Population Structure of Osmunda regalis in Relation

to Environment and Vegetation: An Example

in the Mediterranean Area

Marco Landi & Claudia Angiolini

# Institute of Botany, Academy of Sciences of the Czech Republic 2010

Abstract The structure of 42 natural populations of the endangered fern Osmunda

regalis was studied at the southern limit of its European distribution. The aims wereto i) investigate the population structures and status of the species; ii) test whichlocal habitat and population characteristics correlate with the different populationstructures in the Mediterranean area; iii) evaluate which habitat types are suitable tosupport viable populations. The structure of populations is determined by theattribution of different stages of development of the sporophyte. This studydocumented the life-stage structure of O. regalis using an original classification oflife stages that may be applicable to other fern populations with similar morphology.Using statistical analyses we distinguished: i) dynamic populations, which arecharacterized by a large proportion of sporelings and vegetative adults and areassociated with streams and nemoral species; ii) stable populations, with a higherproportion of generative adults, growing prevalently in habitats rich in hygrophilousgrasses and shrubs, with lower tree cover; iii) senile populations, with a relativelyhigher proportion of senescent individuals and with marked rejuvenation dominatedby vegetative adults, which are prevalently located in spring swamps. The proportionof senescent stage individuals is positively correlated with the mean geographicdistance between populations. Spring swamps, with populations that provide a clearexample of remnant dynamics, are the habitat with the most stable conditions for O.regalis in the Mediterranean area.

Keywords Demography . Fern . Habitat quality . Italy . Life stages . Osmundaceae

Folia Geobot (2011) 46:49–68DOI 10.1007/s12224-010-9086-1

M. Landi (*) : C. AngioliniDepartment of Environmental Science “G. Sarfatti”, University of Siena, Via Mattioli 4,53100 Siena, Italye-mail: landi21@unisi.it

C. Angiolinie-mail: angiolini@unisi.it

Plant nomenclature Tutin et al. (1968–1980)

Introduction

The first step in the conservation of endangered plant populations is to determinetheir biological “status”, by identifying the life stages most critical to populationgrowth, and the causes of demographic variation at these stages (Schemske et al.1994). To this end, many studies have analyzed species’ adaptation to theirenvironment and, in this context, the demography of populations provides importantinformation. Studies of plant populations in different geographic areas that includeenvironmental and demographic data can furnish important answers to ecologicalquestions concerning how species respond to different environmental conditions(Odland et al. 2006).

Three levels of monitoring for plant populations (distribution, population size anddemographic monitoring) can be applied to species according to the priority of theirprotection and management objectives; demographic monitoring is the mostintensive level but is difficult to apply when time (e.g., for endangered species)and resources are limited (Menges and Gordon 1996). A relatively simple alternativemethod can focus on the identification of the different ontogenetic stages (life stages)of a species’ life cycle and analysis of the demographic structure of its populations(Oostermeijer et al. 1994; Hegland et al. 2001; Eckstein et al. 2004). Demographicstudies can identify the critical stages of a plant’s life cycle and, when the results ofsuch studies are related to the different environmental variables, it becomes possibleto predict viability and acquire the knowledge necessary for efficient management orconservation of perennial plants (see also Menges 1990; Jacquemyn et al. 2003;Aguraiuja et al. 2004; Endels et al. 2004; Mróz 2006; Berry et al. 2008; Zheleznaya2009). Another issue of conservation biology is that genetic variation and populationviability are expected to decrease with fragmentation and population isolation(Menges and Dolan 1998; Jacquemyn et al. 2002; Lienert et al. 2002; Hooftman etal. 2003; Eckstein et al. 2004; Jäkäläniemi et al. 2005). These studies, and othersperformed on remnant populations in Mediterranean environments (García et al.1999, 2000), have contributed important information to the knowledge of thespatial structure of populations and their risk of extinction. However, only a fewstudies have examined the life stages or demographic structure of pteridophytes(Cinquemani Kuehn and Leopold 1993; Aguraiuja et al. 2004; Rünk et al. 2006;Aguraiuja et al. 2008).

In this paper, we used the demographic structure of a fern, Osmunda regalis L.subsp. regalis, as a simple tool to assess the demographic future of local populationsin a Mediterranean area (see, i.e., Brys et al. 2003). O. regalis is a homosporouspteridophyte and its life cycle comprises two distinct phases: a haploid gamete-producing phase (gametophyte) and the diploid spore-producing phase (sporophyte).Distinct states of development or life stages can be distinguished within bothgametophyte and sporophyte phases in the pteridophytes (see, e.g., Shorina 2001;Aguraiuja et al. 2004). To this end we used the ramets, which consist of rosettes offronds that arise through clonal growth or from the gametophyte, as the unit foridentification of the stages of development of the sporophyte phases of the life cycle:

50 M. Landi, C. Angiolini

juvenile, vegetative adult, generative and senescent (Rabotnov 1969; Gatsuk et al.1980). The relative proportions of ramets in the different stages of development,or “life-stage spectrum”, was used as the demographic structure. This method isvaluable because the spectrum, which indicates the current demographic statusof a population or population structure (Moora et al. 2007), is considered bymany authors (e.g., Menges 1990; Oostermeijer et al. 1994; Hegland et al. 2001;Jacquemyn et al. 2003) as a much better indicator of the present vitality orviability of a population. Three main types of populations are generallydistinguished: i) dynamic populations, characterized by a large proportion ofyoung plants; ii) stable populations, which include a higher proportion of adultplants than young plants; iii) regressive populations, in which adult plantsdominate and recruitment of new individuals is impeded (see Oostermeijer et al.1994; Aguraiuja et al. 2004). We defined every local population as a spatiallydistinct assemblage of plants, whose irregular boundaries we fitted into a regular-shaped polygon (referred to as a macroplot). These local populations were thenattributed to habitats (streams or spring swamps), as reported by Landi andAngiolini (2008).

The Mediterranean region, whose climate is characterized by a dry summer andrain in spring and autumn, provides an interesting study case for the populationstructure of a fern that has managed not to adapt to dry climates (Pichi Sermolli1970) and that has decreased significantly in many countries, including Italy (e.g.,Tutin et al. 1993; Rameau et al. 1993; Conti et al. 1997; Zenkteler 1999; Hardalova2004; Colling 2005).

The study comprised three steps. First, we ascertained the life-stage spectrum foreach plot and then for each local population from the proportions of the developmentstages of O. regalis rosettes of fronds. Second, we classified these plots and localpopulations into different structural types using cluster analysis. Third, we comparedthis information to data regarding the environment, vegetation and mean geographicdistance between populations.

We aimed to answer the following specific questions: i) What is the populationstructure and status of O. regalis? ii) Which local habitat features and populationfactors (distance and/or density) correlate with the different population structures ofthis fern? iii) Which habitat types are suitable to support viable populations in aMediterranean area?

