Fish and invertebrate responses to dry
season and antecedent flow in southwest Western Australian streams
A. Kitsios1, L. Galvin1, C .Leigh2 and T. Storer1
1
Department of Water, Western Australia
2
Griffith University
Low flows report series, June 2012
NATIONAL WATER COMMISSION — Low flows report series
ii
© 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 from the Commonwealth.
Requests and enquiries concerning reproduction and rights should be addressed to the
Commonwealth Copyright Administration, Attorney General’s Department, National Circuit,
Barton ACT 2600 or posted at www.ag.gov.au/cca.
Online/print: ISBN: 978-1-921853-78-4
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:
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.
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 or the
State Government of Western Australia.
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 the Department of Water on behalf of
the National Water Commission.
NATIONAL WATER COMMISSION — Low flows report series
iv
Contents
Executive summary ..................................................................................................................vii
Report context ......................................................................................................................... viii
1
Introduction ...................................................................................................................... 1
2
Approach ......................................................................................................................... 2
2.1
Site network ......................................................................................................... 2
2.2
Research questions ............................................................................................. 4
2.3
Data requirements ............................................................................................... 4
3
Methods ........................................................................................................................... 7
4
Results ............................................................................................................................. 9
4.1
Low-flow variables ............................................................................................... 9
4.2
Fish abundance ................................................................................................. 11
4.3
Fish diversity ...................................................................................................... 13
4.4
Macroinvertebrate low-flow traits ....................................................................... 14
4.5
BIOENV analyses .............................................................................................. 15
5
Discussion ..................................................................................................................... 17
5.1
Low-flow classifications ...................................................................................... 17
5.2
Ecological relationships ..................................................................................... 17
5.3
Low flow and pools ............................................................................................ 18
5.4
Sampling regime ................................................................................................ 18
6
Conclusion ..................................................................................................................... 19
Appendix A .............................................................................................................................. 20
Shortened forms ...................................................................................................................... 26
References .............................................................................................................................. 27
Tables
Table 1: Macroinvertebrate trait hypotheses with respect to low-flow classes
representing a gradient of change from class 1 (strongly perennial) through
to class 6 (highly ephemeral) ............................................................................................. 4
Table 2: Macroinvertebrate low-flow trait groups and categories (adapted from
Rolls 2011) ......................................................................................................................... 5
Table 3: Low-flow variables ....................................................................................................... 6
Table 4: BIOENV and ANOSIM analyses.................................................................................. 8
Table 5: Results of the BIOENV correlation analysis (Spearman ranked
correlation of fish abundance similarity matrix with the water quality dataset) ................ 16
Table 6: Results of the BIOENV correlation analysis (Spearman ranked
correlation of fish diversity measures similarity matrix with the water quality
dataset) ............................................................................................................................. 16
Table 7: Results of the BIOENV correlation analysis (Spearman ranked
correlation of macroinvertebrate low-flow traits similarity matrix with the
water quality dataset) ....................................................................................................... 16
Figures
Figure 1: Spatial extent of sampling sites with corresponding low-flow
classification ....................................................................................................................... 3
Figure 2: NMDS based on low-flow variables separated by low-flow
classifications ..................................................................................................................... 9
Figure 3: NMDS based on low-flow variables separated by low-flow
classifications overlain with low-flow variables as vectors (correlation >0.5) ................... 10
Figure 4: NMDS based on low-flow variables separated by EPdata factor............................. 11
Figure 5: NMDS based on fish abundance ............................................................................. 12
Figure 6: NMDS based on fish abundance with species as vectors (correlation
>0.4) ................................................................................................................................. 12
NATIONAL WATER COMMISSION — Low flows report series
v
Figure 7: NMDS based on fish abundance with water quality as vectors
(correlation >0.4) .............................................................................................................. 13
Figure 8: NMDS based on fish diversity .................................................................................. 13
Figure 9: NMDS based macroinvertebrate low-flow traits ....................................................... 14
Figure 10: NMDS based on macroinvertebrate low-flow traits showing
correlations > 0.8. ............................................................................................................. 15
NATIONAL WATER COMMISSION — Low flows report series
vi
Executive summary
The south-west of Western Australia (SWWA) is one of the world’s 34 biodiversity hotspots.
The aquatic ecology has a high degree of endemism, unique species assemblages and low
species richness. Recent changes in climate and land use have altered the low-flow
characteristics of many SWWA streams and in response, the ecological characteristics have,
and are continuing, to change.
The project aimed to identify ecological indicators of low-flow stress to guide the management
of systems in an increasing drying climate and under growing pressure for water resources.
Low-flow classifications (Mackay et al. 2012) developed as part of this project have been
applied to the rivers of the SWWA and have been used in interpreting the linkages between
low-flow conditions and the ecology of these rivers.
A large and geographically diverse spatial network of 97 river health monitoring sites from two
river health programs were included in this study. Associated field work was conducted during
the spring and summer of 2008–09 and the spring of 2009 with one sampling event per site.
This resulted in a biological database consisting of fish and macroinvertebrate populations,
and environmental variables including water quality, macroinvertebrate habitat and climate.
The hydrological characteristics of each site were calculated over a period of 15 years. Lowflow variables included the number and variation of zero-flow days in the preceding years,
monthly low-flow percentiles, annual minima of 30 day means and the variation in the annual
minima of 30 day means.
The relationship between the fish abundance, fish diversity measures and macroinvertebrate
low-flow traits in response to low-flow variables was examined separately by non-parametric
multivariate analyses performed using the PRIMER v6 (Plymouth Routines in Multivariate
Ecological Research) package (Clarke & Warwick, 2001).
Although there was tight clustering of sites based on their low-flow characteristics, this
contrasted with large variation in the corresponding biotic assemblages. The sites classified
as ephemeral or moderately ephemeral (low-flow classes 3 and 4) supported animals with
traits suited to conditions of low flow, tolerance of higher levels of salinity, short reproduction
times, air breathing and dispersal by flight. In addition to the hydrological characteristics, the
biotic assemblages (particularly fish abundance) were also influenced by water quality,
geography and land use changes.
Context is important in the interpretation of results. Recent changes in land use, climate and
water use was helpful in explaining many of the patterns in biotic assemblages. The presence
of pools was another factor that aided the interpretation of results which was not
characterised in the low-flow variables.
The drying or connecting of pools within SWWA needs further investigation as this may be
more important for interpreting the ecology than the duration or magnitude of the low-flow
conditions. Moreover, an index representing the presence or absence of pools is required in
any future work of this scale.
NATIONAL WATER COMMISSION — Low flows report series
vii
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 National Water Commission’s Low Flow
Ecological Recovery and Response Project. The circles represent 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
viii
