Wildfire is a primary source of natural disturbance in forest ecosystems, and it plays an important role in determining the landscape structure and plant community composition. Wildfires are classified into ground, surface, and crown fires, based on the strata where the burning occurs [1
]. For example, the shrub and small trees stratum act as a “ladder fuel” that forms a continuous ladder fuel from the surface fuel up to the canopy fuel, which can turn low-intensity surface fires into severe canopy fires, potentially resulting in active crown fires [2
]. Crown fires include active crown fires when a solid flame develops in the crown of trees where the surface and crown phases advances as a linked unit dependent on each other. Passive crown fire is where a fire in the crown of the trees in which a tree or group of trees torch, ignited by the passing front of the fire [1
]. Fire susceptibility is determined by the distribution, type and continuity of fuel [6
]. Assessing the potential of wildfires is an important factor for fire prevention and suppression planning. Forest managers are expressing a growing interest in proactively reducing an area’s susceptibility to fires, yet fires remain responsible for a large proportion of the annual area burned in fire-prone ecosystems. Our knowledge of wildfire prevention and its relationship with forest type is lacking [7
Fuels, weather, and terrain are key factors influencing the initiation and spread of wildfires [10
], and of these three factors, only fuels can be actively managed [11
]. The term “fuel” does not stand for a single object but is a complex multi-layered system, which includes the following layers from surface to canopy: a semi-decomposed layer, an active/fine fuel layer, a large fuel layer, a herb layer, a shrub layer and a tree layer [12
]. The spatial characteristics of fuel include the quantity, size, and continuity, which mainly affect behavior of the fire, such as the rate of spread and fire intensity [13
]. It would be prohibitively difficult to maintain an inventory of all fuel characteristics because fuel is structurally complex and varies widely in its physical attributes. Thus, an orderly method of classifying fuels and inferring fuel properties from limited observations is needed.
A classification and characterization method simplifies the complexity to a reasonable degree and does not oversimplify the description of forest fuel [15
]. Since the 1930s, Hornby [17
] classified fuels based on their potential rate of spread in the United States. Rothermel [10
] developed a mathematical model that allowed consideration of the intensity and rate of spread of fires among reasonably homogenous fuels types, including fire behavior prediction systems. Increasing characterization of different forest types has allowed for the establishment of 13 fuel models to simulate fire intensity and the spread of surface fires through grass, shrub, timber, and logging slash forest types [18
]. The BEHAVE model [19
] was developed to provide standardized numerical fuelbed descriptions in order to generate reasonable and accurate fire behavior predictions using Rothermel’s spread model. This model is the most widely used to predict fire behavior, today, and it greatly increased the demand for quantitative data of different forest types.
Fire spread models were tentatively established by Chinese scholars using the Rothermel model [9
]. These models incorporate an assessment of surface and crown fire potential and enable the user (the forest manager) to create and catalogue fuel classes. However, the limitations of these fuel models and the frequent change of forest types make it difficult to apply fuel models that were developed for other regions.
Fires are a natural part of the landscapes of Sichuan Province in southwestern China, so the dynamics of burning are part of their natural ecosystems [22
]. In Sichuan province, the forested area until the Fifth Forest Resources Inventory was 13,301,500 ha, and was 11.6 ha per capita [9
]. During the 29-year period, from 1979 to 2008, there were 4774 wildfires; 90 percent of all wildfires in a given year occur from January to May [9
]. Therefore, wildfires are an integral part of the region’s ecology and botanical diversity, which makes understanding their dynamics essential for forest management in Sichuan. When a fire occurs, it poses a serious threat to property and safety in regions where natural areas are adjacent to urban areas. Thus, the importance of predicting wildfire behavior in assessing fire potential is a prerequisite for evaluating the effectiveness of fuel management during fire prevention planning [24
Since the 1980s, studies on forest fuel in southwestern Sichuan have assessed the main vegetation types according to fire danger classes [26
], the influence of extreme climate on fuel distribution [23
], the combustion characteristics of Pinus yunnanensis
], and control measures for wildfires [27
]. However, previous studies did not take into consideration the different forest types that are found in the region, mainly due to the difficulty of determining the potential fire behaviour by forest managers during daily observations. To improve fuel management and fire suppression planning, there is a clear need for additional information on the spatial distribution and classification of fuel types in Sichuan Province.
In this study, we conducted field measurements of forests to classify coniferous forests into forest types as a function of their fire potential. Our study includes detailed field classifications in every layer where different diameters of fuel were found, and their implications for the potential of fire spread at the stand scale. The study objectives were to: (1) compare the spatial distribution of fuel loadings in different coniferous forest types, (2) analyze the fire potential of different conifer forests, and (3) classify the different forest types into different fuel types depending on the pattern of fire types that burned them.
Our results indicated that the distribution and structure of four fuel classes, the total loading and fire potential differed among the six forest types. Using CCA analysis, four groups of FT were differentiated (FT1), (FT2), (FT4 and FT3), and (FT5 and FT6), had characteristics in common that determined the type of fires that burned them under the extreme burning condition. The results of the predicted fire potential indicated that the presence of a particular forest type could increase the susceptibility of active crown fires. Thus, less understory loading at the plot level but continuous distribution and lower fuel moisture could have the same effect in initiating crown fires as a higher amount of understory. It is possible that wind speed and continuity are the key elements for the transition from a surface fire to a passive crown fire and, later, to an active crown fire. Niu [14
] suggested that the highest increase in size and severity of fires occur with higher vertical and horizontal fuel continuity. Larger crown width, higher canopy fuel loading, and higher density of trees increase the horizontal continuity and created favorable opportunities for the spread of crown fire. Vertical continuity increased with the presence of three tree layers and the “ladder fuel’’ that provides continuity from the surface fuel to canopy fuel. The FT1 has an increased susceptibility of having active crown fires due to a high tree density and canopy fuel loading, which result in high horizontal continuity and high density as well as a lower live crown with vertical continuity of branches that result in a high vertical continuity. However, FT1 did not generate the highest percentage of active crown fires (Table 3
). This may be due to unsuitable conditions to initiate crown fires, such as the proportion of medium fuel and thick fuel being higher than 68%, which can raise the ignition point [14
], or due to a lower wind speed as a consequence of it being a dense forest [42
]. Thus, FT1 had a high minefield of potential susceptibility for generating active crown fires, but the conditions for crown fire initiation were lower.
