A trait‐based approach to understand the ...

Journal of Vegetation Science && (2017)

A trait-based approach to understand the consequences of specific plant interactions for community structure €b Christian Scho

Keywords Community assembly; Competition; Effect and response traits; Environmental filtering; Facilitation; Foundation species; Niche differentiation; Niche space construction; Nurse plants Abbreviations LDMC = leaf dry matter content; SLA = specific leaf area. Nomenclature Blanca et al. (2011) Received 4 October 2016 Accepted 1 February 2017 Co-ordinating Editor: Sandor Bartha

€ b, C. (corresponding author, Scho [email protected])1,2, Macek, P. ([email protected])1,3,  n, N. ([email protected])1,4, Pisto Kikvidze, Z. ([email protected])5, Pugnaire, F.I. ([email protected])1 1  n Experimental de Zonas Aridas, Estacio Consejo Superior de Investigaciones Cientıficas, EEZA-CSIC, Carretera de ~ada de San Sacramento s/n, E-04120 La Can Urbano, Spain; 2 Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland; 3 Faculty of Science, University of South  e Bohemia, Branisovska 31, CZ-37005 Cesk jovice, Czech Republic; Bude 4 Department of Ecology, Federal University of Rio de Janeiro, Ilha do fundao, 21941-590 Rio de Janeiro, Brasil; 5 Institute of Ethno-Biology and Socio-Ecology, Ilia State University, 5 Cholokashvili Avenue, Tbilisi 0162, Georgia

 n, Zaal Kikvidze & Francisco I. Pugnaire , Petr Macek, Nuria Pisto

Abstract Question: In plant communities, the presence of a species has consequences for other species, with some being competitively excluded while others benefit from the close vicinity of neighbours. Even though such specificity in plant interactions is common and known, there is no empirical assessment of the mechanisms that would help us understand its importance for plant diversity. Here we asked whether analysing spatial associations between plant traits known to affect the environment (i.e. effect traits) and those known to respond to the environment (i.e. response traits) might explain plant–plant interactions and their role in community assembly. Location: Sierra Nevada Mountains, Spain. Methods: In a field study, we addressed the specificity of plant–plant interactions by quantifying effect traits of three co-occurring cushion-forming species and response traits of their associated plant assemblages. Traits were measured at the individual level and then aggregated to trait metrics (mean, range, dispersion) at the plot level. Finally, plot-level metrics of effect traits were related to response traits and the species composition of plant communities. Results: Each cushion-forming species had a distinctive combination of effect traits and harboured a unique plant community with an exclusive composition of response traits. With multivariate statistics we showed that differences in effect traits (branch density and canopy height) among and within cushion species significantly explained response traits (specific leaf area, leaf dry matter content) of associated species and the local-scale species composition.

Conclusions: Using effect and response traits measured at the individual level, we provide a mechanistic understanding of the species specificity of plant interactions and demonstrate how important such specificity is for species diversity in an ecosystem.

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Species-specific interactions

