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Keywords:

  • competition;
  • environmental gradient;
  • facilitation;
  • ontogenetic shift;
  • ontogeny;
  • plant–plant interaction;
  • population structure;
  • size-class distribution

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
  • Environmental conditions and plant size may both alter the outcome of inter-specific plant–plant interactions, with seedlings generally facilitated more strongly than larger individuals in stressful habitats. However, the combined impact of plant size and environmental severity on interactions is poorly understood.
  • Here, we tested explicitly for the first time the hypothesis that ontogenetic shifts in interactions are delayed under increasingly severe conditions by examining the interaction between a grass, Agrostis magellanica, and a cushion plant, Azorella selago, along two severity gradients.
  • The impact of A. selago on A. magellanica abundance, but not reproductive effort, was related to A. magellanica size, with a trend for delayed shifts towards more negative interactions under greater environmental severity. Intermediate-sized individuals were most strongly facilitated, leading to differences in the size-class distribution of A. magellanica on the soil and on A. selago. The A. magellanica size-class distribution was more strongly affected by A. selago than by environmental severity, demonstrating that the plant–plant interaction impacts A. magellanica population structure more strongly than habitat conditions.
  • As ontogenetic shifts in plant–plant interactions cannot be assumed to be constant across severity gradients and may impact species population structure, studies examining the outcome of interactions need to consider the potential for size- or age-related variation in competition and facilitation.

Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The net outcome of interactions between plants varies through space and time, ranging from facilitation and mutualism (i.e. positive) to competition and parasitism (i.e. negative). Spatial variation in the net outcome of plant interactions is strongly linked to environmental conditions, with facilitative interactions generally dominating under conditions of abiotic extremes, low resource availability, high herbivory or intense disturbance (i.e. high environmental severity; sensu Brooker & Callaghan, 1998), and competition being more common in milder environments (Bertness & Callaway, 1994; although see also e.g. Maestre et al., 2009). The outcome of plant–plant interactions can also vary within and between years as environmental conditions fluctuate, with the strength of positive interactions increasing relative to negative interactions during more stressful periods (Tielbörger & Kadmon, 2000; Kikvidze et al., 2006; Sthultz et al., 2007). This spatial and temporal variation in the balance of positive and negative interactions is predicted to be related to environmental severity by the stress-gradient hypothesis (SGH; Bertness & Callaway, 1994; Brooker & Callaghan, 1998), an assumption that is well supported by the majority of studies that have tested the hypothesis (He et al., 2013).

Changes in individuals' size, age or life stage may also influence the outcome of interactions, although this source of temporal variation is less frequently studied (Callaway & Walker, 1997; Soliveres et al., 2010). As plants germinate, establish and grow, their physiological tolerances and resource requirements change, as does their influence on the surrounding environment (Parish & Bazzaz, 1985; Miriti, 2006). In consequence, the balance between the positive and negative components of plant–plant interactions often shifts as plants age, giving rise to ontogenetic shifts in the outcome of interactions (i.e. a change in the nature and/or strength of an interaction related to an individual's ontogeny). The majority of studies show a transition from facilitation during establishment (i.e. neighbouring plants benefit seedling survival) to the inhibition of, or a neutral effect on, adult plant growth and reproduction (Miriti, 2006; Reisman-Berman, 2007; Lortie & Turkington, 2008; Valiente-Banuet & Verdú, 2008; Armas & Pugnaire, 2009). This probably reflects the fact that larger plants often have greater resource requirements which increase their competitive impacts, and also usually have lower sensitivity to climatic extremes, reducing the benefits of environmental amelioration by neighbouring plants.

Schiffers & Tielbörger (2006) hypothesized that the timing of ontogenetic shifts could vary with environmental severity, with the net outcome of interactions remaining positive for longer under more stressful conditions. Thus, under greater environmental severity an ontogenetic shift in the interaction (from facilitation to competition) should be delayed. Sthultz et al. (2007) supported this hypothesis by demonstrating that at low altitudes Fallugia paradoxa facilitates the survival of Pinus edulis seedlings but increases the mortality of adult P. edulis (i.e. a negative ontogenetic shift). By contrast, at a more stressful high-altitude site, all life stages of P. edulis were facilitated by F. paradoxa, illustrating a marked change in the nature of the ontogenetic shift in this interaction with increasing environmental severity. Few other studies have determined whether ontogenetic shifts in plant interactions are affected by environmental conditions (Eränen & Kozlov, 2008; Soliveres et al., 2010), with none explicitly testing Schiffers & Tielbörger's (2006) hypothesis or examining any consequences of the ontogenetic shifts. Ignoring ontogenetic shifts in interactions could lead to incorrect interpretation of variation in the outcome of plant–plant interactions and to inaccurate broad generalizations, which may be especially critical for areas showing rapid changes in environmental severity (see e.g. Hansen et al., 2012). Specifically, the SGH's failure to incorporate ontogenetic shifts in interactions may account for some of the discrepancies between the model's predictions and observed patterns (He et al., 2013). Ontogenetic shifts therefore need to be examined more critically and incorporated more explicitly into plant–plant interaction models.

