Abstract
The recognition of the ecological quality of ecosystems and habitats therein is increasingly important in the Anthropocene. However, there are still scarcely explored ways of how and what to assess to obtain a sound ecological status of habitats. Ferns are an understudied plant group, especially given their usefulness as ecological indicators. Disentangling biotic and abiotic factors that drive fine-scale fern distribution could provide insight into the quality of their habitats. We investigated the environmental factors affecting the distribution of different largely distributed fern species in Europe. We studied their presence and abundance at different life stages in a forest habitat of European priority conservation concern. Our aim was to understand whether fern species can be used as an ecological indicator group in riparian alderwood habitat. We sampled 120 plots of 50 m2 in randomly selected transects along streams of a riparian forest habitat characterized by the presence of many fern species in the understory, controlling for the effects of geology and elevation. Within each plot, fern species were recorded, including vegetative and generative stages of each ramet (rosette of fronds). We modelled fern occurrence and abundance for the different fern life stages, and diversity indices of the fern community in relation to environmental predictors. We found that population- and community-level responses of ferns mainly depended on soil granulometry and, to a lesser extent, moss cover and stream orientation. We also found that the generative life stage compared to the vegetative adult stage benefits from different ecological characteristics for certain fern species. Alterations of the natural hydrology might lead to a general deterioration in habitat quality for ferns. We suggest that some fern species acting as early-warning species, and potentially their life stages, can be used as an ecological quality indicator for riparian forest habitats. This study deepened the understanding of the fine-scale ecology of an array of European ferns in riparian forests and provides valuable information to assist in the conservation of fern species and their populations.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Ferns contribute widely to biodiversity, with some 12,000 species making them the second-largest group of vascular plants after angiosperms (PPG I 2016). Ferns are widely distributed around the globe with some species being ubiquitous, aside from poles and deserts (Moran 2008).
Generally, abiotic factors drive fern species distribution patterns at all scales (Karst et al. 2005). Their distribution responds more directly to edaphic and other environmental factors than to geographic distance between sample sites, partly due to the wind-borne dispersal of spores, which makes ferns less dispersal-limited than other plants (Higgins et al. 2011; Jones et al. 2006; Tuomisto et al. 2003). The role of edaphic factors, including the underlying geology which impacts soil composition, is significant for ferns (Jones et al. 2006; Tuomisto et al. 2003). Although soil granulometry does not seem to be physiologically important for ferns, it correlates with other soil properties such as water, and nutrient retention and release (Zuquim et al. 2014). However, literature about fine-scale distribution of ferns in relation to soil granulometry is scanty.
Fern species distribution is influenced by orientation, which in turn affects light and heat (Sharpe and Shiels 2014). Previous studies have shown how populations of Osmunda regalis are favoured by north-east orientation as a combined effect of lower insolation and protection from dry summer winds (Landi and Angiolini 2008). Elevation gradients also have a profound effect on fern species distribution (Kessler 2000; Nervo et al. 2016; Rahbek 1995, 2005). Further, water largely contributes to the distribution of ferns because it is a necessary element for reproduction and growth (Kessler 2000). However, although earlier studies identified environmental factors driving fern distribution at a large scale, few studies have been conducted to investigate ecological responses that drive their distribution at the fine-scale (Barrington 1993; Kessler et al. 2011; Hernández-Rojas et al. 2020).
The influence of abiotic factors greatly contributes to shape the structure of fern populations. Plant population structure can be used as a means of addressing the demographics and thus the status of the population, often in the context of species conservation (Eckstein et al. 2004; Moora et al. 2007). Also, population structure is a more efficient and time-effective approach to analyse the demographics of the plant community than a full demographic study. Nevertheless, a few European studies have investigated fern population structure, and specifically fern life stages (Bucharová et al. 2010; Landi and Angiolini 2011; Rünk et al. 2006). Habitat characteristics associated with the life stage of a fern species are even less investigated (Cinquemani Kuehn and Leopold 1993; Landi and Angiolini 2011). The remaining studies investigated fern population structure as a means of describing the conditions of the populations by characterizing regional fern population dynamics (Aguraiuja et al. 2004, 2008; Bucharová et al. 2010; Rünk et al. 2006). Importantly, different life stages of fern species have distinct fine-scale habitat preferences (Cinquemani Kuehn and Leopold 1993; Landi and Angiolini 2011). Thus, if the success of species conservation depends on the knowledge about their ecology, an approach for the conservation of ferns must take into consideration a combination of life stages classes, meaning the abundance of sporophytes in each developmental stage of a fern’s life history, and habitat features.
The close relationship between fern occurrence and environmental factors makes ferns good bioindicators (Della and Falkenberg 2019; Higgins et al. 2011; Zuquim et al. 2014). Ferns have been used as environmental indicators for vegetation, soils, environmental integrity, climate change, association with other organisms or contamination of air, soil or water (Della and Falkenberg 2019). However, most studies focus on the tropics, where the most diverse array of ferns can be found (Jones et al. 2006; Ruokolainen et al. 1997; Tuomisto et al. 2002, 2003). Accordingly, the ecological knowledge of fern drivers in non-tropical ecosystems is relatively incomplete.
Studies assessing biotic and abiotic predictors of fern occurrence and abundance at fine scale can improve predictive models of fern distribution at wider, e.g. continental or global, scales. Our work concerns ten fern species widely distributed in Europe. We expect the presence of ferns with vegetative and generative sporophytes to reflect moisture and the different water dynamics, which characterize riparian alderwood habitats. By looking at factors influencing fern distribution measured on a fine scale, we might infer their predictive power as early-warning species and suggest particular species as ecological indicators of the investigated habitat. We aim to pinpoint environmental factors affecting fern communities and fern distribution in a riparian forest habitat of conservation interest. Specifically, we asked: (1) Which environmental factors in riparian Alnus glutinosa forest habitat drive fern species presence and abundance and their various life stages? (2) Do fine-scale fern responses help assess habitat conservation status?
