processes change during secondary succession

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1 Journal of Ecology 2004 Gap dynamics in perennial subalpine grasslands: trends and Blackwell Publishing, Ltd. processes change during secondary succession VIGDIS VANDVIK Department of Botany, University of Bergen, Allégaten 41, N-5007 Bergen, Norway Summary 1 Revegetation of gaps may affect the floristic composition of subalpine grasslands during secondary succession. Six hypotheses concerning overall effects, gap-size and edge effects, and changes in these during secondary succession, are tested using principal response curves (PRCs), a recent derivative of partial redundancy analysis. 2 In a field experiment, large (625 cm 2 ) and small (39 cm 2 ) gaps and controls were established in a replicated successional series (0, 10 and 40 years after abandonment). Colonization modes were quantified in year 1, and the floristic composition was monitored twice yearly over four growing seasons. 3 Micro-successions in gaps account for % of the compositional variance. Size effects add % per successional stage, while edge effects appear only in the mid-successional stage (adding 1.6%). Seed colonization rates are comparable with those observed in temperate systems, and the effects on community composition are considerable (initial gap response, size effect). In contrast, changes in local competitive regimes have weaker effects (revegetation dynamics after the first year, edge effects). This may be attributed to the slow growth rates of alpine plants and the short growing season in subalpine climates, as well as to the infertile soils of the semi-natural grasslands. 4 A majority (74%) of the species are affected by gaps, but their responses are not consistent across successional stages. Species that recruit into gaps primarily as seedlings, and locally rare species, become relatively more dependent on gaps for local population persistence during succession. 5 These experiments give insight into the effects of gap revegetation processes for community composition and population persistence in these perennial grasslands. During secondary succession, changes in disturbance regime affect the gap revegetation processes and the probability for local population persistence for gap-enhanced species. Key-words: competition, disturbance, edge effect, gap revegetation, ordination, principal response curves, size effect, secondary succession Journal of Ecology (2004) Ecological Society Introduction The continuous creation, colonization and filling of bare-ground gaps within a closed sward may be seen as series of microsuccessions that are part of the everyday dynamics of a wide range of plant communities, from intertidal algal fields (Anderson 1999) via tropical and temperate forests (Hubbell et al. 1999; Brokaw & Busing 2000) and grasslands (Fowler 1988; Lavorel et al. 1994; Kotanen 1997a) to alpine heaths (Chambers 1995). These communities can be seen as patchworks of Correspondence: Vigdis Vandvik (tel ; fax ; vigdis.vandvik@bot.uib.no). microsites in different stages of revegetation, whose spatial structure and age distribution are determined by the frequencies with which gaps are created in the landscape; the disturbance regime. At the landscape scale, disturbance regimes affect the probabilities for long-term population persistence of species differently, depending on their life histories and ecological attributes, so that the disturbance regime can be seen as an environmental sieve (Zobel 1992, 1997) that excludes a subset of the regional species pool from the local community. As the range of species, or life histories, locally present will restrict the revegetation dynamics of individual gaps within a community (Reader & Buck 1990; Kotanen 1997a), there is a dynamic link between microsuccessions in gaps and

2 87 Gap dynamics in successional subalpine grasslands ecosystem properties such as diversity, long-term stability and successional change. Over the past 50 years, there has been a general trend throughout the developed world for (traditional) extensive low-intensity land use to give way to either high-intensity land use or abandonment (Mannion 2002). The effects are often dramatic, especially in systems with high diversity and long ecological histories (Hobbs & Huenneke 1992; Milchunas & Lauenroth 1993), and the non-continuation of low-intensity land use in semi-natural grasslands has recently been identified as one of the major factors adversely affecting the flora and fauna in Europe (Stanners & Bordeau 1995), including Scandinavia (Bernes 1993; Fremstad & Moen 2001). While the overall secondary successional pathways (grassland to forest or shrub) and the ultimate cause (decreased frequency of fine-scale disturbances resulting from the cessation of land use) are well established, the consequences for ongoing ecological processes within the landscape are less clear. I investigated whether revegetation processes, such as the microsuccessional dynamics and overall community response following fine-scale disturbances in subalpine perennial grasslands, changed along a secondary successional gradient (0, 10 and 40 years after abandonment of land use). One of the potential effects of fine-scale disturbances is to enable niche partitioning between gap and closed-sward species (e.g. Goldberg 1987; Williams 1992; Bullock et al. 1995; Kotanen 1997a; Pakeman et al. 1998). I therefore tested whether species recruited into gaps proportionally to their relative abundance in the closed vegetation, i.e. (hypothesis 1) whether the composition of the vegetation that develops in bare-ground gaps is different from the surrounding grassland. During secondary succession, the density and frequency of bare-ground gaps decrease, partly due to decreased disturbance, but also because relatively short-lived early successional species are replaced by more long-lived species (Prach et al. 1997). The probability for long-term local population persistence of gap-regenerating species should therefore decrease over time as the vegetation becomes taller and denser and an increasing fraction of the total flora will be unlikely to regenerate from seed except in gaps. In other words (hypothesis 2), the overall compositional difference between gaps and closed vegetation should increase, and the gap response of species, life stages and functional types should change, along a successional gradient. With increasing gap size, environmental factors, such as light, moisture, wind and temperature (Thompson et al. 1977; Goldberg & Werner 1983; Kotanen 1997a; Morgan 1997), and competitive effects (Miles 1974; Bullock 2000) become progressively more different between gaps and closed vegetation. A gradient from closed vegetation through small to larger gaps affects both hypotheses. Gaps of different sizes should be filled with different assemblages of species (hypothesis 1a), and if the diversity of gap-regenerating species decreases during secondary succession, then the potential for size differentiation should also decrease (hypothesis 2a). Within large gaps, environmental and competitive effects will also vary along a edge-to-centre gradient. Edge effects are therefore likely to operate so that the centre and periphery should be colonized by different species (hypothesis 1b), and, by analogy to the size effect, the potential for differentiation along the edgeto-centre gradient should decrease during succession (hypothesis 2b). I tested these hypotheses by using a recent development in multivariate ordination, principal response curves (PRCs) (van den Brink & ter Braak 1997, 1998), that is specifically designed for analyses of multivariate responses in BACI (before after, control impact) experiments. I expanded the usage of the methodology by performing series of PRCs not only on the treatment (i.e. gap creation) vs. control, but also on other types of contrasts (large vs. small gap and edge vs. centre positions within large gaps). In order to achieve a more mechanistic understanding of the processes underlying these compositional patterns, I related gap behaviour and successional responses to the regeneration modes, seed or vegetative (Fowler 1981; Milberg 1993; Arnthórsdóttir 1994), and to the community abundances of the species. Methods STUDY AREA In the Norwegian mountains, the total biomass harvested by grazing and mowing decreased by 61% from 1939 to 1996 (Edelmann 1997). The Norwegian suband low-alpine landscapes are currently comprised of patches of formerly grazed or mown vegetation that are in intensive use, as well as some in traditional use, and others in different stages of secondary succession after abandonment (Austrheim & Eriksson 2001; Vandvik & Birks 2002). This study was carried out in the Vangrøftdalen valley, eastern Norway (10 49 E, N) (Fig. 1a). The climate is subalpine, with a July mean temperature of 11.4 C and a growth season (mean temperatures above 5 C) of 5 months ( normal period, and dominant vegetation types are semi-natural subalpine birch forest and extensive mire systems. Summer farms (n = 87) are scattered throughout the valley and range from farms in current use, with free-ranging grazers (mainly cows), to farms abandoned more than 100 years ago. EXPERIMENTAL DESIGN AND SAMPLING The study sites comprise a set of semi-natural grasslands within these summer farms that represent a chronosequence of two replicates each of current use (0 years), abandoned c. 10 years ago, and abandoned c. 40 years ago. Characteristics of the grassland vegetation vary between stages ( Table 1) with bare-ground

