© 2020. Published by The Company of Biologists Ltd.

Parasite infection directly impacts escape response and stress levels in fish

Bridie JM Allan1, 2, 3, Björn Illing2, Eric P Fakan2, 3, Pauline Narvaez2, 3,7, Alexandra S Grutter4,

Paul C Sikkel5,6, Eva C McClure2,3,8, Jodie L Rummer2 and Mark I McCormick2, 3.

1. Department of Marine Science, University of Otāgo, Dunedin 9054, New Zealand

2. ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville,

Queensland 4811, Australia

3. Department of Marine Biology and Aquaculture, James Cook University, Townsville,

Queensland 4811, Australia

4. School of Biological Sciences, The University of Queensland, St Lucia, Queensland, 4072,

Australia

5. Department of Biological Sciences, Arkansas State University, State University, AR USA

6. Water Research Group, Unit for Environmental Sciences and Management, North-West

University, Potchefstroom 2520, South Africa

7. Centre for Sustainable Tropical Fisheries and Aquaculture, James Cook University,

Townsville, Queensland 4811, Australia

8. Australian Rivers Institute, Griffith University, Gold Coast, Queensland, Australia

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http://jeb.biologists.org/lookup/doi/10.1242/jeb.230904Access the most recent version at First posted online on 1 July 2020 as 10.1242/jeb.230904

Abstract

Parasites can account for a substantial proportion of the biomass in marine communities. As

such, parasites play a significant ecological role in ecosystem functioning via host interactions.

Unlike macropredators, such as large piscivores, micropredators rarely cause direct mortality.

Rather, micropredators impose an energetic tax, thus significantly affecting host physiology

and behaviour via such sublethal effects. Recent research suggests that infection by gnathiid

isopods (Crustacea) causes significant physiological stress and increased mortality rates.

However, it is unclear whether infection causes changes in the behaviours that underpin

escape responses or changes in routine activity levels. Moreover, it is poorly understood

whether the cost of gnathiid infection manifests as an increase in cortisol. To investigate this,

we examined the effect of experimental gnathiid infection on the swimming and escape

performance of a newly settled coral reef fish and whether infection would lead to

increased cortisol levels. We found that micropredation by a single gnathiid caused fast-start

escape performance and swimming behaviour to significantly decrease and cortisol levels to

double. Fast-start escape performance is an important predictor of recruit survival in the wild.

As such, altered fitness related traits and short-term stress, perhaps especially during early

life stages, may result in large scale changes in the number of fish that successfully recruit to

adult populations.

Introduction

Parasites can reach high biomass in marine communities (Kuris et al. 2008) and make up

around 40% of the total biodiversity on Earth making them one of the most successful modes

of life (Poulin and Morand 2000; Hatcher and Dunn 2011). As such, parasites play a significant

role in ecosystem functioning as they exert sub-lethal effects on their host where they can

modify and manipulate behavioural and physiological phenotypes (for review see McElroy and

de Buron 2014). Unlike macropredators such as piscivores, micropredators (which we define

broadly to include both parasites and micropredators as defined more narrowly by Lafferty &

Kuris 2000;2002) typically do not cause direct mortality, but rather cause a constant drain on

energetics, thus significantly affecting host physiology and behaviour (for review see Barber

2007). However, the magnitude of this change depends on the parasite type, parasitic loading,

and the size and ontogenetic stage of the host (Sun et al. 2012). For example, larval and

juvenile fishes are reported to be more vulnerable to the effects of infection than their adult

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counterparts, owing to low body reserves and high metabolism (Strathmann et al. 2002;

Grutter et al. 2011). Moreover, parasitic infection can also affect behaviours and physical

attributes important for fleeing predators such as reducing visual acuity (Seppälä et al. 2005),

limb malformation causing reductions in maximum jumping distance, burst swimming speed

and endurance (Goodman and Johnson 2011) and reducing critical swimming speeds in adult

and newly settled coral reef fishes (Binning et al. 2013; Grutter et al. 2011).

One of the most ubiquitous ectoparasites on coral reefs are gnathiid isopods (Crustacea)

(Grutter et al. 1994; Sikkel and Welicky 2019). Gnathiids, mobile temporary parasites of fish,

feed using a trophic strategy that might best be referred to as micropredation (Kuris and

Lafferty 2000, Lafferty and Kuris 2002). Micropredators attack multiple prey (hosts), much

like predators do, but an individual micropredators effect on their prey tends to be small.

Micropredators of vertebrate hosts briefly feed on blood, and like other classic

micropredators, such as ticks and mosquitos, gnathiids are not transmitted trophically.

Because micropredators feed on several prey individuals, they also do not benefit from

minimising damage to prey (Barber et al. 2000) and can rapidly abandon their prey if it is

incapacitated (Murray 1990; Lehmann 1993). These reef based micropredators feed on a

variety of coral reef fish hosts from teleosts to elasmobranchs and on all host ontogenetic

stages (Grutter and Poulin 1998; Grutter et al. 2017). As such, micropredators can cause

significant physiological stress such as increased oxygen consumption (Grutter et al. 2011),

reduced haematocrit (Jones and Grutter 2005), increased cortisol loads (Triki et al. 2016), and

even mortality (Hayes et al. 2011 ). Previous work by Grutter et al. (2011) estimates that a

single gnathiid can consume up to 85% of the blood volume of a late-stage larval damselfish,

which has the potential to significantly affect behaviours that rely on aerobic activities, such

as swimming (Gallaugher et al. 1995; Grutter et al. 2011). Reduced swimming performance

can affect the way in which a fish interacts with conspecifics and predators and whether it can

settle successfully to the benthic environment (Allan et al. 2013; Grutter et al. 2011).

