IIToday, by value and quantity, Atlantic salmon (Salmo salar) are by far the largest marine farmed commodity, with more than 2.4 million tonnes produced annually [7]. First intensively

I

II

Declarations by the Author

Statement of Originality

This thesis contains no material which has been accepted for a degree or diploma by the University or any other institution, except by way of background information and duly acknowledged in the thesis, and to the best of my knowledge and belief no material previously published or written by another person except where due acknowledgement is made in the text of the thesis, nor does the thesis contain any material that infringes copyright.

Authority of Access

The publishers of the papers comprising Chapters 2-4 and 6 hold the copyright for that content, and access to the material should be sought from the respective journals. The remaining content of the thesis may be made available for loan and limited copying and communication in accordance with the Copyright Act 1968.

Statement of Ethical Conduct

The research associated with this thesis abides by the international and Australian codes on human and animal experimentation, the guidelines by the Australian Government's Office of the Gene Technology Regulator and the rulings of the Safety, Ethics and Institutional Biosafety Committees of the University.

Signed: Date: 26 April 2018

Tina Oldham

III

Statement of Co-Authorship and Thesis Contributions

The following people and institutions contributed to the publication of work undertaken as part of this thesis:

Tina Oldham (TO) University of Tasmania, Launceston, Australia

Barbara Nowak (BN) University of Tasmania, Launceston, Australia

Phillip Crosbie (PC) University of Tasmania, Launceston, Australia

Tim Dempster (TD) University of Melbourne, Melbourne, Australia

Frode Oppedal (FO) Institute of Marine Research, Matredal, Norway

Jan Olav Fosse (JOF) Institute of Marine Research, Matredal, Norway

David Solstorm (DS) Institute of Marine Research, Matredal, Norway

Frida Solstorm (FS) Institute of Marine Research, Matredal, Norway

Lars Helge Stien (LS) Institute of Marine Research, Matredal, Norway

Tone Vågseth (TV) Institute of Marine Research, Matredal, Norway

Hamish Rodger (HR) Vet-Aqua International, Galway, Ireland

Pascal Klebert (PK) Sintef Ocean AS, Trondheim, Norway

IV

Paper 1 (Chapter 2)

Oldham T*, Solstorm D*, Solstorm F, Klebert P, Stien LH, Vågseth T, Oppedal F (2018) Dissolved oxygen variability in a commercial sea-cage exposes farmed Atlantic salmon to growth limiting conditions. Aquaculture 486: 122-129

*joint first authors

Conceived and designed the experiments: DS FO PK FS TV. Performed the experiments: DS TV PK. Analysed the data: TO DS LS PK. Wrote the paper: TO DS FO. All authors contributed to manuscript editing and revision, and approved the final article.

Paper 2 (Chapter 3)

Oldham T, Oppedal F, Dempster T (2018) Cage size affects dissolved oxygen distribution in salmon aquaculture. Aquaculture Environment Interactions 10: 149-156

Conceived and designed the experiments: TO FO TD. Performed the experiments: TO TD. Analyzed the data: TO FO TD. Wrote the paper: TO. All authors contributed to manuscript editing and revision, and approved the final article.

Paper 3 (Chapter 4)

Oldham T, Dempster T, Fosse JO, Oppedal F (2017) Oxygen gradients affect behavior of caged Atlantic salmon Salmo salar. Aquaculture Environment Interactions 9: 145–153

Conceived and designed the experiments: TO FO JOF TD. Performed the experiments: TO JOF. Analyzed the data: TO FO TD. Wrote the paper: TO. All authors contributed to manuscript editing and revision, and approved the final article.

Paper 4 (Chapter 6)

Oldham T, Rodger H, Nowak BF (2016) Incidence and distribution of amoebic gill disease (AGD)—An epidemiological review. Aquaculture 457: 35–42

Conceived and designed the review: TO HR BN. Analysed the data: TO HR BN. Wrote the paper: TO BN. All authors contributed to manuscript editing and revision, and approved the final article.

V

Declaration of Agreement

We the undersigned agree with the stated proportion of work undertaken for each of the published, peer-reviewed manuscripts contributing to this thesis.

Candidate: Date: 26 April 2018

Tina Oldham

Primary Supervisor: Date: 27 April 2018

Barbara Nowak

Head of School: Date: 27 April 2018

VI

SUMMARY

Sometimes, the desire for simplification can lead us astray. In marine aquaculture cages,

where fish welfare and production performance are constantly challenged by tangible

threats, it is easy to dismiss invisible and difficult to monitor dissolved O2 (DO) as

unimportant. But to do so is to ignore the fundamental importance of O2 for survival and

its underlying role in overall health and wellbeing. In this thesis, I demonstrate that while

DO conditions in cages rarely threaten the survival of farmed salmon, hypoxic DO levels

which negatively impact production performance and welfare, defined here as the

quality of life as perceived by the animal, are a common occurrence.

In field experiments conducted in Norway and Tasmania, I found that DO conditions in

commercial salmon cages are highly dynamic, and vary vertically, temporally and

horizontally across the cage width. Several factors correlated with DO variability,

including time of day, cage size, fish behavior and current speed. Using animal-borne DO

sensors, I found that the variability of DO in the cage environment is mirrored in the

conditions experienced by fish. Moreover, in a manipulative experiment salmon proved

capable of detecting and avoiding hypoxic DO conditions, but other environmental and

social factors can supersede hypoxia avoidance. And while the study design of these in-

situ trials was not optimal due to the limitations of working at large scale, it is exactly

that nature of this body of work which provided novel and industrially relevant insights.

Given the variable and heterogeneous nature of DO in marine cages, I also investigated

the implications of exposure to low DO on the production performance and welfare of

salmon in controlled experimental trials. Overall, I found that metabolic O2 demand and

cost of transport decrease with fish size, and increase exponentially with swimming

speed. Exposure to 50% DO saturation significantly reduced aerobic scope for activity

and swimming performance across a wide size range from 0.2 to 3.5 kg; and, cyclic,

short-term exposure accelerated the progression of Amoebic Gill Disease compared to

salmon maintained in normoxic conditions.

As a whole, this thesis demonstrates that the problem of hypoxia in aquaculture cages is

not intractable, but that there are no simple solutions or quick fixes. Maximizing the

production performance and welfare of farmed fish necessitates a systemic approach

based on a site specific understanding of the forces acting to replenish and drawdown

DO, and optimizing farming strategy to match the needs of both the site and fish.

VII

ACKNOWLEDGEMENTS

First and foremost I must thank my parents, Maureen & John, for always pushing me to

be the best version of myself. No dream was ever too big, no goal too extravagant.

Because of you I never question whether or not something is possible, just whether or not

I want it badly enough to put in the required time and effort.

To my husband, Kris – words cannot express how grateful I am for your tireless patience

and support. Thank you for helping me, without hesitation, no-matter how dirty, trivial or

obnoxious the task. Thank you for giving me common sense solutions when I concoct

Rube Goldberg machines. Thank you for dragging me outside and making sure I

maintain work/life balance.

Many thanks also to my supervisors, Barbara Nowak, Tim Dempster, Phil Crosbie and

Frode Oppedal. I sincerely feel like I had the supervisory dream team. Barbara, because

of your reliability and organization I never felt alone or lost, I always knew I had

someone to contact when in need of advice or assistance. Tim & Frode, your incessant

optimism and enthusiasm is infectious, and made this journey feel more like an exciting

adventure than work. Finally, I would’ve been lost numerous times without the practical

guidance and hands-on advice of Phil. Again, thank you all.

I would also like to thank Huon Aquaculture Company for providing site access and

expertise regarding data collection, as well as the numerous staff at IMR who provided

field and lab assistance. Thanks also to the members of the SALTT (UMelb) and Aquatic

Animal Health (UTas) lab groups who provided feedback on papers and presentations,

smoothie breaks and thought-provoking discussions.

Captain Greg, Uncle Ricky, Uncle Willy, Grandma, Uncle Michael, Max and Fleet – I am a

better person for having known and loved you all. Thank you, always.

VIII

TABLE OF CONTENTS

Title page

Declarations by the Author……………………………………………………………………………………………………………………………………..….…II

Statement of Originality

Authority of Access

Statement of Ethical Conduct

Statement of Co-Authorship & Thesis Contributions……………………………………………………………………………………..III

Declaration of Agreement…………………………………………………………………………………………………………………………………..………..V

Summary…………………………………………………………………………………………………………………………………………………………….………..……….VI

Acknowledgements…………………………………………………………………………………………………………….…………………………………..….….VII

Table of Contents……………………………………………………………………………………………………………………………………..……………..…….VIII

Chapter 1 General Introduction……………………………………………………………………………………………………………….….……1

Chapter 2 Dissolved oxygen variability in a commercial sea-cage exposes farmed

Atlantic salmon to growth limiting conditions………………………………………………………………….6

Chapter 3 Cage size affects dissolved oxygen distribution in salmon aquaculture…..….23

Chapter 4 Oxygen gradients affect behavior of caged Atlantic salmon Salmo salar…..36

Chapter 5 Hypoxia reduces metabolic and swimming performance in Atlantic

salmon………………………………………………………………………………………………………………………………………………...50

Chapter 6 Incidence and distribution of amoebic gill disease (AGD)- An epidemiological

review………………………………………………………………………………………………………………………………………..…….……67

Chapter 7 Hypoxia alters the progression of amoebic gill disease in Atlantic salmon..85

Chapter 8 General Discussion…………………………………………………………………………………………………………….………….98

Conclusions………………………………………………………………………………………………………………………………………………………………………...112

Acronyms & Abbreviations…………………………..……………...……………………………………………………………………………..…………..…113

References………………………………………………………………………………………………………………………………………………………….…..………….114

IX

Chapter 1 – Gen Intro

1

Chapter 1 General Introduction

The current global population of 7.6 billion people is projected to steadily increase

through the next several decades, reaching 9.7 billion by 2050 [1]. More people require

more food, and despite considerable effort and technological innovation, demand is

increasing faster than agricultural yield [2]. In 2016 an estimated 815 million people, more

than 1 in every 10 individuals, were chronically undernourished and had insufficient

access to protein and nutrients [3].

Further compounding the problem is the fact that as the human population grows, the

resources required for traditional food production become increasingly scarce. Arable

land use is progressively dedicated to urbanization and crops destined for livestock feed

and biofuel production rather than human consumption [4]. Nearly one-billion people

live in basins with severe water scarcity for at least three months of the year, and 20% of

the world’s aquifers are over-drawn [5, 6]. Global capture fisheries have been stable

since 1996, while the proportion of over-exploited fish stocks increased slowly but steadily

to 31% in 2016 [7].

Despite the sobering state of global food security, many researchers and policy-makers

are hopeful that aquaculture can meet the growing protein demand [2, 8–10]. For years

farmed fish have been the fastest growing protein source globally, with no signs that the

industry is peaking [11]. Between 1990 and 2010 aquaculture production increased at an

average rate of 7.8%, more than double that of pork, dairy, beef or grains [12].

Currently however, most aquaculture is either land-based or coastal, and therefore

constrained by competition from other users, environmental degradation and water

scarcity [2]. On a ‘blue planet’, 70% of which is covered by marine waters, the open

oceans remain a vast, untapped resource. Based on a global analysis of biological

production potential, researchers estimate that aquaculture could produce the total

landings of all wild-capture fisheries using less than 0.015% of the global ocean area [8].

Today, by value and quantity, Atlantic salmon (Salmo salar) are by far the largest

marine farmed commodity, with more than 2.4 million tonnes produced annually [7]. First

intensively farmed in the 1960s, the salmon industry rapidly expanded and now includes

operations in Norway, Chile, Scotland, Ireland, USA, Canada, Tasmania and the Faroe

Islands (www.fao.org).

http://www.fao.org/


2

Driven by increasing demand, the salmon industry is consistently at the forefront of

aquaculture innovation [13]. Among the latest developments is a shift of farms to ever-

more exposed and offshore locations [14, 15]. Moving into the open ocean, however, is a

literal move into uncharted waters for aquaculturists. Physically, the move offshore

presents immense structural challenges due to strong currents, variable winds and

powerful waves; logistically, the time and costs of staffing, transport and monitoring are

dramatically increased [14, 16]. For any novel development in aquaculture to be

successful, the production performance and overall health of the fish must be

maintained despite new challenges. In the case of a paradigm shift for salmon farming,

like moving offshore, success will require an integrated understanding of fish physiology,

behavior and the cage environment.

The importance of O2

Fish in marine cages face a unique challenge- they are exposed to all of the variation

present in the natural environment, but are confined and thus have little ability to avoid

adverse conditions. Most physiologically influential factors, like temperature and salinity,

do not differ from ambient conditions within cages, and are not directly influenced by the

fish themselves [17–20]. Dissolved O2 (DO) however, is a different story.

Oxygen diffuses 10,000 times more slowly through water than air [21], and must enter

water through one of two primary pathways- either via physical transport across the

water’s surface, or algal respiration [22]. These factors, combined with the generally low

solubility of O2 in water, make DO a highly variable and limited resource in aquatic

environments [22]. Such limited availability of DO has profound implications for marine

animals, and influences life in the oceans at every level from individuals to ecosystems

[23–25].

Fundamentally, energy is the ‘currency of life’, without which survival is impossible [26].

The energy generation pathways utilized by animals to produce adenosine triphosphate

(ATP) can be broadly grouped into two categories, those which require O2 (aerobic), and

those which do not (anaerobic) [27]. While aerobic metabolism of a single glucose

molecule produces between 20 to 30 ATP, anaerobic glycolysis yields two ATP and two

molecules of toxic lactic acid [27].


3

Functionally, this means that aerobic metabolism is 10 times more efficient than its

anaerobic counterpart, with minimal risk of dangerous waste accumulation. Therefore,

while anaerobic glycolysis is critical to survival during times of stress, for most organisms

it is not a sustainable alternative to aerobic metabolism [28].

Metabolic demand for energy, in turn, continuously fluctuates with numerous internal

and external factors [24, 29]. At the lower limit, standard metabolic rate (SMR) is the

minimal amount of energy required for a sedentary, non-digestive individual to maintain

homeostasis [30]. Maximum metabolic rate (MMR), at the opposite end of the spectrum,

is the maximum rate at which an individual can transfer O2 from the environment to

mitochondria, the powerhouse of the cell [31]. The difference between MMR and SMR is

an individual’s aerobic scope for activity (AS), and determines capacity to perform the

basic activities of life such as locomotion, digestion, growth and reproduction [32]. Any

reduction in environmentally available DO below the level required to achieve MMR limits

aerobic metabolic activity, and thus the ability of an individual to perform the daily work

required for survival.

Hypoxia in Atlantic salmon aquaculture

The density and viscosity of water mean that DO levels below 100% saturation are a

common and natural occurrence in the marine environment, with some habitats more

prone to low DO than others [21, 22]. Hypoxia, a general term used to describe

conditions in which DO availability is insufficient to support aerobic metabolic demand, is

particularly a concern in coastal and estuarine environments where the vast majority of

salmon farms are currently located [7, 22, 33].

For salmon farmers, the problem of hypoxia is amplified beyond just natural fluctuations.

The high biomass of fish in cages, even at relatively low stocking densities, causes

drawdown of DO as a result of metabolic demand [19]. In addition, beyond the obvious

impact of respiration, the physical presence of the fish and cage structure restrict water

movement, and thus local DO replenishment [34, 35]. Together, the O2 demand of large

numbers of fish combined with the physical blockage of water movement frequently

lead to hypoxic conditions in salmon cages (Table 1.1).


4

In extreme cases, hypoxia has been identified as the cause of mass mortalities on

salmon farms, resulting in the death of entire cages of fish [36]. More commonly, DO

levels sufficient to support SMR but insufficient to achieve peak AS are observed. In every

examination of salmon cages performed to date, no-matter how brief the observation

period, hypoxic conditions have been detected (Table 1.1). Around the world, hypoxia is a

silent, invisible threat to the production performance and welfare of farmed salmon.

Table 1.1 – Maximum and minimum dissolved O2 measurements (% saturation) collected in commercial Atlantic salmon cages.

Year Location Site TypeDO min

(%)

DO max

(%)Attributes Reference

2002 Hordaland, Norway Fjord 55 100+ Control Bergheim et al. 2006

2002 Hordaland, Norway Fjord 95 100+ Oxygenated Bergheim et al. 2006

2003 Rogaland, Norway Fjord 55 100+ Control Bergheim et al. 2006

2003 Rogaland, Norway Fjord 70 100+ Oxygenated Bergheim et al. 2006

2009 Newfoundland, Canada n/a 38 98 Stocking Density = 10 kg m-3 Burt et al. 2012

2008 Newfoundland, Canada n/a 42 100+ Stocking Density = 9 kg m-3 Burt et al. 2012

2008 Newfoundland, Canada n/a 50 100+ Stocking Density = 8.5 kg m-3 Burt et al. 2012

2009 Newfoundland, Canada n/a 66 100+ Stocking Density = 0 kg m-3 Burt et al. 2012

2016 Macquarie Harbour, Australia Semi-closed Harbour 0 100+ Dempster et al. 2016

2002 Solheim, Norway Fjord 57 100+ Stocking Density = 18-27 kg m-3 Johansson et al. 2006

2002 Solheim, Norway Fjord 66 100+ Stocking Density = 7-11 kg m-3 Johansson et al. 2006

2003 Norway Fjord 59 100+ 26 mm net mesh Johansson et al. 2007

2003 Norway Fjord 63 100+ 26 mm net mesh Johansson et al. 2007

2003 Norway Coastal 72 100+ 16 mm net mesh Johansson et al. 2007

2003 Norway Coastal 73 100+ 22 mm net mesh Johansson et al. 2007

2015 Solheim, Norway Fjord 59 87 Lice skirt Oldham et al. 2017

2012 Storeneset, Norway Fjord 26 90 3D monitoring array Oldham et al. 2018a

2015 Huon Estuary, Australia Estuary 57 100+ 168 m circumference Oldham et al. 2018b

2015 Huon Estuary, Australia Estuary 60 100+ 240 m circumference Oldham et al. 2018b

2016 Macquarie Harbour, Australia Semi-closed Harbour 0 100+ Individually tagged fish Stehfest et al. 2017

2011 Bergen, Norway Fjord 51 75 Lice skirt Stien et al. 2012

2011 Bergen, Norway Fjord 70 93 Control Stien et al. 2012


5

Aims of the study

Hypoxic conditions have been observed in salmon cages around the world (Table 1.1).

The objective of this thesis was to examine factors which contribute to the formation of

hypoxia in marine aquaculture cages, and to deepen our understanding of its

consequences for Atlantic salmon welfare and production performance.

Accordingly, the following questions were addressed:

♦ How variable is DO in cages? (chapters 1-3)

♦ What factors contribute to the formation of hypoxic conditions? (chapters 2-3)

♦ Given the choice, will salmon avoid hypoxic areas? (chapters 2 & 4)

♦ Does hypoxia exposure alter the capacity of salmon to cope with other stressors?

(chapters 5-7)

It is hoped that this integrative understanding of the causes and consequences of

hypoxia in marine aquaculture cages will help managers minimize its negative impacts

on farmed salmon, and aid in mapping the path forward for new farming strategies.

Chapter 2 – DO variability in cages

6

Chapter 2

Dissolved oxygen variability in a commercial sea-cage exposes farmed Atlantic

salmon to growth limiting conditions

David Solstorm1§, Tina Oldham2§, Frida Solstorm1, Pascal Klebert3, Lars Helge Stien1, Tone

Vågseth1 & Frode Oppedal1

1Institute of Marine Research, N-5984 Matredal, Norway 2University of Tasmania, Institute of Marine and Antarctic Studies, Tasmania, 7250,

Australia 3Sintef Ocean AS, N-7465 Trondheim, Norway

§ Joint first authors

Corresponding author: [email protected], phone: +61491155431

Conflicts of interest: none

Key words: Salmo salar, aquaculture, hypoxia, behaviour, dissolved oxygen, fish welfare

ABSTRACT

Understanding dissolved O2 flux in marine cages, and how individual fish respond to and

experience such variation, is critical to optimizing growth and production performance of

farmed salmon. We used a high resolution environmental monitoring system to map a 3-

dimensional commercial marine cage with respect to salinity, temperature and dissolved

O2 through time, while also tracking the oxygen experience of 4 individually tagged

Atlantic salmon. Despite all of the dissolved O2 measurements at the reference site being

physiologically suitable for maximum growth, 1 in 4 of the recordings collected within the

cage were below dissolved O2 levels known to reduce feed intake and growth. Recorded

dissolved O2 in the cage ranged from 26 to 90 % saturation with a high degree of vertical,

horizontal and temporal variation. Poorest dissolved O2 conditions consistently occurred

at night in the central and down-current cage positions. Dissolved O2 levels experienced

by individual fish ranged from 30 to 90 % saturation, with variation within 5 minute

intervals as large as 32 percentage points. These results expand the current body of

knowledge on environmental variability in marine cages, and provide valuable insights to

aid farm managers in focusing mitigation and monitoring efforts when and where they

are most needed.

mailto:[email protected]


7

INTRODUCTION

The environment within marine aquaculture cages can be highly variable, and is a critical

determinant of growth rate in farmed fish Reference 37]. Two of the most important

external factors directing fish metabolism are temperature and oxygen availability [22,

38]. Temperature determines metabolic rate, and thus the pace of growth, while

dissolved O2 is the primary limiting factor for aerobic metabolism [29].

Recent work on Atlantic salmon (Salmo salar) post-smolts has demonstrated that, in this

species, aerobic scope[39]and feed intake [40] increase throughout ecologically and

farm relevant temperatures (3-23 ⁰C and 7-19 ⁰C, respectively). In parallel, the metabolic

rate and amount of O2 required for fish to survive and grow also increase. As a

consequence, salmon post-smolt have increasing O2 requirements with temperature, and

the limiting oxygen saturation (LOS) below which they switch to anaerobic glycolysis

rises from 30 % at 6 ⁰C to 55 % at 19 ⁰C [41]. In less extreme hypoxia, as high as 76 %

dissolved O2 saturation, feed intake declines [40]. Even in cyclic hypoxia, with salmon

kept and fed in normoxic conditions but subjected to 1 hour of 50 % dissolved O2

saturation every 6 hours, specific growth rates were reduced by 13 % compared to

normoxic controls [42]. In a similar trial, when salmon were fed during hypoxic conditions,

growth rates were reduced even further [43].

Given its physiological importance, understanding how dissolved O2 varies within marine

cages, and what conditions salmon experience as a result of such variation, is

paramount to maximizing salmon production performance and welfare. Temperature,

current velocity, salinity and dissolved O2 have all been observed to vary vertically in

marine cages [18–20, 37, 44, 45], with mean dissolved O2 as much as 20 percentage

points different between the surface and cage bottom [19]. But fish in marine cages are

not only moving up and down through a 2-dimensional environment, they are faced with

the far more complex challenge of moving, constantly, through an ever changing 3-

dimensional environment.

Little is known about how dissolved O2 varies horizontally within marine cages. Studies of

water movement horizontally across cages have found that current speed and direction

are highly variable [18, 45, 46], and strongly affected by fish behaviour [34, 47].


8

Given that physical transport mechanisms such as currents and wave action are the

primary means through which oxygen is replenished in marine cages [18, 48, 49], and

that fish do not distribute themselves evenly throughout the cage [37, 50, 51], it is

expected that dissolved O2 will also vary horizontally.

Observations of salmon group behaviour have recorded changes in vertical distribution

in response to a wide variety of environmental stimulus including light [52, 53],

temperature, salinity, feeding [50], water current velocity [51], sound [54] and sea lice

infestation level [55]. Avoidance of sub-optimal dissolved O2 conditions, however, is

inconsistent [18–20], and in heterogeneous environments can be superseded by other

factors [44, 45, 56]. A great deal of inter-individual variation in swimming depth has also

been observed within groups of caged salmon [57–60]. And while group observations

provide information on average behaviour and general trends, observations of the

environment as experienced by individuals can provide a deeper understanding of the

physiological implications of cage variability as well as the coping mechanisms

employed by individuals facing heterogeneous conditions [61].

To improve understanding of dissolved O2 variation within the cage environment, and

how salmon respond to and experience such variation, in this case study we, a) tracked

the dissolved O2 experience of multiple individual salmon, and b) mapped the 3-

dimensional marine cage environment with respect to salinity, temperature and

dissolved O2.

MATERIALS & METHODS

Study site

Observations were collected in two case study periods from 8-12 October (period 1) and

2-7 November (period 2) 2012 at a commercial marine cage farm in Storeneset, a small

branch of Fensfjorden, western Norway (60.5° N), Figure 2.1. Measurements were

collected from 1 of the 5 cages at the site which measured 20 m deep and 50 m in

diameter. The depth below the cages varied from 50 to 120 m. According to farm data,

the observed cage was stocked with 170, 300 Atlantic salmon with an average weight of

3.5 kg, corresponding to a stocking density of 15.2 kg∙m-3. Fish were fed continuously at

the water’s surface from 08:00 to 16:00 by an automatic centralised feeding system with

pneumatic feed delivery.