One potential impact of plant interactions and their associated ontogenetic shifts may be on species population structure, acting through altered survival and reproduction rates. However, studies of plant–plant interactions have generally focused either on the impact of neighbouring individuals on the performance of focal plants (e.g. survival, growth rate or photosynthetic efficiency; Cavieres et al., 2005; Sthultz et al., 2007; Armas & Pugnaire, 2009) or on the composition of the entire flora associated with benefactor species (including biomass, species richness and diversity; Tewksbury & Lloyd, 2001; Holzapfel et al., 2006; see also Gross et al., 2009). Use of these methods has yielded important insights into the effect of plant interactions at the individual and community levels (Brooker et al., 2008; Butterfield et al., 2013). However, effects on individuals result in variation at the community level only insofar as the former alter population-level parameters such as stage-specific survival or age-specific reproduction. The balance between mortality (including success of immigration), reproduction and emigration for each species largely determines community diversity (richness, abundance structure and size structure; e.g. Andrewartha & Birch, 1954; Ricklefs, 2008). In consequence, investigations at the population level are essential for understanding how the outcome of individual plant–plant interactions scales up to affect communities.

In this study, we investigated whether there was an ontogenetic shift in the impact of the sub-Antarctic cushion plant Azorella selago (benefactor) on the grass Agrostis magellanica (beneficiary), whether the nature and timing of the ontogenetic shift varied with environmental severity (examined along two different stress gradients), and the extent to which the interaction affected the population structure and reproductive output of A. magellanica.

Materials and Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Study site

Fieldwork was conducted on sub-Antarctic Marion Island (46º54′S, 32º45′E; 290 km2), located in the southern Indian Ocean (details in Chown & Froneman, 2008). This island has a hyper-oceanic climate, with cold but stable temperatures, strong winds, and high humidity, precipitation and cloud cover (Smith, 2002; although the island's climate is changing rapidly; le Roux & McGeoch, 2008a). The island supports a relatively depauparate vascular flora, with 38 vascular plants (Chown et al., 2013).

Altitude and wind exposure represent two important stress gradients on the island. At higher elevations, temperatures are lower and the temperature range more extreme, wind speeds are higher and the soil is more unstable and has a greater frequency and depth of freezing than at lower elevations (Lee et al., 2009; le Roux & McGeoch, 2010). While altitude is an indirect gradient representing multiple proximate environmental factors, under the alpine conditions of Marion Island it can be a useful surrogate for environmental severity (see Austin, 2002). Similarly, as a result of strong winds, exposed sites can be drier than sheltered equivalents, and plants growing there may experience accelerated moisture loss, enhanced cooling and wind-related physical damage (Bate & Smith, 1983; Pammenter et al., 1986; le Roux & McGeoch, 2010). Therefore, because of the direct impact of the mechanical stresses and the indirect effects of microclimatic modification caused by strong winds, wind exposure also provides a measure of a site's abiotic severity (Eränen & Kozlov, 2008).