1 Introduction
This report explores hydrological and ecological relationships in rivers in south west Western
Australia (SWWA). It is one of 11 case studies around Australia that have been prepared for
the National Water Commission as part of the Low Flow Ecological Response and Recovery
Project.
As part of this series of work, the Australian Rivers Institute at Griffith University created a
low-flow hydrological classification of Australia (Mackay et al. 2012). The classification ranges
from strongly perennial to highly ephemeral and in this document is referred to as the ‘lowflow classification’1. This classification was applied to rivers of SWWA and used to interpret
the linkages between low-flow conditions and ecology of these rivers.
SWWA is geographically isolated and one of the world’s 34 diversity hotspots (Conservation
International 2007). The aquatic ecology has characteristically low species richness, unique
species assemblages and a high degree of endemism. SWWA has a Mediterranean climate,
with rivers that are relatively short in length (compared to other states), ephemeral and
unregulated.
With recent changes in climate and land use, the streams of SWWA have also started to
change. Streams that were once permanently flowing are drying due to land use changes
such as tree plantations, groundwater and surface water abstraction and lower rainfall. Other
sites that were historically ephemeral now also have summer flows, possibly due to
urbanisation (Barron et al. 2010), irrigation (Department of Water 2011) or dam releases.
1
The low-flow classification should not be confused with the ‘low-flow variables’ which are a Western Australianspecific dataset used to describe the antecedent low-flow conditions of the ecological sampling network.
2 Approach
Existing hydrological and biological information collected from SWWA river systems was
analysed to identify any linkages between ecology and the antecedent low-flow conditions.
2.1 Site network
The datasets used in the analysis were sourced from two river health programs, the River
Health Assessment Scheme (RHAS) and the Framework for the Assessment of River and
Wetland Health (FARWH). Field work was conducted during the spring and summer of 2008–
09 and the spring of 2009.
Several sites were removed from the initial database due to missing data or the presence of
outliers. In total 97 sites were used in the final analysis (Figure 1). Where possible, the sites
were classified according to the national low-flow hydrological classification (Mackay et al.
2012). Some sites are classified as ‘n/a’ because the gauging stations used to generate data
for these sites were not classified. A number of the unclassified streams are characteristic of
perennial rivers thus the existing classification does not encompass the total range of
hydrological variability seen in Western Australian rivers. The entire site network has also
been classified using a more recent flow regime (1992–2008) but this has not been included
in the analysis that follows. It will be useful in future assessments.
NATIONAL WATER COMMISSION — Low flows report series
2
Figure 1: Spatial extent of sampling sites with corresponding low-flow classification
NATIONAL WATER COMMISSION — Low flows report series
3
2.2 Research questions
A number of research questions were considered before starting the analysis, with the
emphasis on finding relationships between low flow and ecology.
1) Do patterns of variation in low-flow hydrology affect patterns of variation in biotic
assemblages?
2) Can these ecological patterns be explained by other environmental factors?
3) Are there differences among the low-flow classifications in terms of composition or
diversity in the macroinvertebrate traits and fish assemblages or characteristics of
water quality?
Aspects of the first question are addressed in Table 1, illustrating a gradient of
macroinvertebrate trait characteristics that change from the strongly perennial sites to the
highly ephemeral sites.
Table 1: Macroinvertebrate trait hypotheses with respect to low-flow classes representing a
gradient of change from class 1 (strongly perennial) through to class 6 (highly ephemeral)
1.
2.
3.
Strongly
Weakly
Marginally
perennial
perennial
ephemeral
4.
Ephemeral
5.
6.
Moderately
Highly
ephemeral
ephemeral
Salinity
tolerance
Low
a
High
Voltinism
Semi – uni
Multi
Reproduction
type
Aquatic
Food source
(feeding
niche)
Greater variety of
FFGs, including
filter feeders
Respiration
In water (gills)
Duration of
life out of
water
Short (dominated
by fully aquatic life
histories)
Occurrence
of drift
Comparatively
high
Adult
dispersal
No
Minimum
time to
reproduction
Longer
Terrestrial
Reduced species
diversity (e.g.
generalists may
dominate)
In air
Long (dominated by
semi-aquatic and
surface dwellers)
Comparatively lowb
Yes
Shorter
a: except where systems are naturally saline or have secondary salinisation
b: except during spates and drawdown events
2.3 Data requirements
A range of ecological and hydrological variables were identified for possible inclusion in the
multivariate analysis. Only variables with sufficient data and variation were selected for final
inclusion. Full lists of variables are available in Appendix A.
NATIONAL WATER COMMISSION — Low flows report series
4
2.3.1 Ecological data
Fish and crayfish
Fish and crayfish abundance and diversity measures were available at 90 sites. Data were
collected in line with standard assessment methods (Storer et al. 2011a) including a total of
23 different species, seven of which are exotic species. Fish and crayfish scores from river
health monitoring were also included (Storer et al. 2011b).
Macroinvertebrates
The macroinvertebrate species from all 97 sites were assigned low-flow traits modified from
Schafer et al. (2011) and Rolls et al. (2011). Traits were assigned at the family or genus level.
A literature review was conducted and traits were assigned to the endemic species that were
not previously listed. The low-flow traits are shown in Table 2. Analysis was performed on trait
abundances as percentage composition (i.e. for each trait group, the relative abundances of
taxa within each trait characteristic at each site were calculated). Raw abundances were not
directly assessed. Data from the Australian River Assessment System (AusRivAS) analysis
(from previous river health programs) were also included.
Table 2: Macroinvertebrate low-flow trait groups and categories (adapted from Rolls 2011)
Trait group
Grouping characteristic
Salinity tolerance
Low (0-40 ms cm-1), medium-low* (40-80 ms cm-1),
medium (80-120 ms cm-1), high (120-160 ms cm-1)
Voltinism
Semivoltine, univoltine, multivoltine
Minimum time to reproduction
Years (0.2, 0.5, 1-5)
Maximum time to reproduction
Years*
Reproduction type
Aquatic or terrestrial
Drifting (larvae)
Dispersal by drifting* (high or low occurrence in drift
Flying dispersal (adult)
Dispersal by flying (high or low ability)
Food source / trophic group
Predator, herbivore, detritivore, generalist
Respiration
Tegument*, gills, plastron / spiracle
Duration of life stages out of water
Fully aquatic, semi-aquatic, <4 weeks, >4 weeks but < 3
months, edge dwellers
* not used in final analysis due to no data and / or collinearity (see methods)
Water quality
Water quality data were available for 91 of the sites. Data were collected both as in situ
measurements and water grab samples. A list of water quality variables can be seen in
Appendix A. Water quality scores from river health monitoring were also included.
Environmental variables
Environmental variables were measured in the field during sampling events. This included
information regarding about the macroinvertebrate habitat, wetted width, flow rates and water
NATIONAL WATER COMMISSION — Low flows report series
5
level of river, in-stream and riparian vegetation assemblages, and recent rainfall. Additional
information was sourced from spatial datasets including soil type, geological description,
mean annual rainfall, elevation and evapotranspiration.
2.3.2 Hydrological data
Data generation
Fifteen years of daily flow data were available at all 97 sites. Where gauging stations were not
located nearby, data from an ‘indicator gauge‘ was used and the daily flow of the indicator
gauge was scaled by the catchment area of the site. Indicator gauges are recognised
alternatives to use in ungauged catchments. The selection of indicator gauges was based on
the spatial dataset created by the Department of Water and Sinclair Knight Merz (SKM)
during their work on sustainable diversion limits in SWWA (SKM 2007).
Low-flow variables
Numerous low-flow variables were calculated for inclusion in the multivariate analysis. These
are listed in Table 3. All variables were produced from daily flow time series with the
exception of the flow percentiles which were calculated at a monthly time step over a period
of 15 years. Other hydrological variables of interest that were included as factors were
indicator gauge and low-flow classification (Mackay et al. 2012). The low-flow classifications
were assigned to the sampling sites based on the indicator gauge used in the corresponding
hydrological time series. The range of indicator gauges used in the site network for the
Western Australian case study was greater than the range of gauging stations used by
Mackay et al. (2012) to classify the Western Australian streams and thus only 60 of 97 sites
(62 per cent) have been assigned a low-flow classification.
River flow characteristics based on both the Department of Water’s Hydrolinear GIS dataset
and on the data used in the analysis were also included. Indices of hydrological change were
also included – specifically the results of the flow stress ranking – which were calculated as
part of a previous river health program (Storer et al. 2011b).
Table 3: Low-flow variables
preceding 30 days*
Number of zero-flow days
preceding 90 days*
preceding year
preceding three years*
Average per year over three years*
Variation in the number of zero-flow days
Preceding 15 years
Annual minima of the 30-day means
Previous year
Previous two years*
Variation in the annual minima of the 30-day
means
Previous year
Monthly flow percentiles
91.70% (11/12 months)
Previous two years
83.30% (10/12 months)
* not used in final analysis due to zero values and / or collinearity (see Methods)
NATIONAL WATER COMMISSION — Low flows report series
6
3 Methods
A total of 282 variables were identified for inclusion in the multivariate analysis. Following a
validation process, 180 variables were selected and grouped into the following datasets:

fish abundance

fish diversity measures

macroinvetebrate traits

macroinvetebrate habitat

environmental variables

water quality

low-flow variables

FARWH scores.
An additional dataset was collated to provide a list of factors for statistical analysis; aprioridefined environmental drivers that were categorial variables (such as the low-flow class).
The relationship between the fish abundance, fish diversity measures and macroinvertebrate
low-flow traits in response to low-flow variables was examined separately by non-parametric
multivariate analyses performed using the Plymouth Routines in Multivariate Ecological
Research package (PRIMER v6 ) (Clarke & Warwick, 2001).
Before statistical analyses, the distributions of biological and environmental variables were
checked for normality and spread. Data were transformed where required. Macroinvertebrate
low-flow trait data, low-flow variables and environmental data were examined for collinearity
(redundancy). Variables that were found to be collinear (highly correlated with other variables)
were removed from the dataset as their inclusion can have confounding effects (Clarke &
Warwick 2001). Full lists of variables removed and used in analyses can be seen in Appendix
A. In addition, low-flow variables, fish diversity measures and water quality variable datasets
were range standardised before analysis as each dataset contained variables with different
scales and/or units of measurement. Percentage composition of the macroinvertebrate lowflow traits were used hence these data did not require standardisation. The fish abundance
data were log transformed (x+1) before analysis.
Both fish abundance and macroinvertebrate low-flow traits were ordinated by non-metric
Multi-Dimensional Scaling (NMDS). Sites were clustered according to similarities in fish
community assemblage and macroinvertebrate low-flow traits using the Bray-Curtis similarity
matrix.
Low-flow variables and fish diversity measures were also ordinated by NMDS with the
similarity matrix based on Euclidean distance to explore trends. Vectors with significant
correlations (Spearman correlation ≥0.5) for the environmental variables were superimposed
onto the ordination diagrams.
The PRIMER procedure BIOENV was used to determine which of the low-flow variables and
water quality parameters best explained the patterns in the biological datasets (fish
assemblage, fish diversity measures and macroinvertebrate low-flow trait community
pattern).The Spearman’s Rank Correlation was used in this analysis. Results were presented
by rank correlations for single and for combinations of environmental parameters.
Environmental parameters identified by BIOENV as best explaining the community pattern
NATIONAL WATER COMMISSION — Low flows report series
7
were superimposed onto the NMDS ordinations to further explore the relationships between
biotic clusters and environmental parameters.
One-way multivariate analysis of similarity (ANOSIM) was conducted to assess overall
community compositional differences between sites and overall differences between low-flow
class groupings. Statistical significance was set at α = 0.05. A summary of the BIOENV and
ANOSIM analyses performed on the different datasets is displayed in Table 4.
Table 4: BIOENV and ANOSIM analyses
Low-flow
Low-flow
Fish
Fish
variables
class
abundance
diversity
-
ANOSIM
BIOENV
BIOENV
Fish
abundance
ANOSIM
-
MIV traits
ANOSIM
Low-flow
variables
Water
quality
BIOENV
MIV traits
BIOENV
BIOENV
BIOENV
NATIONAL WATER COMMISSION — Low flows report series
8
4 Results
4.1 Low-flow variables
The NMDS of the low-flow variables separated into four main groupings (Figure 2). The
ANOSIM indicated that classes 3 to 5 where highly significantly different (Global R= 0.728,
p=0.0001) with the exception of class 1 (strongly perennial) and 6 (highly ephemeral). No
sites had a class of 2 (weakly perennial).
2D Stress: 0.05
Class
CR-16
CR-15
CR-12
CR-18
HR03015
HR03017
NC-01
FERG-01
GYNU-01
KR
CR-08
EVHAY08
EVHAY14
1
3
4
5
6
EVHAY11
HARV-05
HARV-06
HAY-01
MR-07
CR-09 LUDL-01
ABBA-01
VASS-01
PRES-02
CARB-01
PRES-01
ANNI-01
WILY-01
CR-07
CR-06
CR-05
PR-01
PR-03
EVKAL01
EVKAL03
PR-04
SAM-01
PR-05
PR-06
PR-02
MITC-01
MARG-02
GBC12
EVDEE05
EVDEE02
EVGAR05
EVSHA04
WELD-01
MR-06
MR-05
MR-04
MR-10
MR-16
EVDEN-LG
DENM-03
DENM-01
CLEE-01
HR02010EVGAR02
HR03013
MB-02
MB-01
HR-01
HR-02
HR-03
HR-04
NR-06
NR-04
BOOR-01
HRDSMW
SWN10
JBDG
CR-11
CR-10
CR-17
HR-06
HR-05
SABI-01
MR-12
MR-15
MR-13
MR-17
MRC02
MR-09
MR-18
MRC01
HR01012
MARB-01
WELL-01
BRUN-03
BRUN-06
BRUN-05
PHD1
BRUN-01
AR-01
PHH1
CAPE-01
WR-01
1=strongly perennial, 2=weakly perennial, 3=marginally ephemeral, 4=ephemeral, 5=moderately ephemeral, 6=highly
ephemeral
Figure 2: NMDS based on low-flow variables separated by low-flow classifications
Classes 1 and 6 grouped closely together due to their low variation in one of the low-flow
variables – the annual minima of the 30-day mean (Figure 3) and their high low-flow
percentiles (MonthlyQ83.3 and MonthlyQ91.7). This indicates that although site MARB-01
class 6 (red) site grouped in the bottom left with three class 1 (purple) sites) has been classed
as ephemeral it now has characteristics of a perennial stream (little or no zero-flow days, high
low-flow percentiles) possibly due to large amounts of clearing or increased subsurface
drainage in this area. CAPE-01 should also be closer to these data points, however the best
indicator gauge for this site did not have sufficient data and hence the low-flow variables at
this site are not as accurate. It is located downstream of dam release and its flow regime is
characteristically more perennial.
The class 3 (marginally ephemeral) and 4 (ephemeral) sites are grouped closely together
dominated by the high number of zero-flow days in the previous year (zeroflowprevy). The
class 5 (moderately ephemeral) sites group together and appear to be influenced by the