When coral reef fishes recruit to the benthic environment, it is reported that predator-induced

mortality can be absolute, but averages 60% within the first few days of settlement (Almany

and Webster 2006). Predator avoidance and evasion are key ecological traits that are directly

related to growth and survival. When a predator attacks, prey are faced with a series of

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decisions, such as how fast to respond, which direction to turn, and how fast and how far to

escape in an overall whole-organism behaviour called a fast-start (for review see Domenici

and Blake 1997). Fast-start escape behaviour can significantly increase the probability of prey

escape (Walker 2005; Allan et al. 2013; 2015; 2017). Whole-organism behaviour is a way to

measure how well an organism can perform a given behaviour or ecologically relevant task,

such as fleeing from predation or executing a fast-start response. The effectiveness of fast-

start escape behaviour is a consequence of body morphology, muscle mass, and muscle cell

physiology and energy reserves (Langerhans 2009). Fast-starts are characterised by rapid

acceleration, which is driven by the rapid anaerobically-powered contraction of large

myotomal blocks of fast glycolytic muscle (Rome et al. 1988; Josephson 1993). Although

anaerobically powered, fast-starts are a strenuous form of activity in which the active muscles

require more oxygen than can be supplied during the period of activity. Therefore, an oxygen

debt is accrued that needs to be repaid via aerobic metabolism (Scarabello et al. 1991).

To date, few studies have addressed the effects of parasitic load on fast-start escape

behaviours. Blake et al. (2006), examined the effects of parasite load on the C‐start

performance of the three‐spined stickleback (Gasterosteus aculeatus) and found negative

effects on escape kinematics (Blake et al. 2006). By contrast, Binning et al. (2014) tested the

escape performance of the monocle bream, Scolopsis bilineata, following infection by the

large ectoparasitic cymothoid isopod, Anilocra nemipteri, and observed no change in the

escape performance of parasitised fish, suggesting that infection may not compromise escape

performance. However, these studies used adult fish (overall range in body length of 4 to 13

cm) to measure the effects of parasite infection on escape performance, and it seems likely,

given the physiological cost of parasitic infection (Grutter et al. 2011; Sun et al. 2012), that the

escape performance of coral reef fish recruits would be negatively affected. Therefore, the

main goal of the current study was to understand whether gnathiid infection would

compromise the fast-start escape kinematics of newly settled, coral reef fish recruits.

Furthermore, we evaluated whether experimental exposure to gnathiids induced changes in

cortisol levels. The physiological processes by which fish respond to a stressor can be grouped

into primary, secondary and tertiary responses (Barton and Iwama 1991). Initially,

catecholamines from chromaffin tissue are released, thus stimulating the hypothalamic-

pituitary-interrenal (HPI) axis, which causes the release of corticosteroid hormones. This is

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followed by a secondary response, which involves haematological preparations to increase

the efficiency of metabolic and immune responses (for review see Barton 2002). Finally,

tertiary responses manifest as changes in whole animal performance, such as changes in

condition and behaviour. Increased cortisol following infection by hematophagous parasites

has been observed across multiple taxa, including birds (Quillfeldt et al. 2010), rodents (St.

Juliana et al. 2014), and fishes (Triki et al. 2016). These variables were selected as they are key

metrics of individual performance and are predictors of fish survival in the wild (McCormick

et al. 2018). Newly settled fish were chosen as prey because the life-history shift between

pelagic larvae and settled juveniles represents an important bottleneck where mortality is

intense and selective.

Material and methods

Study species

During December 2016, newly metamorphosed ambon damselfish, Pomacentrus

amboinensis (Pomacentridae) (range 9-12 mm, 10.3 mean standard length (SL), standard

deviation (SD) 0.05) were collected using light traps (Meekan et al. 2001) in the waters off

Lizard Island (14°40’S, 145°28’E) in the northern Great Barrier Reef, Australia. This species is a

common component of the benthic fish fauna of Indo-Pacific reefs, and adults inhabit sandy

areas of lagoons and inshore reefs (Randall et al. 1997). P. amboinensis naturally settle on

patch reef environments near the continuous reef. In this habitat, juveniles are exposed to

reef-associated gnathiids and macropredators that use a variety of feeding modes from

ambush (lizardfish Synodus dermatogenys and the small grouper Cephalopholis microprion) to

pursuit (dottybacks Pseudochromis fuscus and wrasse Thalassoma lunare). These fishes can

be observed to prey on juveniles that venture too far from shelter (McCormick 2012),

including the species used in this study, P. amboinensis. After capture, P. amboinensis were

transferred from light traps to aquaria (65 × 35 × 30 cm) with aeration and water flow for a

minimum of 48 h before use in trials. Coral reef fish recruits, when captured using light traps,

habituate to life in aquaria extremely quickly and will feed within several hours following

removal from light traps.

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Gnathiid exposure

In the evening, prior to behavioural trials (17:00 h), well-fed P. amboinensis were individually

transferred to randomly assigned 700 ml black aquaria filled with filtered seawater. Fish were

left to habituate for 1 h, after which a single, unfed, stage three gnathiid (~ 1.5 mm long,

harvested from a well-established gnathiid culture tank at the Lizard Island Research Station,

Grutter 2001) was carefully transferred to each aquarium via a pipette. Control fish were

treated in the same way and transferred into 700 ml black aquaria filled with filtered seawater.

However, instead of a gnathiid, filtered seawater was added via a pipette. After transfer, the

gnathiids were observed to be swimming freely in the aquaria. Fish were exposed to the

gnathiids during the night, as gnathiids tend to be nocturnally active when their fish hosts are

less active (Grutter and Hendrikz 1999; Sikkel et al. 2009). Fish were left undisturbed for 2 h

and were subsequently checked at 2 h intervals (using a red light to minimise disturbance)

throughout the night with the status of the gnathiid (fed, unfed, or gnathiid missing—

presumably eaten by the fish) recorded. The next day, the fish were tested for swimming

behaviour and fast-start responses in the order in which they had been parasitised, meaning

that they were tested no more than 10 h after the gnathiid was observed to be attached. To

control for a temporal effect, control fish and non-parasitised fish (i.e., the gnathiid remained

unfed at end of infection exposure) were also tested throughout the day. For sample sizes per

treatment, see Figure 1 legend.

Routine swimming and fast start protocol.

Routine swimming and fast starts were examined using individual fish in a transparent circular

acrylic arena (diameter 200 mm; height 70 mm) within a large opaque-sided plastic tank (585

x 420 x 330 mm; 60 L) with a transparent Perspex bottom to allow responses to be filmed from

below using the fish’s silhouette. The water level was maintained at a height of 60 mm to

reduce movements in the vertical plane, and the water in the arena was emptied and refilled

with fresh seawater after approximately every 20 min to maintain water quality and

temperature. The arena was illuminated by an LED light strip wrapped around the outside of

the holding tank with light penetrating with even illumination through the white plastic sides.