3 88 V. Vandvik Table 1 Characteristics of the pre-treatment grassland vegetation at different successional stages calculated from the autumn 1997 census for data set I. Species richness is reported both as means per 625 cm 2 plot and as the total number of species encountered per successional stage Successional stage 0-year 10-year 40-year Vegetation height (cm) 7.7 ± ± ± 2.0 Bare soil (%) 3.5 ± ± ± 2.0 Species richness (625 cm 2 ) 16.1 ± ± ± 2.9 Total number of species Fig. 1 (a) Geographical location of the study area and location of the six subalpine grassland sites, with 0-year experimental sites shown as triangles, 10-year sites as diamonds, and 40-year sites as squares. The area below the forest limit is shaded light grey, and other summer farms indicated by circles. (b) An example of the design within a 4- m 2 experimental block with nine randomly selected areas (gridded) within each. Six were treated as large (25 25 cm) gaps (white) or controls (grey) and frequency in subplot data (data set 1) were used to test for gap effects and changes in such effects during succession. Presence absence data were collected systematically from side, centre and corner subplots within large gaps, and from small ( cm) gap and control subplots at opposite corners of the remaining three areas (marked X, data set II), to test for gap size and edge to centre effects and changes in such effects during succession. gaps primarily found in the grasslands in current use, and range from a few cm 2 (single plants uprooted by grazing) to a few dm 2 (trampling and skid marks). Within the six sites, I investigated regeneration in experimentally created gaps of two different sizes in a 4-year experiment initiated in 1997 in three blocks (2 2 m = 4 m 2 ) at each site. Six large plots (25 cm 25 cm = 625 cm 2 ) and three pairs of small plots (6.25 cm 6.25 cm = 39 cm 2 ) were positioned at random positions within a grid in each block ( Fig. 1b), with the constraint that bare ground (i.e. recent disturbance) was avoided. The corners of the plots (n = 216), were marked with 10-cm metal tubes, to which a cm metal frame, divided into 16 subplots, was attached for the vegetation analyses. Initial censuses were carried out for all species, collecting frequency-insubplot data from large plots, and presence-absence data from small plots. I then created bare-ground gaps from three randomly selected large plots and one from each of the three pairs of small plots within each block by cutting down to 10 cm below ground level along the edges and removing all above- and below-ground plant parts, while leaving the soil. The remaining plots were left as controls. All plots were re-censused at the beginning and end of the growing season (last weeks of June and August, respectively) in 1998, 1999 and In 1998, I counted all ramets that had appeared in small gaps and in systematically positioned corner, side and centre subplots within large gaps (Fig. 1b), mapped their positions, and determined their origin (seed or vegetative) by looking for remains of seeds or cotyledons, runners, rhizomes or other below-ground connections. Although bulbils of Bistorta vivipara are actually vegetative regenerative organs, they function as seeds and are denoted as such hereafter. For each species, the data were used to calculate the relative importance of seed and vegetative recruitment into gaps, f seed, as the total number of seedlings divided by the total number of seed + vegetative recruits. Nomenclature follows Lid & Lid (1994). Data set I consists of frequency-in-subplot data from the large gaps and control plots at the seven recording dates (area = 625 cm 2 ; 3 stages 2 replicate sites 3 plots 3 blocks 2 treatments = 108 plots per census). Data set II consists of presence-absence data from the small gaps and controls, and from three systematically sampled subplots, corner, side and centre, within each large gap (area = 39 cm 2 ; 270 plots per census). I compiled binomial explanatory variables representing successional stage, farm, experimental block, treatment, time and, for data set II, the positions (corner, side and central) within large gaps. All variables, including time, were coded as series of dummy variables.

