Biological Conservation 144 (2011) 339–349
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Biological Conservation
journal homepage: www.elsevier.com/locate/biocon
The role of life-history and location of barriers to migration in the spatial
distribution and conservation of fish assemblages in a coastal river system
Robert J. Rolls ⇑
Australian Rivers Institute, Griffith University, Nathan 4111, Queensland, Australia
a r t i c l e
i n f o
Article history:
Received 9 December 2009
Received in revised form 17 August 2010
Accepted 8 September 2010
Available online 8 October 2010
Keywords:
Fish migration
Diadromy
Connectivity
a b s t r a c t
Water resource development in coastal river catchments contributes to poor fish assemblage health due
to the effects of barriers to migration and altered flow regimes. Impacts of migration barriers on fish
assemblages depend primarily on the location of each barrier within the river network and migration
needs of regional fish fauna. This study examined how temporal and spatial patterns in the distribution
and composition of fish assemblages was associated with varying estuarine connectivity and migration
barriers in higher altitude reaches in the eastern Hunter River catchment, temperate Australia. Species
richness and abundances of diadromous species were expected to be greater in a tributary catchment
with unrestricted connectivity to the Hunter River estuary when compared to a neighbouring tributary
catchment with restricted connectivity. Six diadromous species were sampled only, or in greater abundances, in the unrestricted tributary when compared to the restricted tributary. As a consequence, assemblage composition in the restricted tributary was dominated by non-diadromous species. Greater
abundances of the amphidromous Cox’s gudgeon (Gobiomorphus coxii) were sampled in the unrestricted
tributary following their estuarine-freshwater upstream juvenile migration period when compared to the
restricted tributary. Differences in the accumulations of migratory species immediately downstream of
upland barriers between the two levels of estuary connectivity indicate that migration barriers in
lowland reaches have significant effects throughout the entire catchment. Results of this study indicate
that the location of each barrier to migration within river networks has varying consequences for catchment-scale connectivity loss and assessing the impacts of multiple barriers. Determining the effects and
most appropriate management of migration barriers requires that all obstructions within a river network
are recognised, as multiple barriers can have cumulative and interacting consequences for freshwater fish
fauna, especially diadromous species.
Ó 2010 Elsevier Ltd. All rights reserved.
1. Introduction
Freshwater fish assemblages in coastal river catchments consist
of species with diverse life-history strategies and migration
requirements. Diadromy, the regular migration between freshwater and marine environments at particular stages of the life cycle
(McDowall, 1997), is a common trait in many temperate freshwater fish species, for example eels (Anguillidae) and many species of
Galaxiidae, Eleotridae and Salmonidae (Gillanders, 2005). Not all
coastal freshwater fish exhibit diadromous migrations. For example, Australian smelt (Retropinna sp. complex) and spotted galaxias
(Galaxias truttaceaus) are two Australian fish species that have
been found to undergo flexible (i.e. facultative) diadromous migrations or are capable of completing their life cycle completely in
freshwater (Humphries, 1989; Crook et al., 2008). This diversity
of life-history strategies contributes to spatially variable and
⇑ Tel.: +61 7 3735 3819; fax: +61 7 3735 7615.
E-mail address: r.rolls@griffith.edu.au
0006-3207/$ - see front matter Ó 2010 Elsevier Ltd. All rights reserved.
doi:10.1016/j.biocon.2010.09.011
diverse river fish assemblages in coastal catchments, for example
New Zealand (Jowett and Richardson, 2003) and south-eastern
Australia (Gehrke and Harris, 2000).
Migration barriers, stream gradient and elevation control the
spatial distribution of fish in river catchments (Jackson et al.,
2001; Joy and Death, 2001). Almost all river catchments have natural in-stream barriers (e.g. waterfalls), often in headwater
reaches, and these barriers limit upstream dispersal for migratory
fish. Dams, weirs and road crossings also restrict migration within
catchments, and the specific location of these unnatural barriers
can have variable effects on the spatial and temporal patterns in
fish assemblages. In the upper Mississippi River, USA, fish assemblages had apparent differences only immediately upstream and
downstream of low-head dams (Chick et al., 2006). However, fish
assemblages in coastal river catchments show greater effects of
dams and weirs at the reach and catchment scale (e.g. Joy and
Death, 2001; Gehrke et al., 2002). The prevalence of diadromous
life-histories contributes to significant discontinuities exhibited
in coastal fish assemblages due to anthropogenic migration
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R.J. Rolls / Biological Conservation 144 (2011) 339–349
barriers, however most evidence focuses on relatively small scales
within river catchments (Han et al., 2008).
Research into the spatial scale of the impacts of barriers within
river catchments can be used to make recommendations for connectivity restoration at existing barriers and also the most appropriate locations (i.e. least effect) to construct new migration
barriers, e.g. dams. In some cases, the construction of new dams
places unacceptable risk to the persistence of fish species, such
as the Australian lungfish (Neoceratodus forsteri) in south-east
Queensland, Australia (Arthington, 2009). Dams at low elevation
have the potential for more serious impacts to fish assemblages
than if they are located at higher altitudes (Joy and Death, 2001).