Although the focus of our study was to investigate the relationship betweenpopulation structure and environment in O. regalis, we have presented amethodology that is also applicable to studies of other Osmunda populations.

Material and Methods

Study Species and Site

Osmunda regalis (Osmundaceae) is a clonal plant and as such all the rootstockswithin a population can genetically share the same genome. Asexual reproductionoccurs with rhizomes, which should subsequently break or somehow be separatedinto two clusters and thus two individual plants, but in this fern sexual reproduction

Population structure of Osmunda regalis in relation to environment... 51

is far more prevalent and effective than asexual reproduction (Klekowski 1970,1973). The rootstock, which is like a short trunk, can grow to several cm in height,with mature plants sometimes reaching over 30 cm, and is covered with leaf sheathsand roots. It produces dimorphic fronds (fertile and sterile) and the fertile frondshave sporangia at their apices. The rosettes consist of one or more fronds that growout of the rootstock like a crown. Adult specimens are classified according to theirbiomorph type and considered explicitly polycentric (see Smirnova et al. 2002). O.regalis has great longevity, with some cultivated plants being over 300 years old (seePage 2002). It is a deciduous herbaceous fern and the fronds in the study areacomplete their elongation from May to August.

Osmunda regalis has a long life-cycle turnover, of nearly two years, from spore-sowing to the first sporophyte and spore production (Klekowski 1967). The sporesare green and germinate rapidly, within one day of sowing. This ability to germinatedecreases rapidly with the age of spore; their length of viability being 150–210 days(see Lloyd and Klekowski 1970). Similarly to other species of terrestrial ferns withgreen spores, O. regalis is usually found in edaphic situations with high humidity(Lloyd and Klekowski 1970). The gametophytes are autotrophic, typicallyhermaphroditic, lack an antheridiogen system and gametophyte generation is rathera long process (lasting two or more months), in contrast to other temperate fern taxa(Voeller 1964; Klekowski 1970; Fernández et al. 1997). Experiments on game-tophytes of O. regalis have shown that the gametophytes develop a heart-shapedmorphology even in darkness and the addition of ammonium inhibits its growth(Fernández et al. 1997).

Intergametophytic or intragametophytic mating systems may occur in O. regalis.This takes the form of either selfing within or between the prothalli of same parentsporophytes (intragametophytic and intergametophytic selfing, respectively) oroutcrossing between prothalli arising from the spores of different parent sporophytes(intergametophytic crossing) (Klekowski 1970).

A variety of limitations to the ecological success of ferns have been identified(Page 2002), but O. regalis also has other unfavourable characteristics, such as thepresence of genetic loads that were found to be responsible for the death ofhomozygous individuals after selfing and that disturbed gametogenesis andfertilization (see Klekowski 1973; Zenkteler 1999).

The populations studied were included in an area of approx. 15,000 km2 inCentral Italy (10°06′–11°17′ E, 42°18′–43°15′ N), a Mediterranean region where thespecies is at the southern and easternmost limit of its European distributional area;the species is rare here and local populations are mainly found in spring swamps(swamps that develop at or along the outflow of springs) and along streams (Landiand Angiolini 2008).

Classification of Life Stages

The analysis of population structure was based on the number of individualsattributed to the different ontogenetic stages of the life cycle (Gatsuk et al. 1980).We used ramets, which consist of rosettes of fronds, as the basic unit foridentification of the stages of development. We distinguished six different lifestages in O. regalis populations through field observations of 1,645 ramets and on

52 M. Landi, C. Angiolini

the basis of morphological characteristics. The categories used were as follows(Fig. 1):

1) Gametophyte (Ga);2) Sporeling or juvenile (Sp): rosettes approx. <20 cm in height, simply pinnate

young fronds, lack of sporangia;3) Vegetative adult or immature (Va): rosettes approx. >20 cm in height, multi-

pinnate adult fronds, lack of sporangia;4) Generative or mature (Ge): presence of mature sporangia;5) Senescent (Se): young fronds on large rootstocks. This life stage is considered

as senescent because it appears as a decrease in individual vigour;6) Dormant or dead (Do): large rootstocks without any visible rosettes.

The gametophyte (Ga) and dormant (Do) life stages were omitted from thepopulation analysis because they are extremely difficult to observe in field conditionsand because it was not possible to assign a number of ramets to these categories.

Field Methods and Variables Selected

We analyzed 42 local populations of Osmunda regalis, defined as clusters of plantsof this species separated from other clusters by more than 500 m, but that are usuallyeven further apart. The area of the local population was defined as a regular-shapedpolygon, which covered the bulk of the population. The necessary sample size forestimating a single population with a specified level of precision was calculated ondata obtained from preliminary sampling (Elzinga et al. 2001) using the following

Fig. 1 Schematic drawing of the life stages (Spore; Ga – Gametophyte; Sp – Sporeling; Va – Vegetativeadult; Ge – Generative, Se – Senescent; Do – Dormant or dead) distinguished in the populations ofOsmunda regalis. The arrows in the diagram summarize all possible transitions between the stages. Thetransition from senescent to vegetative adult may be possible due to the breaking of rhizomes (seevegetative reproduction in McVeigh 1937). We were not able to distinguish between large rootstocks withoutany visible rosettes but with the potential to develop rosettes (transition Do/Se) and rootstocks that werecompletely dead. We assume that the transitions Se↔ Do are possible but did not directly observe them

Population structure of Osmunda regalis in relation to environment... 53

equation: n ¼ ðZaÞ2ðsÞ2=ðBÞ2, where (Zα) is the standard normal coefficient, (s) is

the standard deviation of the ramet number sampled, (B) is the desired level ofprecision. We observed all the ramets in 5% of each local population, which is theoptimal sample size required to achieve the target precision of a 95% confidenceinterval, by random selection of 25-m2 square plots. The specific composition of thesurrounding vegetation was investigated in 100-m2 square plots (for details seeFig. 2). In total 207 plots were investigated and those in which Osmunda was found(106 plots) were analyzed. Within each 25-m2 plot we counted the number of rametsin each life stage and recorded the following local habitat features: percent cover oflitter, mosses, trees, shrubs, stones (7.5–60 cm diameter) and boulders (>60 cmdiameter), as well as percent slope and habitat in two wetland classes, based on theclassification system by Warner and Rubec (1997): 1. streams (or waterways), 2.spring swamps. Within each 100-m2 square plot the abundance of all vascular plantswas estimated using the Braun-Blanquet cover-abundance index (Mueller-Domboisand Ellenberg 1974). The field surveys were performed in June–July of 2005 and in2006 to identify the species that flower during early spring or autumn.

