Macroinvertebrate responses to dry
season and antecedent flow in highly
seasonal streams and rivers of the
wet-dry tropics, Northern Territory
Catherine Leigh
Australian Rivers Institute, Griffith University
Low flows report series, June 2012
© Commonwealth of Australia 2012
This work is copyright.
Apart from any use as permitted under the Copyright Act 1968, no part may be reproduced by
any process without prior written permission.
Requests and enquiries concerning reproduction and rights should be addressed to the
Communications Director, National Water Commission, 95 Northbourne Avenue, Canberra
ACT 2600 or email bookshop@nwc.gov.au.
Online/print: ISBN: 978-1-921853-96-8
Published by the National Water Commission
95 Northbourne Avenue
Canberra ACT 2600
Tel: 02 6102 6000
Email: enquiries@nwc.gov.au
Date of publication: June 2012
An appropriate citation for this report is:
Leigh C 2012, Macroinvertebrate responses to dry season and antecedent flow in highly
seasonal streams and rivers of the wet-dry tropics, Northern Territory, National Water
Commission, Canberra.
Disclaimer
This paper is presented by the National Water Commission for the purpose of informing
discussion and does not necessarily reflect the views or opinions of the Commission.
NATIONAL WATER COMMISSION — Low flows report series
iii
Low flows report series
This paper is part of a series of works commissioned by the National Water Commission on
key water issues. This work has been undertaken by Griffith University through the Tropical
Rivers and Coastal Knowledge research hub, on behalf of the National Water Commission.
NATIONAL WATER COMMISSION — Low flows report series
iv
Contents
Contents
Executive summary
Report context
1. Introduction
2. Methods
2.1 Macroinvertebrate data
2.2 Environmental and water quality data
2.3 Hydrological data
2.4 Data preparation
2.5 Data analysis
3. Results
3.1 Macroinvertebrate assemblages
3.2 Effects of season and year in sand habitats (Early AUSRIVAS dataset)
3.3 Effects of season and year in edge habitats (Early AUSRIVAS dataset)
3.4 Antecedent flow history and macroinvertebrate traits and diversity
4. Discussion
4.1 Conclusion
Shortened forms
References
iii
viii
x
1
3
3
3
4
4
12
15
15
15
21
28
40
42
43
44
Tables
Table 1: Flow metrics calculated for different antecedent periods relative to each
sample ................................................................................................................................ 9
Table 2: Statistical models used for PERMANOVA to test the null hypothesis of
no difference in macroinvertebrate assemblage composition between
seasons (early v. late dry) or years (1995 v. 1996) .......................................................... 13
Figures
Figure 1: ‘Reference’ sites in the Northern Territory used in the analysis of
macroinvertebrate assemblage composition in sand habitats, with major
river basins indicated .......................................................................................................... 5
Figure 2: Reference sites in the Northern Territory used in the analysis of
macroinvertebrate assemblage composition in edge habitats, with major
river basins indicated .......................................................................................................... 6
Figure 3: AUSRIVAS sites in Darwin Harbour catchment, with the four sites used
in the present study indicated ............................................................................................. 7
Figure 4: Mean daily flow (m 3 s-1) recorded at gauging stations in close proximity
to the Early AUSRIVAS sampling sites, with macroinvertebrate sample dates
at edge (E) and sand (S) habitats indicated by arrows .................................................... 10
Figure 5: Mean daily flow (m 3 s-1) recorded at gauging stations in close proximity
to the Darwin Streams sampling sites, with macroinvertebrate sample dates
at edge (E) habitats indicated by arrows .......................................................................... 11
Figure 6: Principal Coordinate Analysis (PCO) ordination of macroinvertebrate
assemblage similarities among sand habitat samples collected in the early
(green upright triangles, lotic) and late dry season (blue upside down
triangles, lentic) in 1995 from eight sites in the Daly River basin (DA), with
vectors showing taxa with Spearman correlations > 0.40 presented
separately (circle represents a vector correlation of 1) .................................................... 18
Figure 7: Box and whisker plots of water quality parameters and
macroinvertebrate metrics for sand habitats from eight sites in the Daly River
basin that were lotic in the early dry season of 1995 but lentic in the late dry
season of 1995 ................................................................................................................. 19
NATIONAL WATER COMMISSION — Low flows report series
v
Figure 8: Environmental parameters and macroinvertebrate metrics with
significant Spearman correlations for sand habitats from eight sites in the
Daly River basin in 1995 that were lotic in the early dry season (open
diamonds) but lentic in the late dry season (closed diamonds) ....................................... 20
Figure 9: Principal Coordinate Analysis (PCO) ordination of macroinvertebrate
assemblage similarities among lentic edge habitat samples collected across
multiple river basins, with vectors showing taxa with Spearman correlations
> 0.40 (circle represents a vector correlation of 1) ........................................................... 22
Figure 10: Box and whisker plots of water quality parameters and
macroinvertebrate metrics for edge habitats in multiple river basins that were
lentic in 1995 .................................................................................................................... 23
Figure 11: Environmental parameters and macroinvertebrate metrics with
significant Spearman correlations for lentic edge habitats (from across
multiple river basins) in 1995 ............................................................................................ 24
Figure 12: Principal Coordinate Analysis (PCO) ordination of macroinvertebrate
assemblage similarities among 11 edge habitat samples collected in the
early (green upright triangles, lotic) and late dry season (blue upside down
triangles, lentic) in 1995 from multiple river basins, with vectors showing taxa
with Spearman correlations > 0.40 presented separately (circle represents a
vector correlation of 1) ...................................................................................................... 26
Figure 13: Box and whisker plots of water quality parameters and
macroinvertebrate metrics for edge habitats that were lotic in the early dry
season of 1995 but lentic in the late dry season of 1995, sampled across
multiple river basins .......................................................................................................... 27
Figure 14: Water quality parameters and macroinvertebrate metrics with
significant Spearman correlations for edge habitats that were lotic in the
early dry season (open diamonds) but lentic in the late dry season (closed
diamonds), sampled across multiple river basins in 1995 ................................................ 27
Figure 15: Total Kjeldahl nitrogen concentration versus Trichoptera family
richness in edge habitats (sampled across multiple river basins) in 1996 ....................... 28
Figure 16: Principal Coordinate Analysis (PCO) ordinations of macroinvertebrate
assemblage similarities among 23 sand (left panel) and 31 edge habitat
samples (right panel) collected in the early and late dry seasons from
multiple river basins in 1995 and 1996 ............................................................................. 31
Figure 17: Conceptualisation of significant Spearman correlations between
macroinvertebrate, water quality and environmental characteristics of
samples from sand habitats across multiple river basins and antecedent flow
metrics .............................................................................................................................. 32
Figure 18: Conceptualisation of significant Spearman correlations between
season-to-season differences macroinvertebrate and water quality
characteristics of samples from sand habitats across multiple river basins
and differences in antecedent flow metrics ...................................................................... 33
Figure 19: Conceptualisation of significant Spearman correlations between
macroinvertebrate, water quality and environmental characteristics of
samples from edge habitats across multiple river basins and antecedent flow
metrics .............................................................................................................................. 34
Figure 20: Conceptualisation of significant Spearman correlations between
season-to-season differences in macroinvertebrate and water quality
characteristics of samples from edge habitats across multiple river basins
and differences in antecedent flow metrics ...................................................................... 35
Figure 21: Principal Coordinate Analysis (PCO) ordinations of macroinvertebrate
assemblage similarities among 24 edge habitat samples collected in the
early dry season from four sites in the Darwin Harbour catchment ................................. 37
Figure 22: Conceptualisation of significant Spearman correlations between
macroinvertebrate characteristics of samples from edge habitats in the
Darwin Harbour catchment and antecedent flow metrics ................................................. 38
Figure 23: Conceptualisation of significant Spearman correlations between yearto-year differences in macroinvertebrate characteristics of samples from
edge habitats in the Darwin Harbour catchment and differences in
antecedent flow metrics .................................................................................................... 39
NATIONAL WATER COMMISSION — Low flows report series
vi
Acknowledgements
This report was completed with the support of Charles Darwin University, as part of the
Tropical Rivers and Coastal Knowledge (TRaCK) research hub. TRaCK receives major
funding for its research through the Australian Government’s Commonwealth Environment
Research Facilities initiative, the Australian Government’s Raising National Water Standards
Program, Land and Water Australia, the Fisheries Research and Development Corporation
and the Queensland Government’s Smart State Innovation Fund.
The author thanks the Northern Territory Department of Natural Resources, Environment, the
Arts and Sport (NRETAS) for providing the daily flow and AUSRIVAS sample data, and Rob
Rolls for assistance with the PERMANOVA+ add-on in PRIMER.
NATIONAL WATER COMMISSION — Low flows report series
vii
Executive summary
Low flows are important to riverine ecosystems, particularly in systems that experience
extended dry periods, where low flows can constitute a significant component of the flow
regime and recent flow history.
For rivers and streams in Australia’s wet-dry tropics, our understanding of seasonal changes
in macroinvertebrate assemblages and their responses to natural periods of extended low
flow is limited.
This report explores existing datasets to better understand macroinvertebrates in the wet-dry
tropics, which may be used to support future water resource planning.
AUSRIVAS data from undeveloped streams and rivers across the wet-dry tropics of the
Northern Territory were investigated to explore the effects of low flow and the dry season on
macroinvertebrate assemblage composition, diversity and biological traits.
Four main hypotheses were investigated:
1) There would be a difference in the macroinvertebrate assemblage composition of sites
between early and late dry seasons (within and/or across years).
2) There would be a difference in the water quality and habitat-scale environmental
characteristics of sites between early and late dry seasons (within and/or across years).
3) Water quality and environmental characteristics of sites would be associated with
assemblage diversity and biological traits.
4) Antecedent flow characteristics of the most recent dry and wet seasons would be
associated with assemblage diversity and biological traits in the dry season.
Family-level macroinvertebrate data from early AUSRIVAS sampling events (1995 and 1996)
were collected from sand and edge habitats across multiple river basins. Data from these
habitat groups were analysed separately, and within each group, data were further separated
into four groups – those that were lentic (still water) in both early and late dry seasons for both
years of sampling; those that were lotic (flowing water) in both seasons and years; those that
changed from lotic to lentic between seasons in 1995; and those that changed from lotic to
lentic between seasons in 1996. Relationships between assemblages (composition, diversity
and biological traits) and both contemporaneous water quality data and antecedent flow
metrics were explored.
In addition, genus-level macroinvertebrate data collected in the early dry seasons from 2001
to 2009 from edge habitats of four streams in the Darwin Harbour catchment were used to
further explore relationships between antecedent flow history and macroinvertebrate
assemblage patterns.
Macroinvertebrate assemblages from across the Northern Territory sampled in the early dry
season tended to be more biodiverse, and the taxa more sensitive and more rheophilous
(preferring flowing water) than those sampled in the late dry season. The waters of the sand
and edge habitats harbouring the macroinvertebrates were also often cooler, more oxic and
less turbid and nutrient-rich in the early dry season than towards the end of the dry season.
There were also significant changes in assemblage composition between the early and late
dry seasons, particularly when habitats were in flow during the early dry season but lentic
during the late dry season. These general findings supported the hypotheses that differences
in assemblage and habitat-scale environmental characteristics of sites would exist from the
early and late dry seasons.
NATIONAL WATER COMMISSION — Low flows report series
viii
Causal mechanisms of assemblage responses to low flows and the dry season were not
explicitly examined in this study. In addition, the ability to draw conclusions about these
mechanisms was restricted by the confounding effects of river basin and multiple stressors
(low-flow hydrology as well as physical and chemical changes to habitat) on assemblage
characteristics. Future studies may need to examine low-flow-ecology relationships within
particular river basins and/or use a filters approach to control for variation in the physical and
chemical environment among streams, providing sufficient data are available.
Three facets of the dry season and antecedent hydrology appear to be important direct and
indirect drivers of dry season assemblage composition, diversity and biological traits in the
highly seasonal Northern Territory streams and rivers examined. These are: the length (or
duration) of the dry season before sampling, cease-to-flow events, and flow magnitude on the
day of sampling.
Dry season assemblages sampled towards the end of the dry season, especially from lentic
habitats that tend to be flowing during the early dry season, or those sampled on days of
lower discharge, may be expected to have fewer taxa, and be characterised by nonrheophilous and tolerant taxa, than assemblages sampled earlier in the dry season or on days
of higher discharge.
While macroinvertebrate fauna of these highly seasonal streams and rivers are no doubt welladapted to regular and natural periods of extended low flow, human modification of the dry
season (low) flow regime may alter the resistance and resilience of assemblages to low-flow
events and their duration such that the early wet season recovery of fauna may no longer be
so reliable.
NATIONAL WATER COMMISSION — Low flows report series
ix
Report context
This report is part of a larger series of reports produced for the National Water Commission’s
Low Flow Ecological Response and Recovery Project (Figure S1). This report presents one of
11 hydro-ecological case studies. The purpose of the case studies is to test hypotheses that
relate ecological process and function and biological traits to key hydrological measures that
are affected by low flows. A summary of the findings in this report and the other case studies
are contained in Synthesis of case studies quantifying ecological responses to low flows
(Marsh et al. 2012).
Guidance on ecological response and hydrological modelling for low-flow
water planning
Low-flow hydrological classification of Australia
Review of literature quantifying ecological responses to low flows
Early warning, compliance and diagnostic monitoring of ecological
responses to low flows
Synthesis of case studies quantifying ecological responses to low flows
Figure S1: Context of reports produced for the Low Flow Ecological Response and Recovery
Project. Each circle represents the location of individual case studies and the size of each
circle represents the spatial extent of each case study.
NATIONAL WATER COMMISSION — Low flows report series
x
1. Introduction
Low flows play an important role in structuring riverine ecosystems (Bunn & Arthington 2002;
Poff et al. 2010; Rolls et al. in prep). In systems that experience extended dry periods, low
flows can constitute a significant temporal component of the flow regime and recent flow
history (McMahon & Finlayson 2003). This is true for river systems across much of northern
Australia, where many are unregulated and human disturbance of rivers and catchments is
minimal compared with systems in Australia’s south-east. In the wet-dry tropics, which covers
much of northern Australia, river flow is primarily event-driven (Petheram et al. 2008),
characterised annually by little to no flow during the dry season and high magnitude flows and
hydrological connectivity in the wet season (Leigh & Sheldon 2008). Here, low flows
(including zero flows) are a natural phenomenon of the dry season.
Despite recent (and renewed) interest in the effects of low flow on river ecosystems (in
Australia, see Chessman et al. 2008; Finn et al. 2009; Perry & Bond 2009; and internationally,
see Miller et al. 2007; Zeug & Winemiller 2008; Wood et al. 2010) our fundamental
understanding of the ecological responses to low flow is lacking (Dewson et al. 2007; Rolls et
al. in prep).
For Australia’s wet-dry tropics, current understanding of seasonal changes in
macroinvertebrate assemblages of rivers and streams and their response to natural periods of
extended low flow is based mainly on studies of Magela Creek and other waterbodies in the
East Alligator River basin of the Northern Territory. Marchant (1982) found that over one year,
macroinvertebrate richness and abundance of shallow pool assemblages peaked around the
late wet to early dry season, declining to minima by the end of the dry season (patterns were
similar in the deeper, main-channel pools, but less pronounced). Changes were associated
with the growth of macrophytes during the wet season, which were thought to provide food
and shelter for macroinvertebrates. In a later study that included some of the same sampling
locations, similar patterns were also found, with macroinvertebrate diversity decreasing over
the dry season but rapidly recovering in the early wet season with the resumption of flow
(Outridge 1988). Richness and abundances were associated with the presence of
macrophytes, but the influx of organic detritus with the early wet season flows was considered
to be more important as a food source for macroinvertebrates and, as such, was supporting
biodiverse assemblages at that time of year. Diversity metrics were also correlated with
waterbody depth, water temperature, turbidity, conductivity and chlorophyll, indicative of the
multiple, possibly interrelated factors that vary seasonally with climate and river flow. In a
study of the post-dry-season recolonisation of macroinvertebrate assemblages in the
ephemeral main stem of Magela Creek, Paltridge et al. (1997) found that richness and
abundance generally increased early in the wet season, resulting from recolonisation via drift
with the onset of flow and the re-emergence of taxa from their dry season refuges in the
substrata.
