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The importance of population density and inter-individual distance in conserving the European oyster Ostrea edulis

Published online by Cambridge University Press:  14 June 2018

C. Guy
Affiliation:
School of Biological Sciences, Queen's University Belfast, Belfast BT9 7BL, Northern Ireland
D. Smyth*
Affiliation:
School of Natural and Built Environment, Queen's University Belfast, Belfast BT9 5AG, Northern Ireland
D. Roberts
Affiliation:
School of Biological Sciences, Queen's University Belfast, Belfast BT9 7BL, Northern Ireland
*
Correspondence should be addressed to: D. Smyth, School of Natural and Built Environment, Queen's University Belfast, Belfast BT9 5AG, Northern Ireland email: D.M.Smyth@qub.ac.uk
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Abstract

Fertilization success will determine the rate at which a population can expand and is especially important when considering small, establishing or enduring communities. Introduced species frequently fail to establish reproductively functional populations due to strong Allee effects associated with low densities. The native European oyster, Ostrea edulis broods its fertilized eggs in the pallial cavity for a period of 8–10 days before releasing the larvae. It is considered a partial broadcast spawner and was used as a model species to assess the importance of Allee effects such as inter-individual distance on reproductive success. Distances between individual oysters within test plots in areas of known oyster density were used in conjunction with standardized brood size (n larvae g−1 total wet weight) to assess fertilization success. A significant, positive relationship was observed between brood size and oyster density. Oysters with a nearest neighbour ≤1.5 m were found to brood significantly more larvae than individuals with nearest neighbours ≥1.5 m. Therefore, high density sites need to be maintained to ensure the recovery and enhancement of this OSPAR Convention recognized species in decline.

Type
Research Article
Copyright
Copyright © Marine Biological Association of the United Kingdom 2018 

INTRODUCTION

The procreative success of sexually reproducing species is determined by a number of factors. Two of the key influences are maternal size and population density (Beukema, Reference Beukema1982). The concept that small populations may suffer declines in relation to per capita growth as a result of their size or low densities was first suggested by Allee in 1931. This idea was further explored in his subsequent book on animal ecology in 1949 (Allee et al., Reference Allee, Emerson, Park, Park and Schmidht1949). The concept of the Allee effect has been a widely accepted theory adopted by researchers investigating species facing the threat of extinction as a consequence of low population densities and low fecundity (Stephens & Sutherland, Reference Stephens and Sutherland1999; Barnett, Reference Barnett2001). However, it is equally important when examining species which are recovering from population crashes or ones which have only recently become established (Arim et al., Reference Arim, Abades, Neill, Lima and Marquet2006). By its nature, an invading species is either on the very edge of its native range and colonizing new areas naturally or it has been translocated and is in a low density founding population (Hayes & Barry, Reference Hayes and Barry2008). The same scenario can be anthropogenically induced in species, whereby the wild population or its associated habitat is overexploited as a resource to such an extent that decreases in densities resemble those of an invading species (Smyth et al., Reference Smyth, Roberts and Browne2009; Campos-Silva et al., Reference Campos-Silva, Peres, Antunes, Valsecchi and Pezzuti2017; Sullivan et al., Reference Sullivan, Bird and Perry2017). Once species reach critical densities that make biological functionality a challenge conditions are ideal for the initiation of the Allee effect, which can have major impacts on subsequent population dynamics (Taylor & Hastings, Reference Taylor and Hastings2005). With regards to invasive species biology, the Allee effect can be considered beneficial as it slows population density increase through the introduction of a prolonged lag phase in population growth. This phenomenon affords researchers time to acquire information and initiate decisive management control measures. The Allee effect may even be severe enough in some cases to prevent population expansion beyond the initial cohort of introduced individuals (Tobin et al., Reference Tobin, Berec and Liebhold2011; Fauvergue et al., Reference Fauvergue, Vercken, Malausa and Hufbauer2012).

There are numerous influencing parameters which have been associated with the Allee effect but one of the major components is the availability of a mate, an important requirement in the perseverance of a fecund population (Wells et al., Reference Wells, Strauss, Rutter and Wells1998; Boukal & Berec, Reference Boukal and Berec2002; Kramer et al., Reference Kramer, Dennis, Liebhold and Drake2009).

