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Article

Assessment of Biological and Environmental Factors Influence on Fire Hazard in Pine Forests: A Case Study in Central Forest-Steppe of the East European Plain

by
Vasiliy Slavskiy
1,*,
Daria Litovchenko
1,
Sergey Matveev
1,
Sergey Sheshnitsan
1 and
Maxim V. Larionov
2,3,4,5
1
Faculty of Forestry, Voronezh State University of Forestry and Technologies Named after G.F. Morozov, 8 Timiryazev Street, 394087 Voronezh, Russia
2
Faculty of Ecology and Environmental Protection, Russian State Social University (RSSU), 4 Wilhelm Peak Street, Building 1, 129226 Moscow, Russia
3
Institute of Industry Management, State University of Management (SUM), 99 Ryazanskij Prospect Street, 109542 Moscow, Russia
4
Federal State Budgetary Educational Institution of Higher Education “State University of Land Use Planning” (SULUP), 15 Kazakov Street, 105064 Moscow, Russia
5
World-Class Scientific Center “Agrotechnologies for the Future” (CAAT), Russian State Agrarian University—Moscow Timiryazev Agricultural Academy, 49 Timiryazevskaya Street, 127550 Moscow, Russia
*
Author to whom correspondence should be addressed.
Land 2023, 12(1), 103; https://doi.org/10.3390/land12010103
Submission received: 24 November 2022 / Revised: 17 December 2022 / Accepted: 24 December 2022 / Published: 28 December 2022
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Abstract

:
Vast forest areas are spreaded in Russia and perform environment-forming, nature-protective and climate-regulating functions, including carbon sequestration. At the same time, increasing of destructive forest fires scale in recent decades has led to depletion of forest resources. To combat forest fires, it is necessary to develop preventive measures to reduce the number and severity of forest fires and establish reliable evaluation criteria for fire hazard assessment in forestry. However, indices of fire hazard assessment that exist in Russia are not always allowed to determine the degree of fire hazard reliably. The studies were performed in pine forests on the territory of the Central Forest-Steppe. The key forestry factors influencing the fire hazard situation in pine stands are identified: the presence and amount of combustible materials, the state of the stand, as well as the age structure of tree stand. According to burning indices, the highest fire hazard was common for young and middle-aged pine stands, while for ripening, mature and old-growth forests, fire hazard increasing was not observed. A set of parameters that characterize soil moisture and ground cover peculiarities have also a significant impact. Forest growth conditions were shown to be an important indicator for assessment of fire hazard class. Identified factors that have a key impact on the fire hazard in forests will make it possible to improve methodological approach for monitoring and preservation of forests.

1. Introduction

Fire is a dominant disturbance in temperate and boreal biomes, and increasing burnt areas may substantially alter forests [1,2]. According to the estimates of the Federal Agency for Forestry [3], total annual damage from forest fires is about 20 billion rubles, while from 3 to 7 billion is a direct economic damage to Russian forestry due to wood loss. Another loss are the costs of firefighting and subsequent clearing of burnt areas, animal deaths, atmosphere pollution by combustion products, greenhouse gases emissions, and costs of reforestation.
Hence, among the many important issues of forest protection and reproduction one of the most urgent is the fight against forest fires. Therefore, development of a system for comprehensive assessment of forest fire hazards taking into account factors of forest typology and forest structure that determine flammability is of particular relevance. Obviously, an operational system for assessing and forecasting fire danger should consider wide range of forest characteristics, vegetation state and reflect the significance of the main taxation characteristics.
These problems were studied by many researchers [4,5,6]. M.A. Sofronov and A.V. Volokitina [7] developed a method for assessing the distribution of real fire hazard over the territory based on the medium-scale maps of forest combustible materials. N.P. Kurbatsky, G.A. Dorrera, B.I. Dorogova [8], M.Z. Musina [9], E.N. Valendik [10], M. Fosberg and M. Schroeder [11], P. Labenski [12] used wide spectrum of possible fire sources in their forest fire forecasting systems.
E.N. Valendik and G.A. Ivanova [13] established that various types of forests have its own “fire regime” characterized by a certain type and intensity of fire, recurrence intervals, and degree of damage to plant resources. N.S. Ivanova suggested biogeocenotic and genetic approaches in forest typology [14].
Some researchers found that degree of stability of plantings depends on taxation indicators [15,16,17]. The dependence of the stability of pine plantations against fire was established experimentally, depending on forest site [18], stand age [19,20], average stand height.
Chumachenko [21] investigated natural fire hazard in mixed forest stands [22] and found the admixture of hardwoods in all age classes and in all tiers of coniferous forests reduce fire hazards. Increased flammability of pine plantations is determined by a number of biological features of Scots pine. First of all, high transparency of the tree canopy ofmature pine forests accelerates drying of living ground cover and litter. Also, pine deadwood contains high amount of resinous substances, which inhibit its decomposition rate. Particularly it is inherent to dry group of forest types, where deadwood decomposition is delayed for many years.
To reduce the risk of forest fires systems for regular assessment of forest combustible material stock as well as systems for assessing the fire development (modeling, ground monitoring, satellite data, airborne infrared detection) were used [22,23].
Notably, there are no low-cost methods for significantly reducing the level of fire hazard in forests now. Developing a preventive system that effectively combines data from different remote sensing methods of fire danger as well as implementation of new technologies providing a prompt assess of fire hazards in forests are essential.
The aim of the study was to determine the key factors influencing the flammability in forests for preventive reducing of fire occurrence.
Our stages of work were divided into: preparatory, field, cameral (final).

