4. Potential Fire Behavior Testing

To simulate the fire behavior of surface fine fuels in a pure forest of P. yunnanensis, we conducted experiments on the fire spread of fine fuels in a windless indoor environment. The experiment was divided into an uphill fire spread simulation and a downhill fire spread simulation. Figure 4 illustrates the slope-changed fuel bed (2 m × 1.3 m × 0.3 m) utilized for indoor simulations of real forest burning conditions. To replicate field conditions, a 2 cm layer of plasterboard was placed at the bottom of the fuel bed to minimize heat loss. The weight of the fine fuels was measured before each combustion trial. After adjusting the slope of the fuel bed, we spread the fuel evenly on the plasterboard and ignited the fuel with flame-spraying guns. During the burning process, several parameters were recorded:

Combustion time (CT), ranging from the ignition of the fuel to the extinction of the flame, was monitored using a stopwatch;

Heat radiation (HR) was measured with a radiation calorimeter;

Land surface temperature (LST) was recorded using a non-contact infrared thermometer (DTM-T1, DELIXI ELECTRIC, China);

Flaming height (FH) was assessed with a steel tape measure, observing the reading at the point where the flame reached the highest as it passed over the area where the steel tape had been erected;

Various temperature data were collected using a Type K thermocouple (16-channel, wire diameter 80 μm), which was installed above the flame and collected data every 0.6 s.

At the conclusion of the combustion trial, the Consumption Rate (CR) was calculated by weighing all the remaining burnt material in the fuel bed.

The fireline intensity (FI) is equal to the product of the fuel’s lowest heat of combustion (kJ/kg), the quantity of fuel consumed in the flaming front (kg/m²), and the linear rate of fire spread (m/s) [41].

The Consumption Rate (CR) is defined as:

$$\mathrm{C}\mathrm{R}={\displaystyle \frac{\mathrm{A}-\mathrm{B}}{\mathrm{A}}}\times 100\%$$

(5)

where A represents the weight of fine fuel prior to burning (kg) and B denotes the weight of fine fuel following burning (kg).

2.5. Redundancy Analysis

Redundancy analysis is a method that combines regression analysis with principal component subsystem ranking. It visually represents the relationship between prescribed burning and potential fire behavior characteristics on different slopes. This study utilized Canoco 5.0 software (Microcomputer Power, Ithaca, NY, USA) for the redundancy analysis [42].

2.6. Statistical Analysis

The data were analyzed and processed using SPSS 26 statistical software. To compare the significance of differences in the combustibility of fine fuels, one-way ANOVA and the least-significant difference (LSD) test were employed. Pearson’s correlation coefficient was utilized to assess the linear correlation between combustibility measurements. Additionally, paired-sample t-tests were conducted to compare the correlation between changes in fine fuel combustibility and trends in dead fuel combustibility following prescribed burning. All statistical analyses and graphical representations were executed in Origin 2021 (OriginLab Corporation, Northampton, MA, USA).

3. Results

3.1. Forest Stand Characteristics of P. yunnanensis Forest

The semi-natural forest of P. yunnanensis on Zhaobi Mountain developed naturally following afforestation efforts initiated in the 1980s. After more than 30 years of artificial cultivation and natural thinning, the structural characteristics of the P. yunnanensis forest in this study area have stabilized (

Table 1. The stand conditions and growth patterns of P. yunnanensis in the PB and UB areas. Data are presented as means ± standard deviations; trees ≥ 1 m tall and <10 cm in DBH were classified as shrubs during sampling.

Treatments	Altitude (m)	Slope (°)	Overstory Cover	Tree Density (No./ha)	Tree Height (m)	Crown Base Height (m)	DBH (cm)	Fuel Load (kg/m2)
UB	2059.28 ± 12.43	22.93 ± 5.72	0.69 ± 0.14	1350 ± 499	10.41 ± 1.52	5.94 ± 1.89	14.89 ± 1.79	0.62 ± 0.13
PB	2060.23 ± 22.01	15.91 ± 4.87	0.4 ± 0.14	1231 ± 413	10.26 ± 1.25	7.22 ± 1.52	16.82 ± 2.55	0.46 ± 0.09

). Prescribed burning, implemented at one-year intervals, significantly influences tree density, tree characteristics, and stand structural characteristics [43]. In the UB sample plot, tree density was recorded at 1350 ± 499 No./ha and it was recorded at 1231 ± 413 No./ha in the PB plot. The statistical difference is insignificant (F = 0.709, p = 0.404).

