This document summarizes a project report on the effects of anthropogenic noise pollution on marine species physiology and behavior. It introduces the need to understand noise pollution impacts to help create effective legislation protecting marine environments under criteria like the EU Marine Strategy Framework Directive. While chemical pollution is well-studied, noise pollution effects are less understood. The document reviews noise propagation properties in water and potential impacts on various taxa to motivate further research on a commercially important shellfish, Mytilus Edulis.

1. EDINBURGH NAPIER UNIVERSITY
PROJECT REPORT: 2016
MSC WILDLIFE BIOLOGY AND CONSERVATION
David Bryson
40179101
The Effects of Anthropogenic Noise on Aspects of
Physiology and Behavioural Ecology in a Model Marine
Species Mytilus Edulis

2. Introduction
Human activity has greatly altered the natural acoustic background of the world, in both terrestrial
and aquatic environments. Organisms now face disturbance from the noise created by
anthropogenic activity alongside other damaging but more well-known aspects of human behaviour,
such as habitat degradation, chemical pollution, and habitat fragmentation (Goines & Hagler, 2007).
A lack of current understanding of harmful effects of anthropogenic noise makes implementing
appropriate legislation impossible; however with increasing human population and need for
expansion, anthropogenic noise pollution is a problem that is only going to get worse in both the
terrestrial environment and the aquatic- therefore gathering as much data as possible to help make
informed decisions in legislation is key.
The EU Marine Strategy Framework Directive (MSFD) is a framework formally introduced in 2008
which aims to manage human activities and promote sustainable use of marine goods and services.
The overall objective is to achieve a “Good Environmental Status” in all European waters by 2020.
“Good Environmental Status” (or GES) is defined by the Marine Directive as “The environmental
status of marine waters where these provide ecologically diverse and dynamic oceans and seas
which are clean, healthy and productive”. (European Commission, 2008). The MSFD became part of
UK legislation in June 2010. For UK waters to achieve GES 11 separate criteria have to be met:
1. Maintenance of biological diversity.
2. Exotic species introduced by humans do not significantly alter the natural marine
environment.
3. Populations of fish and shellfish currently exploited by humans are maintained at safe levels
with demographics indicative of a healthy population for each species.
4. All elements of food webs in marine ecosystems are maintained at normal abundance and
diversity, and are at levels that ensure long-term longevity.
5. Human-introduced eutrophication is minimised, in particular the negative effects associated
with eutrophication including loss of abundance and diversity.
6. Benthic ecosystems are not significantly altered by human activities.
7. Altering the hydrology of EU marine systems does not significantly negatively affect marine
ecosystems.
8. Organic and inorganic contaminants do not reach levels at which they become harmful
pollutants to marine species.
9. Contaminants in marine species consumed by humans do not reach levels at which they
pose any health risks to humans.

3. 10. Litter, organic waste, and other forms of human waste do not cause harm to coastal and
marine environments.
11. Introduction of extra energy into the marine environment, in particular underwater noise
produced by human activities, does not adversely affect the marine environment.
Of all of these criteria, the final criteria is the least documented within literature and least
understood- necessitating the need for research into the harmful effects noise pollution can have on
the marine environment. Will appropriate knowledge and evidence, proper legislation can be
implemented to protect marine species and promote sustainable use of marine goods. Research into
noise pollution would also be of benefit to terrestrial environments, but would be of particular
benefit to aquaculture- the UK, in particular Scotland, is one of the largest producers of farmed fish
and shellfish in the world (Bostock et al., 2010). All along the west coast of Scotland there are many
fish and shellfish farms, and any research which benefits production will be of use to these farms.
Noise pollution can loosely be defined as any anthropogenically-produced sound which differs
significantly in its attributes from background acoustic noise and is at sufficient levels that it
negatively affects the physiology and behaviour of organisms subject to it- this can range from
human activity such as traffic, to the arrival of an invasive, particularly vocal species, like many
songbirds due to human activity (Kumschick & Nentwig, 2010). These negative effects can manifest
themselves in many different ways- oxidative stress, and reduced fecundity for example (Demirel et
al., 2009, Schroeder et al., 2012). Noise pollution is most commonly associated with humans in large
cities and patients in hospitals- where constant exposure to noise can lead to adverse effects on
human health, such as hampering recovery times for patients in hospitals (Stansfeld & Matheson,
2003). Within the natural environment, anthropogenically-produced sound can be severely
detrimental to many species. For example, Francis et al. (2009) found that noise pollution by human
activity severely negatively affected bird nest distributions throughout woodlands in the state of
New Mexico, USA. Anthropogenically-produced sound has consistently been shown to alter
behavioural ecology in birds (Francis et al., 2011, Patricelli & Blickley, 2006).
While chemical pollution in nature is well documented in scientific literature, and is often at the
forefront of popular science (for example major oil spills such as the recent major spill in the Gulf of
Mexico in April 2010), noise pollution is by comparison poorly documented, and rarely discussed by
the media. The vast array of anthropogenically-produced sound varies enormously, from engine
noise to controlled demolitions. This leaves a wide spectrum of sound waves, intensities and
volumes which can have an array of effects on different species, in a similar way that the vast array
of chemicals used in anthropogenic processes have differing effects on different organisms. Within