4 89 Table 2 Summary of the PRC analyses. The significance of the difference between the two treatments compared in each analysis is judged from the first Gap PRC axis dynamics by permuting whole time series freely within experimental blocks. B = experimental blocks; T = time; G = gap; C = control; S = successional stage; SG = small gap; CE = central; CO = corner; SI = side subplot within large gap successional subalpine grasslands Data Model PRC axis 1 Testing the effect of Data set Stages Treatments n Variables Covariables Variance F-value P(999) Gap vs. control Hypothesis 1a I All G, C 756 G T B + T < Gaps during succession Hypothesis 2a I All G, C 756 G S T G T + B + T < Gap size during succession Hypothesis 1b & 2b II 0 years SG, CE 252 SG T B + T < Hypothesis 1b & 2b II 10 years SG, CE 252 SG T B + T < Hypothesis 1b & 2b II 40 years SG, CE 252 SG T B + T Edge effects during succession Hypothesis 1c & 2c II 0 years CO, CE 252 CO T B + T Hypothesis 1c & 2c II 10 years CO, CE 252 CO T B + T Hypothesis 1c & 2c II 10 years CO, SI 252 CO T B + T Hypothesis 1c & 2c II 10 years SI, CE 252 SI T B + T Hypothesis 1c & 2c II 40 years CO, CE 252 CO T B + T During the 4 years of the study, data from 17 control and seven gap plots (= 1.7% of the total data) were lost. In order to maintain a balanced structure in the data, which is necessary for the Monte Carlo permutation tests in CANOCO 4.5 (ter Braak & Smilauer 2002), all species that appeared in the plot at the sampling dates immediately before and after the lost census were considered to be present in the lost sample. NUMERICAL ANALYSES, PRINCIPAL RESPONSE CURVES (PRC) I tested the six hypotheses and quantified their effects on community composition using principal response curves (PRCs) (van den Brink & ter Braak 1997, 1998). PRC analyses the effect through time of one or more treatments relative to a control. It is coded as a partial redundancy analysis that allows for time-specific treatment effects (e.g. time gap) while controlling for the overall temporal trend (time) and variation among experimental blocks (blocks). I expanded the approach by performing a series of PRCs focusing not only on treatments vs. controls, but also on different types of contrasts. Thus hypothesis 1 is tested by a PRC of gaps vs. controls, and hypothesis 2 by partialling out the overall effect of gap, and then coding the gaps in the three successional stages as different treatments. Hypotheses 1a and 2a concern the differences between large (625 cm 2 ) and small (39 cm 2 ) gaps. As statistically valid comparisons can only be made using sample plots of similar size, these effects are tested by contrasting small gaps with the central subplot in large gaps (Fig. 1). Hypotheses 1b and 2b, edge effects, are tested by comparing different subplots within large gaps. Central subplots (no vegetated edges) are first tested against corners (two vegetated edges), and if these are significantly different, then each is tested against a side subplot (one vegetated edge) (Fig. 1b). Hypotheses 1a, 1b, 2a and 2b are tested separately for each successional stage. The exact model for each test is given in Table 2. Treatment effects (C dt ) quantify the compositional response to the treatment at each sampling date, and temporal trends are visualized by plotting C dt against time. The species weights (b k ) can be interpreted as the affinity of the species with this diagram; species with high positive values follow the overall community response to treatments while species with high negative values react in the opposite way. For simplicity, separate PRC diagrams are not constructed for each of the 10 contrasts; instead Fig. 2 includes all effects evaluated for data set I, and Fig. 3 includes all effects evaluated for data set II for each of the successional stages. To evaluate the statistical significance of each PRC, whole time-series from individual gaps and controls were permuted freely within experimental blocks. Changes in treatment (or contrast) effects through time are evaluated in sequential tests for each sampling time, permuting the census data freely within blocks; 999 permutations were run in all cases. The statistical analyses were performed using the software package CANOCO 4 (ter Braak & Smilauer 2002), the ordination diagram was drawn in CANODRAW (ter Braak & Smilauer 2002), and PRC diagrams in Sigma Plot version 5 (SPSS 1999). Results HYPOTHESIS 1. THE COMPOSITION OF THE VEGETATION THAT DEVELOPS IN BARE-GROUND GAPS IS DIFFERENT FROM THE SURROUNDING GRASSLAND Differences between gaps and controls through time account for 21.6% of the within-plot variance ( Table 3).

5 90 V. Vandvik Fig. 2 PRC diagram and species weights (b k ) on PRC axes 1 and 2 showing the overall impact of gaps on the floristic composition. The plot is based on the PRC of the model Time + Gaps + Stage-specific gap effects on data set I (Table 3). Only species with relatively strong responses, i.e. with weights outside the range 0.4 to +0.4, along the axes are shown. A = autumn; S = spring.