Tree height was recorded at 10.41 ± 1.52 m in the UB plot and 10.26 ± 1.25 m in the PB plot, demonstrating an insignificant difference (F = 0.130, p = 0.720). Crown base height was notably affected by prescribed burning. Crown base height increased from 5.94 ± 1.52 m in the UB plot to 7.22 ± 1.52 m in the PB plot, also showing a significant difference (F = 5.99, p = 0.018). The DBH of P. yunnanensis increased as a result of fire exposure, rising from 14.89 ± 1.79 cm in the UB plot to 16.82 ± 2.55 cm in the PB plot, with a significant difference observed (F = 10.035, p = 0.003). The amount of fuel in the sample plot was most directly influenced by prescribed burning. The average amount of fuel load decreased from 0.62 ± 0.13 kg/m² in the UB plot to 0.46 ± 0.09 kg/m² in the PB plot, which is a significant difference (F = 33.595, p < 0.001).

3.2. Physicochemical Characteristics of Fine Fuel

The physicochemical characteristics of the fuel are critical indicators explaining its combustion capacity. The physicochemical characteristics of the surface fine fuel in the prescribed burning area and the unburned area are illustrated in Figure 5. In the unburned plot, the average HHV of the fine fuel was 19,811.59 kJ/kg, while in the prescribed burning plot it was slightly higher (20,681.79 kJ/kg). The observed difference between these values was significant (F = 11.459, p = 0.002).

The ash content of fine fuels in the PB plot was 3.27%, marginally falling behind the 3.37% observed in the UB area, but this difference was also not statistically significant (F = 0.074, p = 0.786).

The average crude fat content in the understory fine fuels of the P. yunnanensis forest was 7.65%. In comparison, the crude fat content in the UB area was 6.90%, while in the PB plot it was higher (8.39%), indicating a significant difference (F = 9.454, p = 0.005).

3.3. Potential Fire Behavior of Fine Fuel

Due to the varying slopes in the sampling plots, two burning slopes of 15° and 20° were selected for the indoor test simulations of the prescribed burning samples. For the 15° slope, the variations in fire behavior observed during the burning experiment were recorded. The average uphill flame rate of spread (RS) in the prescribed burning plot was 0.398 m/min, compared with 0.695 m/min in the unburned plot, with a significant difference detected (F = 157.326, p < 0.001). This difference is attributed to the variability in the fuel load between the sample plots. The downhill flame RS was 0.191 m/min in the PB area and 0.337 m/min in the UB area, with a significant difference observed (F = 34.673, p < 0.001).

Flame height is a key observable parameter in forest fire behavior studies, commonly represented by the maximum flame height [44]. The mean FH of uphill flames in the PB plot was 0.8 m, which was significantly lower than that of uphill flames in the UB plot (1.1 m) (F = 14.892, p < 0.001). Similarly, the mean FH of downhill flames in the PB plot was 0.375 m, markedly lower than the mean FH of downhill flames in the UB plot (0.579 m), with this difference being highly significant (F = 17.556, p < 0.001).

Fireline intensity is another critical factor influencing the potential behavior of fires [45]. Simulation results indicate that, when employing the downhill fire ignition method, the average fireline intensity was 29.128 kW/m for the PB plot and 59.985 kW/m for the UB plot according to the Byram fireline intensity algorithm [46], exhibiting a significant difference (F = 21.397, p < 0.001). Importantly, the measured fireline intensity was below 750 kW/m, suggesting a low-intensity fire.

The rate of fuel consumption, assessed through Consumption Rate (CR), plays a vital role in evaluating the effectiveness of prescribed burning. A downward-spreading flame, which burns opposite to the fire front, proves to be particularly effective for fuel consumption (Figure 6).

The temperature data collected during the fire spread experiment were measured using a thermocouple. It is important to note that the temperatures reported by the thermocouple represent the gas temperature above the fuel. Figure 7a,c display data collected after the sample had been burning for 70 s. Figure 7b illustrates the temperature recorded by the thermocouple from ignition to 150 s, when the measured temperature began to flatten out. During the uphill fire, ignition occurred, and it spread rapidly with the flame tilting markedly forward toward the unburned fuel, thereby enhancing the heat transfer efficiency through flame radiation. The highest temperature recorded during this phase was 693.9 °C. In contrast, Figure 7d shows the temperature data recorded from ignition until the complete extinction of the flame at 300 s. The downhill fire exhibited a gentler spread; after ignition, it formed a uniform line of fire that spread horizontally downwards. The maximum temperature recorded in this phase was 504.5 °C, lower than the temperature observed during the uphill fire. The temperature of the flame is directly related to the strength of the fireline intensity [47]. However, the downhill flame was characterized by a prolonged residence time, ensuring thorough combustion.