The prevalence of a dry season decline in macroinvertebrate diversity, wet season recovery
in response to seasonal flow patterns, and concurrent changes in water quality and
biophysical habitat across all rivers and streams of the wet-dry tropics (and across years) is
unknown (although responses are likely to be different in rivers with different flow regimes,
such as perennial versus seasonal or ephemeral rivers). Fortunately, datasets are available
that may be interrogated to help explore the responses of riverine biota to seasonal and low
flows in this region, including macroinvertebrate data collected as part of the Australian Rivers
Assessment Scheme (AUSRIVAS, http://www.ausrivas.canberra.edu.au/). For the present
study, AUSRIVAS data from undeveloped streams and rivers across the wet-dry tropics of the
Northern Territory were investigated to explore the effects of low flow and the dry season on
macroinvertebrate assemblage composition, diversity and biological traits.
NATIONAL WATER COMMISSION — Low flows report series
1
Four main hypotheses were investigated:
1) There would be a difference in the macroinvertebrate assemblage composition of sites
between early and late dry seasons (within and/or across years).
2) There would be a difference in the water quality and habitat-scale environmental
characteristics of sites between early and late dry seasons (within and/or across years).
3) Water quality and environmental characteristics of sites would be associated with
assemblage diversity and biological traits.
4) Antecedent flow characteristics of the most recent dry and wet seasons would be
associated with assemblage diversity and biological traits in the dry season.
NATIONAL WATER COMMISSION — Low flows report series
2
2. Methods
2.1 Macroinvertebrate data
AUSRIVAS operates under the Australian National River Health Program and uses a
standardised and rapid approach to monitor and assess the ecological health of Australian
rivers.
Macroinvertebrate AUSRIVAS data were provided by the Northern Territory Department of
Natural Resources, Environment, the Arts and Sport (NRETAS). Macroinvertebrates were
collected according to the Northern Territory AUSRIVAS protocol (Lloyd & Cook 2001) in the
early and late dry seasons of 1995 and 1996 from multiple streams and rivers that eventually
flow into the Timor Sea and Gulf of Carpentaria, and in the early dry seasons of 2001 to 2004,
2007 and 2009 from four streams in the Darwin Harbour catchment (figures 2, 3 and 4).
The samples from 1995 to 1996 were collected twice a year: in the early dry season (in May,
June, July or August) and in the late dry season (in September, October or November). For
each site, sampling dates were separated by at least three months, which was considered
sufficient to treat samples from the same site as independent given there can be rapid
turnover in macroinvertebrate communities. Macroinvertebrates collected from 2001 to 2009
were collected in April, May or June. The 1995–96 data is referred to in this report as the
Early AUSRIVAS dataset and the 2001–09 data as the Darwin Streams dataset.
Macroinvertebrates were collected from a total length of 10 m of edge and/or sand habitats of
sites (reaches of approximately 100 m in length defined in the Early AUSRIVAS dataset as
‘reference’, ‘test’, ‘floodplain or offstream billabong’, ‘waterfall plungepool’ or ‘poor habitat’).
Edge habitats are near-vertical edges of rivers and streams, ideally with abundant root
material and usually an associated pool. The adjacent water has minimal velocity and the
water depth of the sampled edge is 0.3 m or deeper. Sand habitats are sand beds away from
high-flow areas and without a thick cover of detritus or algae. Macroinvertebrates were
collected from edge and sand habitats using hand nets (250 μm mesh) and preserved in 70
per cent aqueous ethanol. The two habitats (sand and edge) were analysed separately.
In the laboratory, macroinvertebrate samples were sub-sampled using a modified subsampling box (Marchant 1989) until 200 animals were identified. Adults and larvae of the
same taxon were combined numerically. Microcrustacea (ostracods, copepods and
cladoccerans), Cnidaria, Nematophora and Collembola were not included in the 200 count.
Macroinvertebrates from the Early AUSRIVAS dataset were identified to the family level of
taxonomic resolution except for Nematoda (phylum), Oligochaeta (class), Acarina and
Conchostraca (order) and Chironomidae (subfamily). Those from the Darwin Streams dataset
were identified to genus except for Nematoda (phylum), Oligochaeta and Collembola (class),
Odonata (suborder), Pyralidae, Neuroptera and some Coleoptera, Diptera and Hemiptera
(family). Taxonomic nomenclature of the original datasets was retained.
2.2 Environmental and water quality data
Macroinvertebrate data from the Early AUSRIVAS dataset were accompanied by nonbiological data associated with several spatial scales. Large-scale descriptors of the
environment included river basin, biogeographic region, altitude (masl), stream order (1–7),
distance from source (km) and catchment area (km 2). Reach scale descriptors included
proportions of different habitat types within the sampled reach: sand and silt, gravel rock bed,
macrophytes, riffle, snag and pool. Habitat-scale descriptors included mean (water) depth
NATIONAL WATER COMMISSION — Low flows report series
3
(AHDE, m), mean stream width (MEWI, m), current speed [minimum (MICS), maximum
(MACS) and mean (AVCS), m s-1], proportions of different material in the substrate (bedrock,
boulder, cobble, pebble, gravel, sand and silt). Water quality parameters, spot measured at
the habitat scale, included pH, electrical conductivity (COND, mS cm -1), turbidity (TURB,
NTU), dissolved oxygen (DO, mg L-1), temperature (TEMP, °C), alkalinity (as CaCo3, mg L-1),
total oxidised nitrogen (nitrate plus nitrite as nitrogen, NOx, mg L -1), total Kjeldahl nitrogen
(TKN, mg L-1), filterable reactive phosphorus (FRP, mg L-1) and total phosphorus (TP, mg L-1).
Specifics of sampling methods and laboratory techniques, including detection limits, are
provided in Lloyd & Cook (2001).
2.3 Hydrological data
Mean daily flow data (MDF, m 3 s-1) were available from gauging stations on relevant rivers
and in close proximity to the macroinvertebrate sampling sites. However, not all sites had
associated gauging stations or flow data recorded before each sampling occasion. For many
sites, the associated gauging stations also had substantive periods of missing data from their
records in the long-term (15-year) period before macroinvertebrate sampling. Therefore, flow
metrics were only calculated for the most recent wet and dry seasons relative to samples (i.e.
within one year of the macroinvertebrate sample date), and only for sites with associated
gauging stations where the applicable period of MDF data was available.
2.4 Data preparation
2.4. 1 Effects of season and year on macroinvertebrate
assemblages: site selection and sample groups
As there were multiple site types in the Early AUSRIVAS dataset, analyses were restricted to
those defined as ‘reference’. While this reduced the total number of records that could be
analysed, potential effects of site type on variation in macroinvertebrate assemblages were
reduced (akin to applying an environmental filter, sensu Poff 1997). Here, ‘reference’ refers to
the initial set of sites used to develop predictive models for the Northern Territory AUSRIVAS.
In addition, only sites that were sampled in both seasons (early and late dry) and years (1995
and 1996) were included in analyses (except for those involving flow metrics for which a
different set of sites were used – see below), as the effect of late versus dry season on
macroinvertebrate assemblages was the main interest of this research.
Initial exploration of the Early AUSRIVAS data showed the modal current speed in sand and
edge habitats was zero (most samples were collected from lentic habitats). When samples
were collected from lotic habitats, the maximum current speed was 0.49 m s -1 in sand and
0.71 m s-1 in edges. Previous research has shown the lotic or lentic nature of waterbodies in
northern Australian rivers has a major effect on macroinvertebrate assemblage composition
and diversity (Leigh & Sheldon 2009). Therefore, it was likely an analysis of the effect of
season (early versus late) on the Northern Territory macroinvertebrate assemblage data may
be confounded by flow status if not taken into account. Therefore, for each habitat type, sites
were separated into four groups: those that were lentic in both seasons and years of
sampling; those that were lotic in both seasons and years; those that changed from lotic to
lentic between seasons in 1995; and those that changed from lotic to lentic between seasons
in 1996. Data within each of these groups were analysed separately.
In sand habitats (Figure 2), four sites (each in a different river basin) were lotic in both
seasons and years (16 samples in total), 32 sites across nine river basins were lentic in both
seasons and years (64 samples in total), and eight sites within the Daly River basin were lotic
NATIONAL WATER COMMISSION — Low flows report series
4
in the early dry season of 1995 but lentic in the late dry season of 1995 (16 samples in total).
These were the three groups of samples used to investigate the effect of season and year on
macroinvertebrate assemblages in sand habitats and are referred to in this case study as
Lotic Sand, Lentic Sand and Flow Change (1995) Sand respectively.
In edge habitats (Figure 3), three sites were lotic in both seasons and years (12 samples in
total), 42 sites across 13 river basins were lentic in both seasons and years (168 samples in
total), 11 sites across eight river basins changed from lotic to lentic between seasons in 1995
(22 samples in total), and 10 sites across five river basins were lotic in the early dry season
but lentic in the late dry season of 1996 (20 samples in total). The group of three lotic sites did
not provide enough data for analyses, and so only the latter three groups of edge habitat
samples were used in analyses. These will be referred to as Lotic Edge, Lentic Edge, Flow
Change (1995) Edge and Flow Change (1996) Edge respectively.
For the Darwin Streams dataset, all samples from all four sites were used together in
analyses (Figure 4). Macroinvertebrates in these sites were collected from edge habitats only.
Adelaide (AD) Mary (MY)
South Alligator (SA)
East Alligator
(EA)
Goyder (GY)
12 S
"
Finniss
(FN)
#
"
"
" "
"
"
# #
"
14 S
#
"
"
"
Daly (DA)
Keep (KP)
"
"
Roper (RP)
16 S
"
""
Victoria (VC)
Robinson (RB)
18 S
130 E
132 E
134 E
136 E
Figure 1: ‘Reference’ sites in the Northern Territory used in the analysis of macroinvertebrate
assemblage composition in sand habitats, with major river basins indicated
Notes: Closed squares show sites for which the sand habitats were lentic in both sampling periods (early and late dry
season) and both years (1995 and 1996); closed triangles show sand habitats that were lotic in both seasons and
years; and closed circles show sand habitats that were lotic in the early dry season 1995 but lentic in the late dry
season 1995.
NATIONAL WATER COMMISSION — Low flows report series
5
128°0'0"E
10°0'0"S
130°0'0"E
132°0'0"E
134°0'0"E
Melville
Island (ML) Adelaide (AD) Mary (MY)
136°0'0"E
138°0'0"E
10°0'0"S
South Alligator (SA)
Darwin
Harbour
(DW)
East Alligator Goyder (GY)
(EA)
! ))
12 S
12°0'0"S
Finniss
(FN)
!()
!
!( ) ) !( )
)) )
!(
)
!( !(!() ) )
)
!
!(
14 S
14°0'0"S
!)
!
)
)
16 S
16°0'0"S
)
)
!(
)
(!
)
Daly (DA)
)
)
)
)
Keep (KP)
12°0'0"S
!
)
14°0'0"S
!
)
))
)
)
))
)
)
Roper (RP)
16°0'0"S
)
)
)
))
))
Victoria (VC)
Robinson (RB)
18 S
18°0'0"S
130 E
20°0'0"S
132 E
134 E
18°0'0"S
136 E
20°0'0"S
Figure 2: Reference sites in the Northern Territory used in the analysis of macroinvertebrate
assemblage composition in edge habitats, with major river basins indicated
Notes: Open squares show sites for which the edge habitats were lentic in both sampling periods (early and late dry
season) and both years (1995 and 1996); closed circles show edge habitats that were lotic in the early dry season
1995 but lentic in the late dry season 1995; and open circles show edge habitats that were lotic in the early dry
22°0'0"S
season 1996 but lentic in the late dry season 1996.
22°0'0"S
24°0'0"S
24°0'0"S
26°0'0"S
26°0'0"S
128°0'0"E
130°0'0"E
132°0'0"E
134°0'0"E
136°0'0"E
NATIONAL WATER COMMISSION — Low flows report series
138°0'0"E
6
Rapid Creek site DW-21
Bees Creek site DW-26
Elizabeth River site DW-40
Berry Creek site DW-31
Figure 3: AUSRIVAS sites in Darwin Harbour catchment, with the four sites used in the
present study indicated
Source: modified from NRETAS (2007).
2.4.2 Diversity metrics and invertebrate traits
Several metrics were calculated for each macroinvertebrate sample. Henceforth, ‘sample’
refers in this case study to the collection of identified macroinvertebrate taxa and the
accompanying environmental data recorded at a particular habitat at a particular site at a
particular time. For the Early AUSRIVAS dataset, a sample thus refers to data associated with
an edge or sand habitat in a site during the early season 1995, late season 1995, early
season 1996 or late season 1996. For the Darwin Streams dataset, a sample refers to data
associated with an edge habitat in a site during the early dry season of 2001, 2002, 2003,
2004, 2007 or 2009.
Metrics were based on taxonomic presence/absence, as the AUSRIVAS sampling methods
are considered not to assess abundance (Brooks et al. 2011). Total richness (S) and the
richness of Ephemeroptera, Trichoptera and EPT taxa (Ephemeroptera + Plecoptera +
Trichoptera) were calculated for each sample. No sample contained Plecoptera. The mean
SIGNAL grade (avSIG) of taxa present within each sample was also calculated, following
Chessman (2001, 2003). SIGNAL grades for the Northern Territory macroinvertebrate taxa
NATIONAL WATER COMMISSION — Low flows report series
7
range from 1 to 9, where higher grades indicate taxa that are more sensitive to poor water
quality and pollutants.
Finally, biological traits were assigned to macroinvertebrate taxa. Analysis of
macroinvertebrate data has traditionally been based on taxonomic composition, particularly in
Australia. However, analysis of trait composition (e.g. habitat preference, dispersal capacity,
life stage durations) may provide insight into mechanisms by which macroinvertebrate
assemblages respond to, or are affected by, hydrology including low flows (e.g. Chessman et
al. 2010; Brooks et al. 2011). In the present study, family-level biological traits were assigned
according to the dispersal capacity of macroinvertebrates as outlined in Shafer et al. (2011),
rheophily and thermophily values of Chessman (2009), Flow Exposure Groups (FEG) of
Growns & Davis (1994) and several traits outlined in Poff et al. (2006). For context, the
rheophily and thermophily values for all taxa included in the Northern Territory AUSRIVAS
training manual range on a continuous scale from zero to 3.39 and from 0.77 to 1.19, where
higher values are more indicative of rheophilous and thermophilous taxa respectively. The
dispersal capacity trait of Schafer et al. (2011) follows an ordinal scale of low (1) to high (4).
Despite the interest in using trait-based methods of analysis, however, databases of
macroinvertebrate traits for Australian fauna are not yet widely available or complete
(although see Chessman 2009; Brooks et al. 2011; Shafer et al. 2011) compared with those
for northern hemisphere fauna (e.g. Gayraud et al. 2003; Poff et al. 2006). For example,
dispersal capacity was the only trait for which values were available for all taxa in the present
study. Traits for which information was available for a limited number of the taxa included
those of Growns & Davis (1994) and Poff et al. (2006). These traits were not used in analyses
(cf. Brooks et al. 2011) to avoid interpretation of assemblage patterns based on incomplete
knowledge. Thus, only three biological trait metrics were calculated for each sample: the
mean dispersal capacity of taxa (avDC), the mean rheophily (avRheo) and mean thermophily
(avTherm).
2.4.3 Antecedent flow metrics
For analyses involving flow data, only the sites that had associated flow-gauging stations and
the required period of mean daily flow data (within one year of sample date) were included. All
four sites in the Darwin Streams dataset met these criteria, but only 11 ‘reference’ sites in the
Early AUSRIVAS dataset: five in the Daly River basin, two in the Mary River basin and one
each in the Adelaide, Roper, South Alligator and Victoria river basins. For analysis of the
Early AUSRIVAS dataset, this equates to 44 macroinvertebrate samples for each habitat type
if both edge and sand habitats were sampled from all sites in both seasons and years.