Anthropogenic effects on freshwater fish assemblages predominantly occur at the reach-catchment scale, and therefore ecological
research needs to focus on the management of impacts at these
large scales (Fausch et al., 2002; Durance et al., 2006).
Most diadromous freshwater fish species exhibit a seasonal peak
(or peaks) in migration, often associated with adults migrating to
spawn or larvae or juveniles migrating back to freshwater reaches.
Interestingly, few studies examining the impacts of barriers to migration on fish populations or assemblages assess seasonal patterns, i.e.
are differences in abundances or assemblage composition more
apparent during or after migration periods? In the Murrumbidgee
River, south-eastern Australia, average abundances of crimsonspotted rainbowfish (Melanotaenia fluviatilis), common carp (Cyprinus
cario) and goldfish (Carassius auratus) were significantly greater
upstream of a large weir in winter, with the opposite pattern in
summer (Baumgartner, 2004), indicating seasonal migration peaks
resulted in accumulations either up- or downstream. Seasonal changes
in species abundances due to migration or recruitment alter the ability to detect impacts of migration barriers (Gillette et al., 2005),
therefore limiting the ability for appropriate mitigation strategies
and post-restoration assessment to be made (Kibler et al., in press).
The Hunter River catchment, coastal south-eastern Australia,
supports a relatively diverse fish fauna consisting of species with
a range of diadromous (e.g. amphidromous, catadromous) or
non-diadromous (e.g. non-migratory, potamodromous) migration
requirements (Gehrke and Harris, 2000; Brooks et al., 2004; Rolls
et al., in press). Migration barriers have a growing significance
for fish fauna: at least 223 causeways, fords, culverts and bridges,
three large weirs and eight large dams have been constructed in
the Hunter River catchment (Chessman et al., 1997; NSW DPI,
2006a,b). Restoring connectivity within and between tributaries
of the Hunter River catchment is now relevant to compensate for
further losses of connectivity due to a proposed new large dam
on a large tributary, the Williams River. A study conducted during
2006–2007 testing the differences and responses of fish assemblages to flow regime manipulation (Rolls et al., in press) provided
field data to test how differences in freshwater-estuary connectivity between two tributaries of the lower Hunter River catchment
were associated with patterns in the composition of freshwater
fish assemblages. In this current study, it was predicted that restricted connectivity to the lower Hunter estuary would be associated with reduced fish species richness due to lower abundances or
absence of diadromous species when compared to the unrestricted
catchment. Secondly, as diadromous fish in south-eastern Australia
undergo seasonal migrations between freshwater, estuarine and
marine zones, it was also predicted that differences in population
size, and therefore assemblage composition, would be most obvious during or after migration periods. Thirdly, impacts of migration
barriers in reaches upstream of lowland barriers would be less
apparent if the fish fauna had a lower proportion of migratory species. These findings would help predict which species, or groups of
species, would be more susceptible to reduced connectivity and
therefore most likely to respond to future restoration.
2. Methods
2.1. Study region, location of migration barriers and sampling design
The Hunter River catchment is located in the central coast
region of New South Wales, Australia (Fig. 1). The Paterson and
Williams Rivers form two major tributaries of the Hunter River,
their confluences with the main channel of the lower Hunter River
are 15 km apart. Lostock Dam and Chichester Dam are situated in
the slopes region of the Paterson and Williams tributary sub-catchments (both 140 m AMSL), respectively. Seaham Weir is a fixedcrest weir (150 m wide, 2.5 m high, built in 1967) located in the
Williams River 14.9 km upstream of the confluence of the Hunter
and Williams Rivers. It is fitted with a submerged orifice fishway
(NSW DPI, 2006b), a design suited to fast-swimming salmonids
but ineffective for native Australian fish species (Stuart and
Mallen-Cooper, 1999). Seaham Weir, Lostock Dam and Chichester
Dam are currently the three most significant structures in the eastern Hunter River catchment.
Between August 2006 and June 2007, fish assemblages were
sampled at three sites in one regulated (flow regime regulated by
a large upstream dam) and one unregulated tributary of each of
the Paterson and Williams sub-catchments (Fig. 1). All sites were
located at altitudes between 40 and 232 m AMSL, therefore situated in the slopes zone (40–700 m AMSL, sensu Gehrke and Harris,
2000). In the Paterson catchment, sites were located on the regulated reach of the Paterson River reach downstream of Lostock
Dam and on the unregulated Allyn River, whereas in the Williams
catchment, sites were situated on the regulated reach of the Chichester River downstream of Chichester Dam and on the unregulated
Williams River. Lostock Dam is a 38-m high embankment dam
(impoundment volume 20 GL) with a concrete spillway and single
bottom-release outlet valve. Chichester Dam is a 43-m high concrete dam wall (impoundment volume 21 GL). Lostock Dam is used
to supply water for agricultural irrigation downstream via the river
channel, whereas Chichester Dam is used to divert water for
domestic consumption to the lower Hunter region around Newcastle (Fig. 1). Both dams release water to downstream reaches via
bottom-release outlet valves, although water does overflow due
to the small storage capacities combined with the consistent rainfall in the eastern Hunter region. Neither dam has facilities to assist
in maintaining connectivity with upstream reaches, thereby
restricting upstream fish dispersal between downstream and upstream reaches. Fish were sampled monthly between August
2006 and June 2007 at all sites using sweep-net electrofishing
(King and Crook, 2002) using a Smith-Root LR-24 backpack electrofisher operated at 400–500 V DC pulsed at 30 Hz and 12% duty
cycle. At each site and sample time, four composite replicate samples of 180-s power on time were collected from all available riffle,
run and pool habitats. Comparisons of the fish fauna between a previous study in 2000–2001 in the Williams River (Brooks et al., 2004)
(using a combination of boat and backpack electrofishing) and this
study (using backpack electrofishing) found that the proportion of
large bodied species (long-finned eels (Anguilla reinhardtii) and Australian bass (Macquaria novemaculeata) were lower, whereas the
proportion of Australian smelt (Retropinna semoni) was higher
when sampled using backpack electrofishing. Proportions of all
other species were similar between the two sampling techniques.
