Environmental biology of fishes, tập 91, số 3, 2011

Environ Biol Fish (2011) 91:251–259
DOI 10.1007/s10641-011-9772-8

Evoked potential audiogram of the lined seahorse,
Hippocampus erectus (Perry), in terms of sound pressure
and particle acceleration
Paul A. Anderson & David A. Mann

Received: 12 March 2010 / Accepted: 4 February 2011 / Published online: 13 May 2011
# Springer Science+Business Media B.V. 2011

Abstract The hearing sensitivity of the lined seahorse,
Hippocampus erectus (Perry), was determined for both
sound pressure and particle acceleration using the
auditory evoked potential (AEP) technique. Hippocampus erectus demonstrates hearing sensitivity typical of
historically characterized hearing generalist fishes, with
best sensitivities below 600 Hz and maximum sensitivities of 105.0±1.5 dB SPL (re: 1 μPa) and 3.46×
10−3 ±7.64×10−4 m s−2 at 200 Hz. The shapes of the
audiograms for each modality are similar, suggesting
relative similarity in sensitivity between modalities for a
given frequency. In light of the importance of broadband sound in the acoustic landscape of this fish’s
environment, and broadband conspecific sound production that may be used in intraspecific acoustic commuP. A. Anderson (*)
IFAS/SFRC Program in Fisheries and Aquatic Sciences,
University of Florida,
7922 NW 71st Street,
Gainesville, FL 32653, USA
e-mail:
D. A. Mann
College of Marine Science, University of South Florida,
140 7th Avenue South,

St. Petersburg, FL 33701, USA
e-mail:
Present Address:
P. A. Anderson
Center for Conservation, The Florida Aquarium,
701 Channelside Drive,
Tampa, FL 33602, USA

nication, audition to broadband sounds was also
estimated. Maximum broadband sensitivity at 200 Hz
is estimated to be 92.0±1.5 dB SPL (re: 1 μPa) and
7.73×10−4 ±1.71×10−4 m s−2.
Keywords Evoked potential . Audiogram .
Hippocampus erectus . Seahorse . Acoustic .
Particle acceleration

Introduction
The auditory evoked potential (AEP) technique to
measure hearing ability is widely practiced among
human clinicians (e.g., Davis 1976; Picton et al. 1981;
Schroeder and Kramer 1989) and has been expanded to
test hearing ability of representatives from many
vertebrate taxa (Corwin et al. 1982), including fishes
(Kenyon et al. 1998). It is a non-invasive far-field
recording of synchronous neural activity in the eighth
nerve and brainstem auditory nuclei elicited by acoustic
stimuli (Jacobson 1985).
Our objective was to characterize the hearing ability
of the lined seahorse (Hippocampus erectus Perry) in a
comprehensive manner by measuring both the pressure

and particle acceleration of the acoustic stimuli in
hearing tests. These components of sound contribute in
different ways in the near-field and far-field of sound
sources. A vibrating sound source produces two
physical changes in the surrounding environment:
particle motion and pressure wave propagation of the


252

surrounding medium (Dusenbery 1992). The near-field
of a sound source is dominated by local hydrodynamic
flow, established by the displacement of water molecules (particle motion) adjacent to the sound source
(Bass and Clark 2003). In the far-field, acoustic
pressure is proportional to particle velocity (Medwin
and Clay 1998).
It is generally well-accepted that fishes historically
characterized as hearing specialists (Popper et al. 2003;
but see Popper and Fay 2011) respond to both particle
motion and pressure, but are more sensitive to pressure
particularly in the far-field and at frequencies above
70 Hz (Fay et al. 1982). Fishes historically characterized as hearing generalists, that have no specialized
connections between the swim bladder and inner ear,
have yielded equivocal data concerning the relative
importance of pressure sensitivity to sound detection
and processing (Cahn et al. 1969; Sand and Enger
1973; Chapman and Johnstone 1974; Fay and Popper
1975; Jerkø et al. 1989; Yan et al. 2000; Lovell et al.
2005; Horodysky et al. 2008; Wysocki et al. 2009).
The summation of this literature suggests that both

acoustic modalities may be detected and processed by
fishes classically characterized as hearing generalists,
though the relative contributions of each may vary with
respect to distance, frequency, and sound pressure
level. Because fishes historically characterized as
generalists may in fact be processing both particle
motion and pressure components of sound, this
has led Popper and Fay (2011) to discourage the
dichotomy of characterizing fishes as either hearing
specialists or generalists, but instead to consider the
relative importance of sound pressure in hearing
among fishes along a continuum of species. Thus,
both modalities of particle acceleration and sound
pressure are reported here.

Materials and methods
Animal accession, holding, and husbandry procedures
Lined seahorses (H. erectus) were collected as bycatch
from shrimp trawl nets and donated by local fishermen.
Upon accession, animals were quarantined for 1 month
prior to transfer to a sound-dampened holding system.
Clear round acetate tags (approx. 1 cm diameter) were
marked with alphanumeric codes, hung on monofilament line collars, and tied around the necks of

Environ Biol Fish (2011) 91:251–259

seahorses (tagging methods modified from Vincent
and Sadler 1995). Animals were fed frozen mysids
(Piscine Energetics, Kelowna, BC, Canada) in the
mornings and live Artemia sp. (Sea Critters, Key

Largo, FL, USA) enriched with Roti-Rich (Florida
Aqua Farms, Inc., Dade City, FL, USA) in the
afternoons. Tanks were siphoned clean of debris twice
daily and system water changes of 10% were
performed weekly. Water quality parameters remained
within the following ranges during holding: Temperature, 25–27°C; salinity, 28.5–31.5; ammonia–nitrogen,
0 mg L−1; nitrite–nitrogen, 0 mg L−1; nitrate–nitrogen,
2.8–22.7 mg L−1.
Eleven animals were transferred to a soundproofed tank with an established biological filter 2
to 11 days prior to testing. Soundproofing was
accomplished by resting the frame of the tank on a
sturdy lab bench with sections of bearing felt,
installing a subsurface drain that transferred water to
a sump resting on the floor where filtration occurred,
and using a quiet, 15 W water pump with a flexible
return pipe that returned water to the tank below the
water surface. A loop was suspended in the flexible
return line; this attenuated vibration and sound
travelling through the return water and pipe walls
(A. Noxon, Acoustic Sciences Corp., Eugene, OR,
USA, pers. comm., Fig. 1). The ambient noise
profiles of both the holding system and the soundproofed tank were measured with an HTI-96-min
hydrophone (High Tech Instruments, Inc., Gulfport,
MS, USA, sensitivity = −164.1 dB re: 1 VμPa−1,
bandwidth = 2–30,000 Hz), for sound pressure level
(SPL) measurements. The ambient noise profile of the
sound-proofed tank was also measured with an Acoustech geophone probe (Acoustech Corp., State College,
PA, USA, sensitivity = 212 Vm−1 s−1, bandwidth =
100–1,000 Hz) for measurements of particle motion.
Both instruments, when in use, were connected to the

line-in port of a laptop computer running CoolEdit
(Syntrillium Software Corp., Phoenix, AZ, USA).
Hydrophone recordings were collected from the middle
and bottom of tanks. Geophone recordings were
collected from the bottom of tanks in the center, along
three orthogonal axes, because particle motion is a
vector quantity (as opposed to pressure, which is a
scalar quantity). Resulting sound files were calibrated
according to manufacturer instructions and postprocessed with SpectraPlus (Pioneer Hill Software,
Poulsbo, WA, USA). Analysis settings used in Spec-


Environ Biol Fish (2011) 91:251–259

253

Fig. 1 Soundproofed
laboratory tank

Subsurface
Return
Subsurface
Drain

Rag
Animal Holding
Tank

Bearing
Felt

Lab Bench
Clamp
Flexible
Tubing
Soundproofing
Loop
Sponge

Sump

Pump
Stand

traPlus are summarized in Table 1. The Acoustech
geophone probe measures particle velocity. To convert
to acceleration, Fast-Fourier Transforms (FFT’s) processed by SpectraPlus were exported into a spreadsheet

program and particle velocity values converted to
particle acceleration using the following formula:
a ¼ v2pf

ð1Þ

Table 1 SpectraPLUS analysis settings
Ambient noise analysis

AEP stimulus analysis

Sampling rate (Hz)

44100

48828

Sampling format

16-bit

16-bit

Standard Hz weighting

Flat (none)

Flat (none)

Decimation ratio

11

12

Frequency limit

2004.545 Hz, Low-pass filter enabled

2034.500 Hz, Low-pass filter enabled

FFT size

4096

4096

Spectral line resolution

0.979 Hz

0.993 Hz

Smoothing window

Hanning

Hanning

Averaging settings

Infinite, linear, Disable peak hold

1, linear, Enable peak hold

FFT overlap

0%

99%

Time resolution

1021.68 ms

10.07 ms

Input signal overload

Enable overload detection

Enable overload detection

Exclude overloaded data from processor

Exclude overloaded data from processor


254

Environ Biol Fish (2011) 91:251–259

where a = acceleration (m s−2), v = velocity (m s−1),
π = pi (~3.14), and f = frequency (Hz) (Casper and
Mann 2006). The magnitude of particle acceleration
was calculated by vector averaging according to the
following equation:
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
a ¼ x2 þ y2 þ z 2
ð2Þ

SigGen and BioSig software. Sounds were generated
by an RP 2.1 Enhanced Real-Time processor, fed

through a PA5 programmable attenuator to control
sound level, and amplified by a Hafler Trans.Ana
P1000 110 W professional power amplifier before
being sent to the UW30 speaker, where sound was
emitted.

where a = magnitude of acceleration (m s−2), and x,
y, and z refer to acceleration (m s−2) in each of three
orthogonal axes.

