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Effects of reduced salinity on
fertilization and larval development
in the Pacific Oyster, Crassostrea
gigas (Thunberg, 1789)
Alexandra Kinnby
Degree project for Master of Science (45 credits) in
Biology
BIO761, 45 hec
Autumn 2014 and Spring 2015
Department of Biological and Environmental Sciences
University of Gothenburg
Examiner: Professor Kerstin Johannesson
Department of Biological and Environmental Sciences - Tjärnö
University of Gothenburg
Supervisor: Professor Jonathan Havenhand
Department of Biological and Environmental Sciences - Tjärnö
University of Gothenburg
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Front page photo of Crassostrea gigas by Alexandra Kinnby
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Populärvetenskaplig sammanfattning………………………………………………….. 4
Abstract…………………………………………………………………………………… 5
1. Introduction………………………………………………………………………..…… 6
2. Materials and Methods………………………………………………………………… 9
2.1 Source and conditioning of Crassostrea gigas …………………………………….. 9
2.2 Seawater chemistry……………………………………………………………….. 10
2.3 Spawning and fertilization………………………………………………………… 10
2.4 Fertilization success………………………………………………………………. 12
2.5 Larval development (D-stage)…………………………………………………..… 13
2.6 Methodological development……………………………………………………… 13
2.7 Statistical analyses/ Data analysis……………………………………………….. 14
3. Results…………………………………………………..…………………………….. 14
3.1 Fertilization success………………………………………………………………. 14
3.2 Larval development (D-stage)…………………………………………………….. 17
4. Discussion……………………………………………………………………………… 18
4.1 Fertilization success………………………………………………………………. 19
4.2 Larval development (D-stage)…………………………………………………….. 21
4.3 Adaptation or Plasticity?………………………………………………………….. 22
4.4 Sire and Dam effects………………………………………………………………. 23
4.5 Conclusion…………………………………………………………………………. 24
Acknowledgments………………………………………………………………………… 25
References………………………………………………………………………………… 26
Appendix 1
Appendix 2
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Populärvetenskaplig sammanfattning
Sänkt salthalt i havsvatten leder till försämrad befruktning och larvutveckling
hos det japanska jätteostronet, Crassostrea gigas
Klimatförändringarna påverkar marina system genom förändringar i salthalt, temperatur och pH.
Prognoser för förändringar i svenskt klimat tyder på ökad nederbörd och därmed sänkt salthalt i
kustnära hav. Ekosystem nära kusterna är speciellt sårbara på grund av de grunda vattennivåerna.
Utbredning av exotiska (invasiva) arter är en följd av klimatförändringarna. Detta är ett stort hot
mot den biologiska mångfalden världen över.
Ostron odlas över hela världen och har därmed fått stor spridning. Det japanska jätteostronet,
Crassostrea gigas, (Thunberg, 1789), kommer ursprungligen från nordvästra Stilla Havet, men har
förflyttats över hela världen för att användas till ostronodlingar. För att de japanska jätteostronen
skall kunna föröka sig krävs en salthalt på 20 promille och en vattentemperatur på minst 20°C. Av
denna anledning trodde man länge att arten inte skulle kunna spridas och etablera sig i nordligare
breddgrader. Dock har det japanska jätteostronet spridits norrut och år 2007 fann man många
etablerade populationer längs den svenska västkusten. I svenska vatten är blåmusslan, Mytilus
edulis, en viktig ekosystemingenjör. Det japanska jätteostronet trivs under samma förutsättningar
men har en snabbare tillväxt än blåmusslan och det är därför troligt att denna kommer att
konkurreras ut.
Det mest kritiska steget i det japanska jätteostronets livscykel är utveckling av det befruktade ägget
samt larvutvecklingen. Därför har denna studie inriktats på effekten av en sänkt salthalt på den
tidiga utvecklingen av ostron - befruktning och larvutveckling. Vuxna ostron från två geografiskt
sett åtskilda populationer användes, en väletablerad population från Storbritannien och en relativt
ung population från Sverige. Vid varje experimenttillfälle befruktades ägg från tre honor med
spermier från tre hanar, dvs totalt sett nio föräldrakombinationer. Andelen befruktade ägg räknades
två timmar efter befruktning med hjälp av mikroskop. Efter ytterligare 24 timmar kunde antalet
embryon som börjat utveckla skal bestämmas, även detta gjordes med hjälp av mikroskop.
Resultaten visade att befruktning såväl som larvutveckling i japanska jätteostron påverkas negativt
av lägre salthalter. Lägre salthalt i vattnet innebär således att färre ägg kommer att befruktas och
vidareutvecklas. Resultaten visar också att de två populationerna reagerar olika på en förändrad
salthalt, den svenska populationen tycktes ha anpassat sig till att kunna utvecklas i en lägre salthalt.
Detta skulle kunna förklaras av genetisk anpassning.
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Effects of reduced salinity on fertilization and larval development in the Pacific
Oyster, Crassostrea gigas (Thunberg, 1789)
Abstract
Climate change affects marine systems through changes in salinity, temperature, and pH. The
projections for Swedish climate changes suggest increased precipitation and thereby a lowered
salinity in benthic areas. Coastal ecosystems are particularly vulnerable because of the shallow
water levels. Expansion of exotic (invasive) species accompanies climate change; a great threat to
biodiversity. Of aquatic organisms, oysters are among the most translocated worldwide. Crassostrea
gigas (Thunberg, 1789), is native to the north-west Pacific, but has been distributed globally for
aquaculture use under the assumption that unintentional spread would be limited by their
temperature requirement for reproduction. However, mounting evidence shows that C. gigas has
started to outcompete the blue mussel, Mytilus edulis, an important ecosystem engineer.
The most critical phases in the life cycle of C. gigas are embryogenesis and larval development.
Here, the influence of salinity on two important stages of the early development of oysters was
studied in two geographically separated populations - fertilization success and larval development.
Adult C. gigas were obtained; one from an established site and one representing a recently invaded
population. Eggs from 3 females were fertilized with sperm from 3 males yielding a total of nine
parental combinations per experiment. Using microscopy, fertilization success and larval
development could be determined after 2 and 26h, respectively. The results showed that decreasing
salinity had a significant negative effect on fertilization as well as on successful development to
early veliger (D-larvae; i.e. development of a shell) in C. gigas. But also that the two populations
responded differently to changes in salinity. This would most likely be explained by adaptation.