To date, no studies in this region have undertaken a complete
census of fish in a particular reach and then assessed the biases of
separate sampling techniques (e.g. boat versus backpack electrofishing versus passive techniques). However, such assessment is beyond the scope of this study. All fish sampled were identified,
counted and standard length recorded in the laboratory (most fish
were preserved for further gut contents and food web analysis).
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R.J. Rolls / Biological Conservation 144 (2011) 339–349
Fig. 1. Location of sampling sites (s) and significant in-stream barriers in the eastern Hunter River catchment, south-eastern Australia.
2.2. Data analysis
Data were analysed using a four-factor, mixed-model statistical
design testing for differences in fish population and assemblagelevel variables between tributaries (Fixed: Paterson versus
Williams), reaches (Fixed: regulated by upstream migration barrier
versus unregulated with no upstream migration barrier), sites
(Random: three sites) nested in each reach and, sample times (Fixed:
monthly samples between August 2006 and June 2007) (Table 1). In
this study design, two terms are of key interest to test how fish populations and assemblages are associated with migration barrier
locations. Firstly, a significant tributary effect indicates that there
are differences between the two tributary sub-catchments with restricted or unrestricted estuary connectivity. Secondly, a significant
tributary time interaction indicates that differences between tributary sub-catchments vary between sampling times. Variance components (VC) for each term relative to the total variation were also
calculated to indicate the magnitude of significant tests to assist
interpretation. Data were plotted to indicate patterns (i.e. differences) relative to the sub-catchment time interaction term.
Dependent variables for the statistical model included both univariate and multivariate metrics. Differences in the abundances of
each of four fish species with different migration characteristics
were tested as univariate measures. Long-finned eels (Anguilla reinhardtii) are catadromous (live in freshwater for most of their life,
migrate to sea for spawning) (Sloane, 1984) and Cox’s gudgeon
(Gobiomorphus coxii) are amphidromous (move between fresh
and salt water during life cycle, although not necessarily for
recruitment) (Miles et al., 2009). Australian smelt (R. semoni) are
primarily potamodromous (migrate within freshwater reaches,
although see Crook et al., 2008), whereas freshwater catfish (Tandanus tandanus) and flathead gudgeon (Philypnodon grandiceps) are
defined as non-migratory (Pusey et al., 2004). Species richness
(total number of species recorded in each sample) was also analysed to test if species richness was higher in the unrestricted tributary when compared with the restricted tributary. Rather than
using traditional Analysis of Variance, univariate data were analysed using Permutational Analysis of Variance (PERMANOVA,
Anderson, 2001) based on Euclidean distance. This test has the
advantage over traditional ANOVA as the null distribution of the
Table 1
Statistical design used to analyse fish population and assemblage data using Permutational Analysis of Variance.
Source of variation
Type
d.f.
Denominator for F test
Tributary (Tr) (Paterson versus Williams)
Reaches (Re) (upstream barrier versus no upstream barrier)
Sample time (Ti) (monthly samples August 2006–June 2007)
Site (Re) (three sites nested in each river reach)
Tri Re
Tr Ti
Re Ti
Tr site (Re)
site (Re) Ti
Tr Re Ti
Tr site (Re) Ti
Residual (four composite replicates at each site)
Fixed
Fixed
Fixed
Random
Fixed
Fixed
Fixed
Mixed
Mixed
Fixed
Mixed
Random
1
1
10
4
1
10
10
4
40
10
40
396
Tributary site (reach)
Site (reach)
Site (reach) time
Residual
Tributary site (reach)
Tributary site (reach) time
Site (reach) time
Residual
Residual
Tributary site (reach) time
Residual
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R.J. Rolls / Biological Conservation 144 (2011) 339–349
test statistic is determined using permutation, therefore not
requiring the often ecologically unrealistic assumption of normally
distributed data.
Patterns in assemblage composition were tested using the statistical model using multivariate PERMANOVA. Samples were compared using the modified Gower (with a log base 10) dissimilarity
measure (Anderson et al., 2006). The modified Gower measure
has the advantage over the Bray-Curtis measure as Bray-Curtis
lacks discrimination near its upper bound (where there are relatively few common species shared between samples) and exhibits
inconsistent behaviour for sparse data (see Anderson et al., 2006).