Material and methods
Study area
The study area is located in the provinces of Siena and Grosseto (central Italy), at an elevation that ranges from 250 to 600 m a.s.l. The geology is composed of acidic sedimentary rocks affected by low-grade metamorphism (Carmignani et al. 2013). The macroclimate is classified as temperate, with a strong submediterranean influence (Pesaresi et al. 2017). Mean temperature ranges from 22.5 °C in July to 5.7 °C in January. Precipitation varies with seasonality, with winter months being wetter (60–90 mm/month) than the summer months (20–40 mm/month) (Climate-Data 2021). The area is characterized by a low human density, by the absence of industrial activities and by a well-conserved fluvial ecosystem. The study area is included in two Special Areas of Conservation (SACs) interest of the Natura 2000 network of protected areas (Alta Val di Merse—IT5190006 and Val di Farma—IT51A0003). Furthermore, sections of these Natura 2000 sites are categorized as Nature Reserves (Fig. S1 of the Supplementary material).
The area is almost entirely covered by mixed forests dominated by Castanea sativa, Quercus cerris and Q. petraea, while the upper and drier areas are dominated by pine forests of Pinus pinaster. The dominant broadleaf species occurring in the stream habitat is Alnus glutinosa, followed in decreasing order of frequency by Fraxinus ornus, C. sativa, Q. ilex, Carpinus betulus, Corylus avellana, Q. cerris and Q. petraea. The most frequent shrub species are Ilex aquifolium, Rubus hirtus and Frangula alnus. The habitat object of this study named “Alluvial forests with Alnus glutinosa and Fraxinus excelsior (Alno-Padion, Alnion incanae, Salicion albae)”, is considered of priority importance in the list of European habitats of conservation interest (Natura 2000 code: 91E0; Habitats Directive 92/43/EEC) and it is included to the EUNIS habitat “Alnus glutinosa–Alnus incana forest on riparian and mineral soils” (code T12; Chytrý et al. 2020). At least in the Mediterranean, this habitat is characterized by periodical inundations but is otherwise well-drained. It requires oligotrophic waters and occurs in the upper and middle part of the streams, where erosion prevails on sedimentation, thus contrasting with the riparian woods with Salix spp. and Populus spp. occurring in lower parts of rivers and streams where, on the contrary, sedimentation prevails on erosion. From the syntaxonomic point of view, this forest type is classified to the alliance Osmundo-Alnion glutinosae in the order Populetalia albae of the class Alno glutinosae-Populetea albae (Landi and Angiolini 2010; Mucina et al. 2016; Preislerová et al. 2022). This alliance occurs on acidic soils, and it is characterized by the presence of numerous fern species in the understory. Three fern species, Dryopteris carthusiana, Equisetum telmateia and Osmunda regalis occurring in our study area, are listed among the diagnostic species of the habitat for Italy according to the “Italian Interpretation Manual of the 92/43/EEC Habitats Directive” (Biondi et al. 2009).
Study species
We detected 14 native fern species largely distributed in Europe (Table 1). For species-specific responses, ecological investigation was possible for 10 fern species found in more than 10 plots. Fern species detected in this study are reported in Fig. 1. The overall number of ramets recorded in sampling plots and the number of plots with ramets for each fern are reported in Table 2. Distribution of the fern species is in accordance with Plants of the World Online (PoWO, 2019). Biological forms follow Pignatti et al. (2017). Nomenclature follows the Portal to the Flora of Italy (Portal to the Flora of Italy, 2021).
Fern species considered in this study. The species are sorted alphabetically. a Asplenium onopteris; b Asplenium trichomanes; c Athyrium filix-femina; d Dryopteris affinis; e Dryopteris borreri; f Osmunda regalis; g Polypodium interjectum; h Polystichum setiferum; i Pteridium aquilinum; j Struthiopteris spicant. Photo credits: G. Bonari (a, b, c, d, f, i), Portal to the Flora of Italy (j, e, g, h)
Sampling design and data collection
To investigate the effect of physical variables affecting the distribution of ferns, meaning to consider streams with similar ecological conditions, the perennial character of each of the streams investigated in our study was preliminary ascertained. To nullify the effect of particular environmental variables acting on ferns such as geology and elevation (Kessler 2000; Nervo et al. 2015; Tuomisto et al. 2003), sampling was conducted from mid-June to mid-August on plots within transects of similar elevation ranges and in a geologically homogeneous area. We thus selected twenty-two stream sections with similar slope (8–10%) and elevation (350–390 m a.s.l., from the lower to the upper part of the transect). We randomly selected four transects for each main orientation of the streams (i.e., North, East and South). Thus, twelve transects (n = 12) were selected out of the twenty-two possible. No westerly-oriented streams were present in the study area. A 250 m-transect was overlaid in the longitudinal direction along each stream section. In each transect, 10 sampling plots of 50 m2 (5 × 10 m, perpendicular to water flow/running) were equally spaced at intervals of 20 m; thus, a total of 120 plots were made. The 10 m-wide plots encompassed both sides of each stream, thus including the whole fine-scale habitat variability: streambed, mid-slope, upper-slope. No epiphytic ferns were present in our study area.
For each plot we recorded tree, shrub, herbaceous and moss cover (%) as visual groundcover projected vertical estimation, including rocks, stumps and logs, and (sub-)horizontal surfaces for mosses. However, the cover of the shrub and herbaceous layers was not included in the statistical analysis. Shrub and herbaceous cover were deemed of low importance due to their low median coverage (6% for shrub cover; 5% for herbaceous cover), as opposed to the median tree cover of 85%. Moreover, only the tree cover could be used as a proxy for light availability. Moss cover was recorded because it is a proxy of humidity (Given 1993). In our sampling plots, we also recorded soil granulometry, i.e. soil sediment size (%) of sand (< 2 mm in diameter), gravel (2 mm to 7.6 cm in diameter), cobbles (7.6–25 cm in diameter), stones (25–60 cm in diameter), and boulders (> 60 cm in diameter), following the USDA system (Ditzler et al. 2017). Preliminary observations of soil sediment size distribution in sampling plots suggested the occurrence of three distinct categories of soils. We used a k-mean cluster analysis based on the soil granulometric variables to identify sampling plots belonging to soils with a prevalence of large-grained sediments (mainly boulders and stones; n = 39 plots), soils with a prevalence of fine-grained sediments (mainly sand and gravel; n = 28 plots) and soils with a prevalence of mixed-grained sediments, i.e. with an even distribution of all soil granulometric classes of sediments (n = 53 plots).
Within each plot, we recorded the life stages of each ramet (rosette of fronds) of the fern species: vegetative, generative and senile. However, this latter life stage was never found. In our sampling, we recorded the sporophytes only when an unequivocal determination to the species level was possible directly in the field, meaning that we did not consider young sporophytes with unclear or difficult attribution to a fern species due to the lack of identification characters. To quantify fern responses at the community-level, we calculated for each plot several indices of ecological diversity (Chao 1984; Legendre and Legendre 2012): richness (raw number of species), Chao-1 richness, Shannon diversity (H) and Simpson’s dominance (D).