At the end of the 5 min habituation period, routine activity (used to determine routine

swimming) was recorded as a silhouette from below, at 30 fps for 2 min (Casio EX-ZR1000).

Routine swimming was analysed on the 2 min 30 fps video sequences and measured by

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tracking the distance (metres) covered by the fish every second, resulting in 120 data points

per fish. From this distance measure, average speed was also calculated (m s-1).

A fast start was then stimulated by the release of a conical weight with a tapered end into the

testing arena and recorded at 480 fps (Casio EX-ZR1000). Fish were only startled with the

weight when they had moved to the middle portion of the tank, allowing an individual to move

an equal distance in any direction and standardising for fish position relative to the stimulus.

The weight was released from an electromagnet and was governed by a piece of fishing line

that was long enough such that the tapered tip of the weight only just touched the surface of

the water. To avoid a premature fast-start response associated with visual stimulation

occurring, a conical weight was released from above into a 550 mm piece of 48.5 mm diameter

PVC pipe with the bottom edge at a distance of 10 mm above the water level. To ensure a

standardised protocol, fast-start variables were only measured when fish performed a C-start

(commencement of fast-start that results in the individual forming a C-shape, sensu Domenici

and Blake 1997). A minimum of 27 replicates (individual fish) per treatment group were

startled to ensure statistical robustness (controls – n = 34), non-parasitised - n = 34 and

parasitised - n = 27. Trials were conducted between 8:00 and 16:00 h. Kinematic variables

associated with the fast-start response were analysed using Image-J with a manual tracking

plug-in. The centre of mass (CoM) of each fish was tracked for the duration of the response.

The following kinematic variables were measured:

1. Response latency (s) was measured as the time interval between the stimulus onset and

the first detectable movement leading to the escape of the animal.

2. Response distance (m) is a measure of the total distance covered by the fish during the first

two flips of the tail (the first two axial bends, i.e., stages 1 and 2 defined based on Domenici

and Blake (1997), which is the period considered crucial for avoiding ambush predator attacks

(Webb 1976).

3. Response speed (m s-1) was measured as the distance covered within a fixed time (25 ms).

This fixed duration was based on the average duration (22.8 ms) of stage 1 and 2 (as defined

above).

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4. Maximum response speed (m s-1) was measured as the maximum speed achieved at any

time during stage 1 and stage 2.

After fish had been assessed for their routine swimming and fast-start responses, they were

euthanised by cold shock, blotted dry, immediately frozen in liquid nitrogen, and then

transferred back to James Cook University, Townsville, Australia where samples were analysed

for cortisol (controls – n = 14), non-parasitised - n = 13 and parasitised - n = 14.

Cortisol extraction and ELISA

Individual fish were freeze-dried (Christ Alpha 1-2 LDplus, 0.2 mbar, >16 h) and weighed

(Mettler Toledo UMX2 Ultra-Microbalance, 0.1 µg readability) before they were homogenized

in 2 ml Eppendorf vials, using a glass bead, 0.5 ml 1X phosphate-buffered saline (PBS, pH 7.4),

and a shaking mill (MP Biomedical FastPrep24, 3 min). Homogenized tissue was transferred to

a 10 ml glass vial and rinsed with additional 0.4 ml PBS. Ethyl acetate (Ajax Finechem, Thermo

Fisher Scientific) was added (1:9 ratio), and samples were vortexed (Ratek Vortex Mixer, 1

min) and centrifuged (Eppendorf centrifuge 5810 R, 3,500 rpm, 5 min, 4°C). Ethyl acetate has

been shown to be an effective organic solvent for extracting whole-body cortisol from early

life stages of fishes (Yeh et al. 2013). The supernatant was collected and transferred to a 28.5

ml glass vial, and this extraction step was performed four times with all collected supernatants

being pooled. The ethyl acetate was dried off in glass reaction tubes using a centrifugal

vacuum concentrator (Thermo Savant SpeedVac SC110A, 43°C). The samples were

reconstituted on the same day with 1 ml assay buffer and processed following the enzyme-

linked immunosorbent assay protocol provided by Cayman Chemical (Cortisol ELISA Kit,

Cayman Chemical Item Number 500360). The samples were analysed in triplicates with a

spectrophotometer (SpectraMax Plus 384 Microplate Reader, Molecular Devices, average

absorbance calculated from readings at 405 to 420 nm).

Cortisol ELISA validation

Several assay validation steps were performed to test for parallelism, accuracy, and precision

of the cortisol ELISA kit, following recommendations by Metcalfe et al. (2018). Parallelism was

confirmed by comparing dose-response curves of diluted samples against a standard curve

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(ANCOVA, p > 0.05, n = 3). In more detail, reconstituted samples (n = 3) were diluted in the

following series: 1:4, 1:8, 1:12, 1:16, 1:20, and 1:24. A cortisol standard curve, obtained from

the Cayman Chemical ELISA kit (6.6-4,000 pg ml-1 range), was used for assessing if the samples

matched the standard curve. An optimal dilution for the samples (20x) was observed at 50%

relative maximum binding, and sample dilutions falling within 20-80% B/B0 relative maximum

binding were considered as acceptable (Metcalfe et al., 2018). The accuracy of the method

(i.e., the recovery of a known amount of added cortisol) was assessed by spiking three samples

with 800 pg cortisol ml-1, more than half of the samples’ cortisol concentration and within the

detection limit of the Cayman Chemical ELISA kit (see Guest et al., 2016). For each of the three

samples, two fish were homogenized, pooled, and then split into even halves, with one half

receiving the spike and the other the assay buffer. Both parts were then processed in the same

way as all other samples. The spike’s recovery (percentage) was expressed as spiked sample

result – unspiked sample result x 100 / known spike (800 pg ml-1), and the mean recovery

(94.3%, n = 3) was used as correction factor for calculating the samples’ cortisol concentration.

Intra-assay precision of triplicate samples was determined using the coefficient of variation

(CV), and found to be 5.5±4.9 (mean±SD, n = 41).