Study species

We examined the interaction between the two most widespread vascular plant species on Marion Island: Azorella selago Hook. (Apiaceae) and Agrostis magellanica Lam. (Poaceae) (Huntley, 1971). Azorella selago has a compact, prostrate cushion growth form and is a slow-growing, long-lived and stress-tolerant species (Frenot et al., 1993; le Roux & McGeoch, 2004). As a result of the species' compact nature, individual plants retain their dead leaves, developing a rich humus-filled core below a thin surface of green leaves. This organic substrate is thermally buffered relative to the adjacent soil (Nyakatya & McGeoch, 2007), and probably also has higher nutrient and moisture content (observed for other species in this genus; e.g. Cavieres et al., 2005) (see also Hugo et al., 2004; McGeoch et al., 2008). As a result, A. selago provides a more favourable substrate than the surrounding mineral soil for many plants (le Roux & McGeoch, 2008c, 2010) and invertebrates (Barendse & Chown, 2001; Hugo et al., 2004). Agrostis magellanica is the most common species to grow on A. selago plants on Marion Island (Huntley, 1971). It is a perennial grass that occurs in most of Marion Island's habitats and it has the second largest altitudinal range of the island's vascular plants after A. selago (Huntley, 1971; le Roux & McGeoch, 2008b). As a consequence of the extreme longevity of some A. selago individuals (le Roux & McGeoch, 2004), multiple generations of A. magellanica may interact with a single A. selago plant. At low altitudes and in wind-sheltered sites, A. magellanica's performance is negatively impacted by growing on A. selago, but above 150 m elevation and at wind-exposed sites the grass is strongly facilitated by the cushion plant (le Roux & McGeoch, 2010).

Data collection

Agrostis magellanica individuals were collected off A. selago plants and from the adjacent soil along two exposed ridges from sea level to the upper altitudinal limit of vascular plant growth on Marion Island, at c. 20 m altitudinal intervals. In these habitats A. magellanica is the dominant vascular plant growing on A. selago, with the species average cover six times greater than the cover of all other plants combined (le Roux & McGeoch, 2010). In view of the compact canopy of A. selago plants and the rocky, rugose nature of the adjacent substrate in this habitat, A. selago plants are unlikely to trap a disproportionate abundance of seeds (Cavieres et al., 2005; Haussmann et al., 2010). Medium-sized A. selago cushion plants (maximum diameter between 0.3 and 0.6 m) were randomly selected, and all A. magellanica grasses rooted within the A. selago plants were carefully uprooted. A wire ring was moulded around the outer edge of each sampled A. selago cushion plant to reproduce the size and shape of the plant, and then placed 0.1 m from the cushion plant in a randomly selected direction. All A. magellanica individuals rooted within the adjacent soil sample were then collected. The proportion of the ‘soil’ sample covered by large rocks (i.e. large enough to inhibit the growth of grasses) was estimated, and the measurements of A. magellanica abundance, size, mass and reproductive effort at each site were scaled to account for variation in the area available to the grass before calculating interaction intensity (see ‘Data analysis’) (methodology detailed in le Roux & McGeoch, 2010).

In addition, variation in A. magellanica abundance, size, mass and reproductive effort on A. selago and on the adjacent soil was assessed along a wind exposure gradient by sampling eight pairs of A. selago cushions and adjacent soil at each of three sites on an exposed, low-altitude (c. 90 m above sea level (asl)) coastal ridge. The three sites were within 400 m of each other, but differed considerably in environmental severity as a result of differing exposure to the prevailing north-westerly winds (the sites were designated as high wind exposure, intermediate exposure, and low exposure; see le Roux & McGeoch, 2010 for further site details). Following the same methodology as for the altitudinal transects, all A. magellanica individuals were collected from medium-sized A. selago cushions and from adjacent paired soil areas of the same size. Decreasing biomass of soil-rooted A. magellanica with increasing altitude and exposure confirmed that our sampling designs represent ecologically relevant severity gradients (le Roux & McGeoch, 2010).

All harvested A. magellanica individuals (n = 12 155) were returned to the laboratory and dried at 60°C for 48 h. Mass (0.5 mg precision; AE260 Delta Range Balance; Mettler-Toledo, Columbus, OH, USA), number of inflorescences (i.e. current reproductive effort) and number of inflorescence stalks (i.e. an estimate of recent reproductive effort) were recorded for each individual. As A. magellanica abundance and mass, and the number of inflorescences and the number of inflorescence stalks, showed similar patterns, results are only detailed here for A. magellanica abundance and the number of inflorescence stalks (see Supporting Information Figs S1 and S2 for results of analyses of A. magellanica mass and number of inflorescences).