Statistical analyses
We investigated factors affecting population- and community-level responses of ferns in sampling plots using generalized linear mixed models (GLMMs; Zuur et al. 2009). We analysed two response variables for population-level responses: probability of presence and abundance of ramets, in each sampling plot. We modelled occurrence of ramet using binomial errors (link: logit) and ramet abundance using negative binomial errors (link: log), as customarily done when modelling presence/absence and count data, respectively. Models were fitted separately for the two vegetative stages of each species and for total fern ramets of each species. Population-level models could not be run for four species (Asplenium scolopendrium, Dryopteris dilatata, Equisetum telmateia, and Polypodium cambricum), and for abundance of generative ramets of Pteridium aquilinum, because inherent data included almost only 0 counts and models did not converge. Therefore, the ecological investigation was carried out for the remaining 10 fern species. For community-level responses, we used as response variables ecological indices calculated in each sampling plot. Richness, i.e. the number of species, was modelled through negative binomial errors (link: log), Shannon diversity and Chao-1 richness through gaussian errors (link: identity), and Simpson’s dominance using beta errors (link: log), following rule of thumb to model count data, real numbers and continuous variables bounded in the 0–1 range.
In all cases, for both population- and community-level and responses, we tested whether our response variables varied according to potentially influencing predictors while accounting for repeated measures conducted in each transect as a random intercept. Thus, random intercepts allowed the estimation of an average effect of each predictor in all transects. In each global model, we included four fixed effects that are known to be relevant predictors of fern distribution: (1) orientation (categorical; reference level: east-oriented streams); (2) cover of the tree layer (continuous, as %); (3) moss cover (continuous, as %); (4) soil sediment size (categorical; reference level: soil with even distribution of soil granulometric classes). We found no multicollinearity (r <|0.5|; VIFs < 3) between covariates. Continuous explanatory variables were scaled to improve model convergence and allow comparing the relative importance of each predictor.
For each full model, we performed a model selection according to the information-theoretic approach. Each model evaluated, including a different combination of predictors, could represent a different, biologically meaningful a priori hypothesis (Harrison et al. 2018). All the possible combinations between predictors were ranked and weighted from the full model (number of models run per full model: 24 = 16, where 4 is the number of predictors). The null model was also included, to allow comparing model performance relative to a fixed baseline (Mac Nally et al. 2018). Model selection was performed using the minimum Akaike’s Information Criterion corrected for small samples (AICc: Burnham and Anderson, 2002), a metric which considers both model parsimoniousness and goodness of fit (Aho et al. 2014). We followed the ‘nesting rule’ to avoid retaining overly complex models (Harrison et al. 2018), thus we did not select models with ΔAICc ≥ 2 with respect to the best model (the model with the lowest AICc value), and models with an AICc value greater than any simpler alternative. We achieved either a set of top-ranked models or a single best model for each response variable. For each model, the weight, meaning the probability that a given model is the best model, was standardized within the subset of selected models. Selected models are reported in the Supplementary material (Tables S1–S11). For each best model, we estimated coefficients of predictors, 95% confidence intervals and variance of random effects from the top-ranked, namely the best model. The effects of predictors were assessed by checking whether 95% confidence intervals of coefficients overlapped 0. Best models were validated by checking residual patterns (Zuur et al. 2009). We performed model selection and GLMMs through the R packages MuMIn (Bartoń 2012) and glmmTMB (Brooks et al. 2017), respectively.
Considering that positive or negative association between pairs of fern species may arise from similar or opposite responses to environmental factors, we tested potential interspecific associations in abundance using Spearman's correlation on the number of ramets recorded in sampling plots.
Results
The most frequent and abundant ferns were Athyrium filix-femina and Polystichum setiferum (Table 2), both occurring in 52 plots, with 277 and 327 total ramets, respectively. A representative scheme of how ferns occurred in streams is reported in Fig. 2.
Scheme of the main fern species distribution in north-oriented streams: Asplenium onopteris (Ao), Asplenium trichomanes (At), Athyrium filix-femina (Af), Dryopteris affinis (Da), Osmunda regalis (Or), Polypodium interjectum (Pi), Polystichum setiferum (Ps), Pteridium aquilinum (Pa), Struthiopteris spicant (Ss). Dryopteris borreri is not represented in the scheme because it seems to replace D. affinis in south-oriented streams. Image credits: M. Landi
Top-ranked models explaining abundance and presence of ferns are summarised in Table 3 (see Tables S12–S21 of the Supplementary material for more details). Fern responses to potential environmental drivers were often species-specific, with most of them responding to soil sediment size.
For five fern species, including Asplenium onopteris, A. trichomanes, Dryopteris affinis, Polypodium interjectum, and P. setiferum, ramet abundance increased in large-grained soils or decreased in fine-grained soils, either for at least one of the life stages or for the total ramets (Fig. 3). D. borreri abundance, on the other hand, decreased at sites with large-grained soils (Fig. 3d), although such decrease did not occur when vegetative and generative ramets were considered separately.
Effect of soil sediment size (granulometry) on population (a–f) and community (g–h) responses of ferns. Dot and error bar depict observed mean and standard error. Only fern responses significantly influenced by soil sediment size are reported. Asterisk denotes when the abundance is referred to as generative ramets
Abundance of three fern species responded to moss cover either for one of the life stages or for the total ramets: D. affinis and P. setiferum ramets increased with increasing moss cover (Fig. 4a, b), whereas P. aquilinum ramets decreased with increasing moss cover (Fig. 4c).
Moss cover effect on population (a–c) and community (d) responses of ferns. Dot and error bar depict observed mean and standard error. Only fern responses significantly influenced by moss cover are reported. Moss cover was grouped in three classes arbitrarily to improve graphical interpretation. Asterisk denotes when the abundance is referred to as generative ramets
Abundance of D. affinis and P. interjectum also depended on orientation, with D. affinis ramets decreasing in south-oriented streams (Fig. 5a) and P. interjectum ramets decreasing in north-oriented streams (Fig. 5b).