2. Materials and Methods

2.1. Study Sites

Study sites are located on the territory of Suburban Forestry in the Central Chernozem Region (the northern part of Voronezh Region, Russia) and represented natural and artificial forest stands of various tree species inherent to Central Forest-Steppe (Figure 1A) Geographical location of study sites in the Suburban Forestry; B, C, D) Placement of trees in the study areas within the polygon.
Forest fire hazard is known to vary greatly depending on tree age, the proportion of conifers in the composition, anthropogenic factors, terrain, forest structure, forestry activities, etc. However, despite the diversity of forest vegetation and its combinations different tree stands can be combined into groups with similar occurrence conditions and peculiarities of development of forest fires there.

2.2. Field Studies

Thirteen sample plots were established in different forest types and types of forest growth conditions and investigated during forest inventory of Suburb Forestry in 2022. Also, forest stands in established sample plots belonged to different fire hazard classes [24], which is reflected in Table 1.
All taxation and deciphering trial plots are laid b in the forest sites with different growth conditions were studed. For determining the forest growth conditions useds to classifications scheme of P.S. Pogrebnyak [25]. This classification is based on the division of forest areas according to moisture and soil fertility. The trophic groups differ from each other in nutrient contents in the soil: A—pine forest (sandy soils), B—pine-oak forest (sandy loam soils), C—composite forest (loamy soils), D—oak grove (clay soils). Each gigrophic groups divided into: xerophilous (very dry)—0; mesoxerophilous (dry)—1; mesophilous (fresh)—2; mesohygrophilous (moisty)—3; hygrophilous (moist)—4; ultrahygrophilous (wet)—5.
V.N. Sukachev gives the following definition of a forest type [26]: a site of forest is an association of forest parcels (i.e., forest ecosystems), homogeneous in composition of tree species, other vegetation levels, fauna, the relationship between plants and the environment, forest reproduction processes, and corresponding stages of succession and therefore requires uniform forest management practices under the same economic conditions. A type of forest under these conditions can therefore be considered as a type of forest biogeocenosis [24,27,28].
Studied plantings of different ages growing in the forest site: pine site of forest with a predominance in the ground cover the following species: grasses (Szl) (Festuca glauca L., Hieracium pilosella L.), lichens (Slh) (Cladonia L.), green mosses (Szm) (Dicranum scoparium Hedw., Pleurozium schreberi Brid.), small grasses (Str) (Bryidae, Veronica officinalis L.), mossy (Smsh) (Polýtrichum commúne L., Lysimachia vulgaris L.), reed grasses (Srzl) (Calamagrostis epigejos L., Dianthus deltoides L.), brooms and grasses (Srtzl) (Phleum phleoides L., Festuca ovina L.), medium grasses (Ssrt) (Convallaria majalis L., Polygonátum odoratum L.), molinium (Smln) (Molinia caerulea L., Maianthemum bifolium L.), mixed herbs (Srt) (Pulmonaria obscura Dum., Origanum vulgáre L.), large herbs (Sdsn) (Pyrola elliptica Nutt., Rubus saxatilis L.) and ferns (Sdkrt) (Pteridium aquilinum L., Athyrium spinulosum L.).