Data analysis

The mass of A. magellanica individuals collected in this study ranged from 0.5 mg to 19.3 g. Because most individuals were small (43% weighed < 10 mg), plant mass was log10-transformed before analysis. Agrostis magellanica individuals were then categorized into 13 size classes (0.25-mg-interval log10-transformed mass bins), with all individuals with a mass exceeding 103 mg grouped into the heaviest size class. Analyses were repeated using eight and 16 size classes, but as all analyses gave similar results, only results using 13 size classes are presented. Data from the two altitudinal transects showed similar patterns and were therefore pooled for analysis. These data were split into three altitude categories (< 150 m asl, low altitude; 150–300 m asl, mid altitude; > 300 m asl, high altitude) to represent three levels of increasing abiotic stress, with the first category comprising the elevations over which the majority of competitive impacts of A. selago on A. magellanica had been observed by le Roux & McGeoch (2010).

The impact of A. selago on A. magellanica was quantified using the relative interaction index (RII):

  • display math(Eqn 1)

where PT+N and PT–N represent the performance of A. magellanica in the presence and absence of A. selago respectively (Armas et al., 2004). RII is bounded between −1 and 1, with positive values indicating net facilitative interactions, negative values indicating competition, and larger absolute values indicating stronger intensity of the interaction. This index has performed well in other studies investigating the severity–interaction relationship (e.g. Schiffers & Tielbörger, 2006). RII was calculated for each size class of A. magellanica for each stress level, quantifying the impact of A. selago on the performance of the different size classes of the grass (i.e. abundance or number of inflorescence stalks; RIIabund and RIIinflor, respectively). The relationship between RII and A. magellanica size class was modelled using linear and second-order polynomial functions. Models were fitted using maximum likelihood estimation and assuming a beta distribution of the response variables. The beta distribution is suitable for modelling the dependent variables, as RII values are bounded continuous data (Ferrari & Cribari-Neto, 2004). The proportion of variance explained by each model was calculated as a pseudo R2 value (Ferrari & Cribari-Neto, 2004), and analysis of deviance was used to distinguish between competing models. Models were fitted using the gnlm package (Lindsey, 2007) in the R statistical programming language (R Development Core Team, 2011).

Quantile regression (Cade & Noon, 2003) was subsequently used to examine the lower boundary of the RII–A. magellanica size relationship (τ = 0.25; i.e. using the first quartile of the data), investigating whether the impact of A. selago on A. magellanica was constrained by the size of A. magellanica individuals (following e.g. Miriti, 2006). Linear and second-order polynomial models were fitted using the quantreg package (Koenker, 2009) in R, implementing an ANOVA (through the anova.qr function) to determine whether more complex models explained a significantly greater amount of the variation in the data than simpler nested models. Where quadratic models provided the best fit to the data, the fitted curve's turning point was determined and the 95% confidence intervals around the turning point were calculated (Zhou et al., 1993).

Kolmogorov–Smirnov (KS) tests were used to compare the distribution of A. magellanica size classes between different substrates and stress levels, employing Bonferroni-adjusted P values to account for multiple tests on the same data. These tests use the relative abundance of A. magellanica in each size class as a measure of the grass's population structure.

The mass of the smallest flowering A. magellanica individual was determined for each substrate (A. selago or soil) and stress level (low, mid or high altitude or wind exposure) to estimate the size threshold for reproduction in the grass under different conditions. In view of the greater abundance of A. magellanica on A. selago than on the soil, we also calculated the rarefied minimum mass of flowering A. magellanica growing on A. selago using a resampling approach. By randomly selecting (with replacement) the same number of flowering A. magellanica individuals growing on A. selago as were sampled from the soil, bias towards lower minimum flowering masses of A. magellanica growing on A. selago (as a consequence of sampling effects resulting simply from the greater abundance of grasses growing on the cushion plant) was avoided. This procedure was repeated 100 times, and the mean minimum mass of flowering A. magellanica calculated across all repeats.

Agrostis magellanica root:shoot ratios were calculated for each sample, with the Mann–Whitney U statistic used to test for significant differences between substrates and stress levels after trimming the 10% most extreme outliers (extreme values were predominantly associated with the smallest grasses, as the calculation of the ratio was imprecise for individuals with weights that were low relative to the sensitivity of the balance used to weigh them).

