Vegetatio 72: 95-102, 1987 © Dr W. Junk Publishers, Dordrecht - Printed in the Netherlands 95

Vegetation dynamics in early old field succession: a quantitative approach

Jan Lepg Department o f Biomathematics, Biological Research Centre, Czechoslovak Academy of Sciences, Brani~ovskd 31, 370 05 Cesk~ Budbjovice, Czechoslovakia

Accepted 29.5.1987

Keywords: Numerical classification, Ordination, Spatial heterogeneity, Succession, Transition matrix

Abstract

The vegetation dynamics of the first four years of an old field succession were studied in the Bohemian Karst, Czechoslovakia. The vegetation in a set of permanent 1 m 2 quadrats on a newly abandoned field was analyzed yearly using the point quadrat method. The vegetation was classified both based on dominant species and on floristic data (TWINSPAN). Transition matrices were constructed, evaluated, and an ordination of quadrats provided supplementary information. The following conclusions can be drawn concerning the first four years of the succession: 1. The succession was found to be nearly unidirectional. 2. The rate of succession decreased with time. 3. The floristic composition changed more rapidly than the performance of the dominant species. 4. The influence of species composition in very early stages on further development was weak. 5. Whereas the importance of the small-scale environmental heterogeneity decreased with time, the importance of invasion potential increased.

Nomenclature: F. Ehrendorfer 1973. Liste der Gef/isspflanzen Mitteleuropas. Fischer, Stuttgart.

Introduction

This paper presents the results of part of a larger research project investigating an old-field succession in the Bohemian Karst (Lep~ et al., 1982 and refer- ences therein); the dynamics of the very early succes- sional stages (the first four years after abandon- ment) is investigated in detail. The importance of early stages for further successional development was stressed by Egler (1954). The aim here is to evalu- ate the extent to which the composition of earlier communities influences later successional develop- ment and to understand the role of early spatial het- erogeneity in subsequent within-community differ- entiation. Transition matrices are often used for the

description and modelling of succession (Usher, 1979, 1981; Van Hulst, 1979), despite the fact that their use is based on oversimplified assumptions (Van Dorp et al., 1985; Lep~, 1988).

Methods

Field investigation

The vegetation dynamics of a newly abandoned field, ca 60 × 15 m, was followed for the first four years after abandonment (1979-1982). The study area is located on the tertiary Berounka River ter- races near the village of Srbsko (Bohemian Karst,

96

Central Bohemia, Czechoslovakia) about 50 m above the present level of the Berounka River. In 1978, wheat was cultivated on the field. After har- vesting in 1978, the field was ploughed. In the close vicinity on the terrace, there are two old fields of ca 10 and 50 yr age. The vegetation there and its de- velopment provide an indication of the expected fur- ther successional trend: stage dominated byAgropy- ron repens and Artemisia vulgaris - stage with com- petitive broad-leaved grasses (Arrhenatherum elatius, Dactylis glomerata) - xerophytic grassland dominated by narrow-leaved grasses (Festuca rupi- cola, Poa angustifolia).

The climate is summer-warm and dry (relative to that of Central Europe), with a mean annual temper- ature slightly over 8°C and an average annual precipitation of 530 mm (Beroun Meteorological Station). The natural vegetation is formed by a mo- saic of mainly thermophilous forests dominated by Quercus petraea, Quercus pubescens and Carpinus betulus (Quercion pubescenti-petrae and Carpin- ion) and species-rich steppes, particularly on south- ern rocky slopes on limestone (Festucion valesia- cae).

In total 55 permanent quadrats were located with- in the study area and the cover of all species was de- termined each year by the point quadrat method (Goodall, 1952), 100 pins in a square grid. The cover of species present in the quadrat, but not touched by a pin, was assigned arbitrarily to 0.5%. In the course of four years, a few quadrats were accidentally de- stroyed and new ones were layed down to replace them. The coordinates of all quadrats were noted in a Carthesian x,y system; a slight slope (about 2 °) in the direction of the x axis (the longer one) caused a slight topographical gradient, and the configuration of neighbouring plant communities provided a probable invasion gradient in the direction of the y axis. In the direction of the y axis, the fields were ranked: a cultivated field, our old field, permanent grassland. Consequently, the species of the perma- nent grassland penetrated into the field in the direc- tion of the y axis. Forty quadrats were located ran- domly in the lower part and 15 in the upper part of the field.