4. human biology, research has been dedicated to noise pollution in cities and hospitals (Topf, 2000,
Zannin et al., 2002), but if we were to compare the vast array of data on human responses to noise
pollution and compare it to the quantity of data currently available on noise pollution effects on
other taxa, and compare this to current understandings of the varying effects of the vast array of
anthropogenically-produced chemical pollutants, there is a clear gap in knowledge and
understanding. To understand the threats that marine life faces to noise pollution, understanding of
how sound movement differs in water to air is first required.
Sound travels much faster in water than through air- the speed of sound through gases at a
temperature of 200
c at approximately 1,230 km/h, or approximately 340 metres per second. This can
be calculated using the following formula (Cramer, 1993):
Vsound= √(γRT)/M
Where:
γ is the adiabatic constant (the heat capacity of the particular gas, in the case of air this is equal to
1.4).
R is the universal gas constant, equal to 8.314 J mol-1
K-1
.
T is temperature.
M is the molecular mass of the gas- for dry air this is 28.95g/mol.
As water is a denser medium than air, molecules are closer together. As a result sound moves much
faster through the denser medium, and sound travels even faster through solid objects. The speed of
sound through seawater is dependent on the depth of the water at which measurement is taken
(pressure increases with depth, and with increasing pressure molecules are closer together
(Mackenzie, 1981)), and the temperature of the water (with increasing temperatures, molecules
move faster due to the fact that they now contain more energy, and therefore interact with each
other more frequently causing sound waves to travel through the water faster). Because
temperature and pressure are not uniform throughout the oceans, the speed at which sound travels
through the oceans can vary greatly (Mackenzie, 1981). To determine the speed at which sound can
travel through water, the following equation was used:

5. C(D,S,T)=
1448.96 + 4.591T – 5.304 x 10-2
T2
+ 2.374 x 10-4
T-3
+ 1.304 (S-35) + 1.630 x 10-2
D + 1.675 x 10-7
D2
+
1.025 x 10-2
T(S – 35) – 7.139 x 10-13
TD3
Where:
T= temperature (0
c)
S= salinity (ppt)
D= depth (m)
Mackenzie’s equation can be used to measure the speed of sound within temperatures of 2 – 300
c,
salinities of 25 – 40 parts per thousand, and between depths of 0 – 8000m. This equation allows for
a vast array of experimental noise exposure treatments to be undertaken, capable of mimicking the
vast majority of the marine environment. At standard seawater salinity of 35 ppm, a depth of 0m,
and a temperature of 50
c sound travels at a speed of 1496.14m/s, or 5386.1 km/h. Sound travels
faster through seawater than freshwater- as it is a denser liquid than freshwater (Rogers & Cox,
1988). Sound travels in longitudinal waves of pressure which travel through matter- without matter
there is no sound. Every sound wave has a frequency- measured in Hertz. The higher the frequency,
the higher in pitch the sound. The strength of a sound wave determines its amplitude- how loud the
noise is.
Within the marine environment, noise pollution primarily comes in the form of activities such as
shipping lanes, which produce low frequency noise (10 – 500 Hertz) in the water column. Cargo ships
are typically very large vessels-some of the largest ever created, which subsuquently require very
large engines- as a result the noise generated by them is significant. For example, the Wärtsilä-Sulzer
RTA96-C diesel engine produced in Finland, the largest in production, weighs over 2,000 tonnes and
can produce 107,390 hp. An engine of this size can easily produce sound of 130dB and higher. Within
an island country such as the United Kingdom, where shipping is one of the main ways in which
cargo and people are transported (alongside fishing in the rich waters of the North Sea and the great
number of recreational vessels), there is potentially a very large source of noise pollution from ship
engines alone, without even mentioning oil rigs in the North Sea and pile-driving.
Research into noise pollution on terrestrial environments is well-documented, particularly birds
(Rheindt, 2003, Francis et al., 2009). The effects of noise pollution on birds has also shown to affect
ecosystem services they provide, such as increasing pollination by hummingbirds but negatively
affecting seed dispersal (Francis & Kleist, 2012). Within aquatic environments, significant research