Similarities in assemblage composition data were ordinated using
Principal Coordinates Analysis (PCoA) and vectors of Spearmanrank correlations (r > 0.25) between Principal Coordinates and
species abundances were included, and similarities tested using
PERMANOVA run with 9999 restricted permutations. Results of
all statistical tests were determined to be significant at P 6 0.1 to
increase power and reduce type II errors, considered of greater risk
than type I errors in the context of this study. With power set at 90%
and a type 1 error rate of 0.1, median effect sizes for differences in
species richness and total fish abundance between the Paterson and
Williams catchments were 36% and 59%, respectively.
Mean (±95% confidence limits) catch-per-unit-effort (CPUE) of
Australian smelt and Cox’s gudgeon sampled at each site on each
sampling occasion were presented in bar graphs, separated for
each of the two tributaries of both Paterson and Williams catchments. These figures were presented to determine if upstream barriers were associated with restricting upstream connectivity
(indicated by any accumulations of individuals at sites nearest to
the dams), and if the effect of Seaham Weir altered any patterns
in the Williams catchment (when compared with the Paterson
catchment) by altering the abundance of diadromous Cox’s gudgeon within the catchment.
3. Results
3.1. Fish fauna and role of migratory requirements
Twelve fish species were sampled between August 2006 and
June 2007 (Table 2). All 12 species were recorded in the Paterson
tributary, whereas only nine species were sampled in the Williams
tributary. Seven species have diadromous life-histories, with five of
these species identified as catadromous. Six diadromous species
were either sampled only, or in greater abundances, in the Paterson tributary sub-catchment when compared to the Williams tributary sub-catchment. Australian bass (M. novemaculeata) were the
only exception to this pattern, with slightly higher total abundances sampled in the Williams sub-catchment (n = 6) when compared to the Paterson sub-catchment (n = 2). With the exception of
the locally rare Pacific blue-eye (Pseudomugil signifier), which was
sampled (n = 4) only in the Patterson tributary, all non-migratory
or potamodromous species were sampled in both Paterson and
Williams tributaries.
3.2. Spatial and temporal patterns in species abundance and
assemblage structure between catchments
Total fish species richness was significantly greater in the Paterson tributary versus the Williams tributary, specifically when
sampled in November 2006 and January, March and April 2007
(Table 3; Fig. 2). Abundances of long-finned eel were significantly
higher in the Paterson tributary and explained 5.2% of total variation, and this pattern was consistent across all sampling periods.
Amphidromous Cox’s gudgeon were sampled in higher abundances in the Paterson tributary, particularly from December
2006 to June 2007 (Fig. 2). Differences in abundances of Cox’s
gudgeon between the two tributaries accounted for the greatest
Table 2
Migration classifications, peak downstream (;) and upstream (") migration periods and percentage relative abundance of fish species sampled in the eastern
Hunter River catchment between 2006 and 2007.
Species name
Common name
Life-history
Peak migration period
Anguilla australis
Short-finned eel
Catadromous1
;Summer–Autumn
"Year-round4
0.1
<0.1
Anguilla reinhardtii
Long-finned eel
Catadromous1
;Summer–Autumn
"Spring–Summer
4.1
0.4
Gambusia holbrooki
Gambusia
Non-migratory1
7.0
0.7
Gobiomorphus australis
Striped gudgeon
Amphidromous2
;Autumn
"Spring
0.8
<0.1
Gobiomorphus coxii
Cox’s gudgeon
Amphidromous2
;Autumn
"Spring
44.9
8.0
Macquaria novemaculeata
Australian bass
Catadromous1,3
;Winter
"Spring–Summer
0.1
0.2
Myxus petardi
Freshwater mullet
Catadromous1
;Summer–Autumn6
"Autumn7
1.6
*(8)
Notesthes robusta
Bullrout
Catadromous2
;Autumn4
"Winter–Spring
Philypnodon grandiceps
Flathead gudgeon
Non-migratory2,4
0.1
Pacific blue-eye
Unknown4
0.2
Retropinna semoni
Australian smelt
Potamodromous1, although see
Freshwater catfish
5
1
Non-migratory
n
2
3
4
5
6
7
8
Williams
<0.1
Pseudomugil signifer
Tandanus tandanus
1
Paterson
4.0
36.5
85.2
4.5
2345
1.4
3915
Gehrke et al. (2002).
Miles et al. (2009).
Harris (1986).
Pusey et al. (2004).
Crook et al. (2008).
McDowall (1996).
Miles (2007).
Freshwater mullet were sampled in low abundances (two individuals from 177 samples) in the Williams River by Brooks et al. (2004).
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R.J. Rolls / Biological Conservation 144 (2011) 339–349
Table 3
Summary of mixed-model Analysis of Variance results on fish assemblage richness and population abundance of species with varying life-history patterns. Significant differences
(P 6 0.1) are indicated in bold.
