# Intraspecific trade-offs between facilitation and competition in the non-native mollusc Crepidula fornicata

Xavier de Montaudouin, Chiara Accolla

► To cite this version:

Xavier de Montaudouin, Chiara Accolla. Intraspecific trade-offs between facilitation and competition in the non-native mollusc Crepidula fornicata. Marine Ecology Progress Series, 2018, 604, pp.163-171. 10.3354/meps12726. hal-04216685

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Intraspecific trade-offs between facilitation and competition in the non-native mollusc

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*Crepidula fornicata*

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Xavier de Montaudouin,<sup>1*</sup> Chiara Accolla<sup>2</sup>

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Running page head: Facilitation in invasive gastropods

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¹University of Bordeaux-CNRS, UMR EPOC 5805, Station Marine d'Arcachon, 33120

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Arcachon, France

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²Department of Ecology, Evolution and Behavior, University of Minnesota, MN 55108, USA

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Corresponding author*: xavier.de-montaudouin@u-bordeaux.fr

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KEY WORDS: *Crepidula fornicata*. Facilitation. Competition. P/B ratio. Non-indigenous species. Population dynamics

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*Corresponding author*: Xavier de Montaudouin : University of Bordeaux-CNRS, UMR EPOC 5805, Station Marine d'Arcachon, 2 rue du Pr Jolyet, 33120 Arcachon, France

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Tel: 33 5 56 22 39 04; Fax: 33 5 56 83 86 51

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ABSTRACT

We tested the hypothesis that high density populations of the non-indigenous gastropod *Crepidula fornicata* increase settlement of conspecific recruits (facilitation process), and that this facilitation is balanced by competition processes. To verify our hypothesis, we sampled *Crepidula* at two drastically different densities for 10 years. We found that at high densities, the number of one-year old individuals per m² colonizing the habitat and individual growth performances were higher in comparison with the low density condition (Allee effect). On the contrary, the production/biomass ratio (P/B), a good indicator of population fitness, was lower at higher densities. We relate this lower P/B ratio to the deficit of young individuals compared to adult biomass. We conclude that the net effect of high density on the conspecific colonisation processes of the population is positive, thanks to the higher available hard substrate for larvae (facilitation). However, intraspecific competition also occurs and mitigates this positive effect. Therefore, we suggest that it is particularly important to take into account the “net” balance between costs and benefits (i.e. what we observe) when analyzing population growth, in order to better understand its dynamics.

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40 INTRODUCTION

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42 Population demography within communities is thought to be strongly shaped by physical
43 disturbances and negative interactions like competition, predation and parasitism (Hixon et al.

44 2002). However, other studies have highlighted the importance of positive interactions in
45 population and community dynamics (Bruno et al. 2003). In particular, one of these
46 interactions is facilitation, generally defined as all non-consumer interactions among two or
47 more species (named ‘foundation species’) that positively affect at least one of the species
48 involved (Bertness & Callaway 1994), often with major cascade effects on recipient
49 ecosystems (Gribben et al. 2009, Gouhier et al. 2011, Yakovis & Artemieva 2017). Therefore,
50 facilitation occurs when one organism makes the local environment more favourable for
51 another species. This process is mostly described for sessile organisms, which cannot actively
52 escape stress (by locomotion) and consequently profit from the presence of other foundation
53 species mitigating adverse conditions (Bruno & Kennedy 2000, Wonham et al. 2005, Bulleri
54 2009, Branch et al. 2010).

