• flower density;
  • germination rate;
  • isolation distance;
  • local density;
  • pollen limitation;
  • pollen supplementation;
  • seed production;
  • seed quality


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  • • 
    Plants growing at low density can suffer from Allee effects as a result of pollen limitation. Previous studies of Allee effects have focused on the effects of variation among populations in size or density on reproduction. Here, the effects of plant distribution within populations on fitness components are explored in a rare plant, Aconitum napellus ssp. lusitanicum, and ecological and genetic mechanisms underlying these effects are identified.
  • • 
    To detect pollen limitation, seed production was compared under natural versus hand-supplemented pollinations on inflorescences of different sizes in natural patches differing both in flower density and in isolation from other patches. Germination rate and juvenile survival of seeds produced in low- and high-density patches were also compared.
  • • 
    Pollen-supplemented flowers always produced more seeds than open-pollinated flowers, especially among small plants and plants growing at low density. Offspring produced in low-density patches exhibited lower fitness that those produced in high-density patches. This could have been caused by post-fertilization mechanisms, including inbreeding depression or differential maternal resource allocation.
  • • 
    These results show that Allee effects on fitness components (ecological and genetic Allee effects) occur within A. napellus populations at different spatial scales. The spatial distribution of plants seems to be a crucial factor affecting reproductive output and fitness.


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

Recent interest in and reappraisal of Allee effects have increased our appreciation of their ecological and evolutionary consequences (Courchamp et al., 1999; Stephens & Sutherland, 1999; Stephens et al., 1999; Berec et al., 2007). Allee effects comprise two different concepts (Stephens et al., 1999). The ‘component’ Allee effect refers to a positive relationship between any measurable component of individual fitness and population size or density, whereas the ‘demographic’ Allee effect is defined as a positive relationship between population size (or density) and the overall population growth rate. Consequently, demographic Allee effects are the result of different, and often multiple, component Allee effects (Berec et al., 2007).

In plants, the most frequently studied mechanisms causing Allee effects are those that affect reproduction. At low density or in small populations, a decline in reproductive success can often be attributed to the difficulty in finding a mate (Bessa-Gomes et al., 2003). For example, plants growing in small populations (Widén, 1993; Kéry et al., 2000; Brys et al., 2004; Waites & gren, 2004; Elam et al., 2007) or in low-density populations (Kunin, 1992, 1997; Groom, 1998; Bosch & Waser, 1999; Colling et al., 2004; Kirchner et al., 2005) may attract fewer pollinators than plants in large or high-density populations. When flowers produce fewer seeds because they have received fewer pollen grains than necessary to fertilize all of their ovules, this reduction in fecundity is referred to as pollen quantity limitation (Aizen & Harder, 2007) or as an ‘ecological’ Allee effect (Van Kleunen & Johnson, 2005), which may be more likely at low population densities or in small populations (reviewed in Larson & Barrett, 2000; Ghazoul, 2005; Knight et al., 2005).

While pollen quantity limitation is a well-documented mechanism causing declines in seed production per fruit or per plant (Ashman et al., 2004, Knight et al., 2006), reduced fecundity can also result from mating between unsuitable mates. The quality of deposited pollen may decline with reductions in population size or density if, for example, the frequency of mating between relatives or selfing increases. A decline in reproduction as a result of the receipt of genetically inappropriate pollen is termed ‘pollen quality limitation’ (Aizen & Harder, 2007). This process can result in a ‘genetic’ Allee effect: that is, a genetic-level mechanism resulting in a positive relationship between one or more fitness components and population size or density (Berec et al., 2007), which is also common (Stephens et al., 1999; Fischer et al., 2000, 2003; Willi et al., 2005, Berec et al., 2007). In many cases, pollen limitations in quantity and quality may interact synergistically, increasing the threat to small populations (Oostermeijer, 2000; Berec et al., 2007). These two mechanisms, pollen quantity limitation/ecological Allee effect and pollen quality limitation/genetic Allee effect, can both limit seed production, while inbreeding depression as a result of the latter can also reduce the survival and fecundity of seed offspring.

Most previous studies of the Allee effect have focused on the population level, comparing the dynamics of populations of different sizes or of different densities. Yet, studies at this level can fail to detect the occurrence of pollen limitation within populations because compensatory effects can occur among patches of individuals depending on their size or density (Luzuriaga et al., 2006; Stehlik et al., 2006; Wagenius, 2006). Given that local population or floral densities can significantly affect pollinator visitation rates and foraging behaviour, patterns of plant distribution may affect the likelihood of population persistence in ways that may be undetectable at the population level (Stephens et al., 2002; Wiegand et al., 2002; Wagenius, 2006). For example, where habitats are fragmented or deteriorating, low-density or isolated patches may become increasingly numerous and go extinct progressively, while the colonization of new sites becomes increasingly unlikely because of an insufficient number of founders (Ovaskainen & Hanski, 2001). The combination of these two phenomena certainly decreases overall population growth rates and may threaten the local or regional persistence of species. Theoretical models of the Allee effects in subdivided populations have produced various outcomes concerning the role of the Allee effects on metapopulation persistence, depending on the strength of the Allee effect (weak or strong), the frequency of dispersal, and deme size (e.g. Amarasekare, 1998, 2004; Gyllenberg & Hemminki, 1999; Ovaskainen & Hanski, 2001; Rampal et al., 2002). Consequently, within-population spatial structure may affect the magnitude and frequency of Allee effects, as shown in recent studies of conservation (Luzuriaga et al., 2006; Wagenius, 2006), plant mating system (Stehlik et al., 2006), biological invasions (Taylor & Hastings, 2005) and urban ecology (Cheptou & Avendaño, 2006).