Two fern species showed life stage-specific effects on ramets abundance (Table 3). For D. affinis, vegetative ramets decreased in fine-grained soils, while generative ramets increased with moss cover. In P. interjectum, vegetative ramets decreased in north-oriented plots, whilst generative ramets increased in large-grained soils.
Compared to models predicting fern abundance, models predicting probability of fern presence generally provided consistent results, although the effect of soil sediment size often disappeared for some species (Table 3). Apart from A. onopteris, whose presence probability decreased in fine-grained soils, the presence probability of four fern species was determined by stream orientation or moss cover. The probability of presence for A. trichomanes increased in south-oriented plots, while that of D. affinis decreased in south-oriented plots. The probability of presence for P. interjectum decreased in north-oriented plots. Moss cover increased the probability of A. filix-femina presence.
The best selected models predicting fern community indices are reported in Table S22 of the Supplementary material. Community-level responses were mainly conditional on soil sediment size. Although the number of fern species occurring in each plot was not influenced by any predictor, both Chao-1 richness and Shannon index of diversity decreased in fine-grained soils, indicating a higher fern richness and diversity in soils characterized by mixed- or large-grained soils (Fig. 3g). Consistently, Simpson’s dominance index increased in fine-grained classes of soil granulometry (Fig. 3h). Moreover Chao-1 index increased and Simpson’s index decreased with moss cover (Fig. 4d), suggesting an association between fern richness and moss cover.
Concerning potential interspecific interactions, we found only positive associations between fern species. Abundance of A. filix-femina was positively correlated to those of Osmunda regalis and Struthiopteris spicant (rS = 0.50 and rS = 0.48, respectively; P < 0.01). Also, abundance of S. spicant showed a weak, albeit significant, association to that of O. regalis (rS = 0.35; P < 0.01). All other correlations were weaker and not significant.
Discussion
We disentangled environmental factors driving population- and community-level responses of ferns in a riparian Alnus glutinosa forest habitat to understand whether fern species can be used as an ecological indicator group in this habitat. We found that fern diversity and distribution were mainly influenced by soil granulometry and, to a lesser extent, orientation of the streams and moss cover. Compared to previous studies, our work expanded the number of fern species analysed in the same habitat. We first discuss population- and community-level specific responses. Then, we focus on the potential role of fern indication at the habitat level.
Population-level responses
The abundance of different sporophyte demographic life stages, i.e. juvenile, vegetative adult, generative adult and senescent, can be influenced by different environmental variables (Cinquemani Kuehn and Leopold 1993; Rünk et al. 2006). Our results showed that the use of vegetative and generative life stages can be informative of the populations´ ecological conditions.
For Osmunda regalis, we found more vegetative ramets compared to the generative ramets. This agrees with previous findings showing stable populations with a higher proportion of generative adults growing prevalently in spring swamp habitats and lower canopy cover, whereas a few sporophytes reached the generative adult stage in stream habitats (Landi and Angiolini 2011). This is likely due to water flow disturbance and higher canopy. Generally, the high availability of water in the soil supports the occurrence of O. regalis in the streambed. However, the streambed is more unstable compared to the mid-slope and upper-slope, being more influenced by the water flow. Therefore, it is likely that the growth of the sporophyte to the generative adult stage is negatively influenced by flood disturbance than other fern species, e.g. Athyrium filix-femina. Osmunda regalis has a very prominent epigeogenous rhizome and a non-elastic rachis of the fronds that is negatively affected by rolling rocks and debris (Landi and Angiolini 2011). We did not find any predictors correlated with the abundance of ramets for O. regalis. This suggests that favourable characteristics for the development of the sporophyte in stream habitats are lacking, e.g. peaty soil, or they vary little, e.g. low light availability.
Abundances of O. regalis and Struthiopteris spicant in sampling plots were positively associated but did not depend on any investigated predictor, suggesting their preferential occurrence in other habitats, e.g. forest swamps. Consistently, in a demographic study on S. spicant its abundance increased with moisture, being most successful in poorly drained forest swamps (Cousens 1981). In addition, this species has been associated with the abundance of O. regalis in the spring swamps of central Italy (Landi and Angiolini 2008, 2011).
In the investigated streams, A. filix-femina is one of the most abundant fern species and one with the highest number of generative ramets. This finding agrees with the fact that A. filix-femina grows in a great variety of habitats such as marshes, ponds and lakes, streams and humid woods. In Central Europe and in Mediterranean regions, it is often found in shady environments (Douda 2010; Haou and Bélair 2020; Pignatti et al. 2017). However, A. filix-femina preferentially occurs in the streambed according to a previous study on fern abundance and frequency on different elevations in stream channels (Greer et al. 1997). The correlation coefficient indicated that A. filix-femina is positively associated with O. regalis and S. spicant, as it shares its habitat with them. Accordingly, they are confined to streambeds in hilly streams. Furthermore, these fern species are constantly present in the forests of the alliance Osmundo regalis–Alnion glutinosae (Landi and Angiolini 2010). The presence of A. filix-femina depended on moss cover, very abundant in the shady and humid environments of the streams. Therefore, it is likely that the numerous generative ramets produce a high number of spores. Also, A. filix-femina’s more “herbaceous-like” consistency and a generally smaller size compared to other fern species, e.g. O. regalis and Dryopteris affinis s.l., permits A. filix-femina to more easily colonize the streambed habitat and to better cope with flood disturbance. A smaller frond with a more herbaceous-like aspect, being also more flexible, has the advantage of having less resistance to waterpower. Therefore, damages to fern rachides are less likely. Our results support a wide ecological niche for this species, in agreement with the variety of humid environments where it lives, especially if placed in relation to the other ferns of our study.
D. affinis decreases in fine-grained soils. This suggests that the species is negatively affected by the sedimentation processes and flood disturbance. In addition, the increase of generative ramets with moss cover and the decrease of the species in south-oriented streams indicates the species prefers humid and cool habitats. Our results are consistent with the presence of D. affinis group on the north-oriented slopes of Harz Mountains of Germany (Bär et al. 2020), in the ancient woodlands of England (Rackham 1980), but also with the greater adaptation of D. affinis to moderately shaded habitats.