55 Facilitation may consist of providing a suitable substrate for other species, as is the case for
56 the gastropod *Batillaria attramentaris* in its introduced range in Washington, USA. Its
57 proliferation, in fact, increases hard substrate surface (shells) for other species, including
58 *Crepidula convexa* (Wonham et al. 2005). In many other cases, facilitation consists of
59 mitigating physical stress, like reducing wave related physical disturbance either in close
60 vicinity of the foundation species or at a larger scale. Cordgrass (*Spartina alterniflora*), for
61 example, modifies cobble beaches nearby by reducing flow speed, stabilizing the sediments
62 and allowing seedlings of other plants to establish (Bruno & Kennedy 2000). *Mytilus edulis*
63 beds, instead, break the wave energy and facilitate cockle, *Cerastoderma edule*, settlement
50-100 m towards the coast (Donadi et al. 2013). Even though facilitation is often defined as a positive interaction among two or more species (Bertness & Callaway 1994), this biotic factor can also act within a single population, in the same way negative interactions such as competition or predation do (i.e. intraspecific competition or cannibalism, respectively). In this regard, Allee effects describe situations where density of conspecifics is positively correlated with population fitness (Courchamp et al. 1999, Stephens & Sutherland 1999), in contradiction with Verhulst's logistic equation, which states mathematically that population size has a negative effect on its own per capita growth rate (Hixon et al. 2002). Besides, Allee effect is often considered as a major mechanism facilitating non-indigenous species expansion, at least when those have already overpass the first settlement and dispersal stages (Simberloff & Von Holle 1999, Wonham et al. 2005) or other types of invasions (Shaw et al. 2018). One important output concerns the 'left part' of the theoretical curve of Allee effects, which supports the principle that low conspecific density may lead to population extinction or decreased fitness by genetic inbreeding and loss of heterozygosity or demographic stochasticity (Courchamp et al. 1999). However, few studies focus on the "central part" of the curve that shows the positive effect on population growth at high conspecific densities (i.e. inverse density dependence), beyond the threshold where negative effects would be expected.
Authors who assessed Allee effects generally concentrate on life history traits of populations like density/mortality rate (Leslie 2005, Svanfeldt et al. 2017), growth (Tsai et al. 2010) or reproductive output (Leslie 2005). In the present work, based on a 10-yr monitoring of a marine benthic population, we propose to estimate a more comprehensive parameter describing population fitness. — the Production/Biomass (P/B) ratio — in conditions of low and high conspecific densities. The P/B ratio is considered a good indicator of energetic flow in an ecosystem (Brey 1990). It typically estimates the percentage of annually renewed biomass, and consequently integrates recruitment success, individual growth and mortality
rate. Brey (1990) reviewed different correlations (or dependences) between P/B ratios and biological features of macrozoobenthic populations, such as age at sexual maturity, lifespan and number of generations. Moreover, the P/B ratio is an indicator of population health. For example, the P/B ratio of a population of cockles, *Cerastoderma edule*, was 27% decreased by the presence of parasites (Gam et al. 2009). Our study also aimed to highlight the need of clarifying the definitions of competition and facilitation. In fact, one definition of facilitation states that facilitative or positive interactions are encountered between organisms when at least one of the participants benefits without "causing harm to neither" (Bruno et al. 2003). This definition seems antagonistic with the one stating that facilitation appears when the "benefits exceed the costs" (Stachowicz 2001).

Our biological model is the slipper limpet, *Crepidula fornicata*, a gastropod which was accidentally introduced in Europe in 1872 from the East coast of the United States (Blanchard 1997), and is introduced to many coastal areas (Stiger-Pouvreau & Thouzeau 2015). *C. fornicata* appeared in France in the 1940s (Blanchard 1995) and was first recorded in 1969 in Arcachon Bay (Bachelet et al. 1980). These organisms form stacks where up to 12 individuals are piled up (Coum 1979). They are protandric hermaphrodites and exhibit planktotrophic development. Larvae need to reach a specific size in order to attain metamorphic competence. Then, they settle on hard substratum, e.g. conspecific live or dead shells (Henry & Lyons 2016). Paradoxically, although its planktonic larvae necessitate a hard substrate to settle, *C. fornicata* is particularly prolific in soft-substrate habitats. Thus, our hypothesis is that we could observe facilitative processes related to the increase of hard substrates (represented by *C. fornicata*'s shells) with increasing *C. fornicata* density in a soft-sediment environment. Conversely, a high density of conspecifics would beget competition leading to limited growth, higher mortality, and less successful recruitment. Our objective is to assess the net effect of density on population fitness through the P/B ratio and the settlement of one-year individuals.
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## 116 METHODS

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## 119 Study location and sampling