However, this was not the case and there were 31 samples from edges and 23 from sand
habitats (Figure 5).
For each sample, antecedent flow metrics from the most recent dry and wet seasons were
calculated in RAP v3.0.3 (Marsh et al. 2003) (Table 1). The antecedent dry period was
defined from the start of May in the same year of sampling through to the date of sampling.
The antecedent wet season was defined from the start of December in the year before
sampling through to the end of April in the year of sampling (e.g. from 1 December 1995 to 30
April 1995 for samples collected in 1995; and from 1 December 1995 to 30 April 1996 for
those collected in 1996). These dates aligned with the start and end of the dry season as
indicated by the dry season AUSRIVAS sampling periods in 1995 and 1996, which occurred
from May to November each year. Inspection of flow data from the gauging stations
associated with the four Darwin Streams sites suggested the end of April was also an
appropriate marker for the end of the wet season for the 2001 to 2009 samples. However,
‘early dry season’ sampling was conducted in April 2004 at two sites, and in April 2009 in
three sites; antecedent dry season flow metrics were not calculated for these sites and years
(Figure 6). In addition, there were missing data in many of the early wet season periods of the
NATIONAL WATER COMMISSION — Low flows report series
8
Darwin Streams flow data. These were replaced with zeros to produce the hydrographs in
Figure 6, but were not included in the calculation of antecedent wet season flow metrics for
the Darwin Streams. As a result, the antecedent wet periods had different start dates for
different sites and years, being as late as 15 January; and for one site, the MDF data from the
entire 2000–01 wet season was missing. Antecedent wet flow metrics based on duration of
flow (e.g. number of high spell days or days of rising/falling discharge) were therefore not
calculated. However, three more general duration metrics were calculated for each sample
(from the Early AUSRIVAS and Darwin Streams datasets), which were all related to the
number of days from a particular flow event to the sample date (Table 1). There were also
short periods (i.e. < 16 d) of missing data present within nine of the antecedent wet periods
relative to the Darwin Streams sampling dates (total duration of 44 days). Missing data were
replaced with the mean MDF of the two days either side of the missing period and any effect
of this replacement on the antecedent wet season flow metrics was considered minimal.
Finally, the MDF on each sample date was also included in analyses of both the Early
AUSRIVAS and Darwin Streams datasets.
Table 1: Flow metrics calculated for different antecedent periods relative to each sample
Period
Code
Unit
Description a
Dry
DrP10
m3 s-1
10th percentile of mdf (low-flow
threshold)
DrP90
m3 s-1
90th percentile of mdf (high-flow
threshold)
DrMDF
m3 s-1
Mean mdf
DrCV
Wet
CV (standard deviation/mean) of mdf
DrZFD
d
Total duration of zero-flow days
Many zeros (many
streams
experienced nonzero-flow in the dry
season)
DrNZFD
d
Total duration of non-zero-flow days
Highly correlated
with DsinceEndWet
WeMax
m3 s-1
Maximum mdf
WeP90
m3 s-1
90th percentile of mdf (high-flow
threshold)
WeMDF
m3 s-1
Mean mdf
WeCV
General
Comment b
CV (standard deviation/mean) of mdf
WeRateFall
m3 s-2
Mean rate of fall
WeGRateFall
m3 s-2
Greatest rate of fall
FlowOnDay
m3 s-1
MDF on day of sample
DsinceWeMax
d
Number of days between WeMax and
sample date
DsinceEndWet
d
Number of days between 1 May and
sample date
DsinceZF
d
Number of days between sample date
and the last zero-flow day
Highly correlated
with WeRateFall
Not used in Early
AUSRIVAS
analyses because
many streams
experienced long
periods of non-zeroflow
Note: Bold typeface indicates metrics used in analyses (reason for exclusion given in comment).
a
mdf = mean daily flow in m3 s-1
b
highly correlated metrics had |Spearman correlation coefficients| > 0.8
NATIONAL WATER COMMISSION — Low flows report series
9
50
40
0
2000
70
E
E
E,S
E,S
E,S
100
1500
1000
E,S
500
E
70
50
0
2500
Station G8140042, Site DA-07
500
300
0
E,S
E
40
S
E,S
NATIONAL WATER COMMISSION — Low flows report series
E
90
80
60
Station G8140161, Site DA-17
30
E
20
10
Figure 4: Mean daily flow (m 3 s-1) recorded at gauging stations in close proximity to the Early
AUSRIVAS sampling sites, with macroinvertebrate sample dates at edge (E) and sand (S)
habitats indicated by arrows
10
Dec-95
0
Dec-95
Nov-95
Oct-95
Sep-95
Aug-95
Jul-95
Jun-95
May-95
Apr-95
Mar-95
Feb-95
Jan-95
Dec-94
Nov-94
Oct-94
Jun-94
Discharge (m3 s-1)
Jul-94
Dec-96
Nov-96
Oct-96
Sep-96
Aug-96
Jul-96
Jun-96
May-96
Apr-96
Feb-96
Mar-96
Jan-96
Dec-95
Nov-95
Oct-95
Sep-95
Aug-95
Jul-95
Jun-95
May-95
Apr-95
Feb-95
Mar-95
Jan-95
Dec-94
Nov-94
Oct-94
Sep-94
Aug-94
E,S
Nov-95
0
E
Oct-95
200
15
Sep-95
50
200
E
Jul-95
400
E,S
Aug-95
250
250
Jun-95
Station G8140159, Site DA-04
350
May-95
350
25
Apr-95
600
E,S
Mar-95
S
Feb-95
S
Jan-95
1000
Dec-94
1200
Nov-94
Station G8140008, Site DA-02
Oct-94
1800
Sep-94
0
Sep-94
1000
Aug-94
E,S
E,S
Jul-94
1500
Aug-94
2500
Aug-94
Sep-94
Oct-94
Nov-94
Dec-94
Jan-95
Feb-95
Mar-95
Apr-95
May-95
Jun-95
Jul-95
Aug-95
Sep-95
Oct-95
Nov-95
Dec-95
Jan-96
Feb-96
Mar-96
Apr-96
May-96
Jun-96
Jul-96
Aug-96
Sep-96
Oct-96
Nov-96
Dec-96
3000
1000
900
800
700
600
500
400
300
200
100
0
Jun-94
4000
Jul-94
Station G8140067, Site DA-01
Discharge (m3 s-1)
50
May-94
S
E
Discharge (m3 s-1)
150
Discharge (m3 s-1)
Station G8170002, Site AD-03
Jul-94
Aug-94
Sep-94
Oct-94
Nov-94
Dec-94
Jan-95
Feb-95
Mar-95
Apr-95
May-95
Jun-95
Jul-95
Aug-95
Sep-95
Oct-95
Nov-95
Dec-95
Jan-96
Feb-96
Mar-96
Apr-96
May-96
Jun-96
Jul-96
Aug-96
Sep-96
Oct-96
Nov-96
Dec-96
300
E,S
Discharge (m3 s-1)
S
E
Dec-95
1400
Oct-95
E,S
E
Nov-95
150
E,S
Sep-95
1600
Jul-95
E,S
Aug-95
E
Jun-95
3500
Apr-95
Jul-94
Aug-94
Sep-94
Oct-94
Nov-94
Dec-94
Jan-95
Feb-95
Mar-95
Apr-95
May-95
Jun-95
Jul-95
Aug-95
Sep-95
Oct-95
Nov-95
Dec-95
Jan-96
Feb-96
Mar-96
Apr-96
May-96
Jun-96
Jul-96
Aug-96
Sep-96
Oct-96
Nov-96
Dec-96
Discharge (m3 s-1)
200
May-95
Jun-94
Jul-94
Aug-94
Sep-94
Oct-94
Nov-94
Dec-94
Jan-95
Feb-95
Mar-95
Apr-95
May-95
Jun-95
Jul-95
Aug-95
Sep-95
Oct-95
Nov-95
Dec-95
Jan-96
Feb-96
Mar-96
Apr-96
May-96
Jun-96
Jul-96
Aug-96
Sep-96
Oct-96
Nov-96
Dec-96
Discharge (m3 s-1)
100
Mar-95
800
Feb-95
Jun-94
Jul-94
Aug-94
Sep-94
Oct-94
Nov-94
Dec-94
Jan-95
Feb-95
Mar-95
Apr-95
May-95
Jun-95
Jul-95
Aug-95
Sep-95
Oct-95
Nov-95
Dec-95
Jan-96
Feb-96
Mar-96
Apr-96
May-96
Jun-96
Jul-96
Aug-96
Sep-96
Oct-96
Nov-96
Dec-96
Discharge (m3 s-1)
2000
Jan-95
Dec-94
Nov-94
Oct-94
Sep-94
0
Jun-94
Jul-94
Aug-94
Sep-94
Oct-94
Nov-94
Dec-94
Jan-95
Feb-95
Mar-95
Apr-95
May-95
Jun-95
Jul-95
Aug-95
Sep-95
Oct-95
Nov-95
Dec-95
Jan-96
Feb-96
Mar-96
Apr-96
May-96
Jun-96
Jul-96
Aug-96
Sep-96
Oct-96
Nov-96
Dec-96
Discharge (m3 s-1)
0
Aug-94
Discharge (m3 s-1)
0
Jul-94
Jun-94
0
Jul-94
Aug-94
Sep-94
Oct-94
Nov-94
Dec-94
Jan-95
Feb-95
Mar-95
Apr-95
May-95
Jun-95
Jul-95
Aug-95
Sep-95
Oct-95
Nov-95
Dec-95
Jan-96
Feb-96
Mar-96
Apr-96
May-96
Jun-96
Jul-96
Aug-96
Sep-96
Oct-96
Nov-96
Dec-96
Discharge (m3 s-1)
250
Station G8180026, Site MY-04
E,S
30
20
Station G8180252, Site MY-07
10
E
500
5
450
400
300
Station G9030250, Site RP-05
200
150
E
100
80
60
50
Station G8200052, Site SA-02
30
S
20
10
600
400
Station G8110004, Site VC-06
200
E,S
100
0
Jun-09
Dec-08
Mar-09
Jun-08
Sep-08
Mar-08
E
Jun-09
E
Sep-08
Dec-08
Mar-09
Jun-07
Sep-07
Dec-07
Jun-09
Dec-08
Mar-09
Jun-08
Sep-08
Mar-08
Sep-07
Dec-07
Jun-07
Sep-06
Dec-06
Mar-07
Jun-06
Sep-05
Dec-05
Mar-06
Jun-05
Dec-04
Mar-05
Jun-04
Sep-04
E
Jun-09
E
Mar-08
Jun-08
Sep-07
Dec-07
E
Dec-06
Mar-07
Jun-07
Sep-06
Dec-06
Mar-07
Jun-06
Dec-05
Mar-06
Jun-05
Sep-05
Mar-05
E
Mar-08
Jun-08
Sep-08
Dec-08
Mar-09
E
Jun-06
Sep-06
Sep-05
Dec-05
Mar-06
Jun-04
Sep-04
Dec-04
Dec-03
Mar-04
Sep-03
Mar-03
Jun-03
Sep-02
Dec-02
E
Jun-07
Sep-07
Dec-07
E
Dec-04
Mar-05
Jun-05
E
Jun-04
Sep-04
Dec-03
Mar-04
E
Dec-05
Mar-06
Jun-06
Sep-06
Dec-06
Mar-07
E
Dec-03
Mar-04
E
Jun-03
Sep-03
E
Jun-03
Sep-03
Sep-02
Mar-02
Jun-02
E
Jun-05
Sep-05
E
Dec-02
Mar-03
Jun-01
Sep-01
Dec-01
E
Mar-04
Jun-04
Sep-04
Dec-04
Mar-05
100
Mar-02
Jun-02
E
Sep-02
Dec-02
Mar-03
Jun-01
Dec-00
Mar-01
Discharge (m3 s-1)
E
Jun-03
Sep-03
Dec-03
0
E
Dec-01
Mar-02
Jun-02
60
Dec-01
Mar-02
Jun-02
Sep-02
Dec-02
Mar-03
120
Sep-01
Dec-01
15
Jun-01
Sep-01
Discharge (m3 s-1)
15
Jun-01
Sep-01
Dec-00
Mar-01
0
Dec-00
Mar-01
Discharge (m3 s-1)
0
Dec-00
Mar-01
Discharge (m3 s-1)
30
25
Station G8150127, Site DW-21
20
E
10
5
30
25
Station G8150036, Site DW-26
20
E
10
5
140
Station G8150028, Site DW-31
100
80
E
40
20
250
Station G8150018, Site DW-40
200
150
E
50
Figure 5: Mean daily flow (m3 s-1) recorded at gauging stations in close proximity to the
Darwin Streams sampling sites, with macroinvertebrate sample dates at edge (E) habitats
indicated by arrows
NATIONAL WATER COMMISSION — Low flows report series
11
2.5 Data analysis
2.5.1 General analyses – effects of season and year in sand
and edge habitats
For the Early AUSRIVAS dataset, null hypotheses of no differences in macroinvertebrate
assemblage composition between seasons and years (fixed factors) were tested using the
models shown in Table 2 by Permutational Multivariate Analysis of Variance (PERMANOVA)
(Anderson 2001). Basin was also included as a fixed factor in models when samples were
collected from more than one river basin and there were enough samples to provide adequate
degrees of freedom for analyses (Table 2). Count data were transformed to
presence/absence data and samples were then compared based on the Bray-Curtis similarity
measure using 9999 permutations. Samples for which season and/or year had a significant
effect on assemblage similarity (p < 0.05) were then ordinated using Principal Coordinate
Analysis (PCO), which maximises the total variation among samples in the space identified by
the Bray-Curtis similarity measure. Vectors of taxonomic presence/absence with Spearman
correlations > 0.40 were then overlain on the unit circle of the PCO to provide insight as to
which taxa were associated with dissimilarity among sample groups. All multivariate analyses
were performed using PRIMER v6.1.11 with the PERMANOVA+ 1.0.1 add-on package.
Association between environmental and water quality parameters and macroinvertebrate
diversity and trait metrics were also investigated, particularly within samples for which
significant effects of season and/or year on assemblage composition were detected.
Association was described by the Spearman correlation coefficient (rs). In addition, the null
hypotheses of no difference in environmental and water quality parameters, and in diversity
and trait metrics between seasons and/or years were tested using the Mann-Whitney U test.
These univariate analyses were performed in SAS v9.1 with α = 0.05.
For the Darwin Streams dataset, count data were transformed to genus-level and family-level
presence/absence data and the Bray-Curtis similarity measure was used to calculate
assemblage similarity among samples. Family-level classification followed that of the Early
AUSRIVAS dataset. For example, genera within Acarina were relabelled as Acarina and
genera within Chironomidae were relabelled at the subfamily level (as Chironominae,
Orthocladiinae or Tanypodinae).
NATIONAL WATER COMMISSION — Low flows report series
12
Table 2: Statistical models used for PERMANOVA to test the null hypothesis of no difference
in macroinvertebrate assemblage composition between seasons (early v. late dry) or years
(1995 v. 1996)
Samples to which model
Source of variation
Type
applies
Degrees
Denominator for
of
Pseudo-F test and
freedom
variance component
(VC)
Lotic Sand
Season
Fixed
1
Residual
Year
Fixed
1
Residual
Season x Year
Fixed
1
Residual
Residual
Random
Total
Lentic Sand
15
Season
Fixed
1
Residual
Year
Fixed
1
Residual
Basin
Fixed
8
Residual
Season x Year
Fixed
1
Residual
Season x Basin
Fixed
8
Residual
Year x Basin
Fixed
8
Residual
Season x Year x
Basin
Fixed
8
Residual
Residual
Random
Total
Flow Change (1995)
Sand
Season
Fixed
Residual
Random
Residual
14
15
Fixed
1
Residual
Year
Fixed
1
Residual
Basin
Fixed
12
Residual
Season x Year
Fixed
1
Residual
Season x Basin
Fixed
12
Residual
Year x Basin
Fixed
12
Residual
Season x Year x
Basin
Fixed
12
Residual
Residual
Random
116
167
Season
Fixed
Residual
Random
Total
Flow Change (1996)
Edge
1
Season
Total
Flow Change (1995)
Edge
28
63
Total
Lentic Edge
12
1
Residual
20
21
Season
Fixed
Residual
Random
Total
1
Residual
18
19
Note: Terms in bold typeface were of interest to this research.