Statistical analyses

Kinematic analysis

A preliminary analysis of covariance (ANCOVA) found that latency to respond to the startle

was positively related to distance to the stimulus, and the slope of the relationship did not

differ between the two treatments (i.e., homogeneous slopes; F2,84 = 1.77, p = 0.177). To

remove the influence of distance to the stimulus from latency (F1,84 = 11.29, p = 0.001), the

residuals of the relationship were used for subsequent analyses. No other variable was

affected by distance of the fish to the startle stimulus. A multivariate analysis of variance

(MANOVA) was undertaken to determine whether there was a difference in the routine

swimming or fast start kinematics of P. amboinensis after exposure to a single gnathiid.

Dependent variables included were: the fast-start variables distance, speed, maximum speed,

latency (residuals), and the routine swimming variables distance and speed. The nature of

significant differences found by MANOVA in relation to the original variables values were

then compared between treatments using canonical discriminant analyses (CDAs) to

determine how escape and swimming kinematics differed between treatments. Trends in the

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behavioural variables are represented as vectors, which are plotted on the first two canonical

axes, together with treatment centroids and their 95% confidence clouds (Seber 1984). The

strength or importance of each of the original variables in discriminating among groups is

displayed graphically as the length and direction of these vectors. To further explore the

differences between treatments, one-way ANOVAs were used to identify significant

differences within individual behaviours of interest. When significant, differences were

further examined using Tukey's HSD means comparison tests. Pairs of fish were successively

tested in the same water, however, in doing this, it is possible that the behaviour of the second

fish may have been influenced by chemical signals excreted from the first fish. To remove this

potential risk, we suggest using clean water for each trial. To account for this possible bias, we

undertook a repeated‐measures approach to test the potential effect of trial order influencing

the behaviour of the fish, while still allowing us to determine whether there was an effect of

gnathiid exposure. Here, a two‐way repeated‐measures MANOVA was undertaken on a subset

of pairs of fish to test the effect of trial order (1st or 2nd trial) and treatment (control; n - 8 pairs,

non-parasitized; n - 7 pairs and gnathiid; n - 5 pairs) on the routine swimming and fast start

kinematics of P. amboinensis. All assumptions of normality and homogeneity of variances

were visually inspected and found to have been met. Analyses were carried out in Statistica

version 13.

Cortisol analysis

The cortisol results were tested for homogeneity of variance which was found to be violated

(Bartlett’s test, p <0.001). Data were subsequently analysed using a Kruskal-Wallis test with

Dunn’s test and Holm-Sidak adjustment as post-hoc tests. All statistical analyses were

performed in R, version 3.5.1.

Results

Kinematic results

Exposure to a single gnathiid affected nearly all measured kinematic traits (Fig. 1, Fig. 2, Table

1). The MANOVA revealed a significant difference in the overall change in behaviour in

response to gnathiid exposure (Pillai’s Trace 0.414, F12, 164 =3.568 , p = <0.0001). A CDA

displayed the nature of the differences found among treatment centroids and shows a clear

separation of the three treatments into two distinct groups with respect to the six behavioural

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measurements, with the parasitised treatment being separate from the non-parasitised and

control treatments (Fig 1). Control fish and non-parasitised fish were differentiated from

parasitised fish along the first canonical axis, which accounted for 90.4% of the difference

among treatments. This axis was principally driven by trends in fast-start kinematics, which

indicated that control fish and non-parasitised fish travelled further, had higher average

speeds, and exhibited a more rapid response to the drop stimulus (i.e., lower response

latency) than parasitised fish. This suggestion was statistically confirmed by the results of the

one-way ANOVAs, with the parasitised group exhibiting reductions in performance in nearly

all measured traits (Fig. 2). For example, parasitised fish were slower to respond to the

stimulus with increased latency in this group (F 2,86 = 11.425, p = 0.001). The distance achieved

during stage 1 and 2 and the speed achieved during this same period was significantly reduced

(F 2,88 = 3.871, p = 0.0025; F 2,88 = 3.987, p = 0.0022) in fish that had been parasitised. In

addition, the distance and speed over a 2-min period was significantly reduced with

parasitised fish covering half of the distance covered by the control and the non-parasitised

groups (F 2,91 = 9.929, p = 0.001; speed F 2,91 = 9.997, p = 0.001). There was, however, no

significant difference among treatments in the maximum speed achieved during an escape (F

2, 87 = 1.818, p = 0.160). The repeated measures MANOVA revealed a significant effect of

treatment (Wilks 0.337, F8, 28 =2.523, p = 0.033). However, the order in which the trial

occurred was insignificant (Wilks 0.814, F4, 14 =0.7861, p = 0.547). There was also an

insignificant interaction between order of trial and treatment (Wilks 0.646, F8,

28 =0.851, p = 0.566). These results suggest that despite being tested in the same water as a

previous trial, there was no effect of this on routine swimming or fast-start escape behaviour.

Cortisol analysis

Cortisol concentrations were significantly different among treatments (Kruskal-Wallis test, p

< 0.001) but highest in ambon damselfish that were parasitised by gnathiids (Dunn’s post-hoc

test, p < 0.001, see Fig. 3, Table 2). Non-parasitised ambon damselfish showed comparable

cortisol levels to fish maintained under control conditions (Dunn’s post-hoc test, p = 0.244).

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Discussion

Predation is a central tenet in ecology – predators capture, kill, and consume their prey (Lima

and Dill 1990). By contrast, micropredators attack multiple hosts, may briefly feed on blood,

and can influence the mortality schedules of fish through changes in physiology, morphology,

and behaviour (Grutter et al. 2011; Binning et al. 2013; 2014; Artim et al. 2015; Triki et al.

2016; Grutter et al. 2017; Sellers et al. 2019). Here, we demonstrate that experimental

infection by a single gnathiid has a marked influence on the fast-start escape kinematics and

the routine swimming behaviour of settlement stage ambon damselfish. For example, latency

to respond when startled increased following gnathiid infection, and high latencies have been

associated with lower survival (McCormick et al. 2018). In addition to latency, all locomotory

behaviours, with the exception of maximum speed, were found to be reduced when compared

against the control and non-parasitised groups, indicating that there was a kinematic cost

associated with infection.