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The impact of A. selago on A. magellanica was generally positive, increasing the grass's abundance and inflorescence production relative to individuals growing on the adjacent soil in most size classes (i.e. 85% of all RIIabund values > 0 and 90% of RIIinflor values > 0; Table 1). Furthermore, A. selago's effect on A. magellanica abundance was significantly related to the size class of grasses considered (Table 1). Along the wind exposure gradient, the relationship between RIIabund and A. magellanica size was best described at all stress levels by quadratic functions (all with negative quadratic coefficients; Fig. 1a, Table 1). Therefore, A. selago increased the abundance of intermediate-sized A. magellanica most, relative to the abundance of the same A. magellanica size classes on the adjacent soil. By contrast, along the altitudinal gradient the form of the relationship differed according to stress level (Fig. 1b; Table 1); at low elevations the RIIabund was not related to A. magellanica size, while at intermediate altitudes the relationship was quadratic, with A. selago increasing the abundance of medium-sized grasses most. At high altitudes (i.e. under more stressful conditions) A. selago had the most positive effect on the abundance of the largest grasses (i.e. a positive linear relationship; Fig. 1b, Table 1).

Table 1. Results from regression of interaction intensity (relative interaction index (RII)) against Agrostis magellanica size class, for both types of stress gradient (wind exposure and altitude) and all stress levels (low, mid and high; relationships illustrated in Fig. 1)
  n Proportion RII values positiveBeta regression P Quantile regression F P Turning point ± SE 
Minimum adequate modelχ2Turning point ± SEMinimum adequate model
  1. n, number of data points (sum of size classes represented in each sample); χ2 and P, model test statistic and P value when compared with the null model of no relationship.

  2. a

    Quadratic models not sharing letters differ significantly (< 0.05) in their turning points.

  3. b

    Turning point presented for comparison, although the quadratic fit was not significantly better than the linear fit.

Exposure gradient
AbundanceLow990.81Quadratic6.940.0310.48 ± 0.04aaQuadratic29.83<0.0011.10 ± 0.06a
Mid990.92Quadratic10.350.0060.67 ± 0.05bQuadratic5.100.0081.99 ± 0.16b
High1020.97Quadratic27.33< 0.0010.74 ± 0.04bQuadratic9.84< 0.0012.60 ± 0.15c
InflorescencesLow360.78None   Null   
Mid470.96None   Quadratic3.180.0512.13 ± 0.40
High540.98None   Null   
Altitudinal gradient
AbundanceLow1360.57None   Quadratic2.570.0801.54 ± 0.13a
Mid2060.93Quadratic24.70< 0.0010.65 ± 0.02Quadratic12.08< 0.0012.29 ± 0.16b
High1260.88Linear4.740.029 Linear10.990.0012.88 ± 0.23bc
InflorescencesLow490.69None   Linear8.430.006 
Mid960.95None   Null   
High540.96None   Null   
image

Figure 1. Relationship between interaction intensity (relative interaction index for the Agrostis megellanica abundance (RIIabund); i.e. the impact of Azorella selago on A. magellanica abundance) and A. magellanica mass. (a) Wind exposure gradient; (b) altitudinal gradient. The size of symbols reflects the number of overlapping data points. Dashed lines show the best beta regression fit to the data, and dotted lines the best quantile regression fit (details in text and statistics in Table 1). Where a quadratic function gave the best fit, error bars above the panel indicate 1 SE on either side of the turning point.[Correction added after online publication 6 June 2013: in the preceding sentence the definition of RIIabund has been corrected.]

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Quantile regression revealed that the impact of A. selago on A. magellanica abundance was constrained by the size of A. magellanica individuals (Table 1). In five of the six stress gradient–stress level combinations, quadratic models provided a better fit than linear models to the lower bound of the RIIabundA. magellanica size relationship. Along the exposure gradient, the location of the turning points of the RIIabund–size relationship occurred at significantly greater size under higher environmental stress (Table 1, Fig. 1a). Similarly, along the altitudinal gradient the turning point in the quadratic curves was at increasingly larger A. magellanica sizes under progressively greater environmental severity (with no turning point at the highest elevation; Table 1, Fig. 1b). By contrast, the impact of A. selago on the number of A. magellanica inflorescences did not consistently vary with the size of grasses along the exposure or altitudinal gradient when using either beta or quantile regression (Table 1, Fig. S3).