NATIONAL WATER COMMISSION — Low flows report series
13
2.5.2 Flow metric analyses
For the analyses of the Early AUSRIVAS data involving flow metrics (i.e. analyses on the 31
edge samples and 23 sand samples for which there were relevant flow data), a similar
process was followed as outlined above. Null hypotheses of no differences in
macroinvertebrate assemblage composition between seasons, years and basins (fixed
factors) were tested in a full-factorial model by PERMANOVA for edge and sand habitat
samples separately (based on presence/absence data and the Bray-Curtis similarity measure
using 9999 permutations). Edge and sand samples were then each ordinated using PCO.
Vectors of antecedent flow metrics (Table 1), environmental and water quality parameters
(mean stream width, mean current speed and water depth, water conductivity, temperature,
DO, TN as NOx + TKN and TP) and macroinvertebrate diversity and trait metrics (S, EPT
richness, avSIG, avDC, avRheo and avTherm) were overlain on the unit circle of the PCO to
explore the association between similarity in composition among samples and the antecedent
flow history as well as contemporaneous environmental, water quality and macroinvertebrate
assemblage characteristics. Only a selection of the available environmental and water quality
parameters were used in vector overlays because many parameters were highly correlated
(e.g. conductivity and alkalinity) or had little sample-to-sample variation (e.g. the proportion of
macrophyte habitat at the reach scale was zero in most cases). Null hypotheses of no
differences in antecedent flow metrics (for each of the dry season, wet season and general
groups of flow metrics listed in Table 1), contemporaneous environmental and water quality
parameters (listed above), and macroinvertebrate diversity and trait metrics (listed above)
between seasons, years and river basins (fixed factors) were also tested in full-factorial
models by PERMANOVA (based on range standardised data and the Euclidean distance
measure using 9999 permutations). Season was not included as an effect term in the
PERMANOVA on wet season antecedent flow metrics as these metrics were calculated from
the same wet season for both early and late dry season samples from any one year. These
same steps were followed for the Darwin Streams edge samples (based on both genus-level
and family-level presence/absences data), except that no PERMANOVA tests were
performed and no steps involved water quality and environmental parameters, as these were
not available.
Associations between pairs of macroinvertebrate diversity and trait metrics, environmental
and water quality parameters and the antecedent flow metrics were further described by the
Spearman correlation coefficient. Separate analyses were conducted on data from the Early
AUSRIVAS edge and sand habitat samples and data from the Darwin Streams edge samples.
For each of these groups of samples, absolute differences in the macroinvertebrate metrics,
water quality and environmental parameters and antecedent flow metrics of a site between
any two sampling occasions were also calculated. For example, difference in taxonomic
richness of edge habitat samples from a site in the Daly River basin was calculated between
the 1995 early and late dry seasons, the 1995 and 1996 early dry seasons, the early 1995
and late 1996 dry seasons, the late 1995 and early 1996 dry seasons, the 1995 and 1996 late
dry seasons, and the 1996 early and late dry seasons. If the site was part of the Darwin
Streams dataset, the differences were calculated between each pair of sampling years.
Spearman correlations were performed on these difference data to explore association
between the size of the sample-to-sample differences in macroinvertebrate assemblage,
water quality, environmental and antecedent flow characteristics. The Bray-Curtis similarity
(based on presence/absence data) between any two macroinvertebrate samples from the
same site was also included in these analyses. However, sample-to-sample differences in
antecedent wet season flow metrics from the Early AUSRIVAS dataset lacked variation within
sites due to the seasonal nature of sampling (e.g. for any one site, the difference in maximum
flow of the wet season antecedent to early and late dry season samples was zero if samples
were collected in the same year, and the same non-zero value if collected in different years).
Thus, correlation analyses on the Early AUSRIVAS dataset only used differences in
antecedent dry season and general flow metrics (Table 1).
NATIONAL WATER COMMISSION — Low flows report series
14
3. Results
3.1 Macroinvertebrate assemblages
A total of 69 taxa from 146 sand habitat samples from the Early AUSRIVAS dataset were
used in the general analyses that explored effects of season and year on assemblage
composition. There were 38 taxa in the Lotic Sand group of 16 samples, 64 taxa in the Lentic
Sand group of 64 samples and 38 taxa in the Flow Change (1995) Sand group of 16 samples.
In the edge habitats, the 202 samples used in general analyses contained 74 taxa. Within the
Lentic Edge group of 168 samples there were 81 taxa, the Flow Change (1995) Edge group
of 22 samples contained 65 taxa, and the Flow Change (1996) Edge group of 12 samples
contained 62 taxa. For the Early AUSRIVAS samples used in the flow metric analyses, the 23
sand habitat samples had 45 taxa, and the 31 edge habitat samples had 70 taxa. In the
genus-level dataset from the four Darwin Streams sites, there were 109 taxa, which equated
to 43 taxa at the family level of taxonomic resolution.
3.2 Effects of season and year in sand habitats
(Early AUSRIVAS dataset)
3.2.1 Lotic Sand – multiple river basins
Neither season nor year, nor their interaction, had a significant effect on assemblage similarity
in sand habitats that were lotic on all four sampling occasions (early and late dry seasons in
1995 and 1996). That is, assemblage similarity was not different between seasons or years in
this group of samples. Effect of river basin was not specifically tested as each of the four sites
was in a different basin and was therefore accounted for in the model as the residual random
variation.
Out of interest, however, the effect of season on environmental parameters and
macroinvertebrate diversity and trait metrics across years was tested (Mann-Whitney U test).
Season had a significant effect only on habitat water temperature (U = 36.0, p = 0.0008), the
proportion of sand in habitat substrate (U = 91.0, p = 0.0125) and total richness (U = 92.0, p =
0.0102), such that the lotic sand habitats in the four sites were cooler and had a greater
proportion of sand and greater taxon richness in the early dry season than in the late dry
season. There was no difference in mean stream width, habitat water depth, mean current
speed, dissolved oxygen (DO) or nutrient concentrations. These results suggested that in the
sand habitats of these flowing streams and rivers there were few differences in habitat
characteristics and macroinvertebrate assemblages between the early and late dry season
(for the years of study at least).
3.2.2. Lentic Sand – multiple river basins
For the group of samples that had lentic habitats on all four sampling occasions, the only
significant effect on assemblage similarity was that of river basin (pseudo F = 2.08, VC =
19.6%, p = 0.0003). Effects of all other terms in the model (season, year and all interaction
terms) were non-significant (p > 0.05). As such, assemblage similarity among samples
differed among river basins. However, the effect of river basin on assemblage composition
was not of interest to this study and pairwise comparisons of assemblage similarity between
river basins were not conducted.
NATIONAL WATER COMMISSION — Low flows report series
15
Rather, the effect of season on environmental parameters and macroinvertebrate diversity
and trait metrics (across years and within years) was explored (Mann-Whitney U test). Note,
however, that any effect of river basin was not taken into account. Across years, water
temperature was higher in the late dry season than the early dry as was TKN and TURB (p <
0.05). DO was higher in the early dry season, as was NOx, EPT richness and Trichoptera
richness (p < 0.05). However, the only consistent difference when the effect of season was
examined within years was that of temperature. In 1995 and 1996 water temperature was
significantly higher in the late dry season than in the early dry (1995: U = 144.0; 1996: U =
138.5; p <0.0001). This suggested that, ignoring any effect of river basin, the lentic sand
habitats were likely to have been cooler earlier than later in the dry season. Otherwise,
environmental and assemblage characteristics of these habitats did not differ consistently or
greatly between seasons; differences within any one year were perhaps less predictable than
the observed increase in water temperature between early and late dry seasons.
3.2.3 Flow Change (1995) Sand – Daly River basin only
Season did have a significant effect on assemblage similarity in the 16 sand habitat samples
from eight sites in the Daly River basin that were lotic in the early dry season of 1995 but
lentic during the late dry season of the same year (pseudo F = 2.20, VC = 13.0%, p = 0.0342).
The first two axes of the PCO explained 52.2 per cent of the variation in assemblage similarity
among these samples. The vector overlay of macroinvertebrate presence/absence with
Spearman correlation > 0.40 suggested the presence of the following taxa may have been
more strongly associated with assemblages from sand habitats in the late dry season that had
ceased to flow, than with the same habitats that were in flow during the early dry season:
Sphaeriidae, Oligochaeta, Palaemonidae, Hydrophilidae, Dytiscidae, Ecnomidae, Corixidae
and Notonectidae (Figure 7). Taxa that may have been more strongly associated with the
early dry season assemblages in flowing sand habitats included: Elmidae, Simulidae,
Planorbidae, Hydroptilidae, Naucoridae, Leptoceridae, Thiaridae, Orthocladiinae, Tipulidae,
Nematoda, Leptophlebiidae, Ceratopogonidae, Pyralidae and Hydropsychidae.
Rheophily values (Chessman 2009) were available for all the above taxa except for
Oligochaeta and Nematoda; ignoring these two, the former ‘late dry lentic’ group of taxa had a
lower mean rheophily value (0.53) than the ‘early dry lotic’ group (1.31). In addition, SIGNAL
grades were available for all taxa within the two groups and the mean SIGNAL grade of taxa
in the ‘late dry lentic’ group was lower (2.75) than the ‘early dry lotic’ group (4.5). Finally, the
‘late dry lentic’ group contained one EPT taxon (Ecnomidae, Trichoptera) compared with four
EPT taxa in the ‘early dry lotic’ group (Hydroptilidae, Leptoceridae and Hydropsychidae,
Trichoptera; Leptophlebiidae, Ephemeroptera).
There were also significant effects of season on environmental parameters and
macroinvertebrate diversity and trait metrics of the 16 samples from the Daly River basin
(Mann-Whitney U test, p <0.05). Lentic sand habitats in the late dry season of 1995 had
significantly higher water temperatures (U = 98.0, p = 0.0016) and concentrations of TKN (U =
93.5, p = 0.0073) and FRP (U = 91.5, p = 0.0124), but lower DO (U = 49.0, p = 0.0460), EPT
richness (U= 49.5, p = 0.0445), Trichoptera richness (U = 48.0, p = 0.0462) and lower mean
SIGNAL grades (U = 45.5, p = 0.0177) than their equivalent lotic sand habitats in the early dry
season (Figure 8).
Several significant correlations were also detected between environmental parameters and
the diversity and trait metrics across the 16 samples (Spearman rank correlation, p < 0.05)
(Figure 9). DO was positively correlated with avSIG (rs = 0.59, p = 0.0171). Temp was
negatively correlated with Trichoptera richness (rs = -0.67, p = 0.0049) and avSIG (rs = -0.57,
p = 0.0208). NOx was negatively correlated with Ephemeroptera richness (r s = -0.51, p =
0.0451) and TKN was negatively correlated with avSIG (r s = -0.59, p = 0.0155). Mean habitat
depth was negatively correlated with total richness (r s = -0.51, p = 0.0434) and
NATIONAL WATER COMMISSION — Low flows report series
16
Ephemeroptera richness (rs = -0.57, p = 0.0205). Richness of EPT and Trichoptera were
highly correlated (rs > 0.8).
These findings suggested that, along with the loss of flow in the sand habitats of the Daly
River basin sites between the early and late dry season of 1995, the difference found in
macroinvertebrate assemblages between these seasons may also have been associated with
changes in water quality (lower DO, but higher temperature and nutrient concentrations),
reduced habitat depth, an overall reduction in taxonomic richness and evenness, and a
reduction in the numbers of sensitive and rheophilous taxa.
NATIONAL WATER COMMISSION — Low flows report series
17
PCO2 (21.7% of total variation)
20
DA-09
DA-03 DA-15
DA-01
DA-08
DA-15
DA-07
DA-08
0
DA-09
DA-02
DA-02
DA-18
DA-18
DA-03
DA-07
-20
DA-01
-40
-40
-20
0
20
PCO1 (30.5% of total variation)
40
PCO2 (21.7% of total variation)
20
Sphaeriidae
Oligochaeta
Elmidae
Palaemonidae
Simulidae & Planorbidae
Hydrophilidae
Hydroptilidae
Dytiscidae
Naucoridae
Leptoceridae
Thiaridae
Ecnomidae
Orthocladiinae
Tipulidae
Nematoda
Corixidae
Leptophlebiidae
Pyralidae Ceratopogonidae
Notonectidae
0
-20
Hydropsychidae
-40
-40
-20
0
20
PCO1 (30.5% of total variation)
40
Figure 6: Principal Coordinate Analysis (PCO) ordination of macroinvertebrate assemblage
similarities among sand habitat samples collected in the early (green upright triangles, lotic)
and late dry season (blue upside down triangles, lentic) in 1995 from eight sites in the Daly
River basin (DA), with vectors showing taxa with Spearman correlations > 0.40 presented
separately (circle represents a vector correlation of 1)
NATIONAL WATER COMMISSION — Low flows report series
18
7
DO (mg L-1)
Temperature (oC)
30
28
26
6
5
24
4
22
0.008
TKN (mg L-1)
FRP (mg L-1)
0.4
0.006
0.004
0.002
0.3
0.2
0.1
4.5
3
avSIG
Trichoptera (S)
4
2
4.0
1
3.5
0
Early
Late
Early
Late
Figure 7: Box and whisker plots of water quality parameters and macroinvertebrate metrics for
sand habitats from eight sites in the Daly River basin that were lotic in the early dry season of
1995 but lentic in the late dry season of 1995
NATIONAL WATER COMMISSION — Low flows report series
19
5
4.5
4
Trichoptera (S)
avSIG
5.0
4.0
3.5
3
2
1
3.0
20
22
24
26
28
30
0
32
20
22
5.0
5.0
4.5
4.5
4.0
30
32
3.5
0.0
0.1
0.2
0.3
TKN (mg
0.4
3.0
0.5
L-1)
3
4
5
DO (mg
22
6
7
8
L-1)
4
Ephemeroptera (S)
20
18
S
28
4.0
3.5
3.0
26
Temperature (oC)
avSIG
avSIG
Temperature (oC)
24
16
14
12
3
2
1
10
8
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40
Mean habitat (water) depth (m)
0
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40
Mean habitat (water) depth (m)
Ephemeroptera (S)
4
3
2
1
0
0.000
0.005
0.010
0.015
0.020
NOx (mg L-1)*
Figure 8: Environmental parameters and macroinvertebrate metrics with significant Spearman
correlations for sand habitats from eight sites in the Daly River basin in 1995 that were lotic in
the early dry season (open diamonds) but lentic in the late dry season (closed diamonds)
*One extremely high NOx concentration (0.116 mg L-1 at site DA-15 in the early dry season; Ephemeroptera richness
= 2) is not shown on the above plot.
NATIONAL WATER COMMISSION — Low flows report series
20
3.3 Effects of season and year in edge habitats
(Early AUSRIVAS dataset)
3.3.1 Lentic Edge – multiple river basins
As with sand habitats, there was a significant effect on assemblage similarity of river basin in
the group of edge samples that were lentic on all four sampling occasions (pseudo F = 3.31, p
= 0.0001). Assemblage similarity among edge samples thus differed among river basins, and
as with sand habitats, pairwise comparisons of assemblage similarity between river basins
were not conducted.
Unlike the sand habitat samples, however, the interaction of season and year on edge habitat
assemblage similarity explained a small, yet significant proportion of the variation among
samples (pseudo F = 1.95, VC = 3.7 per cent, p = 0.0416). The effect of season thus
depended on the year of sampling and vice versa. Pairwise tests were performed to
investigate this further. Specifically, assemblage similarity was different between early and
late dry season samples in 1995 (t = 1.548, p = 0.0120) but not in 1996, and assemblage
similarity was different between years for the late dry season samples (t = 1.55, p = 0.0115)
but not for the early dry season samples.
