optimising environmental watering of floodplain wetlands for fish

Optimising environmental watering of floodplain wetlandsfor fish

LEAH BEESLEY*, ALISON J. KING* ,1 , BEN GAWNE†, JOHN D. KOEHN*, AMINA PRICE† ,

DARYL NIELSEN†, FRANK AMTSTAETTER* AND SHAUN N. MEREDITH† , 2

*Arthur Rylah Institute for Environmental Research, Heidelberg, Australia†Murray-Darling Freshwater Research Centre, CSIRO Land & Water and La Trobe University, Wodonga, Australia

SUMMARY

1. Flow alteration has reduced connectivity between many of the world’s rivers and their floodplains,

causing changes in riverine productivity and the isolation of floodplain wetlands. Environmental

water is being increasingly used to help restore wetland habitats and their biota, including fish.

However, some of these managed deliveries of water occur into discrete wetlands via artificial struc-

tures or at unseasonal times and may not deliver the expected gains in fish production.

2. In the Murray River, south-eastern Australia, we examined the relationship between attributes of

watering and fish production (species-specific recruitment, total abundance), at two time intervals:

short term (6–8 weeks after watering) and at the end of the spawning season (April) for 26 discrete

watering events. The study also recognised the importance of habitat in mediating fish responses to

watering and examined whether fish abundance after environmental water delivery is better pre-

dicted by attributes of watering or wetland characteristics?

3. We found that attributes of watering, including water source, its method of delivery and timing,

best described fish recruitment (0+ abundance) and total fish abundance. Managers of environmental

water may be able to optimise fish recruitment and abundance if they source their water from the

river and deliver it during the spawning period of the target species via means that facilitate fish

passage.

Keywords: environmental flow, fish recruitment, floodplain wetlands, Murray-Darling Basin, wetlandinundation

Introduction

The floodplain is the dynamic aquatic–terrestrial inter-

face of lowland rivers. It plays an important role in river

function by filtering and recycling nutrients, storing sed-

iments and water, acting as a hot spot of primary pro-

duction and supporting high biodiversity (Junk, Bayley

& Sparks, 1989; Bayley, 1995; Tockner, Malard & Ward,

2000). Floodplain wetlands and their biotas are under

increasing threat around the world from a range of

anthropogenic factors. Arguably, the most significant is

the alteration of their flow regimes through the construc-

tion and operation of dams, weirs and levee banks,

and water abstraction (Sparks, Nelson & Yin, 1998;

Kingsford, 2000; Richter et al., 2003). Today, the majority

of the world’s floodplain wetlands receive less water,

less frequently than in the past, and in many cases, the

seasonality of flooding has been altered (Galat et al.,

1998; Kingsford, 2000; Arthington & Pusey, 2003).

One technique to aid rehabilitation and conservation

is the use of environmental flows of water. In managed

systems, environmental water is that targeted for envi-

ronmental benefit (Arthington et al., 2010; Arthington,

2012). Environmental water aims to mimic key compo-

nents of the natural flow regime and can have specific

objectives related to improving water quality, or the

health of specific biota, through to holistic goals such as

improved ecosystem function (Arthington, 2012).

Although the procurement and application of environ-

mental water is gaining momentum, relatively few

Correspondence: Leah Beesley, Centre for Excellence in Natural Resource Management, The University of Western Australia, PO Box 5771

Albany, WA, Australia. E-mail: [email protected] address: Research Institute for Environment and Livelihoods, Charles Darwin University, Darwin, NT, Australia.2Present address: Department of Fisheries, Perth, Australia.

2024 © 2014 John Wiley & Sons Ltd

Freshwater Biology (2014) 59, 2024–2037 doi:10.1111/fwb.12404

studies have investigated biotic responses to environ-

mental watering (Poff & Zimmerman, 2010), limiting our

ability to deliver specific gains for river and wetland

biota. To date, protocols for environmental water man-

agement and delivery have been typically based around

restoring specific components of the natural flow regime

believed to be ecologically significant (Poff et al., 1997,

2010; Arthington et al., 2006). Given the increasing scar-

city of fresh water, and the need for water to be shared

among multiple users, it is critical that scientists provide

robust and defensible ecological predictions about the

use of environmental water allocations (Richter et al.,

2003).

Native fishes are common targets of environmental

flow restoration. A growing number of studies have

directly assessed how fish respond to the application of

environmental water. These studies report that environ-

mental flows can reinstate habitat or protect refuges

(Bradford et al., 2011; Ellis et al., 2013), increase fish dis-

persal/movement (Tonkin, King & Mahoney, 2008; Rein-

felds et al., 2010) and increase spawning and recruitment

(King, Cambray & Impson, 1998; King et al., 2010; Rolls

et al., 2013). However, this research area is relatively

new, and most studies have involved small spatiotempo-

ral scales (i.e. before and after a single flow pulse in a

relatively small area) (but see Kiernan, Moyle & Crain,

2012). This limits our understanding of the importance

of different attributes of environmental flows (e.g. mag-

nitude, frequency, timing, how the water is delivered,

antecedent conditions) and our understanding of the

extent to which attributes of local habitat may override

the effects of an environmental flow pulse. Greater

understanding will help managers to optimise the out-

comes of environmental flows for fish. For example,

improved knowledge of the relative importance of flow

and habitat characteristics will help managers to decide

whether they should focus their attention on determin-

ing which wetlands should receive water, getting water

delivery right (e.g. how and when to deliver it), or

indeed if both factors are equally important.

