Spatial dissimilarities in plankton structure and function during flood pulses in a semi-arid floodplain wetland system

PRIMARY RESEARCH PAPER

Spatial dissimilarities in plankton structure and functionduring flood pulses in a semi-arid floodplain wetland system

Tsuyoshi Kobayashi • Timothy J. Ralph •

Darren S. Ryder • Simon J. Hunter •

Russell J. Shiel • Hendrik Segers

Received: 20 August 2014 / Revised: 5 November 2014 / Accepted: 10 November 2014 / Published online: 19 November 2014

� Springer International Publishing Switzerland 2014

Abstract Floodplain wetlands in semi-arid regions

have intricate channel-floodplain networks with

highly variable and unpredictable wet and dry phases

related to changes in hydrology and geomorphology.

We tested the hypothesis that the presence of different

hydro-geomorphic habitats in those systems drives

structural and functional differences in aquatic com-

munities. To test this hypothesis, we examined the

densities and species composition (structural vari-

ables), and primary productivity and respiration

(functional variables) of plankton communities, and

water chemistry in three spatially explicit channel,

floodout and lagoon habitat types inundated by

environmental water releases in the Macquarie

Marshes, semi-arid Australia. Significant differences

were recorded among the community-level structural

and functional variables among the three habitats.

Greater densities of phytoplankton, zooplankton and

planktonic bacteria were observed in a hydrologically

isolated floodplain lagoon. The lagoon habitat also had

greater primary productivity of phytoplankton and

planktonic respiration compared with the channel and

floodout. Our results suggest that water release to meet

environmental flow requirements can be an important

driver of planktonic diversity and functional responses

in semi-arid wetland systems by inundating diverse,

hydro-geomorphically distinct habitats.

Keywords Environmental water � Zooplankton �Phytoplankton � Bacterioplankton � Primary

production � Respiration

Introduction

Habitat heterogeneity can delimit the structure and

functioning (hence pattern and process) of a biological

community (Wellborn et al., 1996; Southwood, 1977;

Ward et al., 2002; Ryder & Miller, 2005). The

structure of boundaries that delineate habitats depends

on the complexity, connectivity and history of

Handling editor: Stuart Anthony Halse

T. Kobayashi (&) � S. J. Hunter

Science Division, Office of Environment and Heritage

NSW, P.O. Box A290, Sydney South, NSW 1232,

Australia

e-mail: [email protected]

T. J. Ralph

Department of Environment and Geography, Macquarie

University, Sydney, NSW 2109, Australia

D. S. Ryder

Ecosystem Management, University of New England,

Armidale, NSW 2351, Australia

R. J. Shiel

Ecology and Evolutionary Biology, University

of Adelaide, Adelaide, SA 5005, Australia

H. Segers

Royal Belgian Institute of Natural Sciences, Freshwater

Biology, Vautierstraat 29, 1000 Brussels, Belgium

123

Hydrobiologia (2015) 747:19–31

DOI 10.1007/s10750-014-2119-7

ecosystems characteristics (Jenkins & Boulton, 2003;

Cadenasso et al., 2006; Yarrow & Marı́n, 2007).

Floodplain wetlands in semi-arid regions provide an

example of ecosystems, where habitat extent and

availability are spatially complex and temporally

dynamic. They have intricate channel-floodplain net-

works with variable and unpredictable wet and dry

phases related to changes in hydrology and geomor-

phology (e.g. Shiel et al., 2006; Ralph & Hesse, 2010;

Ralph et al., 2011; Baldwin et al., 2013a). As such,

floodplain wetlands in a spatially complex and tem-

porally dynamic landscape provide a diversity of

hydro-geomorphic habitats for biota that occupy

ecological niches created and maintained by river

flows and floods (Bayley, 1991; Bunn et al., 2006;

Rogers & Ralph, 2011).

Diverse terrestrial and aquatic organisms of varying

body sizes, survival and dispersal strategies and life

cycles occur in these dynamic wetland ecosystems

(e.g. Humphries et al., 1999; Brock et al., 2003;

Jenkins & Boulton, 2003; Iles et al., 2010; Wassens

et al., 2010; Ning & Nielsen, 2011; Baldwin et al.,

2013b). Environmental water releases are a key

management strategy implemented to address the

ecological needs of river-floodplain environments

(Davies et al., 2014), and often have the aim of

restoring structurally and functionally diverse aquatic

communities (Ryder et al., 2008; Meitzen et al., 2013).

During dry phases, eggs of diapausing animals such as

zooplankton remain in dry floodplain soils (Kobayashi

et al., 2009; Ning & Nielsen, 2011), with microbial

decomposition of organic matter adding nutrients and

energy to floodplain soils. When flooding triggers the

next aquatic phase, this conditioned organic reservoir

supports emerging heterotrophic aquatic biota (Ko-

bayashi et al., 2013) that assimilate these resources

into aquatic higher trophic levels (Bunn et al., 2006).

Plankton are clearly a vital component of the boom

and bust cycle in floodplain wetlands, responding

rapidly to changes in habitat conditions, forming an

important source and sink of carbon (Dodson & Lillie,

2001; James et al., 2008; Kobayashi et al., 2009;

Davidson et al., 2012; Kobayashi et al., 2013), and are

recognised as an indicator that can be used to assess

the ecological response of floodplain wetlands to

inundation (Jenkins et al., 2009). The temporal

dynamics of inundation are known to drive large-

scale ecological responses in floodplain wetland

systems (Bayley, 1995), yet small-scale habitat

heterogeneity as a driver of the ecological structure

and functioning of these habitats is poorly documented

(Lindholm et al., 2007; Kobayashi et al., 2013).