Complete enumeration was carried out at each sample plot with determination of tree species and coordinates of each tree, stem diameter, tree height and beginning height of the living crown part, crown diameter and forest cluttering. The ground cover, undergrowth, understory and the degree of clutter were also investigated. The height of the tree and the beginning height of living crown were measured with an accuracy of 0.5 m using a Vertex Laser Geo altimeter (Haglöf, Sweden). The stem diameter was measured with a DP II Caliper (Haglöf, Sweden) at a height of 1.3 m, with an accuracy of 1 cm. The crown diameter was measured with a laser rangefinder along the crown projection in two opposite directions (NS/WE). Measurement accuracy was not less than 0.5 m.
We used the approved scale according to the classes of natural fire hazard, where class I (natural fire hazard—very high), class II (natural fire hazard—high), class III (natural fire hazard—medium), class IV (natural fire hazard—weak), V class (natural fire hazard—absent) [29].
Tree health category was determined visually according to 5-point scale [30]: 1—without signs of weakening; 2—weakened; 3—strongly weakened; 4—drying out; 5—dead wood.
The methodology for conducting the State Forest Inventory (SFI) was taken as the basis for determining the main forestry indicators [31] which has been upgraded to detail the work. Deadwood counting in the trial plots was performed with reference to trees; if deadwood was in open spaced areas, its location was fixed relative to the nearest tree. Deadwood was considered as dead trees at an angle of less than 45% from the ground level. Moreover, tree species, length and diameter at ½ of the length were determined for each deadwood on the trial plot.
Undergrowth and understory within the crown of measured tree were assessed by their density and size according to 3-point scales (for undergrowth: 1—up to 0.5 m; 2—0.5–2 m; 3—more than 2 m; for understory: 1—up to 1 m; 2—1–2 m; 3—more than 2 m) with indication of species and viability (alive/dead). Also based on the recommendations for conducting a SFI the viability of the undergrowth (live/dead wood) is indicated. The ground cover was determined on a three-point scale: 3—contributing to combustion; 2—supporting combustion; 1—flame retardant.

2.3. Fire Hazard and Statistical Analysis

The analysis of forest burning was carried out on the territory of Suburban Forestry from 2002 to 2022 according to the scale developed by G.A. Mokeeva [32].
Some indicators were used for analysis of forest fires: the number of fires in forestry; forest area covered by fires; average area of one fire; fire frequency; causes of fire occurrence. Evaluation of fire frequency in Suburban Forestry was provided according to the scale developed by Sofronov M.A. [7] Burning index (γ, %) was calculated as follows:
γ = S f S a × 100 %
where Sf—forest area covered by fires, ha; Sa—total forest area in the region, ha.
Statistical analysis was provided with STATISTICA 13 [33] a statistical sequential analysis was carried out based on the recommendations of B.A. Dospekhova [34]. Correlation and regression analysis, which allows to assess the closeness of the relationship between various indicators that affect the process and find the relationship between the studied indicators, as well as analysis of variance, which allows to determine the strength of the influence of the acting factor on the effective feature.