Fast-start escape behaviour is a measure of whole organism performance and is influenced by

intrinsic (i.e., physiological and biochemical) and extrinsic processes (i.e., habitat degradation,

predation stress, temperature, and oxygen) (McCormick et al. 2017; Allan et al. 2015;

Domenici et al. 2019). It is the interaction between these processes that can trigger and modify

how an escape is undertaken (Breed and Sanchez 2010). Any factor that disrupts these

processes can lead to increased mortality rates (Allan et al. 2013). Grutter et al. (2011)

quantified the cost of infection by a single gnathiid on newly recruited ambon damselfish,

using metabolic performance measured as oxygen uptake, and found infected fish had

reduced performance, likely driven by blood loss. Consequently, fishes infected with strongly

debilitating parasites may exhibit markedly reduced activity levels to conserve energy; this

may explain the observed decrease in fast-start behaviour in the current study. Infected fish

may have substantially decreased energy reserves (via blood loss), thus reducing the ability to

recover after eliciting an energetically costly escape. In addition, we also observed a 50%

decrease in routine swimming and average speed following infection by a single gnathiid.

Our results contrast those of Binning et al. (2014) who found that the escape performance of

S. bilineata was unaffected following infection by the cymothoid isopod, A. nemipteri, with

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little difference in escape kinematics between non-infected and infected fish. However, these

contrasting results may be driven by ontogeny. For example, Binning et al. (2014) used

infected adult fish (~130 mm body length) that may have a higher physiological tolerance to

infection than the newly recruited fish (~15mm BL) used in the current study. By examining

adult fish, the results may have been biased toward those individuals that could cope with

infection. Those that could not cope with infection may have been removed from the

population, thus underestimating the cost of infection. Moreover, the life history strategies of

the parasites used in both studies are markedly different. A. nemipteri remain on their host

for between 12-16 months and may not exert a major cost to the host, owing to their

dependence on host survival. By contrast, gnathiids have a larval phase consisting of three

stages and associated moults during which they feed on the blood of their host before

releasing from their host (Tanaka 2007). Therefore, the fitness cost exerted on their host is

much greater (i.e., 85% blood loss, sensu Grutter et al. 2011) and depends on the size of the

juvenile host (Grutter et al. 2017). Given an individual parasite is large, relative to its small

hosts (a 1:10 ratio gnathiid to a newly recruited ambon damselfish), it is not surprising that

we observed a significant reduction in the effectiveness of fast-start escape behaviour in the

ambon damselfish as a result of infection. Aside from gnathiid and cymothoid isopods, other

isopods are known to feed on blood or fluids of marine fishes, including cirolanid, coralanid

and aegeid isopods (Poore and Bruce 2012; Smit et al. 2019).

To date, few studies have explored how short-term infections with gnathiids affect coral reef

fish host stress physiology (Grutter and Pankhurst 2000; Grutter et al. 2011; Binning et al.

2014; Triki et al. 2016). We quantified total body cortisol levels following exposure to a

parasite and found that infection led to nearly a two-fold increase in cortisol levels. The effects

of elevated cortisol on behaviour in fish have been well-documented (Barton and Iwama

1991). However, to the best of our knowledge, this is the first study to investigate the

relationship between elevated cortisol and fast-start escape performance in fish. Increased

glucocorticoids prime animals for a number of activities, including reproduction, competition

and avoiding predation. Therefore, it seems likely that glucocorticoids would play an

important role in fast-start escape behaviour. However, if the stressor is severe, the ability of

the fish to cope may be reduced, and the overall effect of stress may become maladaptive

(Barton and Iwama 1991).

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Increased cortisol may be due to either the physiological cost of infection or to the discomfort

caused by the attachment of the parasite. For example, gnathiids were observed to be

attached around the anterior region of the fish. The anterior region is often dense with

nociceptors that, when stimulated, lead to quantifiable changes in neurological activity

(Sneddon et al. 2014) that is indicative of pain. To date, the effect of parasite attachment on

nociception has not been examined. However, it is possible that attachment could cause the

release of cortisol via the nociceptive system hormone (for review see Galhardo and Oliveira

2009). By contrast, it is possible that attachment could trigger an immune response with a

resulting increase in cortisol. The immune system and the release of glucocorticoids are tightly

coupled. Glucocorticoids have a strong anti-inflammatory effect and can induce relevant

changes in immune cells as well as cytokines having the power to stimulate cortisol production

(Wikel and Alarcon-Chaidez 2001; Fulford and Harbuz, 2005). Regardless of the mechanism(s),

our results suggest that short-term exposure to a gnathiid ectoparasite causes the release of

cortisol. Whether the release of cortisol following attachment has long-term effects is

unknown. However, this seems unlikely, given that cortisol rises quickly within the first 4-10

minutes of an experienced stress and lasts for only a few hours (Foo and Lam, 1993; Sumpter,

1997).

We found that by experimentally exposing coral reef fish recruits to gnathiids, their fast-start

escape performance was negatively affected. We also observed increased cortisol levels

following infection. A loss of fitness can decrease survival during metamorphosis as fish

transition from the pelagic to the benthic environment where they face myriad predators

(Hoey and McCormick 2004). Therefore, any external stressor (i.e., parasitism) that reduces

condition, affects behaviour, and/or alters physiology may indirectly increase mortality rates.

For example, Grutter et al. (2017) examined the effect of gnathiid infection on 14 species of

pre-settlement coral reef fish and found that, for small fish (<12 mm), there was significant

mortality following infection by a single gnathiid. This suggests that micropredators may

contribute to size-selective mortality during settlement. Moreover, parasites can interact

with other ecological drivers such as habitat degradation (Sikkel et al. 2019), resulting in an

increase in infection rates with potentially detrimental effects on biodiversity and ecosystem

health. The early life-history stages of marine fishes are critical for the replenishment and

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abundance of keystone species to marine ecosystems (Almany et al. 2007). As such, any

changes at this stage can compromise the integrity of adult populations.