Source
MS
Tr
Re
Ti
Site (Re)
Tr Re
Tr Ti
Re Tr
Tr site (Re)
Site (Re) Ti
Tr Re Ti
Tr Si(Re) Ti
Species richness
15.68
0.00
11.53
1.38
0.09
2.59
1.48
1.51
1.22
1.18
0.85
Residual
Tr
Re
Ti
Site (Re)
Tr Re
Tr Ti
Re Tr
Tr site (Re)
Site (Re) Ti
Tr Re Ti
Tr Si(Re) Ti
Residual
Tr
Re
Ti
Site (Re)
Tr Re
Tr Ti
Re Tr
Tr site (Re)
Site (Re) Ti
Tr Re Ti
Tr Si(Re) Ti
Residual
F
P
10.40
0.00
9.41
1.89
0.06
3.07
1.21
2.06
1.68
1.40
1.16
0.035
0.972
<0.001
0.117
0.819
0.006
0.318
0.085
0.009
0.214
0.244
0.73
Australian smelt
11658.0
5609.5
7530.5
2427.2
5635.7
4219.6
5873.2
2114.8
2363.1
5145.1
1903.7
MS
4.4
0.0
17.5
0.6
0.0
5.9
0.9
1.4
5.0
2.3
2.3
Long-finned eel
12.12
3.67
1.26
2.66
5.94
0.61
0.86
2.75
0.49
0.70
0.57
59.6
5.51
2.31
3.19
3.25
2.66
2.22
2.49
2.83
3.16
2.70
2.55
0.078
0.194
0.002
0.003
0.175
0.025
0.002
0.010
<0.001
0.008
<0.001
747.7
Flathead gudgeon
45.50
0.02
0.96
8.11
0.00
0.98
0.62
8.26
1.00
0.54
0.98
VC
1.8
0.6
5.4
1.0
1.3
4.9
7.4
1.6
10.2
13.6
14.6
37.7
5.51
0.00
0.96
12.70
0.00
0.99
0.62
12.94
1.56
0.55
1.54
0.078
0.967
0.490
<0.001
0.978
0.478
0.793
<0.001
0.016
0.849
0.020
0.64
proportion of variation (16.6%) in the analysis, indicating that
these differences were relatively large when compared to other
effects. Abundances of non-migratory species, such as freshwater
catfish and flathead gudgeon, had variable patterns associated
with estuarine connectivity. Due to low frequency of occurrence
of flathead gudgeon in the Paterson tributary, abundances were
consistently higher in the Williams tributary and accounted for a
large proportion of total variation explained (12.2%). Abundances
of freshwater catfish were similar between both tributary subcatchments throughout the study, although exhibited significant
temporal changes across both tributaries. Patterns in the abundances of Australian smelt showed that although they accounted
for 85% of all fish sampled in the Williams tributary, most of these
individuals were sampled between November 2006 and February
2007 (Fig. 2); the peak spawning and recruitment period for Australian smelt in this region.
Patterns in the composition of all fish sampled in the two catchments indicated although the significant main catchment effect
accounted for a large proportion of variation (10.4%), the significant C T interaction (3.1% variation) indicated that these differences were only apparent during October 2006 and December
2006–June 2007 (Table 4; Fig. 3). Abundances of diadromous Cox’s
12.1
0.0
0.0
7.3
0.0
0.0
0.0
14.8
3.8
0.0
7.4
54.6
F
P
4.41
1.38
2.56
5.71
2.16
1.07
1.75
5.91
1.06
1.23
1.23
0.097
0.308
0.016
<0.001
0.219
0.409
0.097
<0.001
0.365
0.308
0.158
0.46
Cox’s gudgeon
1039.90
5.73
86.15
98.59
52.82
29.96
18.87
138.79
16.99
13.93
16.64
5.2
0.6
2.4
3.7
3.6
0.2
2.3
7.6
0.5
1.6
3.9
68.4
7.49
0.06
5.07
12.96
0.38
1.80
1.11
18.25
2.23
0.84
2.19
0.052
0.816
<0.001
<0.001
0.565
0.095
0.378
<0.001
<0.001
0.603
<0.001
7.61
Freshwater catfish
3.84
0.09
2.65
3.26
0.23
0.49
0.34
1.69
0.57
0.30
0.37
VC
16.6
0.0
7.0
5.0
0.0
2.7
0.4
14.5
5.7
0.0
11.0
37.0
2.28
0.03
4.62
9.07
0.14
1.30
0.60
4.69
1.60
0.82
1.04
0.202
0.876
<0.001
<0.001
0.724
0.264
0.809
0.001
0.015
0.624
0.402
0.36
1.6
0.0
8.5
6.5
0.0
0.9
0.0
5.9
5.3
0.0
0.7
70.6
gudgeon were significantly associated (r = 0.89) with the second
PCoA axis that was associated with separating the assemblages
in the two study tributaries. Australian smelt was significantly
associated (r = 0.94) with the first PCoA axis that separated sites
according to temporal variation. The first and second PCoA axes explained 39.3% and 23% of total sample variation respectively.
3.3. Site scale patterns in abundance of diadromous and nondiadromous species
Accumulations of diadromous Cox’s gudgeon downstream of
Lostock Dam in the Paterson tributary were apparent when compared with spatial patterns in their abundance in the neighbouring
reference reach with no large dam upstream (Fig. 4). This pattern
in accumulation of Cox’s gudgeon was not evident in the Williams
tributary, where abundances were similar between sites in the
reach downstream of Chichester Dam and there were greater
site–site differences in abundances in the neighbouring reference
unregulated reach nearby (Fig. 4).