9

Figure 2.1 - Three diagrams picturing: a) a regional map of the surrounding area, b) farm configuration, and c) instrument organization within the cage. CTDs within the cage were oriented in parallel with the primary current direction, south to north (188 ͦ N), and are identified by distance from the upstream cage edge.

Individual fish experience

A VR100 ultrasonic receiver (Vemco Ltd., Nova Scotia, Canada) equipped with an

omnidirectional hydrophone was positioned inside the cage 1 m from the net at 1 m

depth, and acoustic dissolved O2 transmitters (ADOT-LP-13, Loligosystems.com) were

attached to 8 randomly selected fish (weight 3569 ± 308 g and length 68 ± 5.6 cm (mean

± SD). Following capture, each individual was placed in an anesthetic bath (Finquel,

Tricaine Methanesulfonate, Western Chemical Inc., USA, concentration: 1 g per 10 L

seawater) until respiration rate became slow and irregular (2 - 4 breaths∙min-1). Following

length and weight measurement, fish were placed in a V-shaped surgical cradle and

supplied with a continuous flow of water for gill irrigation. The transmitter (weight 9.9 g,

diameter 13 mm, length 54 mm) was attached below the dorsal fin at the side of the fish

using 2 piano wires. All surgeries were performed by the same individual, and the entire

procedure lasted less than 2 min per fish. Transmitter weight represented 0.2 to 0.3 % of

fish body weight in air. Following surgery, fish were placed in a tank until they reached

equilibrium, and after 5 additional minutes transferred back to sea. The oxygen probes

(MICRO DO, Loligo systems, Denmark) have a measurement range of 0 to 200 % air

saturation with an accuracy ±1 % and T90 <15 s. Transmission frequency was reduced in

period 2 due to declining battery power in the tags (Figure 2.2).

CTD e

CTD d

CTD b

CTD c

CTD a

CTD r

Profiler

a c

b

CAM


10

Environmental variables

During period 2, vertically profiling CTDs (SD204, SAIV AS, Bergen, Norway) connected to

an automatic winch (Belitronics HF5000, Lunde, Sweden) continuously recorded

dissolved O2, temperature and salinity at 5 positions in a transect running from south to

north inside the cage and at a reference position 10 m west of the cage (Figure 2.1). The

CTDs moved at a constant speed of 1.3 m∙min−1 from the surface to 20 m depth, resulting

in approximately 4 complete profiles per hour. A south to north transect was chosen to

align with the prevailing current direction at the site, with the reference CTD located as

close as possible to the cage without being affected by its biomass. All O2 probes were

calibrated at the beginning of the study and assessed for accuracy upon retrieval. Drift

was less than 5 % in all O2 probes, so no data were excluded from analysis. Water

current was monitored at a reference point 50 m south-west of the farm with a surface

mounted acoustic profiling current meter (Aquadopp, Nortek, Norway, Figure 2.1). The

current meter recorded simultaneous measurements of current speed (m∙s-1) and

direction once every 30 minutes at 1 m intervals within a depth range of 1 to 19 m from

the surface.

Swimming speed

Instantaneous swimming speeds were observed 3 times per day at 09:00, 13:00 and 16:00

during period 2 using a winch controlled underwater pan/tilt camera (Orbit GMT AS,

Førresfjord, Norway) placed at 5 m depth 8 m inwards from the edge of the cage (Figure

2.1c). Swimming speed was calculated as body lengths per second (BL∙s−1) by recording

the time taken for the snout and the tail of 15 fish to pass a vertical reference line [62].

Statistical analysis

Dissolved O2 experience was compared between individuals by a linear mixed effects

model using the ‘nlme’ package [63] in R environment 3.2.0 (www.r-project.org). The

model used dissolved O2 saturation as the dependent variable, individual fish ID as the

fixed effect and time as a random effect.

http://www.r-project.org/


11

Figure 2.2 - The experienced O2 levels of 4 individual salmon during 2 periods of 4 days. The y-axis is dissolved O2 saturation (%) and the x-axis date and time of day. The central letter in each plot identifies the individual fish. Areas shaded in grey represent night while unshaded areas represent daylight.


12

Variability of individual oxygen experience was investigated by calculating the change in

dissolved O2 saturation measured during intervals of 5 different durations: 5 min, 10 min, 1

h, 6 h and 12 h, for each individual. Intervals were chosen sequentially so that there was

no overlap, resulting in a maximum of 288, 144, 24, 4 and 2 values per day, respectively,

dependent upon the number of transmissions received. The change in dissolved O2

saturation experienced was calculated by taking the absolute value of the difference

between the highest and lowest measurements collected within each interval.

CTD and water current measurements were averaged over 1 m depth intervals each

hour. Differences in vertical distribution of temperature, salinity and dissolved O2

saturation between all positions were tested for with two-sample Kolmogorov-Smirnov

tests. To correct for multiple comparisons, statistical significance (α = 0.05) was

determined at a Bonferroni corrected p-value of 0.003. Contour plots using dissolved O2

measurements were created for each CTD position (Figure 2.3).

To test for a correlation between reference current speed and dissolved O2 saturation at

each CTD position, time series linear regressions were performed using the tslm function

of the ‘forecast’ package [64] in R environment 3.2.0 (www.r-project.org). In addition to

reference current speed, an explanatory trend variable was included to account for the

cyclic nature of tidal cycles.

For each individual and each cage position, the proportion of all dissolved O2

measurements which fell below the critical production thresholds of limiting oxygen

saturation (LOS) and maximum feed intake were calculated. Briefly, at any given

temperature, metabolic rate remains generally stable with declining O2 until a breakpoint

is reached (the LOS), below which the individual is forced to switch to anaerobic

metabolism [29]. Because anaerobic metabolism can only be safely sustained for a brief

time, the LOS is considered the lower limit for acceptable O2 levels with regards to fish

welfare and performance. We assumed an LOS of 33 % dissolved O2 saturation based on

the stable temperatures recorded throughout our study of 10.2 ± 1.0 C Reference 41].

Similarly, feed consumption is also temperature dependent and remains steady despite

dropping dissolved O2 until reaching a breakpoint below which intake declines.



13

Based on recorded cage temperatures, feed intake was conservatively estimated to

decline below 53 % dissolved O2 saturation [40]. Dissolved O2 saturations greater than 53 %

were deemed physiologically suitable for maximum growth for the temperatures

observed in this trial. This trial adhered to the regulations stipulated by the Norwegian

Regulation on Animal Experimentation (Animal Ethics application ID: 4613).

Figure 2.3 - Environmental dissolved O2 levels recorded during period 2 at 5 positions inside the cage along a south to north transect, labeled as distance from southern cage edge in meters, and at the reference site, ‘R’. The dashed line indicates the reduced feed intake threshold, and the solid line the limiting oxygen saturation.


14

Table 2.3 - Experienced levels of dissolved O2 saturation (mean ± SD) by individual fish during 2 periods of 4 days each. Dissolved O2 measurements were collected by a micro dissolved O2 logger mounted on the dorsal part of the fish.

Dissolved O2 saturation (%)

Fish ID A B C D

Period 1 mean ± SD 61±7 56±7 57±10 50±11 min/max 38/88 30/87 35/90 33/82 n 2209 1808 2255 1599 Period 2 mean ± SD 62±7 59±7 55±6 52±6 min/max 49/75 44/70 42/74 40/68 n 46 264 720 137

RESULTS

Of the 8 individual fish fitted with dissolved O2 loggers, 3 were excluded from final data

analysis due to excessive measurement drift (> 5 %) between study periods, and a 4th

was lost. The remaining 4 individuals equipped with transmitters experienced large

variation in dissolved O2 from 30 to 90 % saturation, spanning the full extent of observed

variation within the cage (Figure 2.2, Table 2.3). Dissolved O2 experience varied

significantly between individuals (F = 458, p < 0.001), with average dissolved O2

experience highest for fish A (61 ± 7 %), and lowest for fish D (50 ± 11 %).

Variation in dissolved O2 levels experienced by individuals within a 5-minute interval

ranged from 4 to 6.6 % on average (max 32 %, Table 2.4). All 4 individuals experienced

dissolved O2 changes as large as 24 % within a 5-minute interval (Table 2.4). Mean

dissolved O2 variation experienced by individual fish within 12-hour intervals ranged from

30 to 39 % (max 51 %, Table 2.4). The lowest dissolved O2 measurements experienced by

all 4 individuals occurred at night (Figures 2.2 & 2.4). Observed swimming speeds did not

differ significantly during daylight hours, and ranged from 57 to 75 cm∙s-1.

All individually tagged fish experienced sub-optimal dissolved O2 levels during the trial,

with dissolved O2 saturations below the threshold for reduced feed intake accounting for

24 to 63 % of collected measurements (Figure 2.6). The majority of sub-optimal

conditions experience by all 4 fish occurred at night (Figure 2.6). Measurements below

the LOS were only recorded by 2 individuals (fish B and D), and accounted for 0.05 %

and 0.17 % of collected data, respectively.


15

Table 2.4 - Experienced dissolved O2 saturations of 4 individual fish calculated for 5 time intervals: 5 min., 10 min., 1 hour, 6 hours and 12 hours during a period of 4 days. The data presented are mean ± SD and maximum experienced dissolved O2 difference for each time interval.

Range in individually experienced O2 saturations (%)

Fish ID 5 min 10 min 1 h 6 h 12 h

A mean ± SD max

5.2±3.9 24.7

7.7±4.5 25.9

15.6±7.0 27.1

24.3±5.8 36.5

30.3±6.1 41.2

B mean ± SD max

5.3±4.5 29.1

7.3±5.4 29.1

13.9±6.4 30.4

23.1±6.4 40.5

29.6±7.3 44.3

C mean ± SD max

6.6±5.2 31.0

9.7±6.6 33.3

18.9±7.7 38.1

31.1±7.6 46.4

38.6±8.0 51.2

D mean ± SD max

4.0±5.7 32.5

6.1±4.7 33.8

12.7±5.9 37.7

23.5±6.4 37.7

31.1±5.8 42.9

Observed dissolved O2 levels at all cage positions were significantly lower than at the

reference site (p < 0.001, Figure 2.3). Lowest dissolved O2 saturation levels were observed

in the surface water layers within the cage during evening hours (Figure 2.3). At positions

8 m, 16 m and 32 m from the southern cage edge, 94 to 96 % of dissolved O2 recordings

were physiologically suitable for maximum growth, while this was true for only 49 % of

the dissolved O2 measurements collected in the central cage position (24 m), and only

28 % for the measurements collected nearest the northern edge (40 m) (Figure 2.5).

Figure 2.5 - Percentage of collected dissolved O2 measurements which fall within critical production thresholds: below the LOS (black), above LOS but below dissolved O2 of maximal feed intake (dark grey) and within ideal conditions (light grey). Position labels represent distance, in meters, from the southern cage edge, with ‘R’ being the reference CTD. Specific percentage values indicate proportion of measurements in each plot within ideal dissolved O2 conditions for production.


16

Figure 2.6 - Percentage of collected dissolved O2 measurements from individual fish which fall within critical production thresholds: below the LOS (black), above LOS but below dissolved O2 of maximal feed intake (dark grey) and within suitable conditions for maximum growth (light grey). The upper chart presents measurements collected during the night (dark), while the lower chart presents measurements collected during the day (light). Specific percentage values indicate proportion of measurements in each plot within ideal dissolved O2 conditions for production.


17

Current speeds were very stable throughout the study (mean ± SD, 4.41 ± 2.2 cm∙s-1 ) with

a brief episode of higher speeds (range 0 – 25 cm∙s-1), and flowed in a consistent

northerly direction (188 ͦN). Significant correlations (Table 2.2, p < 0.001) were detected

between dissolved O2 saturation and reference current speed at all cage positions, but

not at the reference site (Table 2.2, p = 0.309). In the non-central cage positions (8, 16, 32

and 40 m from the southern edge) reference current speed accounted for 27 to 35 % of

the variability observed in dissolved O2 saturation. In the central cage position (24 m),

reference current speed only accounted for 19 % of the observed variability, considerably

less than the non-central positions. Logically, as there is no reason to expect increased

biomass to alter temperature or salinity, horizontal position had no effect on the

temperature and salinity profiles (Table 2.1).

Table 2.1 - Observed environmental conditions in a commercial Atlantic salmon marine cage across a south to north transect, aligned with the typical direction of water movement. Measurements were collected at each position in vertical profiles from 0 to 20 m depth each half hour during period 2 (Figure 2.1).

Distance from upstream edge of cage (m)

8 16 24 32 40

Dissolved O2 (%) mean ± SD min/max

64.7±7.1 43.7/89.1

66.3±7.3 44.4/90.2

52.4±7.4 26.2/76.9

63.9±6.7 29.7/85.6

50.7±4.7 32.2/70.3

Salinity (ppt.) mean ± SD min/max

31.2±1.2 26.3/32.6

31.0±1.1 26.7/32.3

30.8±1.1 26.5/32.0

30.9±1.0 26.5/32.0

31.2±0.9 27.2/32.3

Temperature (C) mean ± SD min/max

10.2±1.0 5.7/11.4

10.2±1.0 6.2/11.6

10.3±1.0 5.8/11.5

10.3±0.9 6.2/11.5

10.3±0.8 6.5/11.5

DISCUSSION

Using a combination of individually tagged salmon and 3-dimensional water quality

measurements, these data reveal important and novel insights about the cage

environment. Extreme temporal and spatial variation in dissolved O2 distribution within

the cage led to salmon experiencing suboptimal conditions known to negatively impact

growth. Each of the tagged individuals experienced the full range of dissolved O2

conditions present within the cage, and though partially relieved by behavior in some

tagged individuals, all 4 fish tagged in this study experienced poor dissolved O2

conditions at some point during this brief survey.


18

Individual oxygen experience

These data show that individual salmon in commercial marine cages can experience a)

variations of up to 32 % dissolved O2 saturation within time periods as short as 5 minutes,

and b) frequent drops in dissolved O2 saturation below levels known to impose negative

effects on feed intake and growth [40–42, 65]. Sub-optimal dissolved O2 conditions

occurred in all measured cage positions, while 100 % of recorded dissolved O2 saturation

measurements at the reference site were physiologically suitable for salmon growth and

performance (Figure 2.5 & 2.6). The observed variation in cage dissolved O2 was larger,

both in time and absolute level, than in previous surveys of marine cages [18–20], and

provides the first example of highly variable dissolved O2 across the width of a cage.

The extreme variability of dissolved O2 in the cage environment was evident in the

dissolved O2 conditions experienced by the 4 individually tagged fish, despite being a

very small sample of the 170, 300 stocked fish. Measurements spanned a range from 30

to 90 % dissolved O2 saturation (Table 2.3), and varied as much as 32.5 % within time

periods as short as 5 minutes for a single individual (Table 2.4). The variation in dissolved

O2 conditions experienced between individual fish was also high. While only 24 % of

dissolved O2 measurements collected by fish A were below the threshold for maximum

feed intake, 63 % of dissolved O2 measurements collected by fish D were in suboptimal

conditions (Figure 2.6). Interestingly however, though a considerable proportion of

measurements collected by all of the tagged individuals were below the threshold for

maximum feed intake (Figure 2.6), the vast majority of those measurements were

collected at night when no feed was available (Figures 2.4 & 2.6). Though not ideal

because intermittent hypoxia still reduces growth rate even if it does not co-occur with

feeding [65], the negative impacts of the sub-optimal dissolved O2 conditions

experienced by the individuals tagged in this study were minimized by fish behavior.

Temperature, light and hunger are important drivers of salmon behavior, with fish

generally schooling deeper during daylight hours and moving closer to the surface in

darkness and when feeding [50]. Though previous work has demonstrated that salmon

are capable of avoiding environmental hypoxia, this behavior can be overruled by other

environmental and social factors, in this case a preference for shallow swimming in

darkness [45, 50, 56, 66].


19

Because the poorest dissolved O2 conditions occurred in the surface waters throughout

this study, the movement of the fish towards the surface at night explains the prevalence

of hypoxic measurements recorded during evening and night hours by the tagged

individuals (Figures 2.3 & 2.4).

Cage environment

Lowest mean dissolved O2 levels were observed in the central (52.4 ± 7.4 %) and down-

current (50.7 ± 4.7 %) cage positions. Given that physical transport is the primary source

of replenishment for consumed O2 in marine cages [19, 48], and that current speed can

be reduced more than 50 % due to the combined effects of fish and net walls [51, 67], it

is unsurprising that low dissolved O2 levels were observed in the cage position furthest

from incurrent water flow. However, despite the down-current position having lowest

mean dissolved O2, absolute lowest dissolved O2 saturation (26.2 %) was recorded in the

central cage position (Table 2.1). Further, it was only in the central cage position that

dissolved O2 saturation repeatedly declined below the LOS for post-smolt Atlantic

salmon (Figure 2.4) [40, 41].

Water flow in and around marine cages is complex and affected by several factors,

including not only the physical properties of the cage structure [34, 68], but also

bathymetry [67], farm organization [69] and the fish themselves [34, 46, 47]. Normally,

salmon form a circular schooling pattern around the cage at background current

velocities below 35 cm s-1, and change to standing against the current at higher velocities

[51, 70]. Dye tracking experiments in marine cages found that while water flowed

straight through empty cages in the primary direction of current flow, in stocked cages

with fish swimming in a circular pattern the surface water converged towards the center

of the cage: in one study by conducting measurements in medium size cages stocked

with adult salmon [47], and another by studying a commercial sized cage partially

shielded by a tarpaulin [46].

Similarly, in very small cages (1 m3) stocked with 65 g rainbow trout, another study found

that the circular swimming of the fish significantly increased water transmission through

the cage during low flow conditions, and drew water into the cage at a rate of ~2 m3

min-1 [71].


20

Figure 2.4 - The experienced O2 levels of 1 individual salmon (fish ‘C’) during a 1-hour period each in daylight (12:00 – 13:00) and darkness (23:00 – 00:00) on 10 October 2012. Dissolved O2 saturation (%) is on the y-axis and minute of the hour on the x-axis. The number in the boxes are the precise O2 measurement at each recorded time-point. The shaded area represents the dissolved O2 threshold for reduced feeding [40].


21

Water currents throughout this study flowed in a primarily south to north direction

across the cage at relatively slow speeds, averaging 4 cm∙s-1 (max 25 cm∙s-1). Given that

Atlantic salmon (1.5 kg) maintained a circular schooling structure below current speeds

of 35 cm∙s-1, we expect that during this study the caged fish were consistently schooling in

a circular pattern, which aligns with the recorded camera observations [51]. We therefore

suggest that the spatial distribution of the fish throughout the cage altered water

exchange patterns, and could explain the reduced dependence of dissolved O2

saturation on reference current speed in the middle of the cage (Table 2.2, R2 = 0.19) as

compared to the other cage positions (Table 2.2, R2 = 0.27 – 0.35). Together, the

combined impacts of schooling fish and slow ambient current speeds likely explain the

particularly low dissolved O2 conditions observed occasionally at the central cage

position.

Table 2.2 - Observed correlations between reference current velocity and dissolved O2 saturation at each CTD position.

Distance from southern cage

edge F-statistic

Degrees of freedom

Residual Standard Error

Adjusted R2 P-value

8 m 47.89 176 3.32 0.350 0.000 16 m 48.98 176 3.39 0.350 0.000 24 m 22.08 176 3.85 0.190 0.000 32 m 37.38 176 3.56 0.290 0.000 40 m 34.24 176 2.94 0.270 0.000

Reference 1.18 176 3.76 0.002 0.309

Additionally, fish respiration combined with current attenuation by the cage structure

explains the highest dissolved O2 conditions occurring at positions 8 and 16 m from the

up-stream cage edge, and lower dissolved O2 at the down-current position (40 m)

furthest from the point of ingress and nearest to the adjacent row of cages.

Unexpectedly, higher dissolved O2 was observed 32 m downstream compared to both

the central (24 m) and downstream (40 m) cage positions. This pattern may in part be

an effect of turbulence and re-circulated water within and behind the cage, similar to a

flow field affected by a high solidity cylinder [72–74].


22

Taken together, present data suggests the horizontal variation in dissolved O2 saturation

levels we observed occurred as a result of the complex interactions of water current,

cage structure, fish respiration and behavior. Future work to investigate the specific

dynamics of the relationship between water movement within stocked cages and

environmental variation is warranted.

CONCLUSIONS

The extreme variability of dissolved O2 conditions observed throughout the cage, ranging

from 30 to 90 % saturation, was mirrored in the experiences of individually tagged fish.

All tagged individuals were exposed to dissolved O2 conditions limiting to growth and

production performance. Additionally, the 3-dimensional mapping of environmental

conditions within the cage documented a novel and complex pattern of dissolved O2

variability across the cage width, with hotspots of poor oxygen conditions in the central

and down-current cage locations. These results demonstrate that maintenance of

dissolved O2 at or above physiologically optimal levels, throughout the cage, is required

to maximize Atlantic salmon welfare and production performance.

Chapter 3 – Cage size affects DO

23

Chapter 3

Cage size affects dissolved oxygen distribution in salmon aquaculture

Tina Oldham1*, Frode Oppedal2, Tim Dempster3

1Aquatic Animal Health Group, Institute for Marine and Antarctic Studies, University of

Tasmania, Australia 2 Institute of Marine Research, Matredal, Norway 3Sustainable Aquaculture Laboratory – Temperate and Tropical (SALTT), School of

BioSciences, University of Melbourne, Australia* Corresponding author:

[email protected]

**Additional information has been provided in this chapter, which expands upon the published article

ABSTRACT

Atlantic salmon aquaculture is shifting toward larger cages, but the water quality

implications of this shift are unknown. While larger cages could improve profitability

through economies of scale, they may increase the risk of low dissolved O2 (DO)

conditions due to reduced water exchange. Low DO conditions reduce feed intake,

meaning that the benefits of shifting to larger cages must be weighed against potential

negative impacts on fish growth. To test the impact of cage size on DO distribution, we

recorded DO saturation in several circular cages of two different sizes on a commercial

salmon farm: six 168 m and four 240 m circumference. Static strings of DO loggers at 1,

4.5, 8, 12 and 16 m depths recorded DO saturation once every 60 seconds throughout a 10

day period in mid-summer. Overall, DO levels in standard 168 m circumference cages

were suitable for salmon feeding and growth. Mean DO levels were highly variable (57 –

134 % saturation), and were lower in cages than at the reference site. On average, DO

saturation decreased with depth, and was lowest during the early morning hours. Lowest

DO measurements occurred in the large 240 m circumference cages, where 1 in 20 of all

recordings were at levels known to reduce salmon feeding and growth. DO levels in

larger cages can suit salmon production, but site specific environmental conditions

throughout the year must be considered to ensure there is sufficient capacity to support

reduced water exchange.

Key words: hypoxia, Salmo salar, Tasmania, welfare, feeding, environment



24

INTRODUCTION

In fish, all activities including locomotion, digestion, reproduction and growth, are

powered by aerobic metabolism and rely on the availability of dissolved O2 (DO) [24]. As

DO saturation declines and oxygen becomes metabolically limiting, activities non-

essential to immediate survival, including feeding and growth, are minimized [40, 43]. For

healthy Atlantic salmon, moderate DO levels, as high as 77 % saturation, lead to reduced

feed intake [40]. Saturations below 40 % force the switch to anaerobic metabolism, and

can be lethal if conditions do not rapidly improve [40]. As a result, the survival and

production performance of farmed salmon is intrinsically linked to DO.

As the largest single aquaculture commodity by value, salmonids represent 16.6 % of

world trade, with demand for Atlantic salmon steadily increasing [7]. To maintain growth

and meet demand, technological advancements which improve efficiency and

sustainability are required [75]. Most cages used in salmon aquaculture are “gravity”

type cages; weighted nets suspended in the water column beneath a surface collar [67].

Average cage size has grown steadily since the inception of the salmon industry in the

1970s. Both cage diameters and depths have increased, allowing an expansion in

production volumes from small 500 m3 – 2,000 m3 units [76, 77] to 20,000 – 80,000 m3

today [78]. Plans to expand salmon farming into offshore and exposed areas will further

increase production volumes, as evidenced by deployment of the world’s largest single

fish cage of 250,000 m3 in 2017 [79]. However, though larger aquaculture cages are more

cost effective due to economies of scale, and are structurally better able to withstand

harsh offshore conditions, increased cage size should decrease DO conditions within

cages.