Many broadcast spawning marine invertebrate species exhibit traits which serve to maximize fertilization success (Gosling, Reference Gosling2003). In sessile species chemically induced gregarious settlements are common (Tamburri et al., Reference Tamburri, Luckenbach, Breitburg and Bonniwell2008). In vagile species external environmental factors such as the lunar cycle (Rudloe, Reference Rudloe2008) or temperature (Mann, Reference Mann1979) are inclined to trigger a mass movement to ensure the close proximity of potential mates and synchronicity in spawning (Yund, Reference Yund2000). The distance between potential mates, the number of gametes produced and the longevity of gametes in the water column plus localized dilution factors can all have major implications for successful fertilization in broadcast spawners (Breen & Adkins, Reference Breen and Adkins1980; Shepherd, Reference Shepherd1986; Gascoigne & Lipcius, Reference Gascoigne and Lipcius2004). Population densities of sedentary sessile species can therefore be considered as fundamental determinants of fitness since individuals cannot move to find a mate (Cruz-Rivera & Hay, Reference Cruz-Rivera and Hay2000).

The European flat oyster Ostrea edulis is a sequentially alternating species, whereby individuals develop firstly as males and after spawning switch sex to produce eggs (Korringa, Reference Korringa1952). This alternation between sexes is thought to continue throughout the lifetime of the oyster (Orton, Reference Orton1922; Walne, Reference Walne1974). It may be possible that some overlap in the presence of spermatozoa and eggs exists, however there have been no documented reports of O. edulis functioning as both sexes simultaneously. Females are larviparous and extrude their eggs into their mantle space where they are retained until fertilized by conspecific sperm acquired from the water column (Orton, Reference Orton1937). Post-fertilization, the eggs are moved to the inhalant chamber where they develop for ~1 week (Orton, Reference Orton1937). After 3–4 days the larvae develop shells and cilia to facilitate swimming (Walne, Reference Walne1974). During this period larvae change from a translucent whitish colour to miniature, dark grey shelled veligers (Korringa, Reference Korringa1952). Within ~10 days the larvae are expelled from the maternal mantle cavity into the plankton where they undergo further development. Spawning takes place from June to mid-September and spat are visible from late summer onwards (Kennedy & Roberts, Reference Kennedy and Roberts1999). The fact that O. edulis females retain larvae in the mantle makes it possible to gauge fertilization success (Adams et al., Reference Adams, Smith, Roberts, Achim, King, Tervit and Webb2008; Lallias et al., Reference Lallias, Boudry and Lapègue2010) and it was this reproductive trait which enabled size–fecundity relationships in the European oyster to be established over 25 years ago (Korringa, Reference Korringa1952; Walne, Reference Walne1974).

The present study is the first to explore the effects of population density and spatial distribution on fertilization success in the European oyster, O. edulis in Strangford Lough, Northern Ireland. This study was undertaken in an attempt to model fertilization success in oysters with the ultimate aim of designing strategies to enhance local range and population size of the native O. edulis. It is envisaged that the findings will have a broader application in similar global scenarios.

MATERIALS AND METHODS

Study area

Strangford Lough is a designated UK Marine Nature Reserve located on the north-east coast of Ireland and lies between 54o35–54o20N and 5o41–5o34W enclosing an area of 150 km2(Figure 1). The average depth of the lough is ~30 m but depths range from 14–60 m, with substrate types varying from bedrock to fine sediments winnowed out by a gradient of tidal water movement (Erwin, Reference Erwin, Keegan, Ceidigh and Boaden1976). The lough can be divided into northern and southern basins. Tidal currents are weak in the north and strong (~3.5 m s−1) in the bottleneck entrance in the south (Kregting & Elsäer, Reference Kregting and Elsäer2014).

Fig. 1. Strangford Lough Northern Ireland and the three survey sites of Newtownards Sailing Club (NSC), Greyabbey and Kircubbin.

Density and inter-individual distance

The three survey sites, Newtownards Sailing Club (NSC), Greyabbey and Kircubbin (Figure 1), were selected as they represented high, medium and low density O. edulis populations, as acknowledged in Guy & Roberts (Reference Guy and Roberts2010) and Smyth et al. (Reference Smyth, Mahon, Roberts and Kregting2018). Sampling was undertaken during July and August in 2009 when O. edulis females were most likely to be brooding (Orton, Reference Orton1937; Korringa, Reference Korringa1952; Walne, Reference Walne1974). All sites were visited on spring tides with a predicted low water of <0.5 m below chart datum with sampling conducted during the 30 min before and after low water.

At each site, five 36 m2 plots were selected parallel to the low water mark. Within each 36 m2 plot, six 1 m2 quadrats were randomly positioned as described by Low (Reference Low2006). A thorough visual census within each quadrat was carried out and the location of all O. edulis recorded diagrammatically and in digital images. The first three O. edulis found within a quadrat were used for subsequent measurements. The three nearest conspecifics to each individual inside the quadrat were located and the inter-individual distances recorded using a Bosch Lazer Rule©. The length of each oyster was also noted alongside the inter-individual distance. Each oyster was assigned a unique reference code before being collected and stored in a correspondingly labelled container.