Acknowledgements

We thank all the staff at the Lizard Island Research Station, and all the students and volunteers

that helped with the light traps and sorting of fish and in the maintenance of the gnathiid

culture. All work carried herein was in accordance with the James Cook University Animal

Ethics guidelines (JCU Animal Ethics approvals A2080, Great Barrier Reef Marine Park

Authority collection permit G12/35117.1.). Funding was provided by an Australian Research

Council Centre of Excellence for Coral Reef Studies (EI140100117). This work was supported

by the Australian Research Council (A00105175, A19937078, ARCFEL010G, DP0557058,

DP120102415), and the US National Science Foundation (OCE-724 1536794). B.I. was

supported by a postdoctoral research fellowship from the German Research Foundation (DFG,

IL-220/2-1) and the ARC Centre of Excellence for Coral Reef Studies.

Author contributions. BJMA, ASG, PCS and MIM conceived the study. BJMA, EM and PN

undertook the lab study. BJMA analysed the kinematic videos. BI and EF undertook the cortisol

analysis. MIM and BI analyzed the data. BJMA wrote the first draft of the manuscript, and all

authors contributed to the writing of the final manuscript. EF produced the figures.

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References

Allan, B. J.M., Domenici, P., McCormick, M. I., Watson, S. A., & Munday, P. L. (2013). Elevated CO2 affects predator-prey interactions through altered performance. PLoS One, 8(3), e58520. Allan B. J.M., Domenici, P., Munday, P. L., & McCormick, M. I. (2015). Feeling the heat: the effect of acute temperature changes on predator–prey interactions in coral reef fish. Conservation Physiology, 3(1), cov011. Allan, B. J.M., Domenici, P., Watson, S. A., Munday, P. L., & McCormick, M. I. (2017). Warming has a greater effect than elevated CO2 on predator–prey interactions in coral reef fish. Proceedings of the Royal Society B: Biological Sciences, 284(1857), 20170784. Almany, G. R., & Webster, M. S. (2006). The predation gauntlet: early post-settlement mortality in reef fishes. Coral reefs, 25(1), 19-22. Almany, G. R., Berumen, M. L., Thorrold, S. R., Planes, S., & Jones, G. P. (2007). Local replenishment of coral reef fish populations in a marine reserve. Science, 316(5825), 742-744. Artim, J. M., Sellers, J. C., & Sikkel, P. C. (2015). Micropredation by gnathiid isopods on settlement-stage reef fish in the eastern Caribbean Sea. Bulletin of Marine Science, 91(4), 479-487. Barber, I., Hoare, D., & Krause, J. (2000). Effects of parasites on fish behaviour: a review and evolutionary perspective. Reviews in Fish Biology and Fisheries, 10(2), 131-165. Barber, I. (2007). Parasites, behaviour and welfare in fish. Applied Animal Behaviour Science, 104(3-4), 251-264. Barton, B. A., & Iwama, G. K. (1991). Physiological changes in fish from stress in aquaculture with emphasis on the response and effects of corticosteroids. Annual Review of fish diseases, 1, 3-26.

Barton, B. A. (2002). Stress in fishes: a diversity of responses with particular reference to

changes in circulating corticosteroids. Integrative and comparative biology, 42(3), 517-525.

Binning, S. A., Roche, D. G., & Layton, C. (2013). Ectoparasites increase swimming costs in a

coral reef fish. Biology Letters, 9(1), 20120927.

Binning, S. A., Barnes, J. I., Davies, J. N., Backwell, P. R., Keogh, J. S., & Roche, D. G. (2014). Ectoparasites modify escape behaviour, but not performance, in a coral reef fish. Animal behaviour, 93, 1-7. Blake, R. W., Kwok, P. Y. L., & Chan, K. H. S. (2006). Effects of two parasites, Schistocephalus solidus (Cestoda) and Bunodera spp.(Trematoda), on the escape fast‐start performance of three‐spined sticklebacks. Journal of Fish Biology, 69(5), 1345-1355.

Jour

nal o

f Exp

erim

enta

l Bio

logy

• A

ccep

ted

man

uscr

ipt

Breed, M., & Sanchez, L. (2010). Both environment and genetic makeup influence behavior. Nature Educ Knowl, 1(10). Clague, G. E., Cheney, K. L., Goldizen, A. W., McCormick, M. I., Waldie, P. A., & Grutter, A. S. (2011). Long-term cleaner fish presence affects growth of a coral reef fish. Biology letters, 7(6), 863-865. Domenici, P., & Blake, R. (1997). The kinematics and performance of fish fast-start swimming. Journal of Experimental Biology, 200(8), 1165-1178. Domenici, P., Allan, B. J.M., Lefrançois, C., & McCormick, M. I. (2019). The effect of climate change on the escape kinematics and performance of fishes: implications for future predator–prey interactions. Conservation Physiology, 7(1), coz078. Fulford, A. J., & Harbuz, M. S. (2005). An introduction to the HPA axis. In Techniques in the Behavioral and Neural Sciences (Vol. 15, pp. 43-65). Elsevier. Foo, J. T. W., & Lam, T. J. (1993). Serum cortisol response to handling stress and the effect of cortisol implantation on testosterone level in the tilapia, Oreochromis mossambicus. Aquaculture, 115(1-2), 145-158. Gallaugher, P., Thorarensen, H., & Farrell, A. P. (1995). Hematocrit in oxygen transport and swimming in rainbow trout (Oncorhynchus mykiss). Respiration physiology, 102(2-3), 279-292. Galhardo, L., & Oliveira, R. F. (2009). Psychological stress and welfare in fish. Annual Review of Biomedical Sciences, 1-20. Grutter, A. S. (1994). Spatial and temporal variations of the ectoparasites of seven reef fish species from Lizard Island and Heron Island, Australia. Marine Ecology Progress Series, 115, 21-30. Grutter, A. S., & Poulin, R. (1998). Intraspecific and interspecific relationships between host size and the abundance of parasitic larval gnathiid isopods on coral reef fishes. Marine Ecology Progress Series, 164, 263-271. Grutter, A. S., & Hendrikz, J. (1999). Diurnal variation in the abundance of juvenile parasitic gnathiid isopods on coral reef fish: implications for parasite-cleaner fish interactions. Coral Reefs, 18(2), 187-191. Grutter, A. S., & Pankhurst, N. W. (2000). The effects of capture, handling, confinement and ectoparasite load on plasma levels of cortisol, glucose and lactate in the coral reef fish Hemigymnus melapterus. Journal of Fish Biology, 57(2), 391-401. Grutter, A. S. (2008). Interactions between gnathiid isopods, cleaner fish and other fishes on Lizard Island, Great Barrier Reef. Journal of Fish Biology, 73(9), 2094-2109.