Distance Measurements

To evaluate the effects of distance on life stages, we calculated the linear distancebetween all possible local population pairs using digital maps, on the basis of thegeographic coordinates of all the known populations (Landi and Angiolini 2007).

We used the mean distances calculated between each population and the others,rather than the minimum distances (see Harrison et al. 2000), because homosporousferns are characterized by long distance dispersal (see Wolf et al. 2001).

Data Analysis

The data regarding the number of ramets in each life stage per plot were used todetermine the relative proportions of each life stage in the plots and in localpopulations, and to subsequently define the demographic structure of the total

Fig. 2 Schematic representation of the random sampling design; the black filled squares indicate the plotselected. For example, in one of the 42 local populations: in a 5×5 m square we sampled the ramets, whilein a 10×10 m square we sampled the vegetation

54 M. Landi, C. Angiolini

population. The demographic structure, or “life-stage spectrum”, was then calculatedfor individual plots (n=106) and for each population (n=42). These samples weresubjected to classification using K-means clustering (Legendre and Legendre 1998).This clustering method split the set of samples into a pre-selected number of groupsby maximizing between-group in relation to within-group variation. A one-waymultivariate analysis of variance (MANOVA) was performed to detect any overalldifferences in the proportions of the life stages (response variables) amongpopulation types (categorical predictor) as obtained by K-means clustering. Separateanalysis was performed on the proportion of each life-stage per plot and population.If significant differences were found, a univariate ANOVA was performed for eachlife stage. To estimate the differences between the mean of each life stage betweenthe population types, the Tukey post-hoc multiple-comparison test for unequalsamples was applied, with a significance level of 0.05. Considering the ratiossuggested as indices of recruitment or indicators of the different populationstructures for long-lived perennial species (Oostermeijer et al. 1994; Hegland et al.2001; Cascante-Marín et al. 2006; Mróz 2006), we decided to use a ratio determinedby sporelings plus vegetative adults, divided by generative adults plus senescentindividuals (abbreviated: (Sp+Va / Ge+Se)).

We used the Kruskal-Wallis test (K-W test) to check whether there was asignificant difference in the ratios between the population types as obtained bycluster analysis. The Mann-Whitney U test was used to determine the significance ofdifferences in the environmental and demographic variables (untransformed data)between two habitats (streams and spring swamps). The Chi-square test was used totest the null hypothesis that the plots of different population types are distributedwith the same frequency as the categories of the two habitats. The differencesbetween populations (categorical predictor) in the density of ramets (responsevariable) were tested by means of a one-way ANOVA. Simple regression analysiswas used to investigate the relationship between geographic distance and theproportion of each life stage within populations, whereas multiple regressionanalysis (Sokal and Rohlf 1995) was used to study the relationship betweenenvironmental factors and the structure of the surrounding vegetation and thepercentage of each life stage. MANOVA/ANOVA and regression analysis wereperformed using Statistica 7.0 (StatSoft Inc. 2001).

Species cover-abundance data (omitting the scores for O. regalis) were expressedon an ordinal scale from 1 to 9, which replaced the original alpha-numeric values ofthe Braun-Blanquet scale (Noest et al. 1989), and were used to create a distancematrix by applying the chi-square resemblance coefficient with perfect gradientrecovery for linear data (see Podani and Miklós 2002). We used a coefficient forlinear species response after a preliminary DCA (detrended correspondenceanalysis), estimating that the length of the gradient in units was below 4.0 SD(3.61 SD) (Lepš and Šmilauer 2003). The distance matrix was used as the input forprincipal coordinates analysis (PCoA), which visualized the pattern of dissimilaritybetween ordinations of plots of different population types. In addition, constrainedordination of this data set was performed with redundancy analysis (RDA); thepopulation types were used separately as a single explanatory variable in constrainedordinations and their effect on the ordination pattern was tested using the MonteCarlo test with 1,000 permutations.

Population structure of Osmunda regalis in relation to environment... 55

The INdicator SPecies ANalysis (INSPAN; Dufrène and Legendre 1997) wasused to classify the 188 species into three pre-defined population types according totheir occurrence and abundance. For each species the strength of its association witha population type was tested with the Monte Carlo test (1,000 permutations). Formultivariate analysis we used the CANOCO software version 4.5 (ter Braak andŠmilauer 2002) for ordinations and PcOrd (McCune and Mefford 1999) forINdicator SPecies ANalysis.

Results

Population Structure and Population Types

The pre-selection of 2, 3, 4 and 5 groups for K-means clustering highlighted that onlythe clustering with three pre-selected groups had a more equally distributed number ofplots and populations were large enough to permit interpretation (see Hegland et al.2001). The classification of the three groups and the proportion of life stages per plotand local population is shown in Fig. 3a,b and can be interpreted as follows. Cluster 1showed a high proportion of sporelings and vegetative adults and consequently a lowproportion of generative and senescent individuals. This is similar to what is known asan invasive (Oostermeijer et al. 1994) or dynamic (Hegland et al. 2001) populationstructure; as the species in this case is rare, we prefer to use the term dynamic. In factthe Sp+Va / Ge+Se ratio in the plots was high, with a mean of 6.63 and maximum of37. Cluster 2 included the plots with a high proportion of generative individuals inrelation to all the other life stages and was interpreted as stable. The Sp+Va / Ge+Seratio was low, with a mean of 0.65 and maximum of 2.8. Cluster 3 was characterizedby different dominant life stages in the plot classification (a higher proportion ofsenescent individuals) and population classification (a high proportion of vegetative

Fig. 3 Demographic structure or life stage spectrum (proportion of the life stages) of the threepopulation types that emerged from K-means clustering per plot (a) and per population (b). Error barsindicate standard deviation. The different letters above bars of the same colour indicate that the meansof the life stage differ significantly for the three types of populations (P<0.05) according to the TukeyHSD test. The total population structure was obtained from the total number of ramets (1,645) assignedto each life stage (c)

56 M. Landi, C. Angiolini

adult and senescent individuals) and by a low ratio, with a mean of 0.71 andmaximum of 1.57, thus being interpreted as senile.

One-way MANOVA revealed significant differences between population types inthe proportion of life stages in individual plots (Wilkes' λ=0.056, F6.202=107.88,P<0.01) and in populations (Wilkes' λ=0.102, F6.74=26.11, P<0.01). Given thesignificance of the overall test, univariate ANOVAs were conducted on each lifestage (dependent variables). Significant effects were found for all life stages, withthe sole exception of the sporeling stage at population level. The results of theunivariate analyses of variance from MANOVA are presented in Table 1.

The K-W test performed on the populations also showed significant differences inSp+Va / Ge+Se ratios (K-W: χ2=19.2, d.f.=2, P<0.01) between groups. Figure 3cshows the total population structure calculated for the study area and demonstrates alife-stage spectrum characterized by the absolute dominance of vegetative andgenerative adults over sporeling and senescent life stages. No significant differencein the density of ramets among the various population types was found (One-wayANOVA: P=0.588).