Comparison of the population structures of A. magellanica growing on A. selago and on the soil revealed a positive effect of A. selago on the abundance of A. magellanica (Table 2), and particularly on the relative abundance of intermediate and large individuals (Figs 2, S4). The largest impact of A. selago on A. magellanica abundance was in the intermediate size classes (e.g. 100.75–102.75 mg; Figs 2, S1), with A. magellanica abundance on A. selago three to 17 times higher than on the soil (Table 2). Along the altitudinal gradient, A. magellanica population structure differed significantly between substrates (i.e. comparing grasses on A. selago and on soil at the same stress level; Table 3). By contrast, population structure did not differ between altitudinal bands when comparing grasses growing on the same substrate (i.e. size-class distribution was not different between low, mid and high altitudes for grasses growing on the same substrate; Table 3, see e.g. Fig. 2). The same trend was evident for A. magellanica population structure on the exposure gradient (i.e. higher KS statistics when comparing population structure between substrates than when comparing between wind exposure levels; Fig. S4, Table S1).

Table 2. The abundance and reproductive effort of Agrostis magellanica growing on the soil and on Azorella selago cushion plants at three stress levels (low, mid and high) along two types of stress gradient (altitude and wind exposure)
 Number of A. magellanica per sample (mean ± SE)Number of A. magellanica inflorescence stalks per sampleMinimum mass of flowering A. magellanica (mg)Agrostis magellanica root:shoot ratio (mean ± SE)
Soil A. selago Soil A. selago Soil A. selago A. selago (rarefied; mean ± SE)Soil A. selago
  1. The mass of the smallest flowering A. magellanica and the mean root:shoot ratio at each stress level on each gradient are also indicated.

  2. a

    Significant difference between A. magellanica samples growing on A. selago and on the adjacent soil (< 0.05; Mann–Whitney U-test).

Altitudinal gradient
Low68.4 ± 17.1174.8 ± 63.011.5 ± 6.214.4 ± 5.11141953.2 ± 2.5a0.32 ± 0.030.19 ± 0.04a
Mid23.6 ± 7.8178.5 ± 27.6a0.7 ± 0.324.3 ± 5.5a428854.6 ± 3.7a0.38 ± 0.050.25 ± 0.02a
High6.8 ± 2.352.2 ± 11.4a0.3 ± 0.321.8 ± 5.9a30766.0 ± 4.9a0.37 ± 0.070.29 ± 0.03
Exposure gradient
Low67.0 ± 21.9225.8 ± 35.5a4.3 ± 2.213.3 ± 5.2432943.1 ± 1.30.40 ± 0.080.25 ± 0.01a
Mid18.9 ± 5.2158.1 ± 45.5a3.3 ± 1.424.8 ± 4.7a1161760.0 ± 3.1a0.37 ± 0.080.22 ± 0.02
High8.5 ± 1.0146.1 ± 21.1a0.5 ± 0.433.9 ± 6.4a12112134.8 ± 15.80.42 ± 0.070.19 ± 0.01a
Table 3. Results of Kolmogorov–Smirnov tests comparing Agrostis magellanica size-class distributions across stress levels (high, mid and low altitude) and substrate types (growing on Azorella selago versus growing on the adjacent soil) along the altitudinal gradient
Stress levelSubstrate comparisonD statisticP value
LowSoil versus A. selago0.320< 0.001a
MidSoil versus A. selago0.353< 0.001a
HighSoil versus A. selago0.474< 0.001a
SubstrateStress level comparison  
  1. a

    Significant after Bonferroni correction.

SoilLow versus mid0.0780.093
SoilHigh versus mid0.0910.650
SoilLow versus high0.1700.033
A. selago Low versus mid0.0170.862
A. selago High versus mid0.0780.005
A. selago Low versus high0.0760.010
image

Figure 2. Size-class distribution of Agrostis magellanica rooted in Azorella selago or in the adjacent soil, in three altitudinal bands (low, < 150 m above sea level (asl); mid, 150–300 m asl; high, > 300 m asl). Black bars indicate the size-class distribution of flowering individuals, while light and dark grey bars indicate all individuals greater than the observed or rarefied size threshold for flowering, respectively. Note the differences in the scaling of the y-axis between panels.

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The minimum flowering size (i.e. reproductive threshold) of A. magellanica differed between individuals growing on the soil and on A. selago, with the grass flowering at a smaller minimum size on A. selago (Table 2; see also Figs 2, S4). Rarefied estimates of A. magellanica's minimum flowering size on A. selago were considerably higher than the observed values, but were still significantly smaller than for grasses growing on the soil in three comparisons (Table 2). Moreover, more inflorescences were produced by grasses growing on A. selago than by those growing on the adjacent soil at all stress levels, with > 99% of inflorescence stalks at high altitudes and wind exposure being carried by A. magellanica individuals growing on A. selago (Table 2). Root:shoot ratios were consistently higher in soil-rooted A. magellanica than in individuals growing on A. selago, with the differences being significant in four of the six comparisons, indicating a greater proportion of biomass allocated to below-ground growth in soil-rooted individuals (Table 2).

