Changes in zooplankton abundance and community … · Web viewKeywords – zooplankton, dissolved organic carbon, glucose, food webs, mesocosms Running Title – Zooplankton responses

Short term changes in zooplankton density and community structure in response to

different sources of dissolved organic carbon in an unconstrained lowland river:

evidence for food web support

Simon M. Mitrovic a,b*, Douglas P. Westhorpe a,b, Tsuyoshi Kobayashi c, Darren Baldwin d,

David Ryanb and James N. Hitchcock a

a University of Technology, Sydney, Centre for Environmental Sustainability, School of

Environment, Broadway, NSW, Australia

b New South Wales Office of Water, New South Wales, Australia

c Office of Environment and Heritage, Department of Premier and Cabinet, NSW, Australia

d CSIRO Land and Water and the Murray-Darling Freshwater Research Centre, La Trobe

University, Wodonga-Victoria, Australia.

* Corresponding author [email protected]

Keywords – zooplankton, dissolved organic carbon, glucose, food webs, mesocosms

Running Title – Zooplankton responses to dissolved organic carbon amendment

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Abstract

The zooplankton community changes that may occur with increases in concentration of

allochthonous dissolved organic carbon (DOC) are not well understood in unconstrained

lowland rivers. We examined in mesocoms over 8 days the short term responses of river

zooplankton to amendments of DOC from two different sources, glucose and leachates of a

common riparian tree (Eucalyptus camaldulensis; river red gum) both alone and with

inorganic nutrients added. DOC additions with and without nutrients increased heterotrophic

respiration and led to significant increases in bacterial biomass. These responses varied

between glucose and leachate addition. In treatments with added DOC, zooplankton density

significantly increased relative to controls. Some zooplankton genera only responded to the

leachate as a DOC source, and community structures significantly varied between the control

and the glucose and leachate amendments. Zooplankton are particularly important in lowland

river systems as they are key organisms for the transfer of carbon to higher trophic levels and

this study indicates allochthonous DOC has the potential to be an important basal resource to

lowland river food webs. This may be particularly important in lowland sections of

unconstrained flood plain rivers during and immediately following floods when allochthonous

DOC is more available.

Introduction

Dissolved organic carbon (DOC) in aquatic systems derives from two distinct sources;

autochthonous primary production within the system or allochthonous organic carbon

entering the system from watershed sources (Cole et al., 2002). When allochthonous sources

of DOC enter aquatic systems, bacterioplankton production may be de-coupled from its

dependence on autochthonous carbon and can greatly exceed that based solely on

autochthonous DOC production (Jansson et al., 2000) despite a smaller proportion of the

DOC being bioavailable (Wilcox et al., 2005). These external sources of allochthonous DOC

can mobilise new energy and may support the production of consumers such as zooplankton

via a food chain based on bacteria in the receiving waters such as lakes (Carpenter et al.,

2005) and streams (Hall Jr & Meyer, 1998).

The importance of allochthonous DOC in subsidising (sensu Polis et al., 1997) food webs is

becoming clearer in some aquatic ecosystems (e.g. Carpenter et al., 2005). For example it has

been suggested that allochthonous DOC as a basal resource accounts for up to 70% of the

carbon utilised by zooplankton (Cole et al., 2011). Zooplankton are particularly important, as

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they are a key organism for the transfer of carbon to higher trophic levels (Humphries et al.,

1999). Microzooplankton such as protozoans, rotifers and juvenile copepods are the major

planktonic consumers throughout the year in freshwater rivers (Kobayashi et al., 1998) and

many are consumers of bacteria, algae or both (Kobayashi et al., 1996). However, the role of

allochthonous sources of DOC in the structuring and/or subsidising of food webs in

unconstrained (floodplain) lowland rivers remains uncertain. In their key synthesis paper,

Thorp and Delong (2002) recognise that substantial loads of carbon can enter the channel in

unconstrained lowland rivers (the flood-pulse concept sensu Junk et al., 1989), but they

contend that most of this carbon is recalcitrant; and the fraction that is relatively bioavailable

is mostly limited to fuelling microbial activity with little or no leakage into the rest of the

metazoan aquatic food-web. They called this model of lowland river function “the revised

riverine productivity model” (Thorp & Delong, 2002). In support of their argument they cite

numerous studies, mostly based on stable isotope analysis, that show that carbon in higher

levels of the food webs in lowland rivers from across the globe is almost entirely derived from

autochthonous sources.

Many rivers of the Murray-Darling Basin become unconstrained floodplain rivers in their

lowland sections with large areas of lateral connectivity to floodplains during flood events.

