J Paleolimnol (2009) 41:453–470 DOI 10.1007/s10933-008-9236-0
ORIGINAL PAPER
Factors affecting diatom distribution in floodplain lakes of the southeast Murray Basin, Australia and implications for palaeolimnological studies Michael A. Reid Æ Ralph W. Ogden
Received: 18 October 2007 / Accepted: 1 July 2008 / Published online: 28 August 2008 Ó Springer Science+Business Media B.V. 2008
Abstract Diatom assemblages of surface sediments in 46 billabongs from four river floodplains in the southeast Murray-Darling Basin, Australia were sampled to investigate drivers of species distribution. The principal purpose of the study was to derive information to aid interpretation of diatom-based palaeoecological studies of these systems and of floodplain lakes more generally. Patterns in billabong diatom assemblages in relation to river reach, hydrology and farming intensity on surrounding land were examined, as were correlations with water quality variables. Seasonal variation in billabong water quality was high relative to spatial variation, and spatial patterns in billabong water quality were weak. In contrast, strong patterns were evident in diatom assemblages. Three main patterns were observed: (1) a distinction between billabongs dominated by planktonic diatoms from those dominated by benthic and attached forms; (2) differences in diatom assemblages in billabongs on different river reaches; and (3) differences in assemblages in billabongs with different hydrology. Of all water quality variables tested, total phosphorus (TP), total M. A. Reid (&) Riverine Landscapes Research Lab, University of Canberra, Canberra, ACT 2601, Australia e-mail:
[email protected] R. W. Ogden eWater Cooperative Research Centre, University of Canberra, Canberra, ACT 2601, Australia
nitrogen (TN) and pH exerted the strongest independent influence on diatom distribution; however, only TP remained an important variable when species variation due to river reach, hydrology, and aquatic plant cover was taken into account. The weak influence of water quality on diatom distribution is interpreted as reflecting the dichotomy between plankton and non-plankton-dominated billabongs, the influence of hydrology and biogeography, the lack of strong spatial water quality gradients and the high degree of temporal variability in water quality. The findings show that diatom records from billabong sediments can provide evidence of long-term changes in the abundance of aquatic macrophytes and hydrology. They also suggest that merging calibration data sets across regions for the purpose of improving diatom transfer functions for water quality reconstruction is of limited value for floodplain lakes, and that performance is more likely to be gained by boosting site numbers within regions. Keywords Billabongs Rivers Floodplains Palaeolimnology
Introduction Along with the other elements of river floodplain systems in Australia, billabongs have been subject to a range of anthropogenic stressors over the last approximately 200 years, including clearance of
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native vegetation, pastoralism, invasive species, flow regulation and water abstraction. There is little doubt that these changes have impacted negatively river and floodplain ecosystems; however, the precise causal mechanisms and hence appropriate management actions are not always clear because most changes were initiated before detailed ecological studies of these systems began (Reid and Ogden 2006). Palaeolimnological studies provide one means for gaining a greater understanding of both the nature of the preEuropean state of these systems as well as the causes of post-European changes (Thoms et al. 1999; Reid et al. 2002). In the past there has been a perception that sedimentary records from fluvial systems are unreliable, due to the dynamics of these environments and the evidence from numerous studies that floodplain lakes are relatively short-lived (Eckblad et al. 1977; Cooper and McHenry 1989; Lewis and Lewin 1983; Rang and Schouten 1989; Erskine et al. 1992). However, in recent times there have been increased efforts to apply palaeoecological approaches to fluvial systems (e.g. Hay et al. 2000; Michelutti et al. 2001; Schonfelder et al. 2002; Gell et al. 2005a; Wolfe et al. 2005, 2006). This trend has been particularly strong in Australia where studies of floodplain lake (billabong) sediments in the Murray Basin have proven highly promising (Donnelly et al. 1999; Thoms et al. 1999; Ogden 2000; Gell et al. 2005a; Reid et al. 2007). In addition to providing records of several thousand years duration (Ogden et al. 2001), these studies have demonstrated dramatic and substantial changes to billabong ecosystems associated with European settlement (Ogden 2000; Reid 2002; Tibby et al. 2003; Reid et al. 2007). In each system, the observed changes occur over ca 1–2 cm of sediment depth, suggesting that, despite their relative shallowness (mostly \2 m), the sediments deposited in these environments maintain a high level of stratigraphic integrity. The timing and ultimate causes of these changes have not always been clear for two principal reasons: first, the difficulties involved in obtaining reliable sediment chronologies for the recent past (Gell et al. 2005a); and second, difficulties in interpreting the proximate drivers of observed stratigraphic changes due to our poor understanding of the ecology of common taxa (Reid 2002; Tibby et al. 2003; Leahy et al. 2005) and of the taphonomic processes leading
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to their incorporation in sediment records (Ogden 2000). The purpose of this paper is to address the second of these issues by examining factors affecting the current distribution and abundance of diatoms in billabong sediments. Specifically, the study will examine the influence of water quality variables such as nutrients, pH, salinity, turbidity, as well as water depth, aquatic plant cover, biogeography, local landuse and hydrology, all of which have been suggested as important proximate or ultimate drivers of ecosystem change in floodplain lakes in Australia (Ogden 2000; Gell et al. 2005a, b; Reid et al. 2007). The implications of the results for interpretation of these and future palaeolimnological records are discussed.
