Eustress Assessment of Quercus petraea (Matt.) Liebl. Dendrochronological Series

Eustress Assessment of Quercus petraea (Matt.) Liebl. Dendrochronological Series MARIYANA I. LYUBENOVA, SIMONA P. PETEVA Department o f Ecology and Environment Protection, Faculty o f Biology; St. Kl. Ohridski University o f Sofia, 8 Dragan Tzankov Bid., 1164 Sofia, Bulgaria E-mail: [email protected] Abstract. The paper deals with Meta analy­ sis of 255 European oak Dendrochronolo­ gical series, which are on average 188 years old from 13 locations in Europe for eustress investigation. The oak chronologies were ana­ lyzed by the original SPPAM 2.0 applica­ tion. The tree ring width sequences were approximated with polynomials of mainly r degree with determination coefficients R2 > 0.45. The growth index {It - the ratio between measured and approximated value) was computed. Years with It less than the threshold value were categorized as eustress ones. The four grade scale for assessment of frequency, duration and depth of eustress was proposed. The influence of climatic ty­ pes of years on the eustress appearance is also investigated. We identified 42 eustress periods on ave­ rage for all studied locations. The obtained eustress characteristics are as follows: Ave­ rage Depth of Eustress, A av= 0.244; Average Duration, Dav = 2; and Average Frequency, Fav = 23 years over 100 years. The risk for stands in three studied locations was esta­ blished. The predominance of hot and dry, and cold and dry years in total number of adverse climatic years (with eustress) was also established. The studied broad-leaved tree species is very important from both economic and socio-ecologic points of view. Proposed ho­ listic approach for meta analyses of series Journal of Balkan Ecology, vol. 18, No 2, 2015

(eustress identification in radial growth of stem) is convenient for fast monitoring of forest communities state and for recognizing the Q. petraea stands under risk in Europe. The capability of approach allows ex­ pression of reactive Plant Functional Types (PFTs) of trees as the groups of trees with the similar behavior connected to the clima­ tic types of years, and with similar charac­ teristics of eustress periods. The original approach for Meta-analysis, software, cha­ racteristics, indexes and coefficients were applied. Key words: dendrochronology, Meta-ana­ lysis, eustress, climatic type of year, growth index, International Tree Ring Data Bank (ITRDB).

INTRODUCTION Owing to climate change (EPCC, 2007), the survival and sustainability future of forest ecosystems has become of great concern ( J u m p et al., 2009; M a t y as, 2010). European oak (Q. Pet­ raea) has provided a reliable frame­ work for chronological dating and reconstruction of past climate and en­ vironmental changes. H a n e c a et al. (2009) had investigated development of oak dendrochronology in Europe. In addition to global warming, the fre­ quency and the intensity of droughts will probably increase in central and so­ uthern Europe. Resulting climate changes and soil water deficits could alter tree growth, according to sensitivity of each species (M i c h e 1 o t et al., 2012). According to K 1i m a (2004), Euro­ pean oak is one of important com­ mercial tree species both as the main timber species and as a species con­ stituting high-quality mixtures with other commercial tree species, namely with beech, pine and larch. Climategrowth relationships based on tree-ring width, basal area increment (BAE) and tree-ring 513 C signatures of European 171

oak in central Eurooe ('Luxembourg) were investigated bv H a r d 11e et al. f2013L Their-studv established a high resilience of sessile oak to climate change. Thev concluded that O. Petraea was an adaptive tree species in central Europe’s forests under shifting climatic conditions. Many forest dyna­ mics models have been developed in the last decades ( M o g u e d e c et al., 2011). For example, yield model was adapted to managing Q. petraea and Fagus sylvatica L. in France. We must explain that the structure of a given model depends on the purpose, for which it has been developed. The used holistic approach for eustress investigation was applied for other oak species ( L y u b e n o v a et al., 2014a,b). Eustress is considered as the stress syndrome, which flows through all phases and a biological system can even adapt to achieve greater sustain­ ability. In this case, the repeating state of diminished radial growth rate of tree stems within a period of one or mul­ tiple years is caused by unfavourable factors in the environment. MATERIAL AND METHODS European oak dendrochronological se­ ries from 13 European locations were studied using the data from Interna­ tional Tree Ring Data Bank (ITRDB, http://www.ncdc.noaa.gov/paleo/treeri ng.html). The geographical range of locations is as follows: latitudes - from 5.25 to 51.45; longitudes - from 6.03 to 16.15 and altitudes: from 30 to 900 m; (Alt av = 363 m) (Table 1). The rele­ vant climate characteristics are: annual temperatures - from 1.55 to 26.7°C for studied locations (T„„ = 9.780C1: annu­ al precipitations - from 530.39 to 2218.86 mm (Pav = 967.02 mm). The series are 255 in number (by locations: 172