Introduction Interactions between neighbours in plant communities range from competitive, where interacting species limit each other’s performance, to facilitative, where at least one of the interacting species benefits from the other (Callaway & Walker 1997). Such negative and positive interactions occur simultaneously (Pugnaire & Luque 2001), the net balance depending on the prevailing conditions (Bertness & Callaway 1994), but also on the identity and characteristics of interacting species (Callaway 1998; Liancourt et al. 2005; Gross et al. 2009; Sch€ ob et al. 2012; Soliveres et al. 2015). Specificity in plant–plant interactions is therefore a key aspect to understand plant community dynamics (Callaway 1998). Specificity in the interaction between two species is determined by (1) the effect of each species on its environment (e.g. Sch€ ob et al. 2013) and (2) the environmental preferences of each species (Gross et al. 2009; Sch€ ob et al. 2012). Plants modify the environment in their immediate vicinity by e.g. casting a shadow, increasing or decreasing resource availability, sheltering from wind, and attracting or repelling herbivores. Such effects are inherent characteristics of any plant individual, therefore differing in type and intensity between species and individuals (Sch€ ob et al. 2013; McIntire & Fajardo 2014; Macek et al. 2016). In other words, species and individuals differ in their impact on the environment. Recent reports have empirically shown that such effects are linked to plant traits (Gross et al. 2008), which can differ among functional groups and species (Violle et al. 2009; Br athen & Ravolainen 2015; Macek et al. 2016), but also within species (Sch€ ob et al. 2013; Bonanomi et al. 2015). For example, alpine cushion plants differ in canopy compactness along elevation gradients, which has significant consequences on their environmental effects (e.g. temperature buffering; Bonanomi et al. 2015) and their capabilities for hosting other species [e.g. species with lower leaf dry matter content (LDMC) that are less drought-tolerant; Sch€ ob et al. 2013]. It is therefore reasonable to hypothesize that the specificity of plant effects on the environment is based on trait differences among species (i.e. plant effect traits). On the other hand, plant species differ in their environmental requirements. Therefore, the environment created by a species may or may not fit the requirements of another species, which will determine whether one species benefits, or not, from the presence of another (e.g. Suding et al. 2003). The environmental requirements of a species have often been linked to its functional traits (Lavorel & Garnier 2002). This led to the concept of trait-based community assembly, where environmental filtering selects species based on their functional traits (Weiher & Keddy

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1995; Kraft et al. 2008). Indeed, functional traits are even used to quantify a species’ niche (Violle & Jiang 2009). Therefore, differences in traits and niche requirements can explain the response of a species to a neighbour (Gross et al. 2009, 2015; Butterfield & Callaway 2013; Le Bagousse-Pinguet et al. 2015). For example, at high elevations in the Sierra Nevada Mountains in Spain the alpine cushion plant Arenaria tetraquetra subsp. amabilis hosts a set of species functionally different from those in neighbouring open areas (Sch€ ob et al. 2012): whereas species with low LDMC or high specific leaf area (SLA) only grew in cushions, species with high LDMC and low SLA only grew in open areas away from cushions, with no (or small) overlap in trait values between microhabitats. It is therefore reasonable to hypothesize that the specificity of plant responses to the environment created by neighbours is the consequence of differences in niche requirements, which may be inferred from plant traits (i.e. plant response traits). Here our aim was to combine these two different sides of specificity in plant interactions in a single study in order to assess their interaction. We first looked at differences in species richness and composition, the effect traits of cushion-forming foundation species (sensu Ellison et al. 2005), and the response traits of the associated plant communities separately. In a second step, using multivariate statistics we related the effect traits of foundation species to response traits of the associated plants and ultimately to plant community composition. Generally, the presence of a particular species can strongly affect community assembly (Butterfield et al. 2013; Kikvidze et al. 2015; Pist on et al. 2015; Chac on-Labella et al. 2016a,b), and we expected that each of the three foundation species present at our study site, and the various phenotypes within a species, would do this differently. Specifically, we hypothesized that each foundation species and its distinct phenotypes is associated with a unique environment depending on its effect traits, and is therefore colonized by a unique set of plant species whose response traits fit that environment. We further expected that these species-specific interactions between foundation species and other plants would contribute to higher plant diversity at the community level due to complementarity of co-existing foundation species.

Methods Study site The study was conducted in the Sierra Nevada Mountains, southeast Spain. The field site is located at 2740 m a.s.l. (37°050 N 03°230 W) on the northern slope of the Veleta peak. It is characterized by patchy vegetation (ca. 10% plant cover) dominated by the cushion-forming

Journal of Vegetation Science Doi: 10.1111/jvs.12523 © 2017 International Association for Vegetation Science