Sound generation, calibration, and AEP acquisition

Experimental setup

Acoustic stimuli were calibrated with the HTI-96-min
hydrophone for pressure measurements of tones and the
Acoustech geophone in three orthogonal axes for
particle motion, all connected to the RP 2.1 processor.
During calibration, the hydrophone or geophone was
positioned in the experimental setup in place of the fish
at the level of the animal’s head, and the stimulus
presentation protocol as described for AEP acquisition
was executed, except without phase alternation. Signals
were captured and averaged by BioSig. Resulting time
domain averaged signals were exported as ASCII
formatted files, imported in SpectraPlus, and 4,096
point FFTs run (SpectraPlus settings in Table 1) to
generate power spectra, from which peak amplitude
measurements were taken. Particle acceleration was
calculated per Eqs. 1 and 2. Calibration runs were

conducted daily.

The testing chamber consisted of a steel tube (1.22 m
high, 20.32 cm diameter, 0.95 cm thickness), closed at
the bottom with a square steel plate (60.96×60.96 cm),
and oriented vertically. Four 51700 Series anti-vibration
floor mounts (Tech Products Corp., Miamisburg, OH,
USA) were placed under each corner of the base of the
tank. The tube was filled with saltwater of approximately
26°C up to a height of 1.12 m. A laboratory stand was
supported on an adjacent vibration-isolated table and
scaffolding descended into the tube for animal suspension. A UW30 speaker (University Sound, Oklahoma
City, OK, USA) was placed at the bottom of the tube in
the centre. This setup was enclosed inside an audiology
booth.
For testing, individual fish were secured in a
harness constructed from Nitex mesh, fastened with
clamps to scaffolding 2.5 cm below the water surface.
The harness restricted movement while allowing
normal respiration. Sub dermal stainless steel needle
electrodes (Rochester Electro-Medical, Inc., Tampa,
FL, USA) were used to record the AEP signal. An
electrode was inserted about 1 mm into the head, over
the medulla region. Reference and ground electrodes
were placed directly in the water in close proximity to
the fish. Evoked potentials recorded by the electrode
were fed through an HS4 fiber optic head stage
(Tucker-Davis Technologies [TDT], Alachua, FL,
USA) and into an RP 2.1 processor (TDT), routed
into the computer and averaged by BioSig software

(TDT). All eleven seahorses were tested for AEP’s to
tone stimuli (described below); also, a dead goldfish
(Carassius auratus) was run to generate control AEP
signals.
Sound stimuli and AEP waveform recordings were
produced with a TDT AEP workstation running

Calibration

AEP acquisition
Stimuli consisted of 60 ms pulsed tones gated with a
Hanning window. The phase of the tone was
alternated between presentations to minimize electrical artifacts from the recordings. During each trial,
nine different frequencies were presented: 100, 200,
300, 400, 600, 800, 1,000, 1,500, and 2,000 Hz.
Amplitudes at each frequency were presented within a
range of approximately 74 to 148 dB re: 1 μPa and
8.60×10−6 to 0.67 ms−2, beginning at amplitudes
below threshold and increasing in 6 dB steps until a
threshold was visually detected in the digital signal
output (see Data analysis). Post-hoc trials were run at
amplitudes that were 3 dB below visual threshold to
improve the resolution of threshold determination. Up
to 2,000 signal presentations (or until detection was
visually confirmed) were averaged to measure the
evoked response at each level of each frequency.


Environ Biol Fish (2011) 91:251–259

255

Data analysis
Evoked potential traces were transformed with the
Hanning window function and converted to power
spectra with a 2048-point FFT in BioSig. Evoked
potentials are visualized as peaks that occur at twice
the frequency of the presented stimulus (Fig. 2). This is
a well-established phenomenon in evoked potentials of
fishes to pure tones in the frequency domain (Egner
and Mann 2005). Visualized peaks were considered
true evoked potentials if they were at least 3 dB above
the average of all peaks occurring within a window of
50 Hz above the presented stimulus frequency. AEP
thresholds were defined as the lowest amplitude at
which a true evoked potential, according to these
criteria, was visualized. AEP waveforms of live
seahorses were checked against AEP waveforms of
dead goldfish to ensure that the identified peak was not
a stimulus or electrical artifact.
Audition of broadband noise was estimated using
calculations proposed by Yost (2000) and employed by
Egner and Mann (2005) for hearing in damselfish.
Specifically, the tonal audiogram was adjusted by an
estimated critical bandwidth that is assumed to be 10%
of the center frequency. Because sound pressure is
expressed on a logarithmic scale (dB), this estimated
adjustment is:
tb ¼ ts À 10 logð0:1f Þ

ð3Þ

Fig. 2 Auditory evoked potentials (AEPs) to a 400 Hz tone pip
depicted in the time domain (left) and in the frequency domain
(right). a Control AEP waveform (dead goldfish). b,c,d AEP
waveforms of H. erectus at progressively lower amplitudes. d

where tb = broadband threshold, ts = spectrum-level
threshold (both in dB re: 1 μPa), and f = frequency
(Hz). A similar estimate of the audition of broadband
noise in terms of acceleration was calculated by first
converting acceleration thresholds to velocity (because
in an ideal far-field situation, velocity is proportional to
pressure, Urick 1975), and using Eq. 3 with dBvelocity substituted for pressure. The resulting velocity
was then converted to acceleration using Eq. 1.

Results
Ambient noise
The long-term holding tanks in which animals were
housed prior to transfer to the AEP laboratory demonstrated an average total RMS power (within the 2 to
998 Hz frequency range) of 117.4±0.9 dB SPL (re:
1 μPa) at the middle of the water column and 128.8±
1.4 dB SPL (re: 1 μPa) at the bottom. The soundproofed
AEP laboratory tank demonstrated an average total
RMS power of 115.8±0.5 dB SPL (re: 1 μPa) at the
middle of the water column and 120.5±0.2 dB SPL (re:
1 μPa) at the bottom. In terms of particle acceleration,
the soundproofed AEP laboratory tank demonstrated a
vector-averaged total RMS power of 4.58×10−3 m s−2,
comprised of total RMS powers of 2.38×10−3 on the

represents amplitude at threshold. Asterisks denote AEPs that
occur at twice the frequency of the presented stimulus (in this
case, 800 Hz)


256

Environ Biol Fish (2011) 91:251–259

horizontal-length (x) axis, 1.82×10−3 on the horizontaldepth (z) axis, and 3.47×10−3 on the vertical (y) axis.
AEP
Average hearing thresholds from 11 H. erectus are
reported in Table 2 for both sound pressure and
particle acceleration. For sound pressure, this species’
most sensitive hearing range is below 400 Hz, with
minimum thresholds at 200 Hz (tonal threshold,
105.0±1.5 dB SPL re: 1 μPa; estimated broadband
threshold, 92.0 ± 1.5 dB). Above 600 Hz, tonal
hearing thresholds increase to levels above most
environmentally relevant noise (Wenz 1962; Urick
1975). For particle acceleration, this species’ most
sensitive hearing range is below 800 Hz, with
minimum thresholds of 3.46×10−3 ±7.64×10−4 m s−2
(tonal) and 7.73×10−4 ±1.71×10−4 m s−2 (estimated
broadband) at 200 Hz (Fig. 3).