Our data shows that D. affinis was more frequent in our streams than D. borreri. Further, no environmental variable that predicted D. affinis abundance was relevant in the model for D. borreri. Both species fall within the D. affinis group. This is the first study that has investigated the ecological differences between these two entities. D. affinis was negatively affected by fine-grained soils and D. borreri by large-grained soils. Therefore mixed-grained soils can be colonized by both species. However, the lower number of predictors in the model for D. borreri, might indicate its wider ecological amplitude compared to D. affinis. This latter species prefers more humidity and is more shade-tolerant. The attribution of species or subspecies rank has been widely discussed and perhaps not yet resolved (Fraser-Jenkis 1980; Marchetti 2004; Pignatti et al. 2017). Our study supports the distinction between these two entities also from the ecological niche perspective. In addition, the results showing their ecological differences are consistent with the much wider distribution in Europe of D. borreri compared to D. affinis (Pignatti et al. 2017; PoWO 2019).
In the streams investigated here, Polystichum setiferum was the most abundant fern species and the most frequent along with A. filix-femina. Both species increased in abundance with moss cover. Similarly to D. affinis, P. setiferum abundance decreased in fine-grained soils, but it was not affected by stream orientation. Previous studies found P. setiferum growing on calcareous sands on ditch banks, and in moderately sunny habitats (Bremer 1995; Lo Gullo et al. 2010). Such ecological characteristics suggest that, as D. affinis, P. setiferum is negatively affected by the sedimentation processes, but it can grow in habitats with more variability in light and soil chemistry.
We rarely found fronds of Pteridium aquilinum with spores (< 2% of the total ramets). The establishment via spores of this species is relatively uncommon and vegetative reproduction is the main strategy of colonization and expansion (Watt 1969; Marrs and Watt 2006). The streams investigated in this study have cool temperatures and low daily temperature range. This is due to the shorter duration of the solar radiation, greater humidity maintained by the continuous water flow and to the denser tree canopy cover, where we also detected an abundant growth of mosses (Landi et al., 2009). Such conditions for P. aquilinum are unfavourable because in our study area the species prefers forests prone to summer fires and drier soils fully exposed to daylight (Karst et al. 2005; Marrs and Watt 2006; Ershova 2010). P. aquilinum has been frequently recognized as a dominant colonizing species of fire disturbed areas (Johnson 2001; Silva and Silva Matos 2006; Gallegos et al. 2015), while in our study area fires rarely reach the streams.
The three species Asplenium trichomanes, A. onopteris and Polypodium interjectum can grow on ground and other substrates as rocks and bark of dead trees. Our results showed that A. trichomanes establishment is favoured in southern orientation and in large-grained soils. Such results are consistent with the increase of juvenile sporophytes in open habitats, its remarkable acclimation to different light conditions, and its preference for growing on vertical rocks or boulders (Bremer 2004; Haou and Bélair 2020; Jermy and Page 1980; Page 1977; Vasheka et al. 2019). Furthermore, a greater presence of stones and boulders at the sites decreases the competition with other herbaceous species. Thus, generative fronds growth is favoured. Our results for A. onopteris showed this species mainly prefers large-grained soils but can also grow on mixed-grained soils. Compared to A. trichomanes, it might be possible that A. onopteris occupies different soil sediment sizes. Lastly, our results showed that Polypodium interjectum is positively affected by the presence of mixed-grained soils, favouring generative life stages, while it decreases in the cooler north-oriented streams.
The fern species we excluded from the statistical analysis were rare or not very frequent in the hilly areas of central Italy, because they live in warmer (P. cambricum), or cooler areas (D. dilatata), or are preferentially basiphilous (A. scolopendrium). On the other hand, Equisetum telmateia is frequent in Italy, but typically present in lower parts of the streams, marshy areas and rivers on sandy or clay soils (Roberts 1980; Marchetti 2004; Pignatti et al. 2017). Therefore, in the upper parts of the streams, usually shady and rocky, the species presence is not favoured.
Community-level responses
Numerous fern species (e.g. Athyrium filix-femina, Dryopteris affinis group, Osmunda regalis, and Struthiopteris spicant) are good indicators of riparian alderwoods of the alliance Osmundo regalis–Alnion glutinosae in Europe (Landi and Angiolini 2010). This community requires high moisture, meso-oligotrophic waters, acid reaction soils and waters that drain through the ground. As suggested by the Simpson index, sites with fine-grained soils support more homogeneous fern communities, i.e. communities dominated by one or few species. This agrees with the Chao-1 and Shannon indices which suggested a lower fern diversity on fine-grained soils. At the community level, this represents a hint that fern communities are governed by soil granulometry. In streams, the presence of fern species and the distribution of their life stages are not random, rather their presence and abundance are driven by the environmental variability of the habitat, with ferns being abundant in some streams and absent in others. When considering the abiotic characteristics of the streams, the variability of the soil granulometry is linked to the distance from the water flow (streambed, mid-slope and upper-slope), and to the flood disturbance. The main direction of the streams favours species growing under different conditions with cooler environments on north-oriented streams, and sunny and warmer environments on south-oriented streams. However, it is important to recall these environmental conditions are not necessarily linked to habitat conservation status. Furthermore, the higher moss cover retains moisture and might promote spore germination, likely explaining why moss cover favours richer and less homogeneous fern communities. The association between fern richness and moss cover was detected through the Chao-1 index, which gives more weight to rare species. Thus, it is also possible that moss cover would primarily positively impact rare fern species, because the habitat quality is better. Other studies highlighted the association between these two groups as both groups are dependent on a film of water on the under-surface of the gametophyte (Pharo et al. 1999). Fern species with abundant vegetative and generative sporophytes in turn reflect the continuity of different water dynamics, humidity, and transport of debris. Fern presence and abundance might have benefited from these factors.
Habitat quality assessment
Ferns allowed us to draw conclusions about an overall good ecological status of the investigated habitat, namely residual alluvial forests, a priority habitat of conservation concern (Natura 2000 code 91E0). Our study further confirms the importance of the ecological indication role of ferns (Della and Falkenberg 2019; Silva et al. 2018). Particularly, we stress their role as early-warning species for environmental changes in the 91E0 habitat (Bonari et al. 2021). An advantage in using ferns as indicators is that they are perennial organisms. Accordingly, most of the fern species evaluated in this study have a distinctive underground stem (rhizome) that each year resprout adventitious roots and stems. They can thus be considered long-living species that are informative on long-term changes of the habitat. Therefore, their presence can be interpreted as a response to a stable habitat, though characterized by a hydrological discontinuity. In our study area, the abundance of ferns in well-preserved stream forest habitat with a high canopy cover can be appraised as good indicators of the ecological status of riparian alderwoods. In our plots, canopy cover was generally high (median = 85%). Some of the investigated ferns are sensitive to changes in soil moisture. Those that increase with moss cover are generally more hygrophilous and could therefore be considered as indicators of good habitat status (e.g. Dryopteris affinis). On the contrary, those species that are less hygrophilous and are favoured by more open forest canopy could indicate habitat worsening (e.g. Polystichum setiferum). Accordingly, we suggest that when the presence of ferns with vegetative and generative sporophytes reflects the different water dynamics and moisture degrees, they can be used as indicators of the ecological habitat integrity. Further, we stress the importance of soil granulometry for habitat quality as it can indicate appropriate environmental conditions of the habitat. Finally, we suggest that an added valuable element for future habitat monitoring is the use of the different fern life stages as they might inform on different ecological characteristics and species requirements.