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The impact of A. selago on A. magellanica was related to A. magellanica size, but not consistently so, with the form of the relationship varying with A. magellanica performance measure and stress gradient type. Moreover, none of the significant ontogenetic shifts documented were of the expected form (i.e. monotonically negative), with the most positive impact of A. selago on the abundance of intermediate-sized grasses. However, despite the variability in the ontogenetic shifts, there was a clear trend for the shift towards more negative interactions to be delayed under greater environmental severity. As a result, the hypothesis that ontogenetic shifts in plant interactions are delayed under more stressful conditions could not be rejected.

Effects of ontogenetic stage

The nonmonotonic relationship between RIIabund and A. magellanica size was unexpected, as seedlings are generally the most strongly facilitated life stage, while the largest individuals usually have neutral or negative interactions with other plants (although more complicated ontogenetic shifts have been described; e.g. Rousset & Lepart, 2000). The A. selago–A. magellanica interaction contrasts with this expected pattern, as the abundance of the smallest A. magellanica individuals was not most strongly increased by A. selago (Fig. 1). This pattern was more pronounced in the quantile regression, suggesting that, while other factors also influence the impact of A. selago on A. magellanica abundance, the occurrence of strong negative interactions are least likely for grasses of intermediate size. The ontogenetic shift observed suggests that there may be multiple facilitative and competitive components to the A. selago–A. magellanica interactions. Indeed, it is likely that with increasing size A. magellanica individuals probably compete more strongly with A. selago for space, nutrients and water, while the benefit of environmental amelioration by the cushion plant probably remains similar (or declines slightly) for larger grasses. However, an additional mechanism that exerts a strong negative effect on the smallest grasses growing on A. selago must also be important to produce a unimodal RIIabundA. magellanica size relationship. One potential mechanism is the overgrowing of small A. magellanica grasses by A. selago, thereby reducing their survival. Indeed, this is quite possible as A. selago shows rapid shoot elongation under shading (le Roux et al., 2005; although other mechanisms may also contribute, including inhibited germination; Olofsson et al., 1999). Therefore, intermediate-sized grasses may benefit most from the interaction with A. selago by being large enough that A. selago cannot overgrow them, but still small enough to avoid strong competition with A. selago and to benefit from environmental amelioration by the cushion plant. By contrast, A. magellanica individuals growing in the open soil probably have a consistently lower probability of mortality with increasing size, as the more extensive root systems of larger individuals would reduce their vulnerability to soil moisture deficits and the chance of frost-heaving (Kleier & Rundel, 2004; Haussmann et al., 2010).

The difference between the shape and significance of the RII–A. magellanica size relationship for the abundance of individuals and of inflorescences fit with the current understanding that the impact of plant interactions differs between performance measures (Brooker et al., 2008). Previous studies have shown that plant survival generally responds strongly to environmental amelioration by neighbouring plants, but that reproduction is less affected by changes in environmental severity caused by the presence or absence of facilitators (Goldberg et al., 1999; Maestre et al., 2005). Thus, a similar pattern may exist in the size dependence of an interaction, with ontogenetic shifts in the benefactor's impact being more pronounced on the beneficiary's abundance than on its reproductive output.

Impacts on population structure

The A. selagoA. magellanica interaction altered the population structure of A. magellanica, with a disproportionately strong increase in medium-size grasses. The shape of the A. magellanica size-class distribution was more strongly affected by the occurrence of A. selago than by differences in altitude, suggesting that the plant–plant interaction has a stronger impact than variation in environmental severity, at least along one of the stress gradients. Differences in the population structure of A. magellanica growing on the soil and on A. selago are probably a result of improved growth and/or survival of individuals on A. selago, with the lower root:shoot ratio observed for the grasses growing on the cushion plant suggesting one possible mechanism. The lower root:shoot ratio probably reflects a reduced requirement for resource allocation to the production of roots when growing on A. selago as a result of the more stable substrate (especially in contrast to the frequent freeze–thaw cycles in the soil; Boelhouwers et al., 2003) and increased availability of water and nutrients that the cushion plant offers (McGeoch et al., 2008; Anthelme et al., 2012). Therefore, through altering the fine-scale environmental conditions experienced by A. magellanica, A. selago also affects the expression of a functional trait in A. magellanica (Cavieres et al., 2005), which may contribute to the interaction's impact on A. magellanica population structure.

