Stanislav N.Sannikov·Nelly S.Sannikova·Irina V.Petrova·Olga E.Cherepanova

Abstract Simulation of fire impact on forest floor renewal in pine forests was based on predictions for 2100 by the Canadian Climate Centre for increase in temperatures of by 4.5 °C and total precipitation by 14% in the West Siberian pre-forest-steppes and empirical regression relationships between them and the degree of burnt forest floor,as well as amount of Pinus sylvestris L.regeneration.It was predicted that by 2100,pine regeneration on fire prone sites under the canopy of the dominant forest type will increase by 29—54% compared to the 1980s but on adjacent open sites,regeneration will decrease twice as much.This means that the regeneration potential and pine population stability in pre-forest-steppes will become as poor as it is today.

Keywords Fire·Forecast·Stability·Population ·Mathematical model·Seeds·Imitation model ·Undergrowth

Introduction

One of the key topics of modern forest ecology and biogeography is the study of climate change impacts on the structure,renewal and dynamics of forest-forming species(Gorchakovsky and Shiyatov 1985;Kullman 1988;Vaganov et al.1998;Holtmeier 2003;Kharuk et al.2006;Lawson and Michler 2014;Eaton et al.2017;Prichard et al.2017;Maher et al.2018;Brown et al.2019;Romeo et al.2020;).The evaluation and forecast of more frequent fires and their(Fosberg et al.1993,1996;Tcvetkov 2014;Valendik et al.2014;Addington et al.2018) are of considerable interest due to rapid climate warming.Wildf ires are a main factor in the renewal of forest plant populations and a fundamental ecosystem process determining forest structure,dynamics,stability and regeneration (Sannikov 1992).The most dramatic fire-climate change driven transformations and even community changes may be expected within the transition between forest and non-forest vegetation—forest and steppe or grasslands in the south and forest and tundra in the north of the boreal zone (Wein and de Groot 1996;Koptseva and Egorov 2017).

Previously large climate-driven changes of stand species composition and even entire vegetation types in North America (Emanuel et al.1985;Kauppi and Posch 1988) and in Central Siberia (Tchebakova et al.2003) were predicted based on correlation models between the factorial-ecological requirements (econiche) of woody plants and climate parameters.Considering climate warming within the boreal zone of North Eurasia,a resulting border off set of zonal vegetation types of several hundred kilometers to the north is expected (Ruan et al.2016;Bogdziewicz et al.2020;Qu et al.2020).

In addition to using phytoclimatic methods,problems of interconnected climate—pyrogenic dynamics of vegetation changes may be solved using other approaches,in particular pyroecological methods.However,for reliable forecasting of future climate impacts on vegetation renewal by fire,it is necessary to identify the key relationships between them in stationary studies.

The main environmental factors and patterns of fire impact on the dynamics of natural renewal ofP.sylvestrisL.cenopopulations in the dominant forest types of the Pineta hylocomiosa group were identified in the Pripyshminsky big pine stand in the pre-forest-steppe subzone of Western Siberia (Sannikov and Sannikova 1985;Sannikov 1992;Sannikova 1992).Relationships between the degree of pine regeneration and the parameters of seed production and stand competition,the hydrothermal regime of the ecoclimate and the degree of burn of the forest floor,were identified and mathematically formalized.

These relationships may be used as elementary models for the prediction of regeneration success related to changes in weather factors and to changes in intensity and frequency of wildf ires.Alternatively,long-term climate-driven-pyroecological forecasting becomes possible,based on verif ied chronological and geographical forecasts of the hydrothermal regime of the vegetative season based on atmospheric circulation models (IPCC 1990;McFarlane et al.1992;Maher et al.2019;Tozer et al.2020).

This study uses simulation modeling to project population levels ofPinus sylvestrisregeneration after fire under the stand canopies and on open sites of the pre-forest-steppe subzone of Western Siberia,considering predicted climate warming to 2100.

Materials and methods

Objectives

The pyroecological and microclimatic studies were carried out on fire sites with a fire prescription of 4—12 years in a closed,mature 160—170 year-old pine forest where the dominant forest type was "cowberry-blueberry-moss pine forest" of the Pripyshminsky stand pine in the pre-foreststeppe subzone of Western Siberia.