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122 All samples were collected from an intertidal mudflat of Arcachon Bay, France (44°39′18.00″N - 1°08′24.62″W). *Crepidula fornicata* are aggregately distributed within a narrow band of 450 × 15 m² along the lowest intertidal levels which can be reached by foot at ebb-tide, when tidal coefficient > 100. Salinity and water temperature seasonally fluctuate in the range 22–32, and 1–25°C, respectively. In this area, patches with high density of *C. fornicata* (ca. 8-m-diameters) are separated by areas where it is rare. Once a year from 2001 to 2010, during the same period (February-March), eight quadrats were sampled and washed on a 5-mm mesh sieve. The size of the quadrats was selected according to *C. fornicata* density: four 0.04-m² quadrats were situated in the middle of a patch (“HIGH” density), while four 0.25-m² quadrats were sampled at least 20 m from the closest high density patch, where *C. fornicata* are rare (“LOW” density). In order to obtain a clear quantitative difference between “LOW” and “HIGH” treatments, we defined “LOW” those samples characterized by less than 2 kg Fresh Weight (FW) of live *C. fornicata*.m⁻² and “HIGH” those having more than 7 kg FW.m⁻². The accuracy of our GPS did not allow to detect whether high density patches were at the exact same location each year, but the whole sampling area (see above) was always within the same mudflat. This period of sampling is just before *C. fornicata*
begins seasonal reproduction (de Montaudouin et al. 2002, Richard et al. 2006, Bohn et al. 2012) and was selected to ensure that our youngest individuals were ca. 1-yr old.

## Cohort determination

Every *C. fornicata* (n = 10,071) was measured with a calliper (1-mm precision) at the lower

edge (straight shell length) and the position in the stack was noted. Former studies have noted

the peculiar fact that *C. fornicata* forms stacks with an average of one individual per year

settling (Coum 1979). Thus the position of an individual in a stack could provide its age

(Deslous-Paoli 1985). An isolated individual (i.e. an individual that is not settled on the top of

another) is considered as a stack of one specimen. However, a recent study, performed in the

same area as this one, showed that more than one individual per year could settle in a single

stack and proposed a model to transform a stack/position matrix into a stack/age matrix (de

Montaudouin & Accolla 2017). The R 3.3.1 script of this model (Team 2014) is available in

de Montaudouin & Accolla (2017). Consequently, we used this model to identify the different

cohorts and calculate population dynamics parameters per year (10 years from 2001 to 2010)

and per *C. fornicata* abundance (LOW and HIGH).

## Population dynamics

Density, Mortality
We calculated the mortality rate of every C. fornicata cohort (Z, yr⁻¹) for each year Y (2001 to 2010) and for each of the density conditions (LOW and HIGH C. fornicata density) by comparing the density N at age t with density N at age t-1. The theoretical density of recruits N₀ (ind m⁻²) was deduced from the exponential mortality model:

$$N_t = N_0 e^{-Zt} \quad (1)$$

where N_t is the number of individuals of a cohort at age t (yr).

Then, we calculated the percentage of 1-year individuals as the ratio of the number of 1-year individuals over the total number of individuals, × 100. This value is a proxy of the success of recruitment related to the density of adults, ca. one year after settlement.

Individual growth

Von Bertalanffy growth function (VBGF) predicts length as a function of age and is commonly used in gastropod growth analysis with or without seasonal correction (Richardson et al. 2005, Chatzinikolaou & Richardson 2008), including examples for C. fornicata (Coum 1979, Deslous-Paoli 1985, de Montaudouin et al. 2001, de Montaudouin & Accolla 2017). Its formulation is:

$$L_t = L_\infty(1 - e^{-K(t)}) \quad (2)$$

where L_∞ is the asymptotic shell length (mm) and K the growth coefficient (yr⁻¹).

For each year Y (2001 to 2010) and each of the density conditions (LOW and HIGH C. fornicata density), we measured growth increment by comparing straight shell length at age t and straight shell length at age t-1. The VBGF parameters, L_∞ and K, were assessed using FISAT II software (version 1.2.2, FAO-ICLARM).