variation in the minimum monthly flows in the previous year (CV_Ann_min30dayprev_y).
NATIONAL WATER COMMISSION — Low flows report series
9
2D Stress: 0.05
Class
1
3
4
5
6
zeroflowprev15ycv
CV_Ann_min30dayprev_y
MonthlyQ83.3
MonthlyQ91.7
Ann_min30day_prevy
zeroflowprevy
1=strongly perennial, 2=weakly perennial, 3=marginally ephemeral, 4=ephemeral, 5=moderately ephemeral, 6=highly
ephemeral
Figure 3: NMDS based on low-flow variables separated by low-flow classifications overlain
with low-flow variables as vectors (correlation >0.5)
The NMDS for the low-flow variables was also separated using the EPdata factor which
distinguishes between ephemeral (e) and perennial (p) sites, based on the daily time series
over the last 15 years (Figure 4). There are some changes in comparison to the NMDS using
the low-flow classifications. Some of the class 5 (moderately ephemeral) and class 6 (highly
ephemeral) sites are now characteristically more perennial. Some of these sites are located in
the Collie catchment, downstream of dam releases. Most of the class 3 and class 4 sites have
remained in the ephemeral category. The ephemeral (e) sites have grouped closely, however
the perennial (p) sites are more scattered, which indicates that their low-flow characteristics
are more variable, perhaps due to changes in the natural flow regime.
NATIONAL WATER COMMISSION — Low flows report series
10
2D Stress: 0.05
CR-08
EPdata
e
p
CR-18
CR-16
CR-15
CR-12
GYNU-01
NC-01
FERG-01
KR
HR03015
HR03017
HARV-05
HARV-06
EVHAY11
MR-07
MR-12
MR-09
MR-18
MRC02
MRC01
MR-15
MR-13
MR-17
WELL-01
BRUN-06
BRUN-05
BRUN-03
HR01012
MARB-01
BRUN-01
PHD1
EVHAY08
EVHAY14
HAY-01
VASS-01
ABBA-01
LUDL-01
CR-09
PRES-02
CARB-01
CR-07
CR-06
CR-05
ANNI-01
WILY-01
PR-03PRES-01
PR-01
PR-04
EVKAL01
EVKAL03
PR-02
PR-05
PR-06
SAM-01
GBC12
MARG-02
MITC-01
HR02010
HR03013
EVDEE02
EVSHA04
WELD-01
EVDEE05
EVGAR05
MR-06
MR-05
MR-04
MR-10
MR-16
DENM-03
EVDEN-LG
CLEE-01
DENM-01
JBDG
SWN10
HRDSMW
BOOR-01
EVGAR02
HR-01
HR-02
HR-03
HR-06
HR-05
HR-04
MB-02
MB-01
NR-06
NR-04
SABI-01
CR-11
CR-10
CR-17
AR-01
PHH1
WR-01
CAPE-01
e=ephemeral, p=perennial (i.e. no zero-flow days)
Figure 4: NMDS based on low-flow variables separated by EPdata factor
4.2 Fish abundance
Initial ordination of the fish abundance dataset revealed no distinct cluster groups, although
there was a clear divide between the majority of sites and three sites with secondary
salinisation. These three sites were removed from the database. Subsequent ordination of the
fish abundance dataset generated no distinct cluster groups except the Palinup River sites
which group together (Figure 5).
The overlay of vectors did not indicate any distinguishing patterns in the data cloud with lowflow variables (very low correlations), fish species, water quality or FARWH scores. An
ANOSIM was done to test research question 3 (Is there a statistically significant difference in
fish composition based on low-flow variables?), with the result being no significant difference.
The fish abundance NMDS was overlain with the fish species as vectors (Figure 6). The class
3 sites appear to be dominated by the Swan River goby (SRG) and gambusia (GAM), while
the class 4 sites appear to be dominated by freshwater cobbler (FCOB) and marron (MARR).
Both the freshwater cobbler and marron depend on permanent water being present either as
flowing water or as pools.
NATIONAL WATER COMMISSION — Low flows report series
11
2D Stress: 0.19
AR-01
EVHAY14
Class
1
3
4
5
6
HARV-06
HAY-01
EVDEE02
CLEE-01
NR-06
ANNI-01
DENM-01
MITC-01
EVHAY11
MR-10
WR-01
PHH1
MB-02
KR DENM-03
MARB-01
BOOR-01
HR01012
WELD-01
NC-01
EVGAR02
EVDEN-LG
HR03015
HR03013
EVSHA04
EVKAL01
WILY-01HR03017
PHD1
EVGAR05 EVHAY08
HR02010
CR-17EVKAL03
EVDEE05
MR-06
MR-17
CARB-01
VASS-01
GBC12
HR-03MR-16
FERG-01MR-04
MR-13
ABBA-01
LUDL-01
MR-12
MARG-02
CR-11 MR-05HR-02
CR-08
BRUN-03
CR-16
BRUN-05
HR-04
HR-01
MR-07
CR-15 GYNU-01 MR-09
CR-06 CR-07
SABI-01
PRES-01
CR-10
HARV-05
CR-09
NR-04
MRC02
MR-18
BRUN-01
BRUN-06
WELL-01
PRES-02 MRC01
CR-12
PR-04
PR-06
PR-05
PR-01
PR-03
PR-02
CAPE-01
CR-05
MB-01
SAM-01
1=strongly perennial, 2=weakly perennial, 3=marginally ephemeral, 4=ephemeral, 5=moderately ephemeral, 6=highly
ephemeral
Figure 5: NMDS based on fish abundance
2D Stress: 0.19
KOO
Class
1
3
4
5
6
WM
RGIL
WPP
NF
JT
GAMB
SRG
MARR
GIL
FCOB
1=strongly perennial, 2=weakly perennial, 3=marginally ephemeral, 4=ephemeral, 5=moderately ephemeral, 6=highly
ephemeral
Figure 6: NMDS based on fish abundance with species as vectors (correlation >0.4)
The NMDS was also overlain with water quality vectors to help explain the data cloud (Figure
7). No strong patterns were observed, however the class 4 sites appear to be separated by
temperature, and the class 3 sites loosely separated by total nitrogen concentrations and
electrical conductivity.
NATIONAL WATER COMMISSION — Low flows report series
12
2D Stress: 0.19
Class
1
3
4
5
6
N (tot) {TN, pTN} (mg/L)
pH
Cond
comp
25(CaCO3)
deg C (in (mg/L)
situ) (µS/cm)
Alkalinity
(tot)
Temperature (in situ) (deg C)
1=strongly perennial, 2=weakly perennial, 3=marginally ephemeral, 4=ephemeral, 5=moderately ephemeral, 6=highly
ephemeral
Figure 7: NMDS based on fish abundance with water quality as vectors (correlation >0.4)
4.3 Fish diversity
Ordination of the fish diversity measures dataset revealed no distinct cluster groups (Figure
8). Overlaying the water quality and low-flow variables as vectors resulted in very poor
correlations. An ANOSIM was performed to test research question 3 (Is there a statistically
significant difference in fish diversity based on low-flow variables?), with the result being no
significant difference.
2D Stress: 0.12
CR-16
WELL-01
PHD1
BRUN-05
MR-06
EVSHA04
CAPE-01
CR-09 EVDEE02
ANNI-01 HR01012
CR-05
MR-18
SAM-01
HR02010
HR03013
MARG-02
EVHAY14
MR-05
EVGAR02
DENM-03
CR-10
NR-06 PRES-02PR-02AR-01
CR-15
BRUN-06 EVDEN-LG
EVKAL03 BOOR-01
NC-01
MR-07
CR-08CR-11
HR03017
VASS-01
GBC12
MARB-01
HR03015 ABBA-01
KR
PRES-01