3. Results

3.1. Fire Hazard Analysis

There were 689 forest fires recorded from 2002 to 2022 with total area of 4001 ha in Suburban Forestry (Table 2). The average area of one fire was 5.8 ha. The most fire hazardous years were 2010 and 2021.
The data in Table 2 indicate that the maximum area covered by forest fires was in ripening forests. Over a 20-year period 55.7% of the total area covered by fire was in ripening forest stands, most of them burned down during a severe wildfire in 2010. The fire was largely due to climatic conditions: the air temperature during the fire season was significantly higher than the long-term average for the region and there was too low precipitation.
Accordingly, the highest burning index for the study period was observed in 2010 and amounted to 0.9%. According to Mokeeva’s scale it is evaluated as strong flammability. The highest frequency of fires was noted in 2021 (0.7 fires per 100 000 ha). According to Sofronov’s scale it is characterized as moderate frequency. The lowest burning index was noted in 2022 (0.002%). The lowest frequency of fires was also observed in 2022 and evaluated as low (0.01 fires per 100,000 ha).
Depending on the nature of the fire and forest composition forest fires are divided into ground fires, crown fires and soil fires. Depending on intensity they are divided into weak, medium and severe. The intensity of burning depends on state and quantity of combustible materials, relief and wind strength. The area covered by fires of different intensity in the study area is shown in Table 3.
According to the data in Table 3 ground fire with different intensity was distributed evenly over the study area. The post-fire mortality in forest stands after stable ground fires is significantly greater than under the influence of runaway fires. This is due to runaway ground fires are characterized by fire spreading over the upper layer of ground combustible materials. Areas covered by ground fire vary significantly in intensity depending on age groups: from 14.9 ha to 678.5 ha (weak), from 17.8 ha to 498.5 ha (medium) and from 10.8 ha up to 317.3 ha (severe).
There is no direct relationship between the area of forest fires and their number. Therefore, the burning index can be considered as more informative indicator of fire hazard. Distribution of areas covered by fires in forest stands of different age groups and values of burning indices depending on forest growth conditions are shown in Table 4.
It is obvious that burning index of tree stands increases in dry and fresh forest growth conditions (A1, A2, B1, B2). This pattern is associated not only with the limit of soil moisture, but also with an increase in content combustible materials and, consequently, increasing of combustion intensity. Contrary, flammability index decreases and fires are often isolated in more humid soil conditions of the studied area (A3, B3, C3). It should be noted that the wildfire in 2010 reached catastrophic scale. Ripening forest stands located at the epicenter of fire were the most harmed. Therefore, tree stands of this age group are out of the general pattern.
Distribution by age groups of forest areas covered by fires depending on forest types are shown in Table 5.
Lichen and grass pine forests grow in forest ecotopes on dry sandy soils. These forests are characterized by a high fire hazard and frequent fires recurrence. Mortality after ground fires of weak and medium intensity the in mature stands confined to these conditions is 20% of the stock, and after severe ground fires—up to 50%.
The consequences of fires in green moss and grass forest types are the most diverse due to their wide area. The state of forest stands after the impact of ground fires in the types of forest growth conditions (A2, B2 and C2) depends on the fire strength and its form, which determines the time of fire exposure. However, the consequences of runaway ground fires of weak and medium strength are more negative in comparison with the consequences of fires of the same strength in dry conditions. This pattern is associated with a longer exposure to fire in these forest types.
Regression analysis was performed to establish the relationship between the burning indices and forest growth conditions/forest types. The results of the initial data alignment are shown in Figure 2.