Patterns of dispersion

Inter-individual distances between O. edulis at the three survey sites were used to assess how spatial distribution patterns of the species varied depending on the overall mean oyster density of the site. Morisita's index of dispersion (I d) and the standardized Morisita index of dispersion were calculated for each of the three sites as per Krebs (Reference Krebs1989).

First, the Morisita index of dispersion (I d) was calculated by:

(1)$$I_{\rm d} = n\left[ {\displaystyle{{\Sigma {\rm \chi} ^2 - \Sigma {\rm \chi}} \over {\{ \Sigma {\rm \chi} ^2 \} - \Sigma {\rm \chi}}}} \right]$$

Where: I d = Morisita's index of dispersion; n = sample size; Σχ = sum of the quadrat counts; Σχ2 = sum of the quadrat counts squared.

Additions were made to this equation by Smith-Gill (Reference Smith-Gill1975) to implement an absolute scale from −1 to + 1 resulting in the Standardized Morisita index of dispersion (I p) (Krebs, Reference Krebs1989). I p is derived by calculating the uniform index (M u) (equation (2)) and the clumped index (M c) (equation (3)).

(2)$$M_{\rm u} = \displaystyle{{{\rm \chi} ^2 \times .97_5 - {\frak n} + \Sigma {\rm \chi} i} \over {\{ \Sigma {\rm \chi} i\} - 1}}$$

Where: χ2 × .975 = Value of the chi-square from table with n − 1 degrees of freedom with 97.5% of area to the right; χi = number of organisms in quadrat i.

(3)$$M_{\rm c} = \displaystyle{{{\rm \chi} ^2 \times 02_5 - {\frak n} + \Sigma {\rm \chi} i} \over {\{ \Sigma {\rm \chi} i\} - 1}} $$

Where: χ2 × 025 = Value of the chi-square from table with n − 1 degrees of freedom with 2.5% of area to the right.

The final calculation to ascertain the standardized Morisita index (Ip) was chosen dependent on the outcomes of equations (2) and (3).

When I d > M c ≥ 1.0:

(4)$$I_{\rm p} = 0.5 + 0.5\left( {\displaystyle{{I_{\rm d} - M_{\rm c}} \over {{\frak n} - M_{\rm c}}}} \right) $$

When M c > I d > 1.0:

(5)$$I_{\rm p} = 0.5\left( {\displaystyle{{I_d - 1} \over {M_c - 1}}} \right) $$

When 1.0 > I d > M u

(6)$$I_{\rm p} = - 0.5\left( {\displaystyle{{I_{\rm d} - 1} \over {M_{\rm u} - 1}}} \right)$$

When 1.0 > M u > I d

(7)$$ I_{\rm p} = - 0.5 + 0.5\left( {\displaystyle{{I_d - M_{\rm u}} \over {M_{\rm u}}}} \right) $$

I p ranges from −1.0 to + 1.0 with 96% confidence limits at + 0.5 and −0.5. Populations with an I p result of zero are classed as randomly distributed, a positive I p result suggests clumped distribution patterns and negative I p results suggest uniform distribution.

Brood density analysis

Presence and density of brooded larvae were used to assess the impact of oyster density and inter-individual distance on fertilization success in O. edulis. The collected oysters were brought back to the laboratory for immediate processing. The initial weight of the oyster was recorded prior to the removal of the left valve. The mantle cavity was then checked for evidence of larval brooding. Brooding individuals could be clearly distinguished as they had masses of white/grey/black particles in the gill area, visible to the naked eye. The mantle of all oysters was then carefully rinsed using a measured amount of filtered seawater to remove all larvae which were collected in a glass beaker for subsequent analysis (Utting et al., Reference Utting, Helm and Millican1991). Beakers containing washings from brooding oysters were gently agitated to ensure larvae were in an even suspension. An aliquot of liquid (5 ml) was then removed from the beaker and placed into a Bogorov tray. The Bogorov tray was divided into 17 equal portions, of which five were randomly selected for larval counts. Each portion contained 0.29 ml of liquid and therefore the total density of larvae being brooded could be back-calculated taking the dilution factors into account (Utting et al., Reference Utting, Helm and Millican1991). As brood size is positively related to the size of the brooding oyster (Walne, Reference Walne1974) brood-size data were standardized to n larvae g−1 total wet weight.

RESULTS

Density, inter-individual distance and patterns of dispersion

The distribution patterns of O. edulis were assessed at NSC, Greyabbey and Kircubbin which correspondingly displayed high, medium and low density populations (Table 1). The O. edulis population at NSC was found to have a standardized Morisita index of dispersion (I p) of −0.56 which denotes a uniform pattern of dispersion. Greyabbey was found to have a clumped O. edulis population distribution (I p = 0.149) and Kircubbin was found to have a randomly distributed population of O. edulis (I p = 0).