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forb species A. tetraquetra subsp. amabilis and Plantago holosteum, and the tussock-forming grass Festuca indigesta (Appendix S1). Open areas in between are covered with siliceous gravel (mica-schist) and sparsely colonized by annual and perennial species. The soil is poorly developed, with a low amount of organic matter (Sch€ ob et al. 2012). The climate is mediterranean, with dry and hot summer months. The nearest climate station in Pradollano at 2507 m a.s.l., about 1 km from the study site, receives a mean annual rainfall of 690 mm and mean annual temperature is 3.9 °C (Worldwide Bioclimatic Classification System, Phytosociological Research Center, ES). Sampling design Within an area of ca. 1 ha we identified, in Aug 2011, four distinct microhabitats, three created by each of the three dominant foundation species (A. tetraquetra, F. indigesta and P. holosteum) and the open microhabitat in between. The different microhabitats seemed randomly distributed at the study site, with equal dominance of the three foundation species (i.e. cover of each foundation species ranged between 2% and 3%). To characterize the microhabitats associated with foundation species, we randomly selected 40 individuals of variable size of each of the three foundation species. One Festuca individual had missing data and was excluded from further analyses. Each sampled individual was considered a plot, which size equalled the horizontal expansion of the plant. Plant size was estimated from the largest diameter and its perpendicular, and area was calculated as p(mean diameter/ 2)2. Arenaria mean size was 168 cm2 (range 8–406 cm2), while Plantago was 149 cm2 (3–638 cm2) and Festuca 241 cm2 (1–1018 cm2). We also sampled ten circular plots (27.6-cm diameter or 598 cm2 area) randomly placed in open areas between foundation species (hereafter called the Open microhabitat), resulting in a total of 129 plots used for analyses. We used a standardized sampling grid (Appendix S2), and all plant effect trait measurements were repeated for each subunit (=part hereafter) of the entire plot, whereas plant response traits were measured for each individual of associated species. We a priori selected easy-to-measure plant functional traits that could stimulate repetition of this approach elsewhere, but acknowledge that other traits may have been equally suitable to describe either the effects of foundation species on the environment or the response of associated species to the environment. However, our goal was not to describe as accurately as possible effect trait– response trait relationships for this specific system, but rather to assess the suitability of such a framework to address specificity in plant interactions.

Species-specific interactions

Plant diversity and plant response traits For each foundation species we recorded each individual of each vascular plant species growing within the foundation species’ canopy and determined its specific location within the sampling grid (Appendix S2). In the Open microhabitat, we sampled the full A–D circles of the grid. For each of the 1350 individuals we measured plant height and took the largest healthy leaf (including the petiole) for determination of LDMC and SLA according to standard procedures (P erez-Harguindeguy et al. 2013). Plant height is related to light competition (Falster & Westoby 2003) and was used as an indicator of light availability. SLA is broadly related to overall resource conditions of the environment, with positive relationships to N uptake (P erezHarguindeguy et al. 2013) and soil nutrient availability (Ordo~ nez et al. 2009), and was used here as indicator for soil nutrient availability. LDMC is often inversely related to SLA, but is also influenced by soil water relations (P erez-Harguindeguy et al. 2013) as it increases with drought (Ackerly 2004), and was used here as an indicator of water availability. Therefore, all three traits are sensitive to changes in resources that may be influenced by foundation species (Sch€ ob et al. 2012) and were used as response traits to potential changes in niche space. Foundation species effect traits In each part of the sampling grid that was at least partially occupied by the foundation species we measured two morphological traits of the foundation species: branch density (i.e. number of terminal branches per cm2) and canopy height, measured as the distance from the surface to the tip of the outermost leaf. Branch density is a good proxy for canopy compactness, which is related to the effects of foundation species on microenvironmental conditions (Sch€ ob et al. 2013; Bonanomi et al. 2015): it has been shown that increased canopy compactness goes together with stronger effects of cushions on soil organic matter and soil water content (Sch€ ob et al. 2013) and strong temperature buffering (Bonanomi et al. 2015). Canopy height indicates the competitive ability of foundation species for light (P erez-Harguindeguy et al. 2013), and we assumed that the shading effect increases with increasing canopy height. Therefore, branch density and canopy height were considered effect traits linked to LDMC, SLA and plant height as response traits of associated species, given the sensitivity of the response traits to changes in soil moisture, soil fertility and light conditions outlined above. Size of the foundation species does likely also affect the interaction with other species (Allegrezza et al. 2016), and was indirectly accounted for by the plot-level (i.e. within-individual) variability of the two effect traits as described below.