For the early and late dry season samples in 1995, the first two axes of the PCO explained
just 28.6 per cent of the variation in assemblage similarity among all the samples. For the
1995 and 1996 samples from the late dry season, the first two axes of the PCO explained
only slightly more of the variation in assemblage similarity (30.8 per cent). Further insight into
the difference between seasons or years in these lentic edge samples was not gained by
plotting early versus late dry season on the ordination of the 1995 samples, or 1995 versus
1996 on the ordination of the late dry season samples, or by overlaying macroinvertebrate
presence or absences with Spearman correlations > 0.40 (Figure 10). The effect of river basin
on assemblage similarity may have increased the difficulty in interpreting the ordinations and
vector overlays.
Despite the difficulty in interpreting the PCO ordinations, tests of the interacting effect of
season and year on environmental parameters and macroinvertebrate diversity and trait
metrics (Mann-Whitney U tests) were informative. Note, however, that any effect of river basin
was not taken into account. Firstly, for samples collected in the late dry season, those from
1995 had higher concentrations of NOx (U = 2141.0, p = 0.0012) and the macroinvertebrate
assemblages were less rich (U = 1563.5, p = 0.0469) than those collected in 1996. Secondly,
for the samples collected in 1995, those from the early dry season had higher DO (U =
2028.5, p = 0.0294) but lower turbidity (U = 1563.5, p = 0.0462), temperature (U = 960.5, p <
0.0001), TKN (U = 1444.5, p = 0.0023) and TP (U = 1508.5, p = 0.0132) than those from the
late dry season; and the macroinvertebrate assemblages were richer (U = 2186.5, p =
0.0003) and had more EPT taxa (U = 2006.0, p = 0.0420) but lower mean dispersal capacity
(avDC, U = 1550.0, p = 0.0355) (Figure 11). This suggested that (ignoring any effect of river
basin) edge habitats that were not in flow during the 1995 dry season tended to be cooler,
more oxygenated and less turbid and had lower concentrations of nutrients early in the dry
season than later in the dry season, when assemblages were less rich and taxa had a greater
capacity to disperse.
There were also some significant correlations between environmental parameters and
macroinvertebrate metrics within the lentic edge samples from 1995: DO was positively
correlated with avSig (rs = 0.27, p = 0.0130) as well as EPT and Trichoptera richness (rs =
0.29, p = 0.0078; rs = 0.31, p = 0.0040; EPT and Trichoptera richness were highly correlated,
rs > 0.8) and TKN was negatively correlated with Trichoptera richness (Figure 12). In
particular, these findings suggested that lentic edge habitats with lower concentrations of DO
NATIONAL WATER COMMISSION — Low flows report series
21
may have supported fewer sensitive taxa and this was perhaps most likely to have occurred
towards the end of the dry season.
40
DA-15
PCO2 (13.9% of total variation)
Orhtocladiinae
Ecnomidae
20
VC-10
Elmidae
Leptoceridae
RP-11
Hydroptilidae
FN-07
AD-02
KP-03
RP-08 DA-05
DA-14
DA-05
VC-06
FN-06
EA-04
ML-01
VC-09
AD-02
RB-02
VC-13
VC-14
DA-10
RP-02
RP-03
AD-06VC-14
RP-13
DA-13
VC-09
EA-03 VC-11
KP-03FN-07 Stratiomyidae
ML-01
DW-11
VC-10
RP-03
FN-06
Hydraenidae
DA-10
FN-03
DA-20
VC-06
DA-15
VC-11
FN-09
EA-04
RB-02 DA-20
RP-11
Dytiscidae
RB-03
RB-03
AD-06
RP-06
GY-03
RP-02
RP-09 SA-04
DA-13
RP-09
VC-05
GY-03
RP-05
Mesoveliidae
DA-14 MY-06
VC-13
FN-03
RP-13Veliidae
VC-05
RP-05
EA-03
MY-06
VC-12
VC-16
0
VC-12
RP-12
RP-08
Hydrophilidae
FN-09
SA-04
Culicidae
DW-11
Libellulidae
RP-06
RP-12VC-04
Coenagrionidae
VC-04
-20
VC-16
ML-04
ML-04
-40
-40
-20
0
20
PCO1 (14.7% of total variation)
40
40
FN-09
VC-04
MY-06
Hydrophilidae
PCO1 (15.2% of total variation)
VC-04
20
VC-14
Gomphidae
MY-06
VC-16
AD-06
EA-03
FN-09
VC-16
SA-04
ML-04
ML-04
RP-08
RP-09
Hydraenidae
Hyriidae
FN-03
Veliidae
Notonectidae
DA-13
SA-04
EA-03
FN-07 DA-10
DA-10
FN-07
DA-20
RP-03
VC-13
RP-12
VC-09 VC-10
AD-06
VC-11
DA-13
VC-05
FN-03
GY-03
VC-13
RP-02
KP-03
GY-03
RP-11VC-05
EA-04
RB-03VC-06
RB-02
DA-14
VC-06
VC-09RP-05 RP-03
EA-04
VC-11
VC-14
RP-12
Leptophlebiidae
VC-10
RP-06 RP-09
RB-03
VC-12
DW-11
RB-02 RP-13
AD-02
Atyidae
ML-01RP-08
KP-03
FN-06
DA-15
RP-05 VC-12 RP-02
DA-20
DA-14RP-13
RP-11
Elmidae
DA-15
AD-02
Leptoceridae
DW-11
FN-06
ML-01
RP-06
Nematoda
0
Ecnomidae
Orthocladiinae
-20
Hydroptilidae
DA-05
DA-05
-40
-40
-20
0
20
PCO1 (15.6% of total variation)
40
Figure 9: Principal Coordinate Analysis (PCO) ordination of macroinvertebrate assemblage
similarities among lentic edge habitat samples collected across multiple river basins, with
vectors showing taxa with Spearman correlations > 0.40 (circle represents a vector correlation
of 1)
Notes: Top figure shows samples collected in 1995, where early dry season samples are shown as green upright
triangles; late dry season as blue upside down triangles. Bottom figure shows samples collected in the late dry
season, where samples from 1995 are shown as green upright triangles; 1996 as blue upside down triangles. See
figures 2 and 3 for river basin codes.
NATIONAL WATER COMMISSION — Low flows report series
22
4
Turbidity (NTU)
6
100
35
Temperature (oC)
DO (mg L-1)
8
30
25
2
20
TP (mg L-1)
TKN (mg L-1)
40
0
0.06
0.6
0.2
60
20
0
0.4
80
0.04
0.02
0.00
2.6
35
2.4
6
avDC
25
EPT (S)
S
30
8
2.2
4
20
2.0
2
15
1.8
Early
Late
Early
Late
Figure 10: Box and whisker plots of water quality parameters and macroinvertebrate metrics
for edge habitats in multiple river basins that were lentic in 1995
Note: One extremely high turbidity record (720 NTU in the late dry season at site RP-05) is not shown.
NATIONAL WATER COMMISSION — Low flows report series
23
avSIG
4.8
4.6
4.4
4.2
4.0
3.8
3.6
3.4
3.2
3.0
0
1
2
3
4
5
DO (mg
6
7
8
9
6
7
8
9
0.6
0.7
L-1)
Trichoptera (S)
7
6
5
4
3
2
1
0
0
1
2
3
4
5
DO (mg L-1)
Trichoptera (S)
7
6
5
4
3
2
1
0
0.0
0.1
0.2
0.3
0.4
TKN (mg
0.5
0.8
L-1)
Figure 11: Environmental parameters and macroinvertebrate metrics with significant
Spearman correlations for lentic edge habitats (from across multiple river basins) in 1995
Note: Samples collected in the early dry season are shown as open diamonds, those in the late dry season as closed
diamonds.
3.3.2 Flow Change (1995) Edge – multiple river basins
Season had a significant effect on assemblage similarity in edge habitat samples that were
lotic in the early dry of 1995 but lentic by the late dry season of the same year (pseudo F =
2.61, VC = 12.7%, p = 0.0035). While these samples were collected across multiple river
basins, the effect of river basin was not tested due to insufficient degrees of freedom. The first
two axes of the PCO explained 42.0 per cent of the variation in assemblage similarity among
these samples. The vector overlay of macroinvertebrate presence/absence with Spearman
correlations > 0.40 suggested the presence of different groups of taxa may be associated with
the early (lotic) versus late (lentic) dry season assemblages of these edge habitats (Figure
13). Taxa more aligned with the lotic edge habitats in the early dry season of 1995 included
Gomphidae, Leptophlebiidae, Hydropsychidae, Nematoda, Elmidae and Polycentropidae.
Those more aligned with the lentic edge habitats in the late dry season of 1995 included
Noteridae, Hydrophilidae, Veliidae, Orthocladiinae, Ecnomidae, Dytiscidae, Palaemonidae,
NATIONAL WATER COMMISSION — Low flows report series
24
Culicidae, Pleidae, Coenagrionidae, Sphaeriidae, Thiaridae, Notonectidae, Viviparidae,
Atyidae and Corixidae.
Rheophily values (Chessman 2009) were available for all the above taxa except for
Nematoda and Viviparidae. As with the sand habitats, and ignoring the two taxa for which no
rheophily values were available, the ‘late dry lentic’ group of taxa had a lower mean rheophily
value (0.47) than that of the ‘early dry lotic’ group (1.79). SIGNAL grades were available for all
the taxa, and as with the sand habitats, the mean SIGNAL grade of taxa in the ‘late dry lentic’
group for these edge habitats was lower (2.9) than that of the ‘early dry lotic’ group (6.0).
Three out of the six taxa in the ‘early dry lotic’ group were EPT taxa (Polycentropidae and
Hydropsychidae, Trichoptera; Leptophlebiidae, Ephemeroptera) compared with one EPT
taxon from the 16 taxa in the ‘late dry lentic’ group (Ecnomidae, Trichoptera).
Season also had significant effects on environmental parameters and macroinvertebrate
metrics within the Flow Change (1995) Edge group of samples (Mann-Whitney U test, p
<0.05). Lotic edge habitats in the early dry season of 1995 had significantly higher
concentrations of DO (U = 178.5, p = 0.0006) and lower water temperatures (U = 93.0, p =
0.0278) than those in the late dry season when the sampled edges were lentic. The
macroinvertebrate samples from the early dry season had higher mean SIGNAL grades
(avSIG, u = 169.0, p = 0.0053) than those sampled from the same edge habitats in the late
dry season (Figure 14), and avSIG was significantly correlated with both water temperature (r s
= -0.46, p = 0.0318) and DO (rs = 0.50, p = 0.0180) (Figure 15).
As such, there were significant differences in assemblage composition and diversity as well
as differences in water quality in these 1995 edge samples between the early dry season
(when the habitats were in flow) and the late dry season (when the habitats were lentic). As
with the sand habitats, these findings suggested that, along with the loss of flow, the
difference in taxonomic composition between early and late dry seasons may also have been
associated with changes in water quality (lower DO, but higher temperature) and a loss of
sensitive and rheophilous taxa from the assemblages. Indeed, many of the seasonal
differences were consistent with those detected in sand habitats sampled in the same year
(1995) that were also lotic in the early dry season but lentic in the late dry season. For both
the sand and edge habitats, there were significant differences in taxonomic composition of the
assemblages and the late dry season samples had lower DO, higher water temperatures and
lower mean SIGNAL grades. The examined edge habitat samples were collected from
multiple river basins, whereas the examined sand habitat samples were from the Daly River
basin only. This suggested the effect of season on the environmental and biotic
characteristics of habitats that were lotic in the early dry but lentic in the late dry season may
have been strong in comparison to any basin effect, in 1995 at least.
NATIONAL WATER COMMISSION — Low flows report series
25
PCO2 (19.4% of total variation)
40
RP-14
20
DW-05
DW-05
DA-08
ML-02
AD-07
GY-02
DA-09
FN-02
0
ML-02
DA-09
RP-01
DA-08 DA-03
AD-07
EA-02
FN-02
GY-02
RP-14
RP-01
EA-02
DA-03
-20
-40
-20
0
20
PCO1 (22.6% of total variation)
40
40
PCO2 (19.4% of total variation)
Hydrophilidae
Orthocladiinae
Ecnomidae
20
Pleidae
Culicidae
Veliidae
Thiaridae
Notonectidae
Planorbidae
Coenagrionidae
Sphaeriidae
Noteridae
Viviparidae & Hyriidae
Atyidae
Polycentropidae
Corixidae
Elmidae
Dytiscidae
Nematoda
Palaemonidae
0
Hydropsychidae
Leptophlebiidae
Gomphidae
-20
-40
-20
0
20
PCO1 (22.6% of total variation)
40
Figure 12: Principal Coordinate Analysis (PCO) ordination of macroinvertebrate assemblage
similarities among 11 edge habitat samples collected in the early (green upright triangles,
lotic) and late dry season (blue upside down triangles, lentic) in 1995 from multiple river
basins, with vectors showing taxa with Spearman correlations > 0.40 presented separately
(circle represents a vector correlation of 1)
Note: See figures 2 and 3 for river basin codes.
NATIONAL WATER COMMISSION — Low flows report series
26
8
25
avSIG
6
DO (mg L-1)
Temperature (oC)
4.5
30
4
4.0
2
20
3.5
0
Early
Late
Figure 13: Box and whisker plots of water quality parameters and macroinvertebrate metrics
for edge habitats that were lotic in the early dry season of 1995 but lentic in the late dry
season of 1995, sampled across multiple river basins
4.8
4.6
avSIG
4.4
4.2
4.0
3.8
3.6
0
2
4
6
8
10
DO (mg L-1)
4.8
4.6
avSIG
4.4
4.2
4.0
3.8
3.6
20
22
24
26
28
30
32
Temperature (oC)
Figure 14: Water quality parameters and macroinvertebrate metrics with significant Spearman
correlations for edge habitats that were lotic in the early dry season (open diamonds) but
lentic in the late dry season (closed diamonds), sampled across multiple river basins in 1995
NATIONAL WATER COMMISSION — Low flows report series
27
3.3.3 Flow Change (1996) Edge – multiple river basins
Season did not have a significant effect on assemblage similarity in edge habitats that were
lotic in the early dry season of 1996 but lentic in the late dry season of the same year. This
was in contrast to the strong effect of season on assemblage similarity in both edge and sand
habitats that were lotic in the early dry but lentic in the late dry of 1995. Out of interest,
however, the effect of season on environmental parameters and macroinvertebrate metrics of
the 1996 edge samples was investigated (Mann-Whitney U tests). Late dry season water
samples had greater turbidity (U = 77.0, p = 0.0301), higher temperatures (U = 55.0, p =
0.0002) and TKN concentrations (U = 69.5, p = 0.0067), but lower concentrations of NOx (U =
137.0, p = 0.0139) than those in the early dry season. The late dry season samples also had
fewer trichopteran families (U = 132.5, p = 0.0273) and there was a significant negative
correlation between TKN and Trichoptera richness (rs = -0.54, p = 0.0148) across the dry
season as a whole (Figure 16). So while no difference in assemblage similarity could be
detected between seasons, there were differences in water quality that could be related to a
reduced number of trichopteran families in the lentic, late dry season samples from these
edge habitats.
4.5
4
Trichoptera (S)
3.5
3
2.5
2
1.5
1
0.5
0
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
TKN (mg L-1)
Figure 15: Total Kjeldahl nitrogen concentration versus Trichoptera family richness in edge
habitats (sampled across multiple river basins) in 1996
Note: Samples collected in the early dry season (lotic habitats) are shown as open diamonds, those in the late dry
season (lentic habitats) as closed diamonds.