Table 1. Mean density, inter-individual distance (cm) and dispersion indices of O. edulis across the three sample sites.

Brood densities

To allow for variation in oyster size and weight, larval brooding was expressed as n g−1 total wet (flesh) weight. Number of brooded larvae showed a significant positive relationship with oyster density (ANOVA, F 1,28 = 4.445, P = 0.044) (Figure 1). The percentage of population found to be brooding larvae was considered positively orientated, but not significantly (ANOVA, F 2,164 = 0.078, NS), related to oyster density (Figure 2).

Fig. 2. Relationship between mean fecundity of larvae (n g1 wet tissue weight) and oyster density (pooled data – all sites).

As oyster densities and distribution patterns differed between sites (Table 1) the data were investigated further to assess if inter-site differences in distribution pattern were reflected in brood densities. The data were then subdivided into ≤1.5 m and >1.5 m to take into account the distance to the nearest neighbour.

Although differences were present in the distribution patterns and density of O. edulis at the three sites, there was no significant variation in the mean inter-individual distances between sites (ANOVA, F 2,164 = 0.030, NS). However, within each site, oysters which were ≤1.5 m from their nearest neighbour were brooding larvae in significantly higher densities than those which were >1.5 m from their nearest neighbour (ANOVA, F 1,37 = 6.730, P = 0.014) (Figure 3).

Fig. 3. Relationship between percentage of brooding oysters and oyster density (pooled data – all sites).

The three sites revealed a gradual weakening of the Allee effect and brood density (Figure 4) as oyster density per m2 decreased from the northerly high density site of NSC through to the low density site of Kircubbin (Table 1). It was also evident that a linkage existed between oyster settlement patterns indicated by the Morisita index and the strength of the Allee effect. As oyster settlements changed from grouped attachments at high density assemblages through to single settlements at low density the Allee effect strengthened.

Fig. 4. Mean brood density (n larvae g1 wet tissue weight) per n × 17 samples at three different sites where the nearest neighbour was ≤1.5 m (open) and >1.5 m (shaded). Error bars represent the standard deviation of the mean.

DISCUSSION

Fertilization success for broadcast spawning bivalves such as O. edulis increases with the age and size of individuals; as the oyster becomes larger it produces greater quantities of eggs and sperm (Walne, Reference Walne1974). A major influence in limiting fertilization success in O. edulis is gamete dilution: a parameter which is more pronounced in fragmented and low-density populations (Oliver & Babcock, Reference Oliver and Babcock1992; Farley & Levitan, Reference Farley and Levitan2001; Vitiello et al., Reference Vitiello, Carlino, Prete, Langellotti and Sansone2011). This scenario existed between the three survey sites examined during this research. Gamete dilution is also a factor in mobile broadcast spawning species such as polychaete worms. However, reduced fertilization success at low population densities of these mobile species can be partially or at least offset by behavioural adaptations such as the formation of synchronized spawning swarms (Coma & Lasker, Reference Coma and Lasker1997; Santu et al., Reference Santu, Nandan and Athira2016). Such strategies are not possible for sessile broadcast spawners. Monitoring fertilization success of broadcast spawners in the field would necessitate detailed plankton studies with a low likelihood of success. Ostrea edulis provides an ideal model for alternatives to this research approach as it is a partial broadcast spawner in which females retain eggs within the mantle cavity while they undergo post-fertilization development (Walne, Reference Walne1974).

This study examined the fertilization success of O. edulis over a range of low density sites which are representative of many of the wild standing stock levels in Europe at the present time (Bostock et al., Reference Bostock, Lane, Hough and Yamamoto2016; Smyth et al., Reference Smyth, Mahon, Roberts and Kregting2018). The research revealed that the O. edulis brooding larvae percentage was positively but not significantly related to density (Figure 3). The weak relationship between percentage brooding and density was not unexpected as brooding percentage simply demonstrates that females within the population have been fertilized and not the rate of fertilization. However, the density of brooded larvae (n larvae g−1 wet tissue weight) was significantly higher in oysters which were <1.5 m away from their nearest conspecific (Figure 4). Although no significant variation was observed between the inter-individual distances at the three sites there was variation in fertilization success between < and >1.5 m. Consequently the findings suggest that it is a combination of the overall numbers of individuals (Figure 2) and the inter-individual distances (Figure 4) which are governing the fertilization success rate.