Mean Distance between the Population Types

Linear regression analysis of the mean distance between populations and theirproportions in life stages only showed a significant positive relationship for thesenescent life stage (r=0.698, P<0.01; Fig. 4). This demonstrated that the proportionof ramets classified as senescent increased with the distance between populations.

Life Stages and Population Structure in Relation to Habitat, Environmental

and Vegetational Variables

Table 2 reports the mean, median and range of demographic and environmentalvariables for all plots and compared by habitat. The Mann-Whitney U-test indicated

Table 1 Univariate results for one-way MANOVA performed to compare the proportion of respective lifestages (response variables) in three population types (categorical predictor) obtained by K-meansclustering (see text). The proportion of each life stage is calculated at the plot (n=106) and populationlevel (n=42)

Variables Plot level Population level

SS df MS F P SS df MS F P

Sporeling 0.415 2 0.207 5.28 <0.01 0.028 2 0.014 0.42 0.655

Error 4.05 103 0.039 1.297 39 0.033

Vegetative adult 3.688 2 1.844 44.97 <0.01 1.416 2 0.708 24.32 <0.01

Error 4.222 103 0.041 1.135 39 0.029

Generative 7.182 2 3.591 167.95 <0.01 2.003 2 1.003 37.95 <0.01

Error 2.202 103 0.021 1.030 39 0.026

Senescent 3.878 2 1.939 180.09 <0.01 0.698 2 0.349 36.47 <0.01

Error 1.108 103 0.010 0.373 39 0.009

Population structure of Osmunda regalis in relation to environment... 57

differences in environmental variables between habitats, except for shrub cover, andhighlighted the presence of a higher number of generatives and especially ofsenescent ramets in spring swamps. The (Sp+Va) / (Ge+Se) ratio showed a meanvalue of 2.76 in streams and 1.01 in spring swamps. The number of plots attributedto each population type (dynamic, stable and senile populations) by K-meansclustering and found in streams and spring swamps are shown in Table 3. The chi-square test indicated significant differences in the number of plots per populationtype observed and expected between streams and spring swamps (Table 3;χ2=31.37; d.f.=3; P<0.01). Higher individual values of χ2 indicated that dynamic

and senile populations are associated with a particular habitat, i.e., respectivelystreams and spring swamps.

Multiple regression analysis (Table 4) showed a clear connection between somelife stages of O. regalis populations (dependent variables) and some environmentalvariables and the structure of the surrounding vegetation (predictor variables). In theregression model the regression coefficients (or β coefficients) were used to representthe independent contributions (positive or negative) of each independent variable tothe prediction of the dependent variable. These regression coefficients showed thatvegetative adults were positively related with tree cover while generative adults werenegatively related with this variable. Generative adults were positively related withshrub cover and slope, whereas the percentage of sporelings and vegetative adults(see the recruitment ratio) were linked to gentle slopes and lower shrub cover andrelated positively with stones. The senescent life stage showed a negativerelationship with boulders. The litter and moss cover were not significant predictor

Fig. 4 Relationship between the mean distance between populations and the proportion of the senescentlife stage in the three types of population. Linear regression fit and ±95% confidence interval are shown

58 M. Landi, C. Angiolini

variables of the life stages of O. regalis and the percentage of the sporeling life stagewas not related with any of the variables.

The Monte Carlo test in the RDA showed that there were significant differencesin vegetation composition between the three population types (P<0.01). However,the plots of the different population types did not occupy separate positions in thePCoA ordination space. There was significant overlapping of the population types inthe ordination space, indicating that the different population structures had manyspecies in common (Fig. 5).

The seven most common species found were prevalently hygrophilous and/oracidophilus: Alnus glutinosa, Blechnum spicant, Carex remota, Castanea sativa,

Fraxinus ornus, Hedera helix, Ilex aquifolium, Pteridium aquilinum and Rubus

Table 2 Mean, median and variation of environmental and demographic variables for all plots (n=106)and the two habitats (68 plots in streams and 38 plots in spring swamps) (untransformed data).Comparisons between streams and spring swamps were made with Mann-Whitney U-tests (** – P<0.01;* – P < 0.05; n.s. – not significant)

Variables All plots In streams In spring swamps P

Mean Median Range Mean Median Range Mean Median Range

Environmental

Tree cover (%) 71.5 75.0 0–95 76.2 80.0 5–95 62.2 65.0 0–90 **

Shrub cover (%) 13.4 6.5 0–70 13.0 10.0 0–60 14.1 5.0 0–70 n.s.

Litter cover (%) 24.6 15.0 5–90 18.8 15.0 5–65 35.4 27.5 5–90 *

Mosses cover (%) 9.7 5.0 0–65 6.4 5.0 0–40 16.3 9.0 0–65 *

Slope (%) 30.2 20.0 0–130 24.2 15.0 0–100 42.4 27.5 0–130 *

Stones (%) 12.5 10.0 0–40 15.9 15.0 0–40 6.6 5.0 0–30 **

Boulders (%) 25.2 15.0 0–80 34.6 40.0 0–80 8.0 0.0 0–65 **

Life stage

Sporeling (nr.) 2.0 0.0 0–22 2.1 1.0 0–22 1.9 0.0 0–17 n.s.

Vegetative adult (nr.) 6.8 4.0 0–26 6.1 3.0 0–26 8.4 5.0 0–26 n.s.

Generative (nr.) 3.7 2.0 0–25 2.8 1.0 0–21 5.6 5.0 0–25 *

Senescent (nr.) 1.3 0.0 0–19 0.2 0.0 0–3 3.4 0.0 0–19 **

Table 3 Summary of the number of plots for each population type and comparison (chi-square testwith 2×3 contingency table) of observed and expected number of plots in streams and spring swamps(* – P<0.01)

All plots In streams In spring swamps χ2

Population types Total (%) Obs. Exp. Obs. Exp.

Dynamic (nr. plots) 37 35 31 23.7 6 13.3 6.19

Stable (nr. plots) 45 42 33 28.9 12 16.1 1.64

Senile (nr. plots) 24 23 4 15.4 20 8.6 23.54

Totals 106 100 68 68 38 38 31.37*

Population structure of Osmunda regalis in relation to environment... 59

hirtus. However, while Fig. 5 highlights the association between mesoxerophilousand/or acidophilous species (i.e., Castanea sativa, Fraxinus ornus, Erica arborea

and Arbutus unedo) and senile plots (positive side of the first axis), it is difficult toidentify species that differentiate the dynamic and stable type plots. The position ofthe species in relation to the types of population structure reported in the ordinationdiagram shows moderate agreement with the results obtained from the INSPAN(Table 5).