We hypothesised that the presence of different

hydro-geomorphic habitats contributes to structural

and functional differences in aquatic communities in

inland floodplain wetlands. To test the hypothesis, we

examined the structural variables (densities and spe-

cies composition) and the functional variables (pri-

mary productivity and respiration) of plankton

communities, and the abiotic conditions in three

spatially explicit habitats during flood pulses created

by environmental water releases in the Macquarie

Marshes, an inland floodplain wetland in semi-arid

Australia. The three habitats were ‘channel’, ‘flood-

plain floodout’ and ‘floodplain lagoon’. The channel

habitat is a section of a parent river system such as a

trunk stream or distributary channel that facilitates

flow throughout the floodplain. The floodplain floodout

habitat is a regularly inundated part of the floodplain

that is hydrologically connected to a channel by

overbank and sheet flow at the shallow, terminal end

of a channel (hence, it receives flow when the channel

receives flow). The floodplain lagoon habitat is a

floodplain depression that is hydrologically connected

and inundated by lateral-overbank flow from a channel,

but is hydrologically isolated from the channel once

flow pulses cease. These aquatic habitats are delineated

hydrologically and geomorphologically. The spatial

extent of these habitats, their connectivity and the

length of the wet phase is highly variable and will drive

the ecological structure and functioning of the wetland

environments (Tockner et al., 1999; Bunn et al., 2006).

Study areas and study sites

The Macquarie Marshes (total area: *210,000 ha) are

located in the north-west of the Macquarie River

catchment in south-eastern Australia (see Fig. 1 in

Kobayashi et al., 2009 for catchment details). Around

19,850 ha of the wetlands are managed as Nature

Reserve and recognised under multiple international

and national conservation agreements (Keith, 2004).

The flow of the Macquarie River is regulated by

Burrendong Dam (storage capacity: 1,188 9 109 l) on

the Macquarie River near Wellington, constructed in

1967, and by Windamere Dam (storage capacity:

368 9 109 l) on the Cudgegong River near Mudgee,

constructed in 1984.

20 Hydrobiologia (2015) 747:19–31

123

Prior to the present study, the Macquarie Marshes

received environmental water releases as multi-modal

flood pulses between December 2007 and March

2008, with a peak flow rate of *2300 9 106 l day-1

over Marebone weir (31�2105500S, 147�4200040E) in the

Macquarie Marshes (Fig. 1). During a receding flood-

pulse phase of 9–11 February 2008, we sampled five

spatially independent locations representing three

habitats, demarcated by differing hydro-geomorphic

characteristics: channel habitats (two locations: C-1

and C-2), floodplain floodout habitats (two locations:

FF-1 and FF-2) and one floodplain lagoon habitat (FL)

along Monkeygar Creek in the southern Macquarie

Marshes (Fig. 2). The problem of obtaining genuine

replicates in spatially connected systems such as rivers

are difficult when the hypotheses aim to test ecological

processes predicted to change along environmental

gradients (Oksanen, 2001). Following Oksanen

(2001), we have treated each floodplain channel and

floodplain floodout habitat as independent, as the

hypotheses being tested relate to indicators that are

responsive within small-scale (hydro-geomorphic

unit) environmental gradients (see also O’Neill et al.,

1986).

Floodplain lagoons are a threatened geomorphic

habitat in the Southern Macquarie Marshes, and

during the last 100 years many have been channelized

due to avulsion and channel incision, for example,

Monkeygar Creek, which now has just one regularly

inundated lagoon (Ralph et al., 2011). As a result of

channel incision, very few lagoons are inundated by

environmental flows. Within each of the five locations,

five spatially independent sites were established for

sampling of biotic and abiotic variables. The location

of sampling sites and the timing of sampling at the

three spatially explicit habitats were largely deter-

mined by access to the wetlands.

The channel and floodplain floodout habitats sup-

ported extensive areas of aquatic vegetation domi-

nated by Common Reed (Phragmites australis (Cav.)

Trin. Ex Steud.), Cumbungi (Typha spp.), Water

Couch (Paspalum distichum L.) and Rushes (Juncus

spp.), whereas the floodplain lagoon habitat was

fringed with River Red Gum (Eucalyptus camaldul-

ensis Dehnh.) and Lignum (Duma florulenta (Meisn.)

T.M. Schust.), with unidentified emergent narrow-

leaved grasses within the flooded area (OEH, 2012).

All five habitats were dry before the delivery of

environmental water, with water depth ranging from

*20 to 40 cm at the sampling sites during the study.

Biotic variables

At each site, a single depth-integrated water sample

was collected from zero to 10 cm depth by submerg-

ing a plastic bottle (120 ml in volume) (n = 25 in

total). For each sample, a 100-ml subsample was

preserved in a 5% v/v Lugol’s iodine solution. In the

laboratory, each preserved sample was poured into a

graduated cylinder and was given a minimum of

14 days to allow the sedimentation of phytoplankton.

The supernatant was then syphoned out to concentrate

the sample by a factor of 10. Phytoplankton were

identified and counted in a Lund cell (Lund, 1959)

with a compound microscope at a magnification of

1009 to 4009; difficult-to-assess taxa were identified

at a magnification of 1,0009. Identification of phyto-

plankton was conducted by referring to the relevant

taxonomic literature (e.g. John et al., 2002). Phyto-

plankton densities were expressed as cells ml-1.