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Species-specific interactions

Calculation of plot-level characteristics In each plot (i.e. equal to the size of the foundation species or a circle of 27.6-cm diameter in case of the Open microhabitat) we recorded the number of associated vascular plant species and the number of individuals per species. Species traits were summarized for each plot by combining the different parts of the sampling grid and calculating the mean, range and dispersion of each variable using measurements at the sub-individual level (i.e. measurements in each part of the sampling grid) for the foundation species and measurements at the individual level for the associated plant community. For further analyses we only used these plot-level metrics. The mean was calculated as the arithmetic mean over all measurements taken within a single plot. The range was calculated as the difference between the highest and lowest values measured for a given variable within a plot. These two measurements were calculated to characterize trait distribution – with optimum and upper and lower limits – within a plot (Jung et al. 2010). Finally, dispersion was calculated as the coefficient of variation of the successive neighbour distances for a variable within a plot (CVNND; Jung et al. 2010; Kraft & Ackerly 2010). For this purpose, the values for a given variable and plot were ordered and then distances between successive values calculated. The dispersion measure is then the coefficient of variation of these distances between successive values within a plot. Dispersion was used as a measure of heterogeneity (regular or clumped) within a plot. Statistical analyses Since total sampling area differed among microhabitats due to differences in plot size and number of plots (total area 6720 cm2 for Arenaria, 9402 cm2 for Festuca, 5954 cm2 for Plantago and 5310 cm2 for the Open microhabitat), the number of species potentially occurring in each microhabitat and over all four microhabitats was estimated using individual-based rarefactions. Species richness was calculated with the function specpool() from the vegan package in R using the Bootstrap algorithm (R Foundation for Statistical Computing, Vienna, AT). Differences in species composition (based on species relative abundance), foundation species effect trait metrics and associated plant species response trait metrics among microhabitats were tested with nonlinear multi-dimensional scaling (NMDS) and PERMANOVA using the functions metaMDS() and adonis() from the vegan package in R. We used the BrayCurtis dissimilarity index to calculate the distance matrix. To evaluate the quality of the ordination we used the stress value (a measure of mismatch between distance measures and the distance in ordination space). Significance of the

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term ‘microhabitat’ was tested with 999 permutations. For graphical display, we plotted the individual site scores (i.e. plots) and the 95% CI of the dispersion for each microsite measured as the SE of the weighted average of the site scores using the function ordiellipse() from the vegan package. To assess how effect traits of the foundation species affect assembly of the associated plant community we applied a trait-based community assembly approach (Weiher & Keddy 1995; Kraft et al. 2008). For this purpose, we first quantified the deviation of the trait mean, trait range and trait dispersion of the associated plant community from a random distribution of trait values (Appendix S3). We performed null model analyses by randomly distributing trait values of each trait among the associated plant individuals, keeping the number of individuals per plot constant. The deviation of the observed trait pattern from the mean trait pattern over 1000 null models was then calculated as standardized effect size (SES), with SESmetric = (mean Observedmetric  mean Nullmetric)/SD Nullmetric. SESmean and SESrange were used as proxies for environmental filtering, and SESdispersion was used as proxy for niche differentiation (Kraft et al. 2008; Jung et al. 2010). Using distance-based redundancy analyses (dbRDAs with Euclidean distances) we explained these response trait patterns resembling community assembly processes, and associated plant community composition (quantified through species relative abundances), with the trait metrics of the effect traits of foundation species (excluding the Open microhabitat). Significance of the model, and of the constraining variables, was assessed with permutation tests (499 permutations). To assess the significance of the constraining variables within each foundation species we restricted permutations within each foundation species. dbRDAs were conducted with the functions capscale() and anova.cca() from the vegan package, while restricted permutations were defined with the how() function from the permute package. All statistical analyses were done in R 3.3.1. R code and data are provided in Appendices S10 and S11, respectively.