Reference empirical relations (submodels)

The following regression relationships established as a result of stationary experiments and observations were used as an empirical basis for predictive modeling of the population level of pine regeneration on the fire sites under the forest canopy,depending on the changes of climate parameters during their appearance and survival (Sannikov and Sannikova 1985;Sannikov 1992):

(1) Dependence of the thickness of burnt-out upper layer of the moss cover (with the dominance ofPleurozium schreberiBrid.) and forest floor on the Nesterov (1949)drought index (Fig.1).In later works,it is usual to note the cumulative stress caused by drought,leading to crop and [the loss of resistance to growth in regenerated pine stands] (Navarro-Cerrillo et al.2018).

Fig.1 The ratio of the thickness of the burnt layers of moss cover and forest litter (Tvp,cm) and the drought rate (∑td) accumulated after rain,Tvp=1.861 Ln (∑t·d)—9.68:R2 =0.87.p ≥ 0.95;t—air temperature at 13 pm.(°C),d—relative humidity def icit at 1.0 pm(hPa)

(2) The relation between the thickness of the unburnt(residual) forest floor layer and the number of pine undergrowth (Fig.2).

Fig.2 The ratio of the thickness of the unburnt layer of the forest litter (Tnp,cm) and the amount of undergrowth of pine sixty years ago(Np,thousand of specimens/ha,with average seed production of 450 thousand of seeds/ha/year).Np=12.23 Tnp-0.65;R2 =0.72,p ≥ 0.95

(3) The linear dependence between pine seedling density and the atmospheric moisture index (Ivanov 1948;Giuggiola et al.2018) (Fig.3).

Fig.3 Dependence of the number of pine seedlings (Nv,thousand Ex./Ha) and the atmospheric humidity index.Nv =154.1 К av—1.74;R2 =0.85,p ≥ 0.99.К av=0.0018·(T+25)·(100 − a).T—Mean monthly daily air temperature,a— mean monthly daily relative air humidity

(4) The dependence between the hydrothermal coefficient of the atmosphereT/∑Pand relative air humidity at 1.0 pm (Fig.4).

Prediction of the level of seed production as a result of an increase in the sum of effective temperatures above 10 °C during the growing season (May—September) was based on the previously established relationship (Sannikov et al.2004,2018):Nc=4.38e0.003∑T,where e is the Napierian base,∑Tthe sum of effective air temperatures above 10 °C.In addition,we included an assumption of an increase in temperatures May—September by an average of 5 °C per month.The theoretical sum of effective temperatures above 10 °C during this period will be 750 °C.Average annual yields of pine seeds in the Pripysh forests are likely to grow by 25%compared with our data in the 1980s when seed production was also calculated (Sannikov and Sannikova 1985).

A simulation of pine regeneration that would survive to the phase of "stable self-seeding older than 6 years" (Sannikov 1992;Sannikov et al.2018) on open,insolated burnt sites was made,using indices of seedling survival as a percentage of the number of seeds that have dispersed to the burnt site within the 5-year renewal period depending on atmospheric moisture index or cumulative stress (Navarro-Cerrillo et al.2018) (Fig.5).

Fig.5 The relationship between the survival index of pine undergrowth (Kav) (6—10 years) in open areas after a fire in the “lingonberry-bilberry-moss pine forest” and the atmospheric humidity index(Kav)

The amount of seeds dispersed by wind to 50 m from the stand edge 25 m high was determined using nomographic charts using data on pine self-sowing numbers on firesites at various distances (Sannikov 1992).

Climate parameter projections

Pine regeneration was simulated using the prediction of average monthly air temperature and precipitation for this region developed by the Canadian Climatological Centre of the Forest Service of Canada (Stocks and Lynham 1996;Tompkins et al.2017) based on atmospheric circulation patterns (McFarlane et al.1992) .Following the forecast,in May 2100 when seed dispersal and the initial,crucial phases of germination and rooting will occur,average monthly air temperatures,compared to 1982—1990 (according to the weather station GMS Tugulym),1Heavy rains and daily precipitation for 1936—1959.Meteorological data for several years.Vol.9 in the Perm,Sverdlovsk,Kurgan,Chelyabinsk regions and the Bashkir ASSR (1967) Hydrometeorological Publish,Leningrad.will increase by 4.5 °C(from 10.1 °C to 14.6 °C) and precipitation by 14% (from 45.8 to 52.2 mm).