Construction of transition matrices

First, two classifications were made of all quadrats in all of the years. In the first the classes were based simply on the species with the highest cover, to be called 'dominants' in this paper. In the second, TWINSPAN (Hill, 1979a) using standard default values was used to generate a floristic classification. Eight groups in this hierarchical classification (i.e. after 3 levels of divisions) were adopted on the basis of the interpretability of the results.

The classifications were mutually compared using the X coefficient of Goodman & Kruskal (1954). The

same coefficient was used to evaluate the relation- ship between vegetation types and years.

The matrices were constructed and evaluated for transitions between particular pairs of years and for transitions between all pairs of years pooled togeth- er. The null hypothesis of statistical independence of subsequent stages was tested using the 2 log X test (Anderson & Goodman, 1957). Categories with low frequencies were lumped. In the same way, the inde- pendence of 1st and 4th year vegetation was tested. The matrices of transition probabilities were con- structed again for each year-to-year transition and for pooled transitions for the whole period. The probabilities were estimated in the ordinary way, i.e.

Pid = Trij(t;t + 1)/Ni(t), (1) where Pij is the probability of transition from the state i to the state j, Trij (t;t + 1) is the number o f transitions from i to j during (t;t + 1) and Ni(t) is the number of quadrats in state i at time t. When N i was < 5 classes were lumped to permit an estimation of Pij. Each year new classes, previously not pres- ent, appeared. For construction and evaluation of the matrix of transition probabilities, the newly ap- pearing classes were pooled into one category, 'new- ly observed', and probabilities were arbitrarily as- signed Pij = 1 and P U = O for i ~ j. This is allowed since there were no cases of transition from a newly- observed class to any previous one. The rate of suc- cession was expressed using 1/I X21 (Usher, 1979), where X2 is the eigenvalue of the matrix P with the second largest absolute value (the largest eigenvalue always equals one).

Ord ina t i on

The quadrats were further subjected to DCA ordina- tion, using the D E C O R A N A program (Hill, 1979b). At first, all quadrats from all years were treated to- gether and the trajectory of quadrats in the ordina- tion space was followed. Subsequently, data from each year was ordinated separately. The length of the first axis might be considered as a rough measure of the within plot differentiation (~-diversity). The spa- tial gradient within the plot was investigated using the regression of the quadrat score on the first DCA axis (DCA1) on quadrat coordinates in real space, thus

D C A 1 = ax + by + c, (2) where x and y are coordinates and a, b and c are regression coefficients. The ratio b / a is then the direction of the gradient in real space determined by the x,y coordinates. Stepwise linear regression of D C A 1 on all the previous states (expressed as D C A 1) and on the location in space was used to determine possible predictors of the vegetation state.

Results

In all, 26 species were found to be dominants (i.e. to provide the highest cover in anyone quadrat); most of them, however, were dominant in very few quad- rats. The least frequent dominants were pooled into biological groups (annuals, biennials, perennials), and their frequency in particular years is given in Ta- ble 1. The floristic classification is characterized by a synoptical table of the eight clusters included (Ta- ble 2). Table 3 presents the frequency of the eight vegetation types in particular years. The similarity of the dominance and floristic classifications is low (~, = 0.47). The floristic classification corresponds better to particular years (X = 0.69) than the classifi- cation based on dominants (~, = 0.49). Using transi- tions between dominants, the hypothesis of statisti- cal independence of subsequent stages was rejected for transitions between year 1 and 2 ( P < 0.05) and between year 3 and 4 (P < 0.01). Using the floristically defined types, the null hypothesis was rejected in all three cases (P<0.01, P < 0 . 0 5 and P<0.01 , respec-

• tively). The pooled matrix was highly non-random in both cases ( P < <0.01). When using the matrix

97

Table 1. F r e q u e n c y % o f d o m i n a n t s in p a r t i c u l a r yea r s .