Methods The billabong data set The billabongs included in the study are situated within the south-eastern portion of the MurrayDarling Basin, one of the largest drainage systems in Australia, covering an area of 1,058,800 km2, roughly 14% of the Australian continent (Fig. 1). The catchments of the parent rivers of the billabongs included in the study extend to 2,200 m, the highest point on the Australian continent. The billabongs themselves are situated in the lowland reaches at elevations from just below 300 m asl to around 100 m asl. Rainfall in the study region ranges from around 750 mm/a at Corryong in the Murray uplands to the east and Alexandra in the south, down to 444 mm/a at Mathoura in the western portion of the study area (Fig. 1). Highest rainfall and runoff occur during winter and spring, with spring discharge substantially augmented, particularly in the Murray River, by snowmelt from the high-altitude areas of their catchments in the Southern Highlands. Although the headwater regions remain largely forested, the floodplains themselves have been cleared to varying degrees for agriculture, mostly pastoralism, and now consist of grassland and open Eucalyptus camaldulensis and E. largiflorens woodland with isolated patches of remnant floodplain forest and woodland, usually in the more frequently flooded areas. The data set consists of surface sediment diatom samples and water quality data from 46 billabongs on
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Fig. 1 The study area
the floodplains of the Murray (30 billabongs), Ovens (8 billabongs), Kiewa (1 billabong) and Goulburn (7 billabongs) rivers. A larger data set is created by the inclusion of physical and chemical data from two of the Goulburn River billabongs for two separate monitoring periods and by repeat surface sediment sampling of these billabongs during the second monitoring period (Table 1). Regulation of river flows to provide water for summer irrigation in downstream areas is affected by three large dams: Hume Dam on the Murray River, Dartmouth Dam on the Mitta Mitta River (a tributary of the Murray) and Eildon Dam on the Goulburn River (Fig. 1). As a result, the billabongs of the
Murray River below Lake Hume and the Goulburn River are subject to a regulated hydrological regime. The effect of this regulation on the flooding regimes for billabongs associated with these rivers varies. In areas immediately downstream of the large impoundments, billabongs situated close to the mainstream may receive river input more frequently during the summer irrigation season as water levels are maintained to supply water to downstream irrigators (Pressey 1986; Maheshwari et al. 1995). Further away from the mainstream and further downstream the effect is generally a reduction in flood frequency as water extraction and flood mitigation take effect (Pressey 1986; Maheshwari et al. 1995). The variable
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Table 1 Physical features, sampling dates, river reaches and hydrological and farming intensity classes of billabongs included in the data set Billabong
River/ Reacha
Max. area (ha)
Mean vegetation cover
Hydrology
Farming intensity
Sediment sampling date
Survey period
1
Murr1
3.0
193
97
4.2
Unregulated
High
8/93
1/92–3/93
2
Murr1
2.9
3
Murr1
1.3
136
45
4.3
Unregulated
High
8/93
1/92–3/93
102
30
4.5
Unregulated
High
9/93
4
Murr1
1/92–3/93
7.9
168
51
3.2
Unregulated
High
8/93
5
1/92–3/93
Murr1
5.8
242
100
2.3
Unregulated
High
9/93
1/92–3/93
6 7
Murr1 Murr1
1.5 0.01
471 235
414 94
2.6 1.9
Unregulated Unregulated
High Low
9/93 8/93
1/92–3/93 1/92–3/93
7a
Murr1
0.44
325
193
2.3
Unregulated
Low
8/93
1/92–3/93
8
Murr1
0.01
300
101
3.6
Unregulated
Low
8/93
1/92–3/93
9
Murr1
3.6
145
122
1.1
Unregulated
High
8/93
1/92–3/93
10
Murr1
8
186
68
3.5
Unregulated
High
9/93
1/92–3/93
11
Kiewa
1.6
139
78
3.3
Unregulated
High
9/93
1/92–3/93
12
Murr2
8
336
50
1.0
Exposed
Low
9/93
1/92–3/93
13
Murr2
2.9
199
94
1.9
Isolated
High
9/93
1/92–3/93
14
Murr2
4.1
300
121
1.0
Exposed
Low
9/93
1/92–3/93
15
Murr2
1.1
187
10
1.7
Isolated
High
11/93
1/92–3/93
16
Murr2
7.8
573
191
1.2
Exposed
High
9/93
1/92–3/93
17
Murr2
2
40
0
5.0
Isolated
High
9/93
1/92–3/93
18
Murr2
1.8
131
0
2.3
Isolated
High
9/93
1/92–3/93
19
Murr2
0.06
230
164
3.0
Exposed
Low
8/93
1/92–3/93
20
Ovens
1.5
200
50
2.3
Unregulated
High
11/93
1/92–3/93
21 22
Ovens Ovens
3.4 0.63
188 210
72 123
1.8 4.2
Unregulated Unregulated
Low Low
11/93 11/93
1/92–3/93 1/92–3/93
23
Ovens
1.6
203
85
3.5
Unregulated
Low
11/93
1/92–3/93
25
Ovens
1.3
153
69
1.8
Unregulated
High
11/93
1/92–3/93
26
Ovens
2.8
186
84
1.0
Unregulated
High
11/93
1/92–3/93
27
Ovens
3.1
151
71
1.5
Unregulated
High
11/93
1/92–3/93
28
Ovens
1.7
167
28
1.2
Unregulated
High
11/93
1/92–3/93
29
Murr3
14.6
105
10
4.0
Isolated
High
8/93
1/92–3/93
29a
Murr3
1.8
447
342
1.3
Isolated
Low
8/93
1/92–3/93
30
Murr3
111
3
4.4
Isolated
High
8/93
1/92–3/93
31
Murr3
2.2
118
9
3.9
Isolated
Low
9/93
1/92–3/93
32
Murr3
4.8
362
161
1.1
Isolated
Low
9/93
1/92–3/93
33
Murr3
2.9
233
148
1.4
Exposed
Low
11/93
1/92–3/93
34
Murr3
2.2
243
99
1.6
Isolated
Low
11/93
1/92–3/93
35
Murr3
5.8
487
323
1.0
Exposed
Low
11/93
1/92–3/93
36 37
Murr3 Murr3
0.6 1.5
208 50
96 0
1.0 5.0
Isolated Isolated
High High
11/93 9/93
1/92–3/93 1/92–3/93
38
Murr3
5.4
314
122
1.0
Isolated
Low
11/93
1/92–3/93
OR
Goulb
1.5
300
180
4.0
Isolated
High
5/92
5/91–7/92
T1
Goulb
2.8
470
405
2.0
Exposed
High
5/92
5/91–7/92
T2
Goulb
1.2
280
150
3.0
Isolated
High
5/92
5/91–7/92
123
67
Max. depth (cm)
Min. depth (cm)
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Table 1 continued Billabong
River/ Reacha
Max. area (ha)
Max. depth (cm)
Min. depth (cm)
Mean vegetation cover
Hydrology
Farming intensity
Sediment sampling date
Survey period
H
Goulb
C1_1
Goulb
2.5
340
250
3.0
Isolated
High
5/92
5/91–7/92
2.8
370
270
2.0
Isolated
High
5/92
C2_1
5/91–7/92
Goulb
1.5
320
210
3.0
Isolated
High
5/92
5/91–7/92
NC
Goulb
0.7
200
90
1.0
Isolated
High
5/92
5/91–7/92
C1_2
Goulb
2.8
393
310
2.2
Isolated
High
5/94
5/93–5/94
C2_2
Goulb
1.5
348
273
2.8
Isolated
High
5/94
5/93–5/94
a
Murr1 = Murray River above Lake Hume; Murr2 = Murray River between Lake Hume and the Ovens River Junction; Murr3 = Murray River below the Ovens River Junction
effects of river regulation on billabong hydrology is summarised by classification of billabongs on these regulated river reaches according to the scheme applied by Pressey (1986) in that author’s inventory of Murray floodplain wetlands below Lake Hume. In this scheme, Pressey (1986) classed low-lying billabongs that experience inflow from the mainstream during the summer irrigation season as hydrological class 2 billabongs. These billabongs experience more frequent connection to the river as a result of regulation and are termed ‘Exposed’ in this study (Table 1). Billabongs at higher elevations that do not receive inflow from summer irrigation releases were classed by Pressey (1986) as hydrological class 3 billabongs and are termed ‘Isolated’ in this study (Table 1). Because the frequency of medium-sized floods has been reduced by river regulation (Maheshwari et al. 1995), ‘Isolated’ billabongs now experience less frequent connection than they did prior to the onset of the regulated regime (Ogden 1996; Table 1). The Ovens, the Upper Murray and Kiewa rivers are subject to largely unregulated flow, although some extraction and inter-basin transfer of water does occur (Crabb 1997). The billabongs on these river reaches are classed as ‘Unregulated’ (Unreg; Table 1). Most of the billabongs included in the study are affected to some degree by agricultural activity, with cattle and sheep grazing being the most widespread. However, there is variation in the intensity of agricultural activity at the local scale, enabling the billabongs to be classed as subject to high or low intensity agricultural activity, depending on whether they are situated within cleared grassland areas or within remnant woodland or forest (Table 1; Ogden 1996; Reid 1997).