For zooplankton, a single depth-integrated water

sample (10 l each) was collected from the surface to

5 cm above the sediment at each site by submerging a

12-L plastic container (n = 25 in total). Zooplankton

samples were concentrated by filtering through a

35-lm mesh sieve to retain microzooplankton such as

rotifers (Likens & Gilbert, 1970). The concentrated

zooplankton samples were preserved in a 70% ethanol

solution. A wide-mouth automatic pipette and Sedge-

wick-Rafter counting cell were used for subsampling

and counting of zooplankton. Zooplankton specimens

were examined and identified under a Leica Diaplan

compound microscope at a magnification of 1009 to

0

500

1000

1500

2000

2500

1/12/2007 31/12/2007 30/1/2008 29/2/2008 30/3/2008

Flow

rate

(106 L

day

-1)

sampling period

Fig. 1 Mean daily flow rate past Marebone weir between

December 2007 and January 2008. The sampling period (9–11

February 2008) is indicated by vertical broken lines

Hydrobiologia (2015) 747:19–31 21

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3209, with an image analysis system consisting of

Leica DFC480 digital camera and Leica IM Version

4.0 digital imaging software (Leica Microsystems,

Germany). The main taxonomic literature used

included Koste & Shiel (1987), Segers (1995) and

Sinev et al. (2005). Counts included all zooplankton,

except protozoans for which only testate amoebae and

ciliates were counted. Zooplankton densities were

expressed as individual numbers per litre (indi. l-1).

In addition, a single sample of planktonic bacteria

(10 ml each) were collected at each site by submerg-

ing a sterilised 10-ml plastic tube (depth integrated

from zero to 10 cm depth) (n = 25 in total). Each

sample was preserved with a filtered formaldehyde

solution (2% v/v final concentration) and stored at 4�C

in the dark (Hobbie et al., 1977). For the bacteria cell

counts, a 1–2 ml subsample was drawn onto a 0.2-lm

black polycarbonate filter (25 mm in diameter) in the

laboratory. Bacteria cells were stained using DAPI

(406-diamindion-2-phenylindole) for a minimum of

15 min (Porter & Feig, 1980). Excess water was

withdrawn under low vacuum pressure (\150 mbar).

A cellulose acetate filter (pore size: 0.45 lm) was

placed between the black polycarbonate filter and the

filter holder as a backing to obtain an even vacuum

(Hawley & Whitton, 1991). The black polycarbonate

filter was then mounted on a glass slide, with a drop of

non-fluorescence immersion oil placed on top of the

Fig. 2 Sampling area and locations of two channel (C-1 and C-2), two floodplain floodout (FF-1 and FF-2) and one floodplain lagoon

(FL) habitats of Monkeygar Creek in the southern Macquarie Marshes

22 Hydrobiologia (2015) 747:19–31

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filter before gently affixing a cover slip. Total bacteria

cell counts were carried out using a fluorescence-

equipped Leica Diaplan compound microscope

(Leica, Germany) at 10009 under ultra-violet light

excitation (excitation filter: BP 340–380 nm). A field

view image of the microscope was projected to a

computer screen using a Leica DFC 480 digital camera

attached to the microscope and Leica Image Manager

(IM) Version 4.0 image analysis software (Leica

Microsystems, Germany). A minimum of 300 cells or

a maximum of 20 screen view images were counted,

permitting the minimum detection of 40 cells ml-1

per sample.

Primary productivity of phytoplankton

and planktonic respiration

Gross primary productivity (GPP, mg C l-1 day-1) of

phytoplankton and planktonic respiration (PR,

mg C l-1 day-1) was estimated from dissolved oxy-

gen concentrations in biological oxygen demand

(BOD) bottles (300 ml volume) measured in situ at

the beginning and the end of light and dark bottle

incubations (Wetzel & Likens, 1991). A single light

and dark bottles were placed at each site (n = 25 in

total). Each bottle was rinsed and filled with sample

water without air bubbles (Wetzel & Likens, 1991),

and incubated at 20–25 cm depth for *24 h. The

daily GPP and PR were estimated for each sample

based on the formulae in Wetzel and Likens (1991,

p. 210).

Abiotic variables

In the field, water temperature (WT, �C) and dissolved

oxygen (DO, mg l-1) were measured using an YSI

Model 5100 Dissolved Oxygen/Temperature Meter

(YSI Inc., Ohio, USA) between 11:30 and 13:00 h

throughout the study. A single depth-integrated water

sample from zero to 5 cm above the sediment (each

*5 l in volume) was collected at each site by

submersing a plastic container (12 l in volume;

n = 25 in total) for measurements of conductivity

(COND, lS cm-1) (ORION Model 160 conductivity

meter, Orion Research Inc., Massachusetts, USA) and

turbidity (TURB, NTU) (HACH 2100ABN turbidim-

eter, Hach Company, Colorado, USA), and for anal-

yses of total nitrogen (TN, mg l-1), dissolved

inorganic nitrogen (DIN, mg l-1), total dissolved

nitrogen (TDN, mg l-1), total phosphorus (TP,

mg l-1), dissolved inorganic phosphorus (DIP,

mg l-1), total dissolved phosphorus (TDP, mg l-1),

dissolved silica (DS, mg l-1) and dissolved organic

carbon (DOC, mg l-1) in the laboratory. The water

samples for DIN, TDN, DIP, TDP, DS and DOC were

immediately filtered through a filter (pore size:

0.45 lm) and were stored at -20�C until they were

analysed. Nutrient analysis methods followed Hosomi

and Sudo (1986) and Eaton et al. (2005). In the present

study, dissolved organic nitrogen (DON) was approx-

imated as the difference between TDN and DIN.

Dissolved organic phosphorus (DOP) was approxi-

mated as the difference between TDP and DIP

(Baldwin, 2013).