To investigate the role of within-population structure on the Allee effect, we conducted a field study to determine the effects of plant distribution within populations on fitness components (seed production, seed mass, germination rate and juvenile survival). Our study system comprised three wild populations of Aconitum napellus ssp. lusitanicum (Ranunculaceae), which naturally occurs along lowland rivers but is rare and protected in the Parisian region (France), where it has < 10 remnant populations. Its recent decline appears to be attributable to the disappearance of suitable wet habitats in this part of France.

In this paper, we measured component Allee effects on seed production, germination rate and juvenile survival of plants of different sizes growing in patches of various densities and isolation within natural populations. We also estimated the relative importance of ecological versus genetic Allee effects on these fitness components.

Materials and Methods

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

Plant species

Aconitum napellus L. ssp. lusitanicum Rouy is a European perennial herb that can reproduce both sexually through seed production and asexually through the formation of rhizomes. It inhabits wet habitats, primarily riparian zones. In February, plants emerge from seeds or rhizomes, forming small clumps (20–50 cm in diameter) that often represent a single genet (Le Cadre, 2005). Flowering spikes of dark-blue, purple or (rarely) white flowers develop during late spring. From June to September, up to 40 zygomorphic flowers gradually open on the main spike of the plant, from base to apex. On some individuals, secondary lateral spikes develop bearing up to 10 flowers. Each flower is hermaphroditic and is pollinated primarily by bumblebees attracted by the two nectar-producing petals (Laverty & Plowright, 1988; Utelli & Roy, 2000; S. Le Cadre, pers. obs.). After pollination, up to three follicles develop from a single flower. Seeds (1–15 per follicle) are then dispersed in August–October. The life cycle of A. napellus is a bit unusual. At full maturity, a ramet flowers and then dies, giving rise to a new small rhizome that will not reach flowering until 3 yr later. As a result, all ramets and inflorescences observed in this study were measured in only one of the two years.

Populations and patches

We conducted our study in three natural populations (P1, S1 and S2) of the Parisian region during the summers of 2000 and 2001 (Fig. 1). The populations consisted of clumps, more or less aggregated, that flowered more or less intensively. Thus, populations differed in the spatial distribution of inflorescences produced (Table 1).


Figure 1. Map of studied populations of Aconitum napellus ssp. lusitanicum in the Parisian region (shaded region) and distances between them.

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Table 1.  Characteristics of the three studied populations of Aconitum napellus ssp. lusitanicum
PopulationYearNumber of inflorescences (mean–variance of number of inflorescences/patch)Inflorescence density/m2Number of patchesNumber of studied inflorescences/type of treatmentNumber of studied flowers/treatment
  1. The number of inflorescences, the inflorescence density (number of inflorescences divided by the spatial area occupied by the population) and the number of patches are shown per population (P1, S1 and S2) and per year (2000 and 2001). The number of inflorescences included in each pollination treatment is shown: O (one open-pollinated flower only), Wp-Ap-O (one within-patch hand-supplemented pollination (Wp), one among-patch hand-supplemented pollination (Ap), and one open pollination (O) on the same inflorescence), Ap-Ap-O (two among-patch hand-supplemented pollinations (Ap) and one open pollination (O) on the same inflorescence) and G-WpC (one geitonogamous cross (G) and one within-patch cross (WpC) on the same inflorescence; both G and WpC flowers were bagged and emasculated). The number of studied flowers is also shown per treatment: that is, total open pollinations (Otot; open pollinations monitored on all inflorescences), hand-supplemented pollinations (within-patch (Wp), among-patch (Ap) and between-population (BP)) and crosses (geitonogamous (G) and within-patch (WpC)). Numbers in parentheses indicate fruits lost during the experiment.