No accumulations of the potamodromous Australian smelt were
detected downstream of large dams in either of the Paterson or
Williams tributaries (Fig. 5). In unregulated reaches (i.e. no up-
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R.J. Rolls / Biological Conservation 144 (2011) 339–349
Fig. 2. Mean (±SD) number of species and catch-per-unit-effort (CPUE) of individual species in the Paterson (clear bars) and Williams (solid bars) tributary sub-catchments
sampled monthly between August 2006 and June 2007. A, C, P and N indicates amphidromous, catadromous, potamodromous and non-migratory, respectively.
Table 4
Summary of mixed-model multivariate Permutational Analysis of Variance results of
fish assemblage composition.
Source
MS
F
P
VC
Tr
Re
Ti
Site (Re)
Tr Re
Tr Ti
Re Tr
Tr site (Re)
Site (Re) Ti
Tr Re Ti
Tr Si(Re) Ti
21.42
1.03
6.60
1.83
2.32
1.04
0.64
1.97
0.51
0.72
0.52
10.89
0.56
12.99
5.34
1.18
1.99
1.27
5.74
1.48
1.38
1.52
0.010
0.730
<0.001
<0.001
0.336
0.001
0.155
<0.001
<0.001
0.075
<0.001
10.4
0.0
17.9
2.4
0.4
3.1
0.8
5.2
2.9
2.4
6.3
Residual
0.34
48.3
stream barrier), abundances of Australian smelt were highly variable between sites, with no particular sites having consistently
greater abundances. This site–site variability was also apparent
in the regulated reaches (i.e. large upstream barrier), indicating
that abundances of Australian smelt were less likely to be influenced by the location of migration barriers.
4. Discussion
4.1. Role of connectivity in structuring fish assemblages
Differences in fish fauna between the Paterson and Williams
tributaries were associated with varying connectivity with the
lower Hunter River estuary. Catchment fragmentation contributes
to homogeneous fish assemblages dominated by habitat generalist
species in reaches upstream of dams and weirs (Layman et al.,
2004; Guenther and Spacie, 2006). The fish fauna of the connected
Paterson tributary was dominated by larger abundances of diadromous species, whereas higher abundances of non-migratory or
potamodromous species were sampled in the restricted Williams
tributary. As dams restrict migration and dispersal, diadromous
species are most susceptible to damming of coastal rivers (e.g.
Han et al., 2008). Consequently, the persistence of diadromous species upstream of weirs without adequate fish passage facilities is
also unlikely in the long term (Morita and Yamamoto, 2002). In this
study, five of the total seven diadromous species were still recorded in the restricted Williams tributary, albeit in lower abundances when compared with the connected Paterson tributary,
indicating that connectivity at Seaham Weir is not completely restricted. However, freshwater mullet (Myxus petardi) and bullrout
R.J. Rolls / Biological Conservation 144 (2011) 339–349
345
Fig. 3. Principal Coordinate Analysis (PCoA) ordinations of assemblage composition indicating differences between the Paterson (s) and Williams (d) tributaries. Ordinations
are presented for (a) all replicate sites in each tributary and (b) the mean of all replicate sites in each tributary for each monthly sampling time (1: August 2006, 11: June
2007) indicating catchment level temporal trajectories in assemblage composition. Vectors of Spearman-rank correlations (r = >0.25) are included to indicate relationships
between species abundances and PCoA axes.
Fig. 4. Mean (±95% confidence intervals) catch-per-unit-effort CPUE of Cox’s gudgeon in the eastern Hunter River catchment sampled at upstream sites (solid bars), midreach sites (grey bars) and downstream sites (clear bars) monthly between August 2006 and June 2007 indicating spatial patterns in abundance of fish in relation to estuarine
connectivity and presence of upstream barriers.
(Notesthes robusta) were not recorded in the Williams tributary,
suggesting that these species may be more susceptible to the
impacts of barriers. This pattern is consistent throughout catchments of temperate Australia. In the Shoalhaven River, southern
coastal New South Wales, Gehrke et al. (2002) concluded that some
diadromous species, such as eels and Cox’s gudgeon, were able to
maintain populations upstream of Tallowa Dam by climbing over
the dam wall.