Estimation of atmospheric moisture indices

Atmospheric moisture and drought indices,which determine the humidity and burning degree of the moss cover and forest floor and,as a consequence,the amount of pine regeneration and undergrowth (Sannikov et al 2018),were predicted for 2100 as follows:

Based on the linear relationship (t=1.093 T+3.015;R2=0.84) between the average monthly air temperature in May at 1.0 pm (t) and the average daily temperature(T=14.6 °C),we estimated the average temperature for May 2100 at 1.0 pm to bet=19.0 °C.

Based on the linear relationship between relative humidity at 1.0 pm (a) and the hydrothermal coefficient of the atmosphereT/ ∑P(see Fig.4),where ∑Pis the average monthly precipitation,the relative humidity at 1.0 pm in May 2100 was predicted to be 42%.The average monthly air humidity def icit at 1.0 pm was predicted to bed=12.8,and the average drought index for one day was calculated ast×d=19.0 × 12.8=243,according to the psychrometric tables (Ilyin and Reznikov 2018).

Finally,the sum of daily indices ∑t·dwas calculated for the period of time after the last rain of at least 3 mm,reducing ∑t·dand the probability of fire spread to zero (Nesterov 1949;Navarro-Cerrillo et al.2018).Based on weather station data,rain amounts ≥ 3 mm occur at least three times a month in this region,with an average monthly precipitation in May of approximately 40 mm.This rain frequency and the corresponding maximum rainless period of 10 days can be used to simulate and estimate the average fire frequency in 2100,when a slight (14%) increase in precipitation compared to 1982—1990 is predicted.

The maximum cumulative index ∑t·dby the end of the 10-day rainless period,determining the degree of dryness,the probability of fire occurrence and the thickness of the burnt ground layer was ∑t·d=243 × 10=2430.This index,determining the maximum number (density) of pine seedlings on burnt sites,and,as a result,the surviving 6—10 year undergrowth,is the most reasonable one for the simulation and evaluation of the renewal success of cenopopulations.In addition,according to our long-term research carried out over 25 years,the occurrence and spread of ground fires in green-moss pine forests become possible only when the ∑t·dindex exceeds 500—700.

Finally,the average daily relative humidity in May 2100(a=61%) was calculated following:a13=− 22.11+1.05a;wherea13is the relative humidity of 42% at 1.0 pm.

The atmospheric moisture index (Кaв=0.47) was calculated following the formula of Ivanov (1948):Кaв=P/0.0018(25+T)2(100 −a);whereTandaare the average daily temperature and relative humidity,respectively.The same parametersa(62%) andКaв (0.54) were found for the period 1982-1990.Thus,the coefficient of the predicted decrease in average monthly humidity in 2100 compared to the end of the twentieth century is 0.87.

Results

Prediction of fire-based pine regeneration under the canopy

Based on the above empirical pyroecological and meteorological relationships,the following algorithm for the simulation of possible pine regeneration in 2100 on burnt sites under canopies was:

Nп=12.23Tнп−0.65×Кaв2/Кaв1×Кc (5);whereTнп is the thickness of burnt forest floor (see Fig.1),Кaв2/Кaв1—the reduction rate of atmospheric moisture index in 2100 compared to the 1980s (0.87),Кc is the increase rate of seed production by 25% (1.25) due to the rise of effective temperatures during summer months (Sannikov et al.2004).

The moisture indicesКaв1andКaв2in 1982-1990 and 2100,respectively,are calculated using the above pyrologic and meteorological relationships:Кaв1=45.8/0.0018(25+10.1)2×(100 62)=0.54;Кaв2=52.2/0.001 (25+14.6)2×(100 61)=0.47.The coefficient of atmospheric relative dryness,which determines the regeneration number and survival (see Fig.3),in 2100 will be equal toКaв2/Кaв1=0.47/ 0.54=0.87,comparing to the 1980s.

As a result of simulation using algorithm 5,the density is:Nп=85,300 specimens/ha × 0.87 × 1.25=92,764 seedlings/ha or rounded to 93 thousand seedlings/ha.

If the thickness of the forest floor and moss cover in the cowberry-blueberry-moss pine forests in the pre-foreststeppe subzone,which have not been burnt for more than 50 years,is equal to 6.5 ± 0.8 cm,and ∑t·d,predicted ten days after raining,equals 2430,the thickness of the burnt forest floor layer,according to Eq.1 (see Fig.1),equals 4.8 ± 0.4 cm and the residual forest floor layer is 1.7 ± 0.2 cm.