Discussion
Hippocampus erectus demonstrates sound pressure
sensitivity that falls within the range of sensitivities

documented for other fishes historically characterized
as hearing generalists (e.g., Kenyon et al. 1998; Yan
2001; Scholik and Yan 2002; Lugli et al. 2003; Egner
and Mann 2005; Lovell et al. 2005; Casper and Mann
2006; Fig. 4a). While this species’ hearing sensitivity
was tested at frequencies up to 2,000 Hz (for sound
pressure), tonal thresholds at frequencies above
600 Hz begin to rise into a range of high SPL’s that
animals are not likely to encounter in the natural
Table 2 Hearing thresholds
of H. erectus (mean ± SE).
Tonal thresholds were
adjusted by an estimated
critical bandwidth that is
assumed to be 10% of the
center frequency to estimate
broadband thresholds, per
Yost (2000)

Frequency (Hz)

environment (Wenz 1962; Urick 1975). Like other
generalists, H. erectus also does not appear to have
any bony or gaseous vesicular connections between
the swimbladder and the inner ear (pers. obs.).
In light of these observations, it is especially
pertinent to report this animal’s audiogram in terms
of particle acceleration, as direct detection of
particle motion in the inner ear is thought to be
the predominant mode of sound reception in fishes

historically characterized as hearing generalists
(Fay and Popper 1975; Popper and Fay 1993).
Likewise, particle acceleration thresholds for the
lined seahorse fall into a range of sensitivities
documented in other generalist fishes and elasmobranches (Casper and Mann 2006; Wysocki et al.
2009; Fig. 4b).
There is remarkable similarity between the shapes of
the audiograms for sound pressure and particle acceleration. Despite the fundamental differences between the
pressure and particle motion component of sound, and
the fundamental differences in the way each modality is
processed by fishes, fishes historically characterized as
specialists (e.g., Ictalurus punctatus, Fay and Popper
1975; some sciaenids, Horodysky et al. 2008) and
generalists (e.g., Ginglystoma cirratum, Casper and
Mann 2006; some sciaenids, Horodysky et al. 2008;
Gobius cruentatus, Chromis chromis, Sciaena umbra,
Wysocki et al. 2009) demonstrate similarities between
the shape of audiograms for each acoustic modality.
Tests that have shown dissimilarities (e.g., Hawkins
and Johnstone 1978; Kelly and Nelson 1975) may be
due to artifactual acoustic discontinuities between
sound pressure and particle motion in constrained
testing environments.

Sound pressure (dB re: 1 μPa)

Particle acceleration (m s−2)

Tonal

Tonal

Broadband

Broadband

100

107.5±2.2

97.5±2.2

0.006248±0.001295

0.001976±0.000409

200

105.0±1.5

92.0±1.5

0.003458±0.000764

0.000773±0.000171

300

109.9±2.5

95.1±2.5

0.007616±0.001695

0.001391±0.000310

400

116.1±1.7

100.1±1.7

600

117.6±1.8

99.8±1.8

0.011851±0.003116

0.001530±0.000402

800

127.7±1.0

108.7±1.0

0.039984±0.005986

0.004470±0.000669

1,000

132.7±1.9

112.7±1.9

0.081532±0.029967

0.008153±0.002997

1,500

133.2±1.8

111.4±1.8

2,000

136.3±1.9

113.3±1.9


Environ Biol Fish (2011) 91:251–259

b

140

SPL (dB re: 1 µPa)

135
130
125
120
115
110
105
100
95
90
100

1

Particle acceleration (m s-2)

a

257

1000

0.1

0.01

0.001

0.0001
100

10000

Frequency (Hz)

1000

Frequency (Hz)

Fig. 3 Audiogram of the lined seahorse, H. erectus, for a sound pressure, and b particle acceleration. (●) = threshold to tonal stimuli,
(○) = predicted threshold to broadband stimuli. Error bars represent mean ± SE

the lined seahorse is exposed are broadband in nature.
Ambient environmental noise is broadband (Wenz
1962; Urick 1975). Greatest hearing sensitivity among
hearing generalist fishes tends to fall in the range of 50–
500 Hz, precisely the range at which ambient noise in
shallow water tends to be propagated (Bass and Clark
2003), leading Popper and Fay (1999) to postulate that
hearing among (generalist) fishes first evolved to
evaluate the broadband “auditory scene.” The role of
hearing in intraspecific acoustic communication is also
important for soniferous fishes, including the seahorse.
Fish (1953) and Colson et al. (1998) characterized the
seahorse click; it is a broadband sound that is emitted
by stridulation of the posterior process of the supra-

The lack of commercially available accelerometers
has hindered ability to evaluate audition to particle
motion. Audition to true sound stimuli that are
comprehensively characterized in terms of sound
pressure and particle motion has only recently been
reported (e.g., Casper and Mann 2006; Horodysky et al.
2008; Wysocki et al. 2009) as a result of recent
developments in commercially available accelerometers (McConnell 2003; McConnell and Jensen 2006).
This work is a contribution to these few, but growing,
number of studies.
In the audiograms presented, audition of broadband
sound is estimated (per Yost 2000; Egner and Mann
2005), as most biologically significant sounds to which

b

140

Particle acceleration (m s-2)

a
SPL (dB re: 1 µPa)

130
120
110
100
90
80
70

60
100

1000

Frequency (Hz)

Fig. 4 Audiograms of representative hearing generalist fishes,
measured by the AEP technique. a Sound pressure: In this
comparative audiogram, the hearing specialist Carassius auratus is also represented for comparison. (●) = Hippocampus
erectus (this study), (■) = Lepomis macrochirus (Scholik and
Yan 2002), (□) = Opsanus tau (Yan 2001), (▲) = Padogobius
martensii (Lugli et al. 2003), (○) = Astronotus ocellatus

0.1

0.01

0.001

0.0001
100

1000

Frequency (Hz)

(Kenyon et al. 1998), (Δ) = Carassius auratus (Kenyon et al.
1998). b Particle acceleration: (●) = Hippocampus erectus (this
study), (■) = Ginglymostoma cirratum (Casper and Mann

2006), (□) = Urobatis jamaicensis (Casper and Mann 2006),
(▲) = Sciaena umbra (Wysocki et al. 2009), (○) = Gobius
cruentatus (Wysocki et al. 2009), (Δ) = Chromis chromis
(Wysocki et al. 2009)


258

occipital against the coronet (Colson et al. 1998). It is
demonstrated in many behavioral contexts, including
feeding (Colson et al. 1998), aggression and competition for mates (Vincent 1994), and distress (Fish 1953).
Traditional audiograms present audition to tonal stimuli
of a range of frequencies, but in light of the relevance
of broadband sounds in the natural history of fishes,
audition to broadband stimuli should also be measured
or estimated.
Acknowledgments Many thanks to B. Casper, M. Hill Cook,
R. Hill, and J. Locascio (University of South Florida) for guidance
with AEP methodology, A. Noxon (Acoustic Sciences Corporation), who shared soundproofing design concepts, R. Shrivastav
(University of Florida) and J. Pattee (Pioneer Hill Software) for
guidance with sound analysis, P. Perkins (Florida Aquarium) for
illustrations provided in Figs. 1 and 2, and W.J. Lindberg, D.
Murie, D. Parkyn, C. St. Mary (University of Florida), I. Berzins
(Florida Aquarium), H. Masonjones (University of Tampa), and
two anonymous reviewers, who provided constructive criticism
for improvement of the manuscript.
Seahorses were donated by Above the Reef and R. Stevens,
his crew, and the Twin Rivers Marina. Live brine shrimp was
donated by Sea Critters, Inc. P. Anderson was supported by the
University of Florida Alumni Fellowship, the Morris Animal

Foundation, The Florida Aquarium Center for Conservation,
The Spurlino Foundation, and an anonymous donor.
Animal collection was authorized by the Florida Fish and
Wildlife Conservation Commission Special Activities License
#05SR-944 and husbandry and experimental protocols were
authorized by the University of Florida IACUC Protocol #D-432,
by the University of South Florida IACUC Protocol #2118, and by
the Florida Aquarium Animal Care and Use Committee.