Results Species richness and composition The estimated species pool varied across microhabitats from 19 (Festuca) to 23 (Plantago), the difference between these extremes being significant (Fig. 1). The species pool over all four microhabitats was 25, which is 28% larger than that of the Open microhabitat alone. This suggests that species pools were partially overlapping but still different among microhabitats. This was confirmed by NMDS ordination, which showed a significant microhabitat effect on species composition (Fig. 2).

Journal of Vegetation Science Doi: 10.1111/jvs.12523 © 2017 International Association for Vegetation Science

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Fig. 1. Estimated species richness for each microhabitat (Open, Arenaria, Festuca, Plantago) separately and for all microhabitats of the site pooled (All) using rarefaction analyses (see Appendix S4). Displayed are means  1 SE. For Open n = 10, for Festuca n = 39, for Arenaria and Plantago n = 40 and for All n = 129.

Foundation species effect traits The mean, range and dispersion of effect traits varied significantly among all three foundation species (Fig. 3). Mean branch density was highest in Arenaria, followed by Festuca and Plantago, whereas canopy height was very different among the three foundation species, being highest in Festuca, followed by Plantago and then Arenaria (Appendix S7). Within plots, Festuca had the widest range for both traits, whereas Arenaria had a range of branch densities wider than Plantago; Plantago, in turn, showed a canopy height range wider than Arenaria. Dispersion of branch density was the most even for Festuca, followed by Arenaria and Plantago. Canopy height was most evenly dispersed within individuals of Festuca, followed by Plantago and Arenaria. Species response traits We found significant differences in trait composition of species associated with each of the four microhabitats for both mean and range (Fig. 4a) and trait dispersion (Fig. 4b). Trait composition for mean and range, but not trait dispersion, of associated species was also significantly different among foundation species (i.e. excluding the Open microhabitat). Plants in the Open had generally higher LDMC and SLA, but were smaller than those associated with foundation species (Appendix S9). Plants associated with Arenaria had the lowest SLA and smallest height of all foundation species, whereas plants associated with Festuca had the lowest LDMC, highest SLA and were the tallest. Plants associated with Plantago had the highest LDMC but rather low SLA while height values were similar to other foundation species microhabitats. Within a plot,

Species-specific interactions

Fig. 2. Species composition of the four microhabitats (Open, Arenaria, Festuca, Plantago) represented by the first two axes of a NMDS ordination. PERMANOVA revealed significant variation in species composition among the four microhabitats (Appendix S5). Displayed are plot means as dots and 95% dispersion ellipses for each microhabitat. Plots: 129, species: 25.

LDMC and SLA ranges were widest in the Open, followed by Plantago, Festuca and Arenaria. The range of plant height was widest in Festuca, followed by Plantago, Arenaria and the Open. Consequently, microhabitats with the highest mean values generally also showed the widest trait range (0.18 5 r 5 0.62). Plant trait values were more evenly dispersed in foundation species compared to the Open. Species specificity of plant interactions and its consequences for community diversity The effect trait metrics of foundation species (mean, range and dispersion of branch density and canopy height) significantly explained both the community assembly processes (F6,107 = 5.90, P = 0.001; Table 1) and community composition (F6,107 = 1.95, P = 0.025; Table 1). But also within foundation species, differences in effect traits explained differences in response trait patterns (F6,107 = 5.90, P = 0.002; Table 1) and in community composition of the associated species (F6,107 = 1.95, P = 0.016; Table 1).

Discussion We showed that each foundation species had a specific combination of effect traits that likely created unique environments and resulted in distinct communities of associated plant species. In other words, the species pool of the species-poorest community was not just a subset of the species pool from the species-richest community, but they only partially overlapped. In addition, even though each microhabitat created by a foundation species did not necessarily host more species than the (unmodified) open

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(a)

(b)

Fig. 3. Effect traits of the three foundation species (Arenaria, Festuca, Plantago) represented by the first two axes of NMDS ordination. Foundation species effect traits (branch density and canopy height) were quantified as mean and range of traits (a) and as dispersion [CVNND; (b)] for each plot. PERMANOVA revealed significant differences in mean, range and dispersion of traits among the three foundation species (Appendix S6). Displayed are plot means as dots and 95% dispersion ellipses for each microhabitat.