MRC01
MITC-01EVDEE05
EVHAY08
CR-06
MR-04
MRC02
CARB-01
HAY-01
PR-06
MR-13
NR-04
HR-01
CR-17
CR-12 EVHAY11
GYNU-01
PHH1
EVGAR05
EVKAL01
PR-03
LUDL-01
DENM-01
BRUN-01
WR-01 MR-16
CLEE-01
SABI-01
CR-07
HR-03HARV-05
MR-10
PR-05
BRUN-03
HR-02 MR-09
MB-02
WILY-01 FERG-01
HR-04
Class
1
3
4
5
6
MR-17
MR-12
HARV-06
WELD-01
PR-04
MB-01
PR-01
1=strongly perennial, 2=weakly perennial, 3=marginally ephemeral, 4=ephemeral, 5=moderately ephemeral, 6=highly
ephemeral
Figure 8: NMDS based on fish diversity
NATIONAL WATER COMMISSION — Low flows report series
13
4.4 Macroinvertebrate low-flow traits
Ordination of the macroinvertebrate low-flow trait dataset revealed no distinct cluster groups
(Figure 9). Overlaying a variety of low-flow factors as vectors revealed no trends. An ANOSIM
was performed to test research question 3 (Is there a statistically significant difference in
macroinvertebrate low-flow traits based on low-flow variables?), the result being no
significant difference.
2D Stress: 0.14
DENM-01
CR-15
CR-16
HAY-01
PR-05
CARB-01
EVKAL01
CR-18
EVHAY08
PHD1
EVKAL03
HR01012
PR-02
BRUN-01
CR-05
HR03015
CAPE-01
SWN10MB-02
NR-04
MR-07
HR03013
PR-06
ABBA-01
PHH1 MB-01
SABI-01
FERG-01
NR-06
GBC12
HR-04
MR-06
ANNI-01
HR02010
PRES-01
VASS-01
JBDG
WELL-01LUDL-01
CLEE-01
SAM-01
MRC02HR-06
MARG-02
MR-09 PR-03
PR-04
MR-12
CR-10
HR-02
CR-11
MR-15
MR-16
GYNU-01
CR-06
EVDEN-LG
HR-01
EVHAY11
WR-01
MR-13
MR-18
MR-05
WELD-01
PRES-02
BOOR-01
MRC01 KR
WILY-01
EVGAR05 HARV-05
CR-08 HR-05
HR-03
AR-01
NC-01
EVDEE02 MITC-01
HR03017
HRDSMW
MR-10
MR-04
MR-17
BRUN-03
EVGAR02
CR-09
BRUN-05
HARV-06
MARB-01
CR-07
DENM-03
EVSHA04
EVDEE05
Class
1
3
4
5
6
BRUN-06
PR-01
CR-17
CR-12
EVHAY14
1=strongly perennial, 2=weakly perennial, 3=marginally ephemeral, 4=ephemeral, 5=moderately ephemeral, 6=highly
ephemeral
Figure 9: NMDS based macroinvertebrate low-flow traits
Overlaying the macroinvertebrate traits as vectors revealed strong trends with many variables
with correlations greater than 0.5. Those greater than 0.8 have been plotted on the NMDS
(Figure 10).
It was predicted in Table 1 that various macroinvertebrate low-flow traits would follow a
gradient of change with the low-flow classifications. As predicted, the assemblages of the
ephemeral sites (classes 3 and 4) are driven by animals that can tolerate higher salinities
(Medium salinity%), have air breathing characteristics (PlastronSpiracleResp%) and use flight
as a mechanism for dispersal (AdultDispersalFly%). These sites also have a short minimum
time to reproduction (0.2 years).
In terms of food source, it was predicted there would be greater variability in the class 1 sites.
However, these sites were dominated by the detritivores. The class 1 sites are also degraded
sites and thus the dominance of the detritivores can be partly attributed to the poor condition
of the sites.
NATIONAL WATER COMMISSION — Low flows report series
14
2D Stress: 0.14
Class
1
3
4
5
6
Detritivore%
MinTR0.2%
MediumSalinity%
GillsResp%
AdultDispersalFly%
PlastronSpiracleResp%
1=strongly perennial, 2=weakly perennial, 3=marginally ephemeral, 4=ephemeral, 5=moderately ephemeral, 6=highly
ephemeral
Figure 10: NMDS based on macroinvertebrate low-flow traits showing correlations > 0.8.
4.5 BIOENV analyses
Ranked correlations between each of the ecological similarity matrices (fish abundance, fish
diversity and macroinvertebrate low-flow traits) and the low-flow variable dataset using the
BIOENV procedure (Clarke & Warwick 2001) revealed that no low-flow variable (or
combination thereof) strongly influenced the groupings of the sites based on the biological
variables alone, thus disproving research question 1.
It was then decided to repeat the BIOENV analyses using the water quality dataset to see if
this could explain any of the patterns in biotic assemblages and address research question 2
(Can these ecological patterns be explained by other environmental factors?). Patterns in fish
abundance had the strongest correlations with water quality, while the correlations for fish
diversity and the macroinvertebrate low-flow traits were not as strong.
Patterns observed in the fish abundance dataset were best explained by the combination of
electrical conductivity, temperature, total nitrogen, nitrate/nitrite as nitrogen and turbidity (ρw =
0.426) (Table 5). Similarly, the patterns observed for fish diversity were best explained by the
same variables as for fish abundance, with the addition of dissolved oxygen and true colour
(ρw = 0.237) (Table 6). The variation in the macroinvertebrate low-flow traits dataset were
best explained by the combination of electrical conductivity, pH, temperature and nitrate/nitrite
as nitrogen (ρw = 0.201) (Table 7).
NATIONAL WATER COMMISSION — Low flows report series
15
Table 5: Results of the BIOENV correlation analysis (Spearman ranked correlation of fish
abundance similarity matrix with the water quality dataset)
Selections
Correlations ρw
electrical conductivity, temperature, total nitrogen,
nitrate/nitrite as nitrogen
0.426
electrical conductivity, temperature, total nitrogen,
nitrate/nitrite as nitrogen, turbidity
0.426
electrical conductivity, temperature, alkalinity, total
nitrogen, nitrate/nitrite as nitrogen
0.420
electrical conductivity, temperature, pH, total
nitrogen, nitrate/nitrite as nitrogen
0.419
electrical conductivity, temperature, dissolved
oxygen, total nitrogen, nitrate/nitrite as nitrogen
0.417
electrical conductivity, temperature, nitrate/nitrite as
nitrogen, turbidity
0.413
electrical conductivity, temperature, true colour, total
nitrogen, nitrate/nitrite as nitrogen
0.412
Table 6: Results of the BIOENV correlation analysis (Spearman ranked correlation of fish
diversity measures similarity matrix with the water quality dataset)
Selections
Correlations ρw
electrical conductivity, temperature, dissolved
oxygen, true colour, nitrate/nitrite as nitrogen,
turbidity
0.237
electrical conductivity, temperature, dissolved
