of beech (Fagus sylvatica), silver fir

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The influence of site factors on the composition and structure of semi-natural mixed-species stands of beech (Fagus sylvatica), silver fir (Abies alba) and Norway spruce (Picea abies) in the Upper Draganul Watershed of North-West Romania I.V. ABRUDAN AND R.A. MATHER Forest Products Research Centre, Buckinghamshire University College, High Wycombe HP11 2JZ, England

Summary Results of redundancy analyses for beech–conifer stands in the mountains of North-West Romania indicate that Abies alba predominates at mid- to upper-slope positions, on steep gradients and favours southerly aspects. In contrast Picea abies was most abundant on frost-susceptible lower slopes and damper sites with north-westerly aspects. A weak ordination with respect to site factors reflected that Fagus sylvatica may have been at the upper elevation limits for its natural distribution. It is concluded that the two conifer species have site requirements that are relatively complementary for both the production and the conservation of mixed stands.

Introduction From the turn of the century the structure and species composition of beech–conifer mixed forests in Romania have been greatly influenced by management. In particular, attempts to improve economic returns from forests have led to the replacement of naturally occurring mixtures of beech (Fagus sylvatica L.), Norway spruce (Picea abies (L.) Karst.) and silver fir © Institute of Chartered Foresters, 1999

(Abies alba Miller) with pure stands of Norway spruce (Marcu, 1974). Many of these pure stands, however, have been shown to be more susceptible to both biotic and abiotic forms of damage than the original mixtures (Florescu et al., 1995). The revival of beech–conifer mixtures on sites naturally suitable for their growth has been a priority for Romanian forest policy since 1976 (Geambasu, 1995). In an endeavour to determine how natural composition and structure may vary Forestry, Vol. 72, No. 2, 1999

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with site conditions and thereby to suggest appropriate management for encouraging the regrowth of beech–conifer mixtures, a number of regional studies have been made of those natural and seminatural forests which have been least affected by human intervention throughout Romania (Decei, 1986), in northern Romania (Brega, 1986) and are ongoing in the Brasov region of Romania (Florescu et al., 1996). The investigations reported here relate to the influence of the main physiographic factors on the composition of semi-natural beech–conifer mixtures in the Upper Draganul Watershed in NorthWest Romania. In this locality, mixed forests form a clearly defined area of about 5000 ha, of which more than half retain their semi-natural status. The climate in this territory is mild and humid in comparison with the more obviously continental climate in other mountain regions of Romania. Soils are, therefore, relatively fertile and about 90 per cent of mixed stands occur on brown acid soils of medium depth.

Methods Transects are widely used for surveying hillside vegetation (Kent and Coker, 1992) and field survey followed the ‘itinerant transect’ model (Chirita et al., 1977; Tarziu, 1993), which is recommended for use in mountainous landforms with broken terrain. Fifty two sample plots were established along 13 transects down slopes traversing 20 forest compartments of the Remeti Forest District (Working Unit I – Boceasa and Working Unit II – Molivis). Transects were divided into ‘elementary units’ (sections corresponding to zones in which vegetation and physiographic characteristics were uniform and clearly recognizable as being distinct from neighbouring zones). One 1000 m2 sample plot (20 m down slope 3 50 m perpendicular to slope) was placed at the mid-point of each elementary unit. The number of plots placed in any one transect (varying between two and six) was therefore related to the vegetation and physiographic variation along slopes. An essential feature of this study is that forest compartments were selected on the basis that, according to forest service records, the three species were approximately equally abundant at

the time of stand regeneration. Plots were in seminatural mixtures, which were found to be between 70 and 95 years old, of a relatively even age-structure and with near-complete canopy closure. Altitude, aspect, position on slope and slope gradient were recorded in each plot. Position on slope was scored 1 to 5 representing lower-valley to upper-slope positions respectively and reflecting site susceptibility to thermal inversion, frosts and exposure. Aspect was also recorded in classes 1 to 5 (1–N, 2–E, 4–W and 5–S), reflecting greater shelter from exposure as well as generally more favourable site conditions. Height (m) and diameter at breast height (d.b.h. in cm) were measured for all stems larger than 6 cm in diameter. In general the little regeneration observed was limited to areas where small gaps had developed in the tree canopy. As a result of these conditions, within-plot variations were smaller than usually reported for such mixtures (Armasescu, 1971; Decei, 1986). Tree dimensions for any one species were, therefore, sufficiently uniform and normally distributed to justify expressing height and d.b.h. as plot mean values rather than using separate size classes.