Although Oliver and Merrick (Oliver & Merrick, 2006) showed that metabolised organic

carbon along a 1000 km reach of the Murray River was predominantly derived from

phytoplankton, that study was undertaken during a period of restricted river-floodplain

interactions. When substantial inundation of the Murray River floodplain did occur after over

a decade of drought, 2000 kms of the river and the lower reaches of its tributaries became

hypoxic (Whitworth et al., 2012); hypoxic conditions persisted for up to 6 months. The

principal driver of hypoxia was microbial metabolism of dissolved organic carbon (DOC)

leached from floodplain sources, mostly litter of the dominant riparian tree, the river red gum,

Eucalyptus camaldulensis (Baldwin, 1999). However, the question of whether or not the

DOC leached into the Murray River during the flood subsidised the riverine food web or

simply remained within the microbial loop was not established.

In order to explore the importance of DOC in subsidising and/or structuring riverine

zooplankton communities we undertook a mesocosm study examining the responses of the

planktonic food web (up to zooplankton) to amended DOC concentration with and without

added inorganic nutrients. We used two sources of DOC – a source more typical of DOC

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derived from floodwater (leachate from Eucalyptus camaldulensis) and for comparison, a

highly bioavailable source (glucose) which is commonly used as a carbon source in

mesocoms (e.g. Faithfull et al., 2012, Hitchcock et al., 2010). We hypothesised that DOC

amendment would increase both bacterial production and bacterioplankton biomass activity

and, that increases in the bacterioplankton would affect zooplankton density and community

structure. We also hypothesised that the different sources of DOC would lead to different

zooplankton communities, as different microbial communities may develop for the different

DOC sources with more complex carbon molecules in the leachate amendments.

Methods

Description of the study area and site

The Namoi catchment in the central north of New South Wales (NSW) is a region covering an

approximate area of 43 000 km2 and forms part of the large Murray-Darling Basin Drainage

System located in eastern Australia. The Namoi River feeds into the Barwon-Darling River,

the only major river system of this large, semi-arid region. Flows are mainly regulated by

Keepit Dam (storage capacity of 425 x 106 m3) and Split Rock Dam (storage capacity of 397 x

106 m3) on the Namoi River and from Chaffey Dam (capacity 62 x 106 m3) on the Peel River.

The study was performed at Boggabri along the Namoi River within the mid to lower

landform zones of the Namoi System (Fig. 1). It has an elevation of ~250 m above sea level

and average annual rainfall of 500-600 mm (DLWC, 2000). The dominant riparian tree

species in the lower catchment were native river red gums and exotic weeping willows (Salix

babylonica). Flooding events are generally the result of upper and mid catchment rain events

which are more common during the summer period.

Experimental design

The mesocosm experiment was performed between the 17th and 25th of April 2007 at

Boggabri on the Namoi River, NSW Australia (30o  40’ 05’’ S; 150 o   03’ 21’’ E) after an

extended period of low flows (>3 months). The experiment was performed using twenty 70 L

plastic mescosms (height 1 m, diameter 0.9 m). About 2000 L of experimental river water

was collected at Boggabri (Fig. 1) from a deep pool at a depth of about 0.3 m using a pump

and stored in a large container, and transported to the experimental facility near the river

within 1 hour of collection. The experimental water was added to each 70 L mesocosm by

hose pipe. Mesocosms were rinsed three times with river water prior to filling. The water in

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the tank was continuously mixed gently to ensure the random distributions of plankton

populations. After filling all twenty mesocosms, they were placed in a roofed, semi-sun area

and kept uncovered to ensure free gas exchange from the water surface. The community

structure of plankton in each mesocosm was similar to that in the river.

The mesocosms were filled in the morning of the 17th April (hereafter referred to as Day 0).

Similar to Karlsson et al. (2007) experiments ran over 8 days, with each of the five treatments

performed in quadruplicate and randomly assigned to mesocosms. Due to the warm water

temperature (approximately 20°C) and dominance by rotifers, we deemed this an appropriate

length of time to allow zooplankton to respond, while minimising possible enclosure effects

of longer experiments. Treatments were a control, amendment with glucose, amendment with

glucose and the inorganic nutrients phosphorus and nitrogen (hereafter glucose + nutrients),

amendment with red gum leachate and amendment with red gum leachate and nutrients

(hereafter red gum + nutrients). The ‘+ nutrients’ treatments were included because in lake

manipulation studies Carpenter et al., (2005) found that nutrient enrichment reduced the

importance of allochthonous carbon subsidies to zooplankton and fish.

A 20 g L-1 solution of carbon as glucose was prepared with distilled water using Sigma®

chemicals. A DOC stock solution of red gum leachate was prepared by soaking

approximately 500 g of E. camaldulensis leaves in approximately 1 L of distilled water for 72

hr at less than 5°C in a dark environment, thus minimising microbial utilisation of readily

bioavailable DOC (Hauer & Lamberti, 2011). Leachate solutions were then filtered using a

0.2 µm (polycarbonate membrane) filter to sterilise by removal of bacteria and other particles

(Hauer & Lamberti, 2011). The DOC concentration of these solutions was determined before

experiments to allow appropriate dilution for experiments. Glucose and red gum amendments

were added to increase DOC levels to approximately 20 mg L-1. This falls within the range of

DOC concentrations reported during high flow events within the mid to lower Namoi River

(Westhorpe & Mitrovic, 2013). Nitrogen was added as KNO3 (approximately 0.5 mg L-1) and

phosphorus as KH2PO4 (approximately 0.2 mg L-1).