Compared to FT1, the susceptibility of having active crown fires in FT5 can increase by the increment of ladder fuels (represented by medium trees, or small trees, especially with epiphytic moss) (Table 1
and Table 3
). Thus, irregular understory density and lower fuel moisture can lead to the highest susceptibility of surface fires transiting to active crown fires. According to the historical fire record, surface, ground and crown fires occurred simultaneously, which caused irreversible damage. Only two fires (with burn areas of 948 and 666 ha, both in March 1999) occurred in FT5 in March 1999 when there was little rainfall. In meteorological records, there were 74 consecutive days without rain fall in our study area. Therefore, the identification of FT5 is important for suppression planning, because it generate fires with behavior exceeding the extinction capacity. It would be best to reduce the amount of ladder fuels by thinning from below, as well as small diameter trees, cutting shrubs and herbs [43
]. Additionally, pruning the crown to a half or third of the height of the tree could help to reduce ladder fuels. It is possible to also immediately fell a few trees to reduce the canopy density and break the horizontal continuity.
FT2 had a single layer with large trees, low surface fuel loading, and a high canopy base height that originated the most surface fires without any active crown fire initiation (Table 2
and Table 3
, Figure 3
). The fuel quantity, structure and continuity of four fuel classes in FT2 makes the transition to crown fire more difficult (Table 3
, Figure 3
). However, combined with the higher horizontal continuity of the surface in this type, contributes to greater spreading for surface fires (Figure 2
). Therefore, cleaning the surface fuel could help suppress the initiation of surface fire.
The type that resulted in the highest instances of passive and active crown fires was FT6 (Table 3
), which had a structure with three layers of small trees, medium trees and large trees (Table 1
), and higher vertical continuity (Figure 3
). In addition, FT6 only included three fuel classes in the crown: active fuel, fine fuel and medium fuel (active fuel + fine fuel > 60%). As a consequence, crown fires can consume more biomass due to the presence of active fuel and fine fuel above a critical rate. This critical spread sustains passive crown fires, which increases the spread, and causes a larger consumption of trees, including active fuel and fine fuel [45
]. FT6 would benefit from the removal of some “ladder fuels” to reduce the canopy density. This could be effective in stopping passive crown fires and preventing the start of new fires, especially if it was combined with patchy canopy and vertical layer management [13
The increment of fuels confirms that types similar to FT6, but with higher vertical continuity (e.g., FT3 and FT4) caused by ladder fuels and higher canopy loading, can increase the susceptibility of having active crown fires (Figure 3
). The two types that caused moderate passive crown fires and active crown fires were FT4 and FT3, which had middle-range canopy fuel loading (Figure 3
) and tree density (Table 1
). FT3 and FT4 had higher spreading for surface fires compared to FT6, which could be caused by higher continuity (Figure 2
) and the large quantity of active fuel and fine fuel, which can cause easy spreading [22
]. It had a high spread of surface fire that climbed up to the canopy because of the distribution of active fuel and fine fuel between 0 m and 1 m. FT3 and FT4 are effective in stopping active crown fires and preventing the start of new active crown fires if the canopy continuity is lessened by the removal of small trees.
Loading and continuity of surface fuels are an important element in determining the spread of surface fire and the transition. The higher continuity of certain forest types results in higher spreading susceptibility of crown fire spread. Ladder fuels result in vertical continuity, which can increase the susceptibility of having active crown fires; large crown width, high canopy fuel loading and tree density increase horizontal continuity and create favorable conditions for burning.
As a consequence, the six forest types have two effects on fire behavior: on one hand they favor the ignition of an active crown with vertical continuity of fuels classes, which determines crown fire initiation; on the other hand, there could be a point of a new crown fire run because of horizontal continuity through the canopy layer, which determines crown fire spread. Forestry managers should take into consideration fuel management and preventive silviculture to estimate the susceptibility of wildfire for the following two reasons. Firstly, this strategy can be effective to stop passive crown fires and also prevent new fires when combined with surface/crown patchiness, understory management and “ladder fuel” management. Several measures can be taken to achieve this goal, such as reducing surface fuel (needles, leaves, grass, dead and down branch wood) [46
], and reducing the amount of ladder fuels (small trees and shrubs) [14
]. The pruned plant material can be masticated or chipped and left on site, which is an option an increasing number of forest managers are using [24
]. The pruning can increase the gap between the surface fuel and the crown base height up to 3 m, effectively breaking the continuity of the distribution of the surface fuel [14
]. Secondly, this strategy could be effective in stopping active crown fire if combined with canopy patchiness of low density and canopy fuel loading management. According to Hall and Burke [47
], crown fuel structure is a critical factor determining whether crown fires occur. Treatments to reduce crown fire susceptibility often focus on reducing canopy fuels and interrupting the surface-canopy fuel continuum. Combining this with a lower vertical and horizontal continuity makes the transition to crown fire more difficult [29
]. Horizontal patchiness of the canopy will reduce the spread of fire within the canopy layer [29
], using measures such as cleaning up litter (active fuel and fine fuel) [24
], increasing canopy gaps [48
], and decreasing tree density [28