Investigating Ecological Indicators of Stress
from Water Scarcity
A discussion paper prepared for the
National Water Commission
WAYNE ROBINSON
numbersman.com.au
MARCH 2010
i
National Water Commission Cover Note
This report is one of several reports prepared for the ‘Assessing Water Stress in
Australian Catchments and Aquifers’ project (formerly titled the National Inventory of
Water Stressed Catchments and Aquifers) which provides an assessment of the
extent to which surface and groundwater systems have been hydrologically altered
because of water extraction, regulation or flow alteration.
Overarching report
NWC, 2012, Assessing water stress in Australian catchments and aquifers, National
Water Commission, Canberra.
Supporting reports
Marsh, N 2010, Hydrological indicators of water stress, report prepared for the
Bureau of Meteorology for the National Water Commission.
O’Keefe, V and Hamstead, M 2010, Understanding jurisdictional and Murray Darling
Basin Authority approaches to identifying water stress, report prepared for the
National Water Commission.
Robinson, W 2010, Investigating ecological indicators of stress from water scarcity,
discussion paper prepared for the National Water Commission.
Sinclair Knight Merz, 2012, Assessing water stress in Australian catchments and
aquifers, technical report prepared for the National Water Commission.
Note - supporting reports do not necessarily reflect the views or opinions of the
Commission.
ii
Executive summary
The National Inventory of Water Stressed Catchments and Aquifers project
proposes to develop an Australia-wide picture of water stress using a
systematic and transparent approach that distinguishes where possible
different causes of water stress, and is informed as much as possible by
existing processes and indicators. This discussion paper forms part of that
project and investigates the use of ecological indicators of water stress.
Specifically, this paper investigates whether and how ecological indicators
derived from existing data collections can be used to indicate the extent to
which water systems across Australia have been impacted by surface and
groundwater scarcity.
The paper looks at in-stream biota (macroinvertebrates, fish, plants, algae,
plankton and miscellaneous taxa), in-stream biological processes, riparian
and floodplain vegetation and water birds as potential indicator groups. An
extensive literature review of the relationships of these groups to water and
flow regimes revealed many responses and tens of potential ecological
indicators.
The paper concludes that there are no ecological indicators that specifically
respond to water-scarcity related stress. In other words, because of the
complex nature of ecosystems and their response to stressors, none of the
indicators trialled can report better on water scarcity than direct measurement
itself.
There are very few existing programs collecting ecological data in an
unbiased manner that could be used to inform the national inventory. The
candidate indicator with the most potential is Normalised Differential
Vegetation Index (NDVI), generated from remote sensed reflectance values
from riparian and flood plain vegetation.
iii
Table of Contents
Executive summary................................................................................................ iii
Table of Contents ................................................................................................... iv
1
Background ..................................................................................................... 1
1.1
1.2
1.3
1.4
Approach ................................................................................................... 2
End Uses ................................................................................................... 2
Definition and Scope .................................................................................. 3
Ecological Indicators Discussion Paper...................................................... 3
2
Introduction to Ecological Monitoring ........................................................... 4
3
Ecological Indicators....................................................................................... 5
3.1
What is an Ecological Indicator? ................................................................ 5
3.2
Indicator Development ............................................................................... 5
3.3
Indicator Variability..................................................................................... 6
3.4
Indicator Demonstration ............................................................................. 7
3.5
How could ecological indicators be used to indicate water stress in
catchments and aquifers across Australia? ........................................................... 7
3.6
Standardising Indicators ............................................................................ 9
3.7
Indicator Responsiveness ........................................................................ 10
3.8
Which Indicators? .................................................................................... 11
3.9
Regional indicators .................................................................................. 11
3.10 It’s all a matter of scale ............................................................................ 11
3.11 Indicators Summary ................................................................................. 12
4
Identifying Potential Ecological Indicators of Water Scarcity for the
Australian Environment. ....................................................................................... 13
4.1
4.2
4.3
4.4
4.5
Literature demonstrating the use of ecological indicators of water scarcity
13
In-stream biota ......................................................................................... 13
Waterbirds ............................................................................................... 20
Vegetation ............................................................................................... 23
Biological Processes ................................................................................ 26
5
Potential suitable indicators for ecological indicators of water scarcity
from responses cited in the literature.................................................................. 29
5.1
5.2
5.3
5.4
5.5
5.6
5.7
6
Macroinvertebrates .................................................................................. 29
Fish .......................................................................................................... 30
Algae/Plankton......................................................................................... 31
Miscellaneous biota ................................................................................. 31
Waterbirds ............................................................................................... 32
Vegetation ............................................................................................... 33
Biological processes ................................................................................ 34
Current Status of Ecological Indicators ....................................................... 34
6.1
6.2
6.3
6.4