Measurements of physico-chemical conditions

Dissolved oxygen was measured daily (at approximately 9 am) using a Hydrolab Surveyor

and MS5 sonde probe by placing the sonde 10 cm below the surface of each mesocosm prior

to any homogenisation. Water temperature, conductivity and pH were recorded on each

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occasion. The probe was rinsed with distilled water between readings to avoid any carry over

between mesocosms. After homogenisation through stirring with clean paddles, a single

sample per mesocosm (4 replicates for each treatment and control) was taken for 20cm below

the surface for all variables. Samples were taken for bacterial biomass (5 mL) on days 0, 1, 3,

6 and 8. Grab samples for chlorophyll a (200 mL), DOC (100 mL) and nutrients (20 mL)

were taken on days 0, 3, 6 and 8. DOC samples were pre-filtered in the field (0.45 µm

Sartorius Minisart filters - cellulose acetate membrane; Sartorius Stedim Biotech, Goettingen,

Germany) attached to disposable plastic syringes, acidified with hydrochloric acid and

refrigerated at 4oC. Samples were analysed in the laboratory by the High Temperature

Combustion Method (APHA, 1998). Nutrient samples were taken after filtration through 0.45

µm pore size syringe filters in pre-washed and sample rinsed PET bottles. Samples were

analysed for filterable reactive phosphorus (FRP) and oxidised nitrogen (NOx-N). The FRP

sub-samples were analysed using the ascorbic acid method and the NOx-N sub-samples were

analysed using an automated cadmium reduction method (APHA, 1998). Samples for

chlorophyll a determination were chilled in the dark until return to the laboratory within 5

hours. Samples were then filtered onto GF/C filters then frozen until subsequent

determination by Standard Methods (APHA, 1998) using the grinding technique and acetone

as a solute with correction for phaeophytin

Sampling and enumeration of bacterioplankton

Bacterioplankton samples (5 mL) were collected in sterile centrifuge tubes and fixed with 0.4

mL of concentrated 0.2 µm filtered formalin (37% Formaldehyde) and stored at 4 oC. In the

laboratory, subsamples (2 mL) were stained with DAPI (4’6-diamindion-2-phenylindole) at a

final concentration of 1 mg mL-1 for 15 minutes and filtered through a polycarbonate black

0.2 µm pore-sized filter (Porter & Feig, 1980). Polycarbonate filters were mounted on to

microscope slides and non-fluorescence immersion oil used. Slides were examined at ×100

using a fluorescence-equipped Olympus BX41 compound microscope. For each slide, ten

pictures of random views (≥ 500 total cells) were captured using an Olympus DP72 camera

and CellSens Standard software (version 1.3). Images were analysed for cell abundance and

volume using CellC software (Selinummi et al., 2005). Bacterial biomass was calculated

using a conversion factor of 0.28 pg C µm-3 (Simon & Azam, 1989).

Sampling, enumeration and identification of zooplankton

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Samples for zooplankton identification and enumeration were taken with a Haney-type trap

(4.2 L) (Gawler & Chapuis, 1987) on days 0, 5 and 8. Samples were collected from each

mesocosm on each day, except for day 0 where 4 random mesocosms were sampled to

determine the initial zooplankton community structure. Zooplankton were retrieved by

filtering through a 35 µm mesh nylon netting (Likens & Gilbert, 1970) glued to the bottom of

a Perspex cylinder and preserved with a 70% v/v ethanol solution. A 1 mL Eppendorf

automatic pipette and a Sedgewick-Rafter counting chamber were used for sub-sampling and

counting of zooplankton. The disposable tip of the pipette was cut to make a 4 mm diameter

opening so that large crustacean zooplankton would not be under-subsampled (Edmondson &

Vinberg, 1971). Each sample bottle was stirred thoroughly in order to ensure the random

distribution of the specimens within the sample bottle. A 1 mL sub-sample was taken with

the automatic pipette and placed in the counting chamber and the zooplankton counted under

a Leica DM2500 compound microscope at a magnification of x50. Preliminary counting of

five replicate samples established that the coefficient of variation was reduced to ~10% when

the mean number of specimens counted exceeded 100. Therefore, subsampling and counting

were repeated until a minimum of 100 specimens of the most abundant taxon were counted.