from 12 to 55), aged from 69 to 401 vears. with diameter on breast height bv locations from 17.94 to 85.07 cm ( D B H n „= 42.98 cm) and with calcu lated expressed population signal from 83.66 to 98.44 % (EPS,,, 90.40 %). The representative samples for the ana­ lysis are with EPS more than 80 %. SPPAM application 2.0 (L y u b e n o v a et al., 2015) was applied for the calculation of parameters as follows: (a) growth index (It) as the ratio bet­ ween measured and approximated va­ lue of tree ring width by polynomial approximation of dependency tree ring widths; (b) age for each series in lo­ cation (acceptance of polynomials with R2 > 0.45); (c) Card index - the num­ ber of rows with established eustress for the specific year; (d) Cov index the relationship between the rows in which stress is established for a given year to the total number of measured widths for the year; (e) K coefficient the ratio of the research period to stres­ sful years; (f) Ct coefficient - the ratio between Card to number (N) of inves­ tigated rows; (g) eustress year (SY) year with It less than the threshold value; (h) depth o f eustress (A) - the threshold value of It declination under 1; (i) frequency o f eustress (F) - the number of stress years for a period of 100 years; (j) duration o f eustress (D) - the number of adjacent eustress years. The climatic type of year (CTY) of the periods of studied series was also determined using the deviations of average annual temperature and preci­ pitation from the average values over 30 years periods and their confidence intervals. The considered CTY are: hot and dry (HD), cold and dry (CD), hot and wet (HW), cold and wet (CIV), nor­ mal and dry (ND), normal and wet (NW), hot and normal (HN), cold and normal (CN) and normal by temperature and precipitation (NN). The adverse year Scientific Research Papers: Forest Ecology

Journal of Balkan Ecology, vol. 18, No 2, 2015

Table 1. Longitude (Long), latitude (Lat), altitude (Alt), average annual temperature (Tav,) and average annual sum of precipitation (Pav) of Quercus petraea (Matt.) Liebl. sampling areas (SA) and characteristics of studied series (diameter of breast height, DBH; number - N, calculated EPS - expressed population signal) P av5 Sampling area Long Lat. Alt., Tav, DBH, Agemin, Agemax, N Period EPS K (m) (°C) (mm) (cm) (SA) year year (% ) 1. Enniscorthy (UK) 6.32 5.25 30 26.7 2172.98 17.94 108 13 161 1811 - 1978 86.87 2. Cavergno (CH) 8.36 46.21 900 1.55 2218.86 37.60 38 401 1602 - 2002 55 94.26 3. Wienerwald (AT) 16.15 48.07 450 8.97 530.39 85.07 123 93.78 1803 - 1995 41 193 4. Ebrach(DE) 10.3 49.47 350 8.22 597.02 28.70 98.44 46 69 1879- 1947 22 5. Nordrhein-Wes­ 6.33 50.26 560 9.58 843.39 40.77 1853 -2004 114 13 83.66 152 tfalen E ifell (DE) 6. Nordrhein-Westf­ 6.25 50.36 400 9.58 843.39 52.48 161 14 193 1812 -2004 88.74 alen Eifel 2 (DE) 7. Nordrhein-West­ 6.16 50.4 843.39 460 48.69 9.58 137 199 13 90.42 1806 2004 falen Eifel 3 (DE) 8. Nordrhein-West­ falen, Sieben-gebirge 7.14 50.4 370 8.86 753.53 36.16 109 18 1847 - 2004 158 93.66 (»>»>______________ 9. NordrheinWestfalen, Haiger8.13 50.51 440 7.84 770.76 32.47 131 1859-2005 14 147 86.51 Siegerland (DE) 10. Nordrhein-West­ falen Oberber7.43 50.58 260 8.58 808.82 42.86 110 1777-2005 12 86.66 229 gisches Land (DE) 11. NordrheinWestfalen Koeln6.48 51.02 45 ‘ 9.87 743.15 58.84 14 116 154 1852-2005 89.89 Bonner Bucht (DE) 12. Hessen, Keller9.04 51.09 400 700.33 7.83 31.97 1849 2005 13 93.36 105 157 wald (DE) 13. Niederrheinisches Tiefland 6.03 51.45 50 9.91 745.23 42.98 170 237 1773 -2009 13 88.92 IDE)______________