6. has been dedicated to higher organisms such as whales and dolphins (Rossi-Santos, 2014, Knight,
2013), and noise pollution is increasing in recognition by governmental bodies (Dolman & Jasny,
2015, McCarthy, 2007). In fish, noise pollution can disrupt communication between fish (Holt &
Johnston, 2015), and can elicit stress responses as has been performed ex-situ using boat engine
noise (Celi et al., 2016). Information like this is useful to the aquaculture industry, where all potential
sources of stress which will lower meat quality in fish and bivalves need to be addressed to maximise
profits, and adhere to animal welfare laws.
By comparison, relatively little research has been dedicated to marine invertebrates- this can be
partly attributed to the enormous diversity of invertebrates within marine environments. Over
170,000 species have been described, however current estimates predict that there could be
anything from 700,000 to 1,000,000 eukaryotic species within the marine environment (Appeltans et
al., 2012). The limited research available on noise pollution effects on marine invertebrates is also
partly due to the current limited understanding of how marine invertebrates perceive and interpret
sound (Budelmann, 2006). As previously mentioned, sound through water causes particle motion- it
is this that many marine invertebrates interpret as sound through the use of special hairs designed
to detect particle motion, as is the case in many crustaceans such as shrimp and crabs (Lovell et al.,
2005).
Filiciotto et al. (2014) investigated behavioural and biochemical responses indicative of stress in
Palinurus elephas, a species of spiny lobster, in response to boat noise pollution ex-situ. The lobsters
were exposed to random sequences of boat engine recordings and their locomotory behaviour
recorded for analysis. Their hemolymph was also analysed to determine changes in biochemistry and
using chemical bioindicators located within the hemolymph, it was determined that the effect of
noise pollution was increasing stress levels within the lobsters through increased movement, and an
increase of glucose and total proteins within the hemolymph. Wale et al. (2013) examined the role
anthropogenic noise exposure had on the behaviour of the Common Shore Crab Carcinus maenas-
repeated noise exposure negatively affected the crabs ability to forage and elicit antipredatory
behaviour (in the form of retreating to shelter). Additionally, Wale et al. (2013) examined
physiological responses to noise exposure in C. maenas in another study. Greater metabolic rates
were noticed in crabs exposed to ship noise playback, which could be an indicator of stress due to
noise. This was more pronounced in larger, heavier crabs than smaller crabs, indicating that this
could be size-dependent.

7. The target species used within this investigation, Mytilus edulis, is commonly known as the Blue
Mussel and is very common along coastal regions of the UK. For example, in the town of
Musselburgh where the specimens for this investigation were sourced from, at low tide huge beds of
mussels containing likely hundreds of thousands of specimens can be seen. M. edulis is part of the
Bivalvia class within the Mollusca phylum, which comprises of over 9,000 species (McMahon &
Bogan, 1991). The blue mussel can be found across the northern hemisphere, as far north as Iceland,
and as far south as western Africa. M. edulis has been extensively studied, and is considered a model
marine species for this reason. This thesis aims to contribute to growing currently unpublished data
investigating other negative effects of noise exposure on M. edulis, such as oxidative stress. M.
edulis is capable of tolerating a variety of factors, and is adept at surviving within intertidal zones.
Adult M. edulis generally reach shell lengths of up to 80mm- in optimal conditions this can be
reached within only a few years, but in less favourable conditions such as the high intertidal zone
where individuals may only be submerged for a few hours a day growth can take up to 20 years
(Seed & Suchanek, 1992). They generally favour depths of less than 10m, and form dense
aggregates, which can be seen when placed into a lab environment (they actively group together to
form beds). When viewing mussel beds ex-situ, vast fields of beds containing many thousands of
individuals can be seen. To aggregate together in these clusters, they use a generic foot that all
members of the Mollusca phylum have to move themselves, and use a material called byssus, a
bundle of filaments (which resembles silk threads), produced in a gland near the foot, to anchor
themselves in place, to rocks and other mussels. Byssal threads have a secondary role- it is also used
to ward off predators, such as crabs and predatory gastropods (Leonard et al., 1999). M. edulis is a
filter feeder and will feed on a variety of organisms, including many species of algae, making it a
relatively easy animal to care for within a laboratory environment. They will also filter detritus from
the water, and generally require fairly low concentrations of algae in the water to open their shells
and begin filter feeding (Riisgard et al., 1981).
Due to the amount of research that has been dedicated to M. edulis, partially due to its relative
abundance and hardiness, M. edulis is considered a model marine species (Wootton et al., 2003). M.
edulis is also an economically important species to Scotland and the rest of the UK- it is commonly
farmed along the west coast of Scotland, where the water quality is very high and free of harmful
pollutants, in addition to having many sheltered enclaves which protect from the notoriously
changeable Scottish weather. In 2008, mussel production in farms from Scotland was estimated at
5,800 tonnes, and this is predicted to continue to increase over the coming years as mussels become
a more popular food choice in Scotland (Scott et al., 2010, Hemroth et al., 2002). In addition to its
economic value, M. edulis is an important source of food for a variety of organisms. At its larval