Zooplankton, except copepods were identified to the genus level using the taxonomic keys

and descriptions of Shiel (1995) and Kobayashi et al., (2009). Copepods were identified as

either nauplii or cyclopoid copepodites (cyclopoids hereafter) as calanoid, harpacticoida and

adult stage copepods were mostly absent from this study. Ciliates were grouped together

except for the genus Vorticella which was quantified separately.

Data Analysis

Repeated measures analysis of variance (ANOVA), with treatments and time as factors, were

used to assess the dissolved oxygen, bacteria, chlorophyll a and DOC data. Before analysis

data were transformed to reduce skewness and to homogenise variances. The data were

analysed in Statistica Version 7 (2004) and Graph Pad Prism. When the ANOVA main test

provided significant results, specific pair-wise differences were located using the Bonferroni

post-hoc test (Zar, 1984).

Non-parametric permutational multivariate analysis of variance (PERMANOVA) (Anderson,

2001a, Anderson, 2001b) was used to assess zooplankton community responses. The

PERMANOVA main test examined the differences between treatments and days. Specific

contrasts were also examined between the following groupings: control/amended; glucose/red

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gum; and nutrients/no nutrients. PERMANOVA provides a distinct advantage when testing

multiple contrasts because frequency distributions are freshly generated for each contrast.

This avoids the problem of accumulated type I errors that are commonly encountered with

parametric post-hoc tests. The PERMANOVA test was treated as an orthogonal design with

days 5 and 8 as time factors. The a priori decision was made that if a significant interaction

was found between treatments and time, then contrasts would be examined separately for days

5 and 8. If the interaction term was not significant, then contrasts were examined across the

pooled days.

Multivariate PERMANOVA tests were performed on the zooplankton community data and

were followed by similarity percentages (SIMPER) analyses to establish which individual

taxa were most influential in driving the differences among factors. Univariate

PERMANOVA tests were performed using the same test design that was applied to the

zooplankton community, on total zooplankton density and each individual taxon that had been

identified as influential by the SIMPER analyses. Nauplii were included in the total

zooplankton counts, but excluded from the community analyses because it was possible that

calanoid and cyclopoids were included, in unknown numbers, in the nauplii counts. Non-

metric multidimensional scaling (nMDS) was used to visually represent the trajectory of

change in zooplankton communities across all treatment and time factors. All zooplankton

densities were log10(x+1) transformed prior to analysis. The data were analysed in PRIMER

V6.1.13 and PERMANOVA+ V1.0.3.

Results

Physico-chemical, bacteria and chlorophyll a changes

Water temperatures over the course of the experiment ranged from 18 to 22.5°C with a mean

temperature of 20.2°C with no significant differences between treatments (P>0.05).

Dissolved oxygen differed significantly (P<0.001) among treatments and with time (Table I

and II; Fig. 2a). By day 2, dissolved oxygen levels in DOC treatments with nutrients had

dropped significantly (P<0.05) below the control and remained significantly different until

day 6. The glucose + nutrients and red gum + nutrients treatments had lower dissolved

oxygen levels on these days than the glucose alone and red gum alone treatments. Glucose

alone was significantly lower than the control on days 4 to 6 while the red gum alone

treatment was lower on days 3 and 5 (P<0.05).

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Bacterial biomass as pg C mL-1 differed significantly among treatments (P<0.01) and with

time (P<0.001) (Table I and 2; Fig. 2b). When DOC was added as glucose, with or without

nutrients, bacterial biomass peaked at day 6 and was significantly higher than the control

(P<0.001). At day 8 both glucose treatments decreased in bacterial biomass and only the

glucose alone had a significantly higher biomass than the control (P<0.001). The treatment

with DOC added as red gum showed increasing bacterial biomass across the experiment and

was significantly higher than the control (P<0.05) at days 3, 6 and 8. The red gum + nutrients

treatment peaked at day 3 and was significantly higher than the control (P<0.001), before

declining in biomass at days 6 and 8.

DOC concentrations during the experiment are shown in Fig. 2c. The amendments with

glucose and the red gum leachate at the start of the experiment (day 0) increased all levels up

to approximately 20 mg L-1. The ambient DOC level in the control was 4.7 ±0.04 mg L-1 and

this did not vary greatly over the experiment. At day 3, DOC utilisation showed similar

patterns to the dissolved oxygen results, with the treatments amended with nutrients

consuming DOC at a significantly (P<0.001) greater rate than those without (Table I and II).

By days 6 and 8, the glucose amendments had significantly lower DOC concentrations than

the red gum treatments (P<0.001) although they remained higher than the control. The red

gum + nutrients treatment had significantly lower DOC concentrations than red gum alone

(P<0.001).

Chlorophyll a concentrations decreased in all treatments across the 8 days (Fig. 2d). Results

differed significantly with treatment and time (Table I and II). The glucose treatment had

significantly lower chlorophyll a concentrations than the control at day 6 (P<0.01). The

glucose + nutrients treatment demonstrated no significantly different concentrations to the

control. When DOC was added as red gum leachate, chlorophyll a concentrations were

significantly lower than the control at days 6 and 8 (P<0.01) and with nutrients at days 3, 6

and 8 (P<0.05).