3.2. Influence of Forest Stand Characteristics on Burning Index

Forest stand characteristics (data from sample plots, Table 1) and values of burning indexes (areas covered by forest fires on the territory of Suburban Forestry) were compared for approbation of the obtained results. Sites were selected in similar types of forests, types of forest growth conditions and age groups.
Obviously, burning indices in certain types of forest growth conditions differ significantly from the forest types corresponding to these conditions. Differences are especially significant in forest stands with fire hazard classes 1 and 2. To assess reliability of differences between the average values of burning indices in forest stands growing under different conditions ANOVA was performed. The results of the analysis are summarized in the Table 6.
Significant differences were revealed between individual values of burning indices of tree stands in forest growth conditions B2 and A2 as well as three stands growing in the corresponding primary forest site—Str., Ssrt. Tree stands in these conditions have a high degree of fire danger and require the most accurate assessment of probability of fire. Therefore, it is advisable to use of forest growth conditions as an additional clarifying indicator for the fire hazard class determination.
Variability of burning indexes in pine forests of different ages in diverse forest growth conditions is shown in Figure 3.
Regardless of the type of forest growth conditions young forests have the highest burning index. Mature stands are characterized by the highest resistance to fires in dry and fresh types of forest growth conditions. This pattern was previously noted by many authors [34]. At the same time, pine stands do not reduce their fire resistance up to 200 years of age. According to B.P. Tikhomirov [35], growth is often observed not only in diameter, but also in height of pine trees 300 years old in Central Siberia and Transbaikalia. It was established that burning index is approximately the same in all age groups (except for young tree stands) in moisty forest growth conditions (A3, B3, C3).
Statistical analysis showed close correlation between the burning index and the ground cover as well as the coarse debris content (accumulation of combustible materials) (Table 7). The strength of the influence of the factor is given in Table 8.
One-way ANOVA was used to identify the influence of individual factors. Results of analysis shows studied forest stand characteristics has no any key influence on the fire occurrence (Table 8). Therefore, a set of features should be considered for establishment of significance levels, which were calculated according to the Fisher criterion Figure 4.
The key factors influencing the burning index of pine stands are the following: coarse debris content, tree stand state and age group. Moreover, a set of parameters determined by the of forest growth conditions (primarily soil moisture and ground cover) have a significant influence.
Figure 5 shows burning indices change depending on the age of the stand. Approximation of the data was provided by second-degree polynomial function with a high value of determination coefficient.
According to the Figure 5, decreasing of fire hazards in forest stands with increasing of their age was revealed. Young tree stands have the highest potential fire hazard. Then, there is a “smoothing” of burning indices values starting from the second class of medium-aged pine stands (more than 60 years).

4. Discussion

Fire management programs typically include prevention measures to reduce the number fires that occur, systems to find fires and fire management systems [36,37,38,39,40]. Improved information about how fire-induced changes to forests may feedback to affect subsequent burning at regional scales could inform forest management and climate-mitigation strategies [41,42,43]. Therefore, the development of preventive measures to reduce the number of fires and the establishment of reliable forestry evaluation criteria for the diagnosis of fire danger are extremely urgent tasks. Forest typology is closely connected not only with the geography of the ranges of tree species, but also with soil biochemistry [44,45,46,47], structure and properties of biogeocenoses [48], dynamics of the carbon balance [49], and is also the basis for monitoring forest biodiversity [50]. The formation of the structure and state of ecosystems based on forest-forming tree species largely depends on their bioecological features [50,51,52,53,54,55] at specific age stages of development.
Also, consideration of environmental factors is of great importance in understanding the state, stability, and ecological role of forest stands [56,57,58,59,60,61,62,63]. It is especially important for protection and restoration of forest ecosystems [64,65,66] as well as in their management [67,68,69]. Accounting for the data obtained on the bioecological features of forest stands and environmental conditions are of paramount importance in managing the resource qualities of forest ecosystems, their stability and protection in forest-steppe and other landscapes. This can be implemented in different areas in natural and artificial ecosystems (in parks, squares, recreational and protective forest plantations) based on Pinus sylvestris L.
In the context of abiotic [70,71,72,73,74] and phytocenotic conditions [75,76,77,78], it is just expedient to consider the ecological state, landscape functions of pine forests and the possibility of protecting them from fires. Maksimova, Abakumov [79] found the average fire interval is more than 2 times shorter in lichen and grass pine forests on sandy and sandy loamy soils than in grass and green moss pine forests in the Central Forest-Steppe. The same peculiarities are typical for other forests in dry conditions. In our study this trend was confirmed. Maximum burning index was revealed in dry of forest growth conditions (A1, B1). However, burning index in fresh forest growth conditions (A2, B2) is comparable to the drier ones, and the frequency of fires decreases. There is a clear trend towards decreasing of part of the area covered by fires with an increase in soil moisture. Our studies are in consistence with the M.A. Sofronov’s opinion [7] about the relationship between tree stand resistance to fire impact and forest growth conditions.
D. Moya et al. [79] note that post-fire mortality increases with increasing fire intensity. In our studies the pattern of increasing mortality depending on tree stand age was noticed: post-fire mortality was greater in mature or old-growth forests than in medium-aged tree stands. At the same time, mature forest stands were the most resistant to fires and young tree stands are damaged to a greater extent.
The indices of fire hazard assessment that exist in Russia do not always make it possible to determine the degree of fire hazard reliably. Protecting forests from fires is a global problem. Vast forest areas are concentrated on the territory of Russia, which perform environment-forming, nature-protective and climate-regulating functions, including carbon storage. The identified factors that have a key impact on the fire hazard in forests will make it possible to improve methodological approach for monitoring and preservation of forests.