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1. Introduction
Some of the largest and most potent selective pressures acting on marine ecosystems at present can
all be captured under the umbrella of climate change (Denman et al., 2007). Climate change affects
many marine systems in several ways, but the most powerful effects are felt in changes to salinity,
temperature, and pH (IPCC, 2007). As these environmental factors change in the oceans, all species
living in the oceans will be affected in turn, in one manner or another (Harley et al., 2006).
Over the last 40 years the average global sea surface temperature has increased 0.11°C per decade
(IPCC, 2014). The mean sea surface temperature is expected to continue rising the coming century
by 1.8-4°C (Solomon et al., 2007).
This higher temperature in the polar oceans leads to increased melting of polar ice, which in many
instances leads to globally reduced salinity (Jenkins, 1998). On a more local scale, higher
temperatures are projected to increase evaporation, leading to an increase in salinity, whereas in
other areas, in particular near the coasts, increased precipitation is likely to lead to reduced salinity
(Wentz et al., 2007). From 1977 to 2007 the sea surface salinity in the southern Baltic sea decreased
with about one psu (Vourinen et al., 2015). The result is thus a polarization towards more extreme
conditions, which can increase vertical stratification and potentially change patterns of ocean
circulation (Durack & Wijffels, 2010).
Coastal ecosystems in particular are expected to be negatively affected (Levitus et al., 2009) by
rising temperature and associated consequences as the shallow water levels make them more
vulnerable to changes in water characteristics (IPCC, 2001; Harley et al., 2006). The salinity of
coastal waters, including those of western Scandinavia, is projected to be further reduced by the
increase in precipitation that follows climate change (Groisman et al., 1999). The changing
conditions cause geographic shifts in niches that result in poleward migrations of species from
warmer areas, thus leading to increased biodiversity in higher latitude ecosystems (Stachowicz et
al., 2002; Beaugrand et al., 2015).
Salinity is an important environmental variable behind physiological changes that define stress
(Tomanek, 2011). Across much of the globe, tidally-induced fluctuations in temperature and salinity
are predominant stress factors (Gagnaire et al., 2006), but along the coast of western Sweden there
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is a deep water mass of high salinity water above which floats a layer of stable surface water with a
salinity that ranges from near freshwater in the Baltic Sea to nearly open ocean salinity in the
Skagerak Sea (Renborg, 2014). Salinity will be affected by climate change, resulting in either
increased or reduced salinity, as described above. This pattern in surface water salinity reductions
may also be expected along the Swedish west coast (van de Waal et al., 2009).
The combined effects of climate change and the expansion of exotic species are believed to be the
greatest threats to biodiversity worldwide (Vitousek et al., 1997; Stachowicz et al., 2002; Park,
2004). Changes in species composition and interactions in marine ecosystems have always
occurred, but novel invasive species – whether a consequence of range expansion or human
introduction – are capable of causing great disturbance to existing ecosystems (Carlton, 1987;
Walther et al., 2002; Diederich et al., 2005). Anthropogenic activities make it possible for these
species to overcome otherwise insurmountable biogeographical barriers and do great damage
(Mooney & Cleland, 2001; Nehring, 2006). The effects of invasive species on native ecosystems are
often a consequence of complex interactions between many different species and via many
pathways (Mooney & Cleland, 2001). Understanding these interactions between native and invasive
species is important if we are to limit future damage and minimize present damage to the
ecosystems.
The ability to exploit an array of abiotic conditions is a common trait among invasive species
(Grosholz & Ruiz, 1996; Kolar & Lodge, 2001). The ability of individuals to rapidly accommodate
to environmental changes by altering the phenotype is termed “phenotypic plasticity”, and may be a
mechanism for invasive species to be more successful. Marine species with a pelagic larval stage
may be more prone to alter their phenotype but may also experience rapid evolution if sufficient
genetic variability is present, i.e. genetic changes occurring through selection (Renborg, 2014).
Among aquatic organisms oysters are perhaps the species that have been the most translocated
worldwide (Diederich et al., 2005; Ruesink et al., 2005). Many exotic oyster species have been
deliberately introduced through aquaculture for their economic value (FAO, 2007). The Pacific
oyster, Crassostrea gigas (Thunberg, 1789), is native to the north-west Pacific, and for many
decades has been distributed globally for aquaculture under the assumption that their temperature
and salinity tolerances for reproduction would limit unintentional spread (Eklund et al., 1977; Zhao
et al., 2012). Several sources suggest that C. gigas requires water warmer than 20˚C and a salinity
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of 20 PSU (practical salinity units) for successful spawning (Fabioux et al., 2005; FAO, 2007).
However, C. gigas has been observed to spread into waters of western Sweden that are typically
cooler and more brackish than this. The increased water temperatures projected due to climate
change will increase the risk for further invasion (Wrange et al., 2010; Strand et al., 2012).
The blue mussel, Mytilus edulis, is an important ecosystem engineer in Swedish shallow coastal
waters (Norling et al., 2014). C. gigas competes directly with M. edulis for hard substrate, and their
faster growth and larger size at maturity make C. gigas more successful (Diederich, 2006). In the
Wadden Sea this has resulted in mussel beds being turned into oyster reefs (Diederich et al., 2005;
Ruesink et al., 2005). Not only the mussels are directly influenced by the presence of oysters - they
alter the local biodiversity and ecosystem form and function (Dolmer et al., 2014) and also have
negative effects on seabirds that prey on the mussels – especially Eider (Somateria mollissima)
(Baird, 2012). It has been noted in some cases that oyster reefs have a higher diversity than adjacent
mussel beds (Markert et al., 2010), but this may be due to facilitated secondary invasions (Lang and
Buschbaum, 2010) and sheltering of juvenile fish or invertebrates (Ruesink et al., 2005).