For the simulation experiments with a slope of 20°, Figure 8a,b show the temperature data recorded by the thermocouple as it stabilized from ignition to the complete extinction of the fire at 150 s. The maximum temperature for the fire burning on the 15° slope was 690.6 °C, while for the 20° slope it reached 741.3 °C. The 20° incline facilitated a faster and more intense burn, resulting in higher temperatures measured by the thermocouple, albeit for a shorter duration. Figure 8c,d present the temperature data recorded during the downhill fire from ignition to complete flame extinction at 300 s. The maximum temperature recorded for the downhill fire on the 15° slope was 455.6 °C, whereas the fire on the 20° slope measured a maximum temperature of 367.9 °C. For the 20° slope, the variations in fire behavior observed during the burning experiment were recorded. The average uphill FH with a slope of 20° was 0.846 m, compared with the downhill flame FH of 0.431 m, slightly higher than the FH on the 15° slope (F = 0.23364, p > 0.05). The mean LST of the uphill fire on the 20° slope was 531.538 °C, higher than the LST on the slope of 15° (522.308 °C), the statistical difference being insignificant (F = 0.490, p = 0.491). Similarly, the mean LST of the downhill fire with a slope of 20° was 622.977 °C, markedly higher than the mean LST with a slope of 15° (573.4 °C), with this difference being significant (F = 7.612, p = 0.011). The flame RS is a factor that is greatly affected by the change in slope. When employing the uphill fire ignition method, the average RS on the 20° slope was 0.705 m/min, with a significant difference detected (F = 102.168, p < 0.001).

3.4. Association Between the Potential Fire Behavior of Fine Fuel and Effects of Prescribed Burning

We investigated the performance of various potential fire behaviors under different upslope and downslope ignition scenarios influenced by prescribed burning (Figure 9). The results indicate that FH, RS, and FI exhibited positive correlations with uphill ignition. Conversely, HR, LST, CT, and CR were positively correlated with downhill ignition.

3.5. Association Between the Potential Fire Behavior of Fine Fuel and Effects of Slope

Additionally, we assessed the effect of the slope on the performance of different potential fire behaviors under both uphill and downhill ignition conditions (Figure 10). The findings reveal that the combustion slope increased the RS, HR, LST, and CR. In contrast, FH and CT were positively correlated with a decreasing slope of combustion.

4. Discussion

4.1. Characteristics of the P. yunnanensis Forest Stand

Prescribed burning at one-year intervals has a significant influence on forest stand characteristics. P. yunnanensis is a highly fire-adapted species that naturally forms a dominant community maintained by fire disturbances. Under typical fire-free conditions, P. yunnanensis displays a very weak regeneration capacity and relies heavily on fire disturbances to promote regeneration [48]. While prescribed burning can facilitate the regeneration of P. yunnanensis, an excessively high burning frequency can be detrimental. All regenerating seedlings may be killed before they develop the necessary fire tolerance. Notably, we observed no P. yunnanensis seedlings taller than 30 cm in the burned area [49].

The effects of prescribed burning on tree growth are influenced by several factors, including the fire tolerance of different plant species, the severity of the fire, the characteristics of the trees, and their condition prior to the fire [50]. P. yunnanensis has the ability to self-prune, and lower dead branches will fall by themselves [51]. In the prescribed burning area, the crown base height was significantly greater than in the unburned area. This increase in crown base height represents an adaptive response of P. yunnanensis to years of prescribed burning [52]. Such growth effectively reduces the impact of fire on the trees during prescribed burning and decreases the likelihood of surface fires spreading to crown fires through the ‘fuel ladder’.

The bark of P. yunnanensis has a unique structure; it is generally brittle and expands slightly when exposed to fire, thereby providing a fire-retardant effect. Some of the fine fuels are fragments of P. yunnanensis bark that have been shed after being burned. The bark serves as a crucial protective tissue during fire disturbances [53]. Additionally, an increase in relative bark thickness offers self-protection for P. yunnanensis against low-intensity fires during prescribed burning [54]. It can also be illustrated by the increase in the DBH of P. yunnanensis after prescribed burning.

4.2. Effect of Prescribed Burning on the Structure of Surface Fine Fuel

Prescribed burning significantly redistributes the structure of the fuel bed and alters the fuel’s flammability. The understory vegetation exhibits varied responses to burning. Specifically, the shrub cover declined significantly after burning and remained consistently lower than the unburned levels throughout the study period. The long-term application of continuous prescribed burning in the forest on Zhaobi Mountain has notably suppressed the growth of understory vegetation. In the prescribed burning area, the average height and cover of understory plants were significantly lower than in the unburned area. The average fuel load on the ground decreased from 0.62 kg/m² (UB) to 0.46 kg/m² (PB), representing a reduction of 25.81%. As a fire-adapted species with high fire resilience, this reduction in fuel load alleviates the competitive pressure between P. yunnanensis and the understory vegetation. Moreover, the fine fuel residues remaining after prescribed burning, primarily plant ash, create a more favorable environment for P. yunnanensis to absorb nutrients, promoting its growth. These findings illustrate the role of prescribed burning in reducing the fuel load in the forest and diminishing the vertical continuity of forest fuels.