We investigated the influence of attributes of water

delivery and wetland habitat on the fish response to

floodplain inundation over a large spatial scale (Austra-

lia’s southern Murray-Darling Basin). The fish response

was measured as total fish abundance (all species) and

species-specific recruitment and was ascertained at two

time scales: short term after watering (6–8 weeks) and at

the end of the annual spawning season. A series of a pri-

ori hypotheses were constructed from an ecological and

management perspective. The ecological hypotheses

were based on our conceptual understanding of the key

ecological processes underlying fish production in flood-

plain wetlands. Management hypotheses were prag-

matic, including factors that a manager could either

manipulate (e.g. month of watering) or choose between

(e.g. location, area of the wetland). We expected that

ecological models would better describe fish production

compared with management models as they contained

factors thought to directly or indirectly control produc-

tion, but we had no a priori expectation about which

ecological process(es) would be most influential.

Methods

Study area and sampling design

This study was conducted in 22 floodplain wetlands

between 2008 and 2010. Twenty of the wetlands were

located between Albury and Renmark on the Murray

River and two were just outside the Murray River’s

catchment (one on the lower Darling River and another

on the lower Murrumbidgee River) (Fig. 1). All 22 wet-

lands received environmental water once and four of

them on two occasions so that a total of 26 watering

events were monitored.

Recognising that the benefits of wetland inundation to

fish are likely to change through time, changes in fish

abundance within wetlands were examined both in the

short term (weeks) and at the end of the spawning sea-

son (weeks to months). This was achieved by sampling

wetlands on three occasions, denoted Time 1 (T1), Time

2 (T2) and in April (Tapril). T1 occurred within

1–2 weeks of the commencement of watering and repre-

sents the community post-immigration from the river

and prior to within-wetland production. T2 occurred

7–8 weeks after the onset of watering and approximately

6 weeks after T1. Tapril occurred during April following

the watering event and represented the end of the

spawning season for most fish species. T1 and T2 data

were used in models assessing the short-term response

to watering, and T1 and Tapril data were used in mod-

els assessing the end-of-spawning-season response.

Wetland parameters

For each sampling event, we recorded (i) the location of

the wetland, (ii) attributes of watering (the source of

water, the method and duration of water delivery, the

presence of a fish exclusion screen), (iii) wetland charac-

teristics (area and depth of water, extent of inundation,

habitat complexity, water quality, primary and second-

ary production) and (iv) the seasonal potential for fish

© 2014 John Wiley & Sons Ltd, Freshwater Biology, 59, 2024–2037

Environmental watering to benefit fish 2025

to spawn within the wetland. See Table S1 for additional

methodological detail.

Fish sampling

The relative abundance of fish during each sampling

event was determined using single-wing fyke nets and a

beach seine. The fyke nets (5 m long, 0.6 m drop, 1.5-

mm mesh, with six hoops, two funnels) were set

overnight (12–14 h soak time) and were fitted with an

exclusion grill (50 9 50 mm) at the first funnel to reduce

potential turtle mortality and consumption of small fish

by turtles. The turtle exclusion grill meant that large-

bodied fish (>100 mm) were also excluded. Common

carp was the dominant large-bodied fish in the study

wetlands (L. Beesley unpubl data), but carp <1 year old

were captured. The seine net (7 m long, 1.5 m drop,

with a small purse, 0.5-mm mesh) was used to sample

approximately 21 m2 of the littoral zone during daylight

hours. Sampling effort was scaled to wetland size to

increase the precision of relative abundance estimates

and species detection in large wetlands, resulting in

more effort afforded in large wetlands and those with

overall low fish density. On average, five seine hauls

and five fyke nets were conducted for each sampling

event.

Fish were identified to species, counted and released.

During each sampling event, the first 100–150 fish of

each species collected by each method were randomly

selected from the catch and measured (fork length, mm).

When the number of fish captured per replicate

exceeded approximately 1000 fish, gravimetric subsam-

pling was used to estimate the number captured. Gravi-

metric subsampling involved placing all fish into an

aerated container and randomly taking 4–7 dip-net

scoops of fish for detailed analysis (until 150 fish of

abundant species had been measured). The weight of

the subsample was noted and was used to extrapolate

species abundance for the remaining sample.

Fish abundance and recruitment

Species-specific relative abundance was determined for

each sampling event as catch-per-unit-effort (CPUE) and

represented the mean number from all seine hauls plus

the mean number of all fyke net sets. The sum across all

species provided a description of total fish abundance

and was used to describe general changes in the fish

assemblage after watering.

To examine patterns in recruitment, relative abun-

dance data were truncated to focus on under-yearling

fish (0+) (larvae and juveniles). This was performed by

multiplying species-specific relative abundance values

for each method by the proportion of fish that were 0+

based on field measurements. Recruitment was only

assessed for four abundant taxa: two natives, carp gud-

geon species complex (Hypseleotris spp.) and unspecked

hardyhead (Craterocephalus stercusmuscarum fulvus), and

1

21–22

2-4

20

6–8

19

5

18

17

161514

1310–12

9

Murrumbidgee River

Murray River

Murray River

Oven’s River

Edward River

Darling River

Wakool River

Fig. 1 Location of the 22 study wetlands in the mid- and lower sections of the Murray River and its major tributaries. The location of the

study region in south-eastern Australia is shown in the inset.


2026 L. Beesley et al.

two aliens, common carp (Cyprinus carpio) and eastern

gambusia (Gambusia holbrooki). These taxa are wide-

spread, locally abundant and breed during the spring

and summer months when the study wetlands were

watered (Lintermans, 2007).