Jour

nal o

f Exp

erim

enta

l Bio

logy

• A

ccep

ted

man

uscr

ipt

Grutter, A. S., Cribb, T. H., McCallum, H., Pickering, J. L., & McCormick, M. I. (2010). Effects of parasites on larval and juvenile stages of the coral reef fish Pomacentrus moluccensis. Coral Reefs, 29(1), 31-40. Grutter, A. S., Crean, A. J., Curtis, L. M., Kuris, A. M., Warner, R. R., & McCormick, M. I. (2011). Indirect effects of an ectoparasite reduce successful establishment of a damselfish at settlement. Functional Ecology, 25(3), 586-594. Grutter, A. S., Blomberg, S. P., Fargher, B., Kuris, A. M., McCormick, M. I., & Warner, R. R. (2017). Size-related mortality due to gnathiid isopod micropredation correlates with settlement size in coral reef fishes. Coral Reefs, 36(2), 549-559. Goodman, B. A., & Johnson, P. T. (2011). Disease and the extended phenotype: parasites control host performance and survival through induced changes in body plan. PLoS One, 6(5), e20193. Guest, T. W., Blaylock, R. B. and Evans, A. N. (2016). Development of a modified cortisol extraction procedure for intermediately sized fish not amenable to whole-body or plasma extraction methods. Fish Physiology and Biochemistry 42, 1–6. Hatcher, M. J., & Dunn, A. M. (2011). Parasites in ecological communities: from interactions to ecosystems. Cambridge University Press. Hoey, A. S., & McCormick, M. I. (2004). Selective predation for low body condition at the larval-juvenile transition of a coral reef fish. Oecologia, 139(1), 23-29. Holmes, T. H., & McCormick, M. I. (2006). Location influences size-selective predation on newly settled reef fish. Marine Ecology Progress Series, 317, 203-209. Jones, C. M., & Grutter, A. S. (2005). Parasitic isopods (Gnathia sp.) reduce haematocrit in captive blackeye thicklip (Labridae) on the Great Barrier Reef. Journal of Fish Biology, 66(3), 860-864. Josephson, R. K. (1993). Contraction dynamics and power output of skeletal muscle. Annual review of physiology, 55(1), 527-546. Kuris, A. M., & Lafferty, K. D. (2000). Parasite-host modeling meets reality: adaptive peaks and their ecological attributes. Evolutionary biology of host–parasite relationships: theory meets reality, 9-26. Kuris, A. M., Hechinger, R. F., Shaw, J. C., Whitney, K. L., Aguirre-Macedo, L., Boch, C. A., ... & Lorda, J. (2008). Ecosystem energetic implications of parasite and free-living biomass in three estuaries. Nature, 454(7203), 515. Lafferty, K. D., & Kuris, A. M. (2002). Trophic strategies, animal diversity and body size. Trends in Ecology & Evolution, 17(11), 507-513.

Jour

nal o

f Exp

erim

enta

l Bio

logy

• A

ccep

ted

man

uscr

ipt

Langerhans, R. B. (2009). Trade‐off between steady and unsteady swimming underlies predator‐driven divergence in Gambusia affinis. Journal of evolutionary biology, 22(5), 1057-1075. Lehmann, T. (1993) Ectoparasites: Direct Impact on Host Fitness. Parasitology Today 9, 8-13. Lima, S. L., & Dill, L. M. (1990). Behavioral decisions made under the risk of predation: a review and prospectus. Canadian journal of zoology, 68(4), 619-640. Marras, S., Killen, S. S., Claireaux, G., Domenici, P., & McKenzie, D. J. (2011). Behavioural and kinematic components of the fast-start escape response in fish: individual variation and temporal repeatability. Journal of Experimental Biology, 214(18), 3102-3110. McCormick, M. I. (2012). Lethal effects of habitat degradation on fishes through changing competitive advantage. Proceedings of the Royal Society B: Biological Sciences, 279(1744), 3899-3904. McCormick, M. I., Chivers, D. P., Allan, B. J.M., & Ferrari, M. C. (2017). Habitat degradation disrupts neophobia in juvenile coral reef fish. Global change biology, 23(2), 719-727. McCormick, M. I., Fakan, E., & Allan, B. J.M. (2018). Behavioural measures determine survivorship within the hierarchy of whole‐organism phenotypic traits. Functional ecology, 32(4), 958-969. McElroy, E. J., & De Buron, I. (2014). Host performance as a target of manipulation by parasites: a meta-analysis. Journal of Parasitology, 100(4), 399-411. Meekan, M., Wilson, S., Halford, A., & Retzel, A. (2001). A comparison of catches of fishes and invertebrates by two light trap designs, in tropical NW Australia. Marine biology, 139(2), 373-381. Metcalfe, S. S., Kroon, F. J., Beale, D. J. and Miller, G. (2018). Development of a validation protocol of enzyme immunoassay kits used for the analysis of steroid hormones in fish plasma. Journal of Experimental Marine Biology and Ecology 499, 26–34. Murray, M. D. (1990) Influence of host behaviour on some ectoparasites of birds and mammals. In: Barnard, C. J. and Behnke, J. M. (eds.) Parasitism and Host Behaviour. Taylor and Francis, London, pp. 290 - 315. Poore, G. C., & Bruce, N. L. (2012). Global diversity of marine isopods (except Asellota and

crustacean symbionts). PLoS One, 7(8).

Poulin, R., & Morand, S. (2000). The diversity of parasites. The quarterly review of biology, 75(3), 277-293.