Only 53 species were either restricted to or significantly associated with one ofthe three population types. The number of these species was highest in the dynamicpopulations (n=16) and stable populations (n=28) and lowest in the senile ones(n=9). The plants associated with or significantly restricted (P<0.01) to the dynamictype population structure were those linked to humid and shady environments suchas Alnus glutinosa, Anemone nemorosa, Asplenium onopteris, Blechnum spicant,Narcissus poeticus and Viola reichenbachiana. Many plants were significantlyassociated with stable type populations, among which hygrophilous herbaceousspecies such as Hypericum hircinum, Polystichum setiferum, Eupatorium cannabi-

Table 4 Multiple regression models with the percentages of each life stage as dependent variables andvegetation structure and environmental characteristics as independent variables. Regressions werecalculated at the level of plots. Only significant results are shown. The results of ANOVA for eachmultiple regression model were used to determine the significance of the regression. The analysis ofvariance table divides the total variation in the dependent variable into two components: one that can beattributed to the regression model (Regression) and one that cannot (Residual). If the significance level forthe F-test is low (less than 0.05), then the hypothesis that there is no (linear) relationship can be rejected

ANOVA

Variable β t P Source SS d.f. MS F-ratio P

Vegetative adult percentage

(R2=0.167) log-transformed Regression 5.90 7 0.843 2.818 0.0101

tree cover 0.325 3.058 0.002 Residual 29.31 98 0.299

Generative percentage

(R2=0.241) log-transformed Regression 13.57 7 1.939 4.465 0.0002

slope 0.214 2.289 0.024 Residual 42.56 98 0.434

tree cover -0.217 -2.138 0.034

shrub cover 0.267 2.611 0.010

Senescent percentage

(R2=0.221) log-transformed Regression 9.95 7 1.422 3.970 0.0007

boulders -0.238 -2.009 0.047 Residual 35.11 98 0.358

Ratio (Sp+Av/Ge+Se)

(R2=0.231) not transformed Regression 807.83 7 114.4 4.22 0.0004

slope -0.245 -2.593 0.010 Residual 2678.61 98 27.3

stones 0.248 2.186 0.031

shrub cover -0.237 -2.307 0.023

R2– the squared multiple regression coefficient, β – standardized regression coefficients, t – t-statistic,

SS – sum of squares, d.f. – degrees of freedom, MS – mean square, F-ratio – variance ratio,P – significance level.

60 M. Landi, C. Angiolini

num and Equisetum arvense and shrub species such as Crataegus monogyna, Ericascoparia, Rubus ulmifolius, and Sambucus nigra are worth mentioning. In contrast,meso-xerophile or pioneer species such as Castanea sativa, Populus tremula andPteridium aquilinum were significant indicators of senile populations.

Discussion

Methodology and Limitations

As stated in the introduction, very few studies of plant populations have aimed tospecifically test fern demography. Our study documented the life-stage structure ofOsmunda regalis by applying an original classification of life stages. Although thelife stages used in our study were identified specifically for the demographicstructure of O. regalis, this method may be applicable to other fern populations withsimilar morphology, as well as to different fern species, although in this case priorknowledge of the morphological structure indicative of the individual life stages is

Fig. 5 First two axes of the PCoA with passively projected species centroids (shown as dots; the plottedspecies are those with correlation with the ordination axes exceeding 0.5 in the absolute value) and plotsof the same population type indicated with different symbols, as shown in the ordination diagram. Arrowsfor the original scores on the PCoA axes are also displayed (the first two axes). Legend for species withabbreviations (letters in bold): Alnus glutinosa, Anemone nemorosa, Arbutus unedo, Athyrium filix-

foemina, Blechnum spicant, Calamintha sylvatica, Carex pendula, Carex remota, Castanea sativa,Clematis vitalba, Erica arborea, Fraxinus ornus, Hedera helix, Ilex aquifolium, Ostrya carpinifolia,Polystichum setiferum, Rubia peregrina, Rubus hirtus, Rubus ulmifolius, Ruscus aculeatus, Sambucus

nigra, Smilax aspera

Population structure of Osmunda regalis in relation to environment... 61

Table 5 Species affinity with dynamic, stable and senile populations of Osmunda regalis

Species Affinity with dynamicpopulations

Affinity with stablepopulations

Affinity with senilepopulations

Frequency I.V. P Frequency I.V. P Frequency I.V. P

Alnus glutinosa IV 52.6 ** IV IV

Anemone nemorosa III 43.9 ** II I

Aquilegia vulgaris I 9.2 * I

Asplenium onopteris II 40 ** I

Blechnum spicant IV 44.2 ** II II

Hypericum androsaemum II 27.5 * II I

Laurus nobilis I 7.4 *

Narcissus poeticus I 16.7 ** I

Ostrya carpinifolia I 13.3 *

Physospermum cornubiense III 31.5 * II I

Polypodium australe I 7.9 *

Polygonatum multiflorum I 7.9 *

Prenanthes purpurea I 19 * I I

Smilax aspera I 9.4 *

Viburnum tinus I 11 * I

Viola reichenbachiana II 27.9 ** I I

Brachypodium sylvaticum II III 34.9 * I

Calamintha sylvatica I II 24.3 **

Carpinus betulus I I 21.7 **

Carex microcarpa I I 11.4 *

Cornus sanguinea I 9.1 *

Crataegus monogyna I I 17 **

Cruciata glabra I I 19.2 **

Cruciata laevipes I I 13.1 *

Daphne laureola I 11.4 *

Equisetum arvense I I 11.4 **

Erica scoparia I I 17.5 ** I

Eupatorium cannabinum I II 32.1 ** I

Fraxinus angustifolia I I 10.2 *

Hedera helix V V 54.4 ** V

Hypericum hircinum I I 19.7 ** I

Juniperus communis I I 10.1 *

Melica uniflora II II 25.8 * I

Polystichum setiferum I II 23.1 ** I

Prunus avium I I 9.1 *

Pulicaria dysenterica I 9.1 *

Quercus cerris I 15.9 **

Quercus ilex II III 29.3 * I

Rhamnus alaternus I I 9.1 *

62 M. Landi, C. Angiolini

required. For example, the rootstocks of Osmunda can grow many centimetres highand can be used to classify the senescent life stage. Moreover, to find the sporangiain the field for the attribution of the generative life stage would require more timeand energy in ferns with non-dimorphic fronds. The limitation of this methodologyis that the field investigations cannot provide information about how O. regalis

population dynamics might change unless they are repeated. Having said this, thestructure of a population may be the result of environmental factors and as suchindicative of its demographic future (Brys et al. 2003).