Fig. 1. Growth index (If) dynamics for different locations and years Table 2. Average number (n) of obtained eustress years (SY), average

values of growth index (It), confidence intervals (p), cardinality (Card), coverage (Cov), Ct - coefficient (Ct) and K - coefficient (K) SY Period K Card Cov Ct SA (year) It (n) P 39 5.95 0.71 0.46 4.13 1 161 1.012 0.045 45 18.44 0.70 0.34 8.91 2 401 1.002 0.046 37 16.14 0.77 0.39 5.22 3 193 1.003 0.036 11 13.82 0.92 0.63 6.27 4 69 1.002 0.066 45 5.18 0.74 0.40 3.38 5 152 0.997 0.042 6.51 0.72 0.47 4.29 6 45 193 1.006 0.039 47 5.47 0.68 0.42 4.23 199 1.060 0.067 7 40 10.08 0.72 0.56 3.95 158 1.001 0.054 8 47 2.43 0.82 0.17 3.13 9 147 1.016 0.053 2.56 0.85 0.21 5.33 10 43 229 1.000 0.046 154 1.005 0.045 45 6.78 0.75 0.48 3.42 11 48 5.56 0.79 0.43 3.27 12 157 1.002 0.048 57 237 0.984 0.035 4.23 0.73 0.33 4.16 13 42 7.93 0.76 0.41 4.59 188 1.007 0.048 Av (AY) was considered as CTY in which the eustress is established. RESULTS AND DISCUSSION The computed Itav for all locations is 1.007, and varied from 0.984 ± 0.035 for location 7 to 1.060 ± 0.067 for lo­ 174

cation 13, which has lowest altitude. Generally, the It has unidirectional changes by locations (Fig. 1). The ob­ tained correlation between sequences of indexes is moderate in 87.18 % of the cases. The significant correlation takes part with 43.59 % of the cases. The observed similar trend in the radial Scientific Research Papers: Forest Ecology

Fig. 2. Depth (Aav,, duration (Dav) and frequency (FaV) for different locations (%)

growth variation for locations, despite differences in local orographic and cli­ matic factors, probably has caused of analogue climatic changes as the cli­ mate is the main driver of changes in the biological events. The calculated average index is 7.9. It highly varies by locations (Table 2). The low value is indicated low number of rows with established eustress for specific year and vice ver­ sa. The values of index depends on the number of investigated rows, the sets of years homogeneity in periods and climatic variations. The average value of Cov index is 0.8 and it has low variation in the range of 0.7-0.8. The calculated index values show that the trees in location have reacted synchro­ nous to the same changes in climatic regimes as the ratio between the rows, in which eustress is established for a given year to the total number of mea­ sured widths for this year is under 0.5. The calculated Ctav is 0.4. The co­ efficient, which is calculated as ratio between Card to number of investi­ gated rows (N), alows to eliminate the wide variation in the number to some extent and the comparison among stu­ died locations is possible. The average

values for locations are between 0.3 and 0.5. The maximum values of co­ efficient are for locations 4 and 8, i.e. according to Ct, the number of ob­ served SY is the highest. The calcu­ lated Kav is 4.6. The average values for locations vary from 3 to 5 with maximums for location 2 and 4, respec­ tively 9 and 6. The coefficient as the ratio: research period / number of eus­ tress years, allows to eliminate the dif­ ference in the length of series and sur­ vey periods of locations to some ex­ tent, but does not allows to deface the differences in climatic factors (Table 2). The obtained average eustress cha­ racteristics for studied locations are as follows: Average Depth of Eustress Aav = 0.244 ± 0.142, Average Duration Dav = 2.44 ± 0.13 y and Average Frequency Fav =23.1 ± 1.3 times for 100 years. The variation of Aav, Dav and Fav va­ lues by locations are respectively: from 0.2 to 0.3; from 2 to 3 and from 11 to 31 (Fig. 2). The highest average depth of eustress is indicated for locations 4 and 7; the highest average length - for locations 4 and 9 and the highest ave­ rage frequency - for locations: 5,9, 11 and 12. The absolute maximums of A and D values and the years of their

