Folia Geobotanica 33: 77-86, 1998

RELATING VARIATION IN THE UNDERSTOREY OF BEECH FORESTS TO ECOLOGICAL FACTORS

Jos6 Miguel Olano 1.), Javier Loidi 1), Gonz~ilez Ander 1) & Adri~in Escudero 2)

1) Dpto. Biologfa Vegetal y Ecologfa, Universidad del Pals Vasco, Leioa, Apdo 644, E-48080 Bilbao, Spain; *)fax +34 4 4648500, E-mail gvbolmej@lg.ehu.es

2) Dpto. Biologfa Vegetal, Univ. Polit~cnica de Madrid, E.U.LT. Agrfcola, E-28040 Madrid, Spain

Keywords: Beech forests, Community analysis, DCA, Fagus sylvatica, Kriging, Northern Spain, Understorey composition

Abstract: A data set of beech (Fagus sylvatica) forests in the Basque Country (Northern Spain), including biotic (floristic relev6s) and environmental data (pH, organic matter, slope, altitude, rock cover), is analyzed in order to describe the relationships between understorey composition and environmental parameters. An ordination technique (DCA) is used to display the floristic gradients, and the interpretation of the floristic space in environmental terms is carried out by a spatial analysis technique (kriging).

The composition of the beech forest understorey responds to a complex environmental'gradient in the study area. Forests growing on acid substrata differ markedly from those growing on soils with higher pH, as the sharp transition between the pH 5 and 6 isolines reflects. When pH values exceed 6, organic matter content becomes the most important factor explaining the vegetation pattern and the rate of change is greater as organic matter content tends to change at a smaller scale than sample size and, as a consequence many transitional forms are found.

INTRODUCTION

Beech (Fagus sylvatica) forests are widely distributed in the Basque Country and neighbouring areas, mainly in the montane belt (LOIDI 1987). These mature forests occur over a wide range of environmental conditions, including a wide variety of substrata (HUNTLEY 1988, CEBALLOS & RU~Z DE LA TORRE 1979, POTT & Ht3PPE 1991) forming very extensive, almost monospecific stands. The occurrence of beech in the area is closely correlated to summer rainfall (ORTtrBAI 1995); thus beech forests appear in areas above 600 m where summer rainfall is always above 170 mm, while oak forests (Quercus robur) and mixed hardwood forests are basically the mature forests of the colline belt (RIVAS-MARTtNEZ 1987).

Although the canopy is almost monospecific throughout the wide range of situations where beech forests are found, understorey composition is rather complex, Ground vegetation usually occurs over narrower ranges than arboreal species with respect to nutrient gradients and other soil factors (PASTOR et al. 1984), so that ground vegetation data has been extensively used as a predictor of soil conditions (PREGITZER & BARNES 1982, HUEBNER et al. 1995, SMITH 1995). The understorey composition shows relationships with environmental factors, mainly with those related to the availability of resources (GRIME 1979), but low intensity disturbance (PtCKETT& WHITE 1985, VAN DER MAAREL 1993), including small gaps, fires, recreational use or grazing, can also strongly influence its composition.

78 J.M. Olano

The high floristic variation of understorey composition may well be responsible for the large number of published papers and associations distinguished by both classical phytosociological approach (DmRSCHI~E 1990, P~aW~-CARRO & DiAZ-GONZALEZ 1987, RrVAS-MARTINEZ et al. 1991) and numerical approaches (FEoLI & LAGONEGRO 1982, TOROK et al. 1989, HArd3S 1994). Consequently, ecological ranges of the newly proposed syntaxa are often difficult to identify.

This paper evaluates the influence of some environmental factors on understorey composition in beech forests and discusses whether these factors are sufficient to explain the variation and whether they can be used to assess site conditions within beech forests. A methodological framework based on ordination techniques and combined with spatial analysis techniques was employed in order to overcome the problems related to the interpretation of long ordination gradients. Nomenclature of taxa follows: TUTIN et. al. (1964-1980).

METHODS

Study area

Research was carried out on beech forests on the eastern Cantabrian fringe of the Iberian Peninsula (Fig. 1), located between 600-1500 m a.s.l., with an average rainfall regime between 1000-1500 nun. Sampling sites were located in the montane belt in the Cantabrian-Basque sector in the provinces of Ala~,a and Navarra (Spain) (biogeographical and bioclimatological terms following RrVAS-MARTiNEZ 1987).