Results and discussion The range of elevation for sample plots was between 1000 m and 1380 m. Fifty per cent of plots were found to be north or east facing, the other occupying warmer and drier slopes of more southerly aspect. Slope gradients were typically between 10° and 30°. Data distributions are summarized in box-andwhisker plots (Tukey, 1977) presented in Figure 1. Data were treated by redundancy analysis (RDA) and the resulting ordination of response data against environmental variables and axes is shown in Figure 2. Owing to the primary aim of establishing the extent of physiographic control over the composition of mixtures, RDA was selected as the most suitable means for direct gradient (canonical) analysis of response data with respect to explanatory variables (Ter Braak and Prentice, 1988; Kent and Coker, 1992). This technique has been applied successfully in comparable circumstances for the analysis of forest condition responses to pollution and climate

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Figure 1. Box-and-whisker distributions for basal area (1a), abundance (1b) and diameter at breast height (1c) by species Picea abies (PA), Abies alba (AA) and Fagus sylvatica (FS). Interpretation: boxes represent interquartile ranges, ‘whiskers’ extend to the furthest data point within 1.5 quartile ranges from interquartile boxes and outliers are plotted as individual points. Each far outlier, a data point more than three interquartile ranges below the first quartile or above the third quartile, is shown as a point with a plus sign through it. Lines bisecting boxes indicate median values and notches in the sides of boxes represent 95 per cent confidence intervals for medians.

(Innes and Whittaker, 1993; Mather et al., 1995). It is also thought that RDA is more robust than

more widely used canonical correspondence analyses (CCA) in circumstances where there are

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linear rather than Gaussian response to environmental stimuli. This may occur when observed environmental gradients are short in comparison with the range of conditions tolerated by the species of interest, as previously reported for forest crops (Mather et al., 1995). The three species were found to be present in most plots. Proportions and dimensions recorded for each species, however, varied considerably. Although the high altitudes of observed stands were not necessarily marginal for the survival of beech, which is known to tolerate suppression for much longer periods than the two conifers, they would certainly be regarded as limiting for economic growth. This is reflected by the plot-mean distributions (Figure 1) which show that basal area for beech (Figure 1a) was usually less than that recorded for the two conifers. Although being more abundant (Figure 1b), beech diameters were generally much smaller (Figure 1c) than those of conifers. Box-and-whisker distributions (Figure 1) indicate that Norway spruce and silver fir were approximately equally abundant and that silver fir tended to be of slightly greater d.b.h. than Norway spruce. The correlation biplot (Figure 2) and the statistical summary for this (Table 1) indicate that the first axis is strongly influenced by and highly significantly related to gradient, aspect and plot position. The first axis alone was found to account for 74 per cent of variation in the overall response–physiographic relationship. The second axis, largely a function of gradient, accounted for a further 11 per cent of variation only. The two conifer species have clearly opposite polarity on the first axis indicating that they occupy relatively different environments. The similar general direction in which silver fir (‘AA-abundance’ and ‘AAbasal area’), aspect and slope position ordinate is consistent with observations that this species tends to occupy mid- to upper-slope locations and is also frequently found on the shoulders of valley spurs with south or westerly aspects. In these conditions silver fir tends to grow to greater dimensions and the juxtaposition of ‘AA-d.b.h.’, ‘AGE’ and ‘GRADIENT’ in the lower left quadrant of the biplot also suggests that individuals of larger d.b.h. and in older stands sometimes occur on steeper slopes. These observations are consistent with the belief that although shade-bearing, silver fir thrives in milder conditions and establishes in