D o m i n a n t

s p e c i e s / g r o u p

Yea r s

1 2 3 4

Papaver rhoeas 83 13 0 0

O t h e r a n n u a l s + 11 13 5 0

Galium aparine 4 55 5 0

Biennia l s + + 0 10 21 2

Brom us sterilis 0 0 6 12 Artemisia vulgaris 0 4 42 53

Achillea millefolium 0 0 11 20

O t h e r

pe renn ia l s + + + 2 5 10 13

+ Aethusa cynapium, Atriplex patula, Avena fatua, Bromus mollis, Chenopodium album, Fallopia convolvulus, Lapsana

communis, Medicago lupulina, Polygonum aviculare a n d Stel- laria media. + + Daucus carota, Lactuca serriola a n d Melilotus officinalis. + + + Agropyron repens, Cichorium intybus, Fragaria viridis, Glechoma hederacea, Poa angustifolia, Taraxacum officinale a n d Trifolium pratense.

Table 2. S y n o p t i c a l t ab l e o f the e ight c lus ters o b t a i n e d b y

T W I N S P A N . N u m b e r s i nd i ca t e the p e r c e n t a g e s o f s amp le s wi th

the species in p a r t i c u l a r c lus te rs . O n l y 19 m a j o r species ( f r o m a

to ta l o f 129) a re i nc luded .

C lu s t e r n r

1 2 3 4 5 6 7 8

Veronica agrestis 82 68 3 - 10 -

Fumaria officinalis 90 12 7 - - -

Lamium amplex- icaule 70 25 1 - - -

Silene noetiflora 56 75 60 50 13 10 2 25

Papaver rhoeas 100 81 98 77 60 26 10 -

Anagallis arvensis 100 87 74 50 20 16 2 -

Viola arvensis 90 37 86 83 40 24 7 25

Sonchus oleraceus 19 12 96 77 13 14 12

Medicago lupulina 80 12 94 66 53 16 10 -

Galium aparine 80 93 98 100 93 62 17 25

Fallopia convolvu- lus 92 87 96 94 93 76 41 37

Polygonum aviculare 41 68 72 88 86 52 5 12

Lapsana communis 58 25 60 61 60 32 28 37

Lactuca serriola - 6 19 77 66 26 12 12

Daucus carota 7 12 52 94 93 90 66 50

Artemisia vulgaris 14 6 68 88 86 100 97 100

Taraxacum officinale 4 6 64 88 86 94 97 100

Achillea millefolium 4 6 37 72 73 96 92 87

Agropyron repens 4 6 1 11 - 14 17 100

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Table 3. Frequency o7o of floristically defined types (see Table 2)

in particular years.

Type Year

1 2 3 4

1 73 2 0 0

2 27 2 0 0

3 0 83 2 0

4 0 11 18 0

5 0 0 22 2

6 0 0 53 30 7 0 0 2 63

8 0 2 5 5

based on the pooled transitions, a positive result of the test is caused simply by the fact that the whole plot is occupied by a relatively uniform plant cover, which changes considerably from year to year. Using the matrices for single year-to-year transitions, a positive result implies some statistical dependence of subsequent stages. However, it may not be taken as unambiguous evidence for the active influence of earlier stages on the latter ones, since it might be caused by the concordant response of subsequent species, or groups of species, to variation in the en- vironment. This is roughly analogous to 'passive as- sociation' (sensu Pielou, 1969). This seems to be the case of transition between year 1 and 2. The active influence might act either through environmental modification or directly on the species themselves. Communit ies of perennial plants are conservative; they remain in the same place for successive years and, consequently, the probability of remaining in the same place is then much higher than that expect- ed under an assumption of statistical independence, as in the transition between year 3 and 4. Testing the independence between year 1 and 4, the null hypothesis may not be rejected using the matrix based on dominants. The floristic matrix indicates weak dependence (P<0.05).