The significance of inter-individual distance with regards to the reproductive success of O. edulis reiterates the importance of maintaining high density populations in a recovering oyster stock as a means of ensuring sustainability (Kennedy & Roberts, Reference Kennedy and Roberts1999). Safeguarding a high density stock of an economically important shellfish such as O. edulis is extremely difficult unless sites are closed and policed (Beck et al., Reference Beck, Brumbaugh, Airoldi, Carranza, Coen, Crawford, Defeo, Edgar, Hancock, Kay, Lenihan, Luckenback, Toropova, Zhang and Guo2011; Selkoe et al., Reference Selkoe, Blenckner, Caldwell, Crowder, Erickson, Essington, Estes, Fujita, Halpern, Hunsicker, Kappel, Kelly, Kittinger, Levin, Lynham, Mach, Martone, Mease, Salomon, Samhouri, Scarborough, Stier, White and Zedler2015). Smyth et al. (Reference Smyth, Roberts and Browne2009) highlighted the detrimental impact illegal harvesting could have on a recovering O. edulis population. Decreases of >500,000 were recorded within the commercially marketable 3–5 years cohort between 2004 and 2006 and as result wild stocks have never recovered to the pre-2004 densities (Smyth et al., Reference Smyth, Kregting and Roberts2016). These large-scale removals of larger, fecund individuals greatly reduce the number of gametes released and increases inter-individual distance which consequently reduces fertilization success. It was unregulated harvesting such as this that led to the collapse of the O. edulis fishery throughout Europe in the mid-1800s (Hiscock et al., Reference Hiscock, Bayley, Pade, Lacey, Cox and Enever2013; Thurstan et al., Reference Thurstan, Hawkins and Roberts2013). It is possible that population distributional changes in undisturbed recovering populations could shift randomly at low densities through to intermediate and high densities as a result of larval attraction to conspecifics and naturally occurring abiotic factors. However, the introduction of illegal harvesting into the scenario would reverse this hypothetical trend and natural density patterns would be compromised (Smyth et al., Reference Smyth, Kregting and Roberts2016).

The European oyster, Ostrea edulis, has been listed by the OSPAR Convention for the Protection of the Marine Environment of the North-East Atlantic as a threatened species in decline since 2003 and was included within the remit of the UK Biodiversity Plan (OSPAR Commission, 2009; UKBAP, 2009). These environmental advisory concords encourage the maintenance and expansion of existing O. edulis assemblages within their native European range (Hiscock et al., Reference Hiscock, Bayley, Pade, Lacey, Cox and Enever2013). If the signatories of these agreements are to meet their obligations the illegal harvesting of O. edulis should be prevented. As the continued removal of wild stocks increases inter-individual distances it will in turn reduce fertilization success and generate a strong Allee effect which could eventually drive populations below recruitment thresholds, resulting in extinction (Liebhold & Tobin, Reference Liebhold and Tobin2010).

Species such as O. edulis which are considered as brooding or partial broadcast spawners have a limited dispersal time, producing larvae which spend a relatively short period of time in a planktonic phase and therefore tend to be more aggregated around the parent population. Species which have a longer planktonic juvenile stage such as Crassostrea gigas are more likely to settle diffusely apart from the parent population due to the effect of broadcast spawning events, larval swimming time, settlement behaviour and ultimately adult distribution (Carlon & Olson, Reference Carlon and Olson1993). The Pacific oyster C. gigas has spread from its introduced aquaculture sites throughout Europe creating concern that its establishment within the low-mid intertidal zone could threaten the existence of indigenous species (Melo et al., Reference Melo, Silva, Gomes, Solé-Cava and Lazoski2010). In Strangford Lough C. gigas is beginning to settle among O. edulis on the lower intertidal and potential for settlements to have detrimental impacts on the small recovering assemblages of native oysters is worrying (Zwershke et al., Reference Zwershke, Emmerson, Roberts and O'Connor2016; Smyth et al., Reference Smyth, Mahon, Roberts and Kregting2018).

At present C. gigas can be considered in the lag phase of population growth in Strangford Lough and this offers concerned habitat managers a time lapse whereby they could accentuate any associated Allee effect. The implementation of anti-invasive control measures such as culling and sacrificial spat collector deployment during this period could hinder the development of large C. gigas assemblages like those currently reported from the Wadden Sea (Nehls et al., Reference Nehls, Diederich, Thieltges and Strasser2006). The findings of this research into the Allee effect have identified the appropriate action to take in Strangford Lough, first to sustain the tentative recovering O. edulis assemblages and second to possibly offer a means of coping with a future C. gigas infestation. If these are executed in conjunction with the comprehensive understanding of the hydrodynamic regime (Kregting & Elsäer, Reference Kregting and Elsäer2014) of the Lough, a maximum cull effect on C. gigas could be achieved while a high density O. edulis population is protected. This represents a blueprint which could be repeated on a global scale for similar invasive species which have formed feral populations.

ACKNOWLEDGEMENTS

We would like to thank the technical staff at QUB Marine Laboratory Portaferry and M. Norris and S. McBride for their fieldwork contribution and assistance with laboratory work.