3.4 Antecedent flow history and macroinvertebrate traits and diversity
3.4.1 Sand and edge habitats (Early AUSRIVAS dataset)
For the macroinvertebrate samples used in flow metric analyses, only river basin had a
significant effect on assemblage similarity and this was only in edge habitats (pseudo F =
2.49, p = 0.0011). Neither season nor year, nor any interaction term, had significant effects on
assemblage similarity in edge or sand habitats nor were there significant differences in
similarity among antecedent flow metrics calculated from the dry or wet seasons. Season had
a significant effect on the general flow metrics (FlowOnDay, DsinceWeMax and
DsinceEndWet), but this was to be expected given the nature of these parameters. For edge
habitats, there were also significant effects of both season and river basin on similarity among
water quality and environmental parameters (pseudo F = 2.69, VC = 41.3%, p = 0.0412 for
NATIONAL WATER COMMISSION — Low flows report series
28
the effect of season; pseudo F = 2.60, VC = 86.1%, p = 0.0060 for the effect of basin); and
there was a significant effect of river basin on similarity among macroinvertebrate diversity
and trait metrics (pseudo F = 2.29, VC = 20.9%, p = 0.0461). There were no significant effects
of season, year, river basin or their interactions on similarity among the water quality and
environmental parameters or among macroinvertebrate metrics in sand habitats.
Together, these results indicated that, in edges, the composition and biological traits of
assemblages along with the water quality (conductivity, temperature, concentrations of DO,
TN and TP) and environmental characteristics (mean stream width, mean habitat depth and
current speed) of their habitat differed among the examined river basins, and to some extent
between the early and late dry seasons. Differences among river basins may thus have
confounded generalised, across-basin correlations between assemblage, water quality and
environmental characteristics and antecedent flow metrics associated with edge habitats.
However, there were insufficient data to perform separate correlations for each river basin
and, despite this limitation, several significant correlations were detected. The significant
correlations are detailed below and can also be discerned from PCO ordinations of sample
assemblage similarity with vector overlays of macroinvertebrate metrics, water quality and
environmental parameters and antecedent flow metrics (Figure 17).
In sand habitats (Figure 18), macroinvertebrate richness (S) was negatively correlated with
average and high-flow magnitudes in the antecedent wet season (WeMax: rs = -0.44, p =
0.0353; WeP90: rs = -0.57, p = 0.0045; WeMDF: rs = -0.50, p = 0.0149).
avSIG was negatively correlated with WeP90 (rs = -0.43, p = 0.0431), DrCV (rs = -0.59, p =
0.0028) and the number of days from the end of the wet season to the sample date (r s = 0.42, p = 0.0485). However, avSIG was also negatively correlated with the water temperature
and TN concentration on the day of sampling (rs = -0.63, p = 0.0013; rs = -0.51, p = 0.0129).
avRheo was positively correlated with low and average flow magnitudes in the dry season
leading up to the sample date (DrP10: rs = 0.42, p = 0.0485; DrMDF: rs = 0.42, p = 0.0460),
but negatively with flow variation in the dry season (DrCV: rs = -0.47, p = 0.0238). avRheo
was also positively correlated with the mean daily flow and mean habitat current speed on the
day of sampling and negatively with the water temperature (FlowOnDay: r s = 0.42, p =
0.0451; AVCS: rs = 0.46, p = 0.0287; TEMP: rs = -0.57, p = 0.0045). avTherm was positively
correlated with WeP90 (rs = 0.43, p = 0.0411), and the water conductivity and temperature on
the day of sampling (COND: rs = 0.50, p = 0.0161; TEMP: rs = 0.61, p = 0.0021).
Results from the correlations of season-to-season differences in macroinvertebrate, water
quality and environmental characteristics of sand habitats with season-to-season differences
in antecedent flow characteristics provided further detail (Figure 19). The Bray-Curtis
similarity between sample assemblages increased as difference in MDF on the day of
sampling decreased (rs = -0.38, p = 0.0421) along with differences in low and mean flow
during the dry season leading up to the sample day (DrP10: r s = -0.39, p = 0.0349; DrMDF: rs
= -0.38, p = 0.0418). Difference in the mean SIGNAL grade was positively correlated with
differences in these same flow metrics (FlowOnDay: rs = 0.42, p = 0.0229; DrP10: rs = 0.43, p
= 0.0204; DrMDF: rs = 0.51, p = 0.0046); as was difference in family richness (FlowOnDay: r s
= 0.40, p = 0.0301; DrP10: rs = 0.44, p = 0.0176; DrMDF: rs = 0.39, p = 0.0350). Family
richness difference was also correlated positively with difference in DrP90 (r s = 0.49, p =
0.0066) and the difference in conductivity and TN concentration on the sample day (COND: r s
= 0.38, p = 0.0414; TN: rs = 0.44, p = 0.0162). Difference in the mean SIGNAL grade was also
positively correlated with differences in water temperature (r s = 0.40, p = 0.0336) and
conductivity (rs = 0.37, p = 0.0467) on the day of sampling. EPT family richness difference
increased with the difference in DrMDF (rs = 0.38, p = 0.0417). Difference in the mean
dispersal capacity of families increased with differences in FlowOnDay (r s = 0.38, p = 0.0343)
and DrP10 (rs = 0.39, p = 0.0378). As the difference in the number of days between the end of
the wet season and the sample day increased, so did the difference in the assemblages’
NATIONAL WATER COMMISSION — Low flows report series
29
mean thermophily value (rs = 0.50, p = 0.0059). Finally, differences in mean thermophily and
rheophily were both positively correlated with the difference in conductivity on the day of
sampling (avTherm: rs = 0.40, p = 0.0328; avRheo: rs = 0.39, p = 0.0371).
In edge habitats (Figure 20), macroinvertebrate richness was negatively correlated with flow
variation in the antecedent wet season (WeCV: rs = -0.36, p = 0.0493) but positively
correlated with the mean stream width and water conductivity on the day of sampling (MEWI:
rs = 0.44, p = 0.0136; COND: rs = 0.41, p = 0.0238). avRheo in edge habitats had similar
correlations with flow metrics as in sand habitats, showing positive correlations with DrP10 (r s
= 0.45, p = 0.0107), DrMDF (rs = 0.46, p = 0.0094), but also with DrP90 (rs = 0.37, p = 0.0379)
and antecedent wet season metrics (WeMax: rs = 0.42, p = 0.0198; WeRateFall: rs = 0.39, p
= 0.0317). However, the mean rheophily value of the taxa was also associated with flow and
current speed on the day of sampling (FlowOnDay: rs = 0.46, p = 0.0088; AVCS: r s = 0.58, p
= 0.0006). avTherm was negatively correlated with flow variation in the antecedent wet
season (WeCV: rs = -0.45, p = 0.0111). avSIG was positively correlated with AVCS (r s = 0.36,
p = 0.0451), but negatively with COND (rs = -0.48, p = 0.0065) on the day of sampling.
Season-to-season differences in assemblage characteristics of edge habitats were not
significantly correlated with differences in antecedent flow metrics (p > 0.05), although this
may have been partly due to broadscale differences in assemblage characteristics among
river basins masking the relationships. However, differences in antecedent flow metrics were
significantly correlated with some differences in water quality parameters (Figure 21), as were
some differences in assemblage characteristics. Similarity between the assemblage
composition of samples decreased as the difference in TN concentration increased (r s = 0.30,
p = 0.0487). Difference in the mean rheophily of taxa also correlated positively with the
difference in mean current speed on the day of sampling (rs = 0.34, p = 0.0246).
NATIONAL WATER COMMISSION — Low flows report series
30
MY-04
20
30
MY-04
RP-05
DA-01
DA-07
PCO2 (15.9% of total variation)
PCO2 (17.9% of total variation)
DA-02
20
DA-02
VC-06
VC-06
10
DA-04
EPTs
S
DA-01
avTherm
DA-04
VC-06
DA-02
DA-04
avSIG
SA-02
0
avDC
MY-04
MY-04
MY-04
10
RP-05
DA-07
MY-04
DA-01
DA-04
MY-04
DA-04
MY-07
DA-17
0
avRheo
DA-01
RP-05
DA-04
DA-17 DA-17
avSIG
DA-01 RP-05
VC-06
VC-06
avTherm
VC-06
S
-10
DA-17
DA-04
avDC
VC-06
EPTs
SA-02
AD-03
avRheo
AD-03
DA-04
DA-02
AD-03
MY-04
-20
-10
DA-01
DA-07
DA-01
DA-07
DA-01
-30
-20
-30
AD-03
-20
-10
0
10
20
-30
30
-20
30
-10
0
10
20
30
MY-04
FlowOnDay
20
DrMDF
RP-05
MY-04
DrP10
DA-01
DA-02
20
DA-07
WeRateFall
10
DsinceWeMax
RP-05
WeMax
DA-04
DrCV
VC-06
WeCV
DA-01
VC-06
10
PCO2 (15.9% of total variation)
PCO2 (17.9% of total variation)
DsinceEndWet
DA-02
DA-04
VC-06
DA-02
DA-04
MY-04
MY-04
WeMax
0
SA-02
MY-04
WeP90
WeMDF
WeRateFall
SA-02
DA-04
DA-02
DrP90
DryP10, DrMDF,
FlowOnDay
-10
DA-01
MY-04
MY-07
DryP90
WeMDF
DA-01
WeP90
RP-05
DA-04
MY-04
DA-04
DA-17
DA-04
DA-17 DA-17
VC-06
MY-04
DA-01
DA-01 RP-05
VC-06
DsinceWeMax
VC-06
-10
DA-04
DA-17
WeCV
VC-06
DrCV
AD-03
DsinceEndWet
AD-03
AD-03
-20
AD-03
DA-07
DA-01
DA-07
DA-01
-30
-20
-30
0
DA-07
-20
-10
0
10
20
-30
30
-20
-10
0
10
30
MY-04
20
30
20
MY-04
RP-05
DA-01
DA-02
DA-07
10
DA-04
TN
VC-06
DA-02
TP
DA-01
VC-06
10
DA-04
TEMP
VC-06
AHDE
DA-02
DA-04
0
PCO2 (15.9% of total variation)
PCO2 (17.9% of total variation)
20
MEWI
COND
AVCS
SA-02
MY-04
DO
MY-04
MY-04
SA-02
DA-04
DA-02
RP-05
0
DA-01
RP-05
MEWI
COND
-10
DA-07
DA-01
DA-17 DA-17
TEMP
RP-05
VC-06
DO DA-01
VC-06
VC-06
DA-04
TP
DA-17
VC-06
AD-03
AD-03
AD-03
-20
AD-03
DA-07
DA-01
DA-07
DA-01
-30
-20
-30
MY-04
DA-04
DA-04
TN
MY-04
-10
DA-01
AVCS
MY-04
DA-04
MY-07
DA-17
AHDE
-20
-10
0
10
20
PCO1 (33.5% of total variation in sand macroinvertebrate samples)
30
-30
-20
-10
0
10
20
30
PCO1 (18.9% of total variation in edge macroinvertebrate samples)
Figure 16: Principal Coordinate Analysis (PCO) ordinations of macroinvertebrate assemblage
similarities among 23 sand (left panel) and 31 edge habitat samples (right panel) collected in
the early and late dry seasons from multiple river basins in 1995 and 1996
Notes: Vector overlays in the top, middle and lower panels respectively show all macroinvertebrate diversity and trait
metrics, all antecedent flow metrics, and all contemporaneous water quality and environmental parameters used in
correlation analyses (see text). Large circles represent vector Spearman correlations of 1.
NATIONAL WATER COMMISSION — Low flows report series
31
 Days since wet season Max ~  water temperature
 TN
Max
 Days since end wet season ~  mean SIGNAL grade
 water temperature
 TN
 Flow on sample day ~  mean rheophily value
 DO
 water temperature
 TN & TP
Antecedent wet season
 MDF ~ family richness
Antecedent dry season
 P10 ~  mean rheophily value
 mean current speed
 water temperature
 mean stream width
 TN & TP
 conductivity
 MDF ~ mean rheophily value
 P90 ~  family richness
 TN & TP
 mean SIGNAL grade
 mean current speed
 mean habitat depth
 mean thermophily value
 mean stream width
 conductivity
 Max ~  family richness
 P90 ~  TN & TP
CV ~  mean SIGNAL grade
 mean rheophily value
 mean current speed
 water temperature
 TN
 conductivity
CV ~  DO
 TN
Figure 17: Conceptualisation of significant Spearman correlations between
macroinvertebrate, water quality and environmental characteristics of samples from sand
habitats across multiple river basins and antecedent flow metrics
Note: Macroinvertebrate diversity and trait metrics are shown in bold typeface and double headed arrows indicate
significant correlations between these metrics and water quality or environmental characteristics of habitats on the
day of sampling.
NATIONAL WATER COMMISSION — Low flows report series
32
 Difference in days since wet season Max ~  difference in water temperature
 difference in conductivity
Max
 Difference in days since end wet season ~  difference in mean thermophily value
 difference in water temperature
 difference in TN
 Difference in flow on sample day ~  between-sample assemblage
similarity (Bray Curtis measure)
 difference in TP*
 difference in family richness
 difference in mean SIGNAL grade
 difference in mean dispersal capacity
 difference in conductivity
Antecedent wet season
Antecedent dry season
Correlation between differences in wet
season flow metrics, macroinvertebrate
metrics, water quality and
environmental parameters not tested
 Difference in P10 ~  between-sample assemblage
similarity (Bray Curtis measure)
 difference in TP*
 difference in family richness
 difference in mean SIGNAL grade
 difference in mean dispersal capacity
 difference in conductivity
 Difference in MDF ~  between-sample assemblage
similarity (Bray Curtis measure)
 difference in family richness
 difference in EPT family richness
 difference in mean SIGNAL grade
 Difference in P90 ~  difference in family richness
Figure 18: Conceptualisation of significant Spearman correlations between season-to-season
differences macroinvertebrate and water quality characteristics of samples from sand habitats
across multiple river basins and differences in antecedent flow metrics
Notes: Macroinvertebrate diversity and trait metrics are shown in bold typeface and double headed arrows indicate
significant correlations between these metrics and water quality characteristics of habitats on the day of sampling.
* Correlation is in opposite direction to that which would be expected.
NATIONAL WATER COMMISSION — Low flows report series
33
 Days since wet season Max ~  water temperature
 TN
Max
 Days since end wet season ~  water temperature
 DO
 Flow on sample day ~  mean rheophily value
 mean current speed
 DO
Antecedent wet season
 MDF ~ mean stream width
 water temperature
 P90 ~  mean stream width
 water temperature
 Max ~  mean rheophily value
 mean stream width
 water temperature
 TP
 CV ~  family richness
 mean thermophily value
 mean stream width
 Mean
fall rate ~  mean rheophily value
 mean stream width
 water temperature
Antecedent dry season
 P10 ~  mean rheophily value
 mean current speed
 mean habitat depth
 DO
 TN & TP
 MDF ~ mean rheophily value
 mean habitat depth
 DO
 TN & TP
 P90 ~  mean rheophily value
 mean stream width
 DO
 TP
 CV ~  mean current speed
 mean habitat depth
 DO
 TN & TP
Figure 19: Conceptualisation of significant Spearman correlations between
macroinvertebrate, water quality and environmental characteristics of samples from edge
habitats across multiple river basins and antecedent flow metrics
Note: Macroinvertebrate diversity and trait metrics are shown in bold typeface and double headed arrows indicate
significant correlations between these metrics and water quality or environmental characteristics of habitats on the
day of sampling.
NATIONAL WATER COMMISSION — Low flows report series
34
 Difference in days since wet season Max ~  difference in mean habitat depth
 difference in water temperature
 difference in TN
Max
 Difference in days since end wet season ~  difference in mean habitat depth
 difference in water temperature
 difference in TN
 Difference in flow on sample day ~  difference in mean current speed
 difference in conductivity
Antecedent wet season
Correlation between differences in wet
season flow metrics, macroinvertebrate
metrics, water quality and
environmental parameters not tested
Antecedent dry season
 Difference in P10 ~  difference in mean current speed
 difference in TP
 Difference in CV ~  difference in water temperature
Figure 20: Conceptualisation of significant Spearman correlations between season-to-season
differences in macroinvertebrate and water quality characteristics of samples from edge
habitats across multiple river basins and differences in antecedent flow metrics
3.4.2 Darwin Streams dataset (edge habitats)
PCO ordination of the Darwin Streams presence/absence data at genus as well as family
levels of taxonomic resolution showed that assemblages from one site (DW-21 at Rapid
Creek) were substantively different to those from the three other sites. In particular,
assemblage characteristics in samples from Rapid Creek were associated with the presence
of several Acarina taxa (Figure 22). As a result, mean SIGNAL grades for these samples
tended to be comparatively high (Acarina SIGNAL grade = 6), despite a large proportion of
Rapid Creek’s catchment area being urbanised (NRETAS 2007; Figure 4).