The Pacific Oyster, C. gigas, is an intertidal species that is commonly reared in estuarine areas. It is
an osmo-thermo-conformer (Gagnaire et al., 2006), and thus tolerates variations in salinity (10-35
PSU with optimal 20-25 PSU) and temperature (-1.8°- 35°C with optimal ~20°C) (FAO, 2007;
Kurihara et al., 2007; Strand et al., 2012). C. gigas is a dioecious broadcast spawning species
(Nehring, 2011); one female can release between 50 and 200 million eggs per spawning (FAO,
2007), which is substantially more than native Scandinavian oyster species (Krassoi et al., 2001).
Fertilization takes place in the water column where larvae hatch and develop through two pelagic
larval forms; trochophore and veliger. The early veliger stage is reached after 24-48h (depending on
temperature), and has a characteristic shape called the “D-stage” due to its D-shaped shell (FAO,
2007). During this developmental process, the shell material is changed from aragonite to calcite,
two forms of CaCO3 that differ in their crystal lattice and susceptibility to climate change. Previous
studies have investigated the impacts of temperature as well as ocean acidification on early life
stages of marine invertebrates, including C. gigas. Few studies (see Pechenik et al., 2007; Allen &
Pechenik, 2010) have focused on the effects of salinity on these stages, although none of them
concerned effects of reduced salinity on C. gigas. However, a study by Ko et al. (2014) showed that
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different developmental stages exhibit different vulnerabilities, and it is important to study effects
on the entire process in order to understand how oyster populations will respond to changes in
climate.
Because of the commercial potential of C. gigas, many early studies have focused on determining
the optimal conditions for reproduction for aquaculture. Today, accelerating climate change also
creates an urgent need to understand how this species will react to changing ocean temperature, pH
and salinity so that we can project further invasiveness and spread of C. gigas. As noted earlier,
salinity of the oceans will be affected by climate change. This is important because salinity impacts
many aspects of physiology and energy use through changes to osmotic pressures, which influence
e.g. growth, reproduction, and dispersal (Kinne, 1971; as cited by Pechenik et al., 2011; Torres et
al., 2011). In turn, all these factors will influence invasion and spread. It has been established that
the most critical phases in the life cycle of C. gigas are embryogenesis and larval development
(Eklund et al., 1977; MacInnes & Calabrese, 1979), and consequently it is reasonable to predict that
these stages might be the most susceptible to changes in salinity. Therefore, this study was designed
to study the influence of salinity on two important stages of the early development of oysters;
fertilization and larval development in two geographically separated populations.
Within a species’ range, the central populations have a higher genetic variation, whereas the
populations at the ecological margins tend to have less genetic variation, but be more strongly
selected for limiting environmental variables, such as salinity. Therefore two populations were
chosen as representatives for these different prerequisites (Parkash, 1973).
It is as yet undetermined how projected changes to salinity will affect C. gigas. Here I investigate
the effect of reduced salinity on the development of early life stages of two populations of C. gigas.
I hypothesize that reduced salinity will negatively impact fertilization and embryonic/larval
development. These negative impacts are expected to be greater in the more central population
because it has not been exposed to strong selection for low salinity.
2. Materials and Methods
2.1 Source and conditioning of Crassostrea gigas
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Two populations of sexually mature adult Crassostrea gigas were obtained – one from Guernsey
Sea Farms (United Kingdom), a location that is “central” to the European distribution of C. gigas
and where this species has been present for over 50 years, and one from Ostrea Sverige AB (Koster,
Sweden) that had been collected from Svallhagen, Tjärnö, and represented a recently invaded
population (Wrange et al., 2010). Oysters from Guernsey were conditioned to reproductive maturity
at 23-25°C in a salinity range of 31-34 practical salinity units (PSU) and a pH of 8.1. Oysters from
Svallhagen were conditioned at similar salinity and pH to those from Guernsey but at lower
temperatures of 14-15°C (conditioning temperatures reflected the prevalent conditions during the
spawning season in the respective locations). Oysters were shipped to Sven Lovén Centre for
Marine Sciences, Tjärnö, Sweden, where the experiments were conducted. Oysters from Guernsey
(hereafter referred to as Guernsey population) were maintained in flowing seawater at 18˚C, pH
8.01, and salinity 33 PSU and fed with Isochrysis galbana and Skeletonema costatum for a period
of up to 2 weeks. Oysters from Koster (hereafter referred to as Svallhagen population) were
obtained the day before or the same day as the experiments were performed.
2.2 Seawater chemistry
For all experiments and dilutions, 0.22 µm Millipore filtered deep seawater (FSW) was used. Five
salinity treatments were applied; 33, 28, 23, 18, and 13 PSU. Dilutions were obtained using FSW
(pH=8.01) and filtered fresh tapwater (FFW; pH=7.95), and verified using a conductivity meter
(Cond 3210, WTW). All filtering and mixing of treatments (dilutions) were done the day prior to
experimentation. All experiments were conducted at 20 ± 0.5°C.
2.3 Spawning and fertilization
Each experiment comprised 3 males and 3 females. Gametes were extracted either with a Pasteur
pipette inserted through a hole drilled in the shell above the gonads (Havenhand & Schlegel 2009),
or by opening the shell completely, i.e. strip-spawning (Beaumont, 2010, p.88).
Sperm from each male were stored in separate Eppendorf tubes on ice to maximize their longevity
(Havenhand & Schlegel, 2009). Sperm concentrations were verified by hemocytometer counts of
samples dyed (and immobilized) with Lugol’s solution. A funnel plot was used to determine how
many hemocytometer fields (cells on the grid) were required per replicate to ensure that the count
was representative of the true concentration (Figure 1). This showed that counting sperm in 32 cells
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9"
average"sperm/hemocytometer"cell"
8"
7"
6"
cell"value"
mean2"
5"
mean4"
4"
mean8"
mean16"
3"
mean32"
2"
mean64"
1"
0"
1"
10"
100"
Log"Number"of"cells"averaged"
Figure 1. Funnel plot of number of cells in a hemocytometer that must be counted, to achieve the
true sperm concentration of Crassostrea gigas sperm in a sample.
provided the optimal balance between accuracy and time required (Figure 1), and therefore this
metric was applied to all subsequent experiments.