As cage size increases, the surface area to volume ratio of the cage declines and water

exchange is reduced [34]. Based on a simple model created to estimate DO levels within

aquaculture cages as a function of stocking density, cage size and current speed, a

stocking density of 15 kg m-3 and current speed of 6 cm s-1, DO concentrations would

drop from 90 % of ambient levels within a 30 m across cage to 50 % in a cage 60 m

across [80] . Predicted DO levels drop further with increased stocking density or cage

length, and decreased current speed [80].


25

Poor DO conditions, below levels known to cause reduced feed consumption and in some

cases even death, have been documented in standard commercial salmon cages (12,500

– 24,500 m3) on 3 continents [17, 18, 20, 44, 81]. For this reason, any alterations to

production strategy which may increase the likelihood of poor DO conditions, such as

increasing cage size, should be approached with caution.

While the theoretical constraints and consequences of larger cages for DO levels are

clear, the effect of cage size on DO has never been tested in a full-scale industrial setting.

Using a unique site where two different cage sizes (168 m and 240 m circumference)

were co-located and contained commercial densities of salmon, we tested if DO

saturation differed with cage size.

MATERIALS & METHODS

Experimental setup

The experimental period ran from 14 - 24 December 2015 on a commercial Atlantic

salmon farm in southeast Tasmania’s Huon Estuary (43.26 ⁰S, 147.07 ⁰E). Bottom depth

beneath the cages ranged from 18 to 30 m. Ten cages were evenly spaced in two

parallel rows of five cages with ~100 m between all cages, arranged perpendicular to the

primary N-S direction of tidal current flow (Figure 3.1ab). Each cage had two nets, an

internal fish containment net (mesh size: 35 mm) as well as an external predator net

(mesh size: 125 mm).

Six of the cages were ‘standard’ size 168 m circumference circular tubes with an internal

net 52.5 m diameter × 16.5 m deep (~35,000 m3 volume), while four of the cages were

‘large’ 240 m circumference circular tubes with internal nets 76 m in diameter × 23 m

deep (~104,000 m3 volume). The farm’s standard anti-fouling maintenance program,

whereby the nets of all cages were visually monitored and regularly cleared of

biofouling, was followed throughout the study. Visual inspection performed by divers and

remotely operated vehicles determined that no detectable blockage increase occurred

on any cages below the top metre of netting at any point throughout the study.


26

Figure 3.1 - a) Geographic location of the farm site in south-eastern Tasmania. b) Cage layout and orientation at the study site. Standard 168 m circumference cages (1,2,3,4,9,10) are represented by solid circles, whereas large 240 m circumference cages (5,6,7,8) are circles with dark centers. The reference site (R) is represented by the diamond 200 m south of the cages. The grey polygons are barges. c) diagram of the double netted cage and location of dissolved O2

loggers which were positioned midway between the edge and center on the western side of each cage.

Stocking densities ranged from 2.11 to 4.04 kg m-3, and average fish weight was between

2.27 and 3.18 kg based on data supplied by the farm (Table 3.1). Fish weight was

determined during well-boat transfer of the full cage population at the time of cage

stocking. As fish were recently distributed among cages at the beginning of the trial,

there was minor size and density variation between cages with mean fish weights and

stocking densities lower in the large cages than in the standard cages (Table 3.1). Fish

were fed to satiation twice daily, beginning at 06:00 and 16:00, respectively.


27

Table 3.1 – Recorded fish weights (mean ± SD) and stocking densities in each cage.

We recorded DO in all 10 cages and a reference site 200 m south of the nearest cage.

Static strings of DO loggers with copper anti-fouling caps (RBRsoloDO, RBR Ltd., Canada)

were deployed at 1, 4.5, 8 and 12 m in all cages, with an extra logger at 16 m in the large

cages and at the reference site (Figure 3.1c). DO saturation measurements were

recorded once every 60 seconds, by each logger, throughout the 10 day period. Across

all 45 loggers, a total of 739,958 DO measurements were collected. Temperature profiles

from 1 to 16 m depth were collected from the reference site at the beginning and end of

the study on 16 Dec 2015 and 27 Dec 2015, respectively.

Data analyses

To test for differences in DO conditions between treatments (standard and large cages),

we created a linear mixed effects model using the ‘nlme’ package [63] in R environment

version 3.2.0 (www.r-project.org). The model used DO saturation as the dependent

variable with fixed effects of treatment and depth. To account for differences between

cages as a result of position, random intercepts were determined by including cage and

time as random variables. Contour plots of DO conditions through time were created for

each individual cage as well as the reference site in Surfer v.10 via Kriging interpolation.

To assess the implications of observed DO levels, DO measurements were compared

against previously determined critical physiological thresholds for Atlantic salmon. For

each treatment (standard, large, reference), the proportion of all DO measurements

collected which fell below the critical production thresholds of limiting oxygen saturation

(LOS) and reduced feed intake were calculated.



28

Briefly, the LOS is considered a lower extreme for fish welfare and corresponds to the DO

level below which an individual can no longer regulate its metabolic rate, and if exceeded

can lead to death [29]. Similarly, feed intake is generally stable with declining DO until a

temperature dependent threshold is reached, below which feeding declines. Because

both the LOS and reduced feed intake thresholds are temperature dependent, the values

used for this analysis were based on the locally collected temperature profiles. Using the

findings for healthy, uninfected fish, feed intake was estimated to decline below 76 %

saturation, with an LOS of 47 % saturation [40, 41]. DO saturations greater than 76 %

were deemed suitable for salmon growth and welfare. These benchmark levels are

conservatively low, as fish in general in south-eastern Tasmanian waters, and specifically

during this study, were infected with amoebic gill disease which likely increases the

susceptibility of fish to low DO levels [82, 83].

RESULTS

DO saturations were highly variable throughout the study (Figure 3.2) and ranged from

57 % to 118 % in cages and 69 % to 134 % at the reference site. The water column was well

mixed from 0 to 16 m depth with regards to temperature and ranged from 15.3 ⁰C to 15.5

⁰C at the beginning of the trial and 16.9 ⁰C to 17.1 ⁰C at the end. On average, DO was

higher at the reference site (96 ± 0.03 %) than in either the standard (90 ± 0.02 %) or

large (89 ± 0.03 %) cages (mean ± SE). There was a small, but significant difference

between mean DO saturation in the large and standard cages (p = 0.037), but no

difference between positions among cages of the same size.

DO saturation decreased with depth in both cage sizes (p < 0.0001), but not at the

reference site (Table 3.2). The lowest average DO saturation, 82 ± 5 %, occurred at the 16

m depth in the large cages, as compared to 95 ± 5 % at the 16 m depth of the reference

site (mean ± SD). Of the 10 days included in the study, lowest daily mean DO occurred on

19 Dec 2015, which corresponded with a neap tide, where water flow was lowest (Figure

3.3). DO levels also varied with time of day (Figure 3.4). Similar patterns were recorded in

both the cages and at the reference site, where DO saturations increased throughout

daylight hours to a peak in the afternoon, after which they dropped through the night to

a minimum in the early morning (Figure 3.4).

Chapter 5 – Hypoxia reduces performance

29

Figure 3.2 – Dissolved O2 saturation in each cage and at the reference site throughout the trial from 14 - 24 Dec 2015. Low dissolved O2 levels known to reduce feed intake and growth in post-smolt Atlantic salmon are shaded in red[40]. Numbers in the upper right corner of plots correspond to cage numbers in Figure 3.1b.


30

Figure 3.3 – Mean daily dissolved O2 saturation in each cage type and at the reference site. Reference conditions are denoted by solid grey triangles, standard cages are solid black squares, and large cages are represented by open circles. Error bars represent 95% confidence internals. The grey shaded area in the center of the plot denotes a neap tidal cycle.

The majority of DO measurements collected during this trial were physiologically

suitable for Atlantic salmon post-smolt growth and welfare (Figure 3.5). No

measurements were recorded below the LOS for Atlantic salmon post-smolts as

calculated by [41]. Further, all measurements at the reference site were above levels

known to reduce feed intake, and less than 1 % of measurements in the standard sized

cages were below it. In the large cages, 5 % of all DO measurements were below the

level known to reduce feed intake. There was a clear pattern with depth in the

percentage of measurements that were below the reduced feed intake threshold. 1 and

4.5 m always had suitable DO conditions, whereas 8 m (3 %), 12 m (5 %) and 16 m (15 %)

had increasingly poor DO levels (Figures 3.2 & 3.5).


31

Figure 3.4 – Mean hourly dissolved O2 saturation in each cage type and at the reference site. Reference conditions are denoted by solid grey triangles, standard cages are solid black squares, and large cages are represented by open circles. Error bars represent 95% confidence internals. The grey shading denotes periods of darkness, while the unshaded area denotes daylight hours. Table 3.2 – Mean ± SD of recorded dissolved O2 saturations across the depth profile in each cage size and at the reference site.


32

DISCUSSION

As one of the primary determinants of fish metabolism, understanding DO dynamics in

aquaculture cages is critical to maximize production performance [24]. Our study

provides evidence that DO levels are lower in larger cages, but also demonstrates that

DO concerns need not prohibit the use of larger cages as long as ambient environmental

conditions are sufficient to support the reduced water exchange. Further, the continuous,

high-resolution DO dataset presented here provides new insights as to the distribution

and variability of DO in salmon cages, and highlights key parameters for consideration

when developing monitoring protocols.

Figure 3.5 - Percentage of collected dissolved O2 measurements which fall within identified

production thresholds: below dissolved O2 of maximum feed intake (red), within ideal conditions (blue) and super-oxygenated (green). The number in the upper right corner denotes cage size, and numbers on the left side identify measurement depth in meters.


33

Our study was conducted at full industrial scale, with stocking densities at the lower end

(≤ 4 kg m-3) of the range for modern production (up to 25 kg m-3). While mean DO

saturation only differed marginally between cage sizes, 90 ± 0.02 % (standard) and 89 ±

0.03 % (large), there were considerable differences at the lower extremes. Though 99 %

of all DO measurements in the standard cages were at levels suitable for salmon

production, almost one in six of the measurements at 16 m depth in the large cages were

at levels known to reduce feed intake and growth in healthy fish (Figures 3.2 & 3.5),

despite stocking densities being lower than or equivalent to those in the standard cages.

The observed pattern of decreasing DO saturation with increasing depth could explain

the lower DO in large cages, as they extended deeper than the standard cages, but this

pattern was only present in cages and not at the reference site (Table 3.2).

It has been well established that fish do not distribute themselves evenly throughout

cages, but rather alter their distribution and behaviour in response to a wide variety of

factors [50]. While some studies have observed avoidance of extremely poor DO

conditions[17, 18], evidence suggests that other environmental factors, such as

temperature and light, override behavioural avoidance of moderate DO levels known to

reduce feed intake and growth[19, 56, 84]. Such uneven distribution can result in intense

crowding and observed fish densities as much as 20× the stocking density [37]. These

findings suggest that the low DO measurements in the large cages are not simply a

result of the cages being deeper, but also the result of altered fish distribution and/or the

larger cage structure impeding water exchange. How fish utilize space in different size

cages and the impact of cage size on water exchange specifically, are topics that

warrant further investigation. Understanding the drivers behind sub-optimal DO

conditions would allow targeted mitigation measures, such as the addition of

supplemental oxygenation at the depths and times of greatest concern, or the use of

lights to optimize the distribution of fish biomass throughout the cage, to be

implemented effectively [53, 85].

Despite the lower DO levels in large cages, the majority of measurements collected

during this study in both cage sizes were at levels suitable for Atlantic salmon production

performance and welfare (Figures 3.2 & 3.5). Overall, DO levels displayed a high degree

of temporal and spatial variability, ranging from 57 % to 134 % saturation, and were

similar to conditions observed in previous studies [18–20].


34

Spatially, we observed a consistent pattern of decreasing DO saturation with increasing

depth inside cages (Table 3.2). This pattern is similar to conditions observed by on a

research farm [19], but the opposite to that observed on commercial farms in both

Norway and Canada [18, 20]. Although no universal mechanism driving DO distribution in

aquaculture cages can be pinpointed due to the many complex interacting forces

present, what is evident from these studies spanning three continents is that site specific

patterns exist. At each site, considerations such as differing oxygen solubility with

temperature, altered mixing patterns as a result of density gradients, and the specific

controlling factors affecting current velocity, direction and regularity must all be

considered to understand prevailing DO conditions [18, 20, 44].

Throughout this study, we also observed a high degree of temporal variability, with DO

saturation fluctuating both on daily and hourly timescales. Daily mean DO saturation

ranged from 87 % to 92 % in cages and from 94 % to 97 % at the reference site. DO levels

at the reference site were less variable, but followed the same daily trends as DO levels

in cages (Figure 3.3). Lowest daily mean DO in both cage sizes and at the reference site

occurred on 19 Dec 2015, which coincided with a neap tide. Neap tides, which occur just

after the 1st or 3rd quarters of the moon, are when there is the least difference between

high and low water, and thus minimal water movement. A previous study which

investigated the relationships between DO, current velocity and tide predictions found a

significant correlation between current velocities and DO conditions in salmon cages, but

no relationship with local tide predictions [18]. A major difference between their study

sites and that of this trial, however, is that water currents in the Huon estuary are

primarily tide driven whereas at their fjordal sites, current patterns were more complex

[18, 86]. Given the importance of tides in controlling currents at our study site, it is logical

that neap tides would coincide with lower DO conditions.

We also observed a distinct daily pattern to DO fluctuations. Broadly, DO levels

increased through the daylight hours to a peak in the afternoon (16:00 – 19:00), and

decreased throughout the night to a minimum in the early morning (6:00 – 10:00, Figure

3.4). The pattern was most pronounced at the reference site, but conditions in both cage

sizes also followed the same pattern.


35

While we do not have data to confirm this explanation, a likely possibility is that

photosynthesis by algae during daylight hours causes a daily increase in DO saturation,

and drawdown due to respiration without replacement at night creates a daily minimum

[48]. Although the precise pattern we observed in this trial is likely to be specific to farms

in the Huon estuary, the influence of daylight on DO conditions in cages has important

implications for farms considering site placements in high latitude areas that experience

light intensities too low for primary production during large periods of the year.

Failure to account for local DO conditions can result in reduced feed intake and growth,

increased susceptibility to disease and, in extreme cases, mortality [40–43, 65]. Our

results confirm the expectation that DO levels are lower in larger cages, but also

demonstrate that larger cage sizes can be used without impacting salmon production

performance or welfare when ambient DO conditions are sufficient, such as those

recorded throughout this study. However, in locations with lower rates of DO

replenishment, such as the conditions observed in Macquarie Harbour, Tasmania [17],

shifting to larger cages is not recommended. Even in this study, with low stocking

densities and high replenishment rates, limiting DO conditions occurred in the large

cages. Therefore, use of very large cages, such as Ocean Farm 1, or higher stocking

densities in the large cages studied here, present risks for salmon welfare and

production performance even at sites with high DO replenishment [79]. Further, though

the precise patterns documented here of decreasing DO with depth and during the night

may be site specific, they could have parallels in many marine cage aquaculture

situations. Together, this study illustrates the importance of site and time specific

considerations when developing monitoring protocols or considering alterations to

production strategy, such as larger cages.

Chapter 4 – Oxygen affects behaviour

36

Chapter 4

Oxygen gradients affect behaviour of caged Atlantic salmon (Salmo salar)

Tina Oldham1*, Tim Dempster2, Jan Olav Fosse3 and Frode Oppedal3

1Aquatic Animal Health Group, Institute for Marine and Antarctic Studies, University of

Tasmania, Australia 2Sustainable Aquaculture Laboratory – Temperate and Tropical (SALTT), School of

BioSciences, University of Melbourne, Australia 3Institute of Marine Research, Matredal, Norway

* Corresponding author: [email protected]

**Additional information has been provided in this chapter, which expands upon the published article

ABSTRACT

Dissolved oxygen (DO) conditions in marine aquaculture cages are heterogeneous and

fluctuate rapidly. Here, by temporarily wrapping a tarpaulin around the top 0-6 m of a

marine cage (≈ 2000 m3), we manipulated DO to evaluate the behavioural response of

salmon to hypoxia. Videos were recorded before, during and after DO manipulation at 3

m depth while vertical profiles of temperature, salinity, DO and fish density were

continuously measured. The trial was repeated four times over a two week period.

Temperature and salinity profiles varied little across treatment periods; however, DO

saturation was reduced at all depths in all replicate trials during the tarpaulin treatment

as compared to the periods before or after. In three out of four trials, swim speeds were

1.5-2.7 times slower during the tarpaulin treatment than the before or after periods.

Significant changes in vertical distribution of fish density and DO were observed between

treatment periods in all replicate trials; salmon swam either above or below the most

hypoxic depth layer (59 – 62 % DO saturation). In a regression tree analysis, the relative

influence of DO in determining fish distribution was 17 %, while temperature (39 %) and

salinity (44 %) explained the majority of variation. Our results demonstrate that salmon

are capable of modifying their distribution and possibly activity level in response to

intermediate DO levels, but that DO is not a primary driver of behaviour at the saturation

levels in this study.

Key words: hypoxia, dissolved oxygen, behaviour, Salmo salar, fish distribution,

aquaculture



37

INTRODUCTION

The energy yield of anaerobic glycolysis is only 10% that of aerobic metabolism [87],

thus animals depend on a consistent supply of oxygen from their surroundings to

achieve optimal performance. In the aquatic environment however, where diffusion

happens slowly and photosynthesis can only partially meet the metabolic demands of

organisms in the surface waters [22], dissolved oxygen (DO) concentration varies both

vertically and horizontally with changing light, temperature, currents [18], wind and

rainfall [33]. For these reasons, DO is a major limiting factor affecting the growth,

distribution and survival of fishes.

Hypoxia, defined in the marine environment as a drop in DO saturation which reduces

metabolic scope [22, 88], occurs naturally in coastal environments [89–91]. Poor DO

conditions are exacerbated in aquaculture cages due to restricted water movement,

nutrient loading and locally increased biomass [18–20, 37]; and are becoming more

common as global temperatures rise [92]. In extreme cases, acute hypoxia results in

mass mortality [93, 94]. In less extreme cases, sub-optimal DO concentrations result in

decreased growth, appetite, immune function, swimming performance and fish welfare

[42, 43, 50, 65, 95].

Fish utilize numerous strategies to mitigate the impacts of hypoxia, including

physiological adjustments, morphological adaptations, molecular defences and

behavioural modifications [22]. The most immediate strategies to minimize acute

hypoxic stress are behavioural adaptations such as avoidance, aquatic surface

respiration, air breathing and altered activity level [96]. Many species of fish can actively

avoid hypoxic conditions [90, 97, 98], but not all [96, 99]. For example, Atlantic cod

(Gadus morhua L.) did not avoid extremely hypoxic conditions when a normoxic refuge

was available [100], whereas in a similar trial rainbow trout (Onchorhynchus mykiss)

displayed avoidance behaviour beginning at 80 % DO saturation (17-19 ⁰C) [101]. Even

among fish that avoid reduced DO concentrations, the point at which behavioural

responses are initiated varies greatly with species, lifestyle and habitat [22, 102].


38

Uncertainty exists regarding the extent to which the world’s most farmed marine fish,

Atlantic salmon (Salmo salar), respond behaviourally to hypoxia. One field trial which

investigated the relationship between environmental parameters and vertical salmon

distribution observed no consistent response to DO, despite reaching levels as low as 57 %

saturation [19]. However, an alternate study at four commercial farm sites found that

salmon avoided specific depth ranges in the water column where lowest DO

concentrations (60 % saturation at 15 ⁰C) occurred [18]. Given that DO concentrations

reach severely hypoxic levels in commercial cages for extended periods of time [20, 44,

45, 50], and that commercially viable mitigation options are limited [37, 81, 103], it is

critical to know whether salmon avoid hypoxic areas for farmers to maximize welfare

and production performance.

Salmon in sea cages alter their distribution and behaviour in response to numerous

stimuli including light [52], temperature, salinity, feeding [50], water current velocity [51],

sound [54] and sea lice infestation level [55]. Given the myriad factors affecting salmon

in sea cages, experimental testing within the marine cage environment is required to

understand the behavioural trade-offs made by salmon in response to hypoxia and

other environmental factors. Here, we manipulated DO levels within a sea cage to

determine if salmon altered their behaviour to avoid areas of low DO concentration

among the other environmental factors which control their vertical distribution.

MATERIALS & METHODS

Experimental Setup

The experiment was performed in a research scale 12 m × 12 m × 29 m marine cage at

the Institute of Marine Research’s Solheim cage environment laboratory stocked at a

density of 7.67 kg/m-3 with 13,428 (mean mass = 2.4 kg) Atlantic salmon (Salmo salar). At

the 15-21 m depth band, below where the majority of fish were observed to aggregate

during preliminary observations, a tarpaulin was permanently attached to the cage net

to create a barrier to oxygen replenishment. To reduce DO below ambient levels and

create a gradient, the entire net cage was raised by crane until the tarpaulin surrounded

the upper 0-6 m depth band where fish schooled at high densities. During DO reduction

periods the total available cage depth was 14 m (Figure 4.1) with a stocking density of

15.34 kg/m-3.


39

For each trial, data were recorded during three periods: 40 minutes prior to raising the

tarpaulin (before), 60 minutes with the tarpaulin secured at the surface (during) and 40

minutes after the tarpaulin was dropped (after). Four replicate trials were conducted

between 30 October – 9 November 2015. All trials were performed in daylight between

09:00 – 16:00 and were timed to co-occur with slack tide to avoid deformation of the

cage.

Figure 4.1 - Diagrammatic sketch of cage setup during each of the three treatment periods: BEFORE (control), DURING (treatment) and AFTER (control).Throughout all trials and treatment periods, temperature, salinity and dissolved oxygen measurements were collected within the top 0 to 6 m of the cage. Vertical fish distribution was estimated by calculating relative echo intensities within the uppermost 6 m depth band during each treatment period. The white band represents the position of the 6m deep tarpaulin.

Though data were collected throughout the entirety of the cage, all analyses were

confined to the top 0-6 m depth band where the tarpaulin was located during treatment.

This strategy was chosen to minimize the potentially confounding effect of the tarpaulin

on fish behaviour. If the entire cage area is considered it is impossible to distinguish

between a response to the reduced DO concentrations within the tarpaulin and a

response to the tarpaulin itself. By focusing only on fish which are within the tarpaulin

area we are assured that any changes in distribution can be attributed to environmental

variations and are not a result of a response to the tarpaulin.

Environmental Variables

During each replicate trial, water temperature, DO and salinity were continuously

recorded by a CTD (SD204, SAIV AS) vertically profiling between 0 and 13 m at

0.6 m min-1 on an automated Belitronics winch. The CTD DO probe was calibrated prior

to the start of each trial.


40

Fish Density Measurements

Vertical fish distribution was quantified using an echo-integration system (Lindem Data

Acquisition, Oslo, Norway) connected to an upward facing transducer with a 15⁰ acoustic

beam positioned beneath the cage at a fixed depth of 30 m [104]. Echo intensity was

recorded once per minute in 7 cm depth intervals from 0-29 m. The sum of all echo

intensity measurements between 0 and 6 m for each minute was then calculated and

mean values of every 7 cm depth band were used to calculate relative echo intensity as

a measure of percent fish biomass. Mean echo intensity values for each 0.21 m depth

band between 0-6 m were calculated for all treatment periods (before, during, after).

Swimming Speed

Fish swimming speed was monitored using an underwater 360⁰ pan/tilt Orbit Subsea

camera controlled from the surface by a winch. Videos during each treatment period

were recorded at a depth of 3 m. Instantaneous swimming speeds were calculated as

body lengths per second (BL s-1) based on the time required for the snout and tail of an

individual to pass a vertical reference line within the cage [105]. Swimming speed was

calculated for 20 individuals haphazardly chosen per treatment period, totalling 240

individuals.

Data Analyses

For each trial, differences in vertical distribution between treatment periods of

temperature, salinity, DO saturation and fish density were tested for with two-sample

Kolmogorov-Smirnov tests. To correct for multiple comparisons, statistical

significance (α = 0.05) was determined at a Bonferroni corrected p-value of 0.007.

Instantaneous swimming speeds were compared using repeated measures ANOVAs.

Significant ANOVA results were further analysed using Tukey’s HSD (honest significant

difference) test for specific pair-wise comparisons. To determine the relative influence of

each environmental factor in explaining vertical fish distribution, data from all trials

during the oxygen reduction period were pooled and fish density was modelled as a

function of temperature, salinity and DO using a non-parametric regression tree method

[18, 19, 106]. Briefly, the single variable is found which best divides the data into two

groups based on reduction of relative error.