oxygen, true colour, total nitrogen, nitrate/nitrite as
nitrogen
0.235
Table 7: Results of the BIOENV correlation analysis (Spearman ranked correlation of
macroinvertebrate low-flow traits similarity matrix with the water quality dataset)
Selections
Correlations ρw
Electrical conductivity, pH, temperature, nitrate/nitrite
as nitrogen
0.201
Electrical conductivity, pH, temperature, true colour,
nitrate/nitrite as nitrogen
0.197
NATIONAL WATER COMMISSION — Low flows report series
16
5 Discussion
5.1 Low-flow classifications
Due to recent changes in climate and land use, the low-flow classifications for SWWA rivers
and streams are not as relevant under the current flow regime used in the analysis for this
report (1992–2008). Class 1 sites have remained strongly perennial, however all other sites
have shifted in some way. The class 3 (marginally ephemeral) sites would now be considered
moderately or highly ephemeral with approximately 50 per cent of these sites experiencing
more than 150 days of zero flow in the year before sampling. The class 4 (ephemeral
streams) have remained ephemeral, or shifted to moderately ephemeral, with the exception of
one site which would now be classified as strongly perennial, possibly due to dam release
upstream. Approximately 50 per cent of the class 5 (moderately ephemeral) sites would now
be classified as more perennial (possibly class 2, weakly perennial) due to their low number
of zero-flow days in the year before sampling (4 or less) and non-zero low-flow percentiles
(approximately 70 per cent of sites have a 0 ML 91.7 percentile flow). If low-flow
classifications are not correctly assigned then any low-flow-ecology relationships have the
possibility of being false.
This shift to increasing ephemeral characteristics may indicate these sites have reached an
altered stable state. They are functioning differently to the natural regime but are not
necessarily in a stressed state.
5.2 Ecological relationships
Although the BIOENV analysis revealed no combination of low-flow variables significantly
influenced the data cloud of the sites based on their macroinvertebrate traits, there were
numerous observations that were in support of research question 1. The sites classified as
ephemeral or moderately ephemeral (classes 3 and 4) supported animals with traits suited to
conditions of low flow; tolerance of higher levels of salinity, short reproduction times, air
breathing and dispersal by flight (Figure 10). The moderately and highly ephemeral sites
(classes 5 and 6) did not share these characteristics. This could be due to a variety of
reasons including the point made in section 5.1, that under the current regime, many of the
class 5 streams have low-flow characteristics which are more perennial or that factors other
than the low-flow classifications are affecting the ecology at these sites.
A high proportion of detritivores were present in the class 1 sites, which was an unexpected
result. On closer review these sites are degraded sites and other degraded sites also grouped
in this area, indicating the condition of the site is having a greater impact in the pattern of
macroinvertebrate assemblages.
The analyses highlighted the fact that the ecology of SWWA is also influenced by factors
other than hydrology, including water quality, geography, general condition and land use
changes. Water quality was a significant influence which separated the secondary salinised
sites (which were not included in the final analysis). Measurements of conductivity, total
nitrogen concentrations and temperature showed a strong correlation with fish abundance.
Interestingly, all the Palinup River (PR) sites grouped together, indicating that certain
characteristics of this river system are affecting the fish abundance. Presence of permanent
water also explained some of the groupings. Despite having different low-flow classifications,
many sites grouped together due to the influence of particular fish species (freshwater cobbler
and marron) which favour permanent waters. Some of these sites have refuge pools, while
others are located downstream of dam releases. The presence or absence of pools may be
NATIONAL WATER COMMISSION — Low flows report series
17
clouding the analysis and should be further investigated to aid interpretation of biotic
assemblages (see Section 5.3).
5.3 Low flow and pools
The low-flow variables considered in this analysis have not included any information about the
presence and health of river pools. Pools provide a refuge for biota during low-flow conditions,
thus their presence is important in understanding relationships between low-flow conditions
and biotic assemblages. Two rivers may have similar low-flow conditions, however one may
have a refuge pool and the other may not – in which case we would expect to see different
biota. However, with the current analysis such sites have no such variable to distinguish them
from each other.
The drying or connecting of pools within SWWA therefore needs further investigation as this
may be more important in determining ecological responses than the duration or magnitude of
low-flow conditions. An index representing the presence or absence of pools is required for
any future work of this scale.
5.4 Sampling regime
Ecological data was collected during spring and summer of 2008–09 and spring of 2009. All
sites experienced flow events in the 90 days before the sampling event. Therefore the effect
and recovery of biota after recent dry conditions could not be assessed. Future work in the
area of low-flow stress and ecology should incorporate seasonal sampling events so that
comparisons can be made with specific characteristics of the hydrograph.
NATIONAL WATER COMMISSION — Low flows report series
18
6 Conclusion
There was no simple and obvious relationship between ecology and hydrology based on the
tests completed herein.
This can be attributed to many factors, including:

dataset limitations

Western Australian streams have adapted to low-flow stress

the extreme conditions of recent years have filtered out sensitive taxa

ecology is driven by factors other than hydrology.
Data from snapshot sampling regimes are limited in their temporal variability. Only regimescale hydrological characteristics could be assessed with this data.
Most sites in this study are classified as moderately ephemeral or ephemeral. Therefore
comparisons in biota based on the different low-flow classifications were limited. This also
indicates the majority of sites may already have adapted to low-flow conditions and their
assemblages are more influenced by other factors including water quality, fish barriers,
presence of refuge pools, geography and land use change.
Future work requires increased sensitivity in site selection and sampling regime. Isolating
different subregions of SWWA would reduce the scatter in the data cloud. Sampling events
should be repeated at specified times so as to increase the chance of capturing changes in
ecology as a result of different low-flow conditions.
Classifying streams based on low-flow characteristics of the current flow regime should be
considered. Recent changes in land use, climate and water use was helpful in explaining
many of the patterns in biotic assemblages.
Additional hydrological information is required for further research into relationships between
low flow and ecology, particularly the presence of pools and the extent of flowing waters.
There is a large dependence on data from gauging stations for use in hydrological analyses.
As the distribution of gauging stations in SWWA is sparse and the characteristics of rivers
change within short distances, other methods of describing hydrological variables need to be
identified.
NATIONAL WATER COMMISSION — Low flows report series
19
Appendix A
List of variables kept () and removed () for analysis
Water quality
Cond comp 25 deg C (in situ) (µS/cm)

pH

Temperature (in situ) (deg C)

O - DO (in situ) (mg/L)

Alkalinity (tot) (CaCO3) (mg/L)

Colour (TCU) (TCU)

N (sum sol ox) {NOx-N, TON} (mg/L)

N (tot) {TN, pTN} (mg/L)

NH3-N/NH4-N (sol) (mg/L)

P (tot) {TP, pTP} (mg/L)

Turbidity (NTU)

O - DO % (%)1

N (sum sol org) {DON} (mg/L)2

PO4-P (sol react) {SRP, FRP} (mg/L)3

[1. removed due to collinearity with O – DO (mg/L)]
[2. removed due to collinearity with TN]
[3: removed due to collinearity with TP]
Low-flow variables
zeroflowprevy

zeroflowprev15ycv

Ann_min30days_prevyear

CV_Ann_min30daysprev_year

MonthlyQ91.7

MonthlyQ83.3

zeroflowprev3y1

zeroflowprev30d1

zeroflowprev90d1

zeroflowprev3yave1

Ann_min30days_prev2years2

CV_Ann_min30dayspreviousyear2years3

[1. removed due to high proportion of zero values]
[2. removed due to collinearity with Ann_min30days_prevyear]
[3. removed due to collinearity with CV_Ann_min30daysprev_year]
NATIONAL WATER COMMISSION — Low flows report series
20
MIV habitat
Channel

macrophytes

Riffle

Pool rocks

Avwetwidth

Bedrock

Boulders

Cobble

Pebble

Gravel

Sand

Silt

Detritus

trailingveg

woody debris

site_mac

Emergemac1

Submergemac1

Floating macrophyte1

Mineral2

AlgalCover2

Minflowday3

Maxflowday3

Loggerflowday3

[1. variables summed and replaced with site_mac]
[2. removed due to low variation of data]
[3. removed due to missing data]
Environmental variables
Maximum daily temp

Elevation

Mean annual rainfall (1975-2003)

Evapo-transpiration1

[1. removed due to colinearity with Mean annual rainfall (1975-2003)]
Fish diversity measures
fishabundance

fishrichness

natdomfexotic

fishdominance

NATIONAL WATER COMMISSION — Low flows report series
21
Factors
flowonday

rainweek

rainday

flowlevel

Class

StreamName

ReachID

Sampledate

year2

EPdata

EPGIS

indicatorgauge

ClassQ91.7

classCV_Ann_min30dayspreviousyear

classCV_Ann_min30daysprevious2years

classAnn_min30daysprevious2years

classzerodayspreviousyear

class#0MLdaysprevious3years

classCV#0MLdaysprevious15years

lowflowclass

MI_Habitat

LONGITUDE

LATITUDE

DISCHARGE CATEGORY

IBRA sub-region

NVIS major vegetation sub-group (number)

Soil type

Geological unit code

Geological description

SWMA1

Salinity1

Walowflowclass1

WAlowflow4class1

1. [new factors added during analysis]
.
NATIONAL WATER COMMISSION — Low flows report series
22
FARWH scores
CDI_score
Infrastructure

NATIVE ABUNDANCE



NATIVE SPECIES
LAND USE

NATIVENESS

LAND COVER CHANGE

OBSERVED/PREDICTED RATIO

HCI_SCORE

OBSERVED/EXPECTED RATIO

LOW FLOW

EXPECTIVENESS




AUSRIVAS
ARTIFICIAL CHANNEL INDEX
SCORE
LONGITUDINAL CONNECTIVITY
INDEX SCORE
MAJOR DAM SUB-INDEX
SCORE
MINOR DAM SUB-INDEX
SCORE
GAUGING STATION SUB-INDEX
SCORE
Road / rail crossings sub-index
score
EROSION INDEX SCORE
EROSION EXTENT SUB-INDEX
SCORE
BANK STABILISATION SUBINDEX SCORE
VEGETATION EXTENT1

NATVINESS1


AQUATIC BIOTA INDEX SCORE2


FISH_CRAY2


HIGH FLOW
PROPORTION OF ZERO FLOW
MONTH VARIATION

SEASONAL PERIOD

WQI_SCORE

TOTAL NITROGEN

TOTAL PHOSPHOROUS
TURBIDITY


TEMPERATURE

MEAN OF NON CRITICALS (TN, TP, Turb
and Temp)
SALINITY
DIEL DISSOLVED OXYGEN
FRINGING ZONE INDEX _SCORE
VEGETATION LENGTH
VEGETATION WIDTH