Data collection

168 sample plots were used, covering every geomorphological and lithological type (limestone, sandstone and marl). Tree stratum cover was always close to 100%. To avoid successional interferences, sites which had not been recently disturbed were selected. They were separated by a minimum of 1000 m or an altitude variation of more than 100 m. Sample plots were circular with an area of 400 m 2. Field work was carried out between May and July (1990 and 1991), so that both spring geophytes and summer plants were fully developed.

The percentage canopy cover of every vascular plant was estimated. Altitude was measured by an altimeter, slope by a clinometer (Suunto PM4-1400PC) and stone cover, was estimated visually. In a subsample of 134 randomly selected relev6s three soil cores per relev6 were randomly collected (0-10 cm depth) and mixed before analysis to reduce soil heterogeneity (PALMER 8z DIXON 1990, ZHANG 1992). Organic matter was estimated by the Walky method (HESSE 1971) and pH was measured in a soil-water mixture (CHAPMAN & PRATT 1961). As organic matter distribution was far from normal, data were log-transformed.

Data analysis

Floristic data were submitted to ordination techniques. Species data were subjected to presence/absence transformation because this transformation is useful to focus on the species range (FISCHER & BEMMERLEIN 1989). Computations were performed with CANOCO 3.11 (TER BRAAK 1988) and CanoDraw (SMILAUER 1992) programs.

Data were submitted to a CA in order to estimate gradient length (TER BRAAK 1987). As gradient length was over 5 standard deviations, a unimodal response model technique was

Beech forest understorey and ecological factors 79

Gulf of Biscay

J

Vl~rla

4J~

Gulf of Biscay

I Iru6a

Fig. 1. Location of sampling area.

selected. In order to reduce arch effect DCA with detrending by fourth order polynomial was employed as recommended by TER BRAAK & PRENTICE (1988).

Two different techniques were used to relate ordination patterns to environmental variables: (a) non-parametric relations (Spearman rank correlation) between the first two ordination axes and the variables, and (b) spatial analysis on the ordination planes. Within the different techniques for spatial analysis (BURROUGH 1987, LEGENDRE &

FORTIN 1989), kriging was prefered to trend surface analysis (TSA) because it is an exact interpolator in known points and it is not necessary to build a global model. A

variogram with a linear model was used to calculate the surfaces, using the 15 nearest neighbours. Computations were done with SURFER package (ANONYMOUS 1993). A number of papers have used this procedure as a second step to interpret ordination results (e.g., MCDONALD & WATERS 1989, MUCINA 1989, HAUSER & MUCINA 1993, BURGAZ et al. 1994). As soil data were only collected for a subsample (n= 134), non-parametric and spatial-analysis for soil related factors are only referred to this group of sample plots. Relev6s without soil data are also included in spatial analysis graphics.

R E S U L T S

A total of 263 vascular plants were found in the understorey of beech forests, the mean number per relev6 was 20 and ground-cover was always very low (average 10%).

Ordinat ion

DCA eigenvalues for the first two axes were 0.39 and 0.32. These values suggest a good dispersion of data along the axes (TER BRAAK 1987). Total inertia is 6.07, the percentage explained by the axis is low due to the presence/absence transformation and the high number of species involved. However, scattergrams are easily interpretable in ecological terms. Sample scattergram (stars in Fig. 3) shows a clear V-shaped distribution with a high density of points in the origin area and two branches extending through the positive sides of the axes. The pattern for species (Fig. 2) is very similar.

The first axis discriminates a group of acidophytic species on the positive part (such as Carex pilulifera, Blechnum spicant, Vaccinium myrtillus). Those species related to rocky and

80 J.M. Olano

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Mercpere fibul~nt AHedehell Clemvltat~ t~ - ASorbaria