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Environ Biol Fish (2011) 91:261–274
DOI 10.1007/s10641-011-9776-4

Spatial and seasonal patterns in freshwater ichthyofaunal
communities of a tropical high island in Fiji
Aaron P. Jenkins & Stacy D. Jupiter

Received: 14 July 2010 / Accepted: 16 January 2011 / Published online: 7 April 2011
# Springer Science+Business Media B.V. 2011

Abstract We surveyed freshwater ichthyofaunal
communities in streams of Vanua Levu, Fiji, under a
range of land cover to assess differential, seasonal
effects on fish abundance and diversity. We collected
fish from 32 families, 19 genera and 87 species,
representing approximately 50% of the known Fijian
freshwater and estuarine fish fauna. Position in reach
was the strongest overall factor influencing fish
abundance and diversity, particularly in the larger,
steeper catchments. However, fish communities
exhibited strong seasonal specificity with over half
(55%) of species observed in only one season. There
were greater numbers of estuarine and marine
migrants and fishes with poor swimming ability in

the dry season, with more schooling species, large
predators and fish that prefer muddy benthos in the
wet. In the more pristine catchments of Kubulau
District, higher species abundance and diversity were
observed in the wet season and were associated with
significantly greater flow, pH and dissolved oxygen.

A. P. Jenkins (*)
Wetlands International-Oceania,
University of the South Pacific,
Suva, Fiji
e-mail:
S. D. Jupiter
Wildlife Conservation Society,
11 Ma’afu Street,
Suva, Fiji

We observed the opposite pattern for fish diversity
and abundance from the more degraded catchments of
Macuata Province. These results suggest that the wet
season is having a net positive effect on habitable
space for fishes in Kubulau and a net negative effect
in Macuata, as species may be lost due to increased
runoff from heavily cleared and cultivated catchments. Integrated water resource management across
the full range of habitats utilized by Fiji’s freshwater
fishes is recommended in order to maintain species
diversity and abundance.
Keywords Freshwater fish . Diversity . Seasonality .
High island . Land cover . Fiji

Introduction
Many mechanisms have been recognized to account for
the distribution of fish species in tropical stream systems.
Natural factors include biogeography (Baranescu 1990;
Covich 2006; Jenkins et al. 2010), geography and
catchment topography (Pusey et al. 1995; Russell et al.
2003), and ecological processes (e.g. predation, competition, food web interactions; Zaret and Rand 1971;
Power 1983). Anthropogenic disruption to catchment
forest cover and hydrology also affects fish distributions
by reducing habitat quality and forming barriers to
dispersal (Holmquist et al. 1998; Eikaas and McIntosh
2006; Jenkins et al. 2010). In addition, strong seasonal
differences in rainfall may result in short-term shifts in


262

community structure as flood pulses affect habitat
availability and condition.
Junk et al. (1989) proposed that community
structure may reflect species and life history characteristics adapted to flood pulses. During flood events
there are large fluctuations in physicochemical characteristics, such as temperature, conductivity, pH,
depth and flow, which can directly and indirectly
influence fish community assemblages (Boujard
1992; Winemiller and Jepsen 1998; Almirón et al.
2000; Galacatos et al. 2004). A considerable body of
research has been conducted on seasonality in fish
assemblages in tropical communities from flooded
forests of South America to Africa. Large river basins
of the Amazon and Congo have highly diverse

communities dominated by species that are welladapted to unpredictable variations in water level and
temperature (Lowe-McConnell 1987; Jepsen 1997).
In these equatorial basins, fishes disperse into flooded
forests and lakes to feed soon after rising water levels
and their subsequent movements may be responding
to low concentrations of dissolved oxygen as plant
matter decays (Lowe-McConnell 1987).
Morphological characteristics that may have evolved
in response to seasonal fluctuations in flow and the
temporal impermanence of tropical streams include
anguilliform shape, dorso-lateral flattening and the
pelvic suction disc (Ryan 1991; Keith 2003; Jenkins
et al. 2010). In addition, there are several life history
strategies associated with strong seasonality. These
include the “periodic” strategy, with high reproductive
output and low parental care (Winemiller 1989;
Tedesco et al. 2008), and the more specific form of
amphidromy, characterized by reproduction in freshwater followed by an obligate downstream migration
of larvae to the sea before fish return upstream as postlarvae cued by large freshwater pulses (Delacroix and
Champeau 1992; Fitzsimons et al. 2002; McDowall
2007; Keith et al. 2008). Such migrations provide
seasonal pulses of biomass from multiple fish species,
but can be negatively affected by degraded water
quality and disruptions to hydrologic flow (Jenkins et
al. 2010). As strong seasonality and steep topography
are dominant features of most tropical, high island
systems in the Pacific (Terry and Raj 2001), these
specialized adaptations may have contributed to some
of the highest global endemism density in freshwater
fish fauna when Pacific Island species richness is

adjusted for land area (Abell et al. 2008).

Environ Biol Fish (2011) 91:261–274

To our knowledge, very few studies have examined seasonality in freshwater fish assemblages of
Pacific island communities. To address this information gap, we investigated differences in fish communities along lower, mid and upper reaches of two
regions of Vanua Levu, Fiji, during the wet and dry
seasons, to assess the main drivers of community
composition as well as specific differences related to
seasonality. We hypothesize that in near pristine,
tropical high island catchments, the wet season offers
greater habitable space for freshwater fishes and cues
upward migrations of amphidromous species. In
addition, given that Jenkins et al. (2010) showed
significant loss of fish diversity when catchment
forest cover fell below 50%, we postulate that
increased sediment-laden runoff during the wet
season may negatively affect fish diversity and
abundance in degraded catchments. Based on our
findings, we develop management recommendations
for best practice actions to preserve and/or restore
habitat for Fiji’s freshwater fishes.

Methods
Study site
The Fiji island archipelago, located between 12–22°S
and 176°E–178°W, includes 332 islands, of which
Vanua Levu is the second largest (5,807 km2; Neall
and Trewick 2008). The southeast sides of Vanua
Levu, like the other main islands of Viti Levu and

Taveuni, face the prevailing trade winds and therefore
receive higher mean precipitation than the northwest,
where rain is shadowed by interior highlands (Terry
2005; Fig. 1). The climate is seasonal with a wet
season frequented by tropical cyclones between
November and April and a dry season from May to
October. During the dry season, rainfall seasonality is
more pronounced for the leeward northwest, which
receives only 20% of the annual total in the dry
months compared with 33% on the windward side
(Terry 2005).
Freshwater fish surveys
We surveyed fish species richness and abundance in
rivers and stream of Kubulau District and Macuata
Province of Vanua Levu, Fiji, during the dry season of


Environ Biol Fish (2011) 91:261–274

263

Fig. 1 Map of rainfall isohyets of the main Fiji islands and stream sampling locations within Macuata Province and Kubulau District (Bua
Province) of Vanua Levu. Forested lands on Vanua Levu are depicted in grey

August 2008 and the wet season of April 2009. We
sampled five catchment basins (Dreketi, Labasa,
Qawa, Tabia, Nataqaga) in Macuata Province and
two catchment basins (Kilaka, Suetabu) in Kubulau
District, covering a range of sizes and catchment
forest cover (Table 1). All Macuata basins have

introduced Oreochromis spp. populations, which are
known to be associated with reductions in native fish
species richness (Jenkins et al. 2010).
We systematically sampled fish communities within 50 m reaches of upper, mid and lower sections of

river basins in Kubulau and Macuata using the exact
methods of Jenkins et al. (2010), modified from field
protocols of Parham (2005) and Fitzsimons et al.
(2007). In brief, we used a variety of techniques to
collect fauna from the rivers/streams to ensure
comprehensive presence/absence assessment. These
techniques included: electrofishing using either a
Deka 3000 (600 V, 10A) or Smith-Root (500 V,
10A) backpack unit; netting with gill nets (1 in.
mesh), large seine nets (0.4 cm2 mesh), medium pole
seine nets (1 mm2 mesh) and small hand nets (1 mm2


264
Table 1 Key catchment
characteristics within the
sampled areas across the two
study regions of Macuata
and Kubulau, including
catchment size (ha), forest
cover (%), presence/absence
of invasive Oreochromis
spp., and number of sites
surveyed in dry (D) and
wet (W) season

Environ Biol Fish (2011) 91:261–274
Catchment

Region

Area (ha)

% Forest cover

Invasive fishes (Y/N)