5. Conclusions

The main conclusions from the results of our study are given below.
  • Tree stand age has a significant factorial influence on burning index in young and middle aged Scots pine stands. At the same time, there is no significant change of burning index in ripening, mature and old-growth pine forests. Additionally, fire hazard decreases with increasing age of middle aged pine tree stands. The tightness of relationship between burning index and tree stand age in young forests is 0.56, and in mature and old-growth is much lower (0.17).
  • The key factors influencing the index of burning of pine stands are the following: the presence and amount of combustible materials, the state of the stand, age groups. In addition, a complex of parameters characterizing soil moisture and the nature of the ground cover have a significant impact.
  • The frequency of fires and the values of the fire index reach high values in dry types growth conditions due to presence of lichens in the ground cover. Under optimal humid conditions the frequency of fires is reduced but the flammability index can remain high in the presence of a significant amount of combustible materials.
  • We have proved (with mathematical confirmation of the reliability of differences) that forest growth conditions are an important indicator that can be used in determining the fire hazard class.

Author Contributions

Conceptualization, V.S.; methodology, V.S. and D.L.; formal analysis, V.S., S.S., S.M. and M.V.L.; investigation, V.S., S.S., S.M. and M.V.L.; writing—original draft preparation, V.S., D.L., S.M. and M.V.L.; writing—review and editing, V.S., D.L., S.S., S.M. and M.V.L.; visualization, V.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded the research was carried out within the state assignment of Ministry of Science and Higher Education of the Russian Federation (theme No. FZUR-2022-0009) “Development of a preventive technology for forest fire hazard control using UAV-based remote sensing”.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy restrictions.

Acknowledgments

The research was carried out within the state assignment of Ministry of Science and Higher Education of the Russian Federation (theme No. FZUR-2022-0009) “Development of a preventive technology for forest fire hazard control using UAV-based remote sensing”. The article was made with support of the Ministry of Science and Higher Education of the Russian Federation in accordance with agreement № 075-15-2020-905 date 16 November 2020, on providing a grant in the form of subsidies from the Federal budget of Russian Federation. The grant was provided for state support for the creation and development of a World-class Scientific Center “Agrotechnologies for the Future”.

Conflicts of Interest

The authors declare no conflict of interest.