Hypothesis construction

To learn about key factors, but avoid statistical errors

(i.e. over-fitting the data), we constructed alternate

hypotheses (statistical models) and used hypothesis test-

ing to look for support among models (see section Statis-

tical Analyses below). Our models were restricted to five

or fewer parameters (as per Anderson, 2008), resulting

in at least 10 observations per parameter for all models.

Two types of hypotheses (models) were constructed:

ecological models and management models. Ecological

models were based on our understanding of the key

ecological processes underlying fish abundance in wet-

lands after environmental watering (see Fig. 2). The

models are a simplification of a complex Bayesian belief

network that was constructed to describe the effect of

environmental watering on ‘fish population health’ (see

Gawne et al., 2012; Vilizzi et al., 2013a). These models

allow us to conceptualise the mechanisms that underpin

the fish response to environmental watering and

describe within-wetland ecological processes indirectly

using wetland habitat characteristics or environmental

watering attributes. In contrast, management models

were pragmatic; that is, they contained wetland habitat

characteristics or environmental watering attributes

managers informed us they could manipulate (e.g.

month of watering) or choose between (e.g. area,

method of water delivery) (see Meredith & Beesley,

2009). The ecological and management models for fish

abundance are described in detail in Table 1.

Ecological and management models were investigated

as full (global) models (i.e. all parameters included) and

as submodels (i.e. models that were increasingly simplis-

tic). This was performed because we recognised that

models that contained more parameters would be pena-

lised by the model selection procedure (see section Sta-

tistical Analyses below). The submodels did not include

all possible combinations of parameters, but included

the parameters we believed ‘a priori’ would be most

influential.

Statistical analyses

Short-term and end-of-spawning-season changes in wet-

land characteristics were investigated by using two-

sided paired t-tests to compare data collected during T1

and T2 (n = 22) and T1 and Tapril (n = 18), respectively.

To ensure independence of samples, only one sampling

event, chosen at random, was included for wetlands that

were watered more than once. Estimates of chlorophyll

a and microcrustacean density were log-transformed

prior to analyses to improve normality and reduce het-

eroscedascity. Wetlands that were dry at Tapril were

excluded from paired analyses.

characteristics

q y ( , )

attributes

, p pquality

Voll f t

Abundance prior to environmentalwatering (H1)Wetland habitat Environmental watering

Location in catchment

Area of residual pool (ha)

Depth of residual pool (m)

Structural complexity (%)

Water DO EC

Source water (river, creek, irrigation canal)

Method of water delivery (pump, unregulated channel, regulated channel i e/culvert)

Loss (mortality/emmigration)Movement out of wetland (H2)Water quality mortality (H5)Predation (fish and bird) (H6)

Fishassemblage in environmental water (H2b)

Food production (phytoplankton, micro-crustaceans)

Abundance of predatory fish and birds

Temperature (˚C)

Area inundated (ha)

Duration of connection (days)

Inflow screens fitted (yes/no)

Time inundation commenced (month)

Gain (recruitment/immigration)Movement into wetland (H2)Spawning inside wetland (H3)

Fishmovement(H2a)

ume o wa er

Abundance post environmental watering

Starvation of larval fish (H4)

Fig. 2 A conceptual model depicting the environmental watering attributes and wetland habitat characteristics affecting wetland fish abun-

dance following environmental watering. The key ecological processes (or pathways) form the basis of the hypotheses (H) tested in this

study (see Table 1). Detailed descriptions of the watering attributes and habitat characteristics are provided in Table S1. The dashed line

represents the linkage between the volume of water delivered to the wetland and the area newly inundated (area inundated). Area inun-

dated was used in the models because an increase in floodplain habitat is more biological meaningful than volume.



To identify which hypotheses best described how fish

abundance (CPUE) responded to environmental water-

ing, we used model selection, whereby each hypothesis

was considered as a competing model. Prior to running

models, we examined watering and habitat characteris-

tics to ensure that strongly collinear terms were not

included in the same model: pairwise correlations (Pear-

son’s r) were used for continuous variables and chi-

squared contingency tables for categorical variables.

Continuous variables with skewed distributions were

transformed prior to analysis. Thus, estimates of area,

chlorophyll a and microcrustacean density were log-

transformed, whereas duration of watering was square-

root-transformed. Models were fitted to the data using

restricted maximum likelihoods (REML) and run in Gen-

stat for Windows, 14th ed. (The Numerical Algorithms

Group Ltd., Oxford, U.K.). Wetland number was

included in all models as a random term and time (T1,

T2 or T1, Tapril) as a fixed term. All other descriptor

variables (watering and habitat attributes, spawning

months) were included as fixed terms and were centred

(mean subtracted to standardise around zero) prior to

analysis. The parametric assumptions of each model

(normality, homoscedascity) were evaluated by viewing

residual plots (q-q, histograms, fitted values). Models

that violated assumptions were omitted from the model

selection procedure. Model selection was based on

Akaike’s information criteria corrected for sample size

(AICc), a measure that describes fit and penalises com-

plexity (Johnson & Omland, 2004). The model with the

lowest value has the best fit relative to its complexity

and is the preferred model, or the model with most sup-

port. Models with AICc weights (normalised relative

likelihood value) within 10% of the weight of the model

with most support (model with highest weight) are con-

sidered to also have good support (Burnham & Ander-

son, 2004). When several models had support

(confidence set), model averaging was used to estimate

parameter values and their variance (Burnham & Ander-

son, 2004; Mazerolle, 2006). The strength of parameters

and their effects were determined by examining their

83% confidence interval (CI); 83% CIs have been found

to be better at providing an a 0.05 level than 95% CIs,

which are overly conservative (Payton, Greenstone &

Schenker, 2003). Strong parameters and their effects are

those whose values did not include zero or overlap with

Table 1 Ecological and management models describing fish abundance in wetlands after environmental watering