Conclusions and implications for conservation
We studied the ecology of several fern species, their populations and communities occurring along streams in a natural forest habitat of European priority importance. We conclude that ferns can help us appraise about the ecological conservation of this habitat. In natural streams across forests, on acidic or sub-acidic soil, the distribution of fern species varies according to the soil sediment characteristics, orientation and moss cover. We also found that growth of the generative life stage compared to the vegetative adult might benefit from different ecological characteristics for certain fern species.
Our study deepened the understanding of fern ecology at fine scale in riparian alderwood forests and provides valuable information for the elaboration of future conservation strategies of fern species that are of conservation interest. We highlight the importance of studying ferns at the population-, community-, and habitat-level to better understand their ecology and use them, along their life stages, as early-warning species in habitat monitoring.
Alnus glutinosa-dominated riparian forests are characterized by a fern-rich understory often made up of small fragments but in an overall good conservation status. From the conservation perspective, this habitat deserves to be protected by anthropogenic disturbances that may alter the soil sedimentation and moss cover. Threats include all modifications of the natural hydrology as streambed interventions, water uptake and eutrophication, of which some of the studied species are sensible to and can be therefore used as early-warning species. Forest roads and plantations are also to be avoided as they may imply habitat modifications and thus a general deterioration in the ecological quality of the habitat.
Data availability
Data used in this study is available from the corresponding author upon request.
References
Aguraiuja R, Moora M, Zobel M (2004) Population stage structure of Hawaiian endemic fern taxa of Diellia (Aspleniaceae): Implications for monitoring and regional dynamics. Can J Bot 82(10):1438–1445. https://doi.org/10.1139/b04-105
Aguraiuja R, Zobel M, Zobel K, Moora M (2008) Conservation of the endemic fern lineage Diellia (Aspleniaceae) on the Hawaiian Islands: Can population structure indicate regional dynamics and endangering factors? Folia Geobot 43(1):3–18. https://doi.org/10.1007/s12224-008-9001-1
Aho K, Derryberry D, Peterson T (2014) Model selection for ecologists: the worldviews of AIC and BIC. Ecology 95:631–636. https://doi.org/10.1890/13-1452.1
Bär A, Bennert HV, Czichowski HJ, Fuchs J, Gausmann P, Ivanova D, et al. (2020) Der Dryopteris affinis-Komplex (Dryopteridaceae) im Harz – Identifizierung, Verbreitung, Ökologie. Tuexenia 40:345–371. https://doi.org/10.14471/2020.40.011
Barrington D (1993) Ecological and historical factors in fern biogeography. J Biogeogr 20(3):275–279
Bartoń K (2012) MuMIn: multi-model inference. R package version 1.15.6. Available at: https://cran.r-project.org/web/packages/MuMIn
Biondi E, Blasi C, Burrascano S, Casavecchia S, Copiz R, Del Vico E, et al. (2009) Manuale Italiano di interpretazione degli habitat della Direttiva 92/43/CEE. Società Botanica Italiana. Ministero dell'Ambiente e della tutela del territorio e del mare, D.P.N. (http://vnr.unipg.it/habitat/).
Bonari G, Fantinato E, Lazzaro L, Sperandii MG, Acosta ATR, Allegrezza M, et al (2021) Shedding light on typical species: implications for habitat monitoring. Plant Sociol 58(1):157–166. https://doi.org/10.3897/pls2020581/08
Bremer P (1995) On the ecology and population dynamics of a Dutch population of Polystichum setiferum (Dryopteridaceae: Pteridophyta). Fern Gazzette 15(1):11–20
Bremer P (2004) On the ecology and demography of a terrestrial population of Asplenium trichomanes (Aspleniaceae: Pteridophyta) in the Netherlands. Fern Gazzette 17(2):85–96
Brooks ME, Kristensen K, van Benthem KJ, Magnusson A, Berg KW, Nielsen A, et al (2017) GlmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J 9:378–400. https://doi.org/10.32614/RJ-2017-066
Bucharová A, Münzbergová Z, Tájek P (2010) Population biology of two rare fern species: long life and long-lasting stability. Am J Bot 97(8):1260–1271. https://doi.org/10.3732/ajb.0900351
Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach, 2nd edn. Springer, Berlin, Germany
Carmignani L, Conti P, Cornamusini G, Pirro A (2013) Geologic map of Tuscany (Italy). J Maps 9(4):487–497. https://doi.org/10.1080/17445647.2013.820154
Chao A (1984) Nonparametric estimation of the number of classes in a population. Scand J Stat 11(4):265–270
Chytrý M, Tichý L, Hennekens SM, Knollová I, Janssen JAM, Rodwell JS, et al (2020) EUNIS habitat classification: expert system, char-acteristic species combinations and distribution maps of European habitats. Appl Veg Sci 23(4):648–675. https://doi.org/10.1111/avsc.12519
Cinquemani Kuehn DM, Leopold DJ (1993) Habitat characteristics associated with Phyllitis scolopendrium (L.) Newm. var. americana fern. (Aspleniaceae) in central New York. Bull Torrey Bot Club 120(3):310–318
Climate-Data (2021) https://en.climate-data.org/europe/italy/tuscany/monticiano-110336/. Accessed Feb 2021
Cousens MI (1981) Blechnum spicant: Habitat and vigor of optimal, marginal, and disjunct populations, and field observations of gametophytes. Botanical Gazzette 142(2):251–258
Della AP, Falkenberg DB (2019) Pteridophytes as ecological indicators: an overview. Hoehnea 46(1):e522018. https://doi.org/10.1590/2236-8906-52/2018
Ditzler C, Scheffe K, Monger HC (2017) Soil survey manual. In: Staff SSD (ed) USDA Handbook 18. Government Printing Office, Washington, DC