(a)

(b)

Fig. 4. Response trait composition of the individual plants inhabiting the four microhabitats (Open, Arenaria, Festuca, Plantago) represented by the first two axes of a NMDS ordination. Plant response traits (plant height, LDMC and SLA) were quantified as mean and range of traits (a) and as dispersion of traits [CVNND; (b)] for each plot. PERMANOVA revealed significant differences in mean, range and dispersion of plant response traits among the four microhabitats (Appendix S8). Displayed are plot means as dots and 95% dispersion ellipses for each microhabitat.

microhabitat, their different species composition resulted in an overall increase in plant diversity at the site level (see also Cavieres et al. 2015; Pist on et al. 2016). In other words, the species-specific and complementary associations of plants to the three co-occurring foundation species contributed to the species diversity at the study site. Differences in the effects of foundation species on their environment, and therefore on community assembly, have been shown in other studies (e.g. Pugnaire et al. 2004; Cavieres et al. 2008; Br athen & Ravolainen 2015; Chen et al. 2015a,b; Pist on et al. 2016). Br athen & Ravolainen (2015) and Chen et al. (2015b) even hypothesized that such species-specific effects are a direct consequence of trait differences among foundation species. However, here we empirically demonstrate the close link between effect traits of foundation species and response traits of

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their associated plants. This may actually indicate that different foundation species, through their species-specific effect traits, influence community assembly processes (Kraft et al. 2008). The three foundation species, through differences in morphological traits, created unique niche spaces that differed not only from the niche space in open areas, but also among all three foundation species. Each of these unique niche spaces showed quantitatively different environmental filters that required a different set of response traits; but also exhibited different levels of niche differentiation. This was supported by ordinations of response traits of associated plants, which showed that species and individuals inhabiting different niche spaces showed different trait combinations. For example, associated plants in Festuca (which itself had the highest canopy) showed the lowest

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Species-specific interactions

Table 1. Results of the permutation tests for significance of the constraining variables in the distance-based redundancy analyses relating the foundation species effect trait metrics (mean, range and CVNND of branch density and canopy height) to the response trait pattern (SESmean, SESrange, SESCVNND of LDMC, SLA and plant height) and community composition (relative abundances of species) of the plant community associated with the foundation species. Permutations were done without restrictions (with permutations among foundation species) and by restricting them within foundation species. df

MeanCanopy height MeanBranch density RangeCanopy height RangeBranch density CVNNDCanopy height CVNNDBranch density Residual

1 1 1 1 1 1 107

Among Foundation Species

Within Foundation Species

Response Trait Pattern

Community Composition

Response Trait Pattern

Community Composition

Variance

F

P

Variance

F

P

Variance

F

P

Variance

F

P

2.71 0.25 0.21 0.44 0.26 0.32 12.70

22.88 2.08 1.77 3.72 2.19 2.73

0.001 0.076 0.137 0.012 0.075 0.051

0.65 0.29 1.04 0.83 2.19 0.16 47.23

1.47 0.66 2.36 1.87 4.96 0.37

0.177 0.557 0.064 0.107 0.007 0.861

2.71 0.25 0.21 0.44 0.26 0.32 12.70

22.88 2.08 1.77 3.72 2.19 2.73

0.002 0.194 0.178 0.094 0.092 0.018

0.65 0.29 1.04 0.83 2.19 0.16 47.23

1.47 0.66 2.36 1.87 4.96 0.37

0.542 0.622 0.054 0.046 0.004 0.888

P-values in bold mean statistically significant effects, whereas P-values in italics show marginally significant effects.