41

The data are separated and the same process repeated, separately, to each sub-group

until no further improvements can be made. Cross-validation is then used to ‘prune’ the

tree to the final model. In the graphical presentation, each split is seen as one stem

dividing into two branches. The branch to the left is the one written out in the split, and

the one to the right the opposite. Branch length is proportional to reduction in relative

error. The ‘leaves’ at the end of each terminal branch are predicted fish density.

RESULTS

Throughout all trials, a consistent pycnocline was observed with a cool, brackish (~10 ⁰C,

20 ppt) surface layer which transitioned to warmer seawater (~13 ⁰C, 30 ppt) at between

2-4 m depth. Temperature and salinity varied little between treatment periods, whereas

DO saturation was reduced by 10 % on average during the tarpaulin treatment as

compared to the before and after periods in all replicate trials (Table 4.1).

Table 4.1 - Range and variation of environmental conditions throughout the experiment.

Fish density observations of the entire 29 m deep cage area found that on average 81%

of the fish biomass swam shallower than 14 m prior to the tarpaulin being raised to the

surface, and that total fish density was lower in the top 0-6 m during treatment than

either before or after in all 4 trials. However, during all four trials, fish density in the 0-2 m

surface band was higher during tarpaulin treatment than in either the before or after

periods.


42

Analysis of variance tests on instantaneous swimming speeds detected significant

variation between treatment periods in 3 of the 4 replicate trials (F > 21.4, p < 0.001). In all

3 cases, swimming speeds were 1.5-2.7 times slower (p < 0.05) during the tarpaulin

treatment (range: 0.35 – 0.36 BL s-1) than the before or after periods (0.53 to 0.95 BL s-1)

(Figure 4.2).

Figure 4.2. - Mean ± SE of instantaneous swimming speeds (BL∙s-1) of Atlantic salmon before, during and after dissolved oxygen reduction treatment. The four replicate trials are represented by: 30-Oct; 2-Nov; 3-Nov; 9-Nov.

In the regression tree model, salinity and temperature had the largest relative influences

on fish density at 44% and 39% respectively, while DO was only 17%. Node 1 of the tree,

salinity < 28.47 ppt, explained the largest amount of variance; however, the surrogate

split of temperature < 12.58 ⁰C had 97% agreement with the primary split, suggesting that

both variables were critical drivers of salmon distribution within the cage. Of the 11 nodes

in the tree, 4 splits were attributed to salinity, 5 to temperature and 2 to DO saturation

(Figure 4.3). The most preferred environment was salinity > 30.43 ppt, temperature < 13.14

⁰C and DO saturation > 65.17%. In both cases where DO saturation was attributed a split,

higher levels of DO were the preferred condition.

0.2

0.4

0.6

0.8

1.0

1.2

Before During After

Bod

y le

ngth

s s

-1

Treatment Period


43

Figure 4.3 - Regression tree of relative fish density as a function of salinity (ppt), temperature ( ͦ C ) and dissolved oxygen (% saturation). At each node the variable/value causing the split is identified. Predicted relative fish density is noted at the end of each terminal branch. Branch length illustrates the reduction in relative error as a result of the previous split.

Trial 1

Environmental conditions between periods were the most variable during trial 1 with

significantly different distributions in both salinity and temperature (Figure 4.4). Vertical

distribution of fish density also differed significantly during each of the measurement

periods. In the period before tarpaulin treatment, lowest fish density was observed at the

surface and increased with depth. During the tarpaulin treatment, minimum fish density

occurred at 1.8 m and markedly increased with depth to a maximum at 6 m. In the period

after tarpaulin treatment, fish density distribution was bimodal with minimum density at

the surface and maximum density peaks at 2 m and 5.4 m (Figure 4.5).

Trial 2

Temperature and salinity distributions did not differ significantly between any of the

treatment periods (Figure 4.4). Vertical distribution of fish biomass was similar during the

before and after periods, with minimum fish densities occurring at the surface and

increasing with depth. During the tarpaulin treatment vertical fish distribution differed

significantly from the period after, with minimum fish density occurring at 3 m and

bimodal peak densities at 1 m and 6 m (Figure 4.5).


44

0

2

4

6

30 Oct 2015

0

2

4

6

2 Nov 2015

0

2

4

6

3 Nov 2015

0

2

4

6

50 60 70 80 90 100

9 Nov 2015

8 10 12 14 16 10 15 20 25 30 35

Dep

th (m

)

Dissolved oxygen (% saturation)

Temperature ( ͦC ) Salinity (ppt)

aba

aba

aba

aba

aaa

aaa

aab

aaa

aaa

ab

ab

ab

Figure 4.4 - Vertical profiles of dissolved oxygen (% saturation), temperature ( ⁰C ) and salinity (ppt) in a marine aquaculture cage before oxygen reduction (blue line), during reduced oxygen treatment (red line) and after returning to normal conditions (green line) for each of 4 replicate trials. Values are mean ± standard error. Significant differences between treatment periods in each plot are indicated by different letters (p < 0.007).


45

Trial 3

Temperature and salinity distributions were similar throughout all treatment periods

(Figure 4.4). Vertical distribution of fish biomass did not differ significantly during the

before and after periods, with minimum fish densities occurring at the surface and

maximum densities near 4 m. During the tarpaulin treatment, vertical fish density

distribution differed significantly from both before and after periods, with minimum fish

density occurring at 1.8 m and gradually increasing with depth (Figure 4.5).

Trial 4

Fish densities were only recorded during two treatment periods in the fourth trial due to

equipment malfunction. Temperature and salinity distributions differed significantly

between the tarpaulin treatment period and the period after (Figure 4.4). During the

tarpaulin treatment, minimum fish densities occurred in the top 4 m and increased

sharply to maximum density at 6 m. After the tarpaulin treatment, minimum fish density

occurred at the surface and increased with depth (Figure 4.5).

DISCUSSION

Behavioral Responses

When at the surface, surrounding the cage perimeter with a tarpaulin quickly and

consistently reduced DO saturations by as much as 20 % within a 60-minute period.

Using this technique, our results provide evidence that salmon have some capacity to

modify their behaviour in response to intermediate DO levels (59 – 78 % saturation) well

above the limiting oxygen saturation (39 ± 1 % at 12 ⁰C) [41] in a marine cage

environment. In all four trials, vertical fish distribution shifted during the DO reduction

treatment with movement away from the depths with the lowest DO concentrations and

an increase in fish density in surface waters.

While it is possible that factors other than DO which changed as a result of the tarpaulin

caused the observed changes in distribution, it is unlikely that such factors were more

important than DO. If fish were responding only to physical changes caused by the

tarpaulin, it would be expected that fish distribution would change in a similar fashion in

all four trials, as the tarpaulin was positioned the same every time. In contrast, though

the fish distribution did change in all four trials, it did not change in the same way. What

was consistent was that lowest fish density coincided with lowest DO levels.


46

However, whether salmon avoid depths within sea cages with lowest DO does appear to

be determined by whether a DO gradient is available within their preferred depth band

based on temperature and salinity, which override a response to intermediate DO

concentrations [50]. With a regression tree model that included temperature, salinity and

DO as predictors, the relative importance of DO in determining fish density was only 17 %,

compared to 44 % for salinity and 39 % for temperature. In a more holistic model which

considered all known determinants of fish distribution within sea cages, such as artificial

and natural light, hunger, water current velocity and social cues, the relative influence of

DO would be reduced even further.

Figure 4.5 - Depth distribution of Atlantic salmon (relative echo intensity) in a marine aquaculture cage before oxygen reduction (40 min), during reduced oxygen treatment (60 min) and after returning to normal conditions (40 min) for each of 4 replicate trials. Significantly different distributions between treatment periods within each trial are indicated by different letters (P < 0.007). Hatching indicates transitional periods during tarp movement.


47

The results of our manipulative experiment align with previous observations that salmon

remained in the warm surface waters of a cage despite DO saturation being 20-30 %

lower than in the deeper, cooler water [45]. During our trial, the heterogeneity of the

cage environment meant the width of preferred depth bands was quite small, however in

environments more homogeneous in salinity and temperature, as is typical of coastal

salmon farms, responses to DO may be more pronounced as they will seldom be

overruled by a pycnocline.

Given that previous work on healthy Atlantic salmon has suggested 70 % DO saturation

at 16 ⁰C as a threshold for reduced growth, and 60 % DO saturation a threshold for fish

welfare [65], we conclude that salmon have a limited capacity to align their swimming

depth with DO conditions which would maximize production performance. Testing

responses at lower DO concentrations, such as the sustained low saturations (26 – 52 %)

recently recorded on a commercial farm in Macquarie Harbour, Tasmania [44], is

required to determine if the relative importance of DO would increase with more extreme

reductions in DO concentration.

With regards to swim speed, behavioural reactions of fish which encounter hypoxic

conditions vary from no response to burst swimming depending on the species and

extent of hypoxia [22, 107]. Increased swim speed improves an individual’s likelihood of

encountering better conditions, but also increases O2 requirements. Alternatively,

reduced swim speeds in response to hypoxia minimize the fish’s O2 requirements, but

also reduces its chance of reaching more oxygenated water. In this study, a marked

decrease of instantaneous swim speed was observed during the reduced DO treatment

as compared to both the before and after periods in 3 of the 4 replicate trials. Though

the observed reduction in swim speed cannot be conclusively attributed to the change in

DO, as it could also be related to the presence of the tarpaulin or altered social

interactions as a result of the reduced fish densities, it is an interesting result for further

investigation.


48

The anadromous lifecycle of salmonids means that during some portions of their lives

the fish may find themselves in rivers [108] and estuaries [109] with low DO, little vertical

stratification and no choice but to carry-on. In such conditions, an increase in activity

level could be lethal, whereas a reduction may allow them to survive until better

conditions occur. Such an adaptation would likely contribute to the success of fish in

aquaculture given that the cage environment periodically limits their ability to escape

hypoxic conditions which will often improve with a changing tide [18].

Practical Implications

As global sea surface temperatures continue to rise and oxygen solubility decreases,

hypoxia is expected to become a more frequent occurrence globally [110]. The

knowledge gained from our experiment stresses the importance for the aquaculture

industry to continue developing mitigation and management practices which minimize

the occurrence and impacts of hypoxia on farmed salmon.

Potential mitigation measures include site selection to prioritize water movement so that

DO replenishment within cages is maximized [18], and farming in deeper areas where

there is increased distance between the cage bottom and decomposing organic matter

in benthic sediments [111]. Frequent fallowing which minimizes organic enrichment

beneath cages will also reduce biological oxygen demand and thus formation of deep

water hypoxia [112]. Further, if future research detects that salmon display more

pronounced avoidance of depths with poor DO conditions when other environmental

factors are uniform, then selection of locations with more vertically homogenous

temperatures and salinities could minimize the need for intervention.

Preliminary work has partially tested the benefits of supplemental aeration [103] and

oxygenation [81] in marine net cages. While these techniques improve DO conditions

within cages at some depths and in some conditions, further study and cost-benefit

analyses are required to optimize performance and assess feasibility at full commercial

scale.


49

Finally, the use of environmental stimuli to alter fish distribution within cages has proven

very successful [52, 54, 113]. Underwater lighting is commonly used to delay maturation

in salmon aquaculture. Recent studies have exploited lights for the secondary purpose of

attracting the school to cage depths with reduced parasite load [114]. The same

technique could be used to attract salmon away from hypoxic depth layers, or through

continuous movement of lights vertically at 1 m min-1 prevent the formation of hypoxic

layers by minimizing prolonged schooling at any one depth [53].

CONCLUSIONS

Fish in marine aquaculture cages are exposed to substantial environmental variation, but

are spatially restricted in their ability to adapt and respond to sub-optimal conditions.

The impact of hypoxia depends critically on which, if any, response is undertaken. Our

manipulative, field-based experiment provides evidence that Atlantic salmon are capable

of altering their behaviour in response to intermediate DO concentrations by seeking out

water layers with higher DO levels, and possibly with reduced activity level, but that such

responses can be overridden by other factors. These results confirm previous

observation-based studies that DO is not a primary driver of Atlantic salmon distribution

within marine cages [18, 19].


50

Chapter 5

Hypoxia reduces metabolic and swimming performance in Atlantic salmon

INTRODUCTION

As the oceans warm, O2 solubility, and thus availability for aquatic organisms, decreases

[115]. At the same time, metabolic rates, and therefor O2 demand, increase [116]. For the

ecologically and commercially important Atlantic salmon, both effective conservation

and efficient farming require understanding the physiological consequences of exposure

to hypoxic conditions.

In their natural habitat, the lifecycle of anadromous salmonids necessitates crossing

through coastal and estuarine habitats prone to hypoxia, with DO levels in spawning

streams recorded as low as 16% saturation (Sergeant et al. 2017). Similarly, all

environmental examinations of salmon aquaculture cages, spanning studies in Canada,

Norway and Australia, have detected hypoxic conditions (Chapter 1). A two week study in

Norway found that 25% of all DO measurements collected throughout a salmon cage

were below levels known to reduce feed intake and growth [84]. In a more extreme

example, hypoxic conditions were consistently present throughout an entire two month

summer study period in two Australian salmon cages, reaching a minimum of 21%

saturation and forcing the fish to remain within a 2 m depth band to survive [17, 44].

For salmon, all activities including locomotion, digestion, growth and reproduction, are

primarily fuelled by energy generated through aerobic metabolism - a process reliant on

O2 availability [29]. As such, the difference between the maximum rate of aerobic

metabolism (MMR) and resting metabolic rate, termed aerobic scope for activity (AAS),

is a valuable tool for examining the consequences of stress and environmental

disturbance [119, 120].

O2 demand, however, varies with many factors. In normoxia, the MMR of salmon is

largely dictated by temperature [39, 121], however as DO saturation declines MMR also

declines while SMR remains unchanged, leading to reduced AAS. As AAS declines,

energetic constraints force fish to minimize all activities non-essential to immediate

survival, including feeding and growth [38, 40, 43].


51

Studies of healthy, 300-500 g salmon found that at 19 °C DO levels as high as 77%

saturation led to reduced feed intake, while the limiting O2 saturation (LOS) required for

basic life support of a non-digestive, resting individual was as high as 55% [40, 41]. The

O2 requirements of sick or active individuals are even higher [122, 123].

In addition to environmental conditions, O2 requirements also vary with size. The

metabolic rate of animals increases with body mass according to the power function:

𝑌 = 𝑎𝑀𝑏

where Y is the metabolic rate, ɑ is a scaling constant, M is mass and b is a scaling

exponent (log-log slope). The ‘metabolic level boundaries hypothesis’ predicts that b

varies systematically among species according to environmental and lifestyle factors,

and is inversely related to an organisms metabolic activity level [124, 125]. The logic is

that in athletic species with higher maintenance costs (due to increased muscle mass,

respiratory surface area and heart size) the scaling of metabolic rate with body size is

limited by flux of waste and resources across surfaces (b ≈ 2/3), while in less athletic

species with lower maintenance costs, surfaces are not limiting and metabolic rate is

directly proportional to body mass (b ~ 1) [126]. Therefore, in athletic species such as

migratory salmonids, it is expected that smaller individuals would have a higher mass-

specific metabolic demand than larger individuals [126], and therefore be more

vulnerable to hypoxia [127].

Despite the physiology of salmon being well-studied, whether or not the metabolic and

performance impacts of hypoxia vary throughout the large post-smolt size range

remains unknown. To examine the metabolic and locomotor consequences of hypoxia in

salmon, we subjected replicate groups of post-smolts of three sizes (0.2 kg - small, 1.0 kg

- medium and 3.5 kg - large) to a standard Ucrit protocol in moderately hypoxic and

normoxic conditions at 16 °C while measuring O2 uptake. We hypothesized that swimming

performance of all sizes would be reduced in hypoxia owing to reduced aerobic capacity,

but that the small fish would be most severely affected as a result of metabolic scaling.


52

MATERIALS & METHODS

Animals

Hatchery-reared Atlantic salmon post-smolts were maintained in circular indoor tanks

(5.3 m3 volume) at the environmental laboratory of the Institute of Marine Research,

Matre, Norway in full-strength filtered and UVC-treated seawater (34 ppt) under a

natural photoperiod. A constant inflow of 150 L per minute from a large, thermally

regulated reservoir ensured high DO levels, removal of waste products and stable

temperatures. Salmon of all sizes were maintained at 16 °C for at least one month prior

to swim tunnel trials. Fish were fed size-appropriate commercial feed through automated

feeding devices.

Swim Tunnel Setup

We used a large Brett-type swim tunnel respirometer described in detail by Reference

128 and Reference 122. Briefly, the swim section of the tunnel was 248 cm long with an

internal diameter of 36 cm, providing a volume of 252 L. The volume of the entire system

was 1905 L. Water currents were generated by a motor-driven propeller with speed, in

rotations per minute, controlled through a frequency converter. An acoustic Doppler

velocimeter, mounted at the rear of the swim section, was used to find the relationship

between propeller speed and current speed in cm s-1. To maintain temperature and DO

levels, flushing of the tunnel was performed by opening a water inlet valve opposite the

swim section which received water from the same reservoir as the holding tanks.

A camera and O2 logger (RINKO ARO-FT, JFE Advanced Co., Ltd., Japan) were mounted

at the rear of the swim section to allow monitoring with no disturbance to the fish. The

respirometer was sterilized prior to beginning trials, and at the experimental mid-point

(day 9). No noteworthy background O2 consumption could be detected when the setup

was empty, and bacterial respiration was therefore considered negligible.

Experimental Protocols

The afternoon prior to measurements, fish were transferred from the holding tank to the

swim tunnel by hand net. During an overnight acclimation period of 15 hours, water

current speed was set to ~ 0.3 BL s-1 with moderate flushing to maintain stable

temperature and DO levels. The following day, for all treatments, the respirometer was

sealed and DO levels were allowed to drop until 45% saturation was reached.


53

The tunnel was then flushed for 10 minutes to reach either 95% (normoxic) or 55%

(hypoxic) DO saturation, at which point the swim trial commenced.

Critical swimming speed (Ucrit) was determined using a typical swim challenge protocol

[123, 129]. Water current velocity was increased stepwise, by approximately 0.3 BL s-1,

every 20 minutes until all fish were fatigued. Flushing was performed during the first 5

minutes of each speed, after which the system was closed and O2 uptake was recorded

for 15 minutes. Ucrit was determined for each individual in three size classes of fish (small,

medium and large) in hypoxic (45-55% DO saturation) and normoxic (85-95% DO

saturation) conditions. Fatigue was defined as when fish were lying against the rear grid

of the swim section and were unable to swim despite tactile stimulation.

Once fatigued, fish were rapidly removed from the tunnel and euthanized with a blow to

the head. Fork length and mass were recorded for all fish (Table 5.1). For the first two

and last two fish fatigued in each trial, blood samples were immediately drawn from the

caudal vein with a heparinized syringe and stored on ice until transfer to -80 °C. Control

blood samples were collected from 9-10 fish of each size class following anaesthesia with

Finquel MS-222 (10 mg L-1) to minimize handling stress.

DO measurements were recorded continuously, every two seconds, throughout all trials.

Group numbers for each size class were chosen so that total O2 uptake rates were

initially similar in all groups and high enough to provide a reliable trace within the test

interval (small = 27-31, medium = 7-10, large = 2). Three replicate tests of each size class

were completed in each DO treatment, except large, normoxic of which there were only

enough fish for two replicates (Table 5.1).

Calculations

Oxygen uptake rates (MO2) were calculated as the slope of a linear regression of DO

saturation through time during each closed period, which was then used to calculate the

mass-specific MO2. Only linear regressions with r2 ≥ 0.95 were used in the analysis. To

correct for the volume occupied by the fish in the tunnel, a density of 1 kg L-1 was

assumed. SMR was estimated by exponentially fitting MO2 as a function of steady

swimming speeds and extrapolating back to speed 0 [130].


54

MMR was defined as the highest MO2 measured which coincided with the current speed

at which the first group of fish reached fatigue, after which MO2 plateaued. In cases

where enough individuals remained to get a reliable DO trace after the first group

reached fatigue, the respirometer was re-sealed for the next speed increment. Absolute

and factorial aerobic scope (AS, FAS) were calculated as the difference or factor

between AMR and SMR, respectively. The metabolic size scaling exponent was estimated

as the slope of a least squares linear regression of the logarithmically transformed mean

SMR and mass of each size class in normoxic conditions.

Ucrit was calculated according to Brett (1964):

Ucrit = 𝑈𝑓 +𝑡𝑓𝑈𝑖

𝑡𝑖

Where Uf is the last completed current speed, tf is the time spent at the current speed of

fatigue, ti is the time interval at each current speed and Ui is the magnitude of each

speed increment. Overall, the large cross-sectional area of the tunnel (1017 cm2) and

video recordings of the fish behaviour meant that no adjustments were required for solid

blocking effects. The largest fish tested had a cross-sectional area of ~95 cm2, and only

overlapped briefly if the fish swimming in front became fatigued and was pushed to the

back of the tunnel. The small and medium fish did not exceed 10% of the tunnel cross-

sectional area even when two to three fish swam in parallel. Therefore, because the fish

tended to distribute themselves evenly throughout the tunnel at all but the slowest

current speeds, solid blocking was not corrected for [129].

The gross cost of transport at each swimming speed, expressed as mgO2 kg-1 km-1, was

calculated by dividing MO2 by the corresponding swimming speed. To determine the

minimum cost of transport (CoTmin), gross cost of transport was plotted against aerobic

swimming speeds and fit with a quadratic function. The swimming speed with the

minimum cost of transport, and thus greatest metabolic efficiency, was determined by

finding the vertex of the parabola.


55

Stress parameter analyses

For each blood sample, 1 mL blood was centrifuged at 3000 g for 5 min, and the resulting

plasma stored at -80 °C until further processing. Plasma lactate and glucose

concentrations were measured spectrophotometrically with a MaxMat PL, while cortisol

was quantified with an ELISA assay kit (IBL International GmbH).

Statistical analyses

Statistical analyses were performed in R version 3.2.0. All data were evaluated for

normality and homoscedasticity by the Shapiro-Wilk and Levene's tests, respectively.

To test for differences between treatment groups within each size class, 1-way ANOVAs

followed by Tukey’s HSD test were applied to the length, weight and stress parameter

data. Metabolic parameters (SMR, AMR, AS and FAS) were each evaluated as a function

of DO treatment and size using type III sum-of-squares 2-way ANOVA’s followed by

Tukey’s HSD test. Because the Ucrit data were not normally distributed, a type III sum-of-

squares 2-way ANOVA was performed on the rank transformed Ucrit values as a function

of DO treatment and size, followed by Tukey’s HSD test. When appropriate, a Bonferroni

correction was applied to account for multiple comparisons, with a significance level of α

= 0.05 for all tests. Data presented are mean ± SE unless otherwise stated.

RESULTS

Length, weight and density measurements did not differ statistically between the hypoxic and normoxic treatments in any of the size classes (Table 5.1). Table 5.1 – The length, weight, fish number and stocking density of each size group and treatment, as well as the number of fish sub-sampled for plasma. All data presented other than fish number (N) are mean ± SE.


56

Aerobic capacity

In normoxia, MMR was highest in the small fish and decreased with larger size (799 ± 31,

536 ± 16 and 438 ± 2 mgO2 kg-1 h-1, respectively). MMR was significantly reduced in

hypoxia, by > 120 mgO2 kg-1 h-1 in all sizes, while SMR (small = 196 ± 4, medium = 133 ± 4,

large = 71 ± 11 mgO2 kg-1 h-1) was unchanged. The calculated scaling exponents based on

the relationships between SMR/MMR and size are bSMR = 0.65 ± 0.04 and bMMR = 0.78 ± 0.05

(Figure 5.1).

Figure 5.1 – Metabolic scaling exponents based on the mean MMR and SMR values of each size class in normoxia.

The combination of stable SMR with reduced MMR in hypoxia resulted in reduced AAS

and FAS in all size classes (Table 5.2). AAS was reduced the least in the medium size

class (41%), and similar amounts in the large (63%) and small (62%) size classes (Table

5.2). In normoxia, mean FAS ranged from 4.03 ± 0.03 to 6.31 ± 0.96, but was reduced in

hypoxia to less than three in all sizes (Table 5.2, Figure 5.2).

Table 5.2 - Critical swimming speed (Ucrit), swimming speed of minimum cost of transport (CoTmin), absolute aerobic scope (AAS) and factorial aerobic scope (FAS) of each size class and treatment. Ucrit of large fish is not shown because some fish did not reach fatigue. Data are presented as mean ± SE (where applicable). * = p ≤ 0.05, ** = p ≤ 0.01, *** = p < 0.001


57

Figure 5.2 – Mean FAS of all replicates of each size class in normoxic (solid circle) and hypoxic (open circle) conditions. Swimming performance

MO2 increased with swimming speed in all sizes (Figure 5.3). In normoxia, absolute Ucrit

increased with size from 91 ± 0.7 cm s-1 in small fish (N = 88) to 98 ± 3.4 cm s-1 in medium

fish (N = 28). For the large fish, two reached fatigue at 92 and 127 cm s-1 in normoxia,

while two exceeded the maximum current speed the tunnel could generate of 140 cm s-1.