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Fig. 2. DCA ordination of the species, presence/absence transformation and detrending by fourth order polynomial. Species names: Anemnemo, Anemone nemorosa; Anthodor, Anthoxantum odoratum; Aquivulg, Aquilegia vulgar|s; ArabalPi, Arabis alp|ha; Arabhirs, Arabis hirsuta; Arrhelat, Arrhenatherum elatius; Arummacu, Arum maculatum; Aspltric, Asplenium trichomanes; Athyfili, Athyrium filix-femina; Blecspic, Blechnum spicant; Bromramo, Bromus ramosus; Cardflex, Cardamine flexuosa; Cardhirs, Cardamine hirsuta; Careflac, Carex flacca; Carepilu, Carex pilulifera; Cephlong, Cephalantera longifolia; Clemvita, Clematis vitalba; Cornsang, Comus sanguinea; Coryavel, Corylus avellana; Crocnudi, Crocus nudiflorus; Crucglab, Cruciata glabra; Dryoaffi, Dryopteris affinis; Epiphell, Epipactis helleborine; Ericvaga, Erica vagans; Galiapar, Galium aparine; Geraluci, Geranium lucidum; Hedeheli, Hedera helix; HeUfoet, HeUeborus foetidus; Hiermuro, Hieracium murorum; Isopthal, Isopyrum thalictroides; Lacthclan, Lathraea clandestina; Lathlini, Lathyrus linifolius; Loniperi, Lonicera periclymenum; Luzumuit, Luzula multiflora; Melimeli, Melinis melisophyllum; Mercpere, Mercurialis perennis; Micemura, Mycelis mural|s; Phytspic, Phyteuma spicatum; Polyvulg, Polypodium vulgare; Pulmlong, Pulmonaria longifolia; Ranutube, Ranunculus tuberosus; Rubipere, Rubia peregrina, Silevulg, Silene vulgar|s; Sorbaria, Sorbus aria; Taraoffi, Taraxacum gr. officinalis; Urtidioi, Urtica dioica; Vaccmyrt, Vaccinium myrtillus; Verocham, Veronica chamaedrys; Verooffi, Veronica officinalis; Vibulant, Viburnum lantana; Vinchiru, Vincetoxicum hirundinaria.

mobile stony substrata (such as Silene vulgar|s, Phyteuma spicatum, Vincetoxicum hirundinaria) appear on the positive side of the second axis. The species core displays a more complex gradient. Within the core, in the lower part of the ordination plane, species related to moist habitats (such as Cardamine flexuosa, Ranunculus ficaria) appear simultaneously

Beech forest understorey and ecological factors 81

with other species characteristic of soils rich in nutrients (factor associated with high organic matter content) (Galium aparine, Urtica dioica, etc.).

As can be seen in Tab. 1, the first extracted axis is negatively related to pH, organic matter, altitude and surface covered by rock. The second axis is negatively correlated to altitude and positively with slope.

Kriging

Kriging analysis on the ordination plane shows a clear pattern for pH (Fig. 3). This variable increases gradually from right to left, with a range between 4 and 7 pH units and a bigger rate of change between 5 and 6 (Fig. 4).

Organic matter content (Fig. 5) shows a fluctuating pattern on the right side of the ordination; however, it shows a very clear gradient in the other half of the ordination, increasing gradually to the left (highest concentration values). This gradient is particularly clear as pH value increases from 5 to 6.

Altitude shows a complex pattern with several maxima. Slope has a maximum in the positive half of the second axis and a minimum in the negative half. Surfaces covered by stones show a clear maximum in the negative half of the first axis, with an optimum corresponding to scree in the upper part and high values corresponding to karstic surfaces in the lower part.

DISCUSSION

Ecological

Spearman correlation and kriging results indicate that pH is the prime factor controlling understorey composition in beech forests. A clear gradient, ranging between 4 and 7, can be detected, with a sharp step located between 5 and 6. This abrupt change can be easily related to marked floristic differences and acidophytic species are almost absent from the rest of the stands. This floristic boundary has been traditionally used to distinguish different types of beech forests, even in syntaxonomical terms (WALLNIJFER et al. 1993). Similar understorey patterns have been described in other forest communities with a monospecific canopy composition, for example in Pinus sylvestris (PAUSAS & CARRERAS 1995), Quercus rotundifolia (EsCUDERO et al. 1996), and also in shrub communities (LOIDI et al. 1994).

The left part of the DCA ordination diagram is related to soil development and higher organic matter content, showing a steeper floristic gradient than pH in this zone. Although

the clumped distribution of the central area Table 1. Summary of Spearman rank correlation of environmental variables with DCA-axes 1 and 2. ** - significant at P < 0.01, * - signific~t at P < 0.05. n= 134 for pH and organic matter content, n=168 for altitude, rock cover and slope.