P12000 35 (2.92–2.81)0.10012 20 5 –10 2555 –2020
 2001 48 (4.36–7.65)0.14511 2818 – – 461818 – – –
S12000 37 (7.40–4.80)0.027 5 23 8 2 – 337 (1)8 4 – –
 2001 33 (5.50–7.10)0.024 6 2011 – – 311111 – – –
S22000 18 (3.60–6.30)0.128 5  6 7 5 – 186 (1)710 – –
 2001 55 (4.58–2.99)0.39012 2217 5 – 441714 (3)10 – –
Total 226 511196612101976463242020

If a positive relationship exists between reproductive success and density, the scale at which it is detectable depends on the factor that causes it. For example, if the relationship is mediated by the effect of density on the pattern of pollinator visitation, then it will be determined by the distribution of distances to which bumblebees disperse pollen. We based our sampling protocol on permutation tests used to estimate the correlation between seed production and local flower density for patches of different sizes (circular patches from 1 to 20 m in diameter around each focal inflorescence; see Harvey & Pagel, 1991 for a description of the utility of such tests). The observed relationship between seed production and patch size was compared against a null model in which seed production is unrelated to patch size. The slope of each regression was tested against a distribution of slopes that we generated by re-sampling 10 000 times from the observed data. We found that the correlation was highest for patches of 1 m in diameter (b = 0.246, R2 = 0.64) as also found by Roll et al. (1997). Thus, each population was arbitrarily divided into nonoverlapping circular patches (5–12) of 1 m in diameter (Table 1). Within each of these patches, we randomly chose one to 12 flowering A. napellus inflorescences. A total of 207 inflorescences were studied; 197 were included in our experimental study of pollen limitation and the effect of pollen source on seed production and quality, and the 10 remaining inflorescences were included only in the study of the effect of pollen source (Table 1).

Quantification of Allee effects

In order to determine whether abiotic differences in patch quality (e.g. soil resources or water supply) could explain differences in seed production, we examined whether the inflorescence size in A. napellus (which may reflect variation in patch quality) varies positively with local flower density. Plants growing in resource-limited patches are expected to be smaller and to produce less seeds. We thus measured and compared the stem height, the number of axillary spikes, and the number of flowers per inflorescence of 52 of the 197 focal inflorescences.

Pollination experiments  On each of the 197 inflorescences we studied one to three target flowers and their resulting fruits. For each target flower, the surrounding conspecific flower density was measured by counting the number of open flowers on its inflorescence (hereafter called ‘floral display’), and by counting the total number of open aconite flowers on the other inflorescences within the patch (hereafter called ‘local flower density’). For each patch, we measured the distance between the focal patch and its closest arbitrary neighboring flowering patch (hereafter called ‘isolation distance’), and the number of flowering individuals of other nectariferous species within the patch (Cirsium oleraceum, Lythrum salicaria, Galeopsis tetrahit, Epilobium hirsutum and Rubus caesius), hereafter called ‘other flowering nectariferous individuals’. All measurements were performed on these inflorescences.

Among the 197 inflorescences, 64 were randomly chosen on which a second target flower was sampled at random from among the open flowers on the inflorescence; this flower was hand-pollinated to provide supplemental pollen but otherwise unmanipulated. For hand supplementations, flowers on a different inflorescence within the same patch were harvested and used to pollinate the target flowers. To avoid crosses within the same genet, we used a donor flower as far as possible from the flower to be pollinated. The pollinations were performed by rubbing the harvested flower against the target one so that the anthers of one brushed against the stigma of the other. To estimate the magnitude of pollen limitation in 2000 and 2001, we compared the seed production of 197 open-pollinated flowers (O) located on separate inflorescences to that of one within-patch hand-supplemented flower (Wp) on each of 64 of these 197 inflorescences (Table 1).

Three types of experiment were conducted in natural populations to test whether pollen source had a significant effect on the reproductive success of A. napellus. In the first experiment, 10 inflorescences from the P1 population were bagged to determine whether spontaneous self-fertilization was possible. In the second experiment, 20 flowers from the P1 population were emasculated in the bud, manually pollinated and then bagged. Two types of pollen treatment were performed on these emasculated flowers: geitonogamy (G; 10 flowers) and within-patch crosses (WpC; 10 flowers; Table 1). For geitonogamous crosses, a flower from the same inflorescence was used as the pollen donor; for within-patch crosses, pollen from a different inflorescence within the same patch was used to pollinate the target flower. In the third experiment, three treatments were performed in each population: within-patch pollination (Wp; 64 flowers among three populations; same data as for estimating pollen limitation), among-patch pollination (Ap; 63 flowers, pollinated on the same inflorescence as the within-patch hand-supplemented pollinations) and between-population pollination (BP; 24 flowers, two flowers per inflorescence; Table 1). Here, the flowers were neither emasculated nor bagged. Crosses between populations were performed between S1 and S2 a few minutes after pollen collection. Flowers that provided pollen were randomly collected from inflorescences of the different sampled patches (not > 2 flowers per inflorescence).

Manipulation effect  Experimental treatments may affect the seed production of the other flowers on the same plant through reallocation of resources (Ashman et al., 2004, Knight et al., 2006). To test this, we compared the seed production of 64 open-pollinated flowers from the same inflorescences as the hand-pollinated ones to that of the 119 open-pollinated flowers from inflorescences on which no hand-pollination had been performed (Table 1).