For the same values of the ∑t·dindices and thickness of the burnt ground substrate,the thickness of the unburnt layer in different biogeocenosis is closely related to the initial thickness of the moss cover and forest floor layer.

Simulation of expected pine regeneration density,according to the submodels mentioned with alternative (with respect to the previously accepted—6.5 cm) values of pref ireTнп of 5.5 cm and 7.5 cm allowed for the determination the following parameters of the undergrowth number.

With the initial thickness of the ground layer of 5.5 cm,the ∑t·d=2430,Tвп=4.8 cm andTнп=0.7 cm,pine regeneration density in 2100 is predicted to be:Nп=154,200 × 0.8 7 × 1.25=167,693 seedlings/ha or approximately—168,000 seedling/ha.With a pre-f ire substrate thickness of 7.5 cm andTнп=2.7 m,the regeneration density is predicted to be:Nп=64,100 × 0.87 × 1.25=69,709 seedlings/ha,or in round figures,70,000 seedlings/ha,i.e.,2.4 times less than the original average thickness of the substrate of 5.5 cm and 25% less than at its thickest of 6.5 cm.The same simulation of the predicted number of pine regeneration can be performed for any thickness of forest floor and moss cover.

Pine regeneration prediction on open sites

The main determining factors in the algorithm for modeling the amount of regeneration (Np) in 2100 on sites with frequent fires are the volume of seed dispersal from the forest edge and the survival of seedlings in full sunlight and soil moisture def iciency:Nп=5Nc ×Кн ×Кв,whereNc is the average annual seed yield at the forest edge over a 5-year period (450 thousand seeds/ha/year × 5),Кн is the degree of seed deposit at the fire site,Кв is the coefficient of pine regeneration survival in 6—10 years (percentage of mature seeds dispersed).

According to our results,the dispersal (Кн) of seed from the 25-m forest edge to the adjacent burnt site is,on average,equal to 26% of pine seed that have matured in the stand(Sannikov 1992).

As the atmospheric moisture index (Кaв) decreases from North to South,the rate of survival pine seedlings on open burnt sites and on harvest/burnt sites rapidly decreases,on average from 6 to 7% of the dispersed seed in the southern taiga to 0.25% in the southern forest-steppe zone (Fig.5).

If the atmospheric moisture index (Кaв) in the pre-foreststeppe subzone decreases from 0.54 in the 1980s to 0.47 in 2100,the survival rate of pine regeneration on burnt sites will decline from 3.3 to 2.5%.

The average pine regeneration predicted in 2100 may be calculated as follows:Nп=450,000 × 5 × 0.26 × 0.02=11,700 seedlings/ha.This degree of regeneration on an average unburnt forest floor thickness of 1.7 cm is almost three times lower than the actual population level of regeneration(30,000—33,000 thousand seedlings/ha) on burnt sites in the 1960s—1980s (Sannikov 1992).

Simulation of the pine regeneration at the end of the twentieth century

To compare the predicted renewal levels of pine regeneration in 2100 with that in 1980—1990,the theoretically expected nominal density of self-seeding on burnt sites using algorithms and methods was calculated,taking into consideration climatic conditions of the late twentieth century.

For burnt sites under the canopy of the mature forest,the calculation according to algorithm 5 is:Nп=12.23Tнп−0.65×Кaв2/Кaв1 ×Кc.The minimum thickness of the unburned forest floor with an initial thickness of 6.5 cm at average daily May temperatures of 10.1 °C after the fire,is determined by the thickness of the burned layer,which in its turn is determined by ∑t·d.Following the known hydrothermal relationships,temperature at 1.0 pm (14.1 °C),the relative air humidity def iciency is 9.2,and ∑t·dfor a 10-day rainless period is 1297.Using Eq.1 (Fig.1) the average thickness of the burnt layer (3.5 cm) and residual layer of the substrate (3.0 cm) was determined.According to model 2 (Fig.2),the density of 6—10 year-old pine regeneration is equal to seedlings/ha.As a result of the simulation of pine regeneration based on values of the initial substrate thickness 5.5 cm and 7.5 cm,density values of 77,900 seedlings/ha and 49,700 seedings/ha,respectively,were obtained.