After extraction, eggs were immediately placed in 10mL 33 PSU FSW in an incubator at 20°C and
were left for at least one hour before fertilization (Song et al., 2009). Allowing eggs to swell in
FSW prior to insemination, increases their diameter to 50µm, simulating the final stage of natural
maturation, (Arakawa, 1990) and decreases the sensitivity to polyspermy (Stephano & Gould,
1988). During this period, egg concentrations for each female were determined after carefully
mixing the suspension, and transferring 500µL to a Petri dish that was examined using Olympus
SZX16 microscope with SDF PLAPO 0.5XPF objective at 0.7x magnification. The concentrations
were estimated visually after prior calibration with suspensions of known concentrations. This
procedure was used in order to allow rapid determination of the egg concentration before each
fertilization experiment. Egg concentrations were adjusted to yield a final egg suspension of ~ 300
oocytes/mL for each female. After one hour, different quantities of FFW were gradually added,
during another hour, to achieve final treatment salinities (33, 28, 23, 18, and 13 PSU) without
causing rapid osmotic shock to the eggs.
Eggs from each female were fertilized with sperm from each male yielding a total of nine families
(parental combinations) per experiment. Fertilizations were achieved by adding sperm in 3
increments, with 2 minutes interval, to maximize fertilization success while also minimizing the
risk of polyspermy (Allen & Marshall, 2014). Gametes were left to fertilize for a total of 12 minutes
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(Havenhand & Schlegel, 2009), after which time fertilizations were terminated by separating sperm
and eggs via centrifugation (Centrifuge 5810 R, Eppendorf) for 5 minutes at 20°C and 2000rcf
(preliminary experiments showed that these conditions did not significantly reduce fertilization
success when compared to gametes that were not centrifuged).
The supernatant containing the sperm was discarded and the 1mL of seawater containing the lightly
pelletted eggs was resuspended in 6.5 mL treatment water. The eggs from each female were
distributed to three Petri dishes i.e. 2.5mL in each dish. At the start of the experiment all females
were crossed with one male and this procedure was repeated with the next male one hour later and
with the third male after another hour (See Appendix 1 for lab protocol and details).
These experiments were conducted once with the Guernsey population and twice with the
Svallhagen population.
2.4 Fertilization success
Eggs were incubated for two hours after which each Petri dish was photographed using a Nikon
D810 digital SLR mounted on an Olympus SZX16 microscope with SDF PLAPO 0.5XPF objective
at 5X magnification. Photos were analyzed in Adobe Photoshop CS6. Eggs were considered
fertilized if they displayed cleavage after two hours (Figure 2)
For reference purposes an overview photo of each well was taken after fertilization and the number
of eggs counted in ImageJ64 using the “Colony Counter” plugin. This number was used as a
reference for calculations of the percentage development to D-stage larvae (see below). After
a
b
Figure 2. Eggs of Crassostrea gigas 2h after addition of sperm.
a) Non-cleaved eggs. b) Eggs displaying cleavage. c) D-stage 26h after addition of sperm.
c
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photographing, Petri dishes were placed back into incubators and held at 20˚C for a further 26h
(larvae are estimated to reach the D-stage 15-28h after fertilization) (FAO, 2007).
2.5 Larval development (D-stage)
After 26h (post-fertilization), all embryos/larvae in each dish were euthanized with 95% ethanol to
stop development. The number of D-stage larvae were subsequently counted manually at 10x
magnification using an Olympus IX71 microscope.
2.6 Methodological development
The accuracy of using the Colony
Counter plugin in ImageJ64 to count
the number of eggs in each well was
confirmed by comparing the count
achieved with ImageJ64 to a manual
count of the eggs from each of 24
photographs (Figure 3).
The influence of initial egg density was
considered in a pilot study. The results
showed that fertilization success was
not affected by initial egg density
Figure 3. Comparison of number of eggs from the
Pacific Oyster, Crassostrea gigas, found in each well
using ImageJ 64, Colony Counter plugin, vs manual
count (n=24; R2≈1).
(Figure 4).
Methodological experiments were also
conducted to determine the most
optimal method for separating fertilized
eggs and sperm. Filtration and
centrifugation were compared.
Filtration through 20µm filter resulted
in loss of eggs, so centrifugation was
attempted as an alternative to reduce the
risk for mechanical errors.
Figure 4. The importance of egg density on fertilization
success in the Pacific Oyster, Crassostrea gigas (n=24;
R2=0.10).
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Centrifugation was performed for 5, 10, and 20 min at 2000rcf at 20°C and the results showed that
centrifugation for 5 minutes yielded a high fertilization success with low variation (Figure 5).
2.7 Statistical analyses/ Data
analysis
All data was analyzed in R studio
with linear mixed-effect models
(lmer). One analysis was performed
with fertilization success ratio as the
response variable and one where Dstage ratio was the response variable.
Random factors were dam/sire and
dam x sire interaction. Salinity and
population were fixed factors. Since
the data were proportions, they were
arcsine transformed to make them
normally distributed (Whitlock &
Schluter, 2009).
One linear-mixed-model analysis
was performed for fertilization and
thereafter another linear-mixed-
Figure 5. Fertilization success ratio in the Pacific Oyster,
Crassostrea gigas, under four different methods to
separate eggs and sperm. Samples were either centrifuged
at 2000rcf at 20°C for 5 (C05), 10 (C10) or 20 (C20) min
or filtered with a 20µm mesh (n=6). Median and the
interquartile range (IQR; first to third quartile) displayed
by the box. The whiskers show the maximum and
minimum values, respectively. Suspected outliers (defined
as 1.5xIQR above the third quartile) shown with the
circles.
model analysis was performed for
the D-stage. Salinity and population were fixed factors in both of these analyses, whereas dam, sire
and salinity were treated as random factors. This complex statistical array allows the calculation of
genetic variance components (Laurila et al., 2002). Following this, each population was analyzed
with a one-way ANOVA with Tukey’s post-hoc test to determine between which salinities there is a
difference in fertilization success and D-stage larval development respectively.
3. Results
3.1 Fertilization success
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Salinity had a pronounced effect on fertilization success in both populations. In both cases, a
decrease in salinity was associated with lower fertilization success, although this effect was stronger
in the Guernsey population, which showed higher fertilization success at high salinities (Figure 6).