Physical and chemical monitoring Field sampling of the Goulburn billabongs was carried out over the period from June 1991 until July 1992 at two-month intervals. Further sampling of two of these billabongs was carried out monthly between May 1993 and May 1994 to augment a palaeoecological study of these billabongs (Reid 1997). Sampling of the Murray, Ovens and Kiewa River billabongs was carried out at two-month intervals over the period from January 1992 until March 1993. In all cases, electrical conductivity (EC), pH and water temperature were measured in the field using a Hanna portable conductivity meter HI 8733 and a Hanna portable pH meter HI 8424. Additional chemical variables were measured in the laboratory using water samples collected in the field. Turbidity (NTU) was measured using a Hach Turbidimeter, model 2100A. Total nitrogen (TN) and phosphorus (TP) and major ions (Na+, Mg2+, Ca2+, K+, HCO3-, Cl-, SO42-) were analysed at the Murray Darling Freshwater Research Centre, EML (Chem) Pty. Ltd. and the Water Studies Centre at Monash University. Methods are outlined in Ogden (1996) and Reid (1997). The water depth of each billabong was measured on each survey trip at the deepest point in the billabong. Billabong area was estimated from aerial photographs or from 1:25,000 topographic maps (Ogden 1996; Reid 1997). Aquatic macrophyte cover (Cover) at all but the Callemondah billabongs was estimated visually using a class-based scale. Five cover classes were applied: 0–5%, 5–25%, 25–50%, 50–75% and 75–100% (Ogden 1996). Cover at the Callemondah billabongs was established through line
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intersect surveys and the same cover class scale was then applied. Submerged, floating and emergent macrophytes were included in the cover estimates. Formal floristic surveys were not carried out, except at the Callemondah billabongs; however, the common aquatic taxa throughout the system included Myriophyllum spp. L., Potamogeton tricarinatus A.Benn., Juncus ingens N.A.Wakef., Eleocharis sphacelata R.Br., E. acuta R.Br. and Azolla pinnata R.Br. Surface sediment sampling Surface sediments were sampled for diatom analysis at the end of the 12-month sampling period used in each sampling program described above. Samples were taken from the deepest section of each billabong using soft sediment corers designed to minimise disturbance of surface sediment layers. The upper 1 cm of sediment was extruded and sectioned in the field to minimise disturbance and maintain stratigraphic integrity. If the surface layer was seen to have been disturbed during the coring process, the material was discarded and a new sample taken. Preparation of samples for diatom analysis followed the methods outlined in Battarbee (1986). Identification and enumeration of diatoms was carried out using an Olympus BH-2 with Nomarski differential interference contrast and standard taxonomic references (Patrick and Reimer 1966, 1975; Germain 1981; Krammer and Lange-Bertalot 1986, 1988, 1991a, b). At least 300 diatom valves were counted for each sample. Data analysis Water quality variables measured over the course of the sampling period were summarised by the median, mean, maximum and minimum values recorded during the full sampling period (these are denoted in the text by the subscripts ‘med’, ‘mean’, ‘max’ and ‘min’, respectively). Data were log 10 transformed where necessary to overcome problems of skewness and non-linear relationships between parameters such as total nitrogen, total phosphorus, turbidity and water depth. Relationships between water quality variables were explored using Pearson correlations and Principal Components Analysis based on median values. Diatom species abundances are expressed as a
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percentage of the total number of valves recorded in each sample. Similarity matrices were calculated for water quality profiles and diatom species assemblages using the PRIMER computer program (Version 6.1.5, Primer-E 2006). In the case of the water quality profiles, the matrix was based on Gower difference measures calculated using median values. The Gower measure was used because it includes an implicit range standardisation, making it an appropriate measure to apply to environmental data incorporating a diverse array of variables, each with differing scales (Belbin and McDonald 1993). For the diatom surface sediment assemblages, the matrix was based on the Bray–Curtis similarity measure, which has been shown to be a robust measure of community-based data (Faith et al. 1991). These matrices were used to examine the influence of hydrology, farming intensity, and river reach, using the classifications listed in Table 1, on billabong water quality and diatom species distributions using the Analysis of Similarity (ANOSIM) procedure in PRIMER. This procedure uses similarity matrices to test for differences between predetermined groupings (i.e., the river reach, farming intensity and hydrology classes listed in Table 1) by comparing the average rank similarities between samples from different groups with the average rank similarities between samples from the same groups (Clarke and Warwick 1994). Relationships between diatom assemblages and water quality gradients were investigated through Canonical Correspondence Analysis (CCA) using the Canoco computer package (Canoco for Windows 4.54 2006). Forward selection was applied to determine which variables, including median, mean, maximum and minimum values for each variable, made a significant contribution (p \ 0.05) to explaining variance in the species data, as tested using a Monte Carlo permutation test (999 permutations). Relationships between diatom assemblages and nonwater quality variables (billabong depth, aquatic vegetation cover, hydrology, river reach and farming intensity) were also investigated using CCA, again with forward selection applied. In this instance hydrology, river reach and farming were represented as nominal variables in the CCA. Variance partitioning (Borcard et al. 1992) was used to investigate the effects of interactions between the significant environmental variables on the diatom assemblage
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ranges for individual billabongs over the course of sampling were generally around 1 m (Fig. 2), with the maximum range being 3.82 m. Water quality data collected from the 48 billabongs are summarised in the box plots displayed in Fig. 2. As for water depth, temporal variability in billabong water chemistry was relatively high (Fig. 2). The billabongs were moderately to highly turbid, with individual readings ranging from 1 NTU to 260 at Billabong 38. A strong negative correlation between turbidity (NTU) and billabong depth (Depth) is evident (Table 2), suggesting that re-suspension of surface sediments through wind-generated turbulence was an important contributor to high turbidity. Billabong median annual pH ranged from 6.12 to 7.99. The pH appears to reflect the concentration of base cations in billabong waters, there being a significant correlation between pH and EC (p = 0.003) (Table 2). The billabongs in the data set can be classed as fresh, with median annual EC ranging from 47 ls cm-1 to 400 ls cm-1 (Fig. 2). The billabongs in the data set ranged from meso to hypereutrophic, with annual median TP ranging from
distributions. In order to investigate the effects of environmental variables exclusive of biogeographic effects, CCA was also carried out separately on subsets of billabongs from each of the river reaches that were shown in ANOSIM to be characterised by distinct diatom assemblages. Finally, the significance of differences in the abundance of key diatom taxa (identified through multivariate analyses) in selected billabong groupings are tested using analysis of variance (using SPSS v14.0).