Zooplankton responses

A total of 19 taxonomic groups of zooplankton were identified. Total zooplankton density

increased in all treatments from day 0 to day 5, with the largest increase occurring in the

glucose, red gum and red gum + nutrients treatments (Fig. 3). Densities across all treatments

declined in roughly the same proportions between days 5 and 8 with the glucose + nutrients

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amendment still lower than the other amendments. PERMANOVA tests identified strongly

significant differences among treatments and days (Supplementary Table I; p<0.005 in both

tests), but there was no significant interaction between the two. The control/amended and

glucose/red gum contrasts were strongly significant (p<0.005 in both tests), but no significant

difference was found in the nutrient/no nutrient contrast (p = 0.27).

Multivariate PERMANOVA tests of zooplankton community structure identified strong

significant differences among treatments and days, and a significant interaction between both

factors (Supplementary Table I; p<0.005 in all three tests). Subsequently the three contrasts

were tested separately across days 5 and 8 (Supplementary Table I). Fig. 4 shows clearly that

the trajectories of the zooplankton communities for glucose, red gum as well as red gum +

nutrients were very similar at day 5. By day 8, the two red gum treatments continued to

respond similarly, whilst the two glucose treatments were less similar at day 8. The control

samples were consistently the most distinct of the treatments.

SIMPER analyses identified ten taxa as accounting for more than 90% of the differences

among each treatment (Supplementary Table I). PERMANOVA tests of these ten taxa

showed considerable variation in responses (Supplementary Table I) and Fig. 5 shows some

of the main protozoan, rotifer and copepod responses. Responses to the control/amended

contrast varied with different taxa. Vorticella spp., Polyarthra spp., Asplanchna spp.,

Trichocerca spp., Anuraeopsis spp and cyclopoid copepods all differed significantly from

control samples on days 5 and 8. Asplanchna (Fig. 5E) and cyclopoid copepods (Fig. 5B)

treatments increased on day 8 whilst Vorticella (Fig. 5C), Anuraeopsis, Proalides (Fig. 5I)

and Trichocerca (Fig. 5J) decreased. Hexarthra spp. had a significant response to both of the

contrasts, and showed a preference for treatments without nutrients (Fig. 5G). Density of

ciliates (other than Vorticella) was much lower than Vorticella, and was highest in control and

glucose treatments on day 8 (Fig. 5D). Polyarthra had significantly higher density in glucose

than red gum treatments (Fig. 5H) while Brachionus (Fig. 5F), Proalides (Fig. 5I) and

cyclopoid copepods (Fig. 5B) responded positively to the red gum treatment. Nauplii were

excluded from the statistical analysis but showed a clear response to red gum treatments at

day 8 (Fig. 5A).

Discussion

Heterotrophic and autotrophic responses

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At the ecosystem level, allochthonous DOC affects river metabolism by subsidising

ecosystem respiration relative to production (Del Giorgio et al., 1999). As a result of DOC

amendment, heterotrophic respiration of all treatments significantly (P<0.05) reduced

dissolved oxygen on certain days of the experiment (mainly days 2 to 5) compared to the

control (Fig. 2a). This suggests the heterotrophic bacterial community could utilise both

DOC sources, probably as aquatic heterotrophic bacterial communities contain a nearly full

complement of carbon processing functional groups (Judd et al., 2006). The bacterial

community appeared to be DOC limited as previously seen in this river over three seasons in

microcosm experiments (Westhorpe et al., 2010). Dissolved oxygen was consumed faster

during days 2 to 3 in the DOC treatments with added nutrients (Fig. 2a) suggesting some co-

limitation of DOC with nitrogen and/or phosphorus which we have previously witnessed in

coastal rivers (Hitchcock & Mitrovic, 2013). Supporting this, the bacterial biomass was

significantly higher at day 3 for the red gum and nutrient treatment compared to red gum

alone (Fig. 2b).

DOC concentration data supported the uptake of DOC by heterotrophs as DOC treatments

with nutrients had lower DOC concentrations at day 3, a similar pattern to the dissolved

oxygen data (Fig. 2c). By day 6 the difference was no longer apparent and the glucose

treatments had lower DOC concentrations than the red gum, which coincides with bacterial

biomass being significantly higher for glucose treatments than red gum treatments. DOC

concentrations for the red gum treatments took longer to drop and remained between

approximately 10 and 12 mg L-1, suggesting that this source of carbon took longer to be

utilised by bacteria. This may be as glucose is low molecular weight and considered highly

labile (Berggren et al., 2010) whilst naturally occurring DOC is a diverse mix of different

compounds of differing molecular weights and labilities (Baldwin, 1999).