No. sites surveyed

Dreketi

Macuata

85,053

57

Y

5D, 6 W

Labasa

Macuata

20,728

61

Y

2D, 2 W

Qawa

Macuata

15,205

54

Y

2D, 2 W

Tabia

Macuata

7,651

47

Y

2D, 2 W

Nataqaga

Macuata

307

29

Y

1D, 1 W

Kilaka

Kubulau

2,474

80

N

6D, 6 W

Suetabu

Kubulau

4,138

72

N

6D, 6 W

mesh); and observations by mask and snorkel. At
each site, 4–6 surveyors made collections from
downstream to upstream for 1 h total.
Lower reach sites, including estuaries, occurred
between the river mouth to the first major obstacle
(e.g. waterfall, culvert, weir). Mid reach sites
occurred between altitudes of 20 and 50 m with
well developed riffles, runs and pools. Typically,
we sampled two sections of mid reaches: one just
above the first major obstacle and a second site
100–200 m upstream. Upper reach sites were
generally characterized by steep gradient headwater
areas with waterfalls and plunge pools, at altitudes
between 45 and 210 m. We sampled two sections
of upper reaches: one just above the largest
headwater waterfall and one just below. We fixed
all specimens that could not be identified in the
field in 10% formalin solution and transferred them
to 70% ethanol solution after 1–2 weeks fixation
for accurate taxonomic verification. We then deposited all voucher specimens in the University of
South Pacific, Suva collections.
At each sampling site, we took a GPS position and

altitude using a Garmin GPS map 76Cx. We
measured water quality variables (temperature, pH,
conductivity, salinity and dissolved oxygen) with a
hand-held YSI multi-meter before entering the water
to minimize disturbance. We measured turbidity using
a turbidity tube calibrated to nepthalometric turbidity
units (NTUs) and flow rate (m/s) by floating a plastic
lid over a marked 10 m section and timing with a
stopwatch.
Statistical analyses
To investigate differences in ichthyofauna community
composition, we pooled species presence-absence
data by reach for each region and season and

calculated similarities using the Bray-Curtis similarity
measure (Bray and Curtis 1957). Results are displayed
using multidimensional scaling (MDS) plots, on which
percent similarity levels are assigned based on hierarchical cluster analysis (group-average linkage). We
used a one-way ANOSIM with 999 permutations
(Clarke 1993) to test the significance of the resulting
division by reach and the BIO-ENV procedure
within the BEST function of PRIMER version 6
software (Clarke and Gorley 2006) to evaluate
potential environmental correlates of community
structure. We performed the BIO-ENV test using a
resemblance matrix of normalized environmental
variables calculated using Euclidean distance
(Clarke and Ainsworth 1993) and tested the significance of the output ρs statistic using the permutation
method of Clarke et al. (2006), run over 999
permutations. Repeated runs of the BVSTEP procedure within BEST were used to identify the most

common subset of fish species with the highest
correlation (ρs ≥0.95) to the Bray-Curtis similarity
matrix for the full suite of species.
To assess specific differences related to season
across regions, we calculated the Shannon-Weaver
diversity index (H’) based on species richness and
abundance data from each sampling location using
PRIMER version 6 software. We then performed a
two-way analysis of variance (ANOVA) in Statistica
version 8.0 software on total fish abundance and
Shannon-Weaver diversity with region and season as
predictor variables. We transformed (ln(x + 1)) fish
abundance data to meet assumptions of normality and
homogeneity of variance. Within each region, we also
performed two-way ANOVA on transformed fish
abundance data with reach and season as predictor
variables. We used nonparametric Mann-Whitney U
tests to evaluate differences in water quality parameters across region and season.


Environ Biol Fish (2011) 91:261–274

265

Results
We collected or observed 1616 individual fishes from 32
families, 19 genera to 87 species over both seasons and
regions (Appendix 1). This amounts to approximately
half of the species of freshwater and estuarine fishes
recorded from Fijian rivers (Jenkins et al. 2010).

Position in reach was a more dominant driver of
fish community composition than region or season:
lower reach sites were significantly distinct from mid
to upper sites in Kubulau and Macuata (ANOSIM
global R = 0.62, p<0.01; Fig. 2a, Table 2). Lower
reach sites in both seasons were characterized by
frequent presence of Zenocharpus dispar, Leiognathus equulus and L. splendens, plus Cristagobius
aurimaculatus, Oxyurichthys opthalmonema, and
Apogon amboinensis found in Kubulau during the
wet season only and in Macuata during the dry season
only (Fig. 2c; Appendix 1). We frequently collected
the following fish species from mid to upper sites:
Anguilla marmorata; Eleotris fusca; Sicyopterus
lagocephalus; Kuhlia rupestris; and Hypseleotris
guentheri, from the Qawa (Macuata) in the dry season
to Suetabu (Kubulau) from both seasons (Fig. 2c).
The upper Macuata sites during the wet season were
the most distinct from all other locations and were
generally quite depauperate, though included: the eels
A. marmorata and A. megastoma; the introduced
tilapia Oreochromis mossambicus; the gudgeon
Bunaka gyrinoides; the goby Awaous guamensis;
and two Fiji endemics, Glossogobius sp. (spot fin)
and Redogobius lekutu, found in the Dreketi River
only (Appendix 1).
Temperature, turbidity and river width were selected as environmental variables with the best match to
explain community structure composition and were
significantly correlated (ρs =0.569, p<0.01) to the fish
community presence-absence matrix. The MDS plot
of temperature, turbidity and river width data show

similar breaks between lower reach versus mid and
upper reach sites (Fig. 2b), with higher temperatures,
greater turbidity and wider river beds in lower reach
sites (Table 3).
Overall, we observed 12% more species during the
wet season (68 vs. 58). However, ANOVA tests
showed significant interaction terms between region
and season, whereby we observed higher species
abundance and diversity in the wet season in Kubulau
District versus the opposite pattern in the dry season

Fig. 2 Two-dimensional MDS plots of (a) freshwater fish
presence/absence pooled by reach and season and (b) mean
environmental variables (temperature, turbidity, width) which
explained the most variance in fish communities. (c) freshwater
fish presence/absence pooled by reach and season overlaid with
vectors for the subset of fish species with the consistently highest
correlation (ρs =0.952) with the full resemblance matrix. Three
letter codes indicate: (first letter) L/M/U: lower/mid/upper;
(second letter) M/K: Macuata/Kubulau; (third letter) W/D: wet/
dry season)

in Macuata Province (Fig. 3a and b, Table 4).
Amphidromous species accounted for a considerable
proportion of the increase in species richness in the
wet season in Kubulau across all reaches, but this was
not observed in Macuata (Fig. 4). In Macuata, there


266

Environ Biol Fish (2011) 91:261–274

Table 2 One-way ANOSIM results of pairwise differences in
fish presence-absence data by reach. Bold values are significant
at p≤0.05
Lower

Mid

similarly low (4.92 mg/L wet vs. 5.03 mg/L dry),
though none of the seasonal differences in Macuata
were significant (Fig. 6).
Over half (55%) of species were observed in only
one season: we collected 19 (21%) species only in the
dry, and 29 (33%) only in the wet (Appendix 1). Of
the exclusively dry season species, 68% were only
seen in the lower and mid reaches of the Dreketi
River system, while 70% of the exclusively wet
season species are found in Kubulau. Only 5 species
were found in both districts in the wet season,
including: Butis amboinensis; Caragobius urolepsis;
Pandaka sp.; Periopthlamus argentilineatus; and
Siganus vermiculatus.

Upper

–

Lower

Mid

1.000

–

Upper

0.969

0.089

–

were significant differences in abundance by reach and
season (Fig. 5a, Table 5), with significantly lower fish
abundance in the upper reach during the wet season
than abundances during the mid-dry, lower-dry and
lower-wet sampling. In Kubulau, there were significant
differences in fish abundances by reach only (Fig. 5b,
Table 5), with highest abundance in the mid reaches
during the wet season which was significantly greater
than upper reaches during the dry season.
The opposing patterns in diversity and abundance are mirrored by notable differences in some
water quality parameters across seasons. Mean dry
season stream temperature in Kubulau was lower
(25.8°C wet vs. 26.8°C dry), while there were
significantly higher wet season values for flow (0.92 m/s
wet vs. 0.36 m/s dry, p<0.001), pH (6.95 wet vs. 6.75
dry, p<0.05) and dissolved oxygen (7.88 mg/L wet vs.