Many significant correlations between assemblage characteristics of samples from the four
sites (calculated from both genus- and family-level presence/absence data) and antecedent
flow metrics were in the opposite direction to that which would be expected (figures 22 and
23). This may have been in part due to influence from Rapid Creek’s unusual sample
characteristics and perhaps the flow characteristics of its urbanised catchment. However,
correlation analyses were repeated without data from Rapid Creek and significant correlations
were similarly counter-intuitive. Results presented below include data from the Rapid Creek
site.
Genus richness decreased as low flow in the antecedent dry period increased (r s = -0.56, p =
0.0205). The lower the MDF on the day of sampling, the higher was the mean SIGNAL grade
of genera (rs = -0.42, p = 0.0440) and richness of EPT families (r s = -0.46, p = 0.0257). Also,
the longer the period between the end of the wet season and the sample date, the higher the
mean rheophily of genera (DrP10: rs = 0.62, p = 0.0073) and the mean SIGNAL grade of
NATIONAL WATER COMMISSION — Low flows report series
35
families (rs = 0.54, p = 0.0257), but the lower the mean thermophily of genera (r s = -0.55, p =
0.0220) and families (rs = -0.62 p = 0.0076). Mean thermophily of families also increased as
low flow in the dry season increased (DrP10: rs = 0.54, p = 0.0257). In addition, Bray-Curtis
similarity of generic composition between samples increased as year-to-year differences in
several flow metrics became greater (WeP90: rs = 0.28, p = 0.0409; WeMDF: rs = 0.29, p =
0.0291; WeMRateFall: rs = 0.27, p = 0.0450; DrCV: rs = 0.45, p = 0.0141). Finally, the
difference in mean dispersal capacity of genera increased as differences decreased in
WeP90 (rs = -0.27, p = 0.0483) and WeMDF (rs = -0.28, p = 0.0359), and the difference in
mean rheophily of genera increased as differences in WeMax (r s = -0.29, p = 0.0340), WeP90
(rs = -0.32, p = 0.0158), WeMDF (rs = -0.28, p = 0.0482) and WeMRateFall (rs = -0.30, p =
0.0269) all decreased.
However, there were significant correlations between the Darwin Streams assemblage
characteristics and antecedent flow metrics for which the directions of correlation were more
intuitive (figures 22 and 23). Mean and high flows in the antecedent wet season were
positively correlated with EPT genus richness (WeMax: rs = 0.54, p = 0.0081; WeP90: rs =
0.60, p = 0.0026; WeMDF: rs = 0.60, p = 0.0024), EPT family richness (WeMax: rs = 0.60, p =
0.0025; WeP90: rs = 0.59, p = 0.0032; WeMDF: rs = 0.59, p = 0.0030) and total family
richness (WeMax: rs = 0.52, p = 0.0105; WeP90: rs = 0.45, p = 0.0298; WeMDF: rs = 0.43, p =
0.0419). Total family richness also decreased as the number of days between the end of the
wet season and the sample date increased (rs = -0.48, p = 0.0218). In addition, generic
composition between samples became less similar as the year-to-year difference in
antecedent dry season low flow increased (DrP10: r s = - 0.43, p = 0.0204) and the difference
in duration since the maximum wet season flow increased (DsinceWeMax: r s = - 0.46, p =
0.0004). Similarity of family-level composition decreased as the difference in duration
between the end of the wet season and the sample date increased (DsinceEndWet: rs = 0.42, p = 0.0245). The year-to-year difference in mean SIGNAL grade of genera increased
with year-to-year differences in antecedent wet and dry flow magnitudes (WeP90: r s = 0.28, p
= 0.0403; DrP10: rs = 0.47, p = 0.0103; DrMDF: rs = 0.42, p = 0.0241). As the difference in
DsinceWeMax increased, difference in the mean thermophily of genera (r s = 0.45, p = 0.0006)
and families increased (rs = 0.33, p = 0.0150); and as the difference in DsinceEndWet
increased, difference in the mean rheophily of genera (rs = 0.40, p = 0.0331) as well as the
mean thermophily of families increased (rs = 0.46, p = 0.0131).
NATIONAL WATER COMMISSION — Low flows report series
36
40
20
2004
2002
Notonectidae
Djalmabatista
Anisoptera
Pyralidae
PCO2 (12.2% of total variation)
Oxus
Fittkauimyia
Coaustraliobates
2001 Nilotanypus
2009
Procladius
Recifella
Limnesia 2001
2002
2007
2004
Rheotanytarsus
Parachironomus
Tasmanocoenis
Wundacaenis
Oecetis
Orthotrichia
?Stictochironomus
Caridinides
2007
2003
2009
Mesoveliidae
Rheocricotopus
2001
2007
2003
2002
2001
2009
0
2003
2007
2007
Larsia
Frontipoda
2009
2009
Corixidae
2003
2001 Harnischia
0
2007
2003 2002
Hydrophilidae
Clypeodytes
Hydrochus
Nanocladius
2001
Empididae
PCO1 (21.3% of total variation)
2009
20
Calamoceratidae
Ecnomina
Unk genus K1
Austrolimnius
Ecnomus
Stempellinella
Dicrotendipes
Noteridae
Veliidae
2001
Ceratopogonidae
Caenidae
Hydrochidae 2009
Sisyriidae
2003
2009
Leptophlebiidae
2004
2004 Corixidae
2004
Acarina
2003
Notonectidae
Elmidae
Ecnomidae
-20
2003
Thienemanniella
2002
2007
Leptoceridae
2002
Palaemonidae
2004
2007 2004
Dytiscidae
2002
2002
2001
2004
-40
-20
-20
0
20
-40
40
-20
0
20
40
20
2004
2002
2001
2009
2007
2003 2002
2009
S
EPTs
2003
2002
2001
2007
avSIG
avDC
2004
2001
0
avRheo
2001
2003
2007
2009
2009
2009
2003
2001
2007
2002
avRheo
S
avSIG
2009
2004
2003
2009
EPTs
2004
avTherm
2004
2003
-20
avTherm
2001
2003
2002
2009
0
PCO1 (21.3% of total variation)
PCO2 (12.2% of total variation)
20
2007
2001
2007
avDC
2003
2007
2002
2004
2007 2004
2002
2002
2001
2004
-40
-20
-20
0
20
-40
40
-20
0
20
40
20
2004
2002
2001
2007
WeMDF
2009
WeMax
2003
20
DrCV
2001
2002
DsinceEndWet
WeCV
2007
DsinceWeMax
2004
2001
WeRateFall
2001
0
2003
DrP90
2009
2009
2001
2003
2007
DsinceZF
2007
FlowOnDay
2003
2002
2003
2001
2002
FlowOnDay
2009
2004
DrMDF
DrP10
DrP90
DsinceEndWet
2004
2003
2009
WeCV
2004
DsinceZF
2003
DsinceWeMax
-20
2007
2002
2009
0
2009
DrMDF
2007
2001
2007
WeP90
PCO1 (21.3% of total variation)
PCO2 (12.2% of total variation)
2009
DrCV
WeMax
WeRateFall
WeMDF
WeP90
2003
DrP10
2002
2004
2007 2004
2002
2002
2001
2004
-40
-20
-20
0
20
PCO1 (32.7% of total variation in macroinvertebrate samples,
based on family-level identification)
-40
40
DW21
DW26
DW31
-20
DW40
0
20
PCO1 (24.0% of total variation in macroinvertebrate samples,
based on family-level identification)
Figure 21: Principal Coordinate Analysis (PCO) ordinations of macroinvertebrate assemblage
similarities among 24 edge habitat samples collected in the early dry season from four sites in
the Darwin Harbour catchment
Notes: PCO based on genus-level presence absence data in left panel; family-level presence/absence data in right
panel. Vector overlays in top panel show taxa with Spearman correlations with the PCO axes > 0.50. Vector overlays
in the middle and lower panels respectively show all macroinvertebrate diversity and trait metrics and antecedent flow
metrics used in correlation analyses (see text). Large circles represent vector correlations of 1.
NATIONAL WATER COMMISSION — Low flows report series
37
 Days since end wet season ~  mean SIGNAL grade of families*
 mean rheophily value of genera*
 family richness
 mean thermophily value of genera*
 mean thermophily value of families*
 Flow on sample day ~  mean SIGNAL grade of genera*
 EPT family richness*
Antecedent wet season
 MDF ~ family richness
Antecedent dry
season
 P10 ~  genus richness*
 mean thermophily value of families*
 EPT genus richness
 EPT family richness
 CV ~  mean rheophily value of genera
 P90 ~  family richness
 EPT genus richness
 EPT family richness
mean rheophily value of families
 Max ~  family richness
 EPT genus richness
 EPT family richness
 Mean
fall rate ~  EPT genus richness
 mean rheophily value of families
Figure 22: Conceptualisation of significant Spearman correlations between macroinvertebrate
characteristics of samples from edge habitats in the Darwin Harbour catchment and
antecedent flow metrics
* Correlation is in opposite direction to that which would be expected.
NATIONAL WATER COMMISSION — Low flows report series
38
 Difference in days since wet season Max ~  between-sample assemblage
similarity of genera (Bray Curtis
measure)
 difference in mean thermophily
of genera and families
Max
 Difference in days
since end wet season ~  between-sample assemblage
similarity of genera and families
(Bray Curtis measures)
 difference in mean rheophily
value of genera
 difference in mean thermophily
value of families
Flow on sample day
Antecedent wet season
 Difference in MDF ~ between-sample assemblage
similarity of genera (Bray Curtis
measure)*
 difference in mean rheophily
value of genera*
 Difference in P90 ~  between-sample assemblage
similarity of genera (Bray Curtis
measure)*
 difference in mean SIGNAL
grade of genera
 difference in mean dispersal
capacity of genera*
 difference in mean rheophily
value of genera*
Antecedent dry
season
 Difference in P10 ~  between-sample assemblage
similarity of genera (Bray Curtis
measure)
 difference in mean SIGNAL
grade of genera
 Difference in MDF ~  difference in mean SIGNAL
grade of genera
 Difference in P90 ~  difference in mean dispersal
capacity of families
 Difference in CV ~  between-sample assemblage
similarity of genera (Bray Curtis
measure)*
 Difference in Max ~ difference in mean rheophily
value of genera*
 Difference in
mean fall rate ~  between-sample assemblage
similarity of genera (Bray Curtis
measure)*
 difference in mean rheophily
value of genera*
Figure 23: Conceptualisation of significant Spearman correlations between year-to-year
differences in macroinvertebrate characteristics of samples from edge habitats in the Darwin
Harbour catchment and differences in antecedent flow metrics
* Correlation is in opposite direction to that which would be expected.
NATIONAL WATER COMMISSION — Low flows report series
39
4. Discussion
Macroinvertebrate assemblages of the streams and rivers sampled across the Northern
Territory in the early dry season tended to be more biodiverse and the taxa more sensitive to
pollutants and more rheophilous than those sampled in the late dry season. In addition, the
waters of the sand and edge habitats harbouring the macroinvertebrates were often cooler,
more oxic and less turbid and nutrient-rich in the early dry season than towards the end of the
dry season. There were also significant changes in assemblage composition between the
early and late dry seasons, particularly when habitats were in flow during the early dry season
but lentic during the late dry season. These general findings supported the hypotheses that
differences would exist in assemblage and habitat-scale environmental characteristics of sites
between the early and late dry seasons.
The changes observed between early and late dry seasons also support findings of previous
studies on Magela Creek fauna (East Alligator River basin), for which taxonomic richness has
been observed to decline over the dry season and to correlate with water temperature,
turbidity and other water quality parameters (Marchant 1982; Outridge 1988; Paltridge et al.
1997). Elsewhere in Australia, similar shifts in assemblage composition in response to
extended dry periods have been observed. For example, in Victorian streams, edge
assemblages shifted during an extended dry period (drought), which was characterised by
reduced flow and increased lentic habitat, due to the replacement of water-quality-sensitive
and rheophilous taxa with more pollution-tolerant taxa associated with still waters (Rose et al.
2008).
In the present study, however, river basin had a significant effect on assemblage composition
such that assemblages from streams and rivers in the same river basin were more similar to
each other than to those from other river basins. Thus, large-scale variation in factors such as
geology, climate and groundwater supply (which affect stream geomorphology, flow
permanence and water quality among other things) likely plays a role in distinguishing the
macroinvertebrate assemblages of different river basins in the region. This is despite previous
research finding little structuring of family-level macroinvertebrate data across northern
Australia (Cook et al. 2010; see also Kay et al. 1999).
In addition, the strongest effects of season on assemblage and habitat-scale environmental
characteristics were found when waters of sand and edge habitats were flowing during the
early dry season but had ceased to flow by the late dry season. This change in flow status
was evidenced by data on current speed in the sampled habitats as well as mean daily flow
data from nearby gauging stations. Interestingly, the effect of the change from lotic (early dry
season) to lentic flow status (late dry season) on assemblage composition, diversity and
biological traits as well as the water quality of their habitats was detected in sand habitats
within the Daly River basin, as well as in edge habitats across multiple river basins. For both
habitat types, change in assemblage composition between the early (lotic) and late (lentic) dry
seasons was accompanied by a decrease in DO concentrations, increase in water
temperatures and a reduction in the sensitivity and rheophily of the macroinvertebrate taxa.
Thus, habitats in the study region that change from lotic to lentic through the course of a dry
season may be the most likely to exhibit pronounced changes in their physical characteristics
and macroinvertebrate assemblages, regardless of the river basin they reside in. Strong
spatial effects of dry season flow status, above those of river basin, on macroinvertebrate
assemblages have been found among waterbodies in the Gulf of Carpentaria drainage
division (Leigh & Sheldon 2009). The present study suggests that temporal change in dry
season flow status of habitats may be an equally strong driver of assemblage structure, and
also of biological traits.
NATIONAL WATER COMMISSION — Low flows report series
40
The link here between ‘low flows’ and the dry season in these river systems, particularly in
reference to habitat flow status, can be thought of as operating in three ways. Firstly, for
habitats that remain lotic throughout the dry season, changes in assemblage characteristics
and their environment between the early and late dry season may be due to effects of an
extended low-flow period. Secondly and thirdly, changes that occur in habitats that remain
lentic throughout the dry season may be due to effects of an extended zero-flow period,
whereas changes that occur in habitats that switch from lotic to lentic may be in response to
the loss of flow during an extended low-flow period.
As stated, the strongest effects of season (early versus late dry) on assemblages and their
environment were found in habitats that switched flow status, but an effect of season on
assemblage composition was also found in edge habitats that remained lentic throughout the
dry season. A possible implication of this is that the macroinvertebrate fauna of the study
region are generally well-adapted to natural periods of extended low flows, but that cease-toflow events and their duration play a major role in structuring assemblages, taxonomically and
functionally. These events and their duration are likely to affect direct and indirect responses
in the macroinvertebrate assemblages. For example, direct negative responses of
rheophilous taxa to long periods of zero flow may be accompanied by negative responses of
sensitive taxa to the changes in water quality associated with cease-to-flow events.