FUNDING

This research was funded by the Department of Agriculture and Rural Development for Northern Ireland.

Footnotes

*

Died 11 October 2017.

References

REFERENCES

Adams, S.L., Smith, J.F., Roberts, R.D., Achim, R.J., King, N.G., Tervit, H.R. and Webb, S.C. (2008) Application of sperm cryopreservation in selective breeding of the Pacific oyster, Crassostrea gigas (Thunberg). Aquaculture Research 39, 14341442.10.1111/j.1365-2109.2008.02013.xGoogle Scholar
Allee, W.C., Emerson, A.E., Park, O., Park, T. and Schmidht, K.P. (1949) Principles of animal ecology. London: Saunders.Google Scholar
Arim, M., Abades, S.R., Neill, P.E., Lima, M. and Marquet, P.A. (2006) Spread dynamics of invasive species. Proceedings of the National Academy of Sciences USA 103, 374378.10.1073/pnas.0504272102Google Scholar
Barnett, A. (2001) Safety in numbers. New Scientist 169, 3841.Google Scholar
Beck, M., Brumbaugh, D.R., Airoldi, L., Carranza, A., Coen, L.D., Crawford, C., Defeo, O., Edgar, G.J., Hancock, B., Kay, M.C., Lenihan, H.S., Luckenback, M.W., Toropova, C.L., Zhang, G. and Guo, X. (2011) Oyster reefs at risk and recommendations for conservation, restoration, and management. BioScience 61, 107116.10.1525/bio.2011.61.2.5Google Scholar
Beukema, J.J. (1982) Annual variation in reproductive success and biomass of the major macrozoobenthic species living in a tidal flat area of the Wadden Sea. Netherlands Journal of Sea Research 16, 3745.10.1016/0077-7579(82)90015-1Google Scholar
Bostock, J., Lane, A., Hough, C. and Yamamoto, K. (2016) An assessment of the economic contribution of EU aquaculture production and the influence of policies for its sustainable development. Aquaculture International 24, 699733.Google Scholar
Boukal, D.S. and Berec, L. (2002) Single-species models of the Allee effect: extinction boundaries, sex ratios and mate encounters. Journal of Theoretical Biology 29, 1326.Google Scholar
Breen, P.A. and Adkins, B.E. (1980) Spawning in a British Columbia population of northern abalone, Haliotis kamtschatkana. The Veliger 23, 177179.Google Scholar
Campos-Silva, J.V., Peres, C.A., Antunes, A.P., Valsecchi, J. and Pezzuti, J. (2017) Community-based population recovery of overexploited Amazonian wildlife. Perspectives in Ecology and Conservation 15, 266270.Google Scholar
Carlon, D.B. and Olson, R.R. (1993) Larval dispersal distance as an explanation for adult spatial pattern in two Caribbean reef corals. Journal of Experimental Marine Biology and Ecology 173, 247263.10.1016/0022-0981(93)90056-TGoogle Scholar
Coma, R. and Lasker, H.R. (1997) Effects of spatial distribution and reproductive biology on in-situ fertilization success of a broadcast-spawning in vertebrate. Biological Bulletin 193, 2029.10.2307/1542733Google Scholar
Cruz-Rivera, E. and Hay, M.E. (2000) Can quantity replace quality? Food choice, compensatory feeding, and fitness of marine mesograzers. Ecology 81, 201219.10.1890/0012-9658(2000)081[0201:CQRQFC]2.0.CO;2Google Scholar
Erwin, D. (1976) A diving survey of Strangford Lough: the benthic communities and their relation to substrate – a preliminary account. In Keegan, B.F., Ceidigh, P.O. and Boaden, P.J.S. (eds) Biology of Benthic Organisms: 11th European Symposium on Marine Biology.Google Scholar
Farley, G.S. and Levitan, D.R. (2001) The role of jelly coats on sperm-egg encounters, fertilization success and selection on egg size in broadcast spawners. American Naturalist 157, 626636.Google Scholar
Fauvergue, X., Vercken, E., Malausa, T. and Hufbauer, R.A. (2012) The biology of small, introduced populations, with special reference to biological control. Evolutionary Applications 5, 424443. doi: 10.1111/j.1752-4571.2012.00272.x.Google Scholar
Gascoigne, J. and Lipcius, R.N. (2004) Allee effects in marine systems. Marine Ecology Progress Series, 269, 4959.Google Scholar
Gosling, E. (ed.) (2003) Bivalve molluscs: biology, ecology and culture. Oxford: Fishing News Books, Blackwell, pp. 131168.Google Scholar
Guy, C.I. and Roberts, D. (2010) Can the spread of non-native oysters (Crassostrea gigas) at the early stage of population expansion be managed? Marine Pollution Bulletin 60, 10591064.Google Scholar