6 91 Gap dynamics in successional subalpine grasslands Fig. 3 PRC diagrams showing the main trends in gap, gap size and edge effects on the floristic composition. The plots are based on PRC analyses per successional stage of the model Time + Gap effects + Size effects + Edge effects on data set II (Table 3). Species scores (b k ) on PRC axes 1 and 2 for each of the three analyses are given in Table 4. A = autumn; S = spring. The effect is highly significant (Table 2) and Fig. 2 shows that species composition was dramatically changed by gap creation, and that, although gaps become more similar to controls with time, the recovery process is relatively slow (Fig. 2 PRC axis 1, Table 2), with differences persisting after 3 years (sequential tests: P < for all except the pre-treatment census). As a large majority of the species (77 out of 84 taxa) occur in both gaps and controls, and only one species, Veronica serpyllifolia, is relatively common in gaps while being absent from the controls ( Table 4), these effects do not reflect strict microsite selectivity between specialist gap and closed vegetation species but rather quantitative differences in gap-colonizing ability. Gap increasers Table 3 Summary of PRCs to quantify the effect of including different factors in the models. Full model PRCs are shown for data set I (n = 756), and per successional stage for data set II (n = 630 per stage) in Figs 2 and 3, respectively. The unique fraction contributed by each factor is found by using all explanatory variables in the model above as covariables. The significance of the PRC axes is judged by permuting the whole time series freely within experimental blocks. Overall differences among experimental blocks are partialled out in all analyses. Abbreviations as in Table 2 Variance explained Variance accounted for by Effects Model Unique Total PRCaxis 1 P(999) PRC axis 2 P(999) Full data (data set I) Time T Gap effects G T < < Stage-specific gap effects G S T < < year successional stage (data set II) Time T Gap effects G T < < Size effects LG T + SG T < < Edge effects LG T + CO T + SI T + CE T < < year successional stage (data set II) Time T Gap effects G T < Size effects LG T + SG T < < Edge effects LG T + CO T + SI T + CE T < < year successional stage (data set II) Time T Gap effects G T < Size effects LG T + SG T < < Edge effects LG T + CO T + SI T + CE T < < 0.001

7 92 Table 4 Recruitment modes (f seed, the fraction of recruits recorded in gaps in 1998 that originated from seeds), total percentage occurrence in data from the V. three Vandvik successional stages, and species weights (b k ) on PRC axes 1 and 2 (Fig. 3) from analyses carried out within successional stages for the most common species. Strong responses (b k outside the 0.4 to 0.4 range) are shown in bold. Pearson s correlation coefficients between f seed and the b k s in different successional stages shown at the bottom of the table are based on all species present. *P < 0.05 Species weights (b k ) Regenerative mode (f seed ) Occurrence (%) PRC axis 1 PRC axis 2 0-year 10-year 40-year 0-year 10-year 40-year 0-year 10-year 40-year Achillea millefolium Agrostis capillaris Alchemilla monticola Alchemilla subcrenata Alchemilla wichurae Anthoxanthum odouratum ssp. alpinum Anthriscus sylvestris Betula pubescens Bistorta vivipara Botrychium lunaria Campanula rotundifolia Deschampsia flexuosa Euphrasia stricta Festuca ovina Gentiana nivalis Geranium sylvaticum Leucanthemum vulgaris Leontodon autumnalis Luzula multiflora ssp. frigidia Luzula pilosa Nardus stricta Phleum pratense Poa pratensis ssp. alpigena Poa alpina Prunella vulgaris Pyrola minor Ranunculus acris Ranunculus auricomus Rhinanthus minor Rumex acetosa Rumex acetosella Sagina procumbens Taraxacum spp Trientalis europaeus Trifolium pratense Trifolium repens Trollius europaeus Vaccinium myrtillus Vaccinium vitis-idaea Veronica alpina Correlation with f seed 0.52* 0.53* 0.63* 0.30* 0.44* 0.68* 0.37* Infrequent species: Carex brunnescens, C. nigra, C. ovalis, C. pilulifera, C. vagiinata, Dactylorhiza spp., Empetrum hermaphroditum, Equisetum pratensis, E. sylvaticum, Epilobium anagallidifolium, Euphrasia frigida, Hieracium lactucella, H. pilosella Hieracium sect. Sylvatica, Juncus filiformis, Juniperus communis, Molinia caerulea, Ranunculus repens, Poa annua, Salix spp. Saussurea alpina, Selaginella selaginoides, Silene pratensis, S. vulgaris, Solidago virgaurea, Taraxacum spp. include ruderals such as Cerastium fontanum and Viola tricolor, grassland herbs such as Alchemilla wichurae, Euphrasia stricta, Luzula frigida and Omalotheca norvegica, and alpine species such as Bistorta vivipara and Gentiana nivalis. There is a general tendency for infrequent species to increase in relative importance in gaps (Pearson s correlation coefficient between b k and number of occurrences in the data: r P = 0.66, 0.72 and 0.82 per successional stage, P < 0.001). In the first year after gaps were created, seedling density was, on average, 1851 m 2 year 1. Overall, 77% of the first-year gap colonisers were of seedling origin, but the relative proportions of seedlings and vegetative recruits varied greatly among species (f seed values, Table 4). Species with high seedling recruitment were more successful gap colonisers than those recruiting into gaps vegetatively (Pearson s correlation coefficient between b k and f seed : r P = 0.54, n = 63, P < 0.001).