Estimation of reproductive success  Reproductive success was estimated by assessing seed production per flower, and, for open-pollinated flowers only, seed quality (biomass) and offspring fitness (germination rate and juvenile survival).

Seed production  Because in this species the seeds fall to the ground as soon as follicles ripen, it was not possible to estimate the number of seeds in fully mature follicles. Seed production was therefore assessed in the immature (still closed) fruits from the 197 open-pollinated and 64 hand-pollinated flowers from the randomly chosen inflorescences. These fruits contained seeds that had almost reached their full size, so the number of seeds counted is the same as it would have been had they been fully ripe.

Seed quality and offspring fitness  As immature seeds were used to estimate reproductive success, it was not possible to use them to measure seed quality (as germination success or seedling mortality). Seed quality was estimated from another data set. We measured the individual seed mass of 440 ripe seeds produced by 43 mature follicles (one per inflorescence) from open-pollinated flowers randomly collected in the S1 (330 seeds) and S2 (110 seeds) populations in late September 2001 (population P1 was not included in this part of the study because of technical constraints). In late September, all flowers had wilted. It was therefore not possible to count the number of open flowers to measure local density. Hence we used the global number of mature follicles around each sampled follicle within a patch of 1 m in diameter to estimate and categorize local fruit density into two classes (high: ≥ 15 flowers; or low: < 15 flowers). A total of 235 seeds were collected in low-density patches and 205 in high-density patches. A sample of 170 seeds (85 each from low- vs high-density patches) were then cultivated in the outdoor garden of the Conservatoire Botanique National du Bassin Parisien (CBNBP) located in the center of Paris. In October 2001, five seeds per fruit were sown in square pots (7 × 7 × 8 cm deep) filled with sterilized soil. Pots were monitored twice weekly for 37 wk for seedling emergence and juvenile survival. The positions of the pots in the garden were randomized during each monitoring event.

Statistical analysis

Statistical analyses were performed using the r environment (Ihaka & Gentleman, 1996). We used linear mixed effects models (lme function of the nmle package of r) to study quantitative variables and generalized linear mixed effect models (glmmPQL function in the MASS library for r; Venables & Ripley, 2002) to study binomial or Poisson-distributed variables. The spatial structure of the data was taken into account by using hierarchical random effects such as inflorescence nested within patch nested within population. This enables one to account for the potential nonindependence of the observations within an inflorescence, patch, or population. Each random effect was tested by comparing two nested models – one with and one without the random effect – using a log likelihood ratio test.

The glmmPQL function assumes multivariate normal random effects and uses penalized quasi-likelihood estimation (Lin & Breslow, 1996). The significance of the fixed effect was determined with F-tests in the lme models and with t-tests in the glmmPQL models. Complex models were simplified by a backward selection process that consists of sequentially removing the nonsignificant interactions. The initial full model was the one that included all fixed effects and their interactions. Model parameters were estimated with restricted maximum likelihood methods. We used a variance function (varIdent of the nlme library) that allows different variances for each level of a stratification variable for modeling heteroscedasticity where necessary (Pinheiro & Bates, 2000).

To detect a relationship between inflorescence morphology and local flower density we used mixed models with local flower density as a fixed effect. As we had sampled several flowers within a single patch, and several patches within a single population, we included patch (n = 27) as a hierarchical random effects factor nested within population (n = 3). Stem height was analyzed with a linear mixed effect model (lme function) whereas the number of flowers on the main spike and the number of axillary flowers were modeled with generalized linear mixed effect models (glmmPQL function) using a Poisson distribution and a log link function.

Seed production – quantification of pollen limitation  The number of seeds per flower was analyzed using a linear mixed effect model (lme function). We used year (2000 and 2001) and pollination treatment (open (O) or within-patch hand-pollinated (Wp)) as categorical fixed variables and local flower density (ln transformed), floral display, patch isolation distance and the number of other flowering nectariferous plants as continuous fixed variables. Random effects were inflorescence (n = 154) nested within patch (n = 51) nested within population (n = 3). We started by running a complex model that included the six fixed effects and their interactions and then simplified it by a sequential backward selection.

Seed production – effect of pollen source  We tested for the effect of pollen source on reproduction by analyzing the number of seeds produced by the pollen-supplemented flowers with a linear mixed effect model. Pollen origin (five categories: geitonogamous (G), within-patch (emasculated (WpC) and not (Wp), treated separately in the analysis), among-patch (Ap) and between-population (BP)) was treated as a fixed categorical effect and inflorescence nested within patch nested within population as random effects.

Seed quality and offspring fitness – seed mass  The seed masses were analyzed with a linear mixed model (lme function) with local flower density (high or low) as a fixed effect and fruit nested within patch nested within population as random effects.