Axis 1 Axis 2

pH -0.582** -0.176 log (organic matter) -0.500** -0.142 Altitude -0.392** -0.390** Rock cover -0.603** 0.026 Slope -0.077 0.245*

could mean a very similar floristic composition, they show varied behaviour both in floristic and environmental terms (Fig. 2). The separation between the relev6s located on acid soils and the other relev6s reflects the way environmental factors are arranged in space. Soil pH in the study area is mainly related to lithological factors (sandstone), which act on a much larger scale than the relev6 size, so that boundaries between these communities are very clear

82 J.M. Olano

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Fig. 3. Kriged values for pH along first two axes, standard deviation of residuals 0.57 pH units. Stars represent relev6s.

7.O0

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Fig. 4. Section of pH kriged surfaces in the first axis, showing the abrupt change between 5 and 6 pH units.

Beech forest understorey and ecological factors 83

,9. ! -0.20 0.60 0.65

I I I I I |

:/

r~I'O ' *-.t, . ( / � 9

1 I * I t I I -0,10 0,00 0.10 0,20 0.30 0,40 0,50

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Fig. 5. Kriged values for organic matter content values (log of parts per thousand) along the two first axes, standard deviation of residuals 0.3760. Stars represent relev6s.

(Fig. 4). On the other hand, surfaces covered by rock and organic matter respond to processes related to limestone, with physico-chemical decomposition occurring on a much smaller scale (metres-centimetres), creating a heterogeneous environment for plants in the same relev6. For this reason relev6s included in the central region display much more complex trends.

The surface covered by rock increases towards the negative side of the first axis with maxima on the upper and lower part of this axis; the first corresponds to forest over screes and the second to forests over karstic surfaces.

Despite severe difficulties encountered when understorey composition has been used to assess site conditions and vice versa (LEAK 1982, WHITNEY 1991), these results clearly show the correlation of environmental site-conditions and plant composition in beech forests (see also GODART 1989, HAKES 1994). They must he a consequence of minimizing successional interferences (BARNES et al. 1982, SMITH 1995) and the search for non-disturbed stands. Most of the variables included in this study are highly correlated to both species and sample distribution.

84 J.M. Olano

Methodological comments

Methods based on gradient analysis imply the assumption that the arrangement of relevts in floristic space is a consequence of an inherent environmental gradient, this fact being the conceptual framework for the use of most of these techniques. However, the gradient displayed in the analysis may not be a simple one, but a combination of several environmental factors. Relationships between any floristic gradient and environmental factors can be examined by parametrical (BLASI et al. 1990) or nonparametrical (JOHN & DALE 1990) regression techniques, or even by canonical methods (CA~ETOr~ 1990, SMITH 1995).

When working with long gradients, the factor(s) responsible for the species changes may be substituted along the axes, as some authors (MuCn~A & VAN TONGEREN 1989) have reported. Canonical or regression techniques, although they may show significant relationships, do not always explain data patterns correctly, as the substitution of explanatory variables along the axis may obscure the trends. These techniques may be misleading with regard to variables which can explain trends in a part of the ordination space, being either irrelevant in the global context or having numerical descriptors of low significance which are hard to interpret. It is assumed that this difficulty increases along with the extracted axes. Some authors recommend partitioning the data to allow interpretation (PEET 1980, WILD] 1989), but mechanisms to do these partitions are far from clear (DALE 1988). In an attempt to overcome this problem and to interpret the whole data set together, the different explanatory variables were kriged through ordination space.

This interpolation technique also permits the inclusion in the ordination of relevts in which some data have not been measured, so their values can be estimated, as we have done with the relevts without soil data. In the framework of the European Vegetation Survey (RoDwELL et al. 1997), where many relev~s lack or have poor environmental data, this technique provides a tool to interpret them in an ecological way. It permits us to ordinate all data based on a floristic matrix, and to then interpret ecological relationships based on a representative subsample of relevts containing quality ecological data, using already existing samples or even an ad hoc

Acknowledgements: This work was supported by a FPI predoctoral grant from Spanish Government. Funding from the project GV 118.310-0124/94 of Basque Country University and Basque Country Government has collaborated to finance this work.

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Received 15 May 1997, accepted 24 November 1997