Hypothesis Description Parameters (global model)

Ecological models

H1 Fish abundance within a wetland prior to water determines fish

abundance after environmental watering

Pre-watering area + pre-watering depth + average

structural complexity + location

H2 The potential for fish to colonise the wetland during

environmental watering determines fish abundance after

environmental watering. This was separated into two

components

● H2a The fish species richness and abundance in the source

water (i.e. the environmental water) determine fish


Source water + location

● H2b The ease with which fish move from the source water

into the wetland determines fish abundance after

environmental watering

Temperature at T1 + duration + carp screen + method of

delivery

H3 The potential for fish to spawn and recruit inside the wetland

determines fish abundance after environmental watering

Month of inundation + number of spawning months

H4 Food production within the wetland structures young-of-year

survival (i.e. drives recruitment), hence determines fish


Newly inundated area + temp + structural

complexity + chlorophyll a + microcrustaceans

H5 Water quality within the wetland structures survival, hence


Temp + dissolved oxygen + conductivity

H6 Predation within the wetland structures survival, hence


Depth + structural complexity + depth*structuralcomplexity

Management models

H7 Watering attributes determine fish abundance after environmental

watering

Newly inundated area (surrogate for amount of water

added) + duration of watering + month of

inundation + method of delivery

H8 Wetland characteristics determine fish abundance after

environmental watering

Inundated area (wetland

size) + depth + structural complexity + location



one another (Mazerolle, 2006). CPUE data were log

(n + 1)-transformed prior to analyses.

Results

Watering and wetland characteristics

Apart from one watering event in autumn, which was

only included in the end-of-spawning-season data set,

the remaining 25 watering events took place during

spring and summer (see Figure S1). Water was delivered

along unregulated connecting channels for just under

half of the studied events, while the remaining deliveries

were facilitated by management via regulators, pumps

or siphon/gravity feed through pipes and culverts. The

environmental water used was nearly always sourced

from the river; however, permanent creeks and irriga-

tion channels were also used. The duration of watering

was relatively short, lasting on average 29 days (range:

2–122 days). For most events, water did not pass

through a carp screen.

Water was delivered into both previously dry and wet

wetlands, and wetland physicochemistry and structural

complexity varied markedly as did the concentration of

chlorophyll a and the density of microcrustacean zoo-

plankton (see Table 2). In the short term after watering

(T1, T2), paired t-tests revealed a significant decline in

depth, and an increase in conductivity, chlorophyll a

and microcrustacean density (statistical results provided

in Table 2). No changes were detected in wetland area,

water temperature, dissolved oxygen or structural

complexity over the same period. Similar, but stronger,

patterns were evident at the end of the spawning season

(T1 to Tapril) for most aspects of habitat, except for

microcrustacean density, which declined to levels similar

to those recorded at T1; wetland area and water temper-

ature declined significantly from T1 to Tapril (Table 2).

The fish assemblage

More than 900 000 fish, representing 10 native and five

alien species, were collected during the study. The catch

was numerically dominated by 0+ size classes (including

larvae), making up 70.7% of CPUE when pooled across

wetlands and sampling events. The 0+ fish assemblage

was dominated by carp gudgeon, which made up 49.4%

of the total 0+ fish CPUE (n = 13 422). Other species that

made a notable contribution included eastern gambusia

(28.6%, n = 10 247), common carp (21.2%, n = 7587) and

unspecked hardyhead (7.3%, n = 2608). Goldfish, Carras-

sius auratus, and Australian smelt, Retropinna semoni,

were present in low numbers, contributing 2.8%

(n = 1012) and 1.0% (n = 369) of 0+ CPUE, respectively.

Temporal trends in total fish catch within wetlands post-

watering varied markedly among watering events (see

Figure S1).

Hypothesis testing: species-specific recruitment and total

abundance

Of the 25 competing models predicting species-specific

0+ CPUE and total fish CPUE, those with the most

Table 2 Mean � SE habitat characteristics of the study wetlands for the three survey times: T1 = within 2 weeks of commencement of envi-

ronmental watering, T2 = 6 weeks after the initial survey and Tapril = end of the spawning season. Significant temporal changes in parame-

ters over the short term (T1, T2; d.f. = 25) or by the end of the spawning season (T1 to Tapril; d.f. = 21) were determined using paired

t-tests and are shown in columns T2 and Tapril in parentheses using arrows; upward arrows indicate an increase through time, downward

arrows indicate a decrease

Habitat Characteristic T1 T2 TaprilΔ

Number of wetlands sampled 27 26 22

Pre-wet area (ha) 5.59 � 3.04 (0 - 60) NA NA

Pre-wet maximum depth (m) 0.63 � 0.13 (0 – 2.5) NA NA

Newly inundated area (ha) 29.84 � 12.01 (0.2 – 220.0) NA NA

Wetland area (ha) 35.48 � 14.79 (0.1 – 280.0) 32.01 � 14.07 11.12 � 5.62 (↓)***Wetland depth (m) 1.12 � 0.12 (0.4 – 2.8) 1.04 � 0.13 (↓)* 0.84 � 0.14 (↓)***Water temperature (°C) 23.5 � 1.1 (12.2 – 31.8) 25.1 � 0.53 16.9 � 0.5 (↓)***Conductivity (mS cm�1) 0.108 � 0.021 (0.04 – 0.54) 0.150 � 0.030 (↑)* 0.119 � 0.014 (↑)***Dissolved oxygen (mg L�1) 6.75 � 0.36 (2.9 – 10.8) 6.09 � 0.52 5.92 � 0.73

Chlorophyll a (lg mL�1) 106.1 � 39.9 (11.4 – 1104.5) 183.0 � 45.8 (↑)** 650.3 � 133.9 (↑)***Microcrustaceans (#/L�1) 202.3 � 53.0 (3.9 - 1066.7) 318.8 � 74.5 (↑)* 204.5 � 41.4

Structural complexity (%) 47.8 � 5.0 (9.0 – 92.5) 55.0 � 5.2 36.4 � 5.5

Δ = four wetlands were omitted from the Tapril sample as they were dry.