The rates of succession expressed as 1/I~, 2 I (Ta- ble 4) indicate a considerable decrease of the rate of succession with the successional age when defined in terms of the dominant species. Based on floristic data, the decrease appears in the last transition. The decrease is obviously caused by the increase of life-

Table 4. Eigenvalue quotients, 1/I~k 2 1, for year-to-year transi-

tion matrices.

Year floristic dominant

data species data

1 - 2 33.3 1.56

2 - 3 50.0 1.17

3 - 4 3.3 1.02

cycle times of constituent species, and is in accor- dance with successional theory. The rates of change are smaller for matrices based on dominant species (Table 5) than for those based on the floristic data (Table 6) (Both classifications used 8 groups).

In the floristic transition matrix (Table 6), the communities may be ordered in such a way that all of the sub-diagonal elements (i.e. Pij where i>j) are zero. This means that all the transitions are strictly unidirectional. The high values of Pij are concen- trated either on or immediately above the diagonal, indicating, that the successional sequences are or- dered and stepwise. In terms of dominant species, the changes are not strictly unidirectional, although most sub-diagonal terms are zero (Table 5). Hence, the succession of community types is considerably

Table 5. Transition matrix based on dominant species for the whole period. Groups as in Table 1.

From To dominant species/group

dominant

species/group Pap Ann Gal Bie Bro Art Ach Per

Papaver

rhoeas 0.13 0.15 0.51 0.02 0

Other

annuals 0.05 0.16 0 0.21 0.05 Galium

aparine 0 0.09 0.06 0.24 0.06

Biennials 0 0 0 0 0.15 Bromus

sterilis 0 0 0 0 1.0

A rtemisia

vulgaris 0 0 0 0.04 0.04

A chillea

millefolium 0 0 0 0 0

Other perennials 0 0 0 0 0.13

0.13 0.02 0.04

0.37 0.11 0.05

0.34 0.15 0.06 0.54 0.23 0.08

0 0 0

0.84 0.04 0.04

0 0.86 0.14

0.13 0 0.74

Table 6. Transition matrix based on the floristic classification

(Table 2) for the whole period.

From To type

type 1 2 3 4 5 6 7 8

1 0.02 0.02 0.92 0.02 0 0.02 0 0

2 0 0 0.50 0.42 0.08 0 0 0

3 0 0 0.02 0.21 0.28 0.45 0.02 0.02

4 0 0 0 0 0.06 0.50 0.38 0.06

5 0 0 0 0 0 0.29 0.71 0

6 0 0 0 0 0 0.30 0.70 0

7 0 0 0 0 0 0 1.0 0 8 0 0 0 0 0 0 0 1.0

more deterministic when defined in terms of floristic data than in terms of dominant species.

The result of the DCA ordination of all quadrats in all years suggests directional changes of vegeta- tion in the course of four years (Fig. 1). The main features of each separate ordination are given in Ta- ble 7. Both the coefficient of determination (R 2) of DCA1 in relation to real space and the direction of the compositional gradient in the real space change dramatically. The coefficient of determination is

DCA 4-

'3

3

2

1

DCA I

Fig. 1. Polygons defined by the first two axes of detrended cor-

respondence analysis (heavy lines). Each polygon contains all

points from one particular year. Individual points are omitted for clarity (similarly as in Usher & Booth, 1984). For illustration,

trajectories of five randomly selected quadrats are shown (light lines). The cross indicates a single outlier from the third year.

99

Table 7. Length of the first ordination axis, D C A 1 (in 'standard

deviation' units; see Hill 1979b for details), coefficient of deter-

mination (R 2) of regression of DCA1 on coordinates in real

space, and direction of gradient in degrees. 0 ° means gradient in

direction of x axis, 90 ° in direction of y axis.