In the Svallhagen population there was no marked difference in fertilization success when the
0.6
0.4
0.0
0.2
Fertilization success
0.8
1.0
salinity was lowered from 35 to 18 PSU, which was the lowest level at which fertilization was
13G
13S
18G
18S
23G
23S
28G
28S
33G
33S
Salinity (PSU)
Figure 6. Box-plot of fertilization success (proportion of eggs observed to be cleaving 2h
after fertilization) at different salinities in two populations of Crassostrea gigas;
Guernsey (G; dark blue) and Svallhagen (S; light blue). Median and the interquartile
range (IQR; first to third quartile) displayed by the box. The whiskers show the
maximum and minimum values, respectively. Suspected outliers (defined as 1.5xIQR
above the third quartile) shown with the circles.
detected (Figure 6). In contrast, the Guernsey population showed a steady decline in fertilization
success from relatively high levels at 33 PSU to low – but not zero – fertilization success at the
lowest salinities (Figure 6).
Linear-mixed-model analysis of all these combined data showed a significant interaction between
salinity and population (t=4.46; P<0.01; Table 1), indicating that the two populations – Guernsey
and Svallhagen – responded differently to the salinity treatments. Sire effects were larger than the
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residual variation, and an order of magnitude greater than dam effects and the dam x sire
interaction. None of these effects were statistically significant (Table 1).
Post-hoc (Tukey’s) tests for the Guernsey population showed that the fertilization success at all
salinities were statistically different from each other (Table 2; although the difference in fertilization
Table 1. Results of linear-mixed-model analysis of the effects of salinity, population,
and parentage on fertilization in Crassostea gigas from Guernsey (UK) and
Svallhagen (Sweden). df = degrees of freedom, F-values (Roman) are provided for
random effects, and t-values (italic) for fixed effects. Significant probability values (P)
are marked in bold.
Source
df
Variance
F (or t)
P
dam
2
0.002939
0.150
0.86012
sire
2
0.023887
1.218
0.29500
sire:dam
4
0.002239
0.114
0.36461
salinity
4
0.045756
12.656
0.00022
population
1
0.137478
1.077
0.47641
sal:popul
4
0.009308
4.460
0.01120
Residual
387
0.019605
Table 2. Influence of salinity on fertilization success and D-stage larvae development
in two populations of Crassostrea gigas, from Guernsey (UK) and Svallhagen
(Sweden). Post-hoc (Tukey’s) test of one-way ANOVA analyses. Significant
probability values (P) are marked in bold.
Fertilization
D-stage
Salinities
Guernsey
Svallhagen
Guernsey
Svallhagen
33-28 PSU
0.0471
0.0879
0.0000017
0.113
33-23 PSU
0.00
0.0675
0.00
0.00
33-18 PSU
0.00
0.00000110
0.00
0.00
18-13 PSU
0.00
0.00
0.00
0.00
28-23 PSU
0.00537
1.00
0.0234
28-18 PSU
0.00
0.0296
0.0104
0.000000100
0.00
28-13 PSU
0.00
0.00
0.00775
0.00
23-18 PSU
0.0000165
0.0398
1.00
0.515
23-13 PSU
0.00
0.00
0.996
0.00
18-13 PSU
0.000599
0.0000125
1.00
0.0000192
!16
success between 33 PSU and 28 PSU was just barely significant; P = 0.0471; Table 2). In contrast,
for Svallhagen, post-hoc testing showed that there was no significant difference in fertilization
success between the three highest salinities, 33 - 23 PSU (Table 2). Consequently, for this
population, fertilization success at the two lowest salinities were significantly different from each
other as well as from the three highest salinities (Table 2).
3.2 Larval development (D-stage)
0.05 −2 0.06
0.03 −30.04
−4
0.02
−5
0.00
0.01
logLarval
development
Larval development
0.07
Like fertilization success, larval development to D-stage (after 26 h) was also noticeably influenced
13G
13G
13S
18G
18S
23G
23S
28G
28G
28S
28S
33G
33G
33S
33S
Salinity (PSU)
Figure 7. Box-plot of larval development (proportion of D-larvae 26 h after fertilization) at
different salinities in two populations of Crassostrea gigas; Guernsey (G; dark blue) and
Svallhagen (S; light blue). Median and the interquartile range (IQR; first to third quartile)
displayed by the box. The whiskers show the maximum and minimum values, respectively.
Suspected outliers (defined as 1.5xIQR above the third quartile) shown with the circles.
by salinity. None of the populations showed larval development at the lowest salinity level (13
PSU). For the Guernsey population development was highest at 35 PSU, lower at 28 PSU, and –
with the exception of a few outliers – zero at lower salinities (Figure 6). In contrast, the Svallhagen
population showed gradually decreasing developmental success with decreasing salinity to 18 PSU.
No D-stage development was observed at 13 PSU (Figure 7).
!17
Table 3. Results of linear-mixed-model analysis of the effects of salinity, population,
and parentage on larval development, to the D-stage, in Crassostrea gigas from
Guernsey (UK) and Svallhagen (Sweden). df = degrees of freedom, F-values (Roman)
are provided for random effects, and t-values (italic) for fixed effects. Significant
probability values (P) are marked in bold.
Source
df
Variance
F (or t)
P
dam
2
0.00003196
0.042
0.95850
sire
2
0.0002295
0.303
0.73750
sire:dam
4
0.0000424
0.056
0.20110
salinity
4
0.0078732
11.082
0.00038
population
1
0.0564298
3.679
0.16900
sal:popul
4
0.002687
6.551
0.00281
Residual
387
0.0007571
Linear-mixed-model analysis on the effect of salinity on D-stage development showed that there
was a significant interaction between salinity and population (t=6.55; P<0.01; Table 3), indicating
that the two populations responded differently to salinity. Further, no significant effects of dam, sire
or dam × sire interaction were observed. The residual variation was more than twice as large as the
dam effects and about three times as large as the sire effects (Table 3). Both dam and sire effects
were an order of magnitude greater than sire × dam interaction (Table 3).
Post-hoc (Tukey’s) tests for the Guernsey population showed that developmental success at the two
highest salinities differed significantly from each other as well as from the three low salinities (the
latter were all zero; Table 3). For the Svallhagen population there was no difference between levels
of developmental success in the two highest salinities nor between that in 23 and 18 PSU.
Development at all the other salinities were significantly different from each other (Table 2).