6.62 mg/L dry, p<0.001). Macuata wet season temperature was higher (26.5°C wet vs. 25.6°C dry), pH was
lower (7.27 wet vs. 7.67 dry) and dissolved oxygen was

Discussion
Position in reach was the strongest factor influencing
freshwater fish diversity and abundance in western
Vanua Levu catchments, particularly in the larger and
steeper systems of Macuata. Species attenuation with
altitude has been well-documented in a number of
systems globally (Pusey et al. 1995; Jenkins 1997;
Russell et al. 2003) and is particularly notable in
small islands where the geographic distance between
headwaters and terminal reaches is comparatively
short. This pattern is distinct from large, geologically
stable systems which can have highly diversified and
numerically abundant resident upper catchment fauna

Table 3 Mean water quality variables by region, reach and season
Site

Flow (m/s)

Altitude (m)

Temp (°C)

pH

DO (mg/L)

Conductivity (μS)

Turbidity (NTU)

Width (m)

0

28.33

6.90

6.49

262.6

13.0

11.3
28.9

Kubulau
Lower Dry

0.3

Lower Wet

0.6

0

27.05

6.97

8.59

285.5

17.5

Mid Dry

0.5

30

26.50

6.80

6.40

226.4

10.0

3.0

Mid Wet

1.0

40

25.73

6.85

7.32

69.4

9.9

9.2

Upper Dry

0.4

90

25.98

6.60

6.94

196.9

0.0

2.0

Upper Wet

1.1

133

24.53

7.03

7.73

96.0

5.0

6.3

Macuata
Lower Dry

0.0

0

27.00

7.20

5.30

36.6

10.0

110.0

Lower Wet

0.4

0

29.00

7.00

4.00

27.0

22.5

150.0

Mid Dry

0.5

30

25.82

7.46

4.26

200.5

5.0

11.7

Mid Wet

0.8

30

26.42

7.32

4.60

101.4

7.0

28.3

Upper Dry

0.3

83

25.20

8.08

5.93

165.9

6.0

11.4

Upper Wet

0.8

83

25.68

7.32

5.50

85.2

11.7

13.4


Environ Biol Fish (2011) 91:261–274

267
Table 4 Two-way ANOVA results of the effects of region
and season on (a) transformed total fish abundance, and
(b) Shannon-Weaver diversity. Bold values are significant
at p ≤ 0.05
Factor

SS

df

MS

F

p

Region

0.0187

1

0.0187

0.0197 0.8890

Season

(a) Total abundance
0.6083

1

0.6083

0.6424 0.4273

Region x Season 8.9213

1

8.9213

9.4214 0.0037

Error

43 0.9469

40.7175

(b) Shannon-Weaver diversity
Region

1.89531

Season

0.01658

1

0.01658 0.0429 0.8368

Region x Season 2.06103

1

2.06103 5.3372 0.0257

Error

Fig. 3 Differences by region and season for: a transformed fish

abundance; and b Shannon-Weaver diversity (H’) index. Error
bars represent ± 95% confidence interval

(Lowe-McConnell 1987) and lower proportions of
migratory fishes crossing multiple habitat types
(Jenkins et al. 2010). In addition, east of Weber’s
line, there is a distinct lack of primary freshwater
fishes except for those found on continental land
masses where considerable speciation within freshwater has occurred (Baranescu 1990).
Species attenuation was not pronounced, however,
in Kubulau catchments where there was no significant
difference in Shannon-Weaver diversity among reaches when sites were pooled across the district. Because
the slope of the Suetabu river is low and there are no
major barriers to dispersal, species typically found in
Western Pacific island mid-lower reaches and estuaries,
such as Butis butis, Eleotris melanosoma, Giurus
hoedti, Kuhlia marginata, Kuhlia munda, Kuhlia

1

1.89531 4.9081 0.0321

16.60490 43 0.38616

rupestris, and Ophiocara porocephala, were present
in headwater communities. We found none of these
species in either season in the headwaters of the Kilaka
river, which has a higher number of waterfalls, greater
slope and higher elevation. In steep river basins with
obstacles to upstream movement, only species with

morphological adaptations for swimming against current (e.g. anguilliform shape) and climbing (e.g.
modified pelvic fin) will be able to reach most
headwater sites (Ryan 1991; Jenkins 1997; Eikaas
and McIntosh 2006).
Although season was not a significant driver of
fish community structure at the river basin level due
to the opposing effects of the wet season on
abundance and diversity across regions (Fig. 3), we

Fig. 4 Seasonal differences in numbers of amphidromous
species in Kubulau and Macuata


268

Environ Biol Fish (2011) 91:261–274
Table 5 Two-way ANOVA of transformed fish abundance by
reach and season for (a) Macuata and (b) Kubulau. Bold values
are significant at p≤0.05
Factor

SS

df

MS

F

p

Reach

12.8351

2

6.4176

9.0274

0.0018

Season

5.4437

1

5.4437

7.6575

0.0123

Reach x Season

0.2403

2

0.1201

0.1690

0.8458

Error

13.5070

19

0.7109

Reach

5.4483

2

2.7241

5.1398

0.0189

Season

2.3680

1

2.3680

4.4679

0.0506

Reach x Season

0.0709

2

0.0354

0.0669

0.9356

Error

8.4802

16

0.5300

(a) Macuata

(b) Kubulau

Fig. 5 Differences in abundance by reach and season for (a)
Macuata; (b) Kubulau. Error bars represent ± 95% confidence
interval

observed high numbers of fish species that were only
seen in one season. The reasons for the high degree of
seasonal exclusivity are likely a combination of
instantaneous variation in fish present during sampling (Bonar and Hubert 2002; McClanahan et al.
2007) and species’ preferences for particular seasonally available habitats and water characteristics. For
example, many of those species only seen during the
dry season spend significant portions of their adult
lives in marine and estuarine environments and are
potentially capitalizing on the longer upward penetration of saline water during this season for feeding,
breeding or to escape predation (Rasalato et al. 2010;
McBride et al. 2010). Key species among this group

are estuarine and marine migrants such as the: bull shark
(Carcharhinus leucus); snappers Lutjanus johnii and L.
monostigma; tarpon (Megalops cyprinoides); spaghetti
eel (Moringua macrocephala); wolf herring (Chirocentrus dorab); and Hardenburg’s anchovy (Stolephorus
insularis). In addition, as the flow rate is much
reduced during the dry season (Fig. 6a), species with
poor swimming ability are more likely to be present
in mid-water and more likely to be sampled than
during high flow conditions of the wet season
(Silvano et al. 2000). Some of these species include:
the humpback cardinal (Apogon lateralis); the milkspotted puffer (Chelonodon patoca); and the silver

moony (Monodactylus argenteus).
Wet season exclusives included fishes that prefer
fresh muddy substrate as habitat, such as the:
mudskippers Periopthalmus argentilineatus and P.
kalolo; scaleless wormgoby (Caragobius urolepis);
longfin snake eel (Pisodonophis cancrivorus); and
unicolor snake moray (Uropterygius concolor).
Meanwhile, certain schooling (Rastrelliger kanagurta, Mugil cephalus and Liza sp.) and larger
predatory species (Lujanus argentimaculatus and L.
fulvus) are likely taking advantage of the large
amounts of allotchthonous matter being washed into
the waterways as both a direct food source or as an
attractant for smaller prey items. Such increases in
migratory species numbers during wet seasons have
also been observed in upper Amazon communities in
response to food and habitat availability (e.g.
Galacatos et al. 2004). These pulsed migrations


Environ Biol Fish (2011) 91:261–274

269

Fig. 6 Mean seasonal differences in Kubulau and Macuata in (a) river flow (m/s); (b) water temperature (°C); (c) pH; and (d) dissolved
oxygen (mg/L). Error bars represent ± 95% confidence interval

provide important seasonal fisheries (McDowall
2007) and are likely major injections of biomass
and diversity into riverine food webs.
The significant difference across regions in wet

season effects on total fish abundance and diversity is
likely related to the strong differences in catchment
land cover between Macuata and Kubulau. Given that
mean catchment size in Macuata is nearly 8 times
greater than in Kubulau (25,789 vs. 3,306 ha),
species-area curves would theoretically predict higher
species richness and abundance in Macuata across
both seasons (Magurran 1988). However, in Kubulau,
mean species richness and abundance were greater in
the wet season, which was associated with lower
water temperatures and higher dissolved oxygen
concentrations. By contrast, species richness and
abundance were lower during the same season in
Macuata, which was associated with higher temperatures (Fig. 6). These results suggest that, in general,
the wet season is having a net positive effect on

habitable space for fishes in Kubulau District and a
net negative effect in Macuata Province, as species
may be lost due to runoff from degraded catchments.
Macuata catchments, on average, possess much less
natural forest cover (49.6 vs. 76.0%) and have much
greater density of roads (1.7 vs. 0.51 per km2) and river
crossings (1.4 vs. 0 per km2) that serve as entry points
for sediment to enter streams. They are additionally
heavily invaded by exotic species such as tilapia
(Oreochromis spp) and mosquitofish (Gambusia affinis) which are not present in Kubulau (Jenkins et al.
2010). Sensitive species, such as Stiphodon rutilaureus, Stiphodon sp. 1, Giurus hoedti, and Redigobius
bikolanus, which are notably all amphidromous species, were either absent from Macuata sites altogether
or were only present during the dry season, while
hardy species, such as Hypseleotris guentheri and