Statistical analyses

Principal component analysis (PCA) with a correlation

bi-plot was used to examine the relative similarities (or

dissimilarities) among the C, FF and FL habitats based

on Pearson’s correlation matrices for five measured

biotic variables that characterised community-level

structure and functioning and 12 abiotic variables

(Table 1). Prior to analysis, all data were transformed

by log10(x), or log10(x ? 1) if a variable contained

zero values, to stabilise the variance and meet the

assumptions of normality and linearity. The Jolliffe

cut-off value was used as an indication of how many

PCs should be considered significant (Jolliffe, 1986).

In addition, we used non-metric multidimensional

scaling (nMDS) followed by analysis of similarity

(ANOSIM) to examine the compositional similarities

(or dissimilarities) of the phytoplankton and zoo-

plankton communities among samples, using the

Horn’s overlap measure (Horn, 1966; Jost et al.,

2011), followed by the similarity percentage (SIM-

PER) method (Clarke, 1993). The SIMPER method

can identify the species primarily contributing to

significant differences between distinct groups of

samples, by estimating the contribution of dissimilar-

ity of a species as a proportion (%) of overall average

dissimilarity between groups. Pairwise comparisons of

mean densities of phytoplankton and zooplankton taxa

among the three habitats required a Bonferroni-

adjusted significance level of P = 0.05/3. PAST

(PAleontological STatistics) statistical computer soft-

ware version 2.15 (Hammer et al., 2001) was used for

all the statistical analyses.

Hydrobiologia (2015) 747:19–31 23

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Results

Plankton density

The mean density of phytoplankton ranged from

3.4 9 103 to 196.8 9 103 cells ml-1 among the five

habitat locations (Table 1). The mean density of

zooplankton ranged from 1.2 9 102 to 537.0 9 102

indi. l-1. The mean density of planktonic bacteria

varied three-fold among locations (3.55 9 106 to

11.51 9 106 cells ml-1). The greatest mean densities

of phytoplankton, zooplankton and planktonic bacte-

ria were all observed at the FL habitat and the

minimum at the FF habitat. A total of 64 taxa of

phytoplankton and 70 taxa of zooplankton were

recorded in the present study. Of them, 37 taxa of

phytoplankton and 27 taxa of zooplankton were

dominant (Tables 2, 3: dominant taxa defined as those

with a mean density of C100 cells ml-1 for phyto-

plankton and C10 indi. l-1 for zooplankton at any one

habitat location).

Primary productivity of phytoplankton

and planktonic respiration

The mean GPP ranged from 0.51 to 6.34 mg C l-1 -

day-1 among the five habitat locations (Table 1). The

mean PR ranged from 0.47 to 4.57 mg C l-1 day-1.

The mean GPP:PR ratio (1.2–3.6) varied three-fold

among locations. The greatest mean GPP and PR

Table 1 Summary statistics for biotic and abiotic variables of channel (C1 and C2), floodplain floodout (FF1 and FF2) and

floodplain lagoon (FL) sites of Monkeygar Creek in the southern Macquarie Marshes during February 2008 (flood-pulse period)

C 1 C 2 FF 1 FF 2 FL

Biotic variables

Density of phytoplankton

(9103 cells ml-1)

8.7 ± 0.7 10.2 ± 0.5 5.2 ± 0.5 3.4 ± 0.5 196.8 ± 34.6

Density of zooplankton (indi. l-1) 341.4 ± 20.0 757.8 ± 125.0 118.2 ± 22.5 882.2 ± 116.0 53702.7 ± 5218.6

Density of planktonic bacteria

(9106 cells ml-1)

6.10 ± 0.28 5.48 ± 0.12 3.55 ± 0.26 8.36 ± 0.90 11.51 ± 1.64

Gross primary productivity of

phytoplankton (GPP,

mg C l-1 day-1)

1.64 ± 0.04 2.23 ± 0.15 0.62 ± 0.10 0.51 ± 0.09 6.34 ± 0.67

Planktonic respiration (PR,

mg C l-1 day-1)

0.48 ± 0.004 0.63 ± 0.06 0.47 ± 0.12 0.60 ± 0.20 4.57 ± 0.44

Abiotic variables

Water temperature (WT, �C) 26.7 ± 0.11 24.1 ± 0.14 27.9 ± 0.51 23.2 ± 1.11 27.2 ± 0.19

Dissolved oxygen (DO, mg l-1) 5.6 ± 0.05 3.1 ± 0.14 7.8 ± 0.50 3.4 ± 0.41 18.2 ± 0.69

Conductivity (COND, lS cm-1) 531.8 ± 0.9 474.2 ± 1.0 311.0 ± 2.2 289.6 ± 18.1 457.8 ± 2.6

Turbidity (TURB, NTU) 28.1 ± 0.56 23.7 ± .90 1.8 ± 0.07 3.2 ± 0.23 42.1 ± 0.62

Dissolved inorganic nitrogen (DIN,

mg l-1)

0.018 ± 0.0065 0.012 ± 0.0016 0.023 ± 0.0017 0.017 ± 0.008 0.032 ± 0.002

Dissolved inorganic phosphorus (DIP,

mg l-1)

0.026 ± 0.0006 0.028 ± 0.0011 0.014 ± 0.0013 0.020 ± 0.0016 0.030 ± 0.0023

Dissolved silica (DS, mg l-1) 4.14 ± 0.054 2.66 ± 0.032 3.77 ± 0.079 2.51 ± 0.082 0.27 ± 0.033

Dissolved organic nitrogen (DON,

mg l-1)

1.14 ± 0.011 0.88 ± 0.004 1.33 ± 0.056 1.34 ± 0.085 2.93 ± 0.23

Dissolved organic phosphorus (DOP,

mg l-1)