Results The physical and chemical character of billabongs Billabongs included in the study were generally small and shallow. The largest billabong included in the study has a surface area of 67 ha, while the greatest depth recorded was 5.72 m. However, the majority of billabongs are less than 5 ha in maximum extent (41 of 52), with maximum depths of less than 4 m (47). The mean depth for all billabongs was 177 cm. Depth
Water temp (°C) Turbidity (NTU)
Depth (m)
Billabong
0
2
4
6
10
20
30
40
0.0
150
200
300
Electrical conductivity (µS cm -1)
pH 6.00
8.00
10.00
300
700
1,100 1,500 1,900
TN (mg-1) 0.01
1 2 3 4 5 6 7 7a 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 29a 30 31 32 33 34 36 37 38 OR T1 T2 H C1_1 C2_1 NC C1_2 C2_2
0.10
1.00
10.00 100.00
TP (mg-1) 0.01
0.10
1.00
10.00
Murray 1
Kiewa
Murray 2
Ovens
Murray 3
Goulburn
Fig. 2 Box plots summarising within-billabong range in recorded depth and water quality
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Table 2 Matrix of Pearson correlation coefficients Veg covermean Veg covermean
Tempmed
Depthmed
ECmed
NTUmed
TNmed
TPmed
pHmed
-0.133
-0.100
0.087
-0.291
0.027
-0.183
0.162
0.063
-0.034
-0.144
-0.196
0.084
0.025
-0.437 -0.174
0.247 0.593
0.081
-0.636 0.122
0.354 0.410
0.613
-0.023
Tempmed
0.366
Depthmed ECmed
0.499 0.558
0.852 0.194
0.860
NTUmed
0.044
0.252
0.001
0.216
TNmed
0.670
0.163
0.077
0.000
0.010
TPmed
0.819
0.553
0.000
0.387
0.000
0.202
pHmed
0.328
0.566
0.010
0.003
0.869
0.082
-0.352
-0.180
0.243 -0.062
0.661
Correlation coefficients (r) are given above the diagonal cells, p-values are given below, p-values \ 0.05 are in bold. The variables NTU, TN and TP were Log 10-transformed before calculating correlations
42 lg l-1 to 990 lg l-1 and TN concentrations ranging from 0.110 mg l-1 to 4.00 mg l-1. Once again, the range of within-billabong nutrient concentrations was often high. TP correlates strongly with NTU and Depth (Table 2). Accordingly, shallow billabongs were characterised by high TP concentrations and high turbidity. Vegetation cover was also negatively correlated with NTU (Table 2). The first axis of the PCA carried out on billabong physical and chemical character reflects variation in depth, turbidity and TP concentrations, which are all strongly correlated (Fig. 3). Thus, billabongs scoring higher on this axis are characterised by greater depth and water clarity and lower TP concentrations (Fig. 3). The second axis in the PCA reflects variation in EC and pH, with billabongs scoring highest on this axis being characterised by higher values in both these variables (Fig. 3). Spatial patterns in billabong water quality Analysis of Similarity (ANOSIM) carried out on water quality data shows that only the billabongs of the Goulburn River, which were characterised by greater water depth, higher EC and pH and lower turbidity, are clearly separated from the billabongs of the remaining reaches (Figs. 3, 4a). There is no separation of billabongs by hydrological regime (Fig. 4b); however, when the comparison was restricted to only Murray 2 billabongs—the single reach where the hydrological distinction between the Exposed and Isolated classes is greatest (Maheshwari et al. 1995)—the difference between these classes was clear (Global R = 0.844). There was no
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significant difference in the water quality of billabongs according to farming intensity on surrounding land (Global R = -0.033). Surface sediment diatom assemblages A total of 306 taxa were identified, although most of these were very rare, and only those present in abundances in excess of 5% in a single sample or greater than 1% in at least four samples (a total of 92 taxa), are considered here and included in the statistical analyses. The relative abundances of the more common taxa are indicated in Fig. 5. The majority of species identified were attached or motile, benthic species and the majority of samples were dominated by diatoms that characteristically display these life habits. The most common of these include the attached taxa Achnanthidium minutissimum (Ku¨tz.) Czarnecki and Gomphonema parvulum Kutzing and the motile benthic species Navicula cryptocephala Kutzing. Of these, A. minutissimum was markedly more abundant in the non-plankton-dominated billabongs of the Goulburn, Ovens and Murray 1 river reach floodplains. G. parvulum and N. cryptocephala were more evenly distributed, but were most common in the billabongs of the Ovens and the Murray 3 (G. parvulum) and the Goulburn River and Murray 1 reach (N. cryptocephala). Cocconeis placentula Ehrenberg was common in some Goulburn River billabongs, but was not abundant in the billabongs of the remaining reaches. Plankton-dominated assemblages were largely restricted to billabongs of the Murray River
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(a)
1.0
1.0
(b) EC
EC
TP
TP pH
pH
TN
TN
NTU
NTU veg cover
veg cover
water temp
water temp water depth
-1.0
-1.0
water depth
1.0
-1.0
-1.0
1.0
Environmental variables
Environmental variables
River reaches
Hydrological class
Murray 1 Murray 2 Murray 3 Kiewa Ovens
Unregulated Isolated Exposed
Goulburn
Fig. 3 Biplots of environmental variables and sample scores from PCA of billabong water chemistry. Samples classed by reach (a) and hydrology (b)
downstream of Lake Hume (Murray 2 and Murray 3). Aulacoseira subborealis (Nygaard) Denys, Muylaert & Krammer and Aulacoseira granulata (Ehr.) Simonsen were the most abundant planktonic diatom taxa at these sites. The abundance of A. granulata was highly variable, particularly in the billabongs of the Murray 2 reach, while the abundance of Aulacoseira subborealis was more consistent across Murray 2 and Murray 3 reaches (Fig. 5). Stephanodiscus parvus Stoermer & Hakansson, Cyclotella pseudostelligera and Cyclostephanos tholiformis Stoermer & Hakansson were occasionally abundant in Murray billabongs. Aulacoseira crenulata (Ehrenberg) Thwaites was relatively common in the sediments of Murray 1 and Ovens billabongs (Fig. 5).
Spatial patterns in diatom surface sediment assemblages Billabong diatom assemblages clearly differed between most reaches, with only the Murray 1 and Ovens reaches and the Murray 2 and Murray 3 reaches returning R-values substantially below 0.5 (Fig. 4a). On this basis, three distinct reach groupings of billabongs with regard to diatom assemblages can be established—the Murray 2 and Murray 3 billabongs, which were dominated by the two planktonic taxa Aulacoseira granulata and A. subborealis (Fig. 5), the combined Murray 1 and Ovens billabongs, which were dominated by the benthic and epipelic taxa Achnanthidium minutissimum, Gomphonema parvulum and Navicula cryptocephala, and the Goulburn billabongs,
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462 Fig. 4 R statistics for pairwise comparisons of reach (a) and hydrological (b) classifications of billabongs characterised by physical and chemical variables and by diatom assemblages. R values in excess of 0.75 suggest groups are well separated, values greater than 0.5 suggest some overlap, but a clear difference between groups, while values less the 0.25 indicate little or no separation of groups (Clarke and Warwick 1994)
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(a)
Ovens
Murray 3
Murray 2
Murray 1
1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0
Water quality Diatom assemblages
(b)
Exposed
Unregulated
Goulburn
Ovens
which were dominated by Achnanthidium minutissimum, Navicula cryptocephala and Cocconeis placentula (Fig. 5). Billabong diatom assemblages also differed between Exposed and Unregulated billabong classes (Fig. 4b). This difference is driven by the dominance of Aulacoseira granulata and, to a lesser degree, A. subborealis in Exposed billabongs. The diatom assemblages of the two regulated classes were not clearly separated; however, as for the water quality data, when the analysis was restricted to the Murray 2 reach only, the two groups were clearly separated (Global R = 0.771). This distinction can be largely attributed to differences in the abundance of A. granulata in Exposed billabongs. ANOVA, comparing the abundance of A. granulata in Exposed and Isolated billabongs of Murray 2 and Murray 3 reaches, shows that A. granulata was more abundant in Exposed billabongs (F = 6.32, p = 0.02). This effect was stronger for Murray 2 reach, although the interaction was not significant and there was also no difference in the abundance of A. granulata across reaches (Fig. 6a). No significant effects were detected
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Murray 3 Murray 2
1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0
Isolated Exposed
when the same analysis was carried out on Aulacoseira subborealis, the other dominant diatom species in these reaches (F = 0.429, p = 0.519) (Fig. 6b). The diatom assemblages of billabongs subject to high intensity farming and those of billabongs subject to low intensity farming were not clearly separated (R = 0.114). Influence of environmental variables on diatom assemblages Forward selection of water quality variables showed that just three made significant, independent contributions to explaining variation in the diatom assemblage data. These were, in order of selection, TNmean, pHmin and TPmed. In combination, these three variables explain 15.3% of the variation in the species data. For the non-water quality variables, four made significant, independent contributions to explaining species variance. In order of selection, these variables were ‘Goulburn’ and ‘Unregulated’, vegetation covermin and ‘Ovens’. In combination these four variables explain 25.7% of the variation in the species data. With
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463
Plankton
Facultative plankton
Attached
1 2 3 4 5 6 7 7a 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 25 26 27 28 29 29a 30 31 32 33 34 35 36 37 38 OR T1 T2 H C1_1 C2_1 NC C1_2 C2_2
Motile benthic
Murray 1
Kiewa
Billabong
Murray 2
Ovens
Murray 3
Goulburn
0
20 0
0
20 0
20
0
20
400
200
20
40
60
80 0
200
20 0
0
20
0
20
40 0
20
0
20
0
0
20 0
20
40 0
0
0
20 0
20 0
0
Fig. 5 Relative abundances of common diatom taxa found in the billabong data set. Billabongs are arranged broadly upstream to downstream
the three water quality and four non-water quality variables included in CCA, the total species variance explained increases to 32.4%; however, forward selection of these seven variables shows that TNmean and pHmin, which were selected 6th and 7th, respectively, did not explain a significantly greater amount of species variation (Table 3). A plot of the CCA ordination using all seven variables is presented in Fig. 7. Variance partitioning confirmed the greater explanatory power of the non-water quality variables,
showing that TNmean, TPmed and pHmin explain only 6.8% of species variation after variation attributable to ‘Goulburn’, ‘Unregulated’, ‘Ovens’ and vegetation covermin is removed. In contrast, ‘Goulburn’, ‘Unregulated’, ‘Ovens’ and vegetation covermin explain 17.1% of the species variation after variance attributable to TNmean, TPmed and pHmin is removed. CCA was repeated separately for each of the river reach groupings that were shown in ANOSIM to be characterised by distinct diatom assemblages.