Sicyopterus lagocephalus, were present during both
seasons. The sensitive species may be affected by
large, seasonal sediment influx into rivers, which can


270

cover benthic food sources and affect visual predators
by increasing turbidity. Further, if these degraded water
quality conditions are sensed by post-larvae prior to
upstream migration, they may prevent recolonization
(Jenkins et al. 2010). In addition, species with small
surface area to volume ratio may be disproportionately
affected by decreasing dissolved oxygen and increasing temperatures. Only very tolerant species can
survive when dissolved oxygen concentrations approach 4 mg L−1 (Itazawa 1971), such as the Pacific
tarpon Megalops cyprinoides (found in Macuata only),
which has adapted to hypoxic conditions by facultative
air breathing (Clark and Seymour 2007).
Comparisons of catch per unit effort (fish biomass
kg hr−1) between Macuata rivers and near pristine
rivers of Tetepare, Solomon Islands using identical
sampling methods suggest that the Fiji rivers are
already severely ecologically compromised. Tetepare
rivers yielded on average 5.2 kg hr−1 (Jenkins and
Boseto 2007) compared with 0.2 kg hr−1 from
Macuata (Jenkins and Mailautoka 2009). The highest
biomass caught in any one site for Vanua Levu was
5.4 kg hr−1 in the lower Dreketi River versus 22.7 kg
hr−1 in the much smaller lower Raro River in
Solomon Islands (Jenkins and Boseto 2007). River

restoration through planting riparian vegetation and
freshwater protected areas may be able to restore
some of the lost functionality in these systems
(Humphries and Winemiller 2009). Jenkins et al.
(2010) documented how community-based management actions can also preserve species richness and
abundance, but local bans on harvesting must be
maintained in order for management actions to remain
effective. For example, between 2006 and 2008, the
communities within Nataqaga catchment enforced a
ban on logging, fishing and waste disposal within the
vicinity of the stream, but harvested the streams with
traditional fish poison prior to the 2009 survey. As a
consequence, species abundance dropped from 78 to
12 fish collected and richness fell from 9 to 5 species,

Environ Biol Fish (2011) 91:261–274

with Bunaka gyroides, Stiphodon sp., Redigobius sp.
and two species of Awaous absent from the community during the 2009 wet season (Jenkins et al. 2006,
2010).

Conclusion
The loss of fish species during the wet season in the
more cleared and cultivated catchments of Macuata
indicate the need for enhanced land management,
particularly along river margins. As many freshwater
fishes in Fiji move across multiple habitats during
their life cycles, the management unit for these fish
should be the entire river basin, including the adjacent
estuarine and marine ecosystems (Jenkins et al. 2010).

Specific management actions, such as permanent bans
on harvesting sensitive species, are also warranted to
protect distinctive fish communities within each
reach. The strong break between lower reach and
mid to upper reach fish communities in Fiji emphasizes the need to sample all reaches at a minimum
when conducting diversity surveys of tropical high
islands. In addition, given the high number of
seasonally exclusive species that contribute to the
higher overall diversity within Vanua Levu river
basins, sampling should be conducted across both
wet and dry seasons in order to completely understand species composition.
Acknowledgements Funding for this project was provided
through grants from the David and Lucile Packard Foundation
(2007–31847) and the Gordon and Betty Moore Foundation
(540.01). The authors gratefully acknowledge the chiefs and
government liaison officers in Kubulau and Macuata, as well as
A. Sesewa and A. Senikau of Fiji Department of Fisheries
Northern Division for logistical assistance. Field data collections were aided by K. Mailautoka, A. Raikabula, W. Naisilisili,
D. Boseto, A. Senikau and K. Moses. D. Hoese, O. Gon, J.
McCoscker and P. Kailola provided taxonomic expertise for
fish identification. The authors thank M. Sheaves for helpful
comments on the manuscript.


Environ Biol Fish (2011) 91:261–274

271

Appendix 1

Table 6 Seasonal presence-absence of ichthyofauna by river
reach across Macuata and Kubulau regions. Species are listed
alphabetically. Life history classifications, after Elliott et al.
(2007), include: freshwater resident (FR); freshwater straggler
(FS); estuarine migrant (EM); marine migrant (MM); marine
straggler (MW); amphidromy (A); obligate catadromy (COB);
and facultative catadromy (FC). Feeding guild classes are:
detritivore specialist (DS); detritivore generalist (DG); planktiSpecies

Family

Life
history

vore generalist (PlG); herbivore specialist (HS); herbivore
generalist (HG); invertivore specialist (IS); invertivore generalist (IG); insectivore specialist (InS); insectivore generalist
(InG); piscivore specialist (PS); piscivore generalist (PG);
carnivore (C); and generalist (G). Status categories are:
indigenous (IND); endemic (END); and introduced (INT).
Seasonal fish presence is indicated in wet (W) and dry (D)
seasons
Feeding
guild

Status

Ambassis miops Gunther 1872

Ambassidae

FS

G

IND

Anguilla marmorata Quoy &
Gaimard 1824
Anguilla megastoma Kaup 1856

Anguillidae

FC

C

IND

Anguillidae

FC

C

IND

Apogon amboinensis Bleeker 1853

Apogonidae

EM

PG

IND

Apogon lateralis Valenciennes 1832

Apogonidae

EM

PG

IND

Awaous guamensis Valenciennes,
in Cuvier & Valenciennes, 1837
Awaous ocellaris (Broussonet 1782)

Gobiidae

A

G

IND

Gobiidae

A

G

IND

(Bennett 1832)

Gobiidae

MM

C

IND

Bunaka gyrinoides (Bleeker 1853)

Eleotridae

A

C

IND

Butis amboinesis Bleeker 1983

Eleotridae

A

IG

IND

Kubulau

Macuata

Lower

Mid

W, D

W, D

Upper

Lower
W, D

W, D

Mid

Upper

W, D

W, D

W, D
W

W

D
D

W

D

W, D

W

D

D

D

W

D

Bathygobius coalitus
W

W
W

Butis butis (Hamilton 1822)

Eleotridae

A

IG

IND

W

Caragbius urolepis (Bleeker 1852)

Gobiidae

EM

IS

IND

W

W
W

W

W, D
W

Carangoides chrysophrys
(Cuvier 1833)

Carangidae

MM

C

IND

W, D

Caranx papuensis Alleyne &
Macleay 1877
Caranx sexfasciatus Quoy &
Gaimard 1825
Carcharhinus leucas (Müller &
Henle 1839)
Chelonodon patoca

Carangidae

MM

PS

IND

W

Carangidae

MM

C

IND

D

Carcharinidae

MM

C

IND

D

Diodontidae

EM

G

IND

(Hamilton 1822)

W

D

Chilomycteius reticulatus
(Linnaeus 1758)

Diodontidae

MM

IS

IND

Chirocentrus dorab (Forsskål 1775)

Chirocentridae

EM

C

IND

Christagobius aurimaculatus
Akihito & Meguro 2000
Ctenogobiops aurocingulus (Herre 1935)

Gobiidae

EM

IS

IND

W

Gobiidae

EM

IS

IND

W

Drombus halei Whitley 1935

Gobiidae

A

IS

IND

Eleotris fusca (Forster, in Bloch
and Schneider 1801)
Eleotris melanosoma Bleeker 1852

Eleotridae

A

C

IND

Eleotridae

A

C

IND

Foa fo Jordan & Seale 1905

Apogonidae

EM

C

IND

Gambusia affinis (Baird & Girard 1853)

Poecilliidae

FS

IG

INT

Gazza minuta (Bloch 1795)

Leiognathidae

EM

C

IND

Gerres sp.