Population Types, Population Structure and Distance

On the basis of the analyses carried out, three different local population types can bedistinguished for Osmunda regalis: dynamic, stable and senile. The senilepopulation type differs from that described by many other authors (e.g., Ostermeijeret al. 1994; Hegland et al. 2001; Jacquemyn et al. 2003) due to the high proportionof vegetative adults in addition to the senescent ones, although it is in line with thefindings of Endels et al. (2004).

Vegetative reproduction in clonal plants allows dispersal in both space and time,through the longevity of clones (see Price and Marshall 1999). We observed manyrhizomes horizontally connected with the large rootstocks of the senescent life stage.

Table 5 (continued)

Species Affinity with dynamicpopulations

Affinity with stablepopulations

Affinity with senilepopulations

Frequency I.V. P Frequency I.V. P Frequency I.V. P

Rubia peregrina II II 30.4 **

Rubus ulmifolius II III 48 **

Sambucus nigra I I 11.4 *

Solidago virgaurea I I 19.8 **

Stachys officinalis I 9.1 *

Carex pallescens II I II 35.4 **

Castanea sativa IV III V 54.3 **

Frangula alnus I I II 23.3 *

Fraxinus ornus V IV V 52.3 *

Mercurialis perennis I I 12.5 *

Populus nigra I I 8.3 *

Populus tremula I I III 26.7 **

Pteridium aquilinum IV IV V 69.1 **

Rubus hirtus IV III V 49 *

Athyrium filix-foemina IV 36.6 n.s. III 30.5 n.s. I

Carex remota IV 32.4 n.s. III III 33.3 n.s.

Ilex aquifolium IV 37.2 n.s. III IV 34.7 n.s.

INSPAN Value (I.V.), * – P<0.05, ** – P<0.01, n.s. – not significant.

Population structure of Osmunda regalis in relation to environment... 63

The high proportion of ramets classified as adults vegetative in senile populationsmay also be due to the contribution of ramets arising from rhizomes that werephysiologically interconnected to the mother plant (Watson 1986). The proportion ofsporelings was low in all population types and always lower than the proportion ofvegetative adults maybe because the young sporophytes of ferns are exposed tohazards that are usually more severe than those experienced by the establishedsporophyte, e.g. susceptibility to competitive pressure from the surroundingvegetation and to submergence by leaf litter from deciduous trees (Grime 1985).The reduced abundance of sporelings in relation to other life stages is also due to thedifference in dynamics between individuals and ramets. For example, a rametsporeling corresponds to a single individual but a senescent ramet is a functional unitthat is repeated (one or several ramets) for each large rootstock. In many studies ofclonal species populations (see Falińska 1995; Barkham 1980; Czarnecka 2008), theincrease in numbers of individuals follows a logistic model, while that of rametsfollows an exponential model. Consequently a senile population with a relativelystable number of rootstocks may have a high production of ramets classified asvegetative adult, generative or senescent. Nevertheless, the large proportion of thesenescent stage in comparison to the generative stage and the high proportion ofvegetative adults in senile populations could indicate a successful recruitment year,or the inability of individuals to proceed into the generative life stage (Willmot 1985;Endels et al. 2004), possibly in response to the deterioration of habitat conditions.

The total population structure demonstrated a life-stage spectrum that can beinterpreted as stable. Confirmation of this distinction was provided by the dataanalyzed, which indicated that the local population types differ in their demographicstructure and in the structure and composition of vegetation, environmentalconditions and habitat types.

The increase in the proportion of the senescent life stage and the lowestabundance of ramets in populations more distant from the others (see Landi andAngiolini 2008) could be associated with their local regression.

Relation with Habitat, Environmental and Vegetational Variables

From the point of view of floristic composition, the three population types are verysimilar and reflect a predominance of azonal vegetation. However, the speciescomposition of the surrounding vegetation is associated to some degree with thestructure of Osmunda regalis populations. Nemoral species and species linked toAlnus glutinosa hygrophilous and riparian woods are mainly found in sites in whichthe species has a dynamic population structure, whereas many hygrophilousherbaceous species and shrubs are associated with stable populations. Some lesshygrophilous species, such as Pteridium aquilinum (a pioneer fern that colonizessenescent O. regalis rootstocks; pers. observation), Populus tremula (a pioneer treespecies) and Castanea sativa are mainly restricted to senile populations. We alsoobserved that in O. regalis each life stage has a different response to environmentalvariables (see also Cinquemani Kuehn and Leopold (1993) regarding Phyllitis

scolopendrium) and distinct life cycles can adapt to the different habitats theyoccupy. The negative relationship between the generative life stage and tree coverindicates that the open patches in vegetation are those most favourable for the

64 M. Landi, C. Angiolini

production of fertile fronds. Slope was found to be a positive factor for reaching thegenerative life stage and indicates that upstream stretches of streams on slopes withaquifer discharges and spring swamps provide favorable conditions for the species inthis stage. Stable populations mainly develop in habitats rich in hygrophilousherbaceous species and shrubs, with low tree cover and sedimentation. Springswamps are characterized by higher densities of ramets than ditches and streams (seeLandi and Angiolini 2008), and by a high proportion of senile populations. Thisreinforces the hypothesis that spring swamps are habitats with the stableenvironmental conditions required for the species to reach the senescent life stage.Field observations suggest that, as well as the probable impact of climatic changesfor rare non-Mediterranean species occurring at the southern margin of their range inEurope (Lavergne et al. 2006), the consequences of external disturbances could alsobe a main reason behind the structure of the senile type populations (Aguraiuja et al.2008), as in summer many senile populations are subject to significant interception/captation of water due to their presence in spring habitats. In contrast, there is apositive relationship between the percentage of sporelings and vegetative adults (seeratio) and stones. The streams investigated here which, compared to spring swamps,had a higher proportion of dynamic type populations, consisted of ditches andheadwaters with favourable conditions for O. regalis (i.e., continuous flow of waterensured by their link to spring swamps situated further upstream). However, thesepopulations are subject to flood disturbances, to the transformation caused byupstream erosion and downstream sedimentation processes, and are characterized bydense forest cover. All these factors can influence the development and the stabilityof populations in streams, where species’ survival can be linked to local colonizationand extinction events caused by flood disturbances and succession of vegetation (seealso Jäkäläniemi et al. 2005).

Conservation Strategies

Our results indicate that the local populations of Osmunda regalis currently varyfrom dynamic to senile, with distinct proportions and conditions in different habitats.Significant relationships between the surrounding vegetation and the populationtypes indicate that variation in floristic composition can be used as a predictor for theO. regalis population structure to some extent (see also Odland 2007).

The populations in spring swamps are remnant populations that remain stable dueto great individual longevity, as long as environmental conditions do not changedrastically. Compared to stream habitats, spring swamps seem to be the best andsafest sites for completion of the life cycle. Cousens et al. (1988) observed thatgreater inundation may restrict parts of the habitat providing safe sites forcolonization and completion of the life cycle of Lorinseria areolata; we assumethat the recurrent flooding of stream habitats can hinder the persistent and regularcompletion of the Osmunda regalis life cycle.