Therefore, while we could not determine a specific Ucrit for the large fish in normoxia, it

exceeded 124 cm s-1.

Figure 5.3 – Regression of the change in metabolic O2 demand with increasing current speed of the small (dotted line), medium (dashed line) and large (solid line) size classes. Data points show mean ± SE.


58

Hypoxia reduced Ucrit significantly, by 21 cm s-1 (N = 91) in the small fish and 9 cm s-1 (N = 23) in the medium (Figure 5.4, Table 5.2). Even in hypoxia, one of the large fish exceeded 140 cm s-1, while Ucrit of the other five were 81, 85, 95, 101 and 102 cm s-1, for an approximate average of > 101 cm s-1 (Figure 5.4). Relative Ucrit decreased with increasing size (Figure 5.4).

Figure 5.4 – Absolute (cm s-1) and relative (BL s-1) critical swimming speed (Ucrit) of each individual in normoxic (solid) and hypoxic (unfilled) conditions. Triangles denote individuals which outswam the 140 cm s-1 maximum speed of the tunnel.


59

Cost of transport was highest in the small fish at all measured speeds, and lowest in

large fish (Figure 5.5). The absolute speed of CoTmin was highest in large fish (67 cm s-1)

and decreased marginally with size to 52 cm s-1 in the small fish, whereas the relative

speed of CoTmin was highest in the small fish (2.0 BL s-1) and decreased with size (medium

1.3, large = 1.0 BL s-1). The swimming speed of CoTmin was not significantly affected by

hypoxia (Table 5.2)

Figure 5.5 – Gross cost of transport as a function of relative swimming speed in small (dotted line), medium (dashed line) and large (solid line) size classes. Stress response

In all sizes, plasma lactate concentrations were significantly elevated after normoxic

swim trials relative to controls, and significantly higher again after hypoxic swim trials

compared to normoxic (Table 5.1). In hypoxia, plasma lactate was lowest in the large fish

(8.1 ± 0.19 mmol L-1), but there was no significant difference between the small (22.2 ± 1.4

mmol L-1) and medium fish (21.2 ± 1.7 mmol L-1) (Table 5.1). Plasma cortisol was elevated

after swim trials compared to controls in all sizes, but hypoxic and normoxic treatment

had no effect on plasma cortisol in the small and medium fish (Table 5.1). In the large fish

which were exhausted, however, plasma cortisol was significantly lower at the end of the

normoxic trials (385 ± 22 ng mL-1) than hypoxic (732 ± 20 ng mL-1).


60

DISCUSSION

Acute exposure to moderate hypoxia, well above the estimated critical O2 level of 35%

saturation at 16 °C [40], significantly reduced aerobic metabolic capacity in salmon

ranging from 200 g to 3.5 kg, causing subsequent declines in swimming performance

irrespective of size (Figure 5.4, Table 5.2). The nature and implications of the reduced

aerobic capacity resulting from hypoxia exposure, however, varied with size.

Performance

While exposure to DO saturations of 45 - 55% did not affect the SMR of any group, it

caused a significant decrease in the MMR of all groups resulting in reduced AAS and FAS

(Figure 5.2, Table 5.2). As the primary energetic reservoir for activity, aerobic scope

limitation has cascading implications for whole organism performance. By reducing an

individual’s capacity to produce energy aerobically, hypoxia diminishes the resources

available for multi-tasking, and forces prioritization among numerous survival

determining activities [96]. Here, FAS was reduced from > 3.5 in all sizes to between 2.3 -

2.7 (Figure 5.2), bordering on the minimum required just for digestion and assimilation in

healthy salmon [131, 132]. Such a reduction of aerobic metabolic capacity, to less than

half of the measured capacity in normoxia in all sizes, resulted in concomitant declines in

swimming performance as measured by Ucrit (Figures 5.2 & 5.4).

In line with previous studies [133], small fish had the highest relative swimming capacity

in normoxia (max = 4.3 BL s-1) despite having the highest cost of transport, while medium

fish only achieved a maximum of 3.0 BL s-1 (Figure 5.4). In terms of absolute current

speeds relevant to migration and aquaculture, however, the larger fish outperformed

smaller individuals, a fact highlighted by our inability to exhaust multiple of the largest

individuals at the maximum current speed we could generate of 140 cm s-1, while Ucrit <

100 cm s-1 in both the small and medium fish in normoxia (Figure 5.4). Even in hypoxia,

one of the six largest fish tested outswam 140 cm s-1.

Conversely, previous work has shown that as routine MO2 increases so too does the LOS

below which salmon must switch to anaerobic metabolism [40, 41, 134]. The high SMR of

small fish, more than double that of the large (196 and 71 mg kg-1 h-1, respectively), with a

lower FAS, then suggests that small salmon are less hypoxia tolerant than larger

individuals.


61

While no other studies have examined the impacts of hypoxia across different sized

salmonids, Reference 135 found that similar hypoxic conditions to those used in this study

resulted in a 43% decline in maximum swimming speed of 20 g rainbow trout

(Oncorhynchus mykiss). Here, we observed that Ucrit was reduced by 23% in the small

fish, and only by 9% in the medium fish (Table 5.2). This would initially appear to be at

odds with the finding of Reference 136 that swimming performance of Atlantic salmon is

more dependent on O2 concentration than that of rainbow trout, however the much

smaller size of the fish used in Reference 135 could well explain the greater observed

impact.

Plasma lactate and cortisol response also varied with size. In all sizes plasma lactate, a

by-product of anaerobic metabolism, was higher after hypoxic swim trials than normoxic,

suggesting that in normoxic conditions swimming cessation was not the result of lactate

accumulation. In hypoxia, anaerobic metabolism, as evidenced by the lower MO2 in

hypoxic compared to normoxic swim trials at the same speeds, began at slowest speeds

(40 cm s-1 ) in the small fish and increased with size to 75 cm s-1 in the medium and 80 cm

s-1 in large fish (Figure 5.6). Further supporting the hypothesis that hypoxia tolerance

increases with size in salmon, plasma lactate concentration in the large fish which were

exhausted during hypoxic swim trials was less than half that of either the small or

medium fish (Table 5.1). This agrees with the explanation provided by Reference 127 that

the faster metabolic rate of small fish necessitates a faster rate of anaerobic glycolysis

in hypoxia to meet energetic requirements, and thus leads to faster lactate accumulation.

Cortisol, which serves many functions and is critical to seawater adaptation in fish, is

always present in low concentrations [137]. In stressful situations, however, such as

hypoxia, catecholamines are released which increase the permeability of gill surfaces

allowing for higher MO2, but which also stimulate excess cortisol production [138].

Elevated cortisol levels, in turn, divert metabolic resources from biosynthetic pathways

and suppress reproductive and immune functions [137, 138]. In this study, while plasma

cortisol concentrations were similar following hypoxic and normoxic swim trials in the

small and medium fish, more than four times higher than that of controls, cortisol levels

in the large fish were twice as high after hypoxic swim trials than after normoxic (Table

5.1).


62

Though caution is required when interpreting the blood parameter data of the large fish

due to small sample size, this finding suggests that although the performance impacts of

hypoxia exposure were most pronounced in small fish, the stress on large fish induced by

sub-optimal O2 levels during migration could have important implications including

reduced reproductive capacity and impaired immune response, and warrants further

investigation.

Metabolic scaling

For species with an active lifestyle, the metabolic level boundaries hypothesis predicts

that scaling of metabolic rate with body size is limited by flux of waste and resources

across surfaces, and therefore that bSMR ≈ 2/3 [124–126, 139]. However, as activity level

increases b should shift upward because metabolism is increasingly driven by resource

demand, which is limited by muscle mass, rather than by flux across surfaces which can

be temporarily alleviated through measures such as O2 storage and tolerance to waste

accumulation [140].

Based on swim tunnel respirometry of groups of similarly sized salmon, whose lifestyle

necessitates high locomotor capacity, we calculated a bSMR of 0.65 ± 0.04 which increased

to 0.78 ± 0.05 for bMMR, findings which align well with the aforementioned predictions [125,

126, 140]. As a result of this size-scaling, mass-specific metabolic demand decreases as

salmon grow, a pattern typical in fish [126, 141]. Here, AAS of the small fish (607 ± 23

mgO2 kg-1 h-1) was much higher in normoxia than either the medium or large (397 ± 7 and

365 ± 12 mgO2 kg-1 h-1, respectively). Upon initial examination, the much higher AAS of the

small individuals would seem to suggest they have the most substantial reserve scope

for energy production, and thus capacity to handle stressors such as hypoxia. However,

given that the energy required to perform aerobic functions is greater per unit mass in

smaller individuals [142, 143], as evidenced by the nearly six-fold difference in cost of

transport between the large and small size classes in normoxia (Figure 5.5), mass-

specific AAS is actually a misleading measure of capacity across varied sizes. FAS on the

other hand, which provides an estimate of energetic production capacity as a factor of

metabolic maintenance requirements (MMR/SMR), is a more informative measure to

compare scope for activity across a wide size range [32, 144]. Interestingly, FAS was

highest in the large size class in both normoxic and hypoxic conditions, despite being

potentially underestimated because several individuals did not reach Ucrit (Table 5.2).


63

Consequently, it then makes sense that of the two sizes in which we were able to

estimate Ucrit, it was the smaller fish with the lowest FAS in hypoxia which experienced the

largest decrease in swimming performance (Figure 5.4, Table 5.2).

Figure 5.6 – The change in O2 uptake rate with current speed of each size group in hypoxic (unfilled circles) and normoxic (solid circles) conditions. Data points show mean ± SE.


64

Conservation Implications

As higher temperatures raise metabolic maintenance costs and DO becomes an

increasingly limited resource in aquatic systems, salmon of all life stages are ever more

exposed to metabolically restricting conditions [145–147]. Instances of failed spawning

due to poor O2 conditions and/or high flows impeding migration have already been

observed on several occasions [148–150]. Our finding that small fish are more affected

by hypoxia exposure than large would seem to contradict the findings of Reference 149

that seaward migrating smolt could move through DO conditions much lower than larger

salmon migrating upstream. However, when considered in conjunction with Reference

136 finding that maximum swimming speed increases linearly with DO concentration, and

the knowledge that seaward travelling smolt passively drift with the tide while upstream

migration requires actively swimming against currents, it then makes sense that upward

migrating salmon would require relatively high DO concentrations to succeed [149].

Indirectly, aerobic scope for activity defines the energetic resources available for survival,

and as such is a critical driver of behaviour (i.e. boldness, activity level) and ecology (i.e.

foraging, habitat selection, predator-prey interactions) [151]. While most studies have

examined the relationship between metabolism and behaviour in groups of individuals of

similar size, we suggest that similar patterns of co-variation may exist as a result of

shifting metabolic profiles with size [152–154]. For example, numerous studies have

shown that individuals with high SMR grow more quickly in high resource environments,

but lose their advantage and are prone to risk taking in sub-optimal conditions with low

food or environmental stressors [152, 155]. Perhaps then, for salmon, while the high SMR

of smaller individuals confers the capacity for fast growth in times of plenty, the

energetic expense of foraging disruptions may make them more likely to increase

activity and risk taking behaviour when exposed to hypoxia, thus increasing vulnerability

to predation [96, 151, 156]. Conversely, larger salmon with low metabolic maintenance

costs have greater reserves and can afford to adopt a ‘wait it out’ response to reduced

O2 levels, as suggested in chapter 4 where large salmon were repeatedly observed to

reduce swimming speed during hypoxic conditions. So, while these hypotheses are

speculative, it is clear from these data that the changing metabolic profiles of salmon as

they grow will lead to differential impacts of hypoxia throughout their lifecycle, and may

have important ecological and evolutionary consequences which require study.


65

Aquaculture Implications

Larger cages designed to withstand the harsh weather of exposed environments

and hold as many fish as possible at a single location are currently the trend in salmon

aquaculture, but large cages present increased risk of hypoxia relative to current

farming practices [15, 79]. In what is currently a typical cage (52 m diameter, 20 m deep)

with a stocking density of 25 kg m-3, if the fish congregate within a 3 m depth band, as

has been previously documented [44], the observed fish density would be 167 kg m-3. In

contrast, in the most recently developed offshore cage which is 80 m in diameter and 50

m deep, if stocked at the same density and the fish congregate within a 3 m depth band

the observed fish density would be 415 kg m-3. Higher fish densities equal higher O2

demand. Therefore, though hypoxia in salmon cages typically coincides with times of

little water movement, as the industry moves towards using larger single cages at

offshore sites farmed fish may be simultaneously challenged by metabolically limiting O2

conditions and faster current speeds than what generally occur at protected farm sites

[15].

Our results show that, in terms of absolute current speeds, larger fish out-perform

smaller individuals, a fact highlighted by our inability to exhaust multiple of the largest

individuals at the maximum current speed we could generate of 140 cm s-1, while Ucrit <

100 cm s-1 in both the small and medium fish in normoxia (Figure 5.4). And while higher

resting metabolic rate, as observed in the small fish, is correlated with the ability to

digest a large amount of food quickly in normoxia [132], in hypoxic conditions it becomes

a liability. Reference 40 demonstrated that the increased metabolic rate resulting from

higher temperatures also increases maximum potential feed intake and growth;

simultaneously, as temperature and feed intake increase, so too does O2 demand. At

7 °C the maximum potential feed intake was 0.47% biomass and was sustained down to

DO saturation of 42%; at 19 °C however, maximum potential feed intake was nearly

doubled to 0.99% biomass, but was only able to be maintained down to 76% DO

saturation [40]. Similarly, the higher resting metabolic rate of small salmon mean they

will reach their reduced feed intake threshold at higher DO saturations than larger

individuals. Any stressors or disturbances, such as currents, disease, competition or

infection with parasites, which frequently occur and incur their own O2 expenses, increase

O2 requirements even further and alter how the available aerobic scope is apportioned.


66

Faced with dual challenges of the energetic demand required to swim against currents

and reduced aerobic capacity because of sub-optimal DO, growth will be impeded and

survival challenged without mitigation. Barriers could potentially be used to reduce the in

cage current speeds, but would reduce O2 replenishment rate and exacerbate hypoxia

[45, 46, 56, 73]. More promising are options which adjust fish behavior, such as

submerged feeding and lights which can be used to redistribute fish throughout cages,

reducing density and attracting them to areas with higher DO [53, 113, 114, 157, 158].

Supplemental oxygenation or aeration to increase mixing could also be used to reduce

hypoxic stress, but will be difficult to ensure that the O2 is distributed throughout the cage

where it is needed [81, 84, 85, 103]. Ultimately, the most effective strategy to maximize

production performance is to adopt a cautious management approach. Autumn

transfer, when hypoxic conditions are most likely, should be avoided with novel cage

designs and new sites. Further, given the results of this study, novel cage designs and

farming sites should be stocked with relatively large fish, which have greater FAS and

swimming capacity, at low stocking densities, until local DO and current speed dynamics

are well understood.

CONCLUSIONS

Hypoxia is an ever-present and increasing threat to all salmon, both farmed and wild.

These results show that moderate hypoxia of 50% DO saturation significantly reduces

aerobic capacity and swimming performance in Atlantic salmon. Further, due to their

elevated mass-specific metabolic demand and increased cost of transport, smaller post-

smolts are more susceptible to reduced DO concentrations than larger individuals.

Chapter 6 – AGD incidence & distribution

67

Chapter 6

Incidence and distribution of amoebic gill disease (AGD) – an epidemiological review

Tina Oldhama, Hamish Rodgerb and Barbara F. Nowaka*

a University of Tasmania, Nationial Center for Marine Conservation and Resource

Sustainability, Locked Bag 1370, Launceston, Tasmania, 7250, Australia b Vet-Aqua International, Oranmore Business Park, Oranmore, Co. Galway, Ireland *Corresponding author: [email protected]

ABSTRACT

Amoebic gill disease (AGD), first documented thirty years ago in sea-caged salmonids, is

an ever increasing global concern in finfish aquaculture. The result of gill infection by

Neoparamoeba perurans, clinical AGD has been observed in fourteen countries

distributed across six continents and in fifteen species of finfish. The greatest impacts of

AGD have been on farmed Atlantic salmon during the seawater grow-out phase. When

left untreated AGD has resulted in up to 80% mortality, and even mild infections reduce

production performance and fish welfare. This review summarizes and analyses three

decades of AGD research and outbreaks, with focus on the causal triad of pathogen,

host and environment.

Keywords: Amoebic Gill Disease, Neoparamoeba perurans, temperature, risk factors


68

INTRODUCTION

Amoebic gill disease (AGD) of sea-caged salmonids was first described in Tasmania,

Australia during the mid -1980s [159] and has since been confirmed in most salmon

producing regions [160]. In some cases, and in the absence of treatment such as the

Norwegian outbreak in 2006, AGD has resulted in mortalities of greater than 80% [161].

Amoebic gill disease is the most serious health challenge for the marine salmonid

industry in Tasmania, and in recent years has become a primary health concern in

Europe [162]. In Tasmania, control of AGD is estimated to increase the cost of production

of Atlantic salmon (Salmo salar) by 20% as a result of lost growth, mortality and

treatment expenses [163]. Estimated AGD-related mortality only based losses were USD

12.55 mln in 2006 in Norway and USD 81 mln in 2011 in Scotland [164]. Additional

economic losses due to AGD, which are difficult to calculate but no less significant, result

from impacts on feed conversion and the downgrading or rejection of carcasses.

AGD manifests clinically as lethargy, anorexia, congregation at the water surface and

increased ventilation rate [165, 166]. Preliminary diagnosis of the infection is often done

through scoring of white mucoid patches present on gills of infected fish [160, 162, 167],

and has been shown to be a good indicator of AGD when checks are performed by an

experienced individual [167, 168]. Confirmation of AGD can be either through observation

of epithelial hyperplasia, lamellar fusion and presence of inter-lamellar vesicles in

conjunction with amoebae containing parasomes in histological sections [160], or PCR of

gill swabs for Neoparamoeba perurans and their association with gross lesions [167, 169].

Numbers of gross and histological lesions are proportional to the inoculation

concentration of amoebae in tank cultures when inoculation concentrations are between

10 – 500 cells L-1 [170], but not at low concentrations between 0.1 -10 cells L-1 (A. Bridle et al.,

unpublished data).

CAUSATIVE AGENT: Neoparamoeba perurans

Neoparamoeba perurans Young et al., 2007 is a marine amphizoic amoeba (Amoebozoa,

Dactylopodida) which has been shown to be the causative agent of AGD world-wide

[171–174]. Neoparamoeba pemaquidensis, a species closely related to N. perurans, was

for many years regarded as the aetiological agent of AGD because it was consistently

isolated from diseased fish [165, 175], however numerous attempts to elicit AGD

experimentally using cultured gill-derived N. pemaquidensis failed [165, 176].


69

Neoparamoeba perurans was not discovered until 2007 when species specific

oligonucleotide probes were developed for a non-cultured gill derived (NCGD) amoebae,

N. pemaquidensis, and N. branchiphila on gill samples from AGD infected Atlantic salmon

and found that only the NCGD amoeba specific probe bound to AGD associated

amoebae while N. pemaquidensis or N. branchiphila were not detected [177].

Phylogenetic analysis based on 18S rRNA and 28S rRNA gene sequences showed that

the NCGD amoebae were separate from other members of the Neoparamoeba genus

and that the NCGD amoeba was a new species, now known as N. perurans. A

subsequent study tested retrospective samples from AGD outbreaks in four species of

fish divided amongst five different countries and found that consistently, since AGD was

first reported, N. perurans were the only detectable amoebae associated with gill lesions

[169]. In 2010, more than 20 years after AGD was first described in marine fish, cultured N.

perurans successfully induced AGD in naive Atlantic salmon [178]. The same N. perurans

clone, maintained in culture for 3 years, decreased in virulence through time, eventually

becoming completely avirulent after 200 passages [179].

Little is known about the biology of N. perurans beyond that they are free-living,

facultative ectoparasites. Neoparamoeba spp. [180] belong to the Vexilliferidae family of

naked, lobose amoebae which lack well-organized surface structures and possess one or

more Perkinsela amoebae (parasomes) - endosymbionts closely related to the flagellate

Ichthyobodo necator [181]. All species of the genus Neoparamoeba share the same

general ultrastructural characteristics, a clearly defined plasma membrane, endocytotic

vesicles and presence of an endosymbiont [165, 181–186] and cannot be differentiated on

the basis of their morphology or even morphometrics[177, 184]. Morphologically N.

perurans cells range from rounded, most often observed in stressful [187] or

crowded[186] conditions, to highly amoeboid with multiple extended pseudopodia [165,

178, 186, 188]. Spherical cells not stained with neutral red and not resistant to potassium

hydroxide or detergent have been observed in an N. perurans culture which was exposed

to adverse conditions: fresh water or DMSO [187]. Twenty percent of the spherical cells

could recover after a few hours in full seawater, and such cells have been interpreted as

pseudocysts [187].


70

Amoebozoa have been assumed asexual until sex is directly observed. This assumption

however has many flaws, foremost of which is the difficulty of culturing and observing

microbial eukaryotes. Recent reconsideration of published data has suggested that the

Amoebozoa lineage is anciently sexual. Sex has been confirmed or direct evidence

recorded in 7 of the 13 Amoebozoa orders, though Dactylopodida to which

Neoparamoeba spp. belongs is not one of them [189]. Thus the sexuality and complete

life cycle of N. perurans is yet to be resolved.

Given the plastic nature of naked amoebae morphology, species identification has

always been a challenge. Prior to the advent of reliable molecular tools for species

distinction Neoparamoeba were distinguished from the Paramoeba genus

morphologically based on the presence of organic microscales in the surface

ultrastructure [180]. While recent molecular evidence suggests the genera

Neoparamoeba and Paramoeba are are paraphyletic and could be synonymized [190],

this would be premature as the nuclear SSU rDNA is highly conserved and insufficient by

itself to formalize such a change [191]. Therefore, until more scaled amoebae are

sequenced and genes other than SSU rDNA are investigated, the evidence is insufficient

to change currently used nomenclature [181].

RESERVIORS OF Neoparamoeba spp.

Naked, lobose amoebae are ubiquitous in the marine environment – found in high

concentrations in a wide variety of habitats ranging from the open ocean to coastal

estuaries [192, 193]. A study of the surface microlayer of the North Atlantic estimated as

many as 1350 amoebae L-1 [194], while another study found between 3,000-23,000

amoebae L-1 on suspended oceanic macro-aggregates in the surface waters of the

Sargasso Sea [195]. The details of N. perurans natural distribution and reservoirs outside

fish farms have yet to be determined.

In 2010 a highly sensitive PCR assay for detection of N. perurans capable of detecting a

single 18S rRNA gene copy was developed [167]. Using this assay, water samples at 0.5

and 15 metre depths were tested at a variety of sites around Tasmania, both farmed and

unfarmed, within and outside sea-cages [167]. At all unfarmed sites, and on farms with

no record of AGD infection, all samples tested negative for N. perurans including gill

swabs.


71

In contrast, N. perurans was detected in water sampled in and near cages with AGD

infected fish, though concentrations were variable and showed no clear correlation with

gross gill pathology scores.

In a subsequent study the same method was used to analyse water samples from within

nine commercial salmon cages in southern Tasmania at five depths and three time

points (early autumn, late autumn, and early winter) totalling 135 samples [196]. Stocking

density, salinity and dissolved oxygen concentration were recorded and remained

relatively constant across all sampling periods, depths, and sites. Water temperatures

were also recorded and declined markedly throughout the study. Amoeba abundance

was highest during the early autumn with a mean of 4.7 ± 2.0 cells L-1; ranging from 0 to

62.3 cells L-1, concurrent with the most frequent freshwater bathing regime and highest

gross pathological gill scores. Depth was the factor most strongly correlated with

amoeba abundance in the early autumn sampling, with more amoebae in surface waters.

Distribution of amoebae with depth was not related to any of the environmental

parameters monitored as they were generally homogenous throughout the water

column. Many possible explanations for the surface concentration of N. perurans were

proposed, but the question cannot be resolved with currently available data. Work is

underway to investigate the relationship between amoeba concentrations and fish

swimming behaviour. Thus, though N. perurans have been detected at low

concentrations in seawater both on and off farms in Tasmania and Scotland [196], the

water column does not appear to be a significant reservoir for the AGD causing amoeba.

In an investigation of environmental reservoirs of N. perurans in America’s Pacific

Northwest, 40 Atlantic salmon were sampled, 20 from Puget Sound, Washington and 20

from Vancouver Island, British Columbia [197]. Additionally, adult sea lice

(Lepeophtheirus salmonis) were removed from salmon, benthic sediment samples were

collected from sites distributed between Puget Sound and Vancouver Island and samples

of marine invertebrates were collected from both within and external to farm sites.