8. stage, where it is planktonic, it is preyed upon by juvenile fish and jellyfish. When it reaches
adulthood, the mussel is often preyed upon by sea stars and members of the Laridae family (gulls) in
birds. Smaller mussels are also preyed upon by Nucella lapillus, the dog whelk (Petraitis, 1987).
As previously mentioned, M. edulis is a filter feeder. It feeds by drawing in water through a siphon,
where it is then pulled into the branchial chamber, and labial palps isolate and push the food into
the mouth of the organism and digestion begins. Waste water is then pushed through another
siphon, known as the excurrent siphon (Dral, 1967). The matter is digested, and matter which cannot
be used as food such as sand particles and other detritus is covered in mucus and passed through
the digestive system, and leaves in the form of pseudofaeces (Foster-Smith, 1975). M. edulis uptakes
oxygen through a similar method- water is passed through the gills, and oxygen removed while
waste products added and filtered back out the gill. As M. edulis is often present in intertidal zones,
it only respires when submerged, and valves remain closed when the tide goes out and they are
exposed to air. M. edulis is not only a model marine species but also an important member of
intertidal ecosystems. It is an opportunistic species, which will colonise new areas rapidly, and
providing optimal conditions (such as spending most of the day submerged, and ideal temperatures)
will quickly reach sexual maturity and reproduce (Suchanek, 1978). In intertidal flats, they will often
be the dominant species owing partially to their hardiness and quick reproductive cycle (Petraitis,
1995).
Despite its status as a model marine species however, very little research has been undertaken to
investigate noise pollution effects in M. edulis. The only research into noise exposure effects on M.
edulis has shown generally negative effects on the animals. Roberts et al (2015) investigated the
sensitivity of M. edulis to substrate-borne vibrations, by creating exposure to vibrations in-situ. A
range of vibrations through the water at varying intensities from 5 Hz to 410 Hz, mimicking pile-
driving activities within the seabed were used and valve closure used as an indicator of negative
behavioural response to vibration, with thresholds for negative behaviour in M. edulis found to
range from 0.06 to 0.55 m s-2
acceleration. The scientists involved concluded that repeated exposure
to high-intensity substrate-borne vibrations caused by anthropogenic noise was likely to negatively
affect the overall fitness of individual mussels and the beds that they form, by interrupting their
normal daily valve movement. This in turn could have knock-on effects to other organisms, as M.
edulis are an important food source for many marine organisms and seabirds (Petraitis, 1987). De
Soto et al. (2013) examined noise exposure on a similar species belonging to the bivalve class, Pecten
novaezealandiae, also known as the New Zealand Scallop, in its larval form. Their research found
that noise exposure at larval stages caused body malformations, and also slowed down the rate of
development, leaving larvae even more vulnerable to predators such as fish. Based on their similar

9. morphology it could be inferred that similar effects are likely to be seen in M. edulis, however
dedicated research will confirm this.
As an indicator of behavioural response to a stimulus, feeding rate is useful (Nielsen, 1999, Ghaffar
et al., 2011). An animal that is not feeding while being exposed to a potentially harmful stimuli (in
this instance noise exposure) is clearly showing it is being subjected to stressful conditions. Over an
extended period of time this is likely to negatively impact the animal’s fitness and likelihood of
survival. Alongside behavioural responses, changes in respiratory rate in response to harmful stimuli
can also prove as useful indicators of a physiological response- In the instance of M. edulis this could
appear in the form of reduced oxygen intake due to closing of valves to protect from noise exposure.
The overall aim of this investigation is to add to the growing data highlighting the negative effects
anthropogenic noise exposure is having on a model marine invertebrate- in the hopes that it may
create awareness of noise pollution effects on smaller species lower in the food chain, and to
prompt change in legislation to protect not only larger marine animals such as cetaceans, which
have been well-documented in terms of noise pollution effects, but the keystone species close to the
base of the marine food webs.
Currently, additional work is being performed at Edinburgh Napier University on the effects of
anthropogenic noise exposure on M. edulis. Noise exposure has shown to compromise DNA
structure at singular cell level in mussels, and thiobarbituric acid-reactive substances (TBARS) were
found to have formed in individual cells within the hemolymph (the mollusca equivalent of blood)
and gills as a by-product of lipid peroxidation, hinting that noise playback was causing oxidative
stress in mussels subjected to treatment. Further oxidative stress experiments, such as O2
-
levels in
cells, Reactive Oxygen Species (ROS) (reactive chemicals containing oxygen that have been subjected
to measurement or a particular chemical process (Bayr, 2005)), and Leptoperoxidase production
however were found to be inconclusive thus far. Further experimental work is planned to be
undertaken within the near future- investigating the effect of noise exposure on frequency of valve
movement, which is an indicator of feeding and respiration (Kramer et al., 1989), and effect length
and variability over longer periods of time.
While the overall aim of current anthropogenic noise exposure research on M. edulis is to determine
all aspects of harmful effects noise pollution can have on this model marine invertebrate species,
this thesis itself aims to investigate whether acute noise exposure affects an aspect of physiology
and an aspect of behavioural ecology in M. edulis- does acute noise exposure affect algal clearance
rate? Similarly, does acute noise exposure also impact the respiratory rate of M. edulis? For the algal
clearance rate experiment, the null hypothesis is that there will be no significant change in feeding