0.024 ± 0.0013 0.018 ± 0.0014 0.037 ± 0.0013 0.037 ± 0.0073 0.159 ± 0.010

Dissolved organic carbon (DOC,

mg l-1)

4.34 ± 0.21 2.84 ± 0.26 7.00 ± 0.78 3.78 ± 0.04 10.05 ± 1.31

Total nitrogen (TN, mg l-1) 1.56 ± 0.026 1.35 ± 0.065 1.59 ± 0.064 1.42 ± 0.11 6.40 ± 0.43

Total phosphorus (TP, mg l-1) 0.17 ± 0.007 0.18 ± 0.012 0.089 ± 0.005 0.112 ± 0.091 1.036 ± 0.075

Mean ± standard error (n = 5) are shown

24 Hydrobiologia (2015) 747:19–31

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Table 2 Dominant phytoplankton taxa and densities (cells ml-1) of channel (C-1 and C-2), floodplain floodout (FF-1 and FF-2) and

floodplain lagoon (FL) habitats of Monkeygar Creek in the Macquarie Marshes during February 2008

C-1 C-2 FF-1 FF-2 FL

Cyanophyta

Anabaena aphanizomenoides 959.6 ± 100.9 849.6 ± 117.0 2324.8 ± 123.7 1394.2 ± 203.7 2444.8 ± 911.9

Aphanocapsa spp. 0 67.6 ± 67.6 295.6 ± 243.1 56.4 ± 56.4 1428.6 ± 876.9

Limnothrix sp. 81.8 ± 36.7 286.2 ± 91.1 104.0 ± 57.7 26.0 ± 26.0 3592.6 ± 638.0

Merismopedia sp. 469.0 ± 146.5 36.0 ± 36.0 0 9.0 ± 9.0 8932.2 ± 2044.6

Planktothrix sp. 39.4 ± 49.4 35.2 ± 35.2 180.2 ± 64.0 0 149.0 ± 85.9

Romaria sp. 0 16.2 ± 10.7 0 0 983.2 ± 701.6

Chlorophyta

Actinastrum sp. 298.2 ± 35.2 301.8 ± 54.6 0 0 13162.6 ± 1674.6

Ankistrodesmus spp. 125.6 ± 16.7 164.4 ± 11.0 23.8 ± 7.2 19.2 ± 4.4 13872.6 ± 3247.3

Carteria sp. 0 0 0.8 ± 0.8 0 973.8 ± 517.8

Chlamydomonas spp. 212.6 ± 53.4 228.0 ± 60.0 5.8 ± 4.5 0.6 ± 0.6 2023.0 ± 372.4

Chlorogonium sp. 0 0 0 0 382.6 ± 209.7

Coelastrum sp. 0 49.4 ± 17.9 17.0 ± 13.2 34.6 ± 10.6 2474.0 ± 2389.5

Crucigenia sp. 180.8 ± 12.3 379.0 ± 36.6 54.2 ± 33.8 185.0 ± 36.6 8109.8 ± 1087.8

Dictyosphaerium sp. 111.8 ± 66.3 967.8 ± 99.8 16.8 ± 10.3 0 42375.2 ± 12897.6

Eudorina sp. 60.2 ± 60.2 93.6 ± 12.9 0 0 224.4 ± 173.5

Golenkiniopsis sp. 3.8 ± 3.8 0 0 0 300.8 ± 105.7

Kirchneriella sp. 54.6 ± 23.2 49.6 ± 5.8 12.4 ± 8.4 46.2 ± 8.2 9159.4 ± 3935.0

Micractinium sp. 90.2 ± 42.8 68.4 ± 41.7 0 0 15923.2 ± 1760.6

Mougeotia sp. 0 7.8 ± 5.5 61.0 ± 42.9 164.0 ± 79.4 0

Pandrina sp. 284.2 ± 53.2 79.4 ± 33.1 2.2 ± 2.2 8.8 ± 5.6 2571.8 ± 724.4

Pediastrum cf. boryanum 108.6 ± 37.5 82.2 ± 38.4 0 5.6 ± 5.6 327.0 ± 95.2

Scenedesmus spp. 585.0 ± 100.4 503.0 ± 56.9 332.8 ± 123.6 524.6 ± 115.3 14101.0 ± 2578.8

Spermatozopsis exultans 23.4 ± 9.7 13.6 ± 8.3 1.2 ± 1.2 4.6 ± 4.6 1466.4 ± 902.4

Sphaerocystis sp. 18.0 ± 18.0 0 2.2 ± 2.2 26.0 ± 26.0 180.4 ± 180.4

Tetraedron sp. 20.8 ± 10.8 14.4 ± 3.7 0 1.2 ± 1.2 1428.8 ± 784.9

Tetrastrum sp. 0 0 0 0 4976.8 ± 1316.1

Chrysophyta

Diceras sp. 2.2 ± 2.2 0 0 0 338.4 ± 338.4

Cryptophyta

Chroomonas sp. 351.8 ± 14.3 277.6 ± 49.4 49.6 ± 8.6 76.4 ± 15.4 6132.6 ± 3144.6

Cryptomonas cf. erosa 546.6 ± 91.2 466.8 ± 90.1 264.4 ± 71.8 58.6 ± 9.9 2522.8 ± 394.0

Dinophyta

Peridinium sp. 8.8 ± 4.5 9.2 ± 2.8 1.4 ± 0.7 0 352.2 ± 41.5

Euglenophyta

Euglena spp. 280.4 ± 28.8 212.8 ± 45.3 10.8 ± 1.7 12.0 ± 2.8 475.0 ± 48.4

Trachelomonas sp. 315.2 ± 72.2 498.2 ± 57.4 77.0 ± 34.2 159.8 ± 56.6 11903.4 ± 1477.4