Douda J (2010) The role of landscape configuration in plant composition of floodplain forests across different physiographic areas. J Veg Sci 21:1110–1124. https://doi.org/10.1111/j.1654-1103.2010.01213.x
Eckstein 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 Oecologica 25(1–2):83–91. https://doi.org/10.1016/j.actao.2003.11.003
Ershova EA (2010) Adaptation of Pteridium aquilinum (L.) Kuhn in Siberia. Contemp Prob Ecol 3(6):698–702. https://doi.org/10.1134/S1995425510060147
Fraser-Jenkis CR (1980) Dryopteris affinis: a new treatment for a complex species in the European Pteridophyte flora. Willdenowia 10:107–115
Gallegos SC, Hassen I, Saavedra F, Schleuning M (2015) Bracken fern facilitates tree seedling recruitment in tropical fire-degraded habitats. For Ecol Manage 337:135–143. https://doi.org/10.1016/j.foreco.2014.11.003
Given DR (1993) Changing aspects of endemism and endangerment in pteridophyta. J Biogeogr 20:293–302
Greer GK, Lloyd RM, McCarthy BC (1997) Factors influencing the distribution of pteridophytes in a Southeastern Ohio hardwood forest. Journal of the Torrey Botanical Society 124(1):11–21
Haou S, de Bélair G (2020) First approach to ecological niche of Numidian lycophytes and ferns in Algeria. Acta Ecol Sin 40:52–63. https://doi.org/10.1016/j.chnaes.2019.05.005
Harrison XA, Donaldson L, Correa-Cano ME, Evans J, Fisher DN, Goodwin CE, Robinson BS, Hodgson DG, Inger R (2018) A brief introduction to mixed effects modelling and multi-model inference in ecology. PeerJ 6:e4794. https://doi.org/10.7717/peerj.4794
Hernández-Rojas AC, Kluge J, Krömer T, Carvajal-Hernández C, Silva-Mijangos L, et al (2020) Latitudinal patterns of species richness and range size of ferns along elevational gradients at the transition from tropics to subtropics. J Biogeogr 47(6):1383–1397. https://doi.org/10.1111/jbi.13841
Higgins MA, Ruokolainen K, Tuomisto H, Llerena N, Cardenas G, Phillips OL, Vásquez R, Räsänen M (2011) Geological control of floristic composition in Amazonian forests. J Biogeogr 38(11):2136–2149. https://doi.org/10.1111/j.1365-2699.2011.02585.x
Jermy AC, Page CN (1980) Additional field characters separating the subspecies of Asplenium trichomanes in Britain. Fern Gazzette 12(2):112–113
Johnson PN (2001) Vegetation recovery after fire on a southern New Zealand peatland. NZ J Bot 39:251–267. https://doi.org/10.1080/0028825X.2001.9512736
Jones MM, Tuomisto H, Clark DB, Olivas P (2006) Effects of mesoscale environmental heterogeneity and dispersal limitation on floristic variation in rain forest ferns. J Ecol 94(1):181–195. https://doi.org/10.1111/j.1365-2745.2005.01071.x
Karst J, Gilbert B, Lechowicz MJ (2005) Fern community assembly: the roles of chance and the environment at local and intermediate scales. Ecology 86(9):2473–2486. https://doi.org/10.1890/04-1420
Kessler M (2000) Elevational gradients in species richness and endemism of selected plant groups in the central Bolivian Andes. Plant Ecol 149(2):181–193
Kessler M, Kluge J, Hemp A, Ohlemüller R (2011) A global comparative analysis of elevational species richness patterns of ferns. Glob Ecol Biogeogr 20:868–880. https://doi.org/10.1111/j.1466-8238.2011.00653.x
Landi 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(1):45–57. https://doi.org/10.1007/s00035-008-0843-1
Landi M, Angiolini C (2010) Osmundo-Alnion woods in Tuscany (Italy): a phytogeographical analysis from a west European perspective. Plant Biosyst 144(1):93–110. https://doi.org/10.1080/11263500903361036
Landi M, Angiolini C (2011) Population structure of Osmunda regalis in relation to environment and vegetation: an example in the Mediterranean area. Folia Geobot 46:49–68. https://doi.org/10.1007/s12224-010-9086-1
Landi M, Frignani F, Bonini I, Casini F, Saveri C, De Dominicis V, Angiolini C (2009) Flora and vegetation in the catchment area of the stream “La Bolza” in the Merse valley. Webbia 64(2):187–212. https://doi.org/10.1080/00837792.2009.10670859
Legendre P, Legendre L (2012) Numerical ecology. Elsevier, Amsterdam, The Netherlands
Lo Gullo MA, Raimondo F, Crisafulli A, Salleo S, Nardini A (2010) Leaf hydraulic architecture and water relations of three ferns from contrasting light habitats. Funct Plant Biol 37(6):566–574. https://doi.org/10.1071/FP09303
Mac Nally R, Duncan RP, Thomson JR, Yen JD (2018) Model selection using information criteria, but is the “best” model any good? J Appl Ecol 55:1441–1444. https://doi.org/10.1111/1365-2664.13060
Marchetti D (2004) Le pteridofite d’Italia. Annali del Museo Civico di Rovereto, Sezione Archeologia. Storia Scienza Naturali 19:71–231
Marrs RH, Watt AS (2006) Biological flora of the British Isles: Pteridium aquilinum (L.) Kuhn. J Ecol 94:1272–1321. https://doi.org/10.1111/j.1365-2745.2006.01177.x
Moora M, Kose M, Jõgar Ü (2007) Optimal management of the rare Gladiolus imbricatus in Estonian coastal meadows indicated by its population structure. Appl Veg Sci 10(2):161–168. https://doi.org/10.1111/j.1654-109X.2007.tb00514.x
Moran RC (2008) Diversity, biogeography, and floristics. In: Ranker TA, Haufler CH (eds) Biology and evolution of ferns and lycophytes. Cambridge University Press, New York, USA
Mucina L, Bültmann H, Dierßen K, Theurillat J-P, Raus T, Čarni A, et al (2016) Vegetation of Europe: hierarchical floristic classification system of vascular plant, bryophyte, lichen, and algal communities. Appl Veg Sci 19:3–264. https://doi.org/10.1111/avsc.12257
Nervo MH, da Silva Coelho FV, Windisch PG, Overbeck GE (2016) Fern and lycophyte communities at contrasting altitudes in Brazil’s subtropical Atlantic Rain Forest. Folia Geobot 51(4):305–317. https://doi.org/10.1007/s12224-016-9253-0