10. rate between mussels exposed to noise exposure against mussels not exposed to noise exposure,
with the alternative hypothesis stating that there will be a significant negative change in feeding rate
in mussels subjected to acute noise exposure. In the respiratory rate experiment, the null hypothesis
is that no significant change in oxygen in consumption will occur between mussels subjected to noise
exposure and those not exposed to noise, while the alternative hypothesis is that there will be a
significant negative decrease in oxygen consumption in mussels subjected to acute noise exposure
against those not subjected to noise exposure. The methodology used to investigate these
hypotheses are as follows:
Materials and Methods
Algal Clearance Experiment
All experiments were performed within the Sighthill campus of Edinburgh Napier University. Each
tank used had a capacity of 138.24l and was filled with approximately 116.64l of seawater.
Temperature was kept at a constant of 120
c, and salinity at a constant of 35ppt, meaning through
the water sound could travel at a speed of 1496.12m/s using Mackenzie’s equation (pressure was
assumed not to have changed). All other water qualities such as nitrites, silicates, and magnesium
were regularly monitored and found to consistently be within normal bounds for seawater (the
water qualities can be found within the appendix of this paper). The M. edulis used in this
investigation were all adults, obtained from the town of Musselburgh, East Lothian, on the morning
of 20th
May 2016 during low tide (approximately 7.30am).

11. Figure 1: Image of the approximate area where the mussels used in this experiment were collected from. The areas in black
are mussel beds. Taken from Google Maps on 16/07/16.
In order to reduce the variability of feeding rates among individual mussels, similarly sized mussels
were collected- this also helped to account for any differences in feeding rates due to age of the
organism. In total, 350 mussels were collected with 250 of these specimens being used for
experimentation. After being thoroughly cleaned by removing any endoparasites, in particular
barnacles, and immersion through clean freshwater to remove any trace contaminants they were
left to acclimatise to a lab environment for two weeks in a large aerated tank with constant flow-
through of sterile and filtered seawater, at the previously mentioned temperature of 120
c and
salinity of 35ppt. They were fed with dead Tetraselmis suecica, bought in high concentrate liquid
form (1.5 billion cells per ml) from www.ZMsystems.co.uk , every 24 hours. Tetraselmis suecica is a
marine green algae, commonly used as food-stock within aquaculture, with a length of up to 10ųm
and a width of up to 14ųm. It is easily visible under a light microscope and mostly contains
Chlorophyll-A, meaning it can be used in spectrophotometry at suitably high concentrations.

12. Figure 2: Microscope image of Tetraselmis suecica within a water sample. Obtained from www.youtube.com on 20/07/16.
Previous experiments involving feeding within M. edulis and closely-related species have utilised T.
suecicca as a food source (Nielsen & Strømgren, 1991, Wong & Levinton, 2004, Vasconcelos, 1995),
validating their suitability for this investigation. Dead T. suecica were used, in order to prevent
changes in algal concentration in the water due to algae reproducing, which could bias results.
Preliminary testing was performed to determine how long noise exposure should run for,
appropriate algal concentrations within the water, and appropriate quantification. 25 mussels were
acclimated in a small tank containing 10l of water for 24 hours before the water was inoculated with
Tetraselmis to make the cell concentration within the water 3000 cells/ml. 3 water samples were
taken every hour and all mussels monitored to determine when their valves closed (an indicator of
when they stopped feeding). After 4 hours, all mussels had closed their valves and subsequently
stopped feeding. The results of this preliminary testing can be found in the results section. 3000
cells/ml was utilised due to recommendations from Riisgȧrd et al. (1981), who concluded that algal
clearance rate in Mytilus edulis is optimal at cell concentrations between 1500-3000 cells/ml In
addition, spectrophotometry was run to determine if this would be a suitable method of
quantification- however the absorbance rates produced by spectrophotometry at a range of
concentrations from 300 cells/ml up to 30000 cells/ml were found to be too low for statistical
analysis. At such low absorbance rates variation due to marks on the cuvettes used could not be
ruled out, therefore this method was abandoned. In addition, mussels exposed to concentrations as
high as 30000 cells/ml were found to not consume enough cells within 3 hours to produce tangible
differences in absorbency rates.