Chlorophyll a declined in the control and all treatments with time (Fig. 2d). The causes of the

chlorophyll a decline relative to the control are not understood, however it may have been

influenced by bacteria being able to out-compete phytoplankton for available nutrients when

DOC was added (and no longer limiting), due to a higher surface area to volume ratio of

bacteria (Blomqvist et al., 2001). Drakare et al., (2002) found that high flows carrying DOC

into a lake led to low primary production despite good conditions for phytoplankton growth.

In their study, primary production did not exceed bacterial production for approximately 20

days after a high flow episode had replenished DOC concentrations. Chlorophyll a may have

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also been reduced by grazing effects as the zooplankton communities changed with time and

also treatment and there may also have been some direct inhibition of phytoplankton by the

leachate. Chlorophyll a decline in the control replicates may have been due to reduced light

availability in the mesocosms as they were partly shaded. Although light penetration was not

changed in these experiments with addition of leachates, it should be considered that it could

be substantially reduced with increased flows, rendering the phytoplankton more susceptible

to light limitation (Jassby et al., 1993). In the Namoi River increases in turbidity greater than

500 NTU can occur with high flow events (Westhorpe et al., 2008). This could further

augment heterotrophic bacteria compared to phytoplankton as relatively more nutrients

become available to the heterotrophic bacteria.

Zooplankton responses to DOC source

Treatments with amendments of all DOC sources increased in density of total zooplankton

compared to the control (Fig. 3). This was most pronounced for the red gum, red gum +

nutrients and the glucose treatment. For protozoan taxa such as Vorticella, DOC amendment

was associated with large increases in density relative to the control but was independent of

the added DOC source (Fig. 5C). The increase in Vorticella is likely mediated through the

large increase of bacterial biomass in DOC treatments which are its primary food source

(Sanders et al., 1989). Due to their short generation times, ciliates are known to respond fast

to increases in food resources (Sommer et al., 1986). Other ciliates (excluding Vorticella)

however remained in much lower abundance (Fig. 5D) which may be due to grazing from

higher trophic organisms or competition with Vorticella or other organisms for resources.

Protozoans have been shown to be a preferred food source for many metazoan zooplankton

(Gifford & Dagg, 1988) and Vorticella has been shown to be an important prey species to

zooplankton (Packard, 2001). In this experiment Vorticella may have played a role in

supporting rotifer species, however they did not appear important for copepods as whilst

Vorticella was high in abundance in all treatments (Fig. 5C), cyclopoids and nauplii only had

a high abundance in red gum treatments (Fig. 5A,B).

Rotifers are known to have some of the fastest growth rates of the metazooplankton and can

peak in density shortly after ciliates (Sommer et al., 1986). In our study, several rotifers

responded rapidly to the different DOC amendments compared to the control such as

Asplanchna, Proalides and Brachionus, with growth rates of between 0.23 and 0.47 d-1, which

was probably influenced by the high water temperature of ~20°C. Similar and greater growth

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rates have been seen in other food source experiments such as 0.8 d-1 (Rothhaupt, 1990) and

0.7 d-1 (Jensen et al., 2006) for Brachionus spp. suggesting food availability and quality was

greatly improved with the addition of DOC. Rotifers may have a wide diet which varies

between taxa and can feed on both autotrophic and heterotrophic organisms (Arndt, 1993,

Gilbert & Jack, 1993). Of the species observed in our experiment bacterivory has been

observed amongst Hexarthra, Proalides, Anuraeopsis, Keratella (Arndt, 1993 and references

therein) potentially creating a short and efficient food web. Other species such as Asplanchna,

Brachionus, Polyarthra and Proalides have been shown to feed on other components of the

microbial loop such flagellates and ciliates, and the larger species such as Asplanchna and

Trichocerca may consume other rotifers (Arndt, 1993 and references therein). These

differences in feeding strategies may explain the different response times between rotifer

genera such as Keratella density peaking early at day 5 (Fig. 5K) and Asplanchna density

peaking later at day 8 (Fig. 5E).

There were also differences in the rotifer response between the glucose and red gum carbon

additions (Supplementary Table 1). Polyarthra responded more to the glucose (Fig. 5H)

whilst Brachionus (Fig. 5F) and Proaliades (Fig. 5I) mainly responded to red gum leachate.

These results are possibly due to the different carbon sources favouring different components

of either the bacterial and/or flagellate community, leading to resources that favoured

Polyarthra in the glucose treatments, and Brachionus and Proaliades in the red gum

treatments. The smaller heterotrophic flagellates and ciliates were not sampled in this study

but may have been important and their inclusion should be considered in future studies.

The different carbon sources also led to significantly different cyclopoid copepod responses.