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(a) 60
Table 3 Results of forward selection in CCA using all sites
50 40 30
Variable
k-1
Variance explained
Goulburn
0.259
8.62
Unregulated
0.2239
7.45
TNmean Vegmin
0.2084 0.1505
6.94 5.01
pHmin
0.1455
4.84
TPmed
0.1334
4.44
Ovens
0.1244
4.14
20
F
p
k-A
10 0 Murray 2 Murray 3 Murray 2 Murray 3 Exposed
Isolated
(b) 35
Goulburn
0.259
8.62
4.34
Unregulated
0.3121
10.39
5.77
0.002 0.002
TPmed
0.1105
3.68
2.09
0.026
Vegmin
0.1093
3.64
2.12
0.002
Ovens
0.0923
3.07
1.83
0.044
TNmean
0.0506
1.68
1
0.398
pHmin
0.0404
1.34
0.8
0.6
Total
0.947
31.51
The marginal and conditional effects of the significant water quality (3) and non-water quality (4) variables are shown. The canonical eigenvalue of each variable, k - 1, indicates the amount of species variance potentially explained by that variable alone (the marginal effect). The k - A value indicates the increase in the sum of all canonical eigenvalues of the ordination when that variable is added sequentially (the conditional effect). At each iteration, the variable explaining the greatest amount of species variance (highest k - A) is added. F and p values are based on Monte Carlo permutation tests with 499 permutations and indicate whether the variables add a significant amount to variance explained
30 25 20 15 10 5 0 Murray 2 Murray 3 Murray 2 Murray 3 Exposed
Isolated
Fig. 6 Estimated marginal means for Aulacoseira granulata (a) and A. subborealis (b) by river reach (Murray 1 and 2) and hydrological class (Exposed and Isolated)
Forward selection in these analyses showed the influence of water quality variables to be substantially greater than for the combined data set (Tables 4–6). In the case of billabongs on the Murray 1, Kiewa and Ovens reaches, the variables TPmin, pHmed and farming intensity explain 20.12% of the
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species variation (Table 4). For the Goulburn billabongs, TPmed, ‘Isolated’, Depthmax and TNmax explain 58.37% (Table 5), while for the Murray 2 and 3 reaches, TPmed, Vegetation covermin, ECmed, ECmax, farming intensity and Temperaturemed explain 56.93% of the variation (Table 6).
Discussion The results of this study indicate that the influence of water quality variables such as pH, EC, turbidity and nutrient concentrations on the distribution of diatom taxa in billabongs across the study area is relatively small when compared to the influence of river reach, hydrology and habitat availability (i.e. whether a billabong is macrophyte or phytoplankton-
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465
(b) 1.0
1.0
(a) pHmin
Goulburn
pH min
Goulburn TN mean
TN mean
Ovens Veg covermin Unregulated
Unregulated TPmed
TPmed
- 1.0
- 1.0
Ovens Veg covermin
-1.0
1.0
- 1.0
1.0
Environmental variables
Environmental variables
Nominal Environmental variables
Nominal Environmental variables
River reaches
Diatom habitat grouping
Murray 1 Murray 2
Planktonic taxa Attached taxa Motile benthic taxa
Murray 3 Kiewa Ovens Goulburn
Fig. 7 Biplot of seven environmental variables and sample (a) and species scores (b) on axes 1 & 2 from CCA ordination using the 50-sample billabong data set. Scaling focused on inter-species distances Table 4 Results of forward selection in CCA using Murray 1, Ovens and Kiewa billabongs only (all unregulated sites) Variable
k-1
Variance explained
TPmin
0.2928
11.35
pHmed
0.2635
10.21
F
p
k-A TPmin pHmed
0.2928 0.2259
11.35 8.76
Total
0.519
20.11
2.3 1.86
0.028 0.022
See Table 3 header for explanation of the forward selection process and derived values
dominated). This result contrasts with most studies of diatom distributions in Australia and elsewhere that suggest water chemistry exerts the greatest control over distributions and that biogeographic influences are relatively minor for these organisms (e.g. Birks et al. 1990; Dixit et al. 1992; Bennion et al. 1996; Gell 1997; Tibby and Reid 2004); however, they are largely consistent with the findings of Hay et al. (2000), which also highlighted the influence of hydrology and macrophyte abundance on diatom assemblages in floodplain lakes of the Mackenzie Delta in the Northwest Territories, Canada.