Seed quality and offspring fitness – germination rate  When studying seed germination, variables of interest are the proportion of seeds that germinate and the time until an event occurs, for example the time to germinate (for seeds that germinate during the experiment) or the time to the end of the experiment (for seeds that do not germinate). The corresponding ‘rate of event’– here ‘germination rate’– is also known as the ‘hazard rate’ and can be analyzed using failure-time analysis models (Fox, 2001). The hazard rate was modelled through a Cox proportional hazard model (coxph function, from package survival, r) with local flower density and population as effects and seed weight as a covariate. The potential for correlation among groups of seeds from the same pot was taken into account by computing a robust variance (cluster option; Therneau & Grambsch, 2000).

Seed quality and offspring fitness – juvenile survival  Juvenile survival was modeled with a generalized linear mixed model (glmmPQL function) using a binomial distribution and a logit link function. Local flower density (high or low) was used as a fixed effect and pot nested within fruit nested within patch nested within population as random effects.


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

After accounting for differences in local flower density, isolation distance and floral display, we detected no significant differences among populations with respect to any fitness component (inline image, P  > 0.56). There were also no differences among patches (inline image, P  > 0.68) except with respect to the number of seeds per flower (inline image, P = 0.013). In addition, we detected no significant differences among inflorescences with respect to fitness components (inline image, P > 0.34). These random terms were, however, always retained in the final models, in order to take into account the structure of the experimental design.

We detected no effect of local flower density on the number of flowers on the principal spike (t1,23 = 0.35, P = 0.73), the number of secondary spikes (t1,23 = 1.40, P = 0.17) or stem height (F1,23 = 0.86, P = 0.36). We consequently inferred that patch quality (e.g. with respect to resource or water supply) did not differ significantly among patches, although it is conceivable that abiotic differences among patches affected floral density but no other inflorescence traits.

Seed production

Quantification of pollen limitation  There was no significant difference in the number of seeds per flower between open-pollinated flowers produced by inflorescences on which one flower had been manipulated and open-pollinated flowers produced by inflorescences that had not been manipulated (F1,142 = 2.007, P = 0.159). This indicates that A. napellus did not reallocate resources from open-pollinated flowers to hand-pollinated flowers. Nor did we find an effect of year on the number of seeds produced per flower (Table 2). The number of other flowering species growing in the vicinity of A. napellus did not influence its seed production (Table 2).

Table 2.  Results from a linear mixed model of the number of seeds per flower
Fixed effects
SourceEstimate (95% CI)d.f.F-valueP-value
  1. Year (2000, 2001), floral display (the number of opened flowers on the studied inflorescence), local density (the number of flowers within a radius of 50 cm), isolation distance (distance in meters between the focal patch and its closest neighboring flowering patch), the number of individuals belonging to other nectariferous species within a radius of 50 cm and pollination treatment (open pollinations (O) and within-patch hand-supplemented pollinations (Wp)) were analyzed as fixed effects. Population, patch nested within population and inflorescence nested within patch nested within population were used as random effects.

  2. CI, confidence interval.

Intercept−6.27 (−3.69, −1.11)1, 10210.090.002
Year (2001 compared with 2000)−0.54 (−1.44, 0.36)1, 451.5390.221
Floral display0.52 (0.31, 0.72)1, 10232.80< 0.001
Local flower density5.30 (4.55, 6.06)1, 101199.0< 0.001
Isolation distance−0.37 (−0.52, −0.22)1, 4536.34< 0.001
Other flowering nectariferous plants−0.09 (−0.30, 0.12)1, 450.7150.402
Pollination treatment (effect of hand pollination compared with open pollination)20.8 (18.5, 23.0)1, 101324.8< 0.001
Floral display × pollination treatment−0.31 (−0.47, −0.16)1, 10115.45< 0.001
Local flower density × pollination treatment−3.35 (−4.08, −2.62)1, 10181.13< 0.001
Isolation distance × pollination treatment0.29 (0.16, 0.42)1, 10121.26< 0.001
Floral display × local flower density−0.11 (−0.17, −0.05)1, 10111.88< 0.001

On average, flowers produced more seeds when they were at high density, immediately surrounded by many other flowers (floral display), or located in a patch close to another patch (Table 2; Fig. 2). The effect of isolation distance on seed number per fruit remained significant even when we removed the few points at the most extreme distance categories (values equal to or above 18 m; Fig. 3).


Figure 2. Effects of local density of Aconitum napellus ssp. lusitanicum on reproductive success (number of seeds per flower) for open pollinations (open circles) and for within-patch hand-supplemented pollinations (closed circles). The area of the circles is proportional to the number of identical data points. Cubic smoothing splines are fitted to the data (open pollinations, dashed line; hand-supplemented pollinations, solid line).

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Figure 3. Effects of isolation distance (distance in meters between the two nearest flowering patches) of Aconitum napellus ssp. lusitanicum on reproductive success for open-pollinations (open circles) and within-patch hand-supplemented pollinations (closed circles). The area of the circles is proportional to the number of identical data points. Cubic smoothing splines are fitted to the data (open pollinations, dashed line; hand-supplemented pollinations, solid line).