Reduced flows are known to affect physical and chemical characteristics of refugial
waterbodies. In particular, the conductivity and diel temperature ranges usually increase and
DO concentrations usually decrease as the waterbodies dry out (Boulton & Suter 1986). Many
macroinvertebrates are sensitive to these water quality parameters (Chessman 2003) and it is
therefore not surprising that tolerant and nonrheophilic taxa are favoured by low-flow
conditions, and particularly when flow ceases for extended periods. Indeed, the simple
dichotomy of flow status (lotic versus lentic low flow) is unlikely to explain all flow-related
changes in macroinvertebrate assemblage characteristics or the physical and chemical
conditions of their habitats during the dry season. The duration of low-flow or cease-to-flow
events (as discussed above) and other aspects of low-flow hydrology (e.g. magnitude,
variability and rate of change) in relation to the dry season sample date and the flow events
occurring in the previous wet season are likely influence the structure of assemblages. In the
present study, several macroinvertebrate diversity and trait metrics as well as habitat-scale
environmental and water quality parameters were correlated with flow metrics calculated from
the wet and also the dry season periods antecedent to the sampling events, as hypothesised.
In sand habitats across the Northern Territory, higher magnitudes of low flow in the
antecedent wet season were associated with a more rheophilous assemblage in the dry
season, and greater flow variation in the dry season leading up to the sample date was
associated with a more tolerant (less pollution-sensitive) assemblage. However, rheophily of
the assemblages was low when the flow magnitude and current velocity on the day of
sampling were also low. In addition, large changes in low-flow magnitudes of the antecedent
dry season and large changes in water quality and flow magnitudes on the day of sampling
between any two sampling events (e.g. between the early and late dry seasons or between
two dry season years) were associated with large changes in assemblage richness, rheophily
and sensitivity and with greater dissimilarity in composition. Changes in edge habitats across
multiple river basins of the Northern Territory were, in general, similar to those in sand
habitats. However, consistent relationships between hydrology and the habitat and
assemblage characteristics in these sand and edge habitats were swayed towards duration of
the low-flow (dry season) period before sampling, the duration between the antecedent wet
season flow peak and the sample date, the flow magnitude on the sample date and the
magnitude of the low-flow threshold (10th percentile of flow) in the antecedent dry season
period, rather than wet season hydrology or high-flow characteristics. Longer durations and
lower flow magnitudes were consistently associated with assemblages with reduced overall
rheophily, and habitats with higher water temperatures, conductivities, nutrient concentrations
NATIONAL WATER COMMISSION — Low flows report series
41
and lower concentrations of DO. In terms of duration, these findings link well with research on
drought, low flows and water withdrawals in other systems throughout the world, whereby the
cumulative duration of low-flow events has a major effect on the ecological responses of
aquatic biota (e.g. Dewson et al. 2007; Miller et al. 2007; Finn et al. 2009).
Relationships between flow metrics and invertebrate metrics were not always as expected
within the Darwin Streams dataset. This may have been in part due to influence from the
distinct assemblage characteristics of the most urbanised site (Rapid Creek) and the flow
characteristics of its urbanised catchment. However, correlation analyses were repeated
without data from Rapid Creek and significant correlations were similarly counter-intuitive.
This perhaps suggests that low-flow-ecology relationships in urban streams may be more
difficult to describe and understand than those in the less developed regions of the Northern
Territory. There were thus fewer consistencies between relationships in edge habitats of the
Darwin Harbour catchment and those of the multi-river basin sand and edge habitats.
However, there appeared to be a consistent link between assemblage characteristics and
certain aspects of low-flow hydrology, specifically the flow magnitudes on the day of sampling
and the low-flow threshold of the antecedent dry season. In particular, when large differences
in the low-flow magnitudes occurred between any two dry season years, there was greater
dissimilarity in composition of the Darwin Harbour assemblages. Future studies may wish to
take a more experimental approach to examining low flows and macroinvertebrate responses
in streams within the Darwin Harbour catchment to control or better account for the effects of
multiple stressors.
4.1 Conclusion
Causal mechanisms of assemblage responses to low flows and the dry season were not
examined explicitly in this study. In addition, the ability to draw conclusions about these
mechanisms was restricted by the confounding effects of river basin and multiple stressors
(low-flow hydrology and both physical and chemical changes to habitat) on assemblage
characteristics. Future studies may need to examine low-flow-ecology relationships within
particular river basins and/or use a filters approach to control for variation in the physical and
chemical environment among streams, providing sufficient data are available.
Based on the findings of this study, three facets of the dry season and antecedent hydrology
are proposed as important direct and indirect drivers of dry season assemblage composition,
diversity and biological traits in the highly seasonal streams and rivers of the Northern
Territory that were examined. These are: dry season duration before sampling, cease-to-flow
events, and flow magnitude on the day of sampling. Dry season assemblages sampled
towards the end of the dry season (especially from lentic habitats that tend to be in flow
during the early dry season or those sampled on days of lower discharge) may be expected to
have fewer taxa and be characterised by non-rheophilous and tolerant taxa, than
assemblages sampled earlier in the dry season or on days of higher discharge. While
macroinvertebrate fauna of these highly seasonal streams and rivers are no doubt welladapted to regular and natural periods of extended low flow, anthropogenic modification of
the dry season (low) flow regime may alter the resistance and resilience of assemblages to
low-flow events and their duration (Boulton 2003) such that the early wet season recovery of
fauna (e.g. Outridge 1988) may no longer be so reliable.
NATIONAL WATER COMMISSION — Low flows report series
42
Shortened forms
DO
dissolved oxygen
FEG
Flow Exposure Groups
FRP
filterable reactive phosphorus
MDF
Mean daily flow
MEWI
mean stream width
NRETAS
Department of Natural Resources, Environment, the Arts and Sport (NT)
PERMANOVA
Permutational Multivariate Analysis of Variance
TKN
total Kjeldahl nitrogen
TP
total phosphorus
TRaCK
Tropical Rivers and Coastal Knowledge
NATIONAL WATER COMMISSION — Low flows report series
43
References
Anderson MJ 2001, ‘A new method for nonparametric multivariate analysis of variance,
Austral Ecology 26: 32–46.
Boulton AJ 2003, ‘Parallels and contrasts in the effect of drought on stream macroinvertebrate
assemblages’, Freshwater Biology 48: 1173–1185.
Boulton, AJ & Suter PJ 1986, ‘Ecology of temporary streams – an Australian perspective’, in
De Deckker P & Williams WD (eds), Limnology in Australia (pp486–496), Council for
Scientific and Industrial Research, Junk, Melbourne.
Brooks AJ, Chessman BC & Haeusler T 2011, ‘Macroinvertebrate traits distinguish
unregulated rivers subject to water abstraction’, Journal of the North American
Benthological Society 30: 419–435.
Bunn SE & Arthington AH 2002, ‘Basic principles and ecological consequences of altered flow
regimes for aquatic biodiversity’, Environmental Management 30: 492–507.
Chessman BC 2001, SIGNAL 2: a scoring system for macro-invertebrates ('water bugs') in
Australian rivers, NSW Department of Land and Water Conservation, Australia.
—2003, ‘New sensitivity grades for Australian river macroinvertebrates’, Marine and
Freshwater Research 54: 95–103.
—2009, ‘Climatic changes and 13-year trends in stream macroinvertebrate assemblages in
New South Wales, Australia’, Global Change Biology 15: 2791–2802.
Chessman BC, Royal MJ & Muschal M 2008, ‘Does water abstraction from unregulated
streams affect aquatic macrophyte assemblages? An evaluation based on comparisons
with reference sites’, Ecohydrology 1: 67–75.
Chessman BC, Jones HA, Searle NK, Growns IO & Pearson MR 2010, ‘Assessing effects of
flow alteration on macroinvertebrate assemblages in Australian dryland rivers’,
Freshwater Biology 55: 1780–1800.
Cook B, Pusey B, Hughes J & Kennard M 2010, ‘Compilation of species distribution datasets
for use as biodiversity surrogates’, in Kennard MJ (ed.), Identifying high conservation
value aquatic ecosystems in northern Australia, final report for the Department of
Environment, Water, Heritage and the Arts and the National Water Commission (pp 57–
74), Charles Darwin University, Darwin.
Dewson ZS, James ABW & Death RG 2007c, ‘A review of the consequences of decreased
flow for instream habitat and macroinvertebrates’, Journal of the North American
Benthological Society 26: 401–415.
Finn MA, Boulton AJ & Chessman BC 2009, ‘Ecological responses to artificial drought in two
Australian rivers with differing water extraction’, Fundamental and Applied
Limnology/Archiv für Hydrobiologie 175: 231–248.
Gayraud S, Statzner B, Bady P, Haybachp A, Scholl F, Usseglio-Polatera P & Bacchi M 2003,
‘Invertebrate traits for the biomonitoring of large European rivers: an initial assessment
of alternative metrics’, Freshwater Biology 48: 2045–2064.
Growns IO & Davis JA 1994, ‘Longitudinal changes in near-bed flows and macroinvertebrate
communities in a Western Australian stream’, Journal of the North American
Benthological Society, 13, 417–438.
Kay WR, Smith MJ, Pinder AM, McRae JM, Davis JA & Halse SA 1999, ‘Patterns of
distribution of macroinvertebrate families in rivers of north-western Australia’,
Freshwater Biology 41:299–316.
NATIONAL WATER COMMISSION — Low flows report series
44
Leigh C & Sheldon F 2008, ‘Hydrological changes and ecological impacts associated with
water resource development in large floodplain rivers in the Australian tropics’, River
Research and Applications 24: 1251–1270.
—2009, ‘Hydrological connectivity drives patterns of macroinvertebrate biodiversity in
floodplain rivers of the Australian wet/dry tropics’, Freshwater Biology 54: 549–571.
Lloyd J & Cook S 2001, Northern Territory AUSRIVAS: Australian River Assessment Scheme
sampling and processing manual, Natural Resources Division, Department of Lands,
Planning and Environment, Northern Territory.
Marsh N, Sheldon F & Rolls R 2012, Synthesis of case studies quantifying ecological
responses to low flows, National Water Commission, Canberra.
Marsh NA, Stewardson MJ & Kennard MJ 2003, River Analysis Package, Cooperative
Research Centre for Catchment Hydrology, Monash University, Melbourne.
Marchant R 1982, ‘Seasonal variation in the macroinvertebrate fauna of billabongs along
Magela Creek, Northern Territory’, Australian Journal of Marine and Freshwater
Research 33: 329–342.
—1989, ‘A subsampler for samples of benthic invertebrates’, Bulletin of the Australian Society
for Limnology 12: 49–52.
McMahon TA & Finlayson BL 2003, ‘Droughts and anti-droughts: the low flow hydrology of
Australian rivers’, Freshwater Biology 48: 1147–1160.
Miller SW, Wooster D & Li JL 2010, ‘Does species trait composition influence
macroinvertebrate responses to irrigation water withdrawals: evidence from the
Intermountain West, USA’, River Research and Applications 26: 1261–1280.
NRETAS 2007, Monitoring in the Darwin Harbour catchment, Northern Territory Government.
Available online at: http://www.nt.gov.au/nreta/water/aquatic/ausrivas/river.html
(accessed July 2011).
Outridge P 1988, ‘Seasonal and spatial variations in benthic macroinvertebrate communities
of Magela Creek, Northern Territory’, Australian Journal of Marine and Freshwater
Research 39: 211–223.
Paltridge RM, Dostine PL, Humphrey CL & Boulton AJ 1997, ‘Macroinvertebrate
recolonization after re-wetting of a tropical seasonally-flowing stream (Magela Creek,
Northern Territory, Australia), Marine and Freshwater Research 48: 633–645.
Perry GLW & Bond NR 2009, ‘Spatially explicit modeling of habitat dynamics and fish
population persistence in an intermittent lowland stream’, Ecological Applications 19:
731–746.
Petheram C, McMahon TA & Peel MC 2008, ‘Flow characteristics of rivers in northern
Australia: implications for development’, Journal of Hydrology 357: 93–111.
Poff NL 1997. ‘Landscape filters and species traits: towards mechanistic understanding and
prediction in stream ecology’, Journal of the North American Benthological Society 16:
391–409.
Poff NL, Olden JD, Vieira NKM, Finn DS, Simmons MP & Kondratieff BC 2006, ‘Functional
trait niches of North American lotic insects: traits-based ecological applications in light
of phylogenetic relationships’, Journal of the North American Benthological Society 25:
730–755.
Poff NL, Richter BD, Arthington AH, Bunn SE, Naiman RJ, Kendy E, Acreman M, Apse C,
Bledsoe BP, Freeman MC, Henriksen J, Jacobson RB, Kennen JG, Merritt DM,
O'Keeffe JH, Olden JD, Rogers K, Tharme RE & Warner A 2010, ‘The ecological limits
NATIONAL WATER COMMISSION — Low flows report series
45
of hydrologic alteration (ELOHA): a new framework for developing regional
environmental flow standards, Freshwater Biology 55: 147–170.
Rolls RJ, Leigh C & Sheldon F (in review), Mechanistic effects of low flow hydrology on
riverine ecosystems: ecological principles and consequences of alteration.
Rose P, Metzeling L & Catzikiris S 2008, ‘Can macroinvertebrate rapid bioassessment
methods be used to assess river health during drought in south eastern Australian
streams?’ Freshwater Biology 53: 2626–2638.
Wood PJ, Boulton AJ, Little S & Stubbington R 2010, ‘Is the hyporheic zone a refugium for
aquatic macroinvertebrates during severe low flow conditions?’ Fundamental and
Applied Limnology 176: 377–390.
Zeug SC & Winemiller KO 2008, ‘Relationships between hydrology, spatial heterogeneity, and
fish recruitment dynamics in a temperate floodplain river’, River Research and
Applications 24: 90–102.
Reports in the low flow series
Balcombe SR & Sternberg D 2012, Fish responses to low flows in dryland rivers of western
Queensland, National Water Commission, Canberra.
Barma Water Resources & Sinclair Knight Merz 2012, Low-flow hydrological monitoring and
modelling needs, report by for the National Water Commission, Canberra.
Barmah D & Varley I 2012a, Hydrologic modelling practices for estimating low flows –
stocktake, review and case studies, National Water Commission, Canberra
Barmah D & Varley I 2012b, Hydrologic modelling practices for estimating low flows –
guidelines, National Water Commission, Canberra
Bond N 2012, Fish responses to low-flows in lowland streams: a summary of findings from the
Granite Creeks system, Victoria, National Water Commission, Canberra.
Bond N, Thomson J & Reich P 2012, Macroinvertebrate responses to antecedent flow, longterm flow regime characteristics and landscape context in Victorian rivers, National
Water Commission, Canberra.
Chessman B et al 2012, Macroinvertebrate responses to low-flow conditions in New South
Wales rivers, National Water Commission, Canberra.
Deane D 2012, Macroinvertebrate and fish responses to low flows in South Australian rivers,
National Water Commission, Canberra.
Dostine PL & Humphrey CL 2012, Macroinvertebrate responses to reduced baseflow in a
stream in the monsoonal tropics of northern Australia, National Water Commission,
Canberra.
Hardie, SA et al 2012, Macroinvertebrate and water quality responses to low flows in
Tasmanian rivers, National Water Commission, Canberra.
Kitsios A et al 2012, Fish and invertebrate responses to dry season and antecedent flow in
south-west Western Australian streams, National Water Commission, Canberra.
Leigh, C 2012, Macroinvertebrate responses to dry season and antecedent flow in highly
seasonal streams and rivers of the wet-dry tropics, Northern Territory, National Water
Commission, Canberra.
Mackay S et al; 2012, Low-flow hydrological classification of Australia, National Water
Commission, Canberra.
Marsh N et al 2012, Synthesis of case studies quantifying ecological responses to low flows,
National Water Commission, Canberra.
NATIONAL WATER COMMISSION — Low flows report series
46
Marsh N et al 2012, Guidance on ecological responses and hydrological modelling for lowflow water planning, National Water Commission, Canberra.
Rolls R et al 2012, Review of literature quantifying ecological responses to low flows, National
Water Commission, Canberra.
Rolls R et al 2012, Macroinvertebrate responses to prolonged low flow in sub-tropical
Australia, National Water Commission, Canberra.
Sheldon F et al 2012, Early warning, compliance and diagnostic monitoring of ecological
responses to low flows, National Water Commission, Canberra.
Smythe-McGuiness Y et al 2012, Macroinvertebrate responses to altered low-flow hydrology
in Queensland rivers, National Water Commission, Canberra.
NATIONAL WATER COMMISSION — Low flows report series
47