Jour

nal o

f Exp

erim

enta

l Bio

logy

• A

ccep

ted

man

uscr

ipt

Quillfeldt, P., Martínez, J., Hennicke, J., Ludynia, K., Gladbach, A., Masello, J. F., ... & Merino, S. (2010). Hemosporidian blood parasites in seabirds—a comparative genetic study of species from Antarctic to tropical habitats. Naturwissenschaften, 97(9), 809-817. Rome, L. C., Funke, R. P., Alexander, R. M., Lutz, G., Aldridge, H., Scott, F., & Freadman, M. (1988). Why animals have different muscle fibre types. Nature, 335(6193), 824. Scarabello, M., Wood, C. M., & Heigenhauser, G. J. F. (1991). Glycogen depletion in juvenile rainbow trout as an experimental test of the oxygen debt hypothesis. Canadian Journal of Zoology, 69(10), 2562-2568. Sellers, J. C., Holstein, D. M., Botha, T. L., & Sikkel, P. C. (2019). Lethal and sublethal impacts of a micropredator on post-settlement Caribbean reef fishes. Oecologia, 189(2), 293-305. Seppälä, O., Karvonen, A., & Valtonen, E. T. (2005). Manipulation of fish host by eye flukes in relation to cataract formation and parasite infectivity. Animal Behaviour, 70(4), 889-894. Sikkel, P. C., Ziemba, R. E., Sears, W. T., & Wheeler, J. C. (2009). Diel ontogenetic shift in parasitic activity in a gnathiid isopod on Caribbean coral reefs. Coral Reefs, 28(2), 489-495. Sikkel, P.C. and Welicky, R.L., 2019. The ecological significance of parasitic crustaceans. In Parasitic Crustacea (pp. 421-477). Springer, Cham. Sikkel, P. C., Richardson, M. A., Sun, D., Narvaez, P., Feeney, W. E., & Grutter, A. S. (2019).

Changes in abundance of fish-parasitic gnathiid isopods associated with warm-water

bleaching events on the northern Great Barrier Reef. Coral Reefs, 38(4), 721-730.

Smit, N.J., Bruce, N.L. and Hadfield, K.A. eds., 2019. Parasitic Crustacea: State of knowledge

and future trends (Vol. 3). Springer.

Sneddon, L. U., Elwood, R. W., Adamo, S. A., & Leach, M. C. (2014). Defining and assessing animal pain. Animal behaviour, 97, 201-212. Strathmann, R. R., Hughes, T. P., Kuris, A. M., Lindeman, K. C., Morgan, S. G., Pandolfi, J. M., & Warner, R. R. (2002). Evolution of local recruitment and its consequences for marine populations. Bulletin of Marine Science, 70(1), 377-396. St. Juliana, J. R., Khokhlova, I. S., Wielebnowski, N., Kotler, B. P., & Krasnov, B. R. (2014). Ectoparasitism and stress hormones: strategy of host exploitation, common host–parasite history and energetics matter. Journal of Animal Ecology, 83(5), 1113-1123. Sumpter, J. P. (1997). The endocrinology of stress. Fish stress and health in aquaculture, 819, 95-118. Sun, D., Blomberg, S. P., Cribb, T. H., McCormick, M. I., & Grutter, A. S. (2012). The effects of parasites on the early life stages of a damselfish. Coral Reefs, 31(4), 1065-1075.

Jour

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logy

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uscr

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Tanaka, K. (2007). Life history of gnathiid isopods-current knowledge and future directions. Plankton and Benthos Research, 2(1), 1-11. Triki, Z., Grutter, A. S., Bshary, R., & Ros, A. F. (2016). Effects of short-term exposure to ectoparasites on fish cortisol and hematocrit levels. Marine biology, 163(9), 187. Walker, J. A., Ghalambor, C. K., Griset, O. L., McKenney, D., & Reznick, D. N. (2005). Do faster starts increase the probability of evading predators?. Functional Ecology, 19(5), 808-815. Webb, P. W. (1976). The effect of size on the fast-start performance of rainbow trout Salmo gairdneri, and a consideration of piscivorous predator-prey interactions. Journal of Experimental Biology, 65(1), 157-177. Wikel, S. K., & Alarcon-Chaidez, F. J. (2001). Progress toward molecular characterization of ectoparasite modulation of host immunity. Veterinary parasitology, 101(3-4), 275-287. Yeh, C. M., Glöck, M., & Ryu, S. (2013). An optimized whole-body cortisol quantification method for assessing stress levels in larval zebrafish. PloS one, 8(11), e79406.

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Table s

Table 1. Results of the analyses of variance on fast-start and routine swimming variables

comparing fish fed on by a gnathiid parasite, those managed to avoid parasitism and control

fish. Asterisks denote routine swimming variables. Eta-squared values are given as a measure

of effect size. Df = 2,87 (86 for routine swimming variables).

Variable F P η2

Latency 11.60 < 0.0001 0.21

Distance 3.96 0.023 0.080

Speed 4.06 0.02 0.086

Maximum speed 1.60 0.21 0.035

Distance travelled* 9.31 0.0002 0.18

Speed* 9.36 0.0002 0.18

Table 2: Cortisol content (pg ml mg-1 dry mass-1) of ambon damselfish exposed to gnathiids.

Treatment n Mean SD SE

Control 14 150.55 41.36 11.05

Non-parasitized 13 175.55 62.30 17.28

Gnathiid 14 365.98 179.35 47.85

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Figures

Figure 1: Comparison of the effect of gnathiid infection on swimming and escape kinematics

in the ambon damselfish Pomacentrus amboinensis. A canonical discriminant analysis

compares the behavioural changes in swimming and escape behaviour after exposure to a

gnathiid showing those parasitised, those fish that managed to avoid parasitism, and control

fish. Vectors represent the direction and intensity of trends in the prey performance: latency,

max speed, distance, speed, routine swimming (RS) speed and RS distance. The circles

represent 95% confidence intervals. N = controls (n=34), non-parasitised (n = 34) and

parasitised (n = 27).

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Figure 2: The effect of gnathiid infection on the swimming and escape kinematics in the ambon

damselfish Pomacentrus amboinensis. Variables displayed are: (a) mean speed (b) response

distance (c) max. speed (d) response latency (e) routine swimming distance (over 2 mins) (f)

routine swimming speed (over 2 min). Errors are standard errors. Letters above bars represent

Tukey’s HSD groupings of means. N = controls (n=34), non-parasitised (n = 34) and parasitised

(n = 27).

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Figure 3: Mean (±SD) cortisol concentration of ambon damselfish Pomacentrus amboinensis

in controls (n=14), and exposed to gnathiids. Cortisol levels of non-parasitised fish were

significantly lower (n = 13), compared to fish that were parasitised by a gnathiid (n = 14).

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