Quantitative genetic analyses were attempted, but the sample sizes were too small, a quick review
of the literature (e.g. Laurila et al., 2002) showed that sample size for quantitative genetics are
usually in the order of at least 60 families. However, an example of how those data could be
calculated is given in an Appendix. Briefly, genetic variances of fertilization success as well as
larval development could give an understanding of how the two populations would be affected by
salinity (Newkirk et al., 1977; Laurila et al., 2002).
!18
4. Discussion
The present study showed that decreasing salinity from 33 to 13 PSU had statistically significant
negative effects on fertilization success and development to D-stage in C. gigas from two
populations. This result is perhaps unsurprising as C. gigas was originally introduced to high
salinity (~33 PSU) waters in Europe, and may therefore be expected to have adapted to the fullymarine salinities that characterize those more central European locations. The significant
interactions between population (Guernsey and Svallhagen) and salinity in the linear mixed models
indicates that C. gigas from the different populations responded differently to salinity in these
experiments. This may be evidence of the ability to adapt to new environments, due to genetic
selection, or may have been a result of phenotypic plasticity, which are discussed further below.
4.1 Fertilization success
For the Svallhagen population fertilization success declined only slightly with salinity in the four
highest salinities (33 - 18 PSU), yet no eggs cleaved at the lowest salinity level (13 PSU). This
suggests that the cut-off salinity level, below which no fertilization occurs, most likely lies between
13 and 18 PSU in this population. This result contrasts markedly with that of the Guernsey
population that showed a steadily declining trend in fertilization success as salinity decreased. This
difference in pattern between the two populations may have arisen because overall fertilization
success in the Guernsey population was ~2 × higher at higher salinities (Figure 5) – i.e. the “flatter”
response of the Svallhagen population may have been an artifact of lower fertilization success
combined with sampling error. Alternatively, this pattern may have arisen because there was a true
difference in shape of the response-norm between the populations. Without further experimentation
(see below) it’s not possible to distinguish between these two possibilities. However it remains clear
that oysters from these populations responded differently to declining salinity.
Comparing the results obtained here, with those from other studies can aid interpretation. For
example, Fujiya (1970) found that in “optimal salinities” around Japan (23-28 PSU) eggs from C.
gigas had a high success in terms of both fertilization and normal larval development. However, if
the salinity was “too high or too low” (actual salinity levels were not stated), eggs were still
fertilized but they did not start to cleave. This finding was explained by the fact that at sub-optimal
salinity the likelihood that the blastomeres of the embryos will separate from each other is
!19
pronounced (Fujiya, 1970). The lack of detail provided by Fujiya (1970) makes it difficult to draw a
firm conclusion, but it seems that the Japanese oyster populations studied by Fujiya (1970) had
“optimal” salinity tolerance below 33 PSU and presumably therefore had a different shape to their
tolerance norms than those seen here.
In a number of marine invertebrates, eggs are more vulnerable to low salinities instantly following
fertilization rather than at fertilization per se; e.g. for the asteroid Luidia clathrata it is the initial
cleavages and not fertilization itself that is most sensitive to salinity (Hintz & Lawrence, 1994).
These observations are further supported by Pechenik et al. (2007) who suggest that the eggs may
be fertilized but unable to complete meiosis and further cleavage under low salinities. In addition,
Qui & Qian (1997) found that Hydroides elegans were unable to develop in salinities lower than 20
PSU – a result that Pechenik et al. (2007) suggest was a consequence of alterations in osmotic
concentration, affecting e.g. pronuclear fusion or the result of a higher concentration of dissolved
oxygen at lower salinities. In this study fertilization success was measured as the proportion of eggs
that were cleaving after 2 h at 20°C. Unlike echinoderms, bivalves do not display a clear
fertilization envelope that indicates successful fertilization (Fong et al., 1995), and therefore it is not
possible to say for sure if the low fertilization success observed here was due to failure to fertilize at
low salinities or if it was due to an inability of the zygote to undergo early embryogenesis. Although
it has been reported that oyster sperm (unknown species) are active down to 5 PSU (Clark, 1935; as
cited by Kinne, 1971; as cited by Pechenik et al., 2007), it is possible that sperm were relatively
inactive in the lower salinities used here. This could be addressed by studying sperm motility as
well as sperm and egg physiology separately at different salinities.
In all cases, it is fundamentally important that an egg is fertilized by one sperm only. The
fertilization of an egg by more than sperm – polyspermy – is usually lethal, and consequently many
mechanisms to block polyspermy have evolved (Kosman & Levitan 2014). Low salinities have
been shown to influence this polyspermy block, and have been associated with increased
polyspermy. For example in the alga Fucus vesiculosus (Serraõ et al. 1999), the polyspermy block
breaks down in low salinities. In many marine organisms the polyspermy block acts through
depolarization of the egg membrane, which stops the entry of more than one sperm. This
depolarization is caused by Sodium (Na+) influx. Sodium has been demonstrated to be important for
both fertilization (for example it’s essential for the formation of a fertilization envelope), and
embryogenesis in echinoids (Schuel et al., 1982). Similar Na+-dependent polysperm-block
!20
mechanisms are active in C. gigas, (Togo & Morisawa, 1999), and although oysters lack
fertilization envelopes, supernumerary sperm that penetrate the vitelline coat of the egg do not
penetrate the egg membrane and form a fertilization cone (Togo & Morisawa, 1999). In the absence
of specific data on the effects of salinity on polyspermy in C. gigas, it is not possible to determine
whether lower salinities result in a lower fertilization success or in a lower cleavage of fertilized
eggs as a result of polyspermy – as is the case for the free-spawning polychaete Hydroides elegans
(Pechenik et al. 2007). The lack of an obvious fertilization envelope in oysters means that observing
cleavage is the most practical way to determine fertilization success (Fong et al., 1995). However,
events in the early cleavages of the fertilized egg are controlled by the maternal genome, before the
zygotic genome takes over continued development (Tadroz and Lipshitz, 2009). Consequently, in
some species, polyspermic eggs may indeed cleave and appear to demonstrate normal development
for the first few hours. Therefore it can not be ruled out that some of the eggs that were observed to
cleave in the experiments described here, were in fact polyspermic. After initial cleavages, however,
the continued development of the embryo is dependent on the zygotic genome – a process that
cannot proceed if the embryo is polyspermic. Thus, assessing the proportion of eggs that
successfully developed to D-stage larvae (after 26h) gets around this problem and provides an
integrated measure of the effects of salinity on fertilization (potentially including polyspermy),
embryogenesis and early larval development.