A growth performance index φ' was also calculated using K and L_∞ (Pauly & Munro 1984), as:
188 $\phi'=2\log(L_{\infty}) + \log K$ (3)

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190 Biomass, Production, P/B

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192 Biomass was calculated from individual shell length with the following equation based on 45

193 specimens ($r^2 = 0.92$) (de Montaudouin & Sauriau 1999):

194 $\log DW = 2.15 \log L - 4.17$ (4)

195 where DW is shell-free dry weight (g) and L the straight shell length (mm). Dry weight was

196 obtained after dissecting the flesh and drying it at 60°C for 48 h.

197 Total annual production P was calculated for C. fornicata according to incremental

198 summation method for populations with non-continuous recruitment and distinguishable year-

199 classes (Crisp 1984):

200 $P = \sum_{t=0}^{t=n} [(N_t + N_{t+1})/2 \times (W_{t+1} - W_t)]$ (5)

201 where $N_t$ is C. fornicata abundance at age t (yr) and $W_t$ is individual dry weight at age t (g).

202 $P/B$ (yr⁻¹) was calculated, dividing production P by mean biomass B, where B is defined as the

203 average C. fornicata biomass at year Y.

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205 Statistical analysis

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207 All parameters (density N, mortality Z, % of 1-year individuals, asymptotic shell length $L_{\infty}$,

208 growth coefficient K, growth performance index $\phi'$, biomass B, production P, P/B ratio) were

209 compared according to C. fornicata sampling conditions (LOW vs. HIGH), using the non-

210 parametric Wilcoxon paired test, with years as paired replicates (n = 10 years). Wilcoxon

211 paired test was chosen because we sampled the same population of C. fornicata each year,

212 with LOW density patches being geographically close to HIGH density patches.
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## RESULTS

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## DISCUSSION

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Length-frequency histograms were obtained for each of the ten investigated years, discriminating high *Crepidula fornicata* density patches from low *C. fornicata* density areas (Fig. 1). Mean density was 4.5 times higher in the HIGH density condition than in the LOW density condition (W = 2.80, p = 0.005) (Table 1). The relative density of 1-year individuals was 2.6 lower in the HIGH density condition than in the LOW density condition (W = 2.80, p = 0.005) (Fig. 1 & 2, Table 1). However, the density of 1-year individuals is 2.5 higher in the HIGH density condition than in the LOW density condition (Table 1). Mortality rate Z was similar for both conditions (W = 0.10, p = 0.919). Asymptotic length $L_\infty$ was similar in both conditions (W = 1.38, p = 0.169), but growth coefficient K was 15% higher in the HIGH density condition (W = 2.80, p = 0.005) (Fig. 3). As a consequence, the growth performance index $\Phi'$ was 1.4% higher in the HIGH density condition (W = 2019, p = 0.028) (Table 1).