Expected pine regeneration success on bare fire sites up to 50 m from the forest edge can be predicted based on the parameters of relative dispersal (0.26) and seedling survival up to 6—10 years (3.6%;Fig.5).Simulating the regeneration response according to the algorithm according to the climate conditions of the 1980s,the results wereNп=450,000 × 5 × 0.26 × 0.036=21,060 seedlings/ha.Therefore,the predicted pine regeneration on frequently burnt sites in 2100,11,700 seedlings/ha,is two times lower than at the end of the twentieth century.

Discussion

Forests are complex ecosystems formed by the longest-living organisms and the vitality of woody plants is supported by smaller elements of this ecosystem which have a significantly shorter life cycles.

The interaction of all system components can be predicted using various models.The most relevant innovative models for the development of forest restoration are described in Blanco et al.(2020).

Alternatively,in regeneration and habitat border displacement ofP.sylvestrisand other forest species,the ecogeographic consequences of climate changes and possible intensification of wild fires can be observed on the northern borders of the boreal zone (Kauppi and Posch 1988;Wein et al.1996;Kharuk et al.2006).It is likely that with the pace of climate warming,restoration of boreal forests will require considerable eff orts,which will also be associated with an increase in forest fires.However,according to climatic models for the RCP 8.5 impact scenario,under favorable conditions,we will be able to maintain the predominance of conifers in boreal zones (Reich et al.2018;Nenzén et al.2020).

The results of this study are consistent with a number of authors who suggest that,with the current rate of global warming,the frequency of fires in Western Siberia will increase.The wildf ire season will start earlier and end later(Kharuk et al.2006;Reich et al.2018;Noce et al.2019).

We obtained qualitatively different results of pine regeneration simulation for open firesites at a distance up to 50 m from the stand edge.The renewal success of the pine species depends mainly on two factors:the degree of seed dispersal from the forest edge and the survival of self-seeding pine seedlings under the influence of direct sunlight and soil moisture def iciency aggravated by grass competition,especially bushgrass [Calamagrostis epigeios(L.) Roth].

Using the widely accepted empirical reductionist method,we tried to isolate and study one environmental factor or variable at a time,namely the inf ulence of fires on the regeneration of a pine forest.

The key ecological factor influencing the amount of pine regeneration on the burnt over sites is the thickness of the residual unburned layer of leaf litter.The role of this factor is described in detail in Sannikova 1985;1992;Sannikov et al.2018;and Tsvetkov 2014.It is determined by the difference between the initial thickness of the organic ground layer (moss cover or forest floor) and the thickness of its burnt upper layer.An important role of forest litter in forest restoration processes was also noted for other plant species such asKandelia obovata.The accumulation of carbon,macro-and micro-nutrients,and ash compounds from forest litter depends on the wind of the development of the entire ecosystem (Caldeira et al.2019;Chen et al.2020).

The projected density of one-year-old pine seedlings in 2100 should be reduced by 13% compared to the density in 1982—1990.Therefore,in case of a sharp increase in air temperatures in May 2100 (by 45%) and a simultaneous increase in precipitation (by 14%),compensating for the moisture def icit of moisture in general,there will be no significant drying out of the atmosphere as a limiting factor for pine regeneration survival.

As a result of modeling the density of pine regeneration based on different values of the initial ground cover thickness (Fig.2),it can be concluded that,depending on the thickness of the initial and unburned litter layer,the normal (under adequate to modern climatic conditions)density of fire-dependent pine regeneration under the forest canopy at the end of the twentieth century was 29—54%less than projected for 2100.

Under the canopy of cowberry-blueberry-green-mosspines,cumulative value the thickness of the burnt layer of the ground cover,the thickness of its unburned layer naturally accumulates as the stand age and density and the time of the last fire increase.In the model mature stands of the forest type in this study,it usually reaches 4—6 cm by the 50th year after a fire and 5—7 cm under the canopy of a forest that has not had fire for more than 100—150 years.

The renewable efficiency coefficient of fires that mineralize thick layer of moss and duff in south and north subzones is 3-5 times higher than in the pre-forest steppe(Sannikov 1992).At the levels of summer temperatures(Ilyin and Reznikov 2018) predicted by the end of the 21 century,we can expect environmentally significant increase of the ground substrate burning degree,and an increase in depth of thawing and heating of the soil root layer (Matveev 2006;Prokushkin et al.2008).An increase in reproduction has been noted for European beech and oak.There is a change in seed fertility of common juniper due to climate warming.Despite an increase in seed production throughout its range,the species is decreasing,which is associated with a reduction in viable seeds (Caignard et al.2017;Gruwez et al.2017;Bogdziewicz et al.2020).