*Significant at a 0.05, **significant at a 0.01, ***significant at a 0.001. The range in wetland habitat characteristics at T1 is shown in

parentheses.



support (confidence set of models) were broadly similar

among the four species examined (carp gudgeon, uns-

pecked hardyhead, common carp and eastern gambusia)

over the short term and to the end of spawning season

(Table 3). For each data set, there were two or three

models with similarly good support. This confidence set

of models was composed of watering attributes, rather

than wetland characteristics, and management perspec-

tive models were typically more effective at describing

fish abundance than the ecological process models

(higher relative weight, see Table S2). The confidence set

of ecological models most often described spawning

activity in the wetland, but also described fish abun-

dance in the environmental water and fish movement

into the wetland (Table 3). Model-averaged parameters

with strong effect sizes within the confidence set of

models included time, source water, method of delivery,

month of inundation, duration of watering and location.

The strength of effects for these factors varied among

species and through time and a presentation of patterns

follows.

Time. The 0+ CPUE of common carp increased mark-

edly in the short term after watering (Fig. 3a). By the

end of the spawning season, 0+ CPUE gains for carp

were lost, but a sixfold gain occurred for eastern gambu-

sia. Total fish CPUE also increased (Fig. 3b).

Source water. Total fish CPUE and carp gudgeon 0+

CPUE were greater when water was sourced from a

permanent channel or the river compared with an irriga-

tion channel, for both the short term and end of the

spawning season (Fig. 3c,d).

Method of delivery. Total fish CPUE was lowest when

water was passed through a small pipe/culvert, highest

when water was delivered through an unregulated

channel and intermediate when delivered through a

Table 3 The ecological process and management perspective models describing fish abundance that received support using Akaike’s infor-

mation criteria corrected for small sample size (AICc). The linear models describe fish recruitment [0+ catch-per-unit-effort (CPUE)] for the

four target species and general fish abundance (total CPUE), in the short term after watering (T1, T2, n = 52) and the end of spawning sea-

son (T1, Tapril, n = 48). Lower AICc values indicate better fit and lower complexity. Akaike’s weights (wi) are given in parentheses for each

model, and models with weights >10% of the model with the lowest AICc value are bolded (candidate set for best model)

Model terms

Short-term response (T1, T2) End-of-season response (T1, Tapril)

0+ 0+

Carp

gudgeon

Unspecked

hardyhead

Common

carp

Eastern

gambusia Total fish

Carp

gudgeon

Unspecked

hardyhead

Common

carp

Eastern

gambusia Total fish

Ecological processes

H2a: fish abundance in the environmental water

H2ai: time + source

water + location

124.8 (0.022) 116.1 (0.000) 135.4 (0.000) 104.1 (0.001) 100.6 (0.467) 124.7 (0.030) 115.9 (0.007) 114.4 (0.019) 117.0 (0.143) 102.1 (0.203)

H2b: fish movement into the wetland

H2bii: time +

MOD + duration

131.3 (0.001) 115.9 (0.000) 140.0 (0.000) 113.1 (0.000) 113.4 (0.001) 127.8 (0.006) 109.8 (0.148) 122.5 (0.000) 114.3 (0.551) 108.6 (0.008)

H3: spawning activity within the wetland

H3i: time + month

of inundation +

number of spawning

months

120.57 (0.176) 100.37 (0.670) 128.8 (0.004) 94.0 (0.232) 113.8 (0.001) 124.8 (0.029) 107.4 (0.492) 109.2 (0.260) – 112.7 (0.001)

Management perspective

H7: watering attributes

H7i: time + newly

inundated area +

duration + month

of inundation + MOD

124.3 (0.028) – 124.5 (0.035) 98.1 (0.030) 108.0 (0.012) 122.8 (0.077) – 113.5 (0.030) 122.7 (0.008) 105.4 (0.038)

H7ii: time + newly

inundated area + MOD

127.5 (0.006) 113.9 (0.001) 135.4 (0.000) 110.9 (0.000) 109.5 (0.006) 124.7 (0.030) 112.1 (0.047) 118.2 (0.003) 122.8 (0.008) 102.9 (0.136)

H7iv: time + month

of inundation + MOD

117.67 (0.750) – 117.9 (0.958) 92.2 (0.572) 100.5 (0.504) 118.3 (0.746) – 108.1 (0.451) 116.7 (0.166) 100.1 (0.553)

H7v: time + month

of inundation

127.0 (0.007) 101.80 (0.327) 129.9 (0.002) 94.7 (0.161) 117.9 (0.000) 125.9 (0.016) 108.9 (0.227) 109.5 (0.219) 121.0 (0.019) 114.8 (0.000)

MOD, method of water delivery.

A detailed description of model terms are provided in Table S1.