Despite numerous studies showing that fish assemblages are
disrupted by connectivity loss (e.g. Gehrke et al., 2002; Gillette
et al., 2005), few assessments are made to determine if impacts
of dams are more severe at times of recruitment and migrations,
or if impacts are consistent throughout all seasons. In this study,
it was predicted that differences between the Paterson and Williams tributaries would be more apparent during or immediately
after key migration periods. Differences in population size between
the two catchments were inconsistent among species and across
sample times, indicating that restricted estuarine connectivity
impacts the recruitment of individuals following spawning. For
example, significantly lower abundances of Cox’s gudgeon in the
Williams tributary when compared to the Paterson tributary were
detected between December 2006 and June 2007 suggesting that
Seaham Weir limits the juvenile migrations from the estuary to
freshwater reaches. In contrast, the abundances of long-finned eels
were significantly higher in the Paterson tributary throughout all
sampling times. Two possible explanations exist for these inconsistent patterns between the two species. Firstly, long-finned eels
may be more impacted by the presence of Seaham Weir restricting
estuarine connectivity than Cox’s gudgeon. This reason is unlikely,
as both species have been found to climb over a 43-m high dam
wall (Gehrke et al., 2002) and other barriers such as waterfalls
(Pusey et al., 2004), and therefore would be expected to be able
to pass Seaham Weir (2.5 m) assuming hydrological conditions allow. Secondly, the greater seasonal difference in abundance of
Cox’s gudgeon when compared to long-finned eel may be due to
differences in life-span and timing of movement from estuarine
346
R.J. Rolls / Biological Conservation 144 (2011) 339–349
Fig. 5. Mean (±95% confidence intervals) catch-per-unit-effort CPUE of Australian smelt in the eastern Hunter River catchment sampled at upstream sites (solid bars), midreach sites (grey bars) and downstream sites (clear bars) monthly between August 2006 and June 2007 indicating spatial patterns in abundance of fish in relation to estuarine
connectivity and presence of upstream barriers. Numbers next to individual bars represent actual abundance where y-axis has been reduced for clarity.
to freshwater reaches for the two species. Although detailed lifehistory information of Cox’s gudgeon is limited, they are unlikely
to live for >5 years and following spawning in lowland freshwater
reaches, larvae are transported downstream into estuaries before
migration into freshwater reaches in late Spring–Summer (Pusey
et al., 2004). Long-finned eels live for around 45 years and do not
show a distinct peak juvenile migration from estuarine to freshwater reaches (Pusey et al., 2004). This indicates that life-history patterns of fish species determine the relative impacts of migration
barriers. Consideration of the life-history patterns and migration
requirements of fish species is therefore crucial in determining
the impacts of barriers to migration and assessing the ecological
outcomes of restoring connectivity. Further research is also
required to determine the role of flow on the timing and success
of migration between freshwater and estuarine reaches.
4.2. Consequences of migration barrier location for detecting effects on
fish species distribution and abundance
Anthropogenic barriers impede fish migrations both upstream
and downstream. In this study, Cox’s gudgeon were consistently
sampled in high abundances immediately downstream of the
Lostock Dam in the Paterson tributary sub-catchment, indicating
that Lostock Dam restricted dispersal further upstream, especially
considering that abundances in the neighbouring unregulated Allyn River were more consistent between sites. Large accumulations
of Cox’s gudgeon were not evident in the reach immediately downstream of Chichester Dam, suggesting that such accumulations of
individuals are not apparent in this tributary sub-catchment impacted by poor estuarine connectivity due to Seaham Weir. In
the Williams sub-catchment, greatest abundances of Cox’s gudgeon were detected at the most highly elevated site (232 m) in
the unregulated tributary, particularly during October and December 2006 and January 2007. Although Cox’s gudgeon are one of the
few Australian diadromous species able to climb over natural and
artificial barriers, significantly large accumulations of juvenile individuals have been shown to accumulate downstream of Tallowa
Dam on the Shoalhaven River (Gehrke et al., 2002), indicating that
juveniles are more susceptible than larger adults to the impacts of
barriers due to a reduced ability to climb over barriers.
Impacts of anthropogenic migration barriers for fish are often
assessed using monitoring programs that compare differences in
fish assemblages between reaches upstream and downstream of
barriers (e.g. Martinez et al., 1994; Gehrke et al., 2002). Similar
sampling designs are often used to evaluate the response of fish
assemblages to attempts to restore connectivity using fishways
(e.g. Calles and Greenberg, 2005; Catalano et al., 2007), with the
prediction that fish assemblages upstream and downstream of barriers will become similar in composition following restored connectivity. Such sampling designs have two potential limitations.
Firstly, in many cases, either downstream or upstream reaches
are tested as reference reaches that imply that artificial migration
barriers only affect fish assemblages upstream of migration barriers and that fish assemblages are expected to be homogeneous
within river reaches. Accumulations of fish below barriers attempting to migrate upstream are therefore likely to exaggerate these
upstream versus downstream differences as under natural conditions (i.e. prior to the construction of a migratory barrier), fish
assemblages would be assumed to have gradual declines in species
richness with increasing distance from lowland estuaries (e.g.