Hayes, K.R and Barry, S.B. (2008) Are there any consistent predictors of invasion success? Biological Invasions 10, 483506.Google Scholar
Hiscock, K., Bayley, D., Pade, N., Lacey, C., Cox, E. and Enever, R. (2013) Prioritizing action for recovery and conservation of marine species: a case study based on species of conservation importance around England. Aquatic Conservation: Marine and Freshwater Ecosystems 23, 88110.Google Scholar
Kennedy, R.J. and Roberts, D. (1999) A survey of the current status of the flat oyster Ostrea edulis in Strangford Lough, Northern Ireland, with a view to the restoration of its oyster beds. Proceedings of the Royal Irish Academy 99B, 7988.Google Scholar
Korringa, P. (1952) Recent advances in oyster biology I, II. Quarterly Review of Biology 27, 339365.Google Scholar
Kramer, A., Dennis, B., Liebhold, A. and Drake, J. (2009) The evidence for Allee effects. Population Ecology 51, 341354.Google Scholar
Krebs, C.J. (1989) Ecological methodology. New York, NY: HarperCollins.Google Scholar
Kregting, L. and Elsäer, B. (2014) A hydrodynamic modelling framework for Strangford Lough Part 1: tidal model. Journal of Marine Science and Engineering 2, 4665.Google Scholar
Lallias, D., Boudry, P. and Lapègue, S. (2010) Strategies for the retention of high genetic variability in European flat oyster (Ostrea edulis) restoration programmes. Conservation Genetics 11, 182189. https://doi.org/10.1007/s10592-010-0081-0.Google Scholar
Liebhold, A.M. and Tobin, P.C. (2010) Exploiting the Achilles heels of pest invasions: Allee effects, stratified dispersal and management of forest insect establishment and spread. New Zealand Journal of Forestry Science 40, S25S34.Google Scholar
Low, P.J. (2006) Conservation status of the native oyster (Ostrea edulis) in Scotland. Unpublished PhD Thesis. Stirling University, Scotland.Google Scholar
Mann, R. (1979) Some biochemical and physiological aspects of growth and gametogenesis in Crassostrea gigas and Ostrea edulis grown at sustained elevated temperatures. Journal of the Marine Biological Association of the United Kingdom 59, 95110.Google Scholar
Melo, C.M.R., Silva, F.C., Gomes, C.H.A.M., Solé-Cava, A.M. and Lazoski, C. (2010) Crassostrea gigas in natural oyster banks in southern Brazil. Biological Invasions 12, 441462. https://doi.org/10.1007/s10530-009-9475-7.Google Scholar
Nehls, G., Diederich, S., Thieltges, D.W. and Strasser, M. (2006) Wadden Sea mussel beds invaded by oysters and slipper limpets: competition or climate control? Helgoland Marine Research 60, 135143.Google Scholar
Oliver, J. and Babcock, R. (1992) Aspects of the fertilisation ecology of broadcast spawning corals: sperm dilution effects and in situ measurements of fertilization. Biological Bulletin 183, 409417.Google Scholar
Orton, J.H. (1922) Phenomena and conditions of sex-change in the oyster (O. edulis) and Crepidula. Nature 60, 212.Google Scholar
Orton, J.H. (1937) Oyster biology and oyster-culture. London: Edward Arnold & Co.Google Scholar
OSPAR Commission. (2009) Background document for Ostrea edulis and Ostrea edulis beds. Report to the Convention for the Protection of the Marine Environment of the North-East Atlantic, 22 pp.Google Scholar
Rudloe, A. (2008) The breeding behaviours and patterns of movement of horseshoe crabs, Limulus polyphemus, in the vicinity of breeding beaches in Apalachee Bay, Florida. Estuaries and Coasts 3, 177183.Google Scholar
Santu, K.S., Nandan, S.B. and Athira, K. (2016) Occurrence of mass swarming of family Acartiidae (calanoid copepods) (zooplankton) in Ashtamudi Estuary, Kerala. International Journal of Marine Science 6, 18. doi: 10.5376/ijms.2016.06.0030.Google Scholar
Selkoe, K.A., Blenckner, T., Caldwell, M.R., Crowder, L.B., Erickson, A.L., Essington, T.E., Estes, J.A., Fujita, R.M., Halpern, B.S., Hunsicker, M.E., Kappel, C.V., Kelly, R.P., Kittinger, J.N., Levin, P.S., Lynham, J.M., Mach, M.E., Martone, R.G., Mease, L.A., Salomon, A.K., Samhouri, J.F., Scarborough, C., Stier, A.C., White, C. and Zedler, J. (2015) Principles for managing marine ecosystems prone to tipping points. Ecosystem Health and Sustainability 1, 1724.Google Scholar