Neoparamoeba perurans DNA was amplified from all 20 gill swabs of fish and several L.

salmonis samples collected in Puget Sound. This is similar to findings in Europe where

sea lice collected from farmed Atlantic salmon have tested positive for N. perurans using

PCR (H. Rodger, unpublished).


72

However, N. perurans DNA was not amplified in any of the gill swabs or L. salmonis

samples collected from Campbell River, B.C., and no N. perurans DNA was amplified from

any of the other marine organisms or sediment samples collected in the region [197].

However, the analytical method used in this study was not sensitive and re-analysis of a

few water samples from the site in Puget Sound confirmed the environmental presence

of N. perurans (A. Bridle and B. Nowak, unpublished). Unfortunately, retesting of all

samples was not possible. N. perurans was detected in association with parasitic isopod

Ceratothoa banksii sampled from Atlantic salmon farmed in Tasmania, but there was no

relationship between the presence of the amoebae on the isopod and AGD status of the

salmon [198]. This indicates that salmon ectoparasites are not a significant reservoir of

infection.

So far there is no evidence that wild fish are a significant reservoir of N. perurans. Neither

Neoparamoeba spp. nor AGD lesions were detected on gills of any of the 325 wild fish

despite 100% infection rate of farmed salmon tested at the same time [199]. These fish

representing 12 different species were caught from three commercial salmon farm sites

and three control sites at least 10 km from farms in southern Tasmania [199]. In other

studies a single blue warehou (Seriolella brama) opportunistically collected from within

an Atlantic salmon sea cage in southern Tasmania tested positive for AGD infection

[200], as well as wild lumpsuckers (Cyclopterus lumpus) and mackerel (Scomber

scombrus) sampled in sea pens of AGD affected salmon in Scotland (H. Rodger,

unpublished).

An extensive survey conducted in British Columbia used histology to examine the gills of

2,969 wild caught fish, 742 of which were on or near active salmon farms, and found no

evidence of AGD [165]. This survey included several wild Pacific salmon species – Chinook

salmon (82), chum salmon (32), coho salmon (48), sockeye salmon (15), pink salmon (12).

Additionally, 2,348 marine fish collected in Scotland and tested for N. perurans using PCR

were all negative with the exception of a single fish, a horse mackerel Trachurus

trachurus, which tested positive [201]. Based on these studies, wild fish do not appear to

be a significant reservoir of N. perurans.


73

Fish species which are being utilized as cleaner fish in European salmonid aquaculture

have also been affected by AGD. In 2013 AGD infection caused by N. perurans resulted in

low level mortalities of cultured ballan wrasse, Labrus bergylta, maintained in land based

tanks [202]. Additionally, another species of cleaner fish, Cyclopterus lumpus, have been

affected by AGD prior to any contact with farmed salmonids (H. Rodger, unpublished).

This suggests that commercially used cleaner fish could be a reservoir of the pathogen

on salmon farms, and that further investigation is needed to understand their role in the

AGD outbreaks.

Before N. perurans was described the distribution of Neoparamoeba spp. in the

environment was investigated using genus specific or even less specific methods. While

such studies are valuable as guidance to direct further research into the epidemiology of

AGD, they should be interpreted with caution because the results are not specific to N.

perurans.

Water samples were collected in both summer and winter, at various distances from sea

cages (inside, 0, 0.5, 240, 280, 750, and 1100 m), and at three different depths (0.5, 5.5,

and 11.0 m) examined the distribution of Neoparamoeba spp. in the water column both

temporally and spatially using a non-species specific immune-dot blot test [203].

Temperature, salinity, dissolved oxygen, turbidity, nitrite, nitrate and bacterial counts

were recorded for each sample. Neoparamoeba spp. densities were highest during the

summer and reduced with distance from the cages. Neoparamoeba spp. density was not

significantly associated with turbidity, temperature or bacterial counts [203].

Neoparamoeba spp. distribution in Tasmanian sediments was investigated by analysing

sediment samples from beneath actively utilized cages, fallowed cages, and reference

sites 150 m from the nearest cage [204]. Amoeba cultures were prepared from sediment

samples [192] and Neoparamoeba spp. identified by the presence of one or more

parasomes and reactivity with the non-species specific polyclonal antibody. Twenty-nine

of the 58 samples collected, including those from reference, fallowed and active sites,

contained Neoparamoeba spp. No relationships were observed between stocking state,

freshwater bathing regime, environmental variables and amoeba distribution or

prevalence.


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Samples at five different time points from 2 to 3 heavily fouled cages containing infected

fish on a commercial farm in southern Tasmania were collected to investigate the role of

biofouling as a reservoir for Neoparamoeba spp. [205]. Amoebae were cultured from

samples and confirmed as Neoparamoeba spp. using the non-specific polyclonal

antibody. Neoparamoeba spp. were present on all fouling organisms tested (amphipods,

ascidians, hydroids, bryozoans, mussels, unidentified biofouling aggregates, and biofilms)

except skeleton shrimp. Highest prevalence was observed on biofouling aggregates

(55%) and the solitary ascidian Ciona intestinalis (50%). A separate test of hydroids

(Ectopleura larynx) from AGD positive farms in Europe (Ireland) detected N. perurans

using PCR, however other fouling organisms have yet to be tested using a species

specific method (H. Rodger, unpublished).

RISK FACTORS

Since its initial identification in the Pacific Northwest of the United States in 1985, AGD has

proven to be a global and ever increasing problem in marine finfish aquaculture [165].

Confirmed outbreaks of AGD have resulted in losses in fourteen countries spread over six

continents (Table 6.1), with Iceland being the only major Atlantic salmon producing nation

for which there are no reports of AGD.

Many reports have speculated about the role of temperature and salinity in AGD

outbreaks, but when considered on a global scale it is difficult to discern trends. Initially

outbreaks in Tasmania were regarded as a summer problem when water temperatures

were between 12 – 20 °C [166], however by the year 2000 fish were requiring freshwater

bathing during winter in water temperatures of 10 °C [206]. Concurrently, similar

observations were made in Washington where AGD related mortalities were observed

during autumn at sustained water temperatures below 10 °C [206]. In more recent

outbreaks, AGD related mortalities have been recorded in temperatures as low as 7 °C

[161, 162, 207].


75

Table 6.1 - Species and geographic distribution of AGD. n/a – not available.

Species Country Impact Current Situation

Reference

Atlantic Salmon Salmo salar

Australia Tasmania

Up to 50% mortality

Recurring problem

Munday 1986, Douglas-Helders et al. 2001, Young et al. 2007

Canada – British Columbia

Minor Sporadic ICES, 2015

Chile Up to 53.8% mortality

Recurring problem

Munday et al. 2001, Nowak et al. 2002, Bustos et al. 2011, Rozas et al. 2012

Faroe islands No mortalities

First recorded 2014

A. K. Olsen 2015 (pers. comm.)

France Minor Sporadic Findlay et al. 1995, Rodger and McArdle 1996, Munday et al. 2001

Ireland Up to 10% mortality

Recurring problem

Rodger and McArdle 1996, Palmer et al. 1997, Young et al. 2008a, Rodger 2014

Norway Up to 82% mortality

Recurring problem

Steinum et al. 2008, Rodger 2014, Powell et al. 2015

Scotland Up to 70% mortality

Recurring problem

Young et al. 2008a, Rodger 2014

South Africa ~5% annual mortality

Project discontinued

Mouton et al. 2014

Spain Major

Cessation of farming attributed to AGD

Rodger and McArdle 1996, Munday et al. 2001

USA - Washington

Up to 21% mortality

Recurring problem

Douglas-Helders et al. 2001, Young et al. 2008, Nowak et al. 2010

Coho Salmon Oncorhynchus kisutch

USA Washington

~25% mortality

No longer farmed

Kent et al. 1988

Rainbow Trout Oncorhynchus mykiss

Australia - Tasmania

Up to 50% mortality

Marine farming mostly discontinued

Munday et al. 1990, 2001


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Chinook Salmon Oncorhynchus tshawytscha

New Zealand Minor Sporadic Findlay et al. 1995, Young et al. 2008a

Brown Trout Salmo trutta

France n/a n/a Munday et al. 2001, Rodger 2014

Turbot Scophthalmus maximus

South Africa ~5% annual mortality

Project discontinued

Mouton et al. 2014

Spain Up to 20% mortality

[182, 208–210]

Sea Bass Dicentrarchus labrax

Mediterranean n/a n/a Reference 182

Sharpsnout Seabream Diplodus puntazzo

Europe n/a n/a Reference 210

Ayu Plecoglossus altivelis

Japan 49.4% mortality

One time occurrence

Crosbie et al. 2010

Olive Flounder Paralichthys olivaceus

Korea n/a Sporadic Reference 211

Blue Warehou, Seriolella brama

Australia Tasmania

n/a n/a Adams et al. 2008

Horse Mackerel Trachurus trachurus

Scotland n/a n/a Stagg et al. 2015

Ballan Wrasse Labrus bergylta

Norway, Scotland & Ireland

Minor mortalities

Sporadic Karlsbakk et al. 2013 H. Rodger, unpublished

Corkwing Wrasse Symphodus melops

Norway n/a n/a Hjeltnes 2014

Lumpsucker Cyclopterus lumpus

Norway & Scotland

n/a n/a H. Rodger, unpublished

One factor which makes it difficult to observe trends in AGD outbreaks is the lack of host

specificity of N. perurans. Amoebic Gill Disease has been recorded in 15 finfish species of

11 different genera (Table 6.1). A focused analysis of the first reported AGD outbreaks in

Atlantic salmon suggests that temperature maxima may play an important role (Table

6.2).


77

The first and most consistent AGD infections reported were those affecting introduced

Atlantic salmon in Tasmania – a locality with no native salmonids and summer

temperatures near the upper tolerance threshold for the species [166]. A decade later

AGD infections were reported in Ireland, France and Spain following the hottest summer

on record up until that time [212]. Amoebic gill disease was then reported in Atlantic

salmon from Chile and Washington in 2001 [206, 213], a climatologically uneventful year.

However, it is worth noting that this was not the first observation of AGD in Washington

[165], but rather the first report of AGD in Atlantic salmon at that location. In Chile, AGD

was only reported as an incidental finding and the outbreaks with associated mortalities

occurred later during a particularly warm and dry year [172].

Five years later, in 2006, AGD infections were reported in Norway and Scotland [161, 214]

during what some researchers estimated was the warmest autumn in Europe since 1500

[215]. The mean monthly sea temperatures in Norway at the time were 3.5 °C higher

than average [161]. In 2010 AGD was then reported in farmed Atlantic salmon in South

Africa [173], and in 2011 major outbreaks again began in Europe, by 2012 reaching as far

as the Orkney and Shetland Islands [162]. Most recently, in 2014, an AGD outbreak was

reported in the remote Faroe Islands (A.K. Olsen pers comm.), a year which again broke

global records according to the U.S. National Climate Data Center – State of the Climate

report.

What all of these reports have in common, despite infections occurring over widely

varying temperatures, is that preceding temperatures were abnormally high for the

region (Table 6.2). These data suggest that though N. perurans appear to be ubiquitous

in coastal marine waters and potentially infectious over a wide range of temperatures,

what may be more important as a risk factor for AGD outbreaks is the thermal tolerance

of the host animal in question.

A field study investigating the relationships between environmental variables and AGD

prevalence over 2 years in southern Tasmania found significant correlations of AGD with

water temperature and salinity [168]. Peak AGD prevalence was recorded in mid-

summer (January) and a second, smaller peak in autumn (March-May). At one farm site

which was brackish throughout the study (surface salinity < 10 ppt), no amoebae were

ever observed in histological sections of the gills.


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However, AGD was recorded at a minimum temperature of 10.6 ⁰C and minimum salinity

of 7.2 ppt. In both cases AGD infection was established prior to the drop in temperature

and salinity.

Table 6.2 - Timeline of first reported AGD outbreaks in sea-caged Atlantic salmon. n/a – not available

Year (1st Record)

Country Temperature ⁰C Anomaly

Temperature ⁰C (max : min)

Reference

1985 Australia (Tasmania)

+1 20 : 12 Munday 1986

1995

Ireland +3 17 : 12 Rodger & McArdle 1996

France +3 n/a Findlay et al. 1995

Spain +1 n/a Rodger & McArdle 1996

2001 Chile 0 12 : 9 Nowak et al. 2002

USA - Washington

-1 12 : 9 Douglas-Helders et al. 2001

2006

Scotland +3 13.5 : 7.5 ICES 2007

Norway +3 14 : 7 Steinum et al. 2008

2010 South Africa +2 15 Mouton et al. 2014

2012 Scotland (Orkney & Shetland)

+3 n/a Rodger 2014

2014 Faroe Islands +2 n/a A. K. Olsen (pers. comm.)

2014 Canada +2 n/a ICES 2015 *Temperature anomaly data based on National Oceanic & Atmospheric Administration ‘Global Mean Land & Ocean Temperature Anomaly’ annual records – retrieved June 2015. https://www.ncdc.noaa.gov/temp-and-precip/global-maps/

https://www.ncdc.noaa.gov/temp-and-precip/global-maps/


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Salinity also plays an important role in AGD [168]. Neoparamoeba perurans are marine

amoebae and have low tolerance for freshwater. Initial studies in California found that

AGD was eradicated from tanks following a brief reduction in salinity [165], while similar

success was achieved in Tasmania by re-locating infected fish pens to an area with

heavy freshwater influx [166].

Though many reports of AGD do not include information on rainfall or salinity, those

which do often describe lower than average rainfall preceding outbreaks [166, 172, 212].

To this day the most utilized commercial treatment for AGD infected fish is freshwater

bathing [216]. However, recent data suggest that N. perurans has contractile vacuoles

which may allow them to adapt to changes in salinity [187]. Further research is needed to

understand the implications of these findings for AGD treatment.

MITIGATION OF AGD

The most effective measures utilized for the mitigation of AGD on commercial farms are

also the most straightforward. Salmon stocking density has a significant impact on

survival after amoebae challenge in laboratory tanks with morbidity beginning 6 days

earlier in tanks stocked at 5 kg m-3 as opposed to tanks stocked at 1.7 kg m-3 [217].

Similarly, in a farm experiment, AGD prevalence was greater in cages initially stocked at

1.7 kg m-3 than those initially stocked at 0.8 kg m-3 [218]. These findings are also

supported by anecdotal evidence from salmon farms in Tasmania where one company

reduced stocking density from a winter maximum of 12 kg m-3 to summer maximum of 8

kg m-3 [160]. For such reasons, intensification of salmon farming (including both increases

in stocking density and biomass farmed) has been proposed as a risk factor for AGD

outbreaks [219].

In addition to stocking density, cage environment also appears to play a role in AGD

progression. In a field study on two Tasmanian farms a significant negative relationship

was observed between the number of times nets were changed and prevalence of AGD

[168]. Similar results were observed in Europe, where heavily fouled pens or pens with

lower water exchange experience more cases of clinically significant AGD [162]. Regular

net changes can improve water flow and dissolved oxygen levels, thus maintaining an

overall healthier farming environment [220]. Additionally, biofouling may be a reservoir

of Neoparamoeba spp. [205].


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Observations of AGD outbreaks in Europe have shown that the more advanced the

disease, the more difficult it is to treat [162]. Caution is needed with regards to treatment

frequency - fish prophylactically bathed in freshwater showed significantly slower weight

gain over a period of five months than fish which were not, but that fish in cages rotated

amongst fallowed sites required less frequent AGD treatment than fish in stationary

cages [218].

As such, bathing frequency can be minimized through site rotation and should be

conducted based on a gill score threshold. Perhaps most significantly for AGD mitigation,

Neoparamoeba spp. can survive on the gills of dead fish for at least 30 hours and are

capable of both multiplying during that time and successfully colonizing the gills of dead

naïve fish [221]. For this reason, prompt removal of all mortalities is critical to minimizing

the spread and severity of AGD outbreaks.

TREATMENT OF AGD

If an outbreak does occur, at present there are only two commercially utilized

treatments for AGD: freshwater or hydrogen peroxide bathing. Freshwater bathing has

been used in Tasmania [159, 216], some areas in Ireland [222] and Norway [223], but is

unfeasible and/or cost prohibitive in some other AGD affected regions [162]. During a

freshwater bath fish are immersed in freshwater (3 ppt or less) for 2 to 4 hours before

being returned to standard seawater. The treatment greatly reduces the number of

amoebae present on gills and decreases the amount of excess mucus [224].

In Scotland, Ireland and Norway some commercial operations have had success using

hydrogen peroxide to control AGD in Atlantic salmon. Dosage levels of 1000 - 1400 mg L-1

for 18-22 minutes were utilized and effective at low temperatures. At temperatures above

13.5 °C, or if fish gills have scores of 3 or greater, peroxide is not a safe or recommended

treatment option [162, 188].

Many alternative treatment options have been tested with varying degrees of success

(Table 6.3), however so far none have been adopted for commercial use. Considerable

research has been conducted investigating immunostimulants and experimental

vaccines [225, 226], however most had little effect on survival of AGD infected fish.


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Commercial Protec Gill diet developed by Skretting Aquaculture Research Center showed

promising results in vitro and in vivo AGD challenges including reduction of mortalities.

Table 6.3 - Results of AGD treatment studies in Atlantic salmon

Treatment Delivery Method

Dosage Result Trial References

freshwater bath < 3ppt, 2-4 h

reduced number of amoebae on gills by 86 ± 9.1%, returned to pre-bath levels after 10 days; prophylactic bathing reduced growth but not mortalities

field [224], [218]

softened freshwater

bath artificially softened water

soft water reduced number of gill amoebae and percent gill filaments with AGD lesions significantly more than hard water with longer lasting effects

field [227]

hydrogen peroxide

bath

1000-1400 mg L-1 in seawater for 18-22 minutes

effectively controlled AGD, however toxicity elevated at temperatures > 13.5⁰C and gill scores ≥ 3

field [162]

hydrogen peroxide

bath

1250 mg L-1 in seawater for 15 minutes

effective to treat light AGD infection, overall morbidity of 6.5-7.1% at 12 & 18 ⁰C

in vitro & tank

[188]

chlorine dioxide bath

25-50 mg -1 added to 6 h freshwater bath

minor improvement compared to freshwater alone

tank [228]

chloramine-T bath

10-50 mg L-1 in 6 h freshwater bath

minor improvement compared to freshwater alone

tank [228]

chloramine-T bath 10 mg L-1 in seawater for 1 h

amoeba numbers reduced, but gill lesion prevalence significantly higher than in freshwater treatment

field [229]


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formalin bath

200 ppm in seawater for 30-60 minutes

results equivocal, reinfestation rapid

field [212]

levamisole bath

1.25 - 5 ppm in freshwater bath

significantly reduced lesions up to 4 weeks post exposure compared to freshwater alone

tank [230]

levamisole bath

2.5 - 5 mg L-1 in freshwater bath

no benefit compared to freshwater alone

field [168]

potassium permanganate

bath 5 mg L-1 no benefit tank [231]

bithionol bath 1 mg L-1 for 1 h in seawater

reduced amoeba numbers & percent lesioned filaments, toxic at higher concentrations

tank [232]

narasin oral 50-60 mg kg -1 for 7 days

reduced lesions, palatability problems

tank [233]

L-cysteine ethyl esther

oral

52.7 mg kg-1 for 2 weeks pre-challenge

significantly delayed progression of AGD; palatability ~65% of control feed

tank [227]

bithionol oral 25 mg/kg -1

significantly delayed onset & reduced severity of AGD infection

tank [234], [235]

N-acetyl cysteine

oral 8g kg -1 no benefit tank [236]

garlic extract n/a

10 g L-1 monitored over 24 hours

significantly reduced cultured and gill derived amoeba numbers within 6 hours

in vitro

[237]

metronidazole n/a

0.1 - 100 mg L-1 monitored over 24 h

no effect relative to seawater controls

in vitro

[237]


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Selective breeding for AGD resistance has been investigated, and initial studies

demonstrated heritable genetic variation in AGD susceptibility in regards to both survival

and gross gill pathology [238–240]. Specifically, AGD resistance manifests in distinct

ways: resistance of naïve fish to initial infection and adaptive resistance developed

during reinfection [163]. The adaptive resistance trait, determined to have greatest

heritability and economic value, has been incorporated as a primary component of the

Tasmanian breeding programme and is expected to extend average bath interval by 3%

per year [163]. Molecular genetic methods of selection are also being considered [241]

but have not yet been adopted.

Recent trials in Tasmania demonstrated considerable improvement in AGD resistance of

brown trout x Atlantic salmon hybrids. Specifically, during six months in sea cages

subjected to natural AGD challenge, Atlantic salmon required freshwater bathing four

times and hybrids needed bathing only once while maintaining comparable survival and

growth rates to Atlantic salmon [242].

KNOWLEDGE GAPS

At present there are many gaps in our knowledge of N. perurans and AGD. To assess the

risk of future outbreaks we must develop a better understanding of the biology of N.

perurans and relationships between amoeba concentrations and environmental

variables such as salinity, temperature, bacterial load, turbidity and dissolved inorganic

nutrients. Distribution of N. perurans in the farming environment should be assessed.

Available qPCR techniques could be used to determine if N. perurans is present among

the Neoparamoeba spp. detected in biofouling and sediments and if those reservoirs are

significant. Relationship between net cleaning and AGD should be investigated.

Treatments other than freshwater or hydrogen peroxide should continue to be

investigated and if successful trialled at a commercial scale. Our current experience

suggests that the development of a vaccine against this disease remains a significant

challenge for the near future. While there is considerable success with selective breeding

for AGD resistance, we have limited knowledge on how host population characteristics

(for example stock type, smolt type or ploidy) affect AGD outbreaks.


84

All experimental studies except one [226] and most field studies investigated AGD in

isolation from other diseases. However, co-infections are not uncommon on farms and

can have synergistic effects on the host or reduce the effects of immunomodulation or

treatment. There is a lack of understanding of those interactions. Furthermore,

preventative measures and treatment of the other disease can affect outcomes of AGD.

For example, given the use of cleaner fish in the Atlantic salmon industry for control of

sea lice and the potential of cleaner fish as a reservoir of N. perurans, further research

should be conducted into polyculture as a risk factor for AGD. Additionally, potential

impacts on AGD of alternative strategies against sea lice, such as ‘snorkel cages’ and use

of lights [54, 114], which encourage fish to spend more time in deeper waters should be

investigated.

AGD continues to cause economic losses to salmon producers. While in the past it

affected only a few geographical areas, the disease is now being reported worldwide.

Global expansion and intensification of aquaculture and climate change will most likely

increase the risks. There is a need for development of cost-effective and novel

management and treatment strategies for AGD. Further investigation of the pathogen

and disease is essential to reduce the costs of AGD and ensure sustainability of salmon

industry.

Chapter 7 – Hypoxia alters AGD progression

85

Chapter 7

Cyclic hypoxia alters the progression of Amoebic Gill Disease

INTRODUCTION

Though widely used in aquaculture, marine cage farming poses unique challenges for

fish; they are exposed to all of the dangers and variation of nature, but are confined and

thus have limited capacity to respond [18, 19]. Highly variable and difficult to monitor, DO

in particular is a mounting concern during the seawater grow-out phase of salmon

production. Metabolically limiting DO conditions, termed hypoxia, have been detected in

Atlantic salmon (Salmo salar) cages around the world, and are predicted to increase in

frequency and severity as the global climate warms [20, 81, 84, 146]. In the wild, evidence

suggests that salmon avoid areas with low DO [109]. In marine cages however, their

response to low DO is mixed. When faced with severely hypoxic conditions, at or below

the point at which they would be forced to switch to anaerobic metabolism (< 30% DO

saturation), salmon in two Tasmanian cages prioritized avoidance of the most hypoxic

areas above other environmental and social factors [17]. However, in the majority of

marine cage studies, salmon remained in moderately hypoxic waters, at levels known to

reduce feed intake, growth and immune competence, despite other areas of the cage

having higher DO [18, 56, 84].

Given the frequency of occurrence and regular exposure of salmon to hypoxia, our

understanding of how such conditions influence susceptibility to disease is inadequate

[243]. All activity is limited by the availability of energetic resources; locomotion,

reproduction, foraging, digestion and growth all require energy. In salmon, the primary

means of energy generation is aerobic metabolism, a process which requires DO [24].

When the amount of environmental DO available is insufficient to meet metabolic

demand, any activity not essential to immediate survival is minimized [29]. In moderately

hypoxic conditions (45 – 55% DO saturation @ 16 °C), the aerobic scope for activity of

Atlantic salmon post-smolts was only 38% of what it was in normoxia (85 – 95% DO

saturation), effectively reducing the energetic resources available by 62% (chapter 5).