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Land 12 00103 g001 550
Figure 1. (A) Geographical location of study sites in the Suburban Forestry; (B–D) Placement of trees in the study areas within the polygon.
Figure 1. (A) Geographical location of study sites in the Suburban Forestry; (B–D) Placement of trees in the study areas within the polygon.
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Land 12 00103 g002 550
Figure 2. Aligned values of burning indices by forest site (blue) and forest growth conditions (red).
Figure 2. Aligned values of burning indices by forest site (blue) and forest growth conditions (red).
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Figure 3. Burning indices of pine forests of different ages in various forest growth conditions.
Figure 3. Burning indices of pine forests of different ages in various forest growth conditions.
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Figure 4. Significance levels of the main taxation characteristics relative to burning index.
Figure 4. Significance levels of the main taxation characteristics relative to burning index.
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Figure 5. The dependence of burning indices on tree stand ages.
Figure 5. The dependence of burning indices on tree stand ages.
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Table
Table 1. Studied forest stand characteristics and their fire hazard classes.
Table 1. Studied forest stand characteristics and their fire hazard classes.
LocationComposition of Tree Species, %Age Groups of Tree StandsAge, Yearsdbh (cm)h (m)fStanding Volume, m3/haDeadwood, m3/haFire Hazard ClassForest SiteFGC
Quarter 108; site 8100% Scots pine + European birchYoung351590.66021SzlA1
Quarter 108; site 10100% Scots pineMiddle aged5524180.6160142SlhA1
Quarter 33; site 12100% Scots pineYoung1253.70.810-1StrA2
Quarter 74; site 9100% Scots pineRipening12030270.7370302SzmA2
Quarter 77; site 1100% Scots pineMiddle aged5019160.4120112StrA2
Quarter 51; site 44100% Scots pineMiddle aged702321.50.9320183SmshA3
Quarter 79; site 1490% Scots pine
10% European birch		Mature and old-growth15048290.7310352SrzlB1
Quarter 33; site 8100% Scots pineUnclosed forest cultures7-2.21.0--1SsrtB2
Quarter 60; site 11100% Scots pineRipening1404427.50.6290322SrtzlB2
Quarter 78; site 1470% Scots pine
30% European birch		Middle aged5524210.9350152SrtB2
Quarter 72; site 1850% Scots pine 50% European birchMiddle aged4516120.7180103SmlnB3
Quarter 44; site 2650% Scots pine 50% English oakRipening903324.50.6260253SdsnC2
Quarter 7; site 3750% Scots pine 40% English oak
10% Linden		Ripening903626.50.7310283SdkrtC3
Note: h—mean height; dbh—mean diameter on breast height; f—density of tree placement (corresponds to the canopy density); FGC—forest growth conditions.
Table
Table 2. Distribution by age groups of forest areas covered by fires.
Table 2. Distribution by age groups of forest areas covered by fires.
Age Groups of Tree StandsPart in Total Number of Fires, %Area Covered by Fires, haTotal Area of Tree Stands, haPart in Total Area, %Area of One Fire, ha
Young15.3615.54054.234.112.5
Middle aged21.9878.41516.412.96.1
Ripening55.72230.42401.920.82.9
Mature and old-growth7.1276.73798.732.21.8
Total100400111,904.91005.8
Table
Table 3. Distribution by age groups of forest areas covered by fires of various intensity.
Table 3. Distribution by age groups of forest areas covered by fires of various intensity.
Age Groups of Tree StandsArea Covered by Ground Fire, haArea Covered by Crown Fire, ha
WeakMediumSevereTotalWeakMediumSevereTotal
ha%ha%
Young21.230.881.8133.8635.691.5254.6481.725
Middle aged41.5158.510.8210.810218324.7124.9667.635
Ripening678.5498.6317.31494.47234.6112.4589.4736.438
Mature and old-growth14.917.8198.5231.2129.122.110.341.52
Total856.1705.7708.42070.2100397.3550.7979.21930.8100
Table
Table 4. Distribution by age groups of forest areas covered by fires depending on forest growth conditions (ha)/burning index (%).
Table 4. Distribution by age groups of forest areas covered by fires depending on forest growth conditions (ha)/burning index (%).
Age Groups of Tree StandsForest Growth ConditionsTotal
A1A2A3B1B2B3C2C3
Young135.5/
0.23		211.9/
0.35		-80.5/
0.14		187.6/
0.28		---615.5
Middle aged97.9/
0.17		132.1/
0.25		-300.4/
0.43		250/
0.5		-79.4/
0.33		20/
0.2		878.4
Ripening1056.4/
0.88		547.8/
0.43		23/
0.74		300.9/
0.44		125.1/