Journal of Balkan Ecology, vol. 18, No 2, 2015

175

Table 3. Maximal values of eustress characteristics (Amax) for investigated Q. petraea (Matt.) Liebl. series and plant functional type of tree (PFT) for different sampling areas (SA)

A

^m ax

SA

Dm ax

value

year

years

period

1 2 3

0.36 0.35 0.36

1923 1984 1981

8 8 4

4 5

0.58 0.49

1940 1942

4 6

6 7 8

0.41 0.56 0.56

1948 1959 1942

7 8 6

9 10 11 12 13

0.60 0.53 0.49 0.47 0.42

1909 1959 1996 1909 1923

9 7 6 7 9

1949-1956 1943-1950 1915-1918 1945-1948 1939-1942 1925-1930 1956-1961 1906-1912 1956-1963 1925-1930 1954-1959 1985-1990 1907-1915 1937-1943 1937-1942 1917-1923 1936-1944

appearance in locations are presented on Table 3. The Amax highest values are again for 4 and 7 and as well for 9 locations. The Dmax highest values are for 1, 2, 7, 9 and 13 locations. So, the absolute maximums of the third eus­ tress characteristics for encompassed years were found for location 9 and absolute maximums in depth and dura­ tion of eustress were obtained for loca­ tion seven. Related to vears are included in related to Dmax sequence of years. These years are published as ad­ verse years for beech and oak stands ( L y u b e n o v a , 2014; L y u b e n o v a et al., 2014ab) - Table 3. According to the scaled average va­ lues (Table 4), the spread Plant Func­ tional Types ( s) are not with T F P tical combinations of A, D and F, i.e. 176

PFT F3D3A1 F1D1A2 F1D1A1 F1D4A5 F4D3A2 F3D2A2 F3D2A5 F3D3A4 F4D5A5 F1D3A3 F4D3A3 F4D2A2 F3D3A2

we can not talk about a significant risk for the most of studied Q. petraea locations for included period of years. The stands show significant risk only in location 9, where the eustress is with very deep depth coupled at high fre­ quency and duration (F4D5A5) (Table 3). Risks to some extend exist for the stands in locations 4 and 7 - very deep eustress, but with normal or very rarely appearance and long or short duration ( F1D4A5, F3D2A5). The potential risk in future exists in location 8, where the trees functional behaviour shows pro­ pensity to appearance of deep eustress, although the eustress frequency and du­ ration are in normal ranges (F3D3A4). Applying the Monte Carlo test, we can not select statistically significant cri­ variable represented by geographical, Scientific Research Papers: Forest Ecology

Table 4. Five-graded scale for assessment of petraea eustress characteristics Duration (D) Depth (A) Frequency (F) Group Value Name Value Value Name Name 19.07Short 2.31 0.25 Often Long 0.27 Very 5 Very Deep Often Long

cance for the growth decreasing (Fig. 4). orographic and climatic factors, such The CTY/N ratio of the relevant clima­ as average temperature and precipita­ tion (Fig. 3) and connections with the tic type and the total number of inves­ tigated years shows that the climate is growth It index and eustress variables for the used European oak locations determined by the background preva­ lence of HD, NW,CW and CD ty from the data base. The chart vectors with total share 53.4 %. of environmental factors are given for informational purposes only, i.e. the According to the ACTY/SY ratio bet­ relations are to each other and to the ween the relevant adverse CTY (with characteristics of the oak. So, as to identified eustress) and the total num­ obtain an objective picture about the ber of eustress years, the HD, CD, CW, climatic influence on the radial growth H W and N W types have the predomi­ and obtained eustress, the climatic ty­ nant influence as stressful climatic pes were identified for studied periods types (69.05 %). In calculating the and locations and their share (%) of ratio between the relevant climatic type participation was calculated (Table 5). of year with stress and the total number The participation of different climatic of relevant climatic types ( ), types (CT) very much varies by loca­ the described patterns are retained with tions because of variation of their geo­ minor changes - HD (55 %) and CD graphical and climatic parameters. The (51 %) prevail. In general, the stress average percent for every CT is cal­ influence of dry to wet climatic types culated and the representative of these prevail, and the cold to warm types is values is presented in Table 5. All mean comparable (Fig. 3). values are reliable for the oak species The stress influence of climatic type behaviour analyses. According to the also depends on the temperature and mean values, the CTs form the fol­ precipitation in previous years. There lowing descending row: HD > CD > is an accumulation of influence on the CW > H W > NW,which reflects degree toof deficiency of heat and hu­ their significance for the radial growth midity also. This can be the result from as they prevailed in climatic backgro­ the impact of other factors. So, the und. Some ratios were calculated for sequence of climatic types for two the detailed analysis of climatic signifi­ years before the current one was exaJoumal of Balkan Ecology, vol. 18, No 2, 2015