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Table 5 Results of forward selection in CCA using Goulburn billabongs only Variable
k-1
Variance explained
TPmed
0.3699
25.49
Depthmax
0.2976
20.51
Isolated
0.1885
12.99
F
p
k-A TPmed
0.3699
25.49
2.4
0.01
Isolated
0.2201
15.17
1.53
0.046
Depthmax
0.257
17.71
2.13
0.024
Total
0.847
58.37
See Table 3 header for explanation of the forward selection process and derived values Table 6 Results of forward selection in CCA using Murray 2 and 3 billabongs only Variable
k-1
Variance explained
TPmed
0.2178
20.00
Veg covermin
0.1575
14.46
ECmed
0.1591
14.61
ECmax
0.182
16.71
High farm
0.1843
16.92
Tempmed
0.0842
7.73
F
p
k-A TPmed
0.2178
20.00
4.25
0.002
Veg covermin
0.1014
9.31
2.11
0.002
ECmed
0.0813
7.47
1.77
0.022
ECmax
0.0752
6.91
1.72
0.04
High farm
0.0731
6.71
1.76
0.032
Tempmed
0.071
6.52
1.81
0.024
Total
0.62
56.93
See Table 3 header for explanation of the forward selection process and derived values
Studies that have shown a predominant influence of water chemistry on diatom distributions support the notion that improved characterisation of diatom optima and tolerances can be best achieved through creation of large regional data sets that maximise the length of the gradient of interest and minimise bias in sampling across the gradient (Gasse et al. 1995; Bennion et al. 1996). The assumption underlying this view is that the cosmopolitan nature of diatom distributions reduces the capacity of biogeographic factors to introduce noise into observed distribution
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patterns. The results of this study suggest that, for these billabongs at least, this assumption does not hold and that individual river reaches have distinct diatom floras associated with them. Reach-scale spatial patterns are evident in the water quality of billabongs included in this survey. However, these patterns are not strong and only the Goulburn River billabongs, with generally higher EC and pH and lower TP, clearly differ from the remaining billabongs. This seems to be largely a reflection of the local geology in the vicinity of the Goulburn billabongs which includes Devonian marine sediments incorporating limestone (Reid 1997). Similarly, although the ‘Exposed’ billabongs form a tight grouping (Fig. 3b), neither this nor the other hydrological groupings have clearly different water quality. The lack of strong spatial patterns in water quality may have been influenced by the fact that the surveys of most billabongs were conducted during a year when rainfall was 60% above average (Ogden 1996). Flooding occurred during the year that the billabongs were sampled and it is possible that differences between ‘Exposed’ and ‘Isolated’ billabongs, for example, would have been more marked if no flooding had occurred. However, the flooding that occurred during the sampling period cannot account for the lack of separation between billabongs on reaches that are not hydrologically connected such as the Ovens and Murray 1 reaches and the Ovens and Murray 2 reaches (Fig. 4a). Thus, the general pattern that emerges is that the location of a billabong, be it at a regional or local scale, does not appear to exert a strong influence over the water chemistry as recorded in this study. In contrast to the relatively weak spatial patterns in billabong water quality, the spatial patterns in diatom assemblages are strong. A fundamental distinction can be made between billabongs that are dominated by planktonic diatoms (predominantly Murray 2 and Murray 3 billabongs) and those dominated by attached and benthic taxa (predominantly billabongs located on the remaining river reaches). Previous studies of the distribution of cladoceran remains in most of the billabongs included in this data set also showed strong distinctions between billabongs with assemblages dominated by planktonic taxa and those dominated by plant-associated taxa (Ogden 2000). This pattern was attributed to feedback mechanisms acting to maintain planktonic dominance and limit growth of submerged plants in large, relatively deep
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billabongs, in accordance with the theory of alternative stable states (Scheffer et al. 1993; Ogden 2000). According to the theory of alternative stable states, a clear-water, macrophyte-dominated state will persist in shallow lakes under low nutrient conditions and a turbid, phytoplankton-dominated state will persist under high nutrient concentrations; however, either state can persist at intermediate nutrient concentrations as a result of feedback processes that act to maintain competitive dominance of macrophytes or phytoplankton (Scheffer et al. 1993, 2001). Billabongs are shallow lakes and, assuming they are subject to alternative stable states, very different diatom floras would be expected to occur in macrophyte-rich and macrophyte-poor billabongs even in the absence of strong differences in water quality, except in relation to light. By repeating CCA separately on the distinct groups of billabongs (Tables 4–6), the more subtle species responses to environmental gradients are drawn out. In this respect, the results of this study support the findings of a recent study carried out on stream and river diatoms in SE Australia that found strong regional differences in diatom communities between those of upland and lowland areas. Philibert et al. (2006) also found that even within these broad groupings, geospatial variables such as altitude, latitude and longitude remained important predictors of diatom distributions. Importantly, however, Philibert et al. (2006) interpreted the importance of these geospatial variables as an artefact of covariance with water quality variables—for example the strong east–west climatic and salinity gradients that exist in south east Australia. While such covariance is likely to have some importance in the case of billabong diatom assemblages— particularly with regard to the Goulburn billabongs—it appears that hydrology, billabong morphometry and biogeographic effects associated with reach-scale population dynamics are more important. A further contrast with the results from the Philibert et al. (2006) study is that diatom distributions in the billabongs in this data set appear to be more strongly influenced by TP than pH, EC and TN. TP was consistently shown to exert the strongest influence on diatom distribution within the reach groupings (Tables 4–6), supporting the notion that the apparent influence of pH and TN on diatom distributions in the full data set (Table 3) was due to the confounding of these variables with reach groups.
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A further factor that may have contributed to weak water quality–species relationships in the full data set is the low level of spatial, relative to temporal, variability in the water quality data. Low spatial variability means that the environmental gradients incorporated in the data set are short (Fig. 2) and this will result in less species turnover (Bennion et al. 1996). On the other hand, high temporal variability ensures that diatom assemblages are dominated by tolerant taxa and/or a mixture of taxa with a broad range in optima (Gell 1997). In combination, these effects will limit the strength of species–environment relationships. It is also possible that the combination of high temporal and low spatial variability in water quality has contributed to the relatively strong geographical distinctions in billabong diatom assemblages. High temporal variability in water quality means that conditions within individual billabongs are likely to become periodically unsuitable for specific taxa. Under these conditions, the abundance of taxa within individual billabongs may be more strongly influenced by the close proximity and sporadic hydrological connection to re-colonisation sources (i.e. nearby billabongs and the river) than by the absolute optima of competing taxa. In this way, subtle differences in the water quality of billabongs within certain reaches may be magnified to create quite distinct diatom assemblages. ANOVAs carried out on the dominant species within the Murray 2 and 3 reaches suggest that the abundance of Aulacoseira granulata is influenced by whether or not the billabong experiences regular connection to the mainstream, particularly within the Murray 2 reach. Given that A. granulata is the dominant planktonic alga in the Murray River below Lake Hume (Sullivan et al. 1988; Hotzel 1997), it is likely that this distinction reflects, at least in part, the direct input of this species from the river. Influx of riverine diatoms to floodplain lakes through hydrological connection was also observed by Hay et al. (2000) in the Mackenzie River Delta, and by Van den Brink et al. (1994) on the Rhine and Meuse Rivers. Aulacoseira granulata has a relatively high sinking rate and thus requires high turbulence to maintain position in the water column (Lund 1964; Kilham et al. 1986; Reynolds 1988). Studies of Murray River potamoplankton show that A. granulata is less abundant where turbulence is reduced, presumably as a result of settling (Hotzel and Croome 1996;
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Bormans and Webster 1999). Thus, the reduced abundance of A. granulata in the isolated billabongs of Murray 2 and Murray 3 reaches may reflect reduced riverine input and its competitive disadvantage under conditions where turbulence is low. Although connection to the main channel may be the most parsimonious explanation for the contrasting abundances of A. granulata in ‘Exposed’ and ‘Isolated’ billabongs, it remains possible that other factors such as water quality or depth may be important. Further studies are required to test these relationships, for example, through the use of sediment traps and direct sampling of plankton communities in ‘Exposed’ and ‘Isolated’ billabongs as well as in the river itself over a time series that incorporates periods when ‘Exposed’ billabongs are both disconnected and connected to the main channel. At this stage, however, with the evidence at hand, it seems likely that the sediments of ‘Exposed’ billabongs preserve elements of the mainstream diatom flora and so could provide a record of hydrological change (Hay et al. 2000; Michelutti et al. 2001) as well as changes to the broader river ecosystem.