Though the initial experimental conditions did not appear to favour cyclopoid survival, by day

8 of the experiment nauplii and copepodite densities were significantly higher in the red gum

treatments, compared to the control and glucose treatments (Fig. 5A,B). These changes are

most likely related to differences in the availability and quality of resources. Cyclopoids are

generally considered omnivores, though food preference will vary between species (Adrian &

Frost, 1993). As there was little difference in chlorophyll a between treatments in this

experiment (Fig. 2D) the increased densities are likely due to difference among heterotrophic

organisms. The main differences that we measured of potential prey items of cyclopoids that

could explain these results are the higher densities of Brachionus and Proalides. Brachionus

in particular is considered a good food source and is a common prey of cyclopoid copepods

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(Kumar & Rao, 2001) and is regularly used in copepod growth cultures (Lubzens et al.,

1985). It’s possible therefore that the increased Brachionus density, supported by favourable

small flagellate or ciliate resources, led to increased cyclopoid density in the red gum

treatments.

Gulati and DeMotts (1997) review on the role of food quality for zooplankton highlighted the

importance of polyunsaturated fatty acids as a main factor affecting growth and reproduction.

As bacteria cannot produce long chained polyunsaturated fatty acids, intermediate organisms

are needed for their synthesis (Breteler et al., 1999). Lubzens et al. (1985) showed in

laboratory cultures that Brachionus plicatilis was cable of synthesising such acids, adding

further evidence that Brachionus spp. may have been important to cyclopoid development in

this experiment. Possible differences in the densities of small flagellates and ciliates that were

not measured here may also be responsible for these differences as they are an important food

source for some copepod species (Broglio et al., 2003, Nakamura & Turner, 1997) and some

have been shown to provide essential fatty acids to metazoans (Breteler et al., 1999, Martin-

Creuzburg et al., 2005).

Another possible explanation is that the organisms in the red gum treatments were a higher

quality food source than those raised on the glucose addition. There is at least some

observational evidence that glucose additions lead to bacterial population distinct from natural

assemblages (Havskum et al., 2003, Hitchcock & Mitrovic, 2013). Whilst there is little

information on how different DOC sources may affect bacterial nutritional quality in

ecological studies, in laboratory cultures different growth mediums may lead to different fatty

acid profiles of bacteria (Kaneda, 1971). It is possible therefore that red gum leachate may

have induced a more diverse or nutritionally healthy bacterial community compared to those

in the glucose treatment leading to intermediary organisms such as flagellates or rotifers of

favourable quality to cyclopoids.

Our results suggest that the use of glucose as a DOC source may not be as representative as

leaf leachates or complex DOC sources for mesocosm experiments that examine changes in

zooplankton community structure. The MDS plot of zooplankton community in this

experiment highlights how different the responses were between glucose and leachate (Fig.

4). Whilst glucose is a simple carbohydrate, the red gum leachate is comprised of a variety

of different organic compounds such as carbohydrates, amino, phenolic and carboxylic acids

as well as a variety of micro-nutrients. Glucose has been frequently used as a DOC source in

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addition experiments however a comparison of responses to glucose and more complex DOC

sources has not been carried out to our knowledge. The different responses of certain

zooplankton taxa to the red gum leachate, compared to the glucose treatment, indicating this

should be considered in interpreting the results of experiments using simpler forms of DOC.

This suggests the effect of different carbon sources on heterotrophic diversity and nutritional

quality in aquatic systems may be an important area of future research.

Role of allochthonous carbon in food webs

Although bacterioplankton often use autochthonously produced DOC preferentially over

allochthonous sources (Kritzberg et al., 2006), the watershed can supply large amounts of

allochthonous assimilable organic carbon, contributing to significant increases in bacterial

production (Wilcox et al., 2005). There is considerable debate concerning the degree of

allochthonous organic matter subsidization of secondary productivity in aquatic environments

(Carpenter et al., 2005). Some evidence has suggested bacterial carbon pools are a minor

source for higher trophic levels. Sobczak et al., (2005) found that zooplankton in the

Sacramento and San Joaquin River preferentially consumed higher quality autochthonous

particulate matter over the more abundant low quality allochthonous organic matter. Pollard

and Ducklow (2011) found that despite high bacterial production driven by allochthonous

DOC in the Brisbane River, Australia, most production could not leave the microbial loop due

to viral lysis.

However, a growing number of studies are finding substantial subsidisation of the flow of

terrestrial organic carbon to zooplankton and fish (e.g. Hoffman et al., 2007, Hoffman et al.,

2008). In freshwater lakes, allochthonous carbon has been reported to support approximately

43% to 75% of bacterial growth (Kritzberg et al., 2006) and a recent study by Cole et al.,

(2011) found that allochthony of some zooplankton taxa is greater than 20% and in some

cases is up to 70% of the organism’s diet. Wilcox et al., (2005) found significant microbial

and invertebrate responses in a stream following the addition of labile carbon which

stimulated food web processes even in a system abundant with organic matter.