Mean biomass and production were 5.4 and 4.2 times higher in the HIGH density condition than in LOW density condition respectively (W = 2.80, p = 0.005) (Table 1). Conversely, P/B ratio was 23% lower in the HIGH density condition than in the LOW density condition (W = 2.50, p = 0.013) (Fig. 4, Table 1).
values that are currently found in areas with longer histories of *C. fornicata* invasion (Hily
1991, de Montaudouin & Sauriau 1999, de Montaudouin et al. 2001, Guérin 2004, de
Montaudouin & Accolla 2017), while the LOW density condition rather described a process
of colonization (de Montaudouin et al. 2001). Likewise, all parameter values (*L*<sub>∞</sub>, *K*, *φ*', *P* and
*B*) but the P/B ratio are within the range of what is already assessed for this species. The P/B
ratio, instead, displayed particularly low values in both HIGH and LOW density conditions.
Indeed, we obtained values between 0.21 and 0.45 yr<sup>-1</sup>, while the expected P/B values for
invertebrates are usually not smaller than 1.00 yr<sup>-1</sup>: P/B = 1.77 yr<sup>-1</sup> for molluscs, P/B = 1.82
yr<sup>-1</sup> for filter feeders and P/B = 1.00 for mollusc filter feeders (Cusson & Bourget 2005).
Moreover, computing models, which provide an estimation of the P/B ratio according to the
lifespan or to the maximum individual weight (Robertson 1979, Tumbiolo & Downing 1994),
gives for *C. fornicata* values between 1.18 and 1.28 yr<sup>-1</sup>. *C. fornicata* is usually not <0.50 yr<sup>-1</sup>
(de Montaudouin & Accolla 2017). This discrepancy could be attributed to the rather
uncommon position of the *C. fornicata* population: our samples were at the intertidal level,
while this species usually lives at the subtidal level (Loomis & VanNieuwenhuize 1985).
The comparison of population dynamics parameter values between LOW and HIGH density
conditions provided a new insight in the facilitation/competition processes of species with
particularly high performances, such as invasive molluscs. The well-established density-
dependent intraspecific competition concept is not fully valid in the present case. Firstly and
unexpectedly, growth performance was not affected by high density, but on the contrary was
slightly stimulated. This result contradicts many studies demonstrating that high suspension-
feeders density is usually related to stunted growth (Peterson & Black 1987, Peterson & Beal
1989, Jensen 1992, Kamermans et al. 1992). Moulin et al. (2007) observed a higher particle
resuspension (i.e. higher available food) during spring tides when fewer stacks of *C. fornicata*
were on the bottom. In our sheltered study site, instead, current speed is low and resuspension
of benthic diatoms, a large part of *C. fornicata* trophic regime (Riera et al. 2002), could rather be related to bioturbation activity due to the grazing activity of the younger stage (Chaparro et al. 1998) and to the lifting behaviour of the older individuals (Diederich et al. 2015). Thus, the higher the density, the higher the bioturbation and the microphytobenthic availability. *C. fornicata* growth can also be stimulated by the contact of conspecifics (Le Gall 1980), such that high density consequently promotes these processes. Finally, we were not able to measure competitive effects on shell growth, although there was certainly trophic competition at these high levels of biomass, as observed with another suspension-feeder, the cockle *Cerastoderma edule* (de Montaudouin & Bachelet 1996). In conclusion, facilitation was the dominating process influencing growth.

The density values of 1-year old individuals clearly illustrate the antagonistic effects of competition and facilitation. In the LOW density condition, 1-year old individuals were on average 38% of total population (i.e. 219 ind.m⁻² out of 575), which corresponded to a [1-yr old]/[>1-yr old] ratio of 0.61. If we extrapolate this ratio to the HIGH density condition, we should obtain an average density of 1-yr old individuals of 1347 ind.m⁻². This would be the pure consequence of a gross facilitation process: the higher the availability of suitable substrate (here conspecific shells density), the higher the larval recruitment. However, the observed density of 1-yr old individuals was only 375 ind.m⁻² in the HIGH density condition (14.5% of total density). This could be caused by intraspecific competition and by a consequent alteration of recruitment by suspension-feeding activity of previously settled conspecific adults, as observed for many other marine species (Woodin 1976, Bachelet et al. 1992, de Montaudouin & Bachelet 1996). Moreover, cannibalism in suspension-feeders has been commonly observed in the laboratory (Young & Chia 1987), and in particular for *C. fornicata* (Pechenik et al. 2004). This relative deficit of younger individuals in the HIGH
287 density condition explained why the P/B ratio was 23% lower than in the LOW density
288 condition.

289 In conclusion, this 10-yr study showed that a 5.4 fold increase of biomass facilitated
290 settlement of 1-year individuals (x 6.1), but this facilitation was modulated by strong
291 intraspecific competition (÷3.6). The net result was positive (x 1.7): facilitation (Allee effect)
292 prevails over competition in terms of colonisation success in high densities. This self-
293 sustained growth of a population, exacerbated by this peculiarity to live piled up in stacks, is
294 certainly a major reason explaining the success of *C. fornicata* in becoming invasive
295 (Blanchard 2009, Stiger-Pouvreau & Thouzeau 2015), but also the success of other sessile
296 species needing hard substrates to settle in environments dominated by soft bottoms
297 (Diederich 2005, Leslie 2005, Lang & Buschbaum 2010, Svanfeldt et al. 2017). Conversely,
298 we also demonstrated that, even though greater density of *C. fornicata* increases population
299 growth (Allee effect), the P/B ratio at high density is diminished, suggesting that a density
300 threshold beyond which fitness is altered has been exceeded in the HIGH density condition.
301 Our study provides evidence for the importance of examining “net” balance between costs
302 and benefits (i.e. what we observe) when analysing population growth. This means that we
303 should stress what is the net competition when costs are high, albeit gross facilitation is
304 present too, or what is the net facilitation when benefits are high in presence of gross
305 competition (Bruno et al. 2003, Leslie 2005).