Reproductive effort

The presence of A. selago also strongly impacted A. magellanica's reproductive output, increasing the grasses' inflorescence production greatly. Our results identified three A. selago-driven changes in the biology and population structure of A. magellanica which contribute to the 1.3- to 73-fold difference in reproductive output between soil-rooted and A. selago-associated A. magellanica populations. First, A. magellanica individuals growing on A. selago tended to flower at smaller sizes than individuals growing on the soil, possibly as a result of the altered resource allocation associated with changes in the root:shoot ratio. The observation that grasses growing on the soil initiate reproduction at a larger size is in agreement with previous studies that demonstrated that flowering is increasingly delayed under progressively more negative interactions (Weiner, 1988). Secondly, the A. selago–A. magellanica interaction disproportionately increased the relative abundance of medium-sized, and thus potentially reproductive, grasses. Finally, the total abundance of A. magellanica individuals of all sizes was increased by A. selago. As a result, a larger number (in absolute and relative terms) of A. magellanica grasses exceed the grasses' minimum flowering size when growing on A. selago, thereby increasing the abundance of potentially reproductive individuals. Thus, the population's reproductive effort is positively affected by A. selago via changes in the grass's abundance, population structure and size threshold for reproduction, highlighting the diverse mechanisms through which this facilitative interaction operates.

Conclusions

Three important conclusions are evident from this study. First, there is a strong ontogenetic shift in the effect of A. selago on A. magellanica, with this size-dependent interaction showing a previously undocumented form (i.e. strongest facilitation for intermediate-size individuals). Secondly, our results provide support for Schiffers & Tielbörger's (2006) hypothesis that ontogenetic shifts may be delayed under greater environmental severity, illustrating that the nature of ontogenetic shifts can be dependent on environmental conditions. Finally, we show for the first time that the relative abundance structure of a beneficiary species is more strongly affected by its interaction with the benefactor species than by variation in abiotic conditions, demonstrating that biotic interactions can be more important than environmental severity in some situations.

As a consequence of the potential for ontogenetic shifts in plant–plant interactions, studies examining interactions need to consider facilitative (or competitive) effects on both the abundance and population structure of beneficiary species, as focusing on the former alone may fail to capture important aspects of the latter. Thus, following the recent calls for the refinement of the stress-gradient hypothesis to reflect improved understanding of competition and facilitation (Maestre et al., 2009; Malkinson & Tielbörger, 2010), we argue that ontogenetic shifts in plant–plant interactions also need to be included in this framework. More generally, by examining the changes in the A. selagoA. magellanica interaction along two environmental gradients, these results highlight the potential for climate change to affect ontogenetic shifts in species interactions. Because shifts in temperature and/or precipitation patterns may affect both the phenology and ontogeny of species (Parmesan, 2006; Barton, 2010), this is a mechanism through which changing climatic conditions could alter species interactions (Klanderud, 2005; Cavieres & Sierra-Almeida, 2012), a key challenge for climate change impact forecasting (Wisz et al., 2013). Therefore, models aiming to accurately predict species- and community-level responses to changing environmental conditions need to consider how shifts in species' ontogenies (via changes in development rates and/or phenology) may affect their interactions with co-occurring species (Barton, 2010; Yang & Rudolf, 2010).

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Financial support was provided by the South African National Antarctic Program through grants from the National Research Foundation (grant numbers 2069543, SNA2004070900002 and SNA2011110700005) and the Centre for Invasion Biology. We thank three anonymous reviewers for their helpful, constructive comments.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Please note: Wiley Blackwell are not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office.

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Fig. S1 Relationship between interaction intensity and Agrostis magellanica mass.

Fig. S2 Relationship between interaction intensity and the abundance of Agrostis magellanica inflorescences.

Fig. S3 Relationship between interaction intensity and the abundance of Agrostis magellanica inflorescence stalks.

Fig. S4 Size-class distribution of Agrostis magellanica growing in the presence and absence of Azorella selago, at three wind exposure levels.

Table S1 Results of Kolmogorov–Smirnov tests comparing Agrostis magellanica size class distributions across stress levels and substrate types along the wind exposure gradient