Aguraiuja et al. (2008) suggested that the regressive populations distinguished bythe smallest number of individuals have a higher probability of extinction. We alsopresume that the dynamic populations in streams with lower densities of ramets(Landi and Angiolini 2008) have a high risk of extinction because the conditions arenot suitable for all Osmunda life cycles. Thus, these dynamic populations can only

Population structure of Osmunda regalis in relation to environment... 65

survive in virtue of a continuous supply of propagules from spring swamps and themaintenance of unaltered spring swamps is therefore an indispensable requisite forthe regional conservation of O. regalis under the current Mediterranean climate.

References

Aguraiuja R, Moora M, Zobel M (2004) Population stage structure of Hawaiian endemic fern taxa Diellia(Aspleniaceae); implications for monitoring and regional dynamics. Canad J Bot 82:1438–1445

Aguraiuja R, Zobel M, Zobel K, Moora M (2008) Conservation of the endemic fern lineage Diellia

(Aspleniaceae) on the Hawaiin Island: can population structure indicate regional dynamics andendangering factors? Folia Geobot 43:3–18

Barkham JP (1980) Population dynamics of the wild daffodil (Narcissus pseudonarcissus). II. Changes innumber of shoots and flowers, and the effect of bulb on growth and reproduction. J Ecol 68:635–664

Berry EJ, Gorchov DL, Endress BA, Stevens MHH (2008) Source-sink dynamics within a plantpopulation: the impact of substrate and herbivory on palm demography. Populat Ecol 50:63–77

Brys R, Jacquemyn H, Endels P, Hermy M., De Blust G (2003) The relationship between reproductivesuccess and demographic structure in remnant populations of Primula veris. Acta Oecol 24:247–253

Cascante-Marín A, Wolf JHD, Oostermeijer JGB, den Nijs JCM, Sanahuja O, Durán-Apuy A (2006)Epiphytic bromeliad communities in secondary and mature forest in a tropical premontane area. BasicAppl Ecol 7:520–532

Cinquemani Kuehn DM, Leopold DJ (1993) Habitat characteristics associated with Phyllitis scolopen-

drium (L.) Newm. var. americana Fern. (Aspleniaceae) in central New York. Bull Torrey Bot Club

120:310–318Colling G (2005) Red list of the vascular plants of Luxembourg. Ferrantia 42, LuxembourgConti F, Manzi A, Pedrotti F (1997) Liste rosse regionali delle piante d’Italia. WWF, S.B.I., CamerinoCousens MI, Lacey DG, Scheller JM (1988) Safe sites and the ecological life history of Lorinseria

areolat. Amer J Bot 75: 797–807Czarnecka B (2008) Spatiotemporal patterns of genets and ramets in a population of clonal perennial

Senecio rivularis: plant features and habitat effects. Ann Bot Fenn 45:19–32Dufrêne M, Legendre P (1997) Species assemblages and indicator species. The need for a flexible

asymmetrical approach. Ecol Monogr 67:345–366Eckstein RL, Danihelka J, Hölzel N, Otte A (2004) The effects of management and environmental

variation on population stage structure in three river-corridor violets. Acta Oecol 25:83–91Elzinga CL, Salzer DW, Willoughby JW, Gibbs JP (2001) Monitoring plant and animal populations.

Blackwell Science, Inc., Malden, MassachusettsEndels P, Jacquemyn H, Brys R, Hermy M (2004) Impact of management and habitat on demographic

traits of Primula vulgaris in agricultural landscape. Appl Veg Sci 7:171–182Falińska K (1995) Genet disintegration in Filipendula ulmaria: consequences for population dynamics and

vegetation succession. J Ecol 83:9–21Fernández H, Bertrand AM, Sánchez-Tamés R (1997) Gemmation in cultured gametophytes of Osmunda

regalis. Pl Cell Rep 16:358–362García D, Zamora R, Hódar JA, Gómez, JM (1999) Age structure of Juniperus communis L. in the Iberian

peninsula: Conservation of remnant populations in Mediterranean mountains. Biol Conservation

87:215–220García D, Zamora R, Hódar JA, Gómez JM, Castro J (2000) Yew (Taxus baccata L.) regeneration is

facilitated by fleshy-fruited shrubs in Mediterranean environments. Biol Conservation 95:31–38.Gatsuk LE, Smirnova OV, Vorontzova LI, Zaugolnova LB, Zhukova LA (1980) Age states of plants of

various growth forms: a review. J Ecol 68:675–696Grime JP (1985) Factors limiting the contribution of pteridophytes to a local flora. Proc Roy Soc

Edinburgh B, 86:403–421Hardalova R (2004) National report of Bulgaria. In Convention on the Conservation of European Wildlife

and Natural habitats, Group of experts on the conservation of plants. Valencia (Spain), 19 September

2004. National Reports. Council of Europe, StrasbourgHarrison S, Maron J, Huxel G (2000) Regional turnover and fluctuation in populations of five plants

confined to serpentine seeps. Conservation Biol 14:769–779

66 M. Landi, C. Angiolini

Hegland SJ, van Leeuwen M, Oostermeijer JGB (2001) Population structure of Salvia pratensis in relationto vegetation and management of Dutch dry floodplain grasslands. J Appl Ecol 38:1277–1289

Hooftman DAP, van Kleunen M, Diemer M (2003) Effects of habitat fragmentation on the fitness of twocommon wetland species, Carex davalliana and Succisa pratensis. Oecologia 134:350–359

Jacquemyn H, Brys R, Hermy M (2002) Patch occupancy, population size and reproductive success of aforest herb (Primula elatior) in a fragmented landscape. Oecologia 130:617–625

Jacquemyn H, Van Rossum F, Brys R, Endels P, Hermy M, Triest L, De Blust G (2003) Effects ofagricultural land use and fragmentation on genetics, demography and population persistence of therare Primula vulgaris, and implications for conservation. Belg J Bot 136:5–22

Jäkäläniemi A, Tuomi J, Siikamäki P, Kilpiä A (2005) Colonization-extinction and patch dynamics of theperennial riparian plant, Silene tatarica. J Ecol 93:670–680

Klekowski EJ Jr (1967) Observations on pteridophyte life cycles: relative lengths under culturalconditions. Amer Fern J 57:49–51

Klekowski EJ Jr (1970) Populational and genetic studies of a homosporous fern-Osmunda regalis. Amer JBot 57:1122–1138.