4.2 Larval development (D-stage)
As for fertilization success, successful development to D-stage larvae was also strongly and
significantly affected by salinity. This is in contrast to earlier work that has claimed salinity has a
relatively modest effect on larval development of C. gigas compared to other factors (Carlson 1982;
Neudecker 1985; as cited by His et al., 1989; but see Robert & His, 1985).
Once again, for development to D-stage there was a highly significant interaction between the
effects of salinity and population, suggesting that the two populations responded differently to
salinity. The Guernsey population had the most successful development at the highest salinity level
(33 PSU), slightly lower at 28 PSU and near-zero or zero at the three lowest salinities. In contrast,
the Svallhagen population showed a gradual decrease in development as salinity decreased,
however, at salinities below 18 PSU no D-larvae were observed. Even at 18 PSU, median
developmental success was zero, although there was substantial variance in response (Figure 6)
!21
indicating that some families from the Svallhagen population had relatively high developmental
success at 18 PSU. It should be remembered that these results were obtained from only 6
individuals from Guernsey and 12 from Svallhagen, and consequently further sampling and
experimentation may change the patterns observed here. Nonetheless, these results suggest that
salinity tolerance may not be species-specific but population-specific; the Svallhagen population
may have already been selected for development at lower salinities, and the presence of substantial
variability among families in responses to 18 PSU indicate that further selection may be possible.
Similar salinity tolerance norms have been found in other studies: in the Mangrove oyster
(Crassostrea rhizophorae) embryonic development to normal D-larvae was most successful in
salinities between 25 and 37 PSU but normal D-larvae were scarce at salinities lower than 16 PSU
(Dos Santos & Nascimento, 1985).
Other workers have reported a variety of difficulties in experiments with C. gigas fertilization. For
example, developmental abnormalities arising from a delay of fertilization after extraction of
gametes have been reported (Helm & Millican, 1977; Dos Santos & Nascimento, 1985). This was
not evident in this study, and although we did not test the longevity of eggs and sperm (all were
used within a few hours of collection) it has been reported that eggs (Fujiya, 1970) as well as
spermatozoa (Sato, 1967; as cited by Fujiya, 1970) can survive for at least 15 hours outside the
gonads.
Egg density has also been shown to play an important role for larval development (Song et al.,
2009). In methodological experiments different egg densities, ranging from 200 to 1600/mL, were
tested here. The results showed no effect of egg concentration (Section 2.6), findings that are in
agreement with those of Stiles and Longwell (1973). Others have, however, suggested that higher
concentrations of eggs would have negative impacts on reproduction of the mollusc Pecten
maximus due to oxygen depletion and accumulation of waste products (Gruffydd and Beaumont,
1970). While this might be a cause for concern, it has been found that C. gigas (Helm & Millican,
1977) can successfully yield almost three times as many normal D-larvae as C. rhizophorae (Dos
Santos & Nascimento, 1985) in a concentration of 1000 eggs/mL, suggesting that C. gigas are
extremely density tolerant.
4.3 Adaptation or Plasticity?
!22
As noted above, the significant interaction between population and salinity that was found in the
analyses, indicates that these two populations have different responses to different salinities.
For both populations, fertilization and developmental success to D-stage seem to reflect the salinity
of the waters where the populations originated. Although the sample sizes were small, the results
suggest that the recently established Svallhagen population has acquired the ability to reproduce at
(lower) salinity levels of the Swedish west coast – levels at which the Guernsey population can
successfully fertilize, but not develop. Different mechanisms for coping with changing
environments may explain this pattern. Natural selection in invasive species acts to result in a
phenotype that is a strong competitor and competent to establish in new environments (Prentis et
al., 2008). Genetic selection of traits more fit for the different conditions is an important
characteristic of invading species. At the same time, organisms may be selected for mechanisms that
enable them to better cope with different conditions, i.e. “phenotypic plasticity” – the ability to
adapt to changing demands by adjusting the phenotypic expression of a genotype (Pigliucci, 2001).
If phenotypes of C. gigas are indeed plastic, then it is reasonable to expect that the ~5 months
during which Svallhagen oysters were conditioned at Ostrea AB on Koster would have had an
overriding influence on their tolerance norms. With the exception of the conditioning temperature,
these conditions (salinity and pH) were almost identical to those of the Guernsey oysters (Section
2.1). Therefore it seems more likely that genetic differences, rather than phenotypic plasticity,
would explain the different salinity tolerance norms observed in these populations.
A number of studies (e.g. Beiras & His, 1995; His et al., 1997) have established that embryos and
larval development in C. gigas are not affected by salinity in the range 20-30 PSU, and suggest that
C. gigas would therefore be a good indicator of water quality in brackish as well as in marine
waters. This study however, suggests that salinity tolerance is not species-specific but populationspecific, and therefore more careful consideration of the origin of oysters is required before making
such statements. In addition, knowing the salinity tolerance norms would make it possible to predict
further spread of C. gigas under climate change. Predicting the future natural distribution and
potential range of C. gigas under climate change could be done with a correlative climate envelope
model (Strand & Lindegarth, 2014).
4.4 Sire and Dam effects
!23
The linear-mixed-models showed that there were no significant effects of dam, sire, or dam × sire
interaction. The dam effects were immensely smaller than the sire effects. This is unusual since the
sire effects are typically assumed to represent only additive genetic variance, whereas dam effects
are also affected by non-nuclear factors such as egg quality (Lynch & Walsh, 1998). The
experimental design used here allows for calculation of genetic variances from the variances
generated from the linear-mixed model. This had been an aim of this work, however the need to
undertake substantial methodological development (Section 2.5), meant that final sample sizes were
far too small to calculate reliable genetic variances (Appendix 2).
4.5 Conclusion
In conclusion, the results show that fertilization and larval development in C. gigas are highly
affected by salinity. This is most likely to be the result of genetic adaptation, although a long-term
phenotypic plasticity response cannot be entirely ruled out. Clarification of these patterns requires a
larger sample size from both populations. In addition, it would be of great interest to study the
plastic abilities of oysters from the two populations through common-garden experiments that
conditioned the oysters at different salinities. This would greatly help an investigation of genetic
variances and help to determine the strength of additive genetic (paternal), maternal, dominance,
and environmental effects (Appendix 2).