More extreme hypoxia would decrease aerobic scope even further.


86

As aerobic scope declines, energetic prioritization becomes necessary. One of the

primary responses to stress in fish is increased circulating levels of the hormone cortisol

[43, 95]. In resting conditions cortisol maintains homeostasis; in stressful conditions,

however, cortisol mobilizes energetic resources by enhancing gluconeogenesis while

suppressing reproductive functions and immune response [137]. In post-smolt salmon,

acute exposure to 50% DO saturation for just one hour caused a five-fold spike in

plasma cortisol which lasted several hours [65]. Further, from exposure to chronic

hypoxia, post-smolt salmon exhibited significantly lower or delayed expression in several

immune related genes which carried on through 58 days of exposure despite cortisol

levels returning to normal [95]. Similarly, exposure to moderate, intermittent hypoxia,

mimicking conditions observed in marine cages, led to significantly reduced leucocyte

function and thus putatively weakened innate immunity throughout a 47 day study [43].

In several non-salmonid species, evidence suggests that the stress and reduced immune

competence caused by hypoxia exposure result in increased susceptibility to disease. For

example, while no Nile Tilapia (Oreochromis niloticus) maintained in normoxic conditions

died as a result of injection with Streptococcus agalactiae, 80% mortality occurred in fish

exposed to sub-lethal hypoxia for 24 hours prior to infection [244]. Similar results were

observed in Channel Catfish (Ictalurus punctatus)- groups exposed to two hours of sub-

lethal hypoxia immediately prior to infection challenge with the bacteria Edwardsiella

ictaluri experienced significantly higher cumulative mortality (36%) than those

maintained in normoxic conditions (12%) [245].

The influence of hypoxia on disease susceptibility in Atlantic salmon, however, remains

unclear. In salmon challenged with infectious pancreatic necrosis virus, onset of disease

and mortality occurred much earlier in fish with slow-release cortisol implants than those

without, but cumulative mortalities at the end of the 45 day trial were similar [246],

suggesting that elevated cortisol levels may alter disease progression but not prognosis.

In contrast, a trial which exposed salmon to constant, mild hypoxia (60 – 65% saturation

@ 12 ⁰C) beginning 2 days after exposure to salmonid alphaviruses (SAV) found no

differences in the progress or development of disease over a 70 day period following

infection [247].


87

Even more intriguingly, when a slightly different question was asked and salmon were

exposed to 4 hours of hypoxia at 4, 7 and 10 weeks post-infection with Piscine

orthoreovirus (PRV), no difference in infection level or histopathology was observed

between groups at any time-point; however, during peak pathology, the hypoxia

tolerance of hypoxia exposed infected fish during an acute challenge was the same as

un-infected controls, and significantly better than the PRV infected fish maintained in

normoxic conditions [248]. No studies have investigated the influence of periodic,

moderate hypoxia, similar to conditions in marine cages, on disease susceptibility and

progression in salmon.

Many pathogens threaten salmon during the seawater production phase, but the

cosmopolitan distribution of amoebic gill disease (AGD), having caused losses in every

major salmon producing country, makes it one of the biggest threats to salmon welfare

globally [82]. Caused by Neoparamoeba perurans, a parasitic amoeba, AGD results in up

to 80% mortality when left untreated [161]. AGD is characterized by epithelial hyperplasia

and lamellar fusion of gills, resulting in compromised gill function and reduced aerobic

scope [122, 249]. Given the focused pathological impact of AGD on gills, the potential role

of hypoxia on disease susceptibility and progression is of particular interest.

Here we tested the hypothesis that exposure to cyclic, moderate hypoxia would alter the

progression of AGD compared to fish maintained in normoxia.

MATERIALS & METHODS

Animals & Husbandry

On 24 May 2017, 200 Atlantic salmon smolts were transferred from a commercial

hatchery (Huon Aquaculture Company, Lonnavale, Tasmania) to the University of

Tasmania’s aquaculture research facility (Launceston, Australia). Fish were randomly

distributed between eight independent 650 L recirculation systems, resulting in 25 fish

per system. Each system consisted of a 300 L holding tank and 350 L sump. Throughout

the trial, all fish were held on a 12:12 light/dark cycle and fed in excess twice daily at

08:30 and 18:30. For the first seven days following transfer, fish were maintained in

freshwater at 15 ⁰C to allow for acclimation to the new systems. From the 5 June to 24

July 2017, temperature and salinity were gradually increased in all systems until the

experimental conditions of 18 ⁰C and 35 ppt salinity were reached.


88

Temperature, DO saturation and salinity were checked daily in each system using an

OxyGuard Handy Polaris 2 (OxyGuard A/S) and refractometer, respectively. Nitrate,

nitrite, total ammonia and pH were regularly tested and maintained in freshwater at NO3

≤ 80, NO2 ≤ 0.25, NH3 ≤ 0.25 mg l-1 and pH = 7.0 and in seawater at NO3 ≤ 160, NO2 ≤ 5.0,

NH3 ≤ 3.0 mg L-1 and pH = 8.1. On 19 July 2017, all fish in two systems were anaesthetized

with 20 mg L-1 clove oil and randomly redistributed throughout the remaining six systems,

resulting in five systems with 33 fish each, and one system with 32 fish. Throughout the

acclimation period, DO in all systems was ≥ 90 % saturation..

Hypoxia induction

On 28 July 2017 the cyclic hypoxia regime commenced (day -12), with triplicate systems

for each of two treatments assigned in a randomized block design. A control group of

three systems were maintained at ≥ 90 % DO saturation (normoxic treatment), and three

systems were subjected to cyclic hypoxia (hypoxic treatment). DO loggers (RBRsolo)

were placed centrally at the same location in each tank and recorded DO saturation

once every five minutes throughout the trial.

Daily, at 09:00, the pumps were turned off and circulation discontinued in all six systems.

In the three normoxic treatment tanks, aeration supplied through a ceramic bubble

generation system was set to the minimal flow rate required to maintain DO ≥ 90 %

saturation. In the three hypoxic treatment tanks, aeration was discontinued and DO

allowed to drop until 50% saturation was reached, at which point aeration was restored

at the flow rate required to maintain hypoxic conditions [65]. Because aeration was

manually controlled, DO during hypoxic periods fluctuated, but was held between 40 to

60% saturation. At 18:30 all pumps were turned back on and circulation restored,

returning all systems to ≥ 90 % DO saturation.

Amoeba inoculation

Gills removed post-mortem from a salmon held in an AGD infection tank were used to

isolate N. perurans (University of Tasmania, Launceston, Australia) as described by [170].

Amoebae were enumerated and tested for viability following the procedure utilized by

[250].


89

On 9 August 2017 (day 0) all amoebae were pooled and divided evenly into six flasks

containing 400 mL of filtered seawater. At 11:00 circulation was discontinued, the water

volume in all six systems reduced to 80 L, and amoebae were simultaneously added to

all systems resulting in an inoculation dose of 1200 cells L-1. Throughout the inoculation

period, aeration was at maximal flow in all systems and DO saturation was ≥ 90 %. At

17:00 the pumps were turned on, all tanks returned to 300 L volume and circulation

restored.

Sampling protocol

Fish were not fed for 24 hours prior to sampling. On day 2, 48 hours after inoculation with

N. perurans, the first non-lethal sampling was performed. Twelve live fish were

transferred by hand-net from their tank into a 100 L bin with light anaesthetic (20 mg L-1

clove oil) and aeration. After 10 minutes, two fish at a time were transferred into a bin

with full strength anaesthetic (40 mg L-1 clove oil) and aeration. When fish became

unresponsive to touch they were removed from the bin and a single swab, with a ¼

rotation between each arch, was swept across the front of all four arches in the left gill

basket. Swabs were immediately placed in 500 L lysis solution (7.8 M Urea, 0.5% SDS, 10

mM Tris and pH 7.5). After sampling, each fish was marked on its dorsal side just above

the anal fin with a sub-dermal injection of alcion blue dye and returned to its tank.

Normoxic systems were sampled first, the water changed in both anaesthetic baths, and

then the hypoxic systems were sampled.

On day 7 a 2nd non-lethal sampling was performed and the left gill arches of all surviving

unmarked fish were swabbed using the above procedure. Hypoxic systems were

sampled first, the water changed in both anaesthetic baths, and then the normoxic

systems were sampled.

Due to an accelerating mortality rate, the final sampling was performed 10 days post-

infection (Figure 7.1). All surviving fish were pre-anaesthetized with 20 mg L-1 clove oil

before being transferred to a bin with full strength anaesthetic of 40 mg L-1 clove oil. For

each individual, fork length and weight were measured and skin, fin and eye condition

were scored from 1-3. Fish were then killed by cervical transection and the right gill

basket was removed.


90

The 2nd right arch was stored in 750 mL RNA stabilization reagent (25 mM sodium citrate,

10 mM EDTA,10 M ammonium sulphate and pH 5.2), and the 3rd and 4th right arches

placed in Seawater Davidsons fixative for 36 hours before transfer to 70% ethanol.

Twenty-four hours before DNA extraction, arches were transferred from RNA

stabilization reagent into 1 mL lysis solution and stored at 4 ⁰C. Because time of death

was unknown, no samples were collected from fish which died outside sampling events.

Figure 7.1 – Experimental timeline. Fish were acclimated to experimental tanks and conditions of 18 ⁰C and 35 ppt salinity for 65 days prior to the start of the experiment. Diel cycling hypoxia began in the treatment tanks (dashed line) 12 days before inoculation with N. perurans, while control systems (solid line) were maintained in Normoxic conditions throughout.

Lesion morphometry

Following fixation, macroscopic images were taken of the anterior surface of the 3rd right

arch and used to assess lesion number and surface area. Gill arches were photographed

submerged in a 70 % ethanol solution against a white grid background with fixed lighting.

Using the wand tool of the ImageJ software program, total visible gill surface area and

the surface area of all lesions were measured [251].

N. perurans enumeration

DNA was extracted from all samples (arches & swabs) using the same protocol. After

vortexing, 250 µL of sample solution was combined with 250 L lysis solution and 2 L

proteinase K (20 mg mL-1). The mixture was then incubated at 37 ⁰C for 30 min. After

incubation, samples were chilled on ice for 5 min, combined with 250 L 7.5 M ammonium

acetate, and vortexed for 20 s. Samples were then centrifuged at 14,000 x g for 5 min

and the resulting supernatant combined with 750 L isopropanol. To facilitate

precipitation, samples were then inverted for 5 min and centrifuged at 16,000 x g for 10

min. The nucleic acid pellets were rinsed twice in 70% ethanol and re-suspended in 100 L

buffer (10 mM Tris, 0.05% Triton X100).


91

A real-time PCR assay which distinguishes an N. perurans-specific 18S rRNA gene

sequence [167] was run on all samples, in duplicate, with no-template controls. All

reactions were run in a CFX Connect PCR Detection System (Bio-Rad). N. perurans cell

counts were estimated using the 2880 copies cell-1 previously determined [167].

Data analyses

Differences in amoeba counts between the hypoxic and normoxic treatments at each

sampling were evaluated with Wilcoxon signed-rank tests, and further visualized using

violin plots showing the median and interquartile range. R version 3.2.0 (www.r-

project.org) was used for all amoeba count analyses. As a measure of gross AGD

severity, the proportion of visible respiratory surface affected by lesions, as determined

from lesion morphometry, was calculated for each individual in the final sampling.

Daily mortality data were used to calculate cumulative mortality as a percentage of the

initial sample size. Lesion and mortality data were plotted in Microsoft Excel. All data are

presented as mean ± SE unless otherwise stated.

RESULTS

Length and weight were very similar in the hypoxic (21.1 ± 0.25 cm & 93.5 ± 4.3 g) and

normoxic (21.1 ± 0.23 cm & 92.3 ± 5.0 g) treatment groups (Table 7.1), and no differences

in skin, fin or eye condition were detected at the final sampling based on qualitative

scoring.

Table 7.1 – Sample number (N) and mean ± SE of the length, weight and N. perurans counts as measured at the 3rd sampling on day 10. Data presented are the overall treatment means followed by the individual replicates.




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Lesion morphometry

There was no difference in mean visible gill surface area, measured in mm2, between

treatments (hypoxic = 16,274 ± 367; normoxic = 16,191 ± 400). Number of lesions ranged

from 0 to 11 in the normoxic treatment, and 0 to 9 in the hypoxic treatment. There was no

significant difference in number of lesions between treatments, nor was there a

difference in mean lesion size. Percentage of visible gill surface area lesioned was 9.0 ±

4.0% in the hypoxic treatment and 6.4 ± 3.7% in normoxic (Figure 7.3).

Figure 7.2 – The variance and distribution of N. perurans counts as determined from real-time PCR. Boxplots of the median and interquartile range are set within violin plots for each treatment at each of the three sampling periods.


93

Amoeba counts

N. perurans were detected on the gills of individuals in both normoxic and hypoxic

treatments at all three sample collection periods. At the first sampling, 2 days post-

infection, amoeba counts were low in all systems, ranging from seven individuals with no

detectable amoeba to a maximum of 20 cells. Despite overall low amoeba numbers, the

distribution of amoeba counts in the normoxic treatment was significantly different from

that of the hypoxic (W = 407, p = 0.006), with a marginally higher median (Figure 7.2a).

By the 2nd sampling, 7 days post-infection, amoeba counts had increased considerably,

ranging from 123 to 12,231 in the hypoxic treatment and 36 to 8,657 in normoxic. The

distribution of amoeba counts were again significantly different between the two

treatments (W = 723, p = 0.02), this time with a higher median in the hypoxic treatment

(2413) than in the normoxic (1449) (Figure 7.2b).

Due to using a different sampling technique, whole arch processing rather than mucous

swabs, the amoeba counts from the 3rd sampling are not directly comparable to the

previous two samples. However, at this sampling there was no difference in distribution

of amoeba counts between the hypoxic and normoxic treatments (p = 0.14), with only 52%

of the hypoxic sample having amoeba counts greater than the mean of the normoxic

sample (Figure 7.2c).

Figure 7.3 – Percentage of visible surface area with AGD lesions on the anterior face of the 3rd right gill arch. Mean ± SE are shown for each of the hypoxic (open diamond) and normoxic (solid circle) replicates.


94

Mortality

Daily mortality rates ranged from 0 to a maximum of 26% in the normoxic treatment

and 0 to 30% in the hypoxic treatment (Figure 7.4). Through day 3 mortality was very low

in both treatments. On days 4 through 7 mortality rate remained low in the normoxic

treatment but increased in the hypoxic group. By the end of day 7, 16 ± 4% of fish in the

hypoxic treatment had died compared to 8 ± 2% in the normoxic treatment. Mortality

was high in all systems from day 8, peaking on day 10 prior to sampling (Figure7.3).

Cumulative mortality at the end of the a percentage of initial sample size, did not differ

with treatment (hypoxic = 60 ± 2%, normoxic = 53 ± 11%).

Figure 7.4 – Cumulative mortality as a percentage of original sample size in hypoxic (open

diamonds) and normoxic (solid circles) treatments from infection (Day 0) through the final

sampling (Day 10). Data presented are mean ± SE.


95

DISCUSSION

Results of this study show that daily exposure to moderate hypoxia of 40 – 60% DO

saturation can accelerate the progression of N. perurans infection in Atlantic salmon, but

does not necessarily alter acquisition or ultimate prognosis. Two days after inoculation

with N. perurans amoebae were present in low numbers on the gills of all fish in both the

hypoxic and normoxic treatments. Despite the low amoeba numbers, amoeba count

distributions were significantly different between treatments with a slightly higher

median in the normoxic group (Figure 7.2a). However, given the very low amoeba

numbers in both treatments (median: hypoxic = 2, normoxic = 3) this early difference

does not appear to be biologically relevant.

By day five of the experiment, four days post-inoculation, mortality rates in the two

treatments diverged with an average of 5 % cumulative mortality in the hypoxic

treatment and 1% in normoxic (Figure 7.4). From 5 - 7 days post-inoculation mortalities

became more frequent in both treatments, but cumulative mortality rate remained

consistently at least twice as high in the hypoxic treatment as in the normoxic (16 ± 4% vs

8 ± 2%, respectively on day 7). Similarly, at the 2nd sampling seven days post-inoculation,

the distributions of amoeba counts were also significantly different between the two

treatments, with a higher median in the hypoxic treatment (2413) than normoxic (1449)

(Figure 7.2b). Indeed, 64% of the individuals sampled from the hypoxic treatment had

amoeba counts greater than the mean of the normoxic (2049 ± 1023) - five of the 33

individuals in the hypoxic treatment had amoeba counts >9,000, while only one individual

in the normoxic treatment exceeded 5,000 cells.

From the 8th day post-inoculation onward mortality rates in both treatments increased

dramatically (Figure 7.4). By the final sampling, 10 days post-inoculation, cumulative

mortalities were similar in the two treatments: 60 ± 2% in hypoxic and 53 ± 11% in

normoxic. Distributions of final amoeba counts were not significantly different either-

only 52% of the hypoxic amoeba counts were higher than the mean of the normoxic

treatment (Figure 7.2c).


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The observed disease progression clearly demonstrates that with equal infection

pressure, as evidenced by the marginally higher amoeba counts in the normoxic

treatment two days post-inoculation, diel-cycling DO to moderately hypoxic conditions

speeds the progression of AGD in post-smolt salmon. The same, however, can not be

said for N. perurans acquisition. For fish, O2 uptake relies on the flow of water over the

gills; in hypoxic conditions, ventilation rate increases and thus so too does the volume of

water physically contacting gills [96]. Given the opportunistic nature of N. perurans and

their presence in the water column, I expected a higher frequency of interaction in the

hypoxic treatments, and thus faster disease acquisition [167, 196, 252]. Further, hypoxia is

known to illicit a stress response in fish, causing the release of cortisol and thus

downregulation of the immune and reproductive systems, another reason to expect

faster acquisition in hypoxia exposed fish [22, 43, 65, 95].

One potential explanation for the lack of difference in acquisition could be that the fish in

our trial received such a high inoculation dose that any differences were masked

because all fish, regardless of ventilation rate, frequently encountered amoebae. We

used an inoculation dose of 1200 cells L-1, much lower than some previous studies which

used up to 9,000 cells L-1, however our amoebae were collected directly from a fish in an

AGD maintenance tank and immediately added to the experimental systems [178]. Given

that virulence is known to vary with amoeba strain, it is possible that the amoebae used

in this trial were particularly pernicious [178, 179, 250].

Another explanation could be that the fish had already acclimated to the diel cycling

hypoxia and were no longer stressed after 12 days of exposure. In one study, exposure to

constant, chronic hypoxia led to elevated cortisol levels in salmon throughout 59 days of

exposure [95]. In contrast, when post-smolt salmon were exposed to daily, cyclic hypoxia

cortisol was only elevated during the first week, after which it returned to control levels

[65]. Unfortunately, as we did not measure cortisol, this hypothesis can be neither

confirmed nor denied with current data. Confounding the issue further is the fact that

exposure to chronic stress is known to reduce the quantity of corticosteroid receptors in

gills, thereby reducing cortisol sensitivity [137]. While this information raises more

questions than it answers at this stage, it also provides an avenue for future exploration,

and raises the possibility that periodic hypoxia exposure may not significantly increase

susceptibility to gill parasites in salmon.


97

AGD, however, is a proliferative gill disease, and though it begins with small multi-focal

hyperplastic lesions it can rapidly escalate, as shown here. In severe cases AGD results in

filament fusion and accumulation of mucous on gills, reducing O2 uptake capacity and

eventually resulting in death [122, 166]. Here, despite low amoeba numbers on gills two

days post-inoculation, N. perurans quickly multiplied, in both treatments (Figure 7.2ab). In

the hypoxic treatment the rapid disease progression resulted in significantly higher

amoeba counts at the 2nd sampling and earlier mortalities than the fish in normoxic

conditions (Figures 7.1 & 7.3). Although this experiment did not differentiate between the

effects of cyclic hypoxia on the host versus the pathogen, there is no evidence which

suggests that low O2 conditions directly influence the virulence of N. perurans while it is

known to reduce the metabolic capacity and performance of salmon (chapter 5).

Surprisingly, despite the accelerated disease progression in the hypoxic treatment, there

was no difference in cumulative mortality at the end-point of the trial 10 days post-

inoculation (Figure 7.4). It is possible that hypoxia exposure did not alter the severity of

the infection, but rather just increased the pace - so impervious individuals were

unaffected irrespective of treatment, but susceptible individuals succumbed sooner as a

result of hypoxia exposure. An alternative possibility is that the increased amoeba

prevalence and disease progression would actually result in increased mortality over a

longer period of time if the infection was allowed to progress, but our end-point was too

early to capture that information. Finally, a more nuanced possibility is that cyclic

hypoxia exposure actually increased the hypoxia tolerance of the surviving fish, as

previously observed [248], and that overall mortality would have been lower in the

hypoxia treatment group had the experiment been allowed to continue.

CONCLUSIONS

Salmon in marine aquaculture cages around the world are frequently exposed to

fluctuating DO levels and moderate hypoxia (chapter 1). However, despite the

pervasiveness of hypoxic conditions in cages and numerous pathogens which threaten

farmed salmon, little attention has been given to the potential impact of hypoxia

exposure on the prevalence and intensity of infectious diseases. This study provides the

first evidence that exposure to moderately hypoxic conditions can accelerate disease

progression in salmon, and suggests that when AGD and hypoxia co-occur, faster more

aggressive treatment is required to minimize disease related mortalities

Chapter 8 – General Discussion

98

Chapter 8 General Discussion

Less obvious than an infection but no less consequential, environmental hypoxia is an

ever-present threat to the production performance and welfare of farmed fish. The

repercussions of hypoxia exposure range from inconsequential to reduced feed intake

and mass mortality, and are felt on salmon farms around the world. With much hope

pinned on aquaculture to be the future protein supply for the world’s growing population,

continued expansion and growth of the industry necessitates a deeper understanding of

the causes and consequences of hypoxic conditions in marine cages. Presented in this

thesis are the findings of research which I hope will help farmers and managers reduce

the occurrence of hypoxia in cages, and when unavoidable, minimize its impacts on fish

welfare and production performance.

DEFINING ‘hypoxia’

At first glance the term hypoxia, which is simply environmental O2 deficiency, is not

complicated. Digging a little deeper, however, vastly different ‘hypoxic thresholds’,

ranging from 0.28 to 6.0 mg L-1 O2, have been proposed for marine animals [20, 253]. The

inconsistency, and indeed the challenge, arise as a result of the word ‘deficiency’. DO

availability exerts a limiting influence on every aspect of life for aquatic animals, and O2

demand, even for a single individual, fluctuates constantly with numerous internal and

external factors. In such a complicated scenario, when the environmental DO level at

which an individual will experience functional consequences as a result of exposure

constantly fluctuates, what conditions can be deemed ‘deficient’?

Just within Atlantic salmon aquaculture, where the universal objectives are to maximize

growth, feed conversion efficiency and welfare, a range of hypoxic thresholds are used.

The simplest threshold, used by some farms in Canada, is a blanket 6.0 mg L-1 O2 below

which feeding is stopped [20, 43]. More recently, an evolution of the feed intake

threshold which accounts for the complicated relationships between O2 solubility,

metabolic capacity and temperature was developed [40]. Their study demonstrated that

the increased metabolic pace resulting from higher temperatures also increases

maximum potential feed intake and growth; simultaneously, as temperature and feed

intake increase, so too does O2 demand.

References

99

At 7 ⁰C the maximum potential feed intake was 0.47% biomass and was sustained down

to a DO saturation of 42% (4.1 mgO2 L-1); meanwhile, maximum potential feed intake was

nearly doubled to 0.99% biomass at 19 ⁰C, but was only able to be maintained down to 76%

DO saturation (5.8 mgO2 L-1) [40].

The problem with any universally applied threshold is that they fail to account for the

varying metabolic capacity and O2 demands of organisms throughout their life and in

different conditions. Any factor which increases an individual’s irreducible metabolic load,

such as digestion or keeping pace with fast currents, increases O2 demand and thus

tolerance for environmental hypoxia [24]. This means that in addition to temperature,

many other factors such as size, general health and activity level all affect what

repercussions, if any, an organism experiences as a result of exposure to DO saturations

of less than 100%.

Indeed, when supplemental O2 was provided if environmental DO saturation dropped to

85%, adult salmon experienced significantly faster growth rates compared to fish in

untreated control cages at the same site [81]. Other studies found even higher minimum

DO requirements for maximum growth, including ≥ 100% DO saturation at 8 ⁰C for post-

smolt salmon [254], and >111% DO saturation at 6.5 - 9.5 ⁰C for pre-smolts [255]. In

contrast, while both of the aforementioned studies observed improved growth with DO

levels above 100% saturation despite being at low temperatures where metabolic rate

and O2 demand are reduced, yet another study found that feed intake of post-smolt

salmon at 11 ⁰C plateaued above 53% DO saturation [40]. This variation is because the

metabolic needs of all fish, even of the same species, are not equal (chapter 5).