Klekowski EJ Jr (1973) Genetic load in Osmunda regalis populations. Amer J Bot 60:146–154Landi M, Angiolini C (2007) Contributo alla conoscenza della distribuzione di Osmunda regalis L. in

Toscana. Inform Bot Ital 39(1):113–122Landi M, Angiolini C (2008) Habitat characteristics and vegetation context of Osmunda regalis L. at the

southern edge of its distribution in Europe. Bot Helv 118:43–55Lavergne S, Molina J, Debussche M (2006) Fingerprints of environmental change on the rare

Mediterranean flora: a 115-year study. Global Change Biol 12:1466–1478Legendre P, Legendre L (1998) Numerical ecology, Development in environmental modelling, 20. Ed. 2.

Elsevier Academic Press, AmsterdamLepš J, Šmilauer P (2003) Multivariate analysis of ecological data using CANOCO. Cambridge

University Press, CambridgeLienert J, Diemer M, Schmid B (2002) Effects of fragmentation on structure and fitness components of the

wetland specialist Swertia perennis L. (Gentianaceae). Basic Appl Ecol 3:101–114Lloyd RM, Klekowski EJJr (1970) Spore germination and viability in pteridophyta: evolutionary

significance of chlorophyllous spores. Biotropica 2:129–137McCune B, Mefford MJ (1999) PCORD for Windows: Multivariate analysis of ecological data, Version

4.0. MjM Software, Gleneden Beach, OregonMcVeigh I (1937) Vegetative reproduction of the fern sporophyte. Bot Rev 3:457–497Menges ES (1990) Population viability analysis for an endangered plant. Conservation Biol 4:52–62Menges E, Dolan RW (1998) Demographic viability of populations of Silene regia in midwestern prairies:

relationships with fire management, genetic variation, geographic location, population size andisolation. J Ecol 86:63–78

Menges ES, Gordon DR (1996) Three levels of monitoring intensity for rare plant species. Nat Areas J16:227–237

Moora M, Kose M, Jõgar Ü (2007) Optimal management of the rare Gladiolus imbricatus in Estoniancoastal meadows indicated by its population structure. Appl Veg Sci 10:161–168

Mróz L (2006) Variation in stage structure and fitness traits between road verge and meadow populationsof Colchicum autumnale (Liliaceae): effects of habitat quality. Acta Soc Bot Poloniae 75:69–78

Mueller-Dombois D, Ellenberg H (1974) Aims and methods of vegetation ecology. John Wiley, New YorkNoest V, van der Maarel E, van der Meulten F, van der Loan D (1989) Optimum transformation of plant

species cover abundance values. Vegetatio 83:167–178Odland A (2007) Geographical variation in frond size, rootstock density, and sexual reproduction in

Matteuccia struthiopteris populations in Norway. Populat Ecol 49:229–240Odland A, Naujalis JR, Stapulionyte A (2006) Variation in the structure of Matteuccia struthiopteris

populations in Lithuania. Biologija 1:83–90Oostermeijer JGB, van’t Ver R, den Nijs JCM (1994) Population structure of the rare, long-lived perennial

Gentiana pneumonanthe in relation to vegetation and management in the Netherlands. J Appl Ecol

31:428–438Page CN (2002) Ecological strategies in fern evolution: a neopteridological overview. Rev Palaeobot

Palynol 119:1–33Pichi Sermolli REG (1970) Appunti sulla costituzione e genesi della flora pteridologica delle Alpi

Apuane. Lav Soc Ital Biogeogr 1:88–126Podani J, Miklós I (2002) Resemblance coefficients and the horseshoe effect in principal coordinates

analysis. Ecology 83:3331–3343

Population structure of Osmunda regalis in relation to environment... 67

Price EA, Marshall C (1999) Clonal plants and environmental heterogeneity. Pl Ecol 141: 3–7.Rabotnov TA (1969) On coenopopulations of perennial herbaceous plants in natural coenoses. Vegetatio

19:87–95Rameau JC, Mansion D, Dumé G (1993) Flore forestière française: guide écologique illustré, 2. Institut

pour le Développement Forestier, ParisRünk K, Moora M, Zobel M (2006) Population stage structure of three congeneric Dryopteris species in

Estonia. Proc Estonian Acad Sci Biol Ecol 55:15–30Schemske DW, Husband BC, Ruckelshaus MH, Goodwillie C, Parker IM, Bishop JG (1994) Evaluating

approaches to the conservation of rare and endangered species. Ecology 75:584–606Shorina NI (2001) Population biology of gametophytes in homosporous polypodiophyta. Russ J Ecol

32:164–169Smirnova OV, Palenova MM, Komarov AS (2002) Ontogeny of different life forms of plants and specific

features of age and spatial structure of their populations. Russ J Developmental Biol 33:1–10Sokal RR, Rohlf FJ (1995) Biometry. Ed. 3. W.H, Freeman and Company, New YorkStatSoft Inc. (2001) STATISTICA (data analysis software system), version 6.0. Available at: http://www.

statsoft.comter Braak CJF, Šmilauer P (2002) CANOCO reference manual and CanoDraw for Windows user’s guide:

software for canonical community ordination, Version 4.5. Microcomputer Power, Ithaca, New YorkTutin TG, Heywood VM, Burges NA, Valentine DH, Walters SM, Webb DA (1968) Flora Europaea.

Cambridge University Press, CambridgeTutin TG, Burges NA, Charter AO, Edmondson JR, Heywood VH, Moore DM, Valentine DH, Walters

SM, Webb DA (1993) Flora Europea 1. Cambridge University Press, CambridgeVoeller BR (1964) Antheridiogens in ferns. In Nitch JP (ed) Regulateurs naturels de la croissance

végétale. Centre National de la Recherche Scientifique, Paris, pp 665–684Warner BG, Rubec CDA (eds) (1997) The Canadian wetland classification system. Ed. 2. Canadian

National Wetlands Working Group, Wetlands Research Centre, University of Waterloo, WaterlooWatson MA (1986) Integrated physiological units in plants. Trends Ecol Evol 1:119–123.Willmot A (1985) Population dynamics of woodland Dryopteris in Britain. Proc Roy Soc Edinburgh B,

86:307–313Wolf PG, Schneider H, Ranker TA (2001) Geographic distributions of homosporous ferns: does dispersal

obscure evidence of vicariance? J Biogeogr 28:263–270Zenkteler E (1999) Sporophytic Lethality in Lowland Populations of Osmunda regalis L. in Poland. Acta

Biol Cracov, Ser Bot 41:75–83Zheleznaya EL (2009) Changes in the structure of a Dactylorhiza incarnata (L.) Soó population during the

overgrowing of a meadow-bog community complex in the Moscow region. Russ J Ecol 40:39–43

Received: 14 July 2009 /Revised: 19 April 2010 /Accepted: 23 April 2010 /Published online: 14 September 2010

68 M. Landi, C. Angiolini