In a broader context, one of the largest threats to marine ecosystems is the establishment of invasive
species. In particular, reef-building species such as C. gigas can cause large modifications to native
ecosystems (Crooks, 2002). Therefore future research should include not only salinity, but also the
effects of other important climate-change variables such as temperature and pH, i.e. investigate the
effects of warming and ocean acidification on fertilization, embryogenesis, and larval development
of C. gigas.
!24
Acknowledgments
Thank you to my supervisor, professor Jon Havenhand, for accepting me as a student and for all the
advice and help during the lab work as well as writing process. Thank you to Joel White for support
when I first came to Tjärnö. I would also like to thank Laura Falkenberg for advice during the end
of my project and Martin Ogemark for providing me with filtered sea water and algae for my
oysters. Thank you to my family for supporting me throughout my project. And, thank you also to
the “White House” and everyone at Sven Lovén Centre for Marine Scienes at Tjärnö.
!25
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Appendix 1
Prepare FSW, dilutions, and dispense FSW to tubes
Male n
Prepare FSW, dilutions, and dispense FSW to tubes
Extract sperm, determine concentration and volume
needed (store on ice)
Male m
Extract sperm, determine concentration and volume
needed (store on ice)
Add 0.5mL egg suspension to each tube.
Male l
Extract sperm, determine concentration and volume
needed (store on ice)
Add 0.5mL egg suspension to each tube.
Time
t=-1
Add 0.5mL egg suspension to each tube.
Prepare FSW, dilutions, and dispense FSW to tubes
t=-1
Add 1.42 ml FW to 29‰ - 14‰
Prior
t=-0:48
Add 1.48 ml FW to 24‰ - 14‰
Extract eggs from 3 females and put them in FSW
(34‰)
t=-0:36
Add 1.48 ml FW to 19‰ - 14‰
t=-2
t=-0:24
Add 1.48 ml FW to 14‰
Determine egg concentration to yield 5000/mL
(once/female) in total of 10mL FSW
t=-0:12
Add xµL sperm to each tube
After 2 min add xµL sperm to each tube
After 4 min add 2xµL sperm to each tube
After 12 min centrifuge for 5min, 20°C, 2000rcf
Extract 9mL from each tube (not the pellet)
Add 6.5mL treatment water to each tube
Extract 2.5mL into petri dishes
Place in incubator (20°C) for 2h
Add 1.48 ml FW to 24‰ - 14‰
Add 1.42 ml FW to 29‰ - 14‰
t=0
t=0:12
t=0:24
Time
t=0:36
t=1
t=1:12
Start male e
Male l
Male m
Add 1.48 ml FW to 19‰ - 14‰
Add 1.48 ml FW to 14‰
Add xµL sperm to each tube
After 2 min add xµL sperm to each tube
After 4 min add 2xµL sperm to each tube
After 12 min centrifuge for 5min, 20°C, 2000rcf
Extract 9mL from each tube (not the pellet)
Add 6.5mL treatment water to each tube
Extract 2.5mL into petri dishes
Male n
Add 1.42 ml FW to 29‰ - 14‰
Add 1.48 ml FW to 24‰ - 14‰
Place in incubator (20°C) for 2h
t=1:24
Add 1.48 ml FW to 19‰ - 14‰
After 12 min centrifuge for 5min, 20°C, 2000rcf
After 4 min add 2xµL sperm to each tube
After 2 min add xµL sperm to each tube
Add xµL sperm to each tube
t=1:36
Start male f
Add 1.48 ml FW to 14‰
Take overview of each dish and 3*5x photos
t=1:48
t=2
t=2:12
Extract 9mL from each tube (not the pellet)
Add 6.5mL treatment water to each tube
Extract 2.5mL into petri dishes
Time
t=3
t=4
t=26
t=27
t=28
Male l
Add 0.5mL of 95% ethanol to each dish
Count the number of D-stage larvae in each dish
Male m
Take overview photo of each dish and 3*5x photos
Add 0.5mL of 95% ethanol to each dish
Count the number of D-stage larvae in each dish
Male n
Place in incubator (20°C) for 2h
Take overview photo of each dish and 3*5x photos
Add 0.5mL of 95% ethanol to each dish
Count the number of D-stage larvae in each dish
Time
34‰
29‰
24‰
5.12ml FSW
19‰
3.64ml FSW
14‰
1.42ml FFW
6.60ml FSW
1.42ml FFW
1.48ml FFW
8.08ml FSW
1.42ml FFW
1.48ml FFW
9.5ml FSW
1.42ml FFW
1.48ml FFW
1.48ml FFW
1.48ml FFW
1.48ml FFW
0:0
0:12
0:24
0:36
0:48
Appendix 2
Quantitative genetic analyses can be calculated using the variances and the residual obtained from the linear mixed model in R studio. The sample size
for this project was to low to generate any reliable genetic variances. See table below for values and calculations. (Laurila et al., 2002).
VA = Additive genetic variance
Vm = Maternal variance
VD = Dominance
Ve = Environmental variance
h2 = Heritabilities
0.0245
0.126
0.109
0.00
0.00
0.00
0.0198
0.00935
0.0256
0.00405
0.00
0.00
0.00
0.00
0.914
0.953
0.831
0.964
h2 (Va/Vtot)
0.00
0.00
0.00
0.00
m2 (Vm/Vtot)
m2 = Maternal effect coefficient
0.001
0.00405
0.190
0.00
Va (4 x Sire) Vm (Dam-Sire) Vd (4 x Sire x Dam) Ve (res-0.5Va-0.75Vd)
Overall 0.0272 0.000946
0.006
0.00234
0.211
Sire x Dam Residual
0.0314 0.00214
0.002
0.00496
Dam
33
0.0476 0.000236
0.005
Sire
28
0.0527 0.0000322
Salinity
23
na
0.00
na
0.728
na
0.00
na
0.0700
na
0.00
na
0.186
na
0.01740
na
0.017
na
0.0465 0.00104
na
18
13