less frost-prone locations than those tolerated by Norway spruce (Stanescu, 1979; Savill, 1991). Although one may have anticipated that altitude would exert greater influence on the first axis, silver fir usually favouring moderate elevations, it is known that due to the Atlantic type of climate peculiar to this region this species may grow at greater elevations than normally recorded in other Romanian mountains (Badea et al., 1983). From Figure 2 it can be seen that Norway spruce occurs more frequently (‘PA-abundance’) and grows more densely (‘PA-basal area’) on slopes with north or easterly aspects. The ordination also indicates that spruce establishes at lower positions on slopes. This region is known for the occurrence of thermal inversions and for this reason, valley floors and lower slopes may be less suitable for frost-sensitive silver fir. Precipitation is greatest on north- and west-facing slopes and the abundance of Norway spruce on such slopes is consistent with its known preference for wet sites (Stanescu, 1979; Savill, 1991). The ordination of height and d.b.h. for spruce (‘PA-height’ and ‘PA-d.b.h.’ in Figure 2) is close to the origin of the biplot and indicates that the occurrence of larger trees is only weakly related to recorded environmental variables. In Figure 2 all beech variables lie close to the origin. This suggests that in comparison with the two conifers, conditions throughout the Upper Draganul Watershed were marginal for the economic growth of beech. In another RDA (not shown) conifer data were treated as explanatory (environmental) variables. The resulting ordination showed a strong polarity in the position of beech in relation to silver fir on the first axis. This is also consistent with the premise that the growth of beech is suppressed by more vigorously competitive silver fir. These findings have important consequences for the future management of beech–conifer mixtures in Romania. In contrast to some other parts of the country where beech thrives in such mixtures (Negulescu et al., 1973), economic production from beech is unlikely in the Upper Draganul Watershed. Although in suppressed condition, the presence of beech in large numbers, however, indicates that it is a natural component of the observed forest. Prescriptions for promoting beech in mixtures throughout Romania, therefore, should recognize

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Figure 2. Correlation biplot for redundancy analysis of plot-mean abundance (stem number), basal area, height and diameter at breast height (d.b.h.) for Abies alba (AA), Fagus sylvatica (FS) and Picea abies (PA) against ‘aspect’, ‘position’ on slope, ‘altitude’, ‘gradient’, ‘gradient’ of slope and stand ‘age’. Interpretation: environmental variables are represented by arrows, the responses are shown as ‘bullets’ and plots are indicated as small triangles. Eigenvalues for the first (horizontal) axis = 0.167 and for the second (vertical) axis = 0.026. Tests of significance by Monte Carlo permutation: Paxis 1 < 0.01; Poverall model < 0.01). The length of arrows (explanatory variable) or the distance of points from the origin (response variables) are proportional to their standard deviations and the cosines of their angular separation correspond to correlation coefficients (Corsten and Gabriel, 1976; Ter Braak, 1987). The heads of arrows and positions of points indicate the direction of maximum variation in value of the corresponding variable. Variables with arrows pointing in the same direction are positively correlated and those lying in opposite directions are negatively correlated. Perpendicular arrows or points indicate zero or low correlations. The longer the arrow, the greater the importance of the variable and also the confidence of the inferred correlation (Ter Braak, 1987; Ter Braak and Prentice, 1988). The same form of interpretation is attached to relationships between variables and the two principal axes.

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Table 1: Statistical summary of relationships between environmental variables and canonical axes

Environmental variable

Canonical coefficient † ———————————– Axis 1 Axis 2

Altitude Aspect Gradient Position on slope Stand age

0.35 20.58 20.61 20.60 20.28

20.11 0.46 20.71 0.26 20.30

t-value ‡ ———————————— Axis 1 Axis 2 2.16* 24.10** 24.31** 23.71** 21.93

20.34 1.58 22.44** 0.79 21.01

†

Canonical coefficients are similar to regression coefficients but have slightly different properties due to their optimization to fit environmental axes to response data, in contrast to regression coefficients, which are derived from response data only (Ter Braak, 1987). ‡ Because of the larger variances associated with canonical coefficients compared with regression coefficients Student’s t-test can only be applied as a general guide. Approximate critical values for a t-test at P $ 0.05 (*) and P $ 0.01 (**) are c. 2.1 and 2.9 respectively (Ter Braak and Looman, 1987).

the considerable variation in site potential for beech growth The other observation of primary importance is the natural coexistence of Norway spruce and silver fir in apparently complementary niches. It would appear that the presence of both conifer species may be equally important for the continuing production and for the conservation of this area. Acknowledgements The authors acknowledge ROMSILVA RA Bucuresti for the funds kindly provided in partial support of this investigation under Romsilva Contract No 9/1995.