CG HH CC EG TF–1

0

1

2

3

irrigation channelpermanent channelriver

Short-term End of spawning season

CG HH CC EG TF

0

1

2

3

T1T2Tapril

CG HH CC EG TF

0

1

2

3

CG HH CC EG TF–1

0

1

2

3

CG HH CC EG TF–1

0

1

2

3

para

met

er e

stim

ate

(+/–

83%

CI)

CG HH CC EG TF–1

0

1

2

3

pipe-culvertpumpregulatorunregulated

CG HH CC EG TF–1

0

1

2

3

CG HH CC EG TF–2

–1

0

1

2

3

4

5MaySeptemberOctoberNovemberJanuaryFebruary

(c) source water

(e) method of delivery

(g) month of inundation

(f)

(h)

(d)

(a) time (b)

Fig. 3 Model-averaged parameter estimates and weighted unconditional 83% confidence intervals of fish catch-per-unit-effort (log-trans-

formed) in the short term (T1, T2) and end of spawning season (T1, Tapril) for time (a, b) and important watering attributes: source water

(c, d), method of delivery (e, f) and timing of delivery (g, h). Estimates are shown for 0+ carp gudgeon (CG), unspecked hardyhead (HH),

common carp (CC), eastern gambusia (EG) and total fish (TF).



pump, in the short term and by the end of the spawning

season (Fig. 3e,f). Regulated water delivery was associ-

ated with total CPUE that was similar to unregulated

and pumping in the short term, but higher than pump-

ing by the end of the spawning season (Fig. 3e,f). Carp

gudgeon 0+ CPUE was lowest when water was deliv-

ered through a pipe or culvert compared with all other

methods (Fig. 3e,f). Unspecked hardyhead 0+ CPUE was

greatest when water was delivered via an unregulated

channel compared with all other methods (except pump-

ing in the short term) (Fig. 3e,f). Common carp 0+ CPUE

was lowest at the end of the spawning season when

water was pumped rather than flowing through an

unregulated channel into wetlands (Fig. 3f). Eastern

gambusia 0+ CPUE did not change with the method of

delivery (Fig. 3e,f).

Month of inundation. The timing of watering was impor-

tant to short-term 0+ CPUE, but the response differed

among species. Carp gudgeon, unspecked hardyhead

and eastern gambusia displayed greater 0+ CPUE when

watering events occurred later in the spawning season

(November to February) than events early in the

spawning season (September and October). Carp dis-

played higher 0+ CPUE in November compared with

other times (Fig. 3g). The timing of watering was less

important to CPUE by the end of spawning season

(Fig. 3h).

Duration of watering. The length of watering was only

important for unspecked hardyhead. Longer events were

associated with increased 0+ CPUE in both the short

term and by the end of season (T1, T2: parameter esti-

mate = 0.072 (83% CI 0.028–0.117); T1, Tapril parameter

estimate: 0.126 (83% CI 0.083–0.168).

Location. Geographical location along the Murray River

was only important for total fish: CPUE was greater for

wetlands in the mid-Murray compared with the lower

Murray [T1, T2: parameter estimate lower Murray = 0.746

(83% CI 0.400–1.092), mid-Murray = 1.998 (83% CI 1.777–

2.219); T1, Tapril parameter estimate lower Murray = 1.009

(83% CI 0.560–1.458), mid-Murray = 1.976 (83% CI 1.763–

2.189)].

Discussion

Attributes of watering affect fish production in wetlands

This study is the first, to our knowledge, to explore the

relative influence of within-wetland habitat characteris-

tics and attributes of environmental watering on fish

abundance in floodplain wetlands. Discrete hypothesis

testing demonstrated that watering attributes were more

important in describing fish abundance than wetland

habitat attributes. Furthermore, models that included

pragmatic water management decisions were just as

effective at describing fish production as ecological mod-

els. The environmental watering attributes that were of

most importance included the source water (where the

environmental water was sourced from), the method of

delivery (e.g. through pipes, regulators or natural chan-

nels) and the timing of environmental water delivery.

Still significant, but of lesser importance, was the dura-

tion of the watering event.

The importance of particular watering attributes dif-

fered among species. However, in general, fish abun-

dance (species-specific recruitment and total abundance

of all species and all size classes) was highest when

watering was relatively natural (i.e. the environmental

water was sourced from the main river channel, or a

large permanent channel, and delivered through a regu-

lated or unregulated channel). Conversely, abundance

was lowest when watering was highly artificial (i.e. when

environmental water was sourced from an irrigation

channel and passed through small pipes or culverts).

Sourcing environmental water from artificial sources,

such as irrigation canals, will diminish fish colonising

ability, because compared with nearby natural water-

courses, irrigation canals typically support lower fish

abundance and biomass (Katano et al., 2003), a higher

proportion of alien species (Cowley, Wissmar & Sallen-

ave, 2007) or fewer native species (King & O’Connor,

2007). Delivering environmental water via artificial

means, such as pumping or through pipes and culverts,

can diminish colonisation by restricting fish passage into

the wetland. Many studies have been conducted world-

wide on the negative effects of pipes/culverts on fish

passage (Baker & Votapka, 1990; Boube’e et al., 1999;

MacDonald & Davies, 2007), but relatively few have

examined the effects of pumping. Nevertheless, pump-

ing is known to cause injury and mortality to fish,

although the extent of the damage is variable across spe-

cies and sizes (Baumgartner et al., 2009; Thompson et al.,

2011). The filtering effect of pumping can be used by

management to benefit the native fish community. That

is, we found that recruitment of the large-bodied alien

pest species common carp was reduced when pumps

were used. Similarly, one-way pumping of environmen-

tal water into the previously dry Hattah Lakes (Victoria,

Australia) excluded common carp and allowed small-

bodied native fish to thrive (Vilizzi et al., 2013b).