0.25		21.3/
0.74		155.9/
0.64		-2230.4
Mature and old-growth28.9/
0.02		27.8/
0.02		-89.9/
0.13		123.4/
0.25		-6.7/
0.03		-276.7
Total1318.7919.623771.7686.121.3242204001
Table
Table 5. Distribution by age groups of forest areas covered by fires depending on forest types (ha)/burning index (%).
Table 5. Distribution by age groups of forest areas covered by fires depending on forest types (ha)/burning index (%).
Age Groups of Tree StandsForest SiteTotal
SzlSlhSzmStrSmshSrzlSrtzlSsrtSmlnSrtSdsnSdkrt
Young35/
0.16		100.5/
0.36		67/
0.1		144.9/
0.3		-80.5/
0.14		101.2/
0.17		59/
0.1		-27.4/
0.05		--615.5
Middle aged28.9/
0.03		59.8/
0.15		64.7/
0.01		67.4/
0.01		8.2/
0.26		300.4/
0.43		32.5/
0.21		181.7/
0.61		-35.8/
0.72		79.4/
0.33		20/
0.35		878.4
Ripening760.6/
0.9		295.8/
0.8		405.4/
0.6		142.4/
0.2		23/
0.7		300.9/
0.44		100/
0.66		15.8/
0.05		21.3/
0.25		9.3/
0.18		155.9/
0.64		-2230.4
Mature and old-growth18.9/
0.03		10/
0.03		7.7/
0.1		20.1/
0.03		-89.9/
0.13		20/
0.13		98.6/
0.34		-4.8/
0.1		6.7/
0.03		-276.7
Total843.4466.1544.8374.831.2771.7253.7355.121.3161242204001
Table
Table 6. Reliability of differences between the average values of burning indices in different forest site and forest growth conditions. Statistical differences (p < 0.05) are marked by bold font.
Table 6. Reliability of differences between the average values of burning indices in different forest site and forest growth conditions. Statistical differences (p < 0.05) are marked by bold font.
Forest Growth ConditionsForest Site
SzlSlhSzmStrSmshSrzlSrtzlSsrtSmlnSrtSdsnSdkrt
A10.551.480.08---------
A2-2.052.172.22--------
A3--0.421.913.05-------
B12.42--0.38-3.184.52-----
B2--0.153.23--3.173.55-1.87--
B3----2.88---3.58---
C2- -4.05---4.35-3.153.411.91
C3--0.23-2.13---2.97-3.744.24
Table
Table 7. Correlation matrix of forest stand characteristics in different forest growth conditions.
Table 7. Correlation matrix of forest stand characteristics in different forest growth conditions.
Forest stand CharacteristicsBurning IndexAge, YearsHeight, mDbh, cmCrown Diameter, mBeginning Height of Living Crown, mCategories of Sanitary ConditionCoarse Debris ContentGround Cover
Burning index10.550.170.110.090.280.420.590.61
Age, years0.5510.660.650.380.530.330.180.04
Height, m0.170.6610.670.360.520.710.110.02
Dbh, cm0.110.650.6710.620.230.120.090.03
Crown diameter, m0.090.380.360.6210.170.680.120.07
Beginning height of living crown, m0.280.530.520.230.1710.320.110.03
Categories of sanitary condition0.420.330.710.120.680.3210.490.04
Coarse debris content0.590.180.110.090.120.110.4910.09
Ground cover0.610.040.020.030.070.030.040.091
Tree height, diameter of stem, crown diameter and crown length weakly (or very weakly) correlate with the values of burning indexes.
Table
Table 8. Influence of forest stand characteristics on burning index.
Table 8. Influence of forest stand characteristics on burning index.
Forest Stand CharacteristicsPower of Influence
(ɳ2 ± m)		Fisher Criterion Actual (F f)Fisher’s Criterion
Standard (F st)
Age, years0.22 ± 0.01115.93.1
Height, m0.21 ± 0.01116.43.1
Mean diameter on breast height0.14 ± 0.00616.53.1
Crown diameter, m0.09 ± 0.00415.53.1
Crown length, m0.17 ± 0.00715.73.1
Categories of sanitary condition0.25 ± 0.01215.23.1
Coarse debris content0.35 ± 0.02215.93.1
Ground cover0.23 ± 0.01215.43.1
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Slavskiy, V.; Litovchenko, D.; Matveev, S.; Sheshnitsan, S.; Larionov, M.V. Assessment of Biological and Environmental Factors Influence on Fire Hazard in Pine Forests: A Case Study in Central Forest-Steppe of the East European Plain. Land 2023, 12, 103. https://doi.org/10.3390/land12010103

AMA Style

Slavskiy V, Litovchenko D, Matveev S, Sheshnitsan S, Larionov MV. Assessment of Biological and Environmental Factors Influence on Fire Hazard in Pine Forests: A Case Study in Central Forest-Steppe of the East European Plain. Land. 2023; 12(1):103. https://doi.org/10.3390/land12010103

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Slavskiy, Vasiliy, Daria Litovchenko, Sergey Matveev, Sergey Sheshnitsan, and Maxim V. Larionov. 2023. "Assessment of Biological and Environmental Factors Influence on Fire Hazard in Pine Forests: A Case Study in Central Forest-Steppe of the East European Plain" Land 12, no. 1: 103. https://doi.org/10.3390/land12010103

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