LDMC and highest SLA values, being the tallest of all associated plants. Furthermore, trait dispersion within foundation species was more homogeneous than in open areas, indicating an increased level of niche differentiation among plants in microhabitats modified by foundation species. This could explain the higher plant density within foundation species compared to open areas. But there were also differences among foundation species, showing particularly strong niche differentiation processes in Festuca. Overall, this trait-based distribution of species in modified microhabitats supports our hypothesis on the importance of trait-based responses of plants to the modified environment being another aspect of the species specificity of plant interactions. From a niche-based perspective, species-specific interactions between foundation species and their associated plants could be explained in terms of creation of specific niche space. The concepts of niche construction (e.g. Odling-Smee et al. 2013) and ecosystem engineering (e.g. Jones et al. 1994) both account for the effects of organisms on their immediate neighbourhood. Both concepts agree in that such environmental changes affect the presence of other species. Our results demonstrate that the construction of new niche space can attract some species with particular traits that otherwise would be absent, resulting in facilitation (see also Butterfield & Briggs 2011; Sch€ ob et al. 2012; Gross et al. 2013). Our results also show that changes in niche space result in the exclusion of some species that no longer fit into the new niche space, resulting in competition. We therefore suggest that the niche concept is not only useful to explain the specificity of plant–plant interactions, but also to explain the consequences of plant– plant interactions for community assembly, as competition would be the result of niche space consumption, whereas facilitation would be the result of niche space construction for a given species.

Conclusion A significant part (>25%) of the species diversity in the studied plant community was due to the presence of foundation species. Each foundation species, because of its own morphology, created a different environment with a specific niche space, hosting some species that otherwise would not occur in this community. This resulted in overall higher species richness at the study site than at each particular microhabitat. This suggests that species-specific modifications of niche space by foundation species and the specific responses of associated species are relevant for community dynamics and strongly contribute to species diversity and composition. In other words, species specificity of plant–plant interactions is a key element of plant community diversity in our study system, while future studies with a similar objective in other ecosystems or with other organisms will help to clarify the role of species specificity of biotic interaction for biodiversity in general.

Acknowledgements This work was partially funded by Organismo Aut onomo Parques Nacionales (grant 0002/9). Additional funding was provided by MINECO (grant CGL2014-59010-R). C.S. was supported by the Swiss National Science Foundation (PBBEP3_128361; PZ00P3_148261). P.M. was additionally supported by MSMT LM2015078 and GACR 17-20839S. N.P. was recipient of a JAEPredoc CSIC research grant.

Authors contributions C.S. and Z.K. designed the study with input from P.M., N.P. and F.I.P.; C.S., P.M. and N.P. collected the data; C.S. and P.M. analysed the data; C.S. wrote the manuscript with contributions from all authors.

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Supporting Information Additional Supporting Information may be found in the online version of this article: Appendix S1. The three foundation species. Appendix S2. Circular sampling grid used for all plots. Appendix S3. Summary table of the standardized effect sizes (SES) of mean, range and coefficient of variation of the nearest neighbour distance in LDMC, SLA and vegetative plant height of all plants occupying the microhabitats. Appendix S4. Individual-based rarefaction curves using bootstrap estimation to show the relationship between the number of individuals and the number of species sampled. Appendix S5. Results of PERMANOVA testing for differences in species composition among the four microhabitats. Appendix S6. Results of PERMANOVA testing for differences in mean, range and dispersion of foundation species effect traits (branch density and canopy height) among the microhabitats characterized by foundation species. Appendix S7. Summary table of the foundation species effect traits: mean, range and coefficient of variation of the nearest neighbour distance for branch density and canopy height of the three foundation species. Appendix S8. Results of PERMANOVA testing for differences in mean, range and dispersion of response traits (LDMC, SLA, plant height) of all plants occupying the four different microhabitats. Appendix S9. Summary table of the mean, range and coefficient of variation of the nearest neighbour distance in LDMC, SLA and vegetative plant height of all plants occupying the microhabitats. Appendix S10. R scripts. Appendix S11. Data.

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