13. Following acclimation, the mussels were divided into 10 groups of 25, with 5 groups being subject to
noise exposure treatment and the other 5 groups used in a control experiment (n=125 for each
treatment). They were starved 48 hours prior to treatment, and 24 hours prior to treatment were
moved to test tanks. The mussels were placed on platforms made of old crab cages (to allow any
pseudofaeces to fall to the tank floor) within a small tank with a volume of 10.8l. This small tank was
then placed on a platform 5cm tall within the large tank.
The test tank was inoculated with T. suecica at T0 to make the cell concentration within the water
3000 cells/ml (as Riisgȧrd et al. (1981) suggested in their paper regarding optimal cell density for
mussel feeding rates). Water samples were taken at the beginning of the experiment (T=0), halfway
through (T=1.5), and at the end of the experiment (T=3). 5 samples of 1ml were taken at each time,
following vigorous stirring of the water for 10 second using a glass rod to spread out the algae within
the water as best as possible. The mussels were subjected to 3 hours of continuous underwater
recordings of boat engines simulating a busy harbour, randomly sequenced, at a maximum volume
of 135-140 dB (for comparison, this is above the human pain threshold for noise, which is around
125dB (Camp et al., 1962)). Sound was supplied through speakers located to the left side of the large
tank (see figure 3), and ship noise was played through an mp3 player containing a six-hour long
sequence of boats leaving and arriving into a busy harbour. Simultaneously, a control experiment
was set up with the exact same parameters as the noise treatment experiment but without any
noise playback.

14. Figure 3: Image taken on 21/06/16 of the M. edulis clearance rate experiment. The control experiment was set up
identically to this.
Following the experiment, each individual mussel was dried using paper towels, and its length and
weight noted. These specimens were then returned to a tank and later boiled to serve as feed for
other organisms in the laboratory, as they came from a contaminated site, and were unfit to be
returned to Musselburgh as per university regulations. The weights and lengths of each mussel in
each experiment were compared and no statistically significant difference could be found between
the noise and control mussels in each day (see the appendix for all statistical tests performed on
weight and length).
Each individual 1ml sample was transferred on to a glass Sedgewick-Rafter counting cell, which
contains a grid 50mm x 20mm (figure 4).

15. Figure 4: Image of a Sedgewick-Rafter counting cell used in this investigation.
Each square within the grid was assigned an x and y co-ordinate, with the bottom-left square being
co-ordinates x1 y1, and using a random number generator 5 random co-ordinates were selected for
analysis within each sample. The counting cell was viewed under an optical microscope and images
were taken using CellSens, a microscope imaging software program, for later analysis. To further
reduce bias during data analysis, each image was assigned a random 6-digit number so that each
image was analysed without knowledge of what treatment the water came from or at what time.
However, during data analysis, it became apparent that it was very easy to differentiate between
samples and instantly tell where they had come from, so this concept was later abandoned. 750
images were taken in total. As the algae did not separate out uniformly through the liquid medium
on the Sedgewick-Rafter Counting Cell, images which had particularly high numbers of algae (>200)
in them were treated as outliers within the dataset and were not included in analysis.
Respiration Experiment
100 mussels were collected from Musselburgh at 9am (low tide) on 20th
June 2016, and left to
acclimate in the Edinburgh Napier University aqualab laboratory setting for two weeks identical to
the conditions the mussels from the algal clearance experiment experienced (120
c, salinity of 35ppt,
all other water qualities such as magnesium, silicates, etc. within normal seawater boundaries). As
with the algal clearance experiment, they were thoroughly cleaned of all epibionts and washed in
clean freshwater before being transferred to a seawater tank. They were fed on T. suecica daily, and
prior to experimentation were starved for 24 hours in order to prevent increased respiration rate
due to extra oxygen demand for digestion becoming a factor.

16. Mussels were tested individually, in watertight respiration chambers with a capacity of 200ml
topped with filtered, sterile seawater. The respiration chambers were kept in a large tank containing
approximately 116.24l of sterile seawater, which was isolated from the rest of the system for the
purpose of this experiment (to prevent small organisms such as bacteria entering the system and
tampering with oxygen consumption rates). Respiratory rate was measured by monitoring changes
in oxygen saturation within the water in the chamber using an oxygen sensor connected to the
computer program Presens 3, through the use of a Fibox 3 optical oxygen meter. Once Presens 3 was
hooked up to the respiration chamber with the mussel inside playback began for 2 hours. The same
ship noise playback equipment used in the algal clearance experiment was used in this experiment
for consistency. Presens 3 took measurements of oxygen saturation within the water every second
for the duration of the experiment, and measurements at T0, T1 and T2 were noted for each for
later analysis. And all mussels were measured and weighed following treatment.
The results of both experiments are as follows:

17. Results
Algal Clearance Experiment
Figure 5: Boxplot showing the mean, interquartile ranges and 95% confidence intervals for each experiment at time T0.
Figure 5 shows the average number of cells counted in each experiment for each treatment. A
general linear model to compare both experiments was performed and at the beginning of the
experiment as predicted there was found to be no significant difference between experiments
(F=0.716, Df 1, 8, P=0.422), and data was normally distributed (p=0.089). It was observed at the
beginning of playback in the noise treatment tank in all experiments mussels would immediately
retreat into their shells upon hearing the ship noise playback, while the control mussels would start
to feed on the recently-added algae to the water. The mussels were regularly monitored but not
interfered with, and at T1.5, 5 1ml samples were taken again:
Control Noise
3035404550
Average Cell Count in Each Experiment at Time T0
Treatment
AverageCellCount

18. Figure 6: Boxplot showing the mean, inter-quartile ranges and 95% confidence intervals for the averages of all samples
collected at T1.5.
At T1.5, it can be observed that the overall mean algal count has dropped between T0 and T1.5 in
the control experiment, while the noise experiment has only dropped slightly, meaning mussels are
eating but at a much reduced rate, or only a select number of the 25 mussels being subjected to
noise were choosing to feed. Visual inspection confirmed that many mussels in the noise treatment
still had their shells closed at T1.5. Although there is a difference between the control experiments
and the noise experiments at t1.5, it is not significant (F=1,393, df= 1,8, P=0.272). Again data was
found to be normally distributed (p=0.272).
Control Noise
152025303540
Average Cell Count in Each Experiment at Time T1.5
Treatment
AverageCellCount

19. Figure 7: Boxplot showing the mean, interquartile ranges and 95% confidence intervals between the average cell count in
both the noise and control treatments at T3, the end of the experiment. The circles denote outliers.
As can be seen in figure 7, there is a clear difference between the cell count in the control treatment
and the noise treatment experiments at T3. Statistical analysis shows that there is a significant
difference between the control and noise treatment experiments at T3 (F=7.929, df, 1,8, p=0.023).
Data was normally distributed again (p=0.432). As a result, the null hypothesis that there is no
significant difference in feeding rates between mussels exposed to ship noise playback and mussels
not exposed to ship noise playback after 3 hours of experimentation can be rejected, and the
alternate hypothesis that there is indeed a significant difference after 3 hours can be accepted.
When examining each experiment independently of each other a significant change can be seen over
3 hours within the control experiment:
Control Noise
510152025303540
Average Cell Count in Each Experiment at Time T3
Treatment
AverageCellCount

20. Figure 8: Average algal cell count observed change over time in the control experiment. The circle at T3 denotes an outlier.
Within the control experiment, there was found to be a significant change in algal cell count over 3
hours (F=28.884, df= 1,13, p=<0.001). A Tukey’s test of pairwise differences was performed, and
found that while there was a significant difference between times T0 and T3 (p=<0.001) and from
T1.5 to T3 (p=0.034), no significant difference was found between times T0 and T1.5 (p=0.093).
Within the Noise exposure experiments the results were different:
0 1.5 3
1020304050
Control
Time
Meanalgalcount

21. Figure 9: Average algal count change observed over time in the noise experiments. The circle denotes an outlier in the
dataset.
Within the noise experiments, no significant change in algal count was found over time (F=2.667,
df=2,12, p=0.110). A Tukey’s test of pairwise differences revealed no significant pairwise differences
between any of the three counts taken.
From the above data, it can be concluded with a significant amount of confidence that noise
exposure at 135dB negatively affects feeding rates within M. edulis when compared against a
control experiment lacking noise exposure.
Respiration Experiment
0 1.5 3
2530354045
Noise
Time (hours)
MeanAlgalCount

22. Discussion
Algal Clearance Experiment
The result show that acute noise exposure clearly impacts feeding behaviour in M. edulis. Numerous
obstacles had to be overcome to create this experiment- the first being a testable methodology free
of bias. Initially, a flow cytometer was planned to be used- which can count the number of
microalgae like Tetraselmis within a water sample following proper calibration (Stauber et al., 2002).
However, due to scheduling conflicts, a flow cytometer could not be used, and another method had
to be sought. As previously mentioned in the materials and methods section spectrophotometry was
considered, but by following the recommendations of Riisgard et al. (1981), who suggest using cell
concentrations of no greater than 3000 cells/ml, this proved to be too low for accurate
spectrophotometry readings. At such low levels of absorbance it would be impossible to determine
whether absorbance rates quantified by the spectrophotometer were coming from the presence of
chlorophyll A in the water sample (which were in turn coming from Tetraselmis in the water sample),
or whether absorbance rates were coming from other sources such as any remaining detritus and
debris still in the water, or marks and scratches on the cuvettes. If cell concentration within the
water were to be increased, not enough would be consumed by 25 mussels. After consulting existing
literature, using a Sedgewick-Rafter Counting Cell proved to be a time-consuming but more robust
method, which when combined with random number generators to take sub-samples within
samples allowed for minimum bias. Another significant advantage of this particular method is that it
is a low-cost, albeit time consuming method, which does not require specialist knowledge beyond
basic microscopy. It is hoped that this method can be further developed from here, and awareness
of its advantages made known, particularly to institutions who may not have the necessary funds to
purchase an expensive machine like a flow cytometer which may cost many thousands of pounds.
This method also does not require specialist training to use, so can be easily taught to volunteer
para-biologists as a way of further cutting costs.
As cell counting proved to be a very time-consuming activity, it proved necessary to take images
using CellSens for later analysis. This has a significant advantage attached to it- it meant more time
and care could be taken when counting, reducing the likelihood of miscounting due to time
pressure.
One interesting thing to notice is that at T1.5 there is no significant difference in algal counts
between the noise and control experiments (figure 6). While this is to be expected with the noise
experiment, where the mussels are not feeding and remaining shut due to acute noise, it raises
interesting questions as to why the control experiment subjects do not feed as much as expected