177

SPEC IE S

ENV. V A R IA B LE S

SA M P LE S

Fig. 3. Redundancy analysis, RDA results

60.00 50.00 40.00 30.00 20.00 0.00

—

■ C TY /N

CD CN 12.30 8.55

CW N D 1 3 2 7 9.04

NN 7.17

N W HD 13.36 14.01

HN 9.61

HW 12.70

■ A C T Y /SY

14.10 8.24

12.82 7.88

6.41

12.09 17.40 8.43

12.64

■ ACTY/CTY 50.99 42.86 42.94 38.74 39.77 4 0 2 4 5 5 2 3 38.98 4 4 2 3 CTY /N

A C T Y /SY ■ ACTY/CTY

Fig. 4. Significance of obtained climatic types of years (CTY, %)

178

Scientific Research Papers: Forest Ecology

Table 5. Share (%) of climatic type’s variation by locations ^ C lim a tic ty p e s

L o c a tio n

CD CN CW NN ND NW HD HN HW 1 12.82 10.26 10.26 20.51 10.26 5.13 12.82 5.13 12.82 2 13.64 11.36 11.36 6.82 2.27 9.09 27.27 6.82 11.36 3 18.92 8.11 13.51 5.41 2.70 8.11 16.22 16.22 10.81 4 18.18 18.18 0.00 27.27 18.18 0.00 0.00 0.00 18.18 5 13.33 8.89 4.44 17.78 4.44 11.11 15.56 2.22 22.22 6 11.11 6.67 2.22 20.00 4.44 17.78 6.67 13.33 17.78 7 22.50 5.00 2.50 7.50 7.50 20.00 17.50 5.00 12.50 8 12.77 12.77 4.26 14.89 8.51 8.51 14.89 10.64 12.77 9 12.77 2.13 8.51 8.51 6.38 14.89 21.28 10.64 14.89 10 9.30 9.30 4.65 16.28 4.65 11.63 18.60 11.63 13.95 11 20.45 9.09 9.09 15.91 20.45 13.64 9.09 2.27 0.00 12 10.42 4.17 14.58 12.50 8.33 10.42 16.67 12.50 10.42 13 12.50 8.93 12.50 5.36 8.93 19.64 14.29 8.93 8.93 A verage

14.52

8.83

1 3 .4 6

7.61

7 .0 4

11.30

4.11 4.07 5.71 6.46 4.38 5.59 E rror 1.14 1.13 1.79 1.58 1.55 1.21 S tu d e n t’s t 1.77 1.77 1.77 1.77 1.77 1.77 Y R e lia b le Y Y Y Y Y *Legend: cold and dry (CD), cold and normal (CN), cold and wet (CW), normal and normal (NN), normal and wet (NW), hot and dry (HD), hot and wet (HW). S t. D ev .

mined. Pattern analysis showed that the change in one of two regimes - warm to cold or dry to wet, also the impact of adverse climatic type in at least two consecutive years and/or a presence of eustress in at least one of the previous years of three-year period surely pro­ voke eustress in the current year. So­ metimes, the current adverse year be­ longs to normal or not so adverse cli­ matic type. CONCLUSION The set of Dendrochronological sequ­ ences subjected to meta-analysis have a similar trend in the radial growth in the studied locations, despite differen­ Joumal of Balkan Ecology, vol. 18, No 2, 2015

16.30

7 .9 4

12.99

6.14 4.52 4.88 1.70 1.26 1.35 1.77 1.77 1.77 Y Y Y normal and dry (ND), and normal (HN), hot

ces in orographic and climatic factors, possibly due to the influence of ana­ logue climatic changes as climate is the main driver for the range of growth. This is a good reason to look for com­ mon and different features in the res­ ponse of the European oak in different ocations to environmental changes. The estimated coefficients and cha­ racteristics of stress periods have maximums of average values for different locations. For location 4, we establish­ ed maximum averages respectively for both coefficients and two of the cha­ racteristics of location 9: respectively for one of coefficients and for two of the characteristics studied. 179