Gehrke and Harris, 2000; Habit et al., 2007). Secondly, the possible
impacts of migration barriers in a river network other than those
targeted for assessment are often ignored (Kemp and O’Hanley,
2010). Upstream versus downstream comparisons and fish passage
assessments need to recognise potential impacts of barriers elsewhere in the river network, as migration barriers at sites closer
to lowland reaches or estuaries are likely to have larger-scale impacts, particularly for diadromous fish, when compared to barriers
at higher altitudes that are likely to have more localised effects
(e.g. Martinez et al., 1994; Fig. 6). Findings from this study, and
others (e.g. Calles and Greenberg, 2005; Slawski et al., 2008), indicate cumulative effects of multiple migration barriers within river
networks. Such cumulative effects have obvious implications for
assessing impacts of individual barriers if successive barriers upstream have reduced or more localised effects. These assessments
are likely to underestimate the impact of a migration barrier if it
is located in a reach that supports a fish assemblage under the
R.J. Rolls / Biological Conservation 144 (2011) 339–349
347
Fig. 6. Conceptual diagram indicating the predicted scale of influence of single migration barriers at A, lowland, B, slope and C, upland reaches. The area shaded indicates the
relative scale of impact for diadromous species. D, indicates the relative scale of influence of two migration barriers, with the impact of a barrier at higher altitude or lower
stream order having a relatively smaller impact (lighter shading) due to the larger-scale impact of a lowland barrier.
influence of other barriers that have catchment-scale consequences (Fig. 6). Monitoring program designs can be improved
by assessing fish species distribution in reference rivers in the absence of artificial barriers, and make comparisons to fish assemblages in rivers with both single and multiple migratory barriers
at different locations.
4.3. Relevance of catchment-scale connectivity for conservation of
freshwater fish biodiversity
Construction of fish passage facilities or complete removal of
redundant barriers is a tool increasingly used to restore reach
and catchment-scale connectivity loss (Bednarek, 2001; Hart
et al., 2002; Calles and Greenberg, 2005). Many programs aimed
at restoring catchment-scale connectivity prioritise this restoration
according to the length of river to benefit from restored connectivity (e.g. Mader and Maier, 2008; Kocovsky et al., 2009). Fish passage designs need to cater for local species, as many designs
limit passage of particular size classes or species due to varying
swimming performances (Calles and Greenberg, 2005). Following
the removal of a series of four small (1.5–2.4 m height) dams in
Baraboo River, USA, rates of recolonisation by fish species into upstream reaches varied, with species that exhibit large-scale spawning migrations (e.g. emerald shiner, Notropis atherinoides) having
greatest increases in catchment distribution (Catalano et al.,
2007). Upstream spawning movements of brown trout (Salmo trutta) through two fishways at hydropower stations in the River
Emån, Sweden, showed that although movement rates were slow,
connectivity was partially restored by the provision of fishways
(Calles and Greenberg, 2005). These examples show that dam re-
348
R.J. Rolls / Biological Conservation 144 (2011) 339–349
moval or provision of fish passage facilities provide unique opportunities to understand connectivity requirements by freshwater
fish and understand how freshwater ecosystems and biota respond
to both lost and restored connectivity.
Recognition of both freshwater-estuarine and whole of catchment connectivity is necessary to assess and manage migration
barriers for migratory fish species, as many fish species occupy
habitats covering distances of hundreds of kilometres over their
entire life cycle (Fausch et al., 2002). In this study, differences in
the composition of fish assemblages between the two tributaries
with varying degrees of estuarine connectivity suggest that barriers to migration in estuaries have impacts throughout the remainder of the catchment. In the Loire River catchment (France),
migration barriers closest to the estuarine tidal limit have been
recommended for improved management (e.g. fishway installation, barrier removal) over higher elevation barriers as the predicted distribution of diadromous European eel (Anguilla anguilla)
within the catchment would double (Laffaille et al., 2009). Abundances of anadromous Chinook salmon (Onchorynchus tshawytscha) have been strongly correlated with the magnitude of habitat
lost due to lowland barriers in the Willamette and lower Columbia
Rivers (Sheer and Steel, 2006), and lowland migration barriers have
greatest impact on the distribution of 30 fish species by restricting
upstream movements (Santucci et al., 2005). Collectively, these
findings show that by the way river networks are arranged, migration barriers in lowland or estuarine reaches have the greatest
magnitude of impact for freshwater fish assemblages. This evidence supports conservation planning approaches that recognise
connectivity between multiple environmental areas (e.g. freshwater-marine) (sensu Beger et al., 2010). Population and assemblage
level tools, such as otolith microchemistry, species distribution
and population genetic analysis, have potential application for
assessing the temporal and spatial scale impacts of migration barriers for freshwater fish (e.g. Wofford et al., 2005; Clarke et al.,
2007; Hughes, 2007; Buysse et al., 2008; Humston et al., 2010).
These tools can provide practical recommendations to inform prioritisation for connectivity restoration and the timeframes required for assessing biotic responses.
Acknowledgements
Andrew Boulton, Mark Dahm, Ivor Growns, Matt Maxwell, Sally
Maxwell, Rick Rolls, Maria Rolls, Rob Veal, and Jacqui Whitland
provided enthusiastic field assistance. Fieldwork was supported
by funding provided by the Australian Research Council, Hunter
Central Rivers Catchment Management Authority and the New
South Wales Department of Water and Energy. Sampling was conducted according to University of New England Animal Care and
Ethics approval (AEC 06/003) and NSW Department of Primary
Industries collection permit (P06/0014). Local landowners are
thanked for allowing access to study sites and their interest and
discussions regarding the ecology, conservation and management
of rivers in the Hunter River catchment. The time taken by Peter
Rose, Kate Smolders and two referees to review this paper is also
gratefully acknowledged, particularly in helping to clarify the specific implications of this study.
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