[1. removed due to collinearity with other fringing zone scores]
[2. removed due to collinearity with other aquatic biota scores]











NATIONAL WATER COMMISSION — Low flows report series
23
Fish abundance
Code
Common name
Species name
TM
Trout minnow
Galaxias truttaceus

WM
Western minnow
Galaxias occidentalis

JT
Common jollytail
Galaxias maculatus

MM
Mud minnow

WPP
Western pygmy perch
Galaxiella munda
Nannoperca vittata
(formerly Edelia vittata)
BPP
Balstons pygmy perch
Nannatherina balstoni

SRG
Swan River goby
Pseudogobius olorum

SWG
South-western goby
Afurcagobius suppositus

NF
Nightfish
Bostockia porosa

FCOB
Freshwater cobbler
Tandanus bostocki

PL
Pouched lamprey
Geotria australis

GOLD1
Goldfish
Carassius auratus

1SPOT1
One-spot live bearer
Phalloceros caudimaculatus

GAMB1
Gambusia
Gambusia holbrooki

RP1
Redfin perch
Perca fluviatilis

RT1
Rainbow trout
Oncorhynchus mykiss

BT1
Brown trout
Salmo trutta

YAB1
Yabby
Cherax spp.

MARR
Marron
Cherax cainii

HMARR
Hairy marron
Cherax teminuimanus

GIL
Gilgie
Cherax quinquecarinatus

KOO
Koonac
Cherax preissi

RGIL
Restricted gilgie
Cherax crassimanus


1. [exotic species]
NATIONAL WATER COMMISSION — Low flows report series
24
MIV traits database
Univoltine%

PneumostomeResp%2

TerrestrialRepro%

PlastronGillsResp%2

SurfaceDwellerDOW%

Over9monthsDOW%2

Semivoltine%

Over3monthsDOW%2

SemiaquaticDOW%

EdgeDOW%2

Predator%

PupationAdultOnLandDOW%2

PlastronSpiracleResp%

OccurInDrift%2

PlantEater%

Navoltinism%3

Multivoltine%

LowMedSalinity%2

More4wkLess3mthDOW%

Nasalinity%3

MinTR0.5%

NAoccurDrift%3

MinTR0.2%

lowOccurDrift%2

MediumSalinity%

CarrionEater%2

LowSalinity%

NAadultDispersalFly%3

lowAdultDispersalFly%

MaxTR0.2%2

Less4wkDOW%

MaxTR0.25%2

GillsResp%

MaxTR0.3%2

Generalist%

MaxTR0.4%2

FullyAquaticDOW%

MaxTR0.5%2

Detritivore%

MaxTR0.75%2

AquaticRepro%

MaxTR1%2

AdultDispersalFly%

MaxTR1to5%2

AbundantSalinity%

MaxTR2%2

MinTR1_5%

MaxTR3%2

MinTR1%1

MaxTR3.5%2

MinTR1.5%1

MaxTR4%2

MinTR1to5%1

MaxTRless0.1%2

MinTR2%1

MaxTRna%3

MinTR3.5%1

MIVRichness2

MinTR0.25%1

MIVAbundance2

MinTR0.3%1

MinTR0.33%1

MinTR0.4%1

MinTR0.75%1

MinTRless0.1%1

MinTRna%1

MIV_cells
picked2

[1. removed due to lack of variation]
[2. removed because information not specific to study questions]
[3. removed due to lack of relevant information]
NATIONAL WATER COMMISSION — Low flows report series
25
Shortened forms
ANOSIM
One-way multivariate analysis of similarity
AusRivAS
Australian River Assessment System
BIOENV
A procedure of the Plymouth Routines in Multivariate Ecological
Research (PRIMER)
DOW
Department of Water
FARWH
Framework for the Assessment of River and Wetland Health
FCOB
Freshwater cobbler
GAM
Gambusia
MIV
Macroinvertebrate
MARR
Marron
NMDS
Non-metric Multi-Dimensional Scaling
PR
Palinup River
PRIMER
Plymouth Routines in Multivariate Ecological Research
RHAS
River Health Assessment Scheme
SKM
Sinclair Knight Merz
SRG
Swan River goby
SWWA
South-west Western Australia
NATIONAL WATER COMMISSION — Low flows report series
26
References
Barron O, Donn MJ & Pollock D 2010, Determining the effectiveness of best management
practices to reduce nutrient flows in urban drains managed by the Water Corporation,
part 1 – main report, CSIRO: Water for a Healthy Country National Research Flagship
Clarke KR & Warwick RM 2001, Change in marine communities: an approach to statistical
analysis and interpretation, 2nd edition, PRIMER-E: Plymouth.
Conservation International 2007, Biodiversity hotspots [online] available at
http://www.biodiversityhotspots.org/Pages/default.aspx accessed 26 October 2011.
Department of Water 2011, Environmental flow regime for the lower Collie River, Shentons
Elbow reach, Environmental water report series, report no. 21, Department of Water,
Western Australia.
Mackay S, Marsh N, Sheldon F, Kennard M 2011, Low flow hydrological classification of
Australia, technical report, National Water Commission, Canberra
Marsh N, Sheldon F & Rolls R 2012, Synthesis of case studies quantifying ecological
responses to low flows, National Water Commission, Canberra.
Rolls R 2011, unpublished low-flow traits database.
Schafer B, Kefford B, Metzeling L, Liess M, Burgert S, Marchant R, Pettigrove V, Goonan P &
Nugegoda D 2011 ‘A trait database of stream invertebrates for the ecological risk
assessment of single and combined effects of salinity and pesticides in South-East
Australia’, Science of the Total Environment 409: 2055-2063.
Sinclair Knight Merz 2007, Recommendations for sustainable diversion limits over winter-fill
periods in unregulated south-west Western Australia catchments, report prepared for
the Department of Water, Perth, Sinclair Knight Merz, Armadale, Victoria.
Storer T, White G, Galvin L, O’Neil K, van Looij E & Kitsios A 2011a, The Framework for the
Assessment of River and Wetland Health (FARWH) for flowing rivers of south-west
Western Australia: method development, Final report, Water Science Technical Series,
report no. 40, Department of Water, Western Australia
— 2011b, The Framework for the Assessment of River and Wetland Health (FARWH) for
flowing rivers of south-west Western Australia: project summary and results, Final
report, Water Science Technical Series, report no. 39, Department of Water, Western
Australia.
Reports in the low flows 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.
NATIONAL WATER COMMISSION — Low flows report series
27
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.
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
28