Bacillariophyta

Aulacoseira distans 206.6 ± 60.1 196.2 ± 26.0 0 1.2 ± 1.2 0

Aulacoseira granulata 1541.0 ± 109.3 1390.0 ± 100.1 1.4 ± 1.4 0 89.6 ± 89.6

Cyclotella spp. 971.8 ± 184.0 1692.4 ± 127.5 88.4 ± 57.4 127.6 ± 33.7 21082.6 ± 2577.1

Nitzschia spp. 462.2 ± 93.4 749.2 ± 114.3 1016.0 ± 280.4 319.8 ± 89.0 1981.4 ± 507.3

Pinnularia sp. 0 0 3.2 ± 1.4 0 112.8 ± 112.8

Mean ± standard error (n = 5) are shown. Dominant taxa are those with a mean density of C100 cells ml-1 at any one habitat

location

Hydrobiologia (2015) 747:19–31 25

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values were both observed at the FL habitat. The

relatively high mean GPP:PR ratio ([3) was observed

at the two C locations.

Abiotic variables

The results were summarised for each of the five

habitat locations (Table 1). The mean values of DO

(range 3.1–18.2 mg l-1), TURB (3.2–42.1 NTU), DS

(0.27–4.14 mg l-1), DOP (0.018–0.16 mg l-1) and

TP (0.089–1.04 mg l-1) varied six to 23-fold among

locations. The mean values of WT (23.2–27.2�C) and

COND (289.6–474.2 lS cm-1) varied less than two-

fold among locations. The high DO concentration of

18.2 mg l-1 was a result of the high phytoplankton

density of 196.8 9 103 cells ml-1 in the FL habitat.

Habitat structural and functional (dis)similarity

The PCA with a correlation bi-plot projected the close

grouping of the five replicate sites within each location

and each habitat (C, FF and FL) onto a two-

Table 3 Dominant zooplankton taxa and densities (indi. l-1) of channel (C-1 and C-2), floodplain floodout (FF-1 and FF-2) and

floodplain lagoon (FL) habitats of Monkeygar Creek in the Macquarie Marshes during February 2008

C-1 C-2 FF-1 FF-2 FL

Protists

Arcella spp. 26.8 ± 6.8 14.6 ± 3.2 2.7 ± 0.4 69.3 ± 23.8 0.7 ± 0.7

Centropyxis spp. 0.4 ± 0.2 0.5 ± 0.4 1.9 ± 0.4 70.7 ± 20.1 1.8 ± 1.2

Difflugia spp. 41.8 ± 8.1 48.6 ± 20.0 2.3 ± 0.3 143.9 ± 32.4 8.1 ± 5.2

Euglypha spp. 0 0.5 ± 0.5 8.5 ± 1.5 27.9 ± 12.1 0

Ciliates 0 0 6.3 ± 1.1 96.2 ± 23.6 12.2 ± 5.0

Rotifers

Brachionus angularis 103.5 ± 11.8 218.7 ± 30.1 0 0 36853.7 ± 3738.5

Brachionus budapestinesis 4.8 ± 1.9 76.1 ± 17.1 0 46.4 ± 46.4 718.3 ± 134.5

Brachionus calyciflorus 0.2 ± 0.2 0 0 0 3310.2 ± 1670.2

Brachionus calyciflorus amphiceros 68.5 ± 7.4 199.4 ± 35.2 0 0 0.7 ± 0.7

Brachionus dichotomus reductus 0 0 0 0 11.3 ± 2.8

Brachionus quadridentatus brevispinus 0.4 ± 0.2 1.1 ± 0.3 0 0 54.0 ± 39.8

Epiphanes cf. spinosa 0 0 0 0 197.1 ± 67.1

Filinia pejleri 2.2 ± 1.2 4.9 ± 1.6 0 0 572.3 ± 158.7

Filinia saltator 1.5 ± 0.6 1.4 ± 0.6 0 0 2946.2 ± 993.1

Itura aurita 13.7 ± 2.6 10.1 ± 2.0 7.3 ± 1.9 29.0 ± 3.7 1.8 ± 1.2

Lecane bulla 14.0 ± 1.8 14.0 ± 2.0 23.5 ± 6.1 198.7 ± 40.6 27.9 ± 11.2

Lecane curvicornis 0 0.7 ± 0.5 12.7 ± 4.8 16.5 ± 2.6 0

Lecane luna 0 1.1 ± 0.9 2.2 ± 0.6 12.2 ± 4.5 27.7 ± 7.8

Lecane lunaris 0 0 1.8 ± 0.7 29.64 ± 6.0 0

Lecane papuana 20.9 ± 2.4 38.7 ± 12.4 5.2 ± 1.3 0.7 ± 0.4 65.0 ± 19.0

Lepadella triptera 4.5 ± 1.5 0.2 ± 0.2 0.6 ± 0.3 11.9 ± 4.1 0.6 ± 0.6

Polyarthra dolichoptera 4.1 ± 0.8 30.6 ± 10.7 0.1 ± 0.1 3.7 ± 1.6 301.3 ± 77.2

Proalides tentaculatus 0 2.0 ± 0.7 0 0 125.1 ± 28.4

Trichocerca pusilla 1.7 ± 0.8 2.9 ± 0.8 0 0.4 ± 0.4 31.9 ± 7.7

Cladocerans

Moina cf. micrura 0 0 0.1 ± 0.1 0 14.2 ± 4.5

Copepods

Nauplii 15.7 ± 1.5 76.9 ± 17.4 25.3 ± 13.1 67.1 ± 26.7 7930.1 ± 2314.9

Cyclopoid copepodites 0 1.3 ± 0.6 1.0 ± 0.4 16.4 ± 3.1 450.0 ± 96.3

Mean ± standard error (n = 5) are shown. Dominant taxa are those with a mean density of C10 indi. l-1 at any one habitat location

26 Hydrobiologia (2015) 747:19–31

123

dimensional plane (Fig. 3). The first two PCs with an

eigenvalue of [0.7 (Jolliffe cut-off value) explained

[80% of total variance. The first PC alone explained

62.7% of variance and separated the FL (correlated

with increased total nutrients, plankton densities, GPP

and PR) from the C and FF habitats. The second PC

explained 21.0% of variance and separated the C and

FF habitats.