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On average, within-patch hand-pollination (Wp) increased seed production by 188%: open-pollinated flowers produced 11.5 ± 0.38 (mean ± SE) seeds whereas hand-pollinated flowers produced 21.5 ± 0.33 seeds. Among open-pollinated flowers, floral display had a significant positive effect on seed set (F1,142 = 21.20, P < 0.001), but among within-patch hand-supplemented flowers (Wp), no effect was detected (F1,21 = 1.283, P = 0.270). In both treatments, seed set increased with local density, but slopes differed (Fig. 2). The positive effect of local density was much stronger for open-pollinated flowers than for within-patch hand-supplemented flowers (b = 5.25, F1,142 = 150.9, P < 0.001 in open-pollinated flowers and b = 1.04, F1,21 = 9.89, P = 0.005 in hand-supplemented flowers; Table 2). The difference between the two types of pollination (open pollination and within-patch supplementation) decreased as local density increased. We also found that the type of pollination influenced the effect of isolation distance on the production of seeds (Table 2, Fig. 3). Among within-patch hand-supplemented flowers (Wp), isolation distance had no effect on seed production (F1,35 = 0.010, P = 0.919), while among open-pollinated flowers, seed production per flower was negatively correlated with the distance to the nearest flowering patch (F1,45 = 33.14, P < 0.001). Almost no seeds were produced by open-pollinated flowers in highly isolated patches (> 18 m; Fig. 3). We also detected a significant interaction between floral display and local density (Table 2): the positive effect of floral display on the production of seeds was stronger at low density than at high density.

Effect of pollen source  No fruits were produced on bagged spikes that were not hand-pollinated. Thus, there was no spontaneous self-fertilization. Within the bags, the 10 geitonogamous (G) pollinations produced significantly (F1,12 = 13.38, P = 0.003) fewer seeds per flower (15.9 ± 0.85 (mean ± SE)) than the outcrossed (WpC) flowers (20.7 ± 1.00 (mean ± SE)), a reduction of c. 20%. Among the unbagged hand-pollinated flowers, we detected significant differences in seed production per flower among outcrossed pollination treatments (F2,81 = 227.6, P < 0.001, Fig. 4); the greater the distance between mates, the higher the seed production.


Figure 4. Effect of the type of pollen treatment on the reproductive success of Aconitum napellus ssp. lusitanicum: geitonogamy (n = 10) and within-patch pollinations (n = 10) for emasculated flowers; within-patch (n = 64), among-patch (n = 63) and between-population pollen supplementations (n = 24) for intact flowers. The line inside the boxes represents the median value (50th percentile). The box surrounding the median shows the 25th (lower) and 75th (higher) percentiles. The lines extending from the boundaries of the box (whiskers) denote the range of values < 1.5 interquartile ranges (IQRs) from the boundary of the box. Any points between 1.5 and 3 IQRs from the box boundary are considered outliers. The widths of the boxes are proportional to the square-roots of the number of observations in the groups. Pair-wise comparisons showed that all the groups were significantly different (P < 0.005, groups A–D), except for the two types of within-patch treatments (P = 0.76, group B).

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Seed quality

The effect of fruit (a random factor) was significant (inline image, P < 0.001), with 20% of the model variance attributable to differences among fruits. Local flower density had a significant and negative effect on seed mass (F1,41 = 5.969, P = 0.019). Seeds produced in patches with few flowers were on average heavier than those produced in high-density patches (4.32 ± 0.12 mg versus 3.89 ± 0.12 mg). Germination rate was not influenced by the population in which the seeds were produced (| z | = 0.54, P = 0.99) but was positively influenced both by seed mass and by local flower density: an increase of 10% in mean seed mass increased the germination rate by 174 ± 7.3% (robust SE) (| z | = 7.59, P < 0.0001) and at high flower density the germination rate was 353 ± 24% (robust SE) higher than at low flower density (| z | = 5.20, P < 0.0001; Fig. 5). Hence, independently of seed mass, flower density had a positive effect on germination. Finally, seedling survival did not depend on seed mass (t45 = −1.176, P = 0.24) but was significantly higher for seeds produced in high-density patches compared with those produced in low-density patches (survival 92%, 95% confidence interval (CI)  80, 97 for high density compared with survival 32%, 95% CI 15, 56 for low density; t13 = −3.87, P = 0.0019).


Figure 5. Proportion of ungerminated seeds of Aconitum napellus ssp. lusitanicum sown in the experimental garden as a function of time and local density (solid line, high density; dashed line, low density).

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

Allee effects within A. napellus populations

Our results confirm our hypothesis that the spatial distribution of both plants and flowers within natural populations (number, density, and isolation) influences reproductive components of A. napellus ssp. lusitanicum.

We found that floral display influenced an individual's reproductive success. As expected, inflorescences with many flowers produced more seeds per flower, and this effect of floral display size was stronger at low density. This suggests that heavily flowered individuals received more viable pollen per flower than sparsely flowered individuals, presumably because of the greater attractiveness of the former. Thus, reproductive success was at least partially determined at the plant level.