Conclusions and implications for palaeolimnological study Although the results of this study indicate that pH, TN and TP are the most important water quality variables controlling diatom distribution in billabongs, the influence of pH and TN on diatom distribution appears to be secondary to whether or not a billabong is phytoplankton- or macrophyte-dominated or the river reach on which the billabong is located. The dichotomy between phytoplankton and macrophyte dominance means that billabongs of similar water quality can support very different diatom assemblages and hence a relatively small proportion of the variation in species assemblages can be attributed to water quality gradients. A high degree of temporal relative to spatial variability in the physical and chemical character of individual billabongs is also likely to contribute to the relatively weak species responses to water quality gradients. Distinctions between the assemblages of billabongs of different rivers and river reaches suggest that distribution is also confounded by hydrological and biogeographic factors.
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This study has provided a broad picture of the environmental variables, mechanisms and processes that drive the distribution of diatoms in billabongs within the study region. Many uncertainties remain, largely as a result of confounding effects that are inherent in the use of species distributions to inform on species preferences. Nevertheless, the information gained from this study will allow for these uncertainties to be addressed through more focused distributional and experimental studies. These patterns have several important implications for palaeolimnological studies. First, diatom-based transfer functions have been established for pH and EC using data from the region (Tibby et al. 2003, 2007; Tibby and Reid 2004; Philibert et al. 2006), the results of this study indicate that there may also be scope to develop a transfer function for reconstructing TP. Second, there may be value in developing separate transfer functions for phytoplankton- and macrophyte-dominated billabongs and for billabongs on different reaches. By separating phytoplanktonand macrophyte-dominated billabongs and different reaches, important sources of confounding in relation to habitat and biogeography can be eliminated. It is possible that these effects are of particular importance in floodplain lakes (e.g. Hay et al. 2000; Michelutti et al. 2001) because of the episodic hydrological connections that occur across water bodies of the same river reaches due to flooding. This issue needs to be further examined through spatially explicit hierarchical sampling of billabongs to identify the spatial scale at which the various potential drivers of diatom distributions (water quality, morphometry, population dynamics and hydrology) operate. Finally, the distribution of diatoms in billabongs of the lower Murray reaches suggests that key elements of the river flora appear to be preserved in billabong sediments. This greatly enhances the scope of reconstructions. The Murray River supports a large phytoplankton population (dominated by the diatom Aulacoseira granulata) that accounts for up to 84% of the primary productivity of the river (Gawne et al. 2007). Evidence that this phytoplankton assemblage is reflected in billabong sediments raises the possibility that changes in this community may be tracked through time. The rivers of the MurrayDarling system are widely held to have undergone profound ecological change as a result of changing land use and river regulation. However, much of the
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evidence for change is either anecdotal or suffers from a disturbing lack of temporal perspective (Thoms et al. 1999; Reid and Ogden 2006). The possibility that palaeolimnological approaches could offer empirical evidence of change within river systems extending over centuries is one that is well worth pursuing. Acknowledgements This research was supported by Australian Post-Graduate Research Awards provided to the authors, and by a research grant from the Murray-Darling Freshwater Research Centre. The School of Geography and Environmental Science, Monash University and the Department of Biogeography and Geomorphology, Australian National University provided field and lab support. The authors also thank the many landholders who allowed access to the billabongs on their properties, Damien Smith for tireless field assistance, Gerry Quinn for valuable statistical advice, and finally, Peter Kershaw and John Tibby for their helpful comments on earlier drafts.
References Battarbee RW (1986) Diatom analysis. In: Berglund BE (ed) Handbook of holocene palaeoecology and palaeohydrology. Wiley, Chichester, pp 527–568 Belbin L, McDonald C (1993) Comparing three classification strategies for use in ecology. J Veg Sci 4:341–348 Bennion H, Juggins S, Anderson NJ (1996) Predicting epilimnetic phosphorus concentrations using an improved diatom-based transfer function and its application to lake eutrophication management. Environ Sci Technol 30:2004–2007 Birks HJB, Line JM, Juggins S, Stevenson AC, ter Braak CJF (1990) Diatoms and pH reconstruction. Philos Trans R Soc Lond B Biol Sci 327:263–278 Borcard D, Legendre M, Drapeau P (1992) Partialling out the spatial component of ecological variation. Ecology 73:1045–1055 Bormans M, Webster IT (1999) Modelling the spatial and temporal variability of diatoms in the River Murray. J Plankton Res 21:581–598 Clarke KR, Warwick RM (1994) Change in marine communities: an approach to statistical analysis and interpretation. National Environment Research Council, Plymouth, pp 1–144 Cooper CM, McHenry JR (1989) Sediment accumulation and its effects on a Mississippi River oxbow lake. Environ Geol 3:33–37 Crabb P (1997) Murray-Darling basin resources. MurrayDarling Basin Commission, Canberra, pp 1–300 Dixit SS, Smol JP, Kingston JC, Charles DF (1992) Diatoms: powerful indicators of environmental change. Environ Sci Technol 26:23–33 Donnelly TH, Ford PW, McGregor D, Allen D (1999) Anthropogenic changes to a billabong in New South Wales. 1. Lagoon evolution and phosphorus dynamics. Mar Freshw Res 50:689–698