Through the combined evaluation of the characteristics of eustress, the esta­ blished risk is only for stands of tree locations: respectively 9 (showed sig­ nificant risk - very deep depth of eus­ tress coupled at high frequency and duration); locations 4 and 7 - very deep eustress, but with normal or very rarely appearance and long or short duration. The calculated ratios between cli­ matic types and adverse years for stu­ died periods prove stressful impact on the species of mainly warm and dry, and cold and dry years. The wet years may also have some importance for suppression of the radial growth. Fur­ thermore, the change in one of two re­ gimes - warm to cold or dry to wet, also the impact of adverse climatic ty­ pe in at least two consecutive years and/or a presence of eustress in at least one of the previous two years surely provoke eustress in the current year. Proposed holistic approach for meta - analysis and eustress identification are applicable for fast monitoring of forest communities and for recognizing the stands under risk, where the eus­ tress frequently appears, with very long duration and very deep depth. Mixed forests with the dominance of Quercus dalechampii L. are very important broad-leaved communities in Bulgaria. The same analysis within the species distribution range is necessary to compare the results and to confirm the obtained patterns. REFERENCES K 1 i m a, S. 2004. Importance of Ses­ sile Oak in the Mixture with Larch and Beech on Sites Operated by the Training Forest Enterprise Krtiny. Main Tasks of Silviculture at the Beginning of the 21 st Century MZLU, Bmo, 159-172. 180

IPCC. 2007. Climate Change: the Phy­ sical Science Basis. Contribution of Working Group I to the Forth Assessment Report of the Intergovern­ mental Panel on Climate Change. Cambridge University Press, Cam­ bridge, UK, 1009. H a n e c a, K., K. C u f a r, H. B e e c k m a n. 2009. Oaks, Tree-rings and Wooden Cultural Heritage: Re­ view of the Main Characteristics and Applications of Oak Dendro­ chronology in Europe. - Journal of Archaeological Science, 36,1-1. J u m p, A. S., C. M a t y a s, J. P e n u e 1a s. 2009. The Altitude-forLatitude Disparity in the Range Re­ tractions of Woody Species. - Trends in Ecology and Evolution, 24, 694701. M a t y a s, C. 2010. Forecasts Needed for Retreating Forests - Nature, 464, 1271. L e M o g u e d e c , G., J-F. D h 6 t e. 2011. Fagacees: a Tree-Centered Growth and Yield Model for Sessile Oak {Quercus petraea L.) and Com­ mon Beech {Fagus sylvatica L.). Annals of Forest Science (2012) 69: 257-269 DOI 10.1007/sl 3595-0110157-0. M i c h e 1o t, A., N. B r e d a , C. D a m e s i n, E. D u f r e n e. 2012. Differing Growth Responses to Cli­ matic Variations and Soil Water De­ ficits of Fagus sylvatica, Quercus petraea and Pinus sylvestris in a Temperate Forest. - Forest Ecology and Management, 265, 161-171. H a r d 11 e, W., T. N i e m e y e r, T. A s s m a n n , A. A u l i n g e r , A. F i s h t n e r , A. L a n g , C. L e u s c h n e r , B. N e u w i r t h , L. P f i s t e r, M. Q u a n t e, C. R i e s, A. S c h u 1d t, G. von O h e i m b. 2013. Climatic Responses of Treerins Width and 513 C Signatures of Sessile Oak {Quercus petraea Liebl.) Scientific Research Papers: Forest Ecology

on Soils with Contrasting Water Sup­ ply.-Plant Ecol 214, 1147-1156. L y u b e n o v a , M., A. C h i k a 1a nov, V. L y u b e n o v a . 2014a. An example of Holistic Approach for Analysis of Periods with Low Stems Growths and their Application. - Comptes rendusde I ’Academie Bulgare des Sciences, Biologie, Ecologie, 67(4), 541-550. L y u b e n o v a , M., N. G e o r g i e va , V. L y u b e n o v a . 2014b. Assessment of Oak Dendrochronological Series in Protected Zone (Bul­

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garia) for Eustress Identification in Forest Stands. - IJAIR 3. 1, 116-124. L y u b e n o v a . M. 2014. Assessment of Red Oak Dendrochronological Series for Eustress Identification in Forest Stands. - Journal of Balkan Ecology, 17(4), 391-401. L y u b e n o v a , M., A. C h i k a 1a n o v , V. L y u b e n o v a , St. V a t ov. 2015. SPPAM 2.0: Scientific Description and Use. - Journal of Environmental Science, Computer Science and Engineering & Techno­ logy, Sec. B, 4(1), 37-51.

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