8 93 Gap dynamics in successional subalpine grasslands HYPOTHESIS 2. THE OVERALL COMPOSITIONAL EFFECT OF GAPS WILL INCREASE, AND THE GAP RESPONSE OF SPECIES WILL CHANGE ALONG A SECONDARY SUCCESSIONAL GRADIENT A PRC model that allows for stage-specific gap effects increases the explained variance by 10.2% relative to a model with a single trend in revegetation (Table 3), and gap effects differ significantly among all three stages (PRCs on all two-way combinations of stages; sequential tests: P < for all except the pre-treatment census). The 40-year gaps appear most distinct floristically (PRC axis 2, Fig. 1), and the succession towards the composition of the controls (the slope of the PRC curve through time) is slightly slower here (Fig. 2, PRC axis 1), consistent with the first part of hypothesis 2. The gap effect increases considerably during succession, with 8.8% of the compositional variance in the 0-year grasslands being accounted for by gap-related revegetation trends, 9.4% in 10-year grasslands, and 12.2% in 40-year grasslands (Table 3). Overall, 74% of the species are affected by gaps, positively or negatively, in at least one stage, but their responses are generally not consistent along the successional sequence (Table 4). Species that are gap-enhanced in early successional grasslands tend to decrease in abundance or be absent from the grassland vegetation of later successional stages (correlation between b k in 0-year grasslands and relative change in total abundance between 0 and 40 years: r P = 0.46, n = 32, P < 0.01). Many of these are species typical of low-growing open vegetation, such as Alchemilla wichurae, Euphrasia stricta, Gentiana nivalis, Sagina procumbens, Botrychium lunaria, Rhinanthus minor and Cerastium fontanum (Table 4). Further, many species that occur throughout the successional sequence, including Bistorta vivipara, Luzula frigida, Rumex acetosella and Trifolium repens, tend to become more gap-enhanced during succession (i.e. b k values decrease, Table 4). These differences between stages support the second part of hypothesis 2. HYPOTHESIS 1A: GAP SIZE AFFECTS COLONIZATION. HYPOTHESIS 2A: SIZE EFFECTS DECREASE DURING SECONDARY SUCCESSION Allowing for differential effects of large and small gaps increases the explained variance by % within stages (Table 3). The differences between large and small gaps seem to accelerate through revegetation, because, unlike large gaps, small ones do not tend towards the composition of controls (Fig. 3). PRC axis 2 further differentiates a subset of the gap-enhanced species that do not colonize small gaps, such as Alchemilla wichurae and Gentiana nivalis (negative b k values on PRC axis 2, Table 4), from species that appear predominantly in small gaps, such as Botrychium lunaria and Trollius europaeus (negative b k values on PRC axis 1 and positive on PRC axis 2). The size effect is highly significant in the 0- and 10-year stages (Table 2), where it appears in the first year after treatment and persists through the study period (P < 0.002), but disappears in the 40-year successional stage (Table 2). These results support hypotheses 1a and 2a. HYPOTHESIS 1B: THERE ARE EDGE EFFECTS ON COLONIZATION. HYPOTHESIS 2B: THESE EFFECTS DECREASE DURING SECONDARY SUCCESSION Significant edge effects appear only in the midsuccessional stage (P = 0.03, Table 2). The effects are weak (Table 3), and develop slowly, as significant differences between corners and centres do not appear until 2 years after gap creation (P = 0.62, 0.25, 0.51, 0.87, 0.05, 0.03, 0.20 for sequential tests of the corner centre contrast in 10-year grasslands at A-97, S-98, A-98, S-99, A-99, S-00 and A-00 censuses, respectively). The trajectories of the different subplots within large gaps in the 10-year stage through time appear distinct and parallel, with corners approaching the controls first, followed by sides, while centres differ most strongly from the closed vegetation (PRC axis 1, Fig. 3). This suggests that these edge effects may be ecologically interpretable despite the weak overall compositional response. Hypothesis 1b cannot therefore be rejected for the 10-year successional stage, nor Hypothesis 2b for the 10-year to the 40-year stages. Discussion GAP REGENERATION AND SPECIES COEXISTENCE IN SUBALPINE GRASSLANDS The initial colonization of bare ground is limited by the local availability of propagules, and hence there is a general tendency for species that are common in the established vegetation also to become the most successful gap colonisers (Reader & Buck 1990; Arnthórsdóttir 1994; Bullock et al. 1995; Rogers & Hartnett 2001). Despite this overall constraint, which is reflected in a relationship between abundance in closed vegetation and gaps (r P = 0.89, n = 66, P < 0.001, data set