Compositional (dis)similarities of phytoplankton

and zooplankton between habitats

Three distinct habitat groups (C, FF and FL) were

indicated by nMDS ordination (stress = 0.01), based

on Horn’s similarity measure for the dominant 37 taxa

of phytoplankton and 27 taxa of zooplankton

(Tables 2, 3). A one-way ANOSIM indicated a

significant dissimilarity between each habitat (Global

R = 0.99, P \ 0.0001; Bonferroni-corrected P B

0.0027 for pairwise comparisons). The SIMPER

analysis showed the taxa contributing [5% of com-

positional dissimilarity between the C and FF habitats

were Aulacoseira granulata (31.1%), Cyclotella spp.

(24.6%), Anabaena aphanizomenoides (18.3%) and

Dictyosphaerium sp. (7.0%); between the FF and FL

habitats Dictyosphaerium sp. (54.7%), Cyclotella spp.

(10.4%), Microcatinium sp. (5.9%) and Ankistrodes-

mus spp. (5.2%); and similarly between the FL and C

habitats Dictyosphaerium sp. (55.3%), Cyclotella spp.

(9.5%), Microcatinium sp. (6.0%) and Ankistrodesmus

spp. (5.3%). For the zooplankton community, the taxa

that had contributed to[5% of compositional dissim-

ilarity between the C and FF habitats were Brachionus

angularis (28.1%), B. calyciflorus amphiceros

(22.2%), Lecane bulla (18.3%), Difflugia spp.

(7.9%), B. budapestinensis (6.3%) and unidentified

ciliates (5.1%); between the FF and FL habitats

B. angularis (92.2%) and nauplii (5.5%); and between

the FL and C habitats B. angularis (92.1%) and nauplii

(5.5%).

Discussion

The hydro-geomorphic characteristics of channels,

floodplain floodout and floodplain lagoon habitats

appear to be important drivers of structural and

functional differences in planktonic communities in

semi-arid floodplain wetlands. Changes in the

structure of plankton communities with habitat-dis-

tinct abiotic conditions have been reported from other

river-floodplain systems. For example, concentrations

of nutrients and suspended particles differed, and

phytoplankton abundance in channel and floodplain

habitats varied with hydrological connectivity during

flood pulses in the Danube River, Austria (Heiler et al.,

1995). In the Sacramento River, USA, phytoplankton

abundance was higher in floodplain habitats than in

channel habitats (Sommer et al., 2004). Also, zoo-

plankton community structure varied spatially

between floodplain lakes reconnected with the river

channel in the Narran Lakes, Australia (James et al.,

2008), and those in ephemeral floodplain pools

differed from communities in hydrologically discon-

nected pools in the upper Murray River in Victoria,

Australia (Shiel et al., 1998). In the present study, we

found not only changes in structure of plankton

communities but also consistent differences in func-

tional variables (GPP and PR) among different hydro-

geomorphic habitats.

Several species of phytoplankton and zooplankton

showed patterns of occurrence that were strongly

related to the different habitats in the Macquarie

Marshes. Aulacoseira was abundant in the channel but

displaced by Dictyosphaerium in the floodplain flood-

out and floodplain lagoon where water flows diminish,

and hydraulic stability and residence time increase.

Aulacoseira is a relatively heavy chain-forming dia-

tom with a low surface-area-to-volume ratio, while

Dictyosphaerium is a buoyant colonial green alga with

a high surface-area-to-volume ratio (Reynolds, 1984).

Their spatial changes reflect hydraulic conditions of

the habitats. For zooplankton, the superabundance of

Brachionus angularis at the highly eutrophic flood-

plain lagoon fits with the finding that this rotifer is an

indicator of eutrophy in lentic systems (Pontin &

Langley, 1993). Similar responses have been reported

in other wetland systems based on taxonomic groups

including epiphytic diatoms and macroinvertebrates

(Davidson et al., 2012), and planktonic microbial

communities (Kobayashi et al., 2009, 2013). This

suggests that the inundation of distinct channel,

floodplain floodout and lagoon hydro-geomorphic

habitats in semi-arid regions is an important driver

for taxa-specific responses that contribute to local-

scale biodiversity (see also Nielsen et al., 2013).

Channel-floodplain networks have highly variable

and unpredictable wet and dry phases that can promote

Hydrobiologia (2015) 747:19–31 27

123

spatially distinct ecological responses (Jenkins &

Boulton, 2003; Iles et al., 2010; Baldwin et al.,

2013b). In the Macquarie Marshes, the hydrologically

isolated floodplain lagoon habitat (inundated by

lateral-overbank flow) was most distinct due to high

concentrations of dissolved inorganic and organic

matter, densities of phytoplankton and zooplankton

and rates of GPP and PR relative to the two other

habitats. Despite their geomorphic differences, the

channel and floodplain floodout habitats were more

similar to one another due to their greater longitudinal

hydrological connectivity, that is, where channelized

flow becomes overland flow in the wetland. In

comparison with other studies, the observed values

for the biotic and abiotic variables are similar to those

reported for other semi-arid river-floodplain systems

in Australia that experience flood pulses (Jenkins &

Boulton, 2003; James et al., 2008) and in other

regions, such as Europe (Heiler et al., 1995; Hein et al.,

2004) and Africa (Lindhom et al., 2007; Davidson

et al., 2012). However, concentrations of nutrients (N

and P) and GPP rates of phytoplankton in the

floodplain lagoon were higher than those reported

from flood-pulsed floodplains elsewhere (Lindhom

et al., 2007; James et al., 2008; Davidson et al., 2012),

suggesting that the floodplain lagoons in this system

play a disproportionate role in floodplain wetland

productivity.