Shepherd, S.A. (1986) Studies of southern Australian abalone (genus) Haliotis: VII. Aggregative behaviour of the H. laevigata in relation to spawning. Marine Biology 90, 231236.Google Scholar
Smith-Gill, S.J. (1975) Cytophysiological basis of disruptive pigmentary patterns in the leopard frog Rana pipiens. II. Wild type and mutant cell-specific patterns. Journal of Morphology 146, 3554.Google Scholar
Smyth, D., Kregting, L. and Roberts, D., et al. (2016) Using particle dispersal models to assist in the conservation and recovery of the overexploited native oyster (Ostrea edulis) in an enclosed sea lough. Journal of Sea Research 108, 5059.Google Scholar
Smyth, D., Mahon, A.M., Roberts, D. and Kregting, L. (2018) Settlement of Ostrea edulis is determined by the availability of hard substrata rather than by its nature: implications for stock recovery and restoration of the European oyster. Aquatic Conservation: Marine and Freshwater Ecosystems 28, 110. https://doi.org/10.1002/aqc.2876Google Scholar
Smyth, D., Roberts, D. and Browne, L. (2009) Impacts of unregulated harvesting on a recovering stock of native oysters (Ostrea edulis). Marine Pollution Bulletin 58, 916922.Google Scholar
Stephens, P.A. and Sutherland, W.J. (1999) Consequences of the Allee effect for behaviour, ecology and conservation. Trends in Ecology and Evolution 14, 401405.Google Scholar
Sullivan, A.P., Bird, D.W. and Perry, G.H. (2017) Human behaviour as a long-term ecological driver of non-human evolution. Nature Ecology and Evolution 1, 6571.Google Scholar
Tamburri, M.N., Luckenbach, M.W., Breitburg, D.L. and Bonniwell, S.M. (2008) Settlement of Crassostrea ariakensis larvae: effects of substrate, biofilms, sediment and adult chemical cues. Journal of Shellfish Research 27, 601608.Google Scholar
Taylor, C.M. and Hastings, A. (2005) Allee effects in biological invasions. Ecology Letters 8, 895908.Google Scholar
Thurstan, R.H., Hawkins, J.P. and Roberts, C.M. (2013) Oyster (Ostrea edulis) extirpation and ecosystem transformation in the Firth of Forth, Scotland. Journal for Nature Conservation 21, 253261.Google Scholar
Tobin, P.C., Berec, L. and Liebhold, A.M. (2011) Exploiting Allee effects for managing biological invasions. Ecology Letters 14, 615624.Google Scholar
UKBAP (2009) Native oyster (Ostrea edulis ) UK biodiversity species action plan. London: UK Biodiversity Group, pp. 241242.Google Scholar
Utting, S.D., Helm, M.M. and Millican, P.F. (1991) Recent studies on the fecundity of European flat oyster (Ostrea edulis) spawning stock in the Solent. Journal of the Marine Biological Association of the United Kingdom 71, 909911.Google Scholar
Vitiello, V., Carlino, P.A., Prete, F.D., Langellotti, A.L. and Sansone, G. (2011) Effects of cooling and freezing on the motility of Ostrea edulis (Linnaeus 1758) spermatozoa after thawing. Cryobiology 63, 118124.Google Scholar
Walne, P.R. (1974) Culture of bivalve oysters. 50 years of experience at Conway. London: Whitefriars Press.Google Scholar
Wells, H., Strauss, E.G., Rutter, M.A. and Wells, P.H. (1998) Mate location, population growth and species extinction. Biological Conservation 86, 317–234.Google Scholar
Yund, P.O. (2000) How severe is sperm limitation in natural populations of marine free-spawners? Trends in Ecology and Evolution, 15, 1013.Google Scholar
Zwershke, N., Emmerson, M.C., Roberts, D. and O'Connor, N.E. (2016) Benthic assemblages associated with native and non-native oysters are similar. Marine Pollution Bulletin 111, 305310.Google Scholar
Figure 0

Fig. 1. Strangford Lough Northern Ireland and the three survey sites of Newtownards Sailing Club (NSC), Greyabbey and Kircubbin.

Figure 1

Table 1. Mean density, inter-individual distance (cm) and dispersion indices of O. edulis across the three sample sites.

Figure 2

Fig. 2. Relationship between mean fecundity of larvae (n g1 wet tissue weight) and oyster density (pooled data – all sites).

Figure 3

Fig. 3. Relationship between percentage of brooding oysters and oyster density (pooled data – all sites).

Figure 4

Fig. 4. Mean brood density (n larvae g1 wet tissue weight) per n × 17 samples at three different sites where the nearest neighbour was ≤1.5 m (open) and >1.5 m (shaded). Error bars represent the standard deviation of the mean.