We also found that reproductive success was affected by larger scale patterns of floral distribution (local density and isolation distance). Seed production of A. napellus in open-pollinated flowers was positively correlated with local flower density and negatively correlated with isolation distance. Furthermore, the number of seeds produced by open-pollinated flowers was always lower than the number of seeds produced by hand-supplemented flowers. This set of results suggests that A. napellus suffers from within-patch Allee effects as a result of pollen limitation in low-density or isolated patches.

We also examined seed quality, germination rate and juvenile survival. The seeds produced in low-density patches were on average heavier than those produced in high-density ones. This could result from a resource allocation trade-off between seed mass and seed number (De Jong & van Noordwijk, 1992). Seed mass and local density influenced germination rate. The lower number of (heavier) seeds produced in low-density patches was not counterbalanced by a higher germination rate (Oostermeijer et al., 1994; Kéry et al., 2000; Kolb, 2005 but see Menges, 1991; Fischer et al., 2003). In fact, both germination rate and offspring survival were lower for seeds produced in low-density patches. Similar results have also been found in small populations of other plant species (Oostermeijer et al., 1994; Fischer & Matthies, 1998; Fischer et al., 2003; Kolb, 2005).

Four processes could lead to this reduction in fitness at low local densities or in isolated patches. First, local densities could reflect differences in environmental quality (the availability of water, soil nutrients or light). For example, if patches were variable in quality, we would expect to find a positive correlation between adult plant density and mean individual vigor. Secondly, pollinators of A. napellus may exhibit less constancy when other nectar-producing flowers are available; that is, the frequency of allospecific pollen transfer may increase, clogging A. napellus stigmas with pollen that does not germinate or that cannot fertilize its ovules. Alternatively, other flowering species could act as magnets and promote visitation of A. napellus. These phenomena should affect seed production but not the germination rates of the seeds produced. Thirdly, in patches where floral density is low, the frequency of self-fertilization or pollination between closely related genotypes may increase, thereby reducing seed production as a consequence of partial self-incompatibility or inbreeding depression, or seed quality as a consequence of inbreeding depression. Finally, pollinators may be less attracted to flowers when they occur at low density, such that seed production becomes highly pollen-limited.

We found no evidence suggesting that variation in patch quality – the first hypothesis – is the cause of the observed variation in reproductive success; that is, we found no relationship among the total number of flowers per inflorescence (open flowers and buds), the number of axillary stems per plant, stem height, and the number of open flowers per patch. If low-density patches were resource-limited, they should produce fewer seeds, smaller seeds, and/or seeds with lower germination rates. Contrary to this prediction, in our study, seeds were heavier in low-density patches. These results are consistent with those reported by Lamont et al. (1993), Widén (1993), Fischer & Matthies (1998) and Costin et al. (2001).

Similarly, the number of individuals of other flowering nectariferous plants – the second hypothesis – did not negatively affect seed production in A. napellus (cf. Caruso, 1999, 2001; but see Waser 1978; Campbell & Motten 1985; Galen & Gregory 1989; Jennersten & Kwak 1991; positive effects have been reported by Thomson, 1981; Moeller, 2005). We detected no significant effect within patches of the number of plants of other rewarding species on seed production per flower. This is in accordance with our field observations (unpublished results); bumblebees visiting A. napellus flowers are mostly specialists and avoid the flowers of other species. A. napellus pollen transported by pollinators is probably not significantly diluted with pollen from other plant species.

The third hypothesis for the observed reduction in seed production per flower at low floral density – an increase in selfing rate and/or in consanguineous matings – is likely to apply here: an example of a genetic Allee effect. In our experiment, the reduction of 20% in seed production between geitonogamous and outcrossed hand-pollinations suggests three possible mechanisms: a failure of self pollen to germinate or to grow effectively, early-acting inbreeding depression or late-acting maternal selection occurring between pollination and seed maturation. Moreover, the greater the distance between pollen donor and recipient, the higher the seed production per flower, indicating that pollinations between proximate and probably related plants resulted in a higher number of unviable offspring than crosses between more distant plants. At low density, plants have fewer available mates, which may result in higher rates of selfing and crosses with related individuals. This is consistent with a pattern in which pollinators are more likely to transfer pollen between closely related plants in low-density patches than in high-density patches. Indeed, when plants are scarce, pollinators tend to maximize their foraging efficiency by visiting more flowers per plant, thus increasing geitonogamous (within-plant) pollen transfer (Heinrich, 1979; De Jong et al., 1993; Klinkhamer & De Jong, 1993; Ferdy & Smithson, 2002; Ohashi & Yahara, 2002; Oddou-Muratorio et al., 2006). Relative to outcrossing, such geitonogamous selfing results in reduced offspring fitness (germination rate and juvenile survival) because of inbreeding depression.