Perhaps a warming climate for some coniferous species will lead to an increase in seed production and the renewal of f rie-dependent species at the northern edges of their habitats.

To illustrate the results of our work and the consistency of our data with those of our colleagues,we present a map of changes in the boundaries and density of a pine forest from Noce et al.(2019) (Fig.6).

Fig.6 Present distribution of pine species on the territory of the Russian Federation and according to calculated scenarios.The map was the result of the mathematical analysis of the Cascade Ensemble System (CES).The map ref lects the results of this study

In the long-term,there will be a decrease in the density of the major forest-forming species (birch,pine,larch) with a significant increase in aspen and fir.This conclusion is valid for the entire territory of the Russian Federation.An important result of this study is the observation of a reduction in the area of forests formed by two or three species.Such forests are more common in Western Siberia (for example,pure pine forests in the southern taiga and pure spruce forests in the northern taiga).According to our results,the area of pine forests in Western Siberia will decrease due to an increase in the frequency of fires.General warming,a decrease in the moisture content of air masses and an increase in the number of pines seedlings can be considered the main results of the increase in fire frequency.Increased competition among young trees leads to their partial drying out.One of the factors in the transition of a ground fire to the upper crowns is a large amount of dead pine undergrowth.

In general,if the current rate of warming and climate drying out remain the same,then the pine renewal on burnt sites and on other open sites (cutting areas,abandoned farmlands)a modern pre-forest-steppe (podtaiga) will develop according to the "forest-steppe" type.It is characterized by more abundant seed production,higher degree of forest floor burn,mass appearance and rapid dying off of pine self-seeded seedlings under the canopy as well as much lower survival rates and less than twice the regeneration on insolated continuous fire sites.

The weakening of the potential for renewal,settlement and stability of pine forests by the end of the twenty-first century may result in their becoming steppes and retreating north,enhanced by anthropogenic stress.This well-illustrated by the map of Noce et al.(2019) (Fig.6).The warming of south Western Siberia inevitably stimulates other structural and functional changes in the fire-dependent pine ecosystems.If the thickness of the unburned forest floor declines from 2.5—3.0 cm to 1.0—1.5 cm,we can expect a reduction of small-leaved species in the stand composition together with an increase in their seed renewal relative to the vegetative one.

Conclusion

The hypothetical number ofP.sylvestrisregeneration,considering climate warming and fires in pine forests,can be predicted on the basis of climatological forecast of temperatures and precipitation during the reforestation period,as well as empirical relationships between them and other hydrothermal parameters,stand seed production,degree of substrate burn,and its influence on the density of pine seedlings.

The simulation of the expected pine regeneration in the dominant pine forests was based on the prediction of the Canadian Climate Centre for 2100 regarding an increase in air temperatures (by 4.5 °C) and precipitation (by 14%) in the West Siberian pre-forest-steppe.According to the forecast for 2100,stand density,depending on the initial thickness of forest floor and moss cover,atmospheric drought index,the thickness of the burnt layer and the residual layer of forest floor,pine regeneration may be 70—168 thousand seedlings/ha on the burnt sites under a forest canopy and less than 11.7 thousand seedlings/ha) on open burnt sites,which corresponds to the current forest-steppe level of pine renewal.

The simulated nominal post-f ire density of pine regeneration in the same type of forest in climatic conditions of the 1980s was 29—54% lower under the forest canopy,but twice as high on adjacent open sites,compared to the density predicted for 2100.Thus,one of the possible environmental consequences of warming and climate drying in pine forests of the pre-forest-steppe of Western Siberia in the twenty-first century may be a twofold reduction in their renewal intensity on continuous fire-prone sites,the main method of their reproduction.There is risk that the stability and settlement potential of pine populations in this subzone will reduce.

At the same time,on the northern border of the forested area,where overall warming of the environment will increase,we can expect a significant intensification of seed production,regeneration and resettlement of populations of light-needle species.

The study was carried out within the framework of the state program of the Botanical Garden of the Ural Branch of the Russian Academy of Sciences.

AcknowledgementsThe researchers thank the three reviewers and the editor of the Journal for their work on the manuscript.