4.3. Differences in Physicochemical Characteristics of Fine Fuels

The physicochemical properties of fine fuels are critical indicators for understanding their combustibility and warrant thorough investigation. In our study, the average HHV across different sample plots showed significant differences (F = 11.459, p = 0.002); however, the ash and crude fat contents exhibited slight differences. These discrepancies can be attributed to the different types of surface fuels present. Fuels with a crude fat content greater than 6% are classified as high-fat fuels. The average ash content was approximately 3.32%, indicating relatively low levels and suggesting that the fine fuels in the P. yunnanensis forest exhibit good combustibility. P. yunnanensis possesses low ash content and a high HHV value, rendering it a highly combustible material. This observation aligns with the findings of Su [31], which suggest that the fire-adapted syndrome of P. yunnanensis is an intermediate type between fire-tolerant and fire-embracing types, making it well adapted to the environment where crown fires occurred.

4.4. Differences in Potential Fire Behavior of Fine Fuel Under Effects of Prescribed Burning

In the unburned areas, the ground fuel thickness was greater than that observed in the prescribed burning sample plots, resulting in lower combustion temperatures during the PB area’s fine fuel behavior experiments. Compared with the UB sample plots, the average RS for the PB samples in uphill and downhill plots decreased by 42.7% and 43.3%, respectively. Additionally, the average FH was reduced by 27.9% for uphill burns and 35.2% for downhill burns. The FI remained low in the downhill ignition plots, suggesting that regular prescribed burning effectively reduces the accumulation of fuel, lowers the forest’s flammability, and helps prevent the occurrence of large, high-intensity fires caused by human activity. Furthermore, the downhill ignition method employed in prescribed burning significantly slows the rate at which flames spread. During the uphill fire, ignition occurred, and it spread rapidly with the flame tilting markedly forward toward the unburned fuel, thereby enhancing the heat transfer efficiency through flame radiation. The average RS for uphill flames in PB plots was recorded at 0.398 m/min, while downhill flames spread at only 0.191 m/min (less than 4 km/h, which is considered the safe speed limit for prescribed burning). Although this experiment was conducted in a controlled, windless indoor environment, real-world prescribed burning scenarios will naturally be influenced by various environmental conditions. Nevertheless, these findings suggest that firefighter safety can be enhanced under actual field conditions during prescribed burns. While our study has investigated the impact of prescribed burning on fine fuel, there are certain limitations we must acknowledge. Specifically, the samples we have been able to compare in this paper are limited to prescribed burning areas with only a one-year interval and unburned areas. In our future research, we aim to expand our investigation by obtaining samples from PB areas with three-year intervals and five-year intervals in hopes of gaining a deeper understanding of the prescribed burning cycle that is most suitable for the southwestern forest region.

4.5. Differences in the Potential Fire Behavior of Fine Fuel Under Effects of Slope Degrees

In our research, we focused on the effects of slope on the potential fire behavior of fine fuels within P. yunnanensis forests, where the slope range generally falls between 15° and 20°. A slope of 15° is considered gentle, while a slope of 20° is relatively steep. We wanted to explore the effect of slope on the potential fire behavior of fine fuel under P. yunnanensis [55]. Our findings indicate that an increase in slope positively influences RS, HR, LST, and CR. In laboratory fire behavior spread experiments, thermocouple measurements revealed that fire spreads uphill more quickly, reaches higher temperatures, and exhibits more intense burning on a 20° slope than on a 15° slope. Conversely, the effect of slope on fire spreading downhill is noteworthy; fires on a 20° slope propagate more slowly than those on a 15° slope, with lower temperatures and flame radiation primarily directed forward, making them less effective at igniting unburned fuel. Future research endeavors will incorporate slope factors and undertake more comprehensive and thorough investigations.

5. Conclusions

The evaluation of the flammability of fine fuels in P. yunnanensis forests was conducted using three key indicators: forest stand characteristics of P. yunnanensis forest, the physicochemical properties of fine fuels, and potential fire behavior parameters. The main conclusions from this research are as follows. First, prescribed burning is an efficacious approach to limiting the expansion of shrubs and herbs beneath P. yunnanensis forests while also minimizing the chance of surface fires escalating into crown fires. Second, prescribed burning can effectively control surface fine fuels, especially in terms of fuel load. The average fuel load in the prescribed burning area is less than half that in the unburned area. Third, combining the fire-tolerator and fire-embracer characteristics of P. yunnanensis, the fine fuels in P. yunnanensis forests are combustible and flammable and, if left unmanaged, are likely to cause high-intensity fires. In summary, implementing low-intensity prescribed burning in P. yunnanensis forests within the Southwest China Forest Region is essential for regulating the fine fuels on the forest floor and maintaining an acceptable fire risk level in the area. Given the potential for long-term fire disturbances, regular prescribed burning in fire-prone environments and fire-adapted stands is both necessary and viable.