Gerriedae

Giurus hoedti (Bleeker 1854)

Eleotridae

A

IG

IND

Glossogobius bicirrhosus (Weber 1894)

Gobiidae

A

IS

IND

W, D
D
D

D
W, D

W, D

W, D

W

W, D

W

W
W, D
W
D
W

W
W


272

Environ Biol Fish (2011) 91:261–274

Table 6 (continued)
Species

Family

Life
history

Feeding
guild

Status

Kubulau
Lower

Macuata
Mid

W

Upper

Lower

Mid

Upper

W, D

D

W, D

D

D

Glossogobius sp. 1

Gobiidae

A

IS

END

Glossogobius sp. 2

Gobiidae

A

IS

END

Gymnothorax polyuranodon
(Bleeker 1853)
Hippicthys albomaculosus Jenkins
and Mailautoka 2009
Hyporhamphus dussumieri
(Valenciennes 1847)
Hypseleotris guentheri
(Bleeker 1875)
Kuhlia marginata (Cuvier, in Cuvier
and Valenciennes 1829)
Kuhlia munda (de Vis 1884)

Muraenidae

COB

PG

IND

Sygnathidae

EM

IS

END

Belonidae

MM

InG

IND

Eleotridae

FS

InG

IND

W, D

W, D

W, D

Kuhliidae

COB

IG

IND

W

D

W, D

W, D

W, D

D
W

W

Kuhliidae

COB

IS

IND

W, D

Kuhlia rupestris (Lacepède 1803)

Kuhliidae

COB

IS

IND

W

Lamnostoma kampeni (Weber &
de Beaufort 1916)
Leiognathus equulus (Forsskål 1775)

Ophichthidae

EM

IS

IND

W, D

Leiognathidae

EM

C

IND

W, D

W, D

Leiognathus splendens (Cuvier 1929)

Leiognathidae

EM

C

IND

W, D

W, D

Liza macrolepsis (Smith, 1846)

Mugilidae

FC

PlG

IND

Liza melanoptera (Valenciennes,
in Cuvier & Valenciennes 1836)
Liza sp.

Mugilidae

FC

PlG

IND

W

D

Mugilidae

FC

PlG

IND

Liza subviridis (Valenciennces,
in Cuvier & Valenciennes 1836)
Lutjanus argentimaculatus
(Forsskål 1775)
Lutjanus fulvus (Forster, in Bloch
and Schneider 1801)
Lutjanus johnii (Bloch 1792)

Mugilidae

FC

PlG

IND

W

Lutjanidae

FC

PG

IND

W

Lutjanidae

FC

C

IND

W

Lutjanidae

FC

PG

IND

D

W, D

D

W, D

D

W
D

D

Lutjanus monostigma
(Cuvier 1829)

Lutjanidae

MM

C

IND

Lutjanus russelli (Bleeker 1849)

Lutjanidae

FC

C

IND

D

Megalops cyprinoides (Broussonet 1782)

Megalopidae

FC

PG

IND

Microphis bracyurus (Bleeker 1853)

Sygnathidae

FS

IS

IND

Microphis leiaspis (Bleeker 1853)

Sygnathidae

FS

IS

IND

Microphis retzii (Bleeker 1856)

Sygnathidae

FS

IS

IND

Monodactylus argenteus
(Linnaeus 1758)
Moringua macrocephalus
(Bleeker 1863)
Mugil cephalus Linnaeus 1758

Monodactylidae

EM

DG

IND

Moringuidae

MS

PS

IND

Mugilidae

FC

PlG

IND

Mugilogobius notospilus (Günther, 1877)

Gobiidae

A

G

IND

Ophiacara porocephala (Valenciennes,
in Cuvier & Valencienne 1837)
Oreochromis mossambicus
(Peters 1852)
Oxyuricthys opthalmonema
(Bleeker 1856–57)
Pandaka sp.

Eleotridae

A

DS

IND

Cichlidae

FS

G

INT

Gobiidae

EM

G

IND

W

D

Gobiidae

EM

PG

IND

W

W

Periopthalmus argentilineatus
Valenciennes, in Cuvier &
Valenciennes 1837
Periopthalmus kalolo Lesson 1831

Gobiidae

EM

IS

IND

W

W

Gobiidae

EM

IS

IND

W

Pisodonophis cancrivorus
(Richardson 1848)

Opichthidae

EM

PG

IND

W

W

D
D
W, D

W
D

W, D

W

W
D
D

W
W
W

W, D

W

W
W, D

W, D


Environ Biol Fish (2011) 91:261–274

273

Table 6 (continued)
Species

Family

Life
history

EM

Feeding
guild

IS

Status

IND

Kubulau

Macuata

Lower

Mid

W

D

Upper

Lower

Psammogobius biocellatus
(Valenciennes,
in Cuvier & Valenciennes 1837)
Rastelliger kanagurta (Cuvier 1816)

Gobiidae

Scombridae

MM

PlG

IND

W

Redigobius bikolanus (Herre 1927)

Gobiidae

A

G

IND

D

Redigobius leveri (Fowler 1943)

Gobiidae

FR

G

END

Redigobius roemeri (Weber 1911)

Gobiidae

FS

G

IND

Redigobius sp. 1 (lekutu)

Gobiidae

FR

G

END

Sicyopterus lagocephalus

(Commerson, in Lacepède 1800)
Sicyopus zosterophorum
(Bleeker 1956–57)
Siganus vermiculatus (Valenciennes, in
Cuvier & Valenciennes 1835)
Sphyraena obtusata (Cuvier,
in Cuvier & Valenciennes 1829)
Stenogobius sp.

Gobiidae

A

HS

IND

Gobiidae

A

IS

IND

Siganidae

EM

HS

IND

W

Sphyraenidae

EM

C

IND

W

Gobiidae

A

PG

END

Stiphodon rutilareus Watson 1996

Gobiidae

A

HG

IND

Stiphodon sp. (lailai)

Gobiidae

A

HG

END

Stolephorus insularis Hardenberg 1933

Engraulidae

MM

PlG

IND

Terapon jarbua (Forsskål 1775)

Tetrapontidae

FC

G

IND

W

W

W, D

W
D

W, D

D

W, D

D

D
D

W, D
W

W, D

W

W

W, D

D

D
D

Engraulidae

MM

DG

IND

W

Upeneus vittatus (Forsskål 1775)

Mullidae

MM

IS

IND

D

Uroconger sp.

Congridae

EM

IS

IND

Uropterygius concolor Rüppell 1838

Muraenidae

EM

PG

IND

W

Yongeichthys nebulosus (Forsskål 1775)

Gobiidae

EM

G

IND

W, D

W

W, D

Zenocharpus dispar (Valenciennes
in Cuvier and Valenciennes 1847)

Hemirhamphidae

FM

InS

IND

W, D

W

W, D

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Environ Biol Fish (2011) 91:275–286
DOI 10.1007/s10641-011-9777-3

Pelagic larval duration and population connectivity
in New Zealand triplefin fishes (Tripterygiidae)

Yair Y. Kohn & Kendall D. Clements

Received: 4 July 2010 / Accepted: 1 December 2010 / Published online: 5 March 2011
# Springer Science+Business Media B.V. 2011

Abstract The relationship between pelagic larval
duration (PLD) and population connectivity in marine
fishes has been controversial, but most studies to date
have focused on tropical taxa. Here, we examine PLD
in 11 species of triplefin fishes from a temperate
environment in the Hauraki Gulf, New Zealand, to
describe daily increment patterns and settlement
marks in the otoliths. The formation of daily increments was validated using larvae of known age and
tetracycline marking of settled juveniles. Settlement
mark identity was verified by comparing total
increment counts from otoliths of recently settled
fishes with PLD counts from post-settlement fishes. A
similar pattern of three groups of increments across
the otolith was found in all specimens examined. The
settlement mark was similar in all species and
occurred as a sharp drop in increment width within
the area of transition in optical density. PLD was
lengthy, compared to species of triplefins from

Y. Y. Kohn (*) : K. D. Clements
School of Biological Sciences, University of Auckland,
Private Bag,
92019 Auckland, New Zealand
e-mail:
Present Address:

Y. Y. Kohn
Zoology Department, The University of Otago,
340 Great King St.,
9016 Otago, New Zealand

elsewhere, and ranged between 54.4±1.7 SE days in
Bellapiscis lesleyae to 86.4±2.6 SE days in Forsterygion malcolmi. Variation in PLD within species was
high but did not mask interspecific differences. PLD
was not phylogenetically constrained, as sister species
differed significantly in PLD. PLD was compared
with genetic population connectivity for eight of the
study species using mitochondrial gene flow data
from Hickey, Lavery, Hannan, Baker, Clements. Mol
Ecol 18:680–696 (2009). The observed lack of
correlation between PLD and gene flow suggests that
dispersal is limited by other factors, such as larval
behaviour and the availability of settlement habitat.
Keywords Pelagic larval duration . Population
connectivity . Otolith microstructure . Triplefin fishes

Introduction
The relationship between pelagic larval duration
(PLD) and population connectivity in marine fishes
has been controversial (Macpherson and Raventos
2006). PLD was, until recently, considered a “black
box” and there was little understanding of the
processes that influence larval dispersal and settlement (Cowen and Sponaugle 2009). Traditionally,
larvae were thought of as passive particles that drifted
with the currents like plankton (Fuiman 2002). Recent
work on reef fishes has shown that both physical

processes and biological traits affect dispersal, and