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308 All applicable institutional and/or national guidelines for the care and use of animals were followed.

309

310 Acknowledgements
311 The authors are grateful to Pascal Lebleu for his significant help in the field experiment. Many thanks

312 to the three Referees who significantly helped in improving the manuscript.

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460

461 Fig. 1. Shell length frequency histogram of *Crepidula fornicata* from 2001 to 2010 at the LOW and
462 HIGH density conditions, and by age. Black bars concern the 1-yr individuals.

463 Fig. 2. Mean relative proportion of 1-yr ind.m⁻² (+ 1 standard error) of *Crepidula fornicata* at the LOW
464 and HIGH densities condition, from 2001 to 2010 (N = 4 replicates).

465 Fig. 3. Modelled growth curve of *Crepidula fornicata* with average Von Bertalanffy growth function
466 parameters (2001-2010) at the LOW and HIGH densities conditions (Table 1).

467 Fig. 4. Mean Production/Biomass ratio of *Crepidula fornicata* at the LOW and HIGH densities
468 condition, from 2001 to 2010.

469
<figure><img src="image_2.png" /><figcaption>Figure 1</figcaption></figure>
<figure><img src="image_3.png" /><figcaption>Figure 2</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>Figure 3</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Figure 4</figcaption></figure>
<table><caption>Table 1. Summary of results of Wilcoxon paired test examining the effect of *Crepidula fornicata* density (LOW and HIGH) on different parameters of their population dynamics.</caption><thead><tr><th></th><th>LOW</th><th>HIGH</th><th>W</th><th>P</th></tr></thead><tbody><tr><td>Density N (ind.m<sup>-2</sup>)</td><td>575 (403-712)</td><td>2583 (2084-2891)</td><td>2.80</td><td><strong>0.005</strong></td></tr><tr><td>Mortality rate Z (yr<sup>-1</sup>)</td><td>0.44 (0.40-0.47)</td><td>0.45 (0.38-0.49)</td><td>0.10</td><td>0.919</td></tr><tr><td>% 1-yr old</td><td>38.0 (30.0-47.0)</td><td>14.5 (9.0-28.0)</td><td>2.80</td><td><strong>0.005</strong></td></tr><tr><td>Asymptotic length L<sub>∞</sub> (mm)</td><td>39.0 (33.8-41.7)</td><td>37.9 (36.1-41.3)</td><td>1.38</td><td>0.169</td></tr><tr><td>Growth coefficient K (yr<sup>-1</sup>)</td><td>0.47 (0.42-0.54)</td><td>0.54 (0.49-0.59)</td><td>2.80</td><td><strong>0.005</strong></td></tr><tr><td>Growth performance index Φ'</td><td>2.85 (2.76-2.93)</td><td>2.89 (2.84-2.92)</td><td>2.19</td><td><strong>0.028</strong></td></tr><tr><td>Biomass B (gDW.m<sup>-2</sup>)</td><td>47 (39-53)</td><td>256 (243-304)</td><td>2.80</td><td><strong>0.005</strong></td></tr><tr><td>Production P (gDW.m<sup>-2</sup>.yr<sup>-1</sup>)</td><td>19 (13-20)</td><td>79 (64-89)</td><td>2.80</td><td><strong>0.005</strong></td></tr><tr><td>P/B (yr<sup>-1</sup>)</td><td>0.40 (0.34-0.45)</td><td>0.31 (0.21-0.34)</td><td>2.50</td><td><strong>0.013</strong></td></tr></tbody></table>