Year Length of R 2 direction

D C A 1 axis

1 2.50 0.76 - 3

2 3.76 0.18 - 10

3 3.42 0.12 86

4 1.85 0.28 84

large in the first year when the gradient is in the direc- tion of the x-axis, and it is particularly small in the third year (although the regression is still significant, P < 0.05). In the last two years, the gradient is in the direction of the y-axis. This suggests that the very slight environmental gradient played an important role only in the first year or two. Our field observa- tions suggest that even very small differences in soil texture and moisture caused differences in the time of seed germination, which itself affects competi- tion between annual species. In the third and fourth year, the importance of invasion from neighbouring communities increased.

Stepwise multiple linear regression was used to select the predictors of the present state of vegetation (expressed by DCAI). Predictors were selected from all previous states of the quadrats (i.e. their DCA 1 scores) and from quadrat coordinates in real space. Predictors selected and values of R 2 are listed in Ta- ble 8. The results suggest that the dependence be- tween subsequent stages increases with time.

Table 8. Predictors of the state of vegetation (expressed by a

quadrat 's score on D C A 1) selected by the stepwise multiple linear

regression and corresponding coefficient of determination (R2).

x and y are coordinates in real space, the number correspond to years of D C A 1.

Year predictors R 2

1 x 0.76 2 x 0.18

3 2, y 0.37

4 3, y 0.68

100

Discussion

Matrix models are often used for modell!ng ecologi- cal succession (Usher, 1979, 1981; Van Hulst, 1979; Lep~, 1988). They have not been used here as predic- tive tools since new species and new vegetation types appeared each year. It is hardly possible to predict the composition of vegetation in future. The conclu- sion that the plot will be occupied by new species and vegetation types is essentially correct, but uninfor- mative. This old field succession is very rapid be- cause the vegetation types were nearly completely replaced by others within three years. This rate is considerably faster than that reported by Hobbs (1983) for heathland communities. Consequently, because the power of the tests would be extremely low, it is inappropriate to test assumptions of tem- poral homogeneity or of the Markovian property.

The assumption of independence of subsequent stages was rejected in most cases, as was done by Usher (1979) when examining a number of matrices from the literature. However, the association was weak in the first two transitions, but it increased con- siderably in the transition from the 3rd to the 4th year.

Usher (1979, 1981) suggested that the transition matrix could provide information on the type of suc- cessional mechanisms, i.e. discriminate between the facilitation, tolerance and inhibition models of Con- nell & Slatyer (1977), and he noted the possible difficulties with the definition of states, vegetation types, etc. Correspondingly, our study shows the striking differences between matrices based on differently defined types. Despite these differences, both our matrices (Tables 5 and 6) correspond roughly to the matrix indicating the facilitation model. However, we have found no features of pav- ing the way by earlier stages for the later stages. On the contrary, it seems that the main mechanism in our case is the outcompeting of weeds (mostly annu- als) by perennials. In the transition matrix for dominants, we find large diagonal values for the perennials and small ones for the annuals. The large transition probabilities are for P a p a v e r rhoeas --

G a l i u m aparine, annuals -- A r t e m i s i a vulgaris,

G a l i u m apar ine -- A r t e m i s i a vulgaris, and biennials -- A r t e m i s i a vulgaris. It seems that the mechanisms

for these changes may not be reliably distinguished on the basis of the final effect (as reflected by the transition matrix), but on the basis of manipulative experiments (Schmidt, 1983; Armesto & Pickett, 1986) or roughly estimated using supplementary in- formation about life history strategies of species themselves. The fact that the vegetation types may be ordered in such a way that all the sub-diagonal elements are zeros reflects only the fact that the suc- cession is strictly unidirectional. Again, the direc- tionality of succession depends on the definition of vegetation type and on the type and area of the sam- ples that were used. For example, comparing our ma- trices with those presented by Hobbs & Legg (1983) and Lippe et al. (1985) from a heatland, our matrices are more unidirectional. It is partially caused by the fact that the old field succession in the very early stages is more directional than that in heathlands. However, differences in the sampling technique have to be considered. Hobbs & Legg (1983) used 10 z 10 cm squares and Lippe et al. (1985) used sin- gle points as sampling units, whereas we used 1 m 2 samples (consisting of 100 points). The changes on larger plots may be considered as the sum of changes on smaller plots. Consequently, purely statistically, it could be expected that the larger plots would be

more deterministic than the smaller ones. The ap- parently stable composition of plant communities on larger plots, resulting from the dynamic changes on smaller plots, has been reported both from forest and grassland stands, e.g. by Shugart (1984) and Hroudov~i & Prach (1986).