I), the composition of the vegetation that develops within gaps in these grasslands differs strongly and persistently from the closed-sward controls (Figs 2 and 3). The estimated species responses (b k values) are remarkably consistent across data sets and scales of study, and imply a c. 20% increase and decrease, respectively, in the number of small-plot occurrences in the most characteristic gap-enhanced and closed-sward species in the first year after disturbance (calculation based on data set I: b k C dt 100/16, Fig. 2; data set II: b k C dt 100, Fig. 3 and Table 4). Hence, these species do not have absolute gap or closed-sward requirements, but exhibit a range of responses ranging from positive via neutral to

9 94 V. Vandvik negative, supporting the view that the gap responses are continuous rather than on-off traits (Hubbell et al. 1999; Bullock 2000). The strong and highly significant compositional response to gap size indicates that the small and large experimental gaps, which were selected to be within the typical range of gap sizes created by domestic grazers in these grasslands (personal observation), are colonized by partially distinct assemblages of species. Seed colonisers appear predominantly in large gaps (f seed and PRC axis 2, r P = 0.37, 0-year stage Fig. 3 and Table 4). Large gaps fill more slowly, thereby providing increased time for seed colonization to occur (Bullock et al. 1995; Rogers & Hartnett 2001), and they are more environmentally different from the closed vegetation (Goldberg & Werner 1983; Kotanen 1997b; Morgan 1997; King & Grace 2000), so that gap-detecting germination responses in seeds (Grime et al. 1981) will be more efficient here. In contrast, edge effects are weak (Table 2), induce a different compositional response (expressed along a different PRC axis, Table 3, Fig. 3), and are much slower, as a significant effect does not appear until 2 years after gaps are created. Clearly, these edge effects do not operate on initial colonization or early establishment, nor through microenvironmental differences (Kotanen 1997b), as centre and edge environments will become progressively more similar during gap revegetation. The experimental results (Fig. 3, 10-year stage) are more consistent with predictions based on competitive exclusion, which should induce a temporary divergence in floristic composition between centres and edges as vegetation closes along the edgeto-centre gradient and poor competitors (i.e. typical bare-ground species, species with low b k values) are gradually excluded. The overall impression emerging from the gap, size and edge effects combined is that the grassland community responds strongly and relatively quickly to changes in the microenvironment (initial gap response, size effect), but in a weaker and slower way to changes in local competitive regimes (revegetation dynamics after the first year, edge effects, clonal encroachment). This contrasts the fast and predominantly clonal colonization reported from perennial grasslands elsewhere (Rapp & Rabinowitz 1985; Milberg 1993; Arnthórsdóttir 1994; Kotanen 1997b), and may indicate that clonal growth rates and response to release from competition in these grasslands is strongly limited by factors such as the short growing season and slow growth rates in cold climates (Körner 1999), and low soil productivity resulting from continuous removal of biomass through centuries of low-intensity free-range grazing (Mannion 2002; Vandvik 2002). In contrast, seed recruitment is high, and compares with those of temperate alvar grasslands (van der Maarel & Sykes 1993; Gigon & Leutert 1996), supporting Chambers s (1995) observation that the seed recruitment responses to disturbance in cold climates parallels that of more benign environments. CHANGES IN GAP EFFECTS DURING SECONDARY SUCCESSION A major objective of this study was to investigate whether, and how, revegetation dynamics of fine-scale gaps in a closed sward change along a successional sequence. The formal test, performed on data set I (Table 2), demonstrates that such changes occur in these grasslands. The differential gap responses are also relatively strong, with the explained variance increasing considerably, from 21.6% to 31.8%, when they are allowed for in the PRCs (Table 3). Although the differences in gap revegetation dynamics among successional stages in these data could potentially be caused by other factors (e.g. altitude, topography, substrate, moisture or soils), there are several reasons to conclude that land-use history is of overriding importance. First, replicate farms within successional stages were carefully selected to avoid systematic differences in other factors. Second, local site factors are relatively unimportant for the vegetation at summer farms, because