In the present study, biotic and abiotic variables

were not measured over time due to logistical

restrictions. However, the duration, spatial extent

and hydrological connectivity of inundated habitats

would vary during flood pulses (Ward et al., 2002). It

is likely that time-related factors affect the structure

and function of plankton communities in different

habitats of inland floodplain wetlands. In river-flood-

plain systems in the northern hemisphere, water

quality and plankton community structure change

with hydrological connectivity and the duration of

water retention (Heiler et al., 1995; Baranyi et al.,

2002; Ahearn et al., 2006). In Australia, James et al.

(2008) reported the temporal effects on zooplankton

dynamics in inundated floodplain lakes. Shiel et al.

(2006) also found temporal variations in species

diversity and assemblages of zooplankton in arid river

systems. However, it was not possible to freely access

flooded areas in inland floodplain wetlands once they

were inundated due to their isolated and remote

location (see also Ahearn et al., 2006). Although there

were significant structural and functional differences

among hydro-geomorphic habitats, the lack of tem-

poral replication in the present study means that the

Fig. 3 Principal

component analysis (PCA)

with a correlation bi-plot

based on the community-

level plankton and abiotic

variables (Table 1). Half

filled square channel habitat

C-1; half filled triangle

channel habitat C-2; filled

square floodplain floodout

habitat FF-1; filled triangle

floodplain floodout habitat

FF-2; filled circle floodplain

lagoon habitat FL

28 Hydrobiologia (2015) 747:19–31

123

results need to be interpreted with caution inherent in

studies that lack temporal replication (Oksanen,

2001). Innovative sampling approaches and method-

ologies, such as constructing a platform in a channel or

on a floodplain, may be used to overcome such

limitations to measure ecological conditions over time

during flood pulses in inland floodplain wetlands with

restricted access during flow pulses.

Ecosystem processes are rarely compared among

small-scale features such as the hydro-geomorphic

habitats used in the present study (cf. Mulholland

et al., 2001). Our results suggest that rates of

planktonic GPP and PR are responsive to the inunda-

tion of distinct hydro-geomorphic habitats. The rates

of GPP and PR reported in the present study are

consistently higher in all three habitats than those

reported for planktonic communities in similar semi-

arid river systems; however, the pattern of increasing

GPP and PR with reduced flow rates from channel to

isolated floodplain lagoon habitats found in this study

mimics the pattern found within channel habitats of

semi-arid floodplain rivers experiencing reduced flows

(Oliver & Merrick, 2006; Gawne et al., 2007; Oliver &

Lorenz, 2007). In particular, very high rates of both

planktonic GPP and PR in the floodplain lagoon

habitat are comparable with rates reported for isolated

water holes in dryland river systems (Burford et al.,

2008; Kobayashi et al., 2011, 2013). Planktonic

processes clearly play a critical role in carbon cycling

and transformation in semi-arid floodplain wetlands.

Habitat-scale responses identified in the present study

demonstrate the importance of environmental water-

ing inundating all distinct hydro-geomorphic habitats

to maximise the diversity of planktonic functional

responses.

Environmental water has been released to inland

floodplain wetlands in Australia and elsewhere to

address the ecological needs for inundation of river-

floodplain environments (Arthington & Pusey, 2003;

Poff & Zimmerman, 2010). The present study has

identified the potential for the delivery of environ-

mental water to promote habitat heterogeneity, and

therefore structural and functional diversity in aquatic

biological communities in a spatially complex land-

scape. Biological communities with varying hydro-

logical needs may require specific environmental

watering strategies that consider biological and eco-

logical trade-offs (Moog et al., 1995; Hughes, 1997;

Poff & Zimmerman, 2010; Rogers & Ralph, 2011).

For example, based on the present results, environ-

mental watering regimes to maximise functional

responses (e.g. high GPP:PR ratio in channel habitat)

may lead to reduced local-scale planktonic abundance

and diversity by not inundating floodplain features.

Therefore, environmental watering strategies that seek

diverse ecological outcomes should include the inun-

dation of channel, floodplain floodout and lagoon

hydro-geomorphic habitats as an important driver of

structural and functional responses in semi-arid wet-

land systems.

Acknowledgements We thank Sarah Imgraben and Benjamin

Daly for help in field work. Thanks are due to Renee Shepherd,

Neil Saintilan, Sharon Bowen, Rachael Thomas and Tim

Pritchard for logistic support, Ed Czobik for analysing

nutrient samples, Marion Costigan (University of New

England) for analysing DOC samples, and Derek Cannon

(Phyto-ID) for conducting the identification and cell counts of

phytoplankton. We are grateful to Graeme Enders, Tim

Hosking, Louise Goggin and two anonymous reviewers for

incisive comments. This work was partly funded by the NSW

Wetland Recovery Program, which was jointly funded by the

NSW Government and the Australian Government’s Water

Smart Australia programme. The views and conclusions

expressed in this paper are those of the authors and do not

necessarily represent the official policies, either expressed or

implied, by the respective organisations.

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