References Armasescu, S. 1971 Consideratii la cunoasterea caracteristicilor auxologice ale arboretelor amestecate. Revista pãdurilor No 8. Bucuresti, 411–414. Badea, L., Gastescu, P., Velcea, V., Bogdan, O., Donisa, J., Dragomirescu, S. et al. 1983 Geografia României, Vol. I. Editura Academiei R.S.R., Bucuresti. Brega, P. 1986 Regenerarea naturala a fagetelor, bradetelor si amestecurilor de rasinoase cu fag din nordul tarii. Editura Ceres, Bucuresti. Chirita, C., Vlad, I., Paunescu, C., Patrascoiu, N., Rosu, C. and Iancu, I. 1977 Statiuni forestiere. Editura Academiei R.S.R., Bucuresti. Corsten, L.C.A. and Gabriel, K.R. 1976 Graphical exploration in comparing variance matrices. Biometrics 39(2), 159–168. Decei, I. 1986 Cercetãri privind determinarea indicilor de productie si productivitate a arboretelor amestecate de

rãsinoase cu fag în vederea stabilirii compozitiilor optime. MS, ICAS, Seria a II-a, Bucuresti. Florescu, G., Negrutiu, F. and Abrudan, I.V. 1995 Cercetari privind particularitatile structurale ale amestecurilor de rasinoase cu fag din nord-vestul Muntilor Apuseni. Romsilva Contract No 9/1995. Universitatea Transilvania din Brasov. Florescu, I.I., Nicolescu, N., Abrudan, I. and Eremia, M. 1996 Fundamente ecologice si economice privind regenerarea si conducerea arboretelor cu functii multiple din zona montana a Brasovului. MI Contract No 5005/1996. Universitatea Transilvania Brasov. Geambasu, N. 1995 Unele aspecte teoretice privind reconstructia ecologica a ecosistemelor forestiere deteriorate. In Revista pãdurilor No 4. Bucuresti, 24–29. Innes, J.L. and Whittaker, R.J. 1993 Relationships between the crown condition of Sitka and Norway spruce and the environment in Great Britain: an exploratory analysis. J. Appl. Ecol. 30, 341–360. Kent, M. and Coker, P. 1992 Vegetation description and analysis; a practical approach. John Wiley, Chichester, 363 pp. Marcu, G.H. 1974 Cercetari privind extinderea culturii molidulul in R.S. Romania. Editura Ceres Bucuresti. Mather, R.A., Freer-Smith, P.H. and Savill, P.S. 1995 Analysis of the changes in Forest Condition in Britain 1989 to 1992. Forestry Commission Bulletin No 116. HMSO, London. 53pp. Negulescu, E.G., Stanescu, V., Florescu, I. and Tarziu, D. 1973 Silviculturã. Fundamente teoretice si aplicative. Editura Ceres Bucuresti. Savill, P.S. 1991 The silviculture of trees used in British Forestry. CAB International, Wallingford, 143pp.

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Stanescu, V. 1979 Dendrologie. Editura didacticã si pedagogicã, Bucuresti. Tarziu, D. 1993 Pedologie si statiuni forestiere. Editia a II-a. Reprografia Universitãtii ‘Transilvania’ din Brasov. Ter Braak, C.J.F. 1987 Ordination. In Data Analysis in Community and Landscape Ecology. R.H.G. Jongman, C.J.F. ter Braak and O.F.R. van Tongeren (eds). Pudoc, Wageningen, 91–173. Ter Braak, C.J.F. and Looman, C.W.N. 1987 Regression.

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Received 10 October 1997