469 Eckblad JW, Peterson NL, Ostlie K (1977) The morphometry, benthos and sedimentation rates of a floodplain lake in Pool 9 of the Upper Mississippi River. Am Midl Nat 97:433–443 Erskine W, McFadden C, Bishop P (1992) Alluvial cutoffs as indicators of former channel conditions. Earth Surf Process Landforms 17:23–37 Faith DP, Humphrey CL, Dostine PL (1991) Statistical power and BACI designs in biological monitoring: comparative evaluation of measures of community dissimilarity based on benthic macroinvertebrate communities in Rockhole Mine Creek, Northern Territory, Australia. Aust J Mar Freshw Res 42:589–602 Gasse F, Juggins S, Ben Khelifa L (1995) Diatom-based transfer functions for inferring past hydrochemical characteristics of African lakes. Palaeogeogr Palaeoclimatol Palaeoecol 117:31–54 Gawne B, Merrick C, Williams DG, Rees G, Oliver R, Bowen T, Treadwell S, Beattie G, Ellis I, Frankenberg J, Lorzen Z (2007) Patterns of primary and heterotrophic productivity in an arid lowland river. River Res Appl 23:1070– 1087 Gell PA (1997) The development of a diatom database for inferring lake salinity, Western Victoria, Australia: towards a quantitative approach for reconstructing past climates. Aust J Bot 45:389–423 Gell P, Tibby J, Fluin J, Leahy P, Reid M, Adamson K, Bulpin S, MacGregor A, Wallbrink P, Hancock G, Walsh B (2005a) Accessing limnological change and variability using fossil diatom assemblages, south-east Australia. River Res Appl 21:257–269 Gell PA, Bulpin S, Wallbrink P, Hancock G, Bickford S (2005b) Tareena Billabong – a palaeolimnological history of an ever-changing wetland, Chowilla Floodplain, lower Murray-Darling basin, Australia. Mar Freshw Res 56:441–456 Germain H (1981) Flores des diatomees eaux douces et saumatres. Societe Nouvelle des Editions Boubee, Paris, pp 1–444 Hay MB, Michelutti N, Smol JP (2000) Ecological patterns of diatom assemblages from Mackenzie Delta lakes, Northwest Territories, Canada. Can J Bot 78:19–33 Hotzel G (1997) Long-term observations on the phytoplankton in a large river (River Murray, Australia). Phycologia 36:41–41 Hotzel G, Croome R (1996) Population dynamics of Aulacoseira granulata (EHR.) SIMONSON (Bacillariophyceae, Centrales), the dominant alga in the Murray River, Australia. Arch Hydrobiol 136:191–215 Kilham P, Kilham SS, Hecky RE (1986) Hypothesized resource relationships among African planktonic diatoms. Limnol Oceanogr 31:1169–1181 Krammer K, Lange-Bertalot H (1986) Susswasserflora von Mitteleuropa. Bacillariophyceae i Teil Naviculaceae. Gustav Fischer Verlag, Stuttgart, 876 pp Krammer K, Lange-Bertalot H (1988) Susswasserflora von Mitteleuropa. Bacillariophyceae ii Teil Bacillariaceae, Epithemiaceae, Surirellaceae. Gustav Fischer Verlag, Stuttgart, 576 pp Krammer K, Lange-Bertalot H (1991a) Susswasserflora von Mitteleuropa. Bacillariophyceae iii Teil Centrales,
123
470 Fragilariaceae, Eunotiaceae. Gustav Fischer Verlag, Stuttgart, 596 pp Krammer K, Lange-Bertalot H (1991b) Susswasserflora von Mitteleuropa. Bacillariophyceae iv Teil Achnanthaceae. Gustav Fischer Verlag, Stuttgart, 437 pp Leahy PJ, Kershaw AP, Tibby J, Heinjis H (2005) A palaeoecological reconstruction of the impact of European settlement on Bolin Billabong, Yarra River floodplain, Australia. River Res Appl 21:131–149 Lewis GW, Lewin J (1983) Alluvial cutoffs in Wales and the Borderlands. Special Publications of the International Association of Sedimentologists, pp 145–154 Lund JWG (1964) Primary production and periodicity of phytoplankton. Verhandlung Int Vereinigung Limnol 15:37–56 Maheshwari BL, Walker KF, McMahon TA (1995) Effects of regulation on the flow regime of the River Murray, Australia. Regul Rivers Res Manage 10:15–38 Michelutti N, Hay MB, Marsh P, Lesack L, Smol JP (2001) Diatom changes in Lake Sediments from the Mackenzie Delta, NWT, Canada: paleohydrological applications. Arct Antarct Alp Res 33:1–12 Ogden RW (1996) The impacts of farming and river regulation on billabongs of the southeast Murray Basin, Australia. Unpublished PhD thesis, Australian National University Ogden RW (2000) Modern and historical variation in aquatic macrophyte cover of billabongs associated with catchment development. Regul Rivers Res Manage 16:497–512 Ogden RW, Spooner N, Reid MA, Head J (2001) Sediment dates with implications for the age of the conversion from palaeochannel to modern fluvial activity on the Murray River and tributaries. Quatern Int 83–85:195–209 Patrick R, Reimer CW (1966) The diatoms of the United States, vol I. Academy of Natural Science, Philadelphia Patrick R, Reimer CW (1975) The diatoms of the United States, vol II. Academy of Natural Science, Philadelphia Philibert A, Gell P, Newall P, Chessman B, Bate N (2006) Development of diatom-based tools for assessing stream water quality in south-eastern Australia: assessment of environmental transfer functions. Hydrobiologia 572: 103–114 Pressey RL (1986) Wetlands of the River Murray below Lake Hume. River Murray Commission, Canberra, 134 pp Rang MC, Schouten CJ (1989) Evidence for historical heavy metal pollution: the Meuse. In: Petts GE (ed) Historical change of large alluvial rivers: Western Europe. Wiley, London, pp 127–142 Reid MA (1997) A diatom-based palaeoecological study of the dynamics of Goulburn River billabongs, southeastern Australia. Unpublished PhD thesis, Monash University Reid MA (2002) A diatom-based palaeoecological study of two billabongs on the Goulburn River floodplain, southeast Australia. In: John J (ed) Proceedings of the15th international diatom symposium. Gantner Verlag, Ruggell, pp 237–253
123
J Paleolimnol (2009) 41:453–470 Reid MA, Ogden RW (2006) Trend, variability or extreme event? The importance of long-term perspectives in river ecology. River Res Appl 22:167–177 Reid MA, Fluin J, Ogden RW, Tibby J, Kershaw AP (2002) Long-term perspectives on human impacts on floodplainriver ecosystems, Murray-Darling Basin, Australia. Verhandlung Int Vereinigung Limnol 28:710–716 Reid MA, Sayer CD, Kershaw AP, Heijnis H (2007) Palaeolimnological evidence for submerged plant loss in a floodplain lake associated with accelerated catchment soil erosion (Murray River, Australia). J Paleolimnol 38:191–208 Reynolds CS (1988) Functional morphology and adaptive strategies of freshwater phytoplankton. In: Sandgren CD (ed) Growth and reproductive strategies of freshwater phytoplankton. Cambridge University Press, Cambridge, pp 388–433 Scheffer M, Hosper SH, Meijer ML, Moss B, Jeppesen E (1993) Alternative equilibria in shallow lakes. Trends Ecol Evol 8:275–279 Scheffer M, Carpenter S, Foley JA, Folke C, Walker B (2001) Catastrophic shifts in ecosystems. Nature 413:591–596 Schonfelder I, Gelbrecht J, Schonfelder J, Steinberg CEW (2002) Relationships between littoral diatoms and their chemical environment in northeastern German lakes and rivers. J Phycol 38:66–82 Sullivan C, Saunders J, Welsh D (1988) Phytoplankton of the River Murray: review of monitoring 1980 to 1985. Murray-Darling Basin Commission, Canberra, p 61 Thoms MC, Ogden RW, Reid MA (1999) Establishing the condition of lowland floodplain rivers: a palaeo-ecological approach. Freshw Biol 41:407–423 Tibby J, Reid MA (2004) A model for inferring past conductivity in low salinity waters derived from Murray River (Australia) diatom plankton. Mar Freshw Res 55:597–607 Tibby J, Reid MA, Fluin J, Hart BT, Kershaw AP (2003) Assessing long-term pH change in an Australian river catchment using monitoring and palaeolimnological data. Environ Sci Technol 37:3250–3255 Tibby J, Gell PA, Fluin J, Sluiter IRK (2007) Diatom-salinity relationships in wetlands: assessing the influence of salinity variability on the development of inference models. Hydrobiologia 591:207–218 Van den Brink FWB, Van Katwijk MM, Van der Velde G (1994) Impact of hydrology on phyto- and zooplankton community composition in floodplain lakes along the Lower Rhine and Meuse. J Plankton Res 16:351–373 Wolfe BB, Karst-Riddoch TL, Vardy SR, Falcone MD, Hall RI, Edwards TWD (2005) Impacts of climate and river flooding on the hydro-ecology of a floodplain basin, Peace-Athabasca Delta, Canada since AD 1700. Quat Res 64:147–162 Wolfe BB, Hall RI, Last WM, Edwards TWD, English MC, Karst-Riddoch TL, Paterson A, Palmini R (2006) Reconstruction of multi-century flood histories from Oxbow Lake sediments, Peace-Athabasca Delta, Canada. Hydrol Process 20:4131–4153