The absolute minimum amount of O2 an individual needs to survive is that required to

sustain their SMR. In salmon, SMR increases linearly with temperature between 3 and

23 ⁰C [39], and is inversely related to size (chapter 5). Each of these factors is a critical

determinant of metabolic O2 demand, and together dramatically impact hypoxia

tolerance, as evidenced by the six-fold increase in SMR between a 200 g fish at 23 ⁰C

measured in chapter 5 and the 450g fish at 3 ⁰C measured using the same methods and

equipment [39]. Beyond just temperature and size, several other factors also affect an

individual’s irreducible metabolic load.

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Though SMR provides an estimate of the absolute minimum metabolic rate of a

stationary individual in a non-digestive state, such conditions never exist in the marine

cage environment. In the real world, fish must allocate their limited metabolic resources

among numerous demands beyond SMR including digestion, naturally varying currents

and contending with bacterial, viral and parasitic pathogens [256]. Exactly how much

energy an individual is able to devote to each activity among the many demands is

limited by its AS [32].

The more food fish consume, the faster they grow and, subsequently, the greater their

O2 demand [42, 65, 132, 257]. Throughout a range of sizes, from 5 - 2000 g, feeding

salmon to satiation results in a 50 – 120% increase in O2 demand relative to fasted fish

[132, 257, 258]. Further, once digestion begins, MO2 is irreducibly elevated until

assimilation is complete. How long digestion and assimilation take varies with ration, but

in small salmon has been observed to last anywhere between 2.5 – 8.5 hours [132]. Such

elevation of O2 demand leads to a temporary reduction in hypoxia tolerance, and

reduces the energetic resources available for other activities [41, 134]. Indeed, previous

work documented a significantly reduced Ucrit in fed fish compared to fasted controls,

despite no differences in SMR, MMR or AS [257].

At the same time, with no bottom to rest on nor boulders to shelter behind, farmed fish

have no choice but to face currents head on [51]. As a result, essentially any current

speed > 0 cm s-1 exponentially increases metabolic O2 demand (chapter 5). Further,

because cost of transport is inversely related to size, swimming demands a

disproportionately large amount of energetic resources in small fish (Figure 5.5). Also,

like all animals in the marine environment, farmed salmon are fighting a steady battle

against numerous pathogens [259]. This double trouble is particularly challenging for

fish because while sustaining immune defences demands energetic resources, many

pathogens affect gills and reduce O2 uptake capacity [43, 82, 95, 122, 260, 261]. Such a

conundrum is exemplified by AGD; while hypoxia exposure hastens disease progression

(chapter 7), reduced gill function as a result of AGD infection increases the risk of

hypoxemia [122]. In 330 g post-smolt salmon, MMR and AS were reduced by half in AGD

affected individuals compared to uninfected controls of the same size, resulting in

concomitantly reduced swimming performance [122]. Similarly, PRV infection reduced

cardiac performance, haemoglobin-O2 affinity and hypoxia tolerance [248].

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Finally, while the previously mentioned variable factors affect O2 demand everywhere,

several intrinsic factors which are permanent but vary between farms also affect the

metabolic capacity of salmon. Triploid fish, which are attractive because they are sterile

and grow fast in calm, cool conditions, have reduced gill surface area and O2 transport

ability compared to diploids, resulting in reduced MMR and AS at temperatures > 12 ⁰C, as

well as reduced hypoxia tolerance [262–265].

Similarly, growth hormone transgenesis, a technique used to achieve higher growth rates,

also affects fish physiology. SMR of size-matched transgenic salmon was 25% higher

than that of controls, with no difference in MMR or gill surface area, resulting in reduced

AS and capacity for activity [266]. Comparable studies of transgenic coho salmon

(Oncorhynchus kisutch) have found similar results – transgenic fish grow much faster,

but have significantly lower MMR and Ucrit relative to unmodified controls of the same

size [266, 267]. Finally, even just simple selection for fast growth alters metabolic

physiology; while SMR did not differ between wild and domesticated strains of

Norwegian salmon, MMR was 24% higher in the wild fish, with a concomitantly higher AS

[268].

Ultimately, immune competence, capacity to deal with stressors and growth all depend

on the availability of sufficient environmental DO to meet metabolic demand, and the

ability of the organism to transport O2 to the necessary tissues. Metabolic demand, in

turn, is determined by a multitude of factors, some of which are highly variable and can

change from one minute to the next, others which are fixed but vary from farm to farm.

As a result, DO concentrations which may lead to hypoxemia for one cage of fish can be

perfectly fine for another. The severity of the impacts of hypoxemia, which can range

from reduced feed intake to mortality, depends on the degree of disparity between O2

demand and supply. There is no one-size-fits-all DO threshold for salmon aquaculture; to

maximize production performance and welfare, management decisions must be tailor

made based on the environmental conditions at a site, and the O2 requirements of the

fish of concern.

References

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THE CAGE ENVIRONMENT

Overlaying the many layers of O2 demand is environmental DO availability. Availability

and distribution of DO, however, is not independent of other factors, but is the

culmination of all of the physical, chemical and biological processes occurring at any

given place and time (chapters 2 and 3). The upper limit on the amount of DO a body of

water can hold is set by pressure, temperature and salinity [268]. At 15 ⁰C and 30 ppt

salinity, in what are considered ideal farming conditions for salmon growth, 100% DO

saturation is equivalent to 10 mgO2 L-1. As water warms and becomes more saline, the

solubility of O2 decreases (Figure 8.1). In conditions more like a summer day in Tasmania,

at 22 ⁰C and 35 ppt, 100% DO saturation is equivalent to just 7.1 mgO2 L-1.

Figure 8.1 – The impacts of salinity (20 ppt = blue, 25 ppt = green, 30 ppt = yellow, 35 ppt = red), temperature and reduced saturation on DO availability [268].

O2, however, is rarely 100% saturated throughout the water column (Table 1.1, Figure 8.1).

While many organisms compete to utilize DO, input only comes from two sources:

diffusion of O2 across the water’s surface and algal photosynthesis [22]. Photosynthesis

requires light. As a result, all DO in the oceans must originate from the euphotic zone,

and while diffusion continues 24 hours a day, photosynthesis is strictly limited to daylight

hours. The lack of photosynthetic O2 production in the dark at least partially explains the

findings in chapters 2 and 3 that mean DO was lower at night than during daylight.

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And while the rate of re-oxygenation at a site varies with weather and algal density, O2

demand in cages dwarfs local supply from both aeration across the water’s surface and

photosynthesis [48]. Fish farms run on an O2 deficit, and rely on currents for

replenishment.

Based on the metabolic data collected in chapter 5, in ideal conditions of 15 ⁰C and 30

ppt, assuming an initial DO saturation of 100% throughout, a cage of active ~250 g post-

smolts stocked at 10 kg m-3 could utilize all available DO within an hour without water

exchange (Figure 8.2). In conditions more like those of Macquarie Harbour, Tasmania,

with all of the fish crowded into a 3 m depth band, all available DO could be used up in

as little as 20 minutes in the absence of replenishment (Figure 8.2) [17, 44].

Figure 8.2 – The time required for active (MMR – black lines) and inactive (SMR – gray lines) fish of three size classes to use all of the available DO in a cage when at different group densities. Dotted lines are the small = 0.2 kg fish, dashed lines are medium = 1.0 kg, and solid lines are large = 3.5 kg fish. Calculations are based on an initial DO concentration of 8.0 mg L-1 throughout the cage and no replenishment. Based on data collected in chapter 5. The shaded area delineates conditions in which all DO would be used within 1 hour or less. The result of these interacting forces of O2 supply and demand in marine cages is a

capricious, ever-changing DO landscape (chapters 2 and 3).

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Amidst all of the variability, however, there are some discernible patterns. Globally, as

observed in chapter 2, stronger currents, which equate to more water exchange,

correlate with higher DO in marine cages [18, 19, 269]. DO levels are lower in the dark

than during daylight (chapters 2 and 3). And, though the amount DO required by any

individual is variable, it is always true that more individuals mean more respiration and

thus greater O2 demand. Therefore, higher stocking densities result in lower average DO

levels in cages [19, 270, 271]. Further, if the fish are not distributed evenly throughout the

cage, but rather concentrate in preferred areas, the functional density in that area will be

higher and result in faster DO usage than expected based on planned stocking density

(Figure 8.2).

Farming infrastructure also alters local flow and O2 dynamics [34]. Field measurements

in empty commercial cages documented a 21% reduction of current speed inside cages

relative to measurements at a reference position [67, 72]. Any biofouling on the cage,

which decreases net porosity, reduces current speed further. On nets with high solidity,

current speed reductions of as much as 70% have been observed [34, 272]. Further, on

heavily fouled nets vortices create internal circulation within cages reducing water

exchange even more [67, 73]. Size also affects the flow field around cages as a result of

reduced surface area to volume ratios and greater total biomass in larger cages [34, 80]

(Figure 8.3). As would be expected with less water exchange, DO measurements in

chapter 2 were lower in 240 m compared to 168 m circumference cages, despite having

lower stocking densities and the same netting.

Figure 8.3 – Predicted current speed reduction with increasing cage diameter and stocking density from ambient conditions of 50 cm s-1. Based on the model developed by Aure et al[80].

References

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Salmon farms, however, rarely consist of a single cage. Most farms are an array of

several cages, the dimensions of which vary from operation to operation and also affect

water exchange and DO [34, 69]. Typical farm arrays consist of two parallel rows

ranging in length from two to ten cages, and may be oriented either perpendicular or

parallel to the primary direction of water movement.

Aligning the array parallel to current flow minimizes the stress on cage moorings, but

reduces water exchange; aligning the array perpendicular to the current maximizes DO

replenishment, but exacerbates strain on the cage structure [34]. Interestingly, for

arrays aligned parallel to the current, having two rows of cages increases water

exchange relative to a single row [35].

At the same time however, the rate of water exchange is increasingly reduced down the

line of cages as the outgoing current from the previous cage is the ingoing current to the

next [34]. With a velocity reduction of 20% per cage, as has been measured on a clean

net with only 19.7% solidity, if the incoming current at the first cage was 50 cm s-1, a 2nd

cage would receive 40 cm s-1, the 3rd 32 cm s-1and by the 10th cage only 7 cm s-1 [34, 272].

In the case of heavily fouled nets, the current speed would be reduced to effectively zero

by the 7th cage [34, 272]. In low flow conditions, such as those in chapter 2 when average

current speed was just 4 cm s-1, with heavily fouled nets only the first three cages would

receive any DO replenishment at all.

Beyond the patterns which hold true globally, others which are more location or

condition specific also exist. Vertical distribution of DO in cages is consistently

heterogeneous. In Tasmania, at shallow sites with little distance between the cage

bottom and seafloor, DO decreases with depth; in Norway and Canada however, at

deeper farm sites, lowest DO saturation usually occurs in the upper half of the cage [15,

18–20, 84].

In chapter 2, distinct DO variation across the width of the cage was also observed, with

lowest DO in the middle and down-current cage positions. Many factors contribute to DO

distribution throughout the cage, not the least of which is the fish themselves. On the

most basic level, the solid bodies of the fish impede currents and create turbulence – the

more fish, the greater the impact [34, 35, 271].

References

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Beyond their physical presence, the relationship between fish behavior and DO is

dynamic- they both alter local DO conditions, and are perpetually reacting to them. For

farmed fish, swimming speed, activity level, schooling behavior and cage positioning are

steadily adjusted in response to fluctuating circumstances [50, 96]. The precise nature of

the response varies with the capabilities and needs of the affected fish [96].

At low current speeds ≤ 20 cm s-1, 1.5 kg salmon typically swim in a circular pattern and

utilize most of the cage volume; as current speeds increase, some fish begin to hold

position and stand against the net facing into the incoming current [51]. By speeds of 46

cm s-1, equivalent to 0.93 BL s-1, all salmon in the cage stand against the current [51]. As a

result, in fast current speeds with the fish holding position, a DO gradient would be

expected across the cage, similar to the distribution seen in wild fish schools [273].

Conversely, fish schooling in a circular pattern creates a very different water movement

dynamic. In very small cages, circular schooling significantly increased water mixing

during low flow periods, by as much as a factor of 12 compared to empty cages [71]. A

similar study in larger cages observed a delayed and rotational movement of dye

through stocked cages which was not present in empty ones, leading the researchers to

suggest that circular schooling generates a suction effect which causes increased mixing

around the cage perimeter and stagnation in the center [47].

During the study in chapter 2, with average current speeds of 4 cm s-1, lowest DO

measurements were recorded in the center of the cage. Based on video observations,

during daylight hours the fish were consistently schooling in a circular pattern at swim

speeds of 68 cm s-1. Therefore, it is possible that the circular schooling of the fish,

swimming considerably faster than the external ambient current speeds, created a

suction effect which pulled and held DO depleted water in the center of the cage. This

behavioral effect would explain the reduced dependence of DO saturation on reference

current speed observed in the middle of the cage (Table 2.2, R2 = 0.19) as compared to

the other positions (Table 2.2, R2 = 0.27 – 0.35), because it would be replenished at a

slower rate.

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Further, several studies have investigated the relationship between tides and DO in

salmon cages without detecting any connection; these studies, however, were performed

at locations with complex patterns of water movement strongly affected by wind driven

currents and uneven bathymetry [18–20, 48]. In contrast, the finding in chapter 3 that

mean DO was significantly lower on the day of a neap tide as compared to the other 9

days of observation suggests there may be more to the story. Neap tides are the point in

a tidal cycle with the least difference between high and low water, and thus correspond

to minimal water movement as a result of tidal forcing.

In estuaries and other sites which rely primarily on tidal currents for water exchange,

such as the majority of salmon farming sites in Tasmania, the timing and strength of

currents are relatively predictable, but also inherently include slack periods with little

water movement [86, 274]. While the correlation between predicted tidal height and DO

in chapter 3 is anecdotal because our measurements only overlapped with a single neap

tide, it suggests there is potential at some locations to forecast ‘at risk’ periods for

hypoxia based on tides.

BEYOND BASIC CAGES

In addition to the basic structures required for fish containment, several alterations to

cage design have been developed in response to predators and parasites. In areas

where sharks and seals are common, a second net has been added to cages to create a

buffer between predators and farmed fish. While having an external net is very

successful for reducing interactions between farmed fish and predators, they also create

yet another barrier to water exchange [15, 272].

Other adaptations, such as those used to mitigate the impacts of sea lice, work by

intentionally reducing the water flow into the cage and thus the frequency of encounters

between parasitic copepods and salmon [256]. One tactic used by the salmon industry is

to wrap the upper few meters of the cage with a tarpaulin which diverts a large portion

of water flow around the cage; unfortunately, it also rapidly and dramatically reduces

DO levels [45, 46, 56]. In chapter 4, within one hour of tarpaulin deployment around the

top 3 m of a cage, DO dropped by 20%.

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On a commercial farm when a 3 m skirt was left on a cage for several days, median DO

plummeted within the tarpaulin where high densities of fish were congregating and

remained at or below 55% saturation despite reference DO consistently being above 85%

saturation [45].

Snorkel cages are another lice mitigation strategy based on the physical barrier principle;

salmon are restricted from entering the surface water layer except within a chamber

impervious to copepod larvae [275]. Such snorkel cages are highly effective for reducing

sea lice infestation, and the relatively small volume of the snorkel makes it possible to

maintain acceptable levels of DO simply by pumping deeper, well oxygenated water to

the surface [117, 118].

Results from studies of tarpaulin skirts, however, demonstrate that intervention is

required to ensure DO remains suitable within the snorkel, and that equipment failure

would result in DO levels getting very low, very quickly [45, 56].

At the most extreme end of lice mitigation technologies, completely closed sea cages

have also been trialled [276]. The sealed cage design necessitated providing a constant

flow of O2, but was successful throughout three years of production at minimizing sea

lice infestation without adverse effects on salmon survival or growth rate. However,

though monitored, no data were provided on the DO levels within the cage or the

amount of O2 required to maintain welfare [276].

Considered collectively, naturally variable DO conditions complicated by aquaculture

infrastructure and aggravated by locally high farming biomass result in a complex and

fluctuating cage environment prone to hypoxia. As a result, low DO conditions constantly

challenge farmed fish welfare and production performance. However, by understanding

the environmental dynamics and associated risk factors at a site, trends and patterns

such as those outlined here can aid farmers to predict when and where hypoxic

conditions are most likely to occur, and facilitate informed deployment of management

strategies to minimize negative impacts.

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FUTURE FISH FARMING

Warmer sea surface temperatures as a result of climate change will speed up the

metabolic pace of salmon in most farming locations, and thus increase potential growth

rate; in some respects improving prospects for salmon aquaculture [40, 277, 278]. The

reduced solubility of O2 as a result of warmer temperatures, however, will exacerbate the

severity and frequency of already common DO fluctuations in marine cages (Table 1.1,

Figure 8.1) [146]. Combined, this makes ocean warming a double-edged sword for

farmed salmon – as DO availability decreases, their metabolic pace increases, raising

their O2 demand and decreasing hypoxia tolerance [39]. Minimizing the negative impacts

of climate change then, and optimizing potential benefits, necessitates implementation of

locally appropriate mitigation and adaptation strategies [110].

In Tasmania, a global warming hotspot where water temperatures already border the

thermal maximum for Atlantic salmon during summer, action is required if the fish, and

industry, are to survive [17, 279, 280]. Worldwide, in 2015 and 2016 approximately 25% of

the ocean’s surface area experienced the longest or most intense marine heatwave ever

recorded; around Tasmania, sea surface temperatures were 3 – 4 ⁰C higher than the

climatological average [280]. Luckily, there are many ways to mitigate the growing

threat of hypoxia in cages and increase resilience.

The most effective strategy is to minimize the risk of low DO by choosing farm locations

with stable and high ambient DO saturation. The dramatic influence of site choice on DO

distribution is epitomized by comparing the conditions observed in chapter 3 in the Huon

estuary with those of simultaneous studies in Macquarie Harbour, Tasmania [17, 44]. All

three studies were performed simultaneously, in the midst of the 2015/16 marine

heatwave in Tasmania, in cages of the same size and design, operated by the same

company, with similar stocking densities, yet the observed DO conditions are

dramatically different. While mean DO was 90% saturation in the standard cages

studied in the Huon estuary in chapter 3, mean DO saturation in the Macquarie Harbour

cages was 50%, with anoxic conditions in the cage bottom [17]. Given the critical influence

of mixing on DO distribution, sites with reliable currents and infrequent slack water

periods, as evidenced by a homogeneous water column, are the best locations for cages

with regards to DO [18].

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Also influential, both on prevalence of low DO conditions and benthic impact, is the depth

of the site (chapters 2 and 3) [17, 48, 111, 281]. As a result of excess feed and fish faeces

beneath cages, organic enrichment of bottom sediments is common at shallow farming

sites < 50 m deep, and leads to increased bacterial respiration and subsequent low DO

saturation in bottom waters [17, 48, 281]. Even at a deep (>100 m) well-flushed site,

organic enrichment increased benthic metabolism throughout an 18 month production

cycle; the difference was that benthic fluxes rapidly recovered to control conditions after

only a 2.5 month fallowing period, much shorter than required at shallow sites [111]. As

such, farming at deeper, well-flushed sites where organic matter is dispersed more

rapidly, and fallowing between production cycles, will minimize local eutrophication [111].

The DO related consequence of shifting to offshore farm sites is relatively unknown;

waste dispersion is improved, but currents and thus replenishment can be less

predictable, and larger, more robust cages are required to withstand the challenging

weather conditions [16]. Specifically, tides have relatively little influence on water

movement patterns at offshore sites relative to wind and density driven currents [18,

282]. On one hand, this means that such sites can have steadier, faster average current

speeds and thus faster DO replenishment; on the other, current speeds are less

predictable, potentially very strong and susceptible to extended doldrums [16, 18, 51]. In

areas with primarily tide driven currents, periods of slack water have a maximum

duration of one hour, after which the tide will switch and water movement will return.

Better still, the timing of slack water periods at any location around the world can be

predicted years in advance. Offshore sites have only long-term trends and current

weather forecasts on which to base DO replenishment expectations.

In addition, offshore and exposed coastal sites in many salmon farming regions are

susceptible to deep-water upwelling events [283–285]. Through Ekman forcing,

persistent alongshore winds push buoyant, oxygenated surface waters away from the

coast which are replaced by nutrient rich, de-oxygenated bottom water [286]. Such

upwelling events not only threaten aquaculture operations by reducing DO levels, but

also by bringing the nutrients needed to spawn harmful algal blooms to the surface [94,

284, 287]. In all, offshore farming has the potential to minimize the occurrence of hypoxia

in cages, but to do so will require a cautious and informed approach to farming strategy

and site choice.

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It is also important to match cage design to the capacity and needs of the site. If farming

at a shallow site, cage designs which maximize the distance between the bottom of the

cage and seafloor will reduce exposure of fish to low DO bottom water, and facilitate

waste dispersal by removing the impediment of the cage to current flow (chapter 3).

Cage diameter should also be chosen based on the flow regime at the site – with smaller

cages and lower stocking densities at sites with less replenishment (Figure 8.3).

Beyond the individual cages, farm layout and orientation can also minimize occurrence

of low DO in cages. Aligning cages perpendicular to the primary current direction and

using only two rows of cages will minimize flow reduction and DO depletion between

cages, ensuring maximum replenishment [34, 35]. At the same time, establishing

biofouling removal protocols which ensure maximum net porosity is preserved at all

times is critical to maintaining high DO saturations [34, 73, 73].

Beyond the operational choices of location, farm design and layout, understanding local

water flow and DO distribution will improve ability to predict, and thus mitigate, the

impacts of low DO conditions. Initial monitoring of DO throughout local cages, in a

variety of conditions, will provide an understanding of local O2 dynamics from which

testing protocols can be developed. By determining when and where hypoxic conditions

are most likely to occur, testing can focus on high risk cage areas which then serve as

sentinels of dangerous conditions. Understanding the local DO dynamics should also

inform feeding procedure – avoiding periods when high O2 demand and low supply

coincide.

In the event of poor DO conditions, there are active mitigation options. While salmon

avoid lethally low DO levels, they cannot be relied upon to choose optimal DO levels

(chapters 2 & 4). The most minimally invasive option for active interference is to lure the

fish to the cage depths with the best conditions using underwater lights and/or feeding

[53, 113, 114, 158, 288]. More extreme, air or pure oxygen can be pumped into cages to

improve DO levels [81, 85, 103].

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However, while such systems can be very effective at improving DO conditions in the

near area, the high cost and limited spatial distribution mean that to perform optimally it

must be combined with an understanding of when and where O2 is most needed in the

cage [81]. Finally, if oxygenation is used to induce feeding in dire conditions such as those

documented in Macquarie harbour [17], it must be continued throughout the full duration

of post-prandial metabolism to avoid further local DO depletion.

CONCLUSION

It is easy to understand the desire to measure DO saturation in one location, once a day,

and based on comparison of that measurement to a fixed threshold decide whether or

not fish should be fed. But, to do so is to ignore the heterogeneous nature of the cage

environment as well as the multitude of factors, ranging from temperature to

domestication, which determine the production performance and welfare implications of

varying DO conditions. At one end of the spectrum, an overly cautious threshold risks not

feeding fish while they have sufficient AS for digestion and assimilation, and thus missed

growth potential; at the other end of the spectrum, farmers risk wasted feed, reduced

efficiency and environmental degradation. Thus, if the objective is to maximize the

growth, efficiency and welfare of fish, O2 optimization should serve as the base from

which farm design and management decisions are made. If a fish can’t breathe, it can’t

move, it can’t eat and ultimately, it can’t survive.

ACRONYMS & ABBREVIATIONS

113

ACRONYMS & ABBREVIATIONS

AGD – amoebic gill disease

AS – aerobic scope

CoT – cost of transport

DO – dissolved O2

Kg – kilogram

L – liter

LOS - limiting O2 saturation/ critical O2 concentration

MMR – maximum metabolic rate

MO2 – metabolic oxygen uptake rate

O2 - oxygen

[O2]crit – critical O2 concentration/ limiting O2 saturation

ppt – parts per thousand

PRV - Piscine orthoreovirus

s - second

SMR – standard metabolic rate

Ucrit – critical swimming speed

Uopt – optimum swimming speed

References

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Documents

IIToday, by value and quantity, Atlantic salmon (Salmo salar) are by far the largest marine farmed commodity, with more than 2.4 million tonnes produced annually [7]. First intensively