The eigenvalue ratio 1/1~21 is used as a relative measure of the rate of succession, or the rate of con- vergence to a steady state. Its value depends obvious- ly on the time step used; however, the ratio may be easily adjusted to a 1-year step (Lippe et al., 1985). Obviously, this value depends also on the definition of vegetation types and on the area of the sample plot. Hence, comparison even with I-year adjusted ratios given for various successional matrices from the literature by Lippe et al. (1985) is very difficult. The differences in order of magnitude between plant and animal successions correspond to differences in their life cycle duration; similarly, grassland succes- sion is more rapid than forest succession.

The differences caused by the use of various sam-

pie p lo t s sugges t t ha t t he succes s ion m u s t be c o n s i d -

e red as t he d y n a m i c s o f a s t r u c t u r e d h i e ra rch ica l sys-

t e m (Al l en & Starr , 1982). T h e r e are several scales o f

p a t t e r n in v e g e t a t i o n (e.g. G r e i g - S m i t h , 1981). W h e n

we c o n s i d e r succes s ion as a s e q u e n t i a l r e p l a c e m e n t

o f v e g e t a t i o n types , t h e n the c o n c l u s i o n s have to be

re la ted to t he scale o n w h i c h the v e g e t a t i o n types are

de f ined . T h e i m p o r t a n c e o f scale in t he s tudy o f

v e g e t a t i o n p rocesses was s t ressed by b o t h A l i e n &

S ta r r (1982) a n d M i r k i n (1985). T h e f o l l o w i n g c o n -

c lus ions have to be c o n s i d e r e d wi th respec t to all o f

t hese res t r ic t ions .

T h e success ion was f o u n d to be n e a r l y un id i r ec -

t iona l . T h e ra te o f success ion d e c r e a s e d wi th t i m e as

t he l ife cycle d u r a t i o n o f c o n s t i t u e n t species in-

creases. T h e f lo r i s t i c c o m p o s i t i o n c h a n g e s m o r e

r ap id ly t h a n t h a t o f d o m i n a n t species. T h e i n f l u e n c e

o f sma l l scale e n v i r o n m e n t a l h e t e r o g e n e i t y

dec reased d u r i n g the f irs t f o u r years. S i m i l a r resul ts

were p re sen t ed by S te r l ing et al. (1984), i n d i c a t i n g a

dec rease in t h e i m p o r t a n c e o f m i c r o t o p o g r a p h y . In

c o n c o r d a n c e wi th the i r results , t he d i f f e r e n t i a t i o n

b e t w e e n p a r t i c u l a r o ld - f i e ld s in t he B o h e m i a n Kars t

( h ighe r scale o f pa t t e rn ) increases wi th t i m e d u e to

t he d i f f e r en t i a l a p p e a r a n c e o f sh rubs w h i c h is relat-

ed to d i f f e rences in t he d e p t h o f soi l (P rach , 1981;

Lep~ & P r a c h , 1981; K l a u d i s o v ~ & Lep~, in prep.) .

C o n s i d e r i n g the w i t h i n - f i e l d d i f f e r e n t i a t i o n , t he in-

f l uence o f t he ea r ly v e g e t a t i o n c o m p o s i t i o n on fur-

t he r d e v e l o p m e n t o f t he p l an t c o m m u n i t y was rela-

t ive ly weak.

Acknowledgements

I t h a n k Drs M. B. Usher , M. B. Dale , M. S t r a~kraba

a n d two a n o n y m o u s reviewers fo r c r i t i ca l ly review-

ing the m a n u s c r i p t a n d fo r l inguis t ic help, J.

Lehovcov~i-Bla2kov~i fo r f ie ld ass i s tance a n d D.

Susterov~i for typ ing .

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