Page CN (1977) An ecological survey of the ferns of the Canary Islands. Fern Gazzette 11(5):297–312
Pesaresi S, Biondi E, Casavecchia S (2017) Bioclimates of Italy. J Maps 13(2):955–960. https://doi.org/10.1080/17445647.2017.1413017
Pharo EJ, Beattie AJ, Binns D (1999) Vascular plant diversity as a surrogate for bryophyte and lichen diversity. Conserv Biol 13(2):282–292
Pignatti S, Guarino R, La Rosa M (2017) Flora d’Italia, vol 1, 2nd edn. Edagricole, Milano, Italy
Portal to the Flora of Italy (2021) Available at https://dryades.units.it/floritaly Accessed Feb 2021
PoWO (2019) Plants of the World Online. Facilitated by the Royal Botanic Garden, Kew. Published on the internet; http://www.plantsoftheworldonline.org/ Accessed Mar 2021
PPG 1 (2016) A community-derived classification for extant lycophytes and ferns. J Syst Evol 54(6):563–603. https://doi.org/10.1111/jse.12229
Preislerová Z, Jiménez-Alfaro B, Mucina L, Berg C, Bonari G, Kuzemko A, et al (2022) Distribution maps of vegetation alliances in Europe. Appl Veg Sci. https://doi.org/10.1111/avsc.12642
Rackham O (1980) Ancient woodland: its history, vegetation and uses in England. Arnold, London, UK
Rahbek C (1995) The elevational gradient of species richness: a uniform pattern? Ecography 18(2):200–205. https://doi.org/10.1111/j.1600-0587.1995.tb00341.x
Rahbek C (2005) The role of spatial scale and the perception of large-scale species-richness patterns. Ecol Lett 8(2):224–239. https://doi.org/10.1111/j.1461-0248.2004.00701.x
Roberts RH (1980) Polypodium macaronesicum and P. australe: a morphological comparison. Fern Gazzette 12(2):69–74
Rünk K, Moora M, Zobel M (2006) Population stage structure of three congeneric Dryopteris species in Estonia. Proc Est Acad Sci 55:15–30. https://doi.org/10.3176/biol.ecol.2006.1.02
Ruokolainen K, Linna A, Tuomisto H (1997) Use of Melastomataceae and pteridophytes for revealing phytogeographical patterns in Amazonian rain forests. J Trop Ecol 13(2):243–256
Sharpe JM, Shiels AB (2014) Understory fern community structure, growth and spore production responses to a large-scale hurricane experiment in a Puerto Rico rainforest. For Ecol Manage 332(15):75–86. https://doi.org/10.1016/j.foreco.2014.01.023
Silva USR, Silva Matos DM (2006) The invasion of Pteridium aquilinum and the impoverishment of the seed bank in fire prone areas of Brazilian Atlantic Forest. Biodivers Conserv 15:3035–3043. https://doi.org/10.1007/s10531-005-4877-z
Silva VL, Mehltreter K, Schmitt JL (2018) Ferns as potential ecological indicators of edge effects in two types of Mexican forests. Ecol Ind 93:669–676. https://doi.org/10.1016/j.ecolind.2018.05.029
Tuomisto H, Ruokolainen K, Poulsen AD, Moran RC, Quintana C, Canas G, Celi J (2002) Distribution and diversity of pteridophytes and Melastomataceae along edaphic gradients in Yasuni National Park, Ecuadorian Amazonia. Biotropica 34:516–533. https://doi.org/10.1646/0006-3606(2002)034[0516:DADOPA]2.0.CO;2
Tuomisto H, Ruokolainen K, Yli-Halla M (2003) Dispersal, environment, and floristic variation of Western Amazonian forests. Science 299(5604):241–244. https://doi.org/10.1126/science.1078037
Vasheka O, Gratani L, Puglielli G (2019) Leaf physiological and structural plasticity of two Asplenium (Aspleniaceae) species coexisting in sun and shade conditions. Plant Ecology and Evolution 152(3):426–436. https://doi.org/10.5091/plecevo.2019.1525
Watt AS (1969) Contributions to the ecology of bracken (Pteridium aquilinum). VII. Bracken and litter 2. Crown Form. New Phytol 68(3):841–859
Zuquim G, Tuomisto H, Jones MM, Prado J, Figueiredo FOG, Moulatlet GM, et al (2014) Predicting environmental gradients with fern species composition in Brazilian Amazonia. J Veg Sci 25(5):1195–1207. https://doi.org/10.1111/jvs.12174
Zuur AF, Ieno EN, Walker NJ, Saveliev AA, Smith GM (2009) Mixed effects models and extensions in ecology with R. Springer, New York, USA
Funding
Open access funding provided by Libera Università di Bolzano within the CRUI-CARE Agreement. GB was funded by the Free University of Bozen-Bolzano, Italy through the project BIOmen (TN202L).
Author information
Authors and Affiliations
Contributions
GB conceived the idea, interpreted the results and wrote the first draft of the manuscript; NF conducted statistical analyses and wrote the associated text; SRF prepared the data, participated in statistical analyses, and contributed to the manuscript; CA contributed to results interpretation and commented on the manuscript; EB participated in data collection; ML conceived the idea, planned the sampling, collected the data, identified the species, interpreted the results and participated in writing the manuscript.
Corresponding author
Ethics declarations
Conflict of interest
Authors have no conflict of interest to declare.
Ethical approval
Plant names agree with the International Code of Nomenclature for algae, fungi, and plants.
Animal research
Not applicable.
Consent to participate
Not applicable.
Consent to publication
All authors agreed with the content, gave explicit consent to submit, and they obtained consent from the responsible authorities at the institute/organization where the work has been carried out, before the work is submitted.
Plant reproducibility
Not applicable.
Clinical trials registration
Not applicable.
Additional information
Communicated by Daniel Sanchez Mata.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Bonari, G., Fattorini, N., Fruchter, S.R. et al. Fine-scale fern ecological responses inform on riparian forest habitat conservation status. Biodivers Conserv 31, 2141–2161 (2022). https://doi.org/10.1007/s10531-022-02431-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10531-022-02431-8