Low seed production and poor offspring quality in low-density patches could result from inbreeding depression (biparental inbreeding) and/or maternal control over fertilization and provisioning (Stephenson & Winsor, 1986; Shaw & Waser, 1994; Charlesworth & Charlesworth, 1999; Kenta et al., 2002). Such results of maternal control have been found in Delphinium, a genus close to Aconitum (Waser et al., 1987; Waser & Price, 1991, 1993). Based on the present results, we are not able to disentangle the effects of deleterious recessives in self-pollinated flowers from the preferential allocation of maternal resources to cross-pollinated flowers. Regardless of the mechanism, however, genetic Allee effects may reduce fitness components in plants growing in low-density patches (Fischer et al., 2003; Kolb, 2005; Willi et al., 2005). Differences in pollen quality could also explain the significant positive relationship observed between seed production among within-patch hand-pollinated flowers and floral density. However, this mechanism is not sufficient to explain the magnitude of the difference between hand-supplemented pollinations and open-pollinations. Thus, plants in low-density patches appear to suffer from a decline in both the quality and the quantity of the deposited pollen.

Finally, the fourth hypothesis – that A. napellus is more pollen-limited at low density than at high density – may also contribute to the observed variation among patches in seed production. When patches of flowering spikes are quite small, pollinators are unlikely to encounter them by chance or are not sufficiently attracted to spend the energy necessary to visit them (e.g. Schulke & Waser, 2001; Kirchner et al., 2005; Cheptou & Avendaño, 2006). At very low density, some flowers produced no seed. If pollinators are less attracted by small patches, they are also less attracted by isolated patches. Indeed, we found that seed production decreased as the distance between two adjacent flowering patches increased. More precisely, the number of seeds per fruit increased with distance when patches were less than 8 meters apart, and decreased with distance for distances between 8 and 18 m. In patches isolated from others by > 18 m, seed production was very low. This suggests that reproduction in small and isolated patches of A. napellus ssp. lusitanicum is limited by the amount of pollen deposited, which constitutes an ecological Allee effect.

The third and fourth hypotheses are supported by studies performed on pollinator behaviour that showed that low-density patches received few visits but bumblebees visited more flowers per inflorescence, and inflorescences in isolated patches at very low density were not visited at all (Le Cadre, 2005).

By comparing the results of open and hand-supplemented pollinations, we can estimate the relative contributions of genetic and ecological Allee effects to the reduction of fitness components in A. napellus patches. To measure the ecological Allee effects more precisely, it would be necessary to measure pollen deposition among the stigmas of flowers in patches representing different densities and degrees of isolation.

In summary, our study highlights the importance of considering variables measured at different scales to determine factors controlling the reproductive success of a given species. It also reveals that comparisons of fitness components at the population level may be unable to detect component Allee effects such as density-dependent pollen limitation. In our study, we did not detect any significant effect of population identity on reproduction and fitness. These results underscore the value of examining directly those attributes of population structure that significantly contribute to plant reproductive success.

Effect on population viability and implications for conservation

In this study, we detected component Allee effects as defined by Stephens et al. (1999). In fact, seed production per flower (a component of individual fitness) of A. napellus is reduced at low density as a result of reductions in both pollen quantity and quality. The extent to which this impact results in a decline in population growth rate – a demographic Allee effect – depends on the life history of the species. Unfortunately, in the case of A. napellus, we have no data to support a demographic Allee effect because the populations have not been monitored for long enough (2 yr only) and because individual-based demographic censusing is not possible in this species (because of vegetative reproduction, individuals are not discernable).

Nevertheless, we deduce that seed production in A. napellus depends strongly on insect pollination and that the distribution and size of plant patches may be critical to the success of any restoration plan. Indeed, for all species, there may be a density threshold below which the extinction risk is high (Dennis, 1989; Kunin & Iwasa, 1996). However, few empirical studies have been conducted to detect the parameters of this extinction threshold. For example, Groom (1998) established a threshold number of individuals and a threshold distance between patches of Clarkia concinna (respectively, 50 individuals and 16 m of isolation). In the case of A. napellus populations, patches with < 12 flowers or isolated by > 18 m face uncertain reproductive futures. To manage populations, we could either reinforce existing patches or create relay patches (Kwak & Vervoort, 2000). Further studies of the potential effects of pollinator composition and behavior, and their spatial and temporal variation, on plant reproductive success should be investigated (Kwak et al., 1991). We propose that the construction and monitoring of experimental populations would be a useful tool for determining the existence of extinction thresholds and the population parameters (i.e. the distribution, abundance, and size of subpopulations) at which they occur. Such an approach could contribute to the identification of a long-term population management plan (Bosch & Waser, 2001; Schulke & Waser, 2001).


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

The authors thank C. Griveau and C. Heim for their help during experimentation in the field, and M. Evans, E. Porcher, N. M. Waser, C. Essenberg and two anonymous referees for helpful comments on a previous version of this manuscript.


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  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
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