The importance of the source fish assemblage (repre-

sented by ‘source water’ in our analysis) and the

method of delivery suggest that colonisation dynamics

are critical to the fish production benefits that can be

gained from environmental watering. The importance

of colonisation dynamics is analogous to the impor-

tance of landscape factors in shaping fish assemblages

in rivers, wetlands and lakes (Snodgrass et al., 1996;

Hershey et al., 2006; Beesley & Prince, 2010). Studies

conducted at broad spatial scales have found that fac-

tors that affect migration, such as distance to refuge

pools, the length of hydrological connectivity and the

presence of barriers (e.g. dams, waterfalls, elevation),

affect fish species richness and abundance (Taylor,

1997; Galat et al., 1998; Baber et al., 2002). If fish coloni-

sation into environmentally watered wetlands is

impeded, then low fish density may limit subsequent

reproduction and recruitment, particularly for species

with low fecundity. Colonisation dynamics will be criti-

cal when wetlands are dry prior to receiving environ-

mental water.

Delivering environmental water sourced from artificial

habitats via artificial means is less than ideal, but in

many cases, it is the only option available to managers

(Meredith & Beesley, 2009). This is particularly the case

in eroded, heavily fragmented or drought-stricken

systems, such as the Murray River. If the aim of water-

ing is to improve the health of riparian vegetation along

wetland margins, then the method used to deliver the

water is likely to be less important. However, if manag-

ers wish to obtain more holistic ecological gains (e.g.

benefits for fauna also), then both connectivity and the

condition of the water source and target wetland should

be considered.

An important, if not surprising, finding of our study

is that watering during the peak spawning period deliv-

ered the greatest short-term (6 week) gain in recruit-

ment. Appropriately timed floodplain inundation has

been found to maximise fish recruitment in other studies

(see Galat et al., 1998; King, Tonkin & Mahoney, 2009;

Gorski et al., 2011). The timing of watering would proba-

bly have been an even stronger predictor of short-term

recruitment had this study sampled a greater number of

watering events outside the spawning season (e.g.

autumn–winter in the Murray River).

Interestingly, we found that the timing of watering

was of reduced importance when fish abundance was

assessed at the end of the spawning season (April). This

may be because short-term gains in recruitment may be

lost within disconnected wetlands as they shrink. Fol-

low-up watering events that allow the wetland to recon-

nect to the river channel are likely to deliver the greatest

benefit to the metacommunity.

The duration of watering was related to recruitment

for only one of the four species studied, the unspecked

hardyhead, which had greater recruitment after longer

watering events (>1 month). Longer connection between

the source water and the wetland allows more time for

fish passage and was positively related to fish species

richness and abundance in temporary wetlands in Flor-

ida, U.S.A. (Baber et al., 2002). Studies of fish movement

into wetlands conducted elsewhere in the Murray River

found that peak movement of unspecked hardyhead did

not occur until the seventh week of wetland–river con-

nection (A. Price, Murray-Darling Freshwater Research

Centre, pers. comm.). Short watering events could ham-

per colonisation of unspecked hardyhead and other

slower-moving species. Apart from a few studies noting

that fish move into wetlands during the rising phase of

the hydrograph (Kwak, 1988; Lyon et al., 2010), there is

little information about how characteristics of flow affect

the movement of fish species between river and wetland

habitats.

Our study indicates that factors that affect colonisation

affect how the wetland fish assemblage responds to

environmental watering. However, our evidence is only

correlative. While findings from other studies support

our results, sampling the fish assemblage in different

types of source water at the time of watering and sam-

pling the fish moving into the wetland would strengthen

our inference. In addition, sampling the fish assemblage

prior to environmental watering, as well as after water-

ing has ceased, will help future studies to separate out

the effects of colonisation from within-wetland recruit-

ment post-watering. We chose not to examine fish

abundance over the longer term (1 year plus), as we

could not guarantee that wetlands would not reconnect

with the river and this would confound our ability to

determine the influence of initial watering attributes.

Wetland habitat characteristics are less important for

shaping wetland fish production

High primary productivity and low predation pressure

are thought to be the key reasons why floodplain wet-

lands are productive nurseries for fish (Junk et al., 1989;

Bayley, 1995). However, we found that these processes

were less important in shaping wetland fish abundance

than attributes of watering. The lack of an association

between fish abundance and predation risk (described

by proxies of structural complexity and wetland depth)

may be a consequence of the rarity of predatory fish



within the study wetlands (see MacDonald et al., 2012).

As a mediator of biotic interactions, habitat is likely to

play a more important role in wetlands that support

high numbers of predators, such as the neotropical lakes

of Venezuela (Rodriguez & Lewis, 1994; Tejerina-Garro,

Fortin & Rodriguez, 1998). The lack of an association

between fish recruitment and food density in our study

was not an artefact of limited variation in microcrusta-

cean density in the study wetlands. Indeed, microcrusta-

cean density varied by two orders of magnitude

(17–1867 L�1), spanning the range that is thought to

affect the survival rates of fish larvae (Rowland, 1996).

Our results suggest that starvation is not a key process

driving recruitment in this system. However, it is possi-

ble that top-down regulation of microcrustaceans by fish

larvae (see Grosholz & Gallo, 2006) may be obscuring

our capacity to detect this type of relationship.