Only a few examples of allochthonous carbon subsidies to the food webs or its influence on

metabolism of lowland rivers are available (e.g. Bunn et al., 2003). Vink et al., (2005)

quantified ecosystem metabolism in the middle reaches of a river and showed that

phytoplankton production dominated ecosystem production. However, the authors speculated

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that the high contribution of phytoplankton in the Murrumbidgee system could be a

consequence of flow regulation and resultant loss of riverine connectivity with adjacent

floodplains. Oliver and Merrick (2006) found autochthonous organic carbon fuelled riverine

metabolism of some regulated rivers, primarily by reductions in flow and subsequent

reduction in organic matter. Hoffman et al., (2008) investigated the sources of organic matter

supporting lower food web production in a tidal freshwater portion of an estuary and found

that the degree to which zooplankton were supported by autochthonous sources declined

exponentially with discharge.

Elucidation of the different pathways of energy subsidisation and its effects on the

fundamental properties of food web dynamics and carbon cycling is an expanding frontier of

ecological research. The impacts of cross-ecosystem subsidies depend on the characteristics

of the imported material, the route of entry into the food web, the types of consumers present

and the productivity of the recipient system (Cole et al., 2006). Here we have shown how

zooplankton of an unconstrained lowland floodplain river may respond to amendments of two

DOC sources using mesocosm experiments. DOC amendment to the mesocosms was shown

to influence bacterioplankton and protozoan dynamics and influence zooplankton community

structure. The extrapolation of these mesocosm results to the river situation requires further

study to see if similar patterns are observed. DOC concentrations remain elevated for periods

of greater than a week after inflows (Westhorpe & Mitrovic, 2013) and due to the length the

river system flow peaks may travel for weeks allowing time for planktonic community

changes to occur. Our results support the contention that DOC supply may stimulate

heterotrophic bacterioplankton and may alter zooplankton density and community structure.

Acknowledgements

This work was funded by the New South Wales Government’s Integrated Monitoring of

Environmental Flows Program. Dr. John Brayan, Adam Crawford, Jon Holliday and staff of

the NSW Office of Water laboratory are thanked for analysis of water quality parameters.

Thanks to Rebecca Herron for assisting with the determination of bacterial abundance and

John Lemon for looking after the experimental location. We would like to thank Dr Bruce

Chessman for very helpful comments to improve this manuscript.

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Table I. Summary of repeated measures analysis of variance for dissolved oxygen, bacterial

biomass, chlorophyll a and DOC.

Source df F p

Dissolved oxygen Time 7 141.42 <0.001

Treatment 4 47.94 <0.001

Time*Treatme

nt 28 9.73 <0.001

Bacterial biomass Time 4 110.9 <0.001

Treatment 4 12.65 <0.01

Time*Treatme

nt 16 27.56 <0.001

Chlorophyll a Time 3 185.5 <0.0001

Treatment 4 5.088 <0.01

Time*Treatme

nt 12 3.351 <0.01

DOC Time 12 1863 <0.001

Treatment 3 519.7 <0.001

Time*Treatme

nt 4 249 <0.001

23

684

685

686

687

688

689

690

Table II. Summary of repeated measures analysis of variance Bonferroni post-hoc test results

for dissolved oxygen, bacterial biomass, chlorophyll a and DOC. C=control, G = glucose, GN

= glucose and nutrients, R = red gum, RN = red gum and nutrients. Level of statistical

significance indicated by: *** p < 0.001, ** p < 0.01, * p < 0.05.

Da

y

C x

G

C x

GN C x R

C x

RN G x R

G x

GN

R x

RN

GN x

RN

Dissolved Oxygen 1

2 * *

3 ** * * *

4 * * *

5 * * * *

6 *

7

8

Bacterial biomass 3 * *** ** ***

6 *** *** ** *** ***

8 *** *** *** **

Chlorophyll a 3 *

6 ** ** *

8 *** *

DOC 3 *** *** *** *** *** *** ***

6 *** *** *** *** *** *** ***

8 * *** *** *** *** *** ***

24

691

692

693

694

695

696

697

698

699

List of Figures

Fig. 1. Namoi River catchment and location of the study site at Boggabri, NSW, Australia.

Fig. 2. Changes in dissolved oxygen concentrations (a), bacterial biomass (b), DOC

concentrations (c) and chlorophyll a concentrations (d) over the course of the

experiment (n=4; ± standard error for all except bacterial biomass n=2; ± standard

error).

Fig. 3. Changes in mean zooplankton concentrations over the course of the experiment

(n=4; ± standard error).

Fig. 4. nMDS plot of mean zooplankton concentrations (Log10(x+1) transformed for each

treatment type across 3-days (0, 5 and 8 days).

Fig. 5. Changes in mean density for some important taxa over the course of the experiment

(n=4; ± standard error).

25

700

701

702

703

704

705

706

707

708

709

710

711

712

713

714

715

716

717

718