23. (figure 8). Further investigation into why mussels did not feed as much as expected in the control
experiments is required- it simply could be due to variation, or may be due to the presence of
humans- the answer is not currently clear.
The results correlate with previous literature- that noise exposure is overall detrimental to M. edulis,
both at physiological and behavioural levels. However, upon receiving the results of the algal
clearance experiment, this immediately creates more questions than it answers. While the results
clearly show that acute noise exposure over a short period of 3 hours negatively effects feeding
rates in M. edulis, how does this look over a longer space of time? For example, over days or even
weeks, as many mussels living in harbours experience? Do M. edulis eventually become acclimated
to loud noise exposure from anthropogenic sources? And if so, how long is this acclimation period?
In addition, the very high level of noise (minimum of 135 dB) used in the algal clearance experiment
is unlikely to be completely representative of the natural environment. Distance, type of engine, and
frequency of ship movement are all factors which will differ from harbour to harbour and the
position of the mussel on the seabed. Therefore this raises another question- do differing intensities
of noise exposure produce variable rates of feeding in M. edulis? At what point does anthropogenic
noise exposure cease to be a harmful stimuli to mussels? While this study shows that there is
significant difference in feeding rates between acute noise exposure and control experiments,
further investigation into noise intensity and duration should be undertaken to determine long-term
and intermediate effects on mussel behaviour. In addition, while this study has shown the harmful
effects of noise, it has shown no indication of the effects the particle motion caused by sound may
have. Setting up a similar experiment with the use of a device such as a Shaker table to mimic sound
pressure waves would help to determine what effects the pressure waves themselves may have. A
Shaker table is capable of mimicking sound pressure waves consistently- unlike the ship noise
playback recording used in this experiment, which may have shown variation due to different types
of engines with different sound frequencies, resulting in different strengths of pressure waves.
Similarly, this investigation and other work undertaken at Edinburgh Napier University has shown
the effects that anthropogenic noise can have on mussels which have reached maturity. However, is
this similarly the case in juveniles? And how does noise pollution influence development? M. edulis
undergoes metamorphic change over its life cycle- upon hatching it becomes a trochophore larva (a
free-swimming planktonic larva with cilia to aid locomotion). From here it metamorphasises into a
veliger larva, where it is still-free swimming but is developing a shell, before finally becoming mostly
sessile as an adult and forming beds with other members of its species in shallow waters (Suchanek,
1981). Further investigation to determine whether feeding rates are altered at juvenile stages who
are present in the water column could further the argument for protective legislation for bivalves if

24. similar results are found. As previously mentioned in the introduction section of this investigation,
De Soto et al. (2013) found that noise exposure had damaging effects on development in another
member of the bivalve class, Pecten novaezealandiae. By adapting the methodology they followed,
effects of noise on development of M. edulis alongside feeding rates could be determined.
Another factor to consider is that the mussels sourced for this investigation came from a
contaminated site- Musselburgh. The area has numerous contaminants, such as petro-chemicals and
mercury (McLusky & Martins, 1998). Mercury in particular is harmful to M. edulis (Géret et al., 2002)
and can easily bioaccumulate in animals higher in the food chain such as seabirds and fish (Monteiro
et al., 1996). The mussels used in this investigation were not tested in any way to determine how
much mercury was in their hemolymphs- therefore it is unknown if it had any effect on feeding and
respiratory rates. Further investigation involving mussels obtained from a non-contaminated site
(such as the west coast of Scotland) and then comparison involving noise against potentially
contaminated specimens would help identify if contaminants have had any effect on susceptibility to
noise exposure in M. edulis.
It is hoped that the data provided by this investigation, alongside the other work performed at
Edinburgh Napier University will be used to prompt change in Scottish legislation. A well-known
model species like M. edulis will hopefully garner attention, as the results obtained from current
investigation will likely be of interest to those invested in the growing mussel farming industry in
Scotland.
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