We found that only one non-watering factor, locality,

was related to fish abundance within wetlands after

environmental watering. Wetlands located upstream of

the town of Swan Hill had greater total fish abundance

than those downstream. Position within the catchment is

well known to shape fish assemblage structure; how-

ever, changes are typically in terms of increasing species

richness downstream (Schlosser, 1987; Osborne & Wiley,

1992; Taylor, 1997). We suggest our result is an artefact

of a partial correlation between location and method of

water delivery. For example, the vertical distance

between water level in the river and the floodplain

increases with increasing distance down the Murray

River, so that managers in the lower reaches (with

higher banks) have no option but to pump water. Fur-

ther investigation of pumping events higher in the catch-

ment and/or more natural watering events lower in the

catchment would help to tease these factors apart.

Wetland watering to improve fish communities at the river

scale

While there is still some debate about the importance of

the floodplain as a spawning and nursery area for fish in

temperate systems (see Humphries, King & Koehn, 1999;

King, Humphries & Lake, 2003; Zeug & Winemiller,

2008), studies in tropical systems have revealed

that floodplain-derived carbon makes a substantial

contribution to fish production in the main river channel

(Winemiller & Jepsen, 1998; Jardine et al., 2012). For pro-

ductivity gains to benefit the fish metacommunity and

the river system in general, wetland fish and biota-laden

water must be able, at least on some occasions, to return

to the river. Indeed, good lateral connectivity is viewed

as fundamental to the healthy functioning of lowland

rivers (Junk et al., 1989; Sparks, 1995; Sparks et al., 1998).

In the southern Murray-Darling Basin, wetland managers

rarely consider facilitating the movement of fish or biota-

laden water back to the river after discrete wetland or

creek watering events (Meredith & Beesley, 2009). This

is, in part, because most environmental watering of wet-

lands is not carried out with the fish metacommunity or

the whole-of-river in mind. Rather, watering generally

has a narrower ecological target, for example, to improve

the health of drought-stressed riparian vegetation, assist

the breeding of colonial waterbirds or sustain refuge

aquatic habitat for threatened fish (Kingsford & Auld,

2005; Meredith & Beesley, 2009; Russo, Fisher & Roche,

2012). The imperative to generate as many ecosystem

gains as possible with a limited and valuable resource

(environmental water) means that managers will increas-

ingly try to benefit multiple biological targets with their

watering. Further investigation is needed to determine

the extent to which native fish production in floodplain

environments augments or subsidises fish production at

a larger spatial scale, during both drought and flood.

There is also a need to determine how important the

return of biota-laden water to the river is for within-river

fish production. Without this information, we cannot

assess whether small-scale environmental watering

events can play a role in sustaining system-wide fish

productivity during periods of prolonged river–wetland

disconnection, a situation that is likely to become

Environmental water

Habitat relationships

Biotic relationships

Geographic filter

location in MDBDetermines the likely presence of the fish species in the area

Watering filter

Determines how many and what size class of fish move into wetland, and if they breed

Affects fish growth, body condition and survival

Fish abundance/recruitment

method of delivery, source water, timing, duration of connection, carp screen

water quality, habitat structure, food availability, hydroperiod

competition and predation

Fig. 4 Conceptual filter detailing how landscape, watering, habitat

and biotic relationships are predicted to affect the fish productivity

response to the delivery of environmental water into floodplain

wetlands.



increasingly common under a drying climate and

increasing human demand for water (Poff et al., 2003).

Viewing the outcome of environmental watering through a

hierarchical filter

We propose that fish production in response to environ-

mental water delivery be viewed in terms of a hierarchi-

cal filter, sensu Poff (1997) (Fig. 4). Firstly, geographical

location will determine the subset of species that may

respond to the environmental watering event, and the

life-history characteristics of these species will determine

their capacity to respond quickly to watering events.

Species best placed will be those with early maturation,

short generation times and protracted spawning,

typically termed r-selected (Pianka, 1970) or opportunis-

tic species (Winemiller & Rose, 1992). Secondly, water-

ing attributes will determine how many, what species

and what size class move into the target wetland (source

water, method of delivery). The timing of watering will

also determine whether species are able to breed in the

short term. Finally, habitat and biotic interactions within

the wetland will affect the growth, body condition and

survival of fish after watering.

Acknowledgments

We thank Danielle Smith, Simon Maffei and Alasdair

Grigg for assistance in the field and laboratory, and An-

thea Brecknell for project management. We thank the fol-

lowing natural resource managers for making available

information related to managed watering; Keith Ward,

Melanie Tranter, Heidi Kleinert, Paula D’Santos, Sascha

Healy, Emma Wilson and James Maguire. We thank Jane

Reid, Sam Cross, Mick Greatz, Paul Cohrs, Tim Mills and

Lance Howley for access to their property. Fish sampling

was performed under animal ethics approval AEC07-14,

and NSW fisheries permit P07/0115. This work was

funded by the National Water Commission through its

Raising National Water Standards Program. This Austra-

lian Government programme supports the implementa-

tion of the National Water Initiative by funding projects

that are improving Australia’s national capacity to

measure, monitor and manage its water resources.

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Supporting Information

Additional Supporting Information may be found in the

online version of this article:

Table S1. Definitions of parameters used in the linear

models.

Table S2. Linear models describing 0+ CPUE for the

four target species and total CPUE, in the short-term

after watering (T1, T2, n = 52) and the end-of-season

(T1, Tapril, n = 48).

Figure S1. Total fish catch-per-unit effort (CPUE) for the

three sampling periods (T1, T2, and Tapril) for each wet-

land watering event.

(Manuscript accepted 3 June 2014)



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