these are located in similar places in the landscape, and centuries of landuse before abandonment have homogenized any initial differences (Vandvik & Birks 2002). Third, timing of abandonment and other differences in land-use generally relate more to economy and interests of the landowner than to ecological characteristics (productivity, spatial isolation) of the summer farm (personal observation). Fourth, land-use history accounts for a very large fraction (> 75%) of the total between-farm floristic variability in these data (tested in a partial CCA, not presented here). Overall, it is therefore likely that the effects of land-use history are of overriding importance for the systematic differences in floristic composition, and in gap responses, appearing between successional stages. Thus, for an appreciable fraction of the species in these grasslands, the relationship between abundance in controls and the probability of appearance in bareground gaps changes during succession. Seed colonisers become relatively more gap dependent, and are therefore more likely to become locally extinct, through the successional sequence (the correlation between f seed and PRC axis 1 becomes stronger, Table 4). This result appears to contradict, at a speciesby-species scale, the results of others, for example Moen & Oksanen s (1988) experiment in alpine snowbeds, which showed that the growth and performance of tall herbs, including Omalotheca norvegica, Trollius europaeus and Bistorta vivipara, increased when protected from grazers, whereas I found that these three species all become increasingly gap-enhanced during secondary succession. Seedling establishment of Trollius europaeus (and 73% of the subalpine grassland perennials investigated) is effectively inhibited in closed grassland vegetation (Vandvik 2002), however, and the apparent contradiction may be resolved if we realize that changes in disturbance regimes may exert different, sometimes opposing, influences on the vegetative and regenerative life phases of species.

10 95 Gap dynamics in successional subalpine grasslands The relative increase in gap dependency of seed colonisers along the 40-year sequence indicates that the availability of safe sites for regeneration becomes a more serious limitation for population persistence than the availability of propagules during secondary succession (cf. Eriksson & Ehrlen 1992). This may, in part, be attributed to the relatively extensive seed banks under these grasslands (66 species, 2131 seeds m 2, unpublished data). At the secondary successional time-scales studied here (0 40 years), these seedbanks may offer a potential for re-establishment if species go locally extinct (storage effects sensu Chesson 1983; Warner & Chesson 1985). This may explain why locally infrequent species tend to increase in relative importance in gaps (this study, Lavorel et al. 1994). At the whole-field scale, 28 species are lost and only seven new species appear along the 40-year secondary succession, showing that abandonment may have relatively dramatic long-term effects on local community composition and diversity. The local disturbance regimes of these grasslands may be seen as environmental sieves (Zobel 1992, 1997) that function to exclude subsets of the species in the regional species pool from local communities. Conclusions The results of this study demonstrate that fine-scale disturbances can have considerable effects on the community structure and floristic composition of subalpine perennial grasslands. Gaps do not exert simple on-off effects, as small and large gaps and edges and centres are colonized by partially distinct assemblages of species, and these overall trends as well as the responses of individual species change during secondary succession. This illustrates how processes operating at different scales may interact (Pickett et al. 1987, 1989; Zobel 1992): the disturbance regime, at the scale of the entire grassland, affects the dynamics within individual disturbances. The gap, size and edge effects combined indicate that the gap microenvironment facilitates seed colonization at rates comparable with those observed in temperate systems (initial gap response, size effect), whereas the responses to changes in local competitive regimes (revegetation dynamics after the first year, edge effects, clonal encroachment) are relatively weak and slow. This may be attributed to the slow growth rates of subalpine plants and the short growing season in subalpine climates, as well as to the infertile soils of the semi-natural grasslands. A consequence is that a given disturbance regime (i.e. frequency of gap creation) will have a stronger compositional effect here than under more benign conditions. 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