In-stream biota ......................................................................................... 34
Waterbirds ............................................................................................... 37
Vegetation ............................................................................................... 39
Biological Processes ................................................................................ 41
iv
7
Identification of indicators feasible to use, based on criteria including
whether adequate data exist to populate the indicator. ..................................... 41
7.1
7.2
7.3
7.4
7.5
8
Introduction .............................................................................................. 41
In-stream Biota ........................................................................................ 41
Waterbirds ............................................................................................... 42
Vegetation ............................................................................................... 43
Biological Processes ................................................................................ 43
Options and recommendations for the way forward................................... 44
8.1
Introduction .............................................................................................. 44
8.2
In-stream Biota ........................................................................................ 44
8.3
Waterbirds ............................................................................................... 48
8.4
Vegetation ............................................................................................... 48
8.5
The way forward using NDVI ................................................................... 49
Before using NDVI ............................................................................................... 53
9
Alternative view ............................................................................................. 54
10
Conclusion ..................................................................................................... 55
Appendix 1 Water birds literature review ............................................................ 56
A1.1 Literature Review of Waterbird Ecology relevant to water use and water
scarcity ................................................................................................................ 56
A1.2 There’s lots we need to consider before using waterbirds as indicators ... 63
A1.3 Literature Review of Waterbirds as indicators .......................................... 66
Appendix 2 Literature Review of Vegetation Ecology relevant to water scarcity
................................................................................................................................ 77
Appendix 2.1 README FILE FOR MODIS-DERIVED Land Products (Paget and
King 2008) ........................................................................................................... 92
Appendix 3
Summary of literature review of in-stream biota ecology
relevant to water scarcity ..................................................................................... 98
Acknowledgements............................................................................................. 106
References ........................................................................................................... 107
v
1
Background
One of the key aims of improved water planning and management under the
National Water Initiative (NWI) is to avoid over-allocation and overuse of
surface and groundwater systems, and to return already over-allocated and/or
overused systems to sustainable levels of extraction.
The National Water Commission’s (NWC) 2009 and 2007 Biennial
Assessments on progress of water reform have identified shortcomings in how
water plans implement the concept of environmental sustainability and in the
recovery of water from over-allocated and overused systems. Consequently,
the NWC has identified addressing over-allocation and overuse in water
systems as a high priority. This is reflected in our Sustainable Water
Management Improvement Strategy and NWC Water Dependent Ecosystem
Position Statement.
A major difficulty in addressing over-allocation and overuse issues is the
absence of a nationally agreed method for determining the sustainable levels
of extraction within a water system. As a consequence the extent of overallocation is unknown at a national level. However, in the absence of an
agreed procedure, the Commission believes it is possible to provide
defensible evidence of the extent to which water scarcity is causing significant
water stress to water systems. This scarcity can arise from climatic changes
and other causes as well as from water extraction and use.
The National Inventory of Water Stressed Catchments and Aquifers project
proposes to develop an Australia-wide picture of water stress using a
systematic and transparent approach that distinguishes where possible
between different causes of water stress, and is informed as much as possible
by existing processes and indicators.
1
1.1
Approach
The Inventory is being developed through the following stages:
(a)
Understanding existing approaches to identifying water stressed
catchments and aquifers, e.g. those used by jurisdictions, the MBDA
and the CSIRO Sustainable Yields work
(b)
Producing a series of maps, and an associated report, of the
hydrological stressors or pressures present in each catchment/aquifer
(to be undertaken by the Bureau of Meteorology in collaboration with
CSIRO and other specialists)
(c)
Clarifying the feasibility of using ecological indicators that are sensitive
to water scarcity to help determine levels of water stress via a
discussion paper and workshop (this project). If the approach is
feasible, an ecological indicators project will be implemented
(d)
Commissioning discussion papers related to other dimensions of water
stress and, if feasible and supported by the Steering Committee,
developing indicators
(e)
Integrating and packaging the above to produce a national inventory of
water stressed catchments and aquifers, and supporting documents.
1.2
End Uses
The inventory is intended for national use. The inventory will assist the
National Water Commission in:

Undertaking periodic national assessments such as Biennial
Assessments

Encouraging nationally consistent interpretations of water stress and
building public understanding of the extent of water stress

Informing the priorities, processes and programs of the NWC and other
organizations

Achieving aspects of the National Water Initiative relevant to its charter.
2
1.3
Definition and Scope
For the purposes of this inventory, water stressed catchments and aquifers
are those that demonstrate signs of significant surface and/or ground water
scarcity as indicated by:

Available jurisdictional assessments of water scarcity or water stress

The hydrological stressors present in the catchment/aquifer relevant to
ecological processes and, depending on the results of scoping
investigations,
o The state of the water scarcity-sensitive ecology in the
catchment/aquifer area
o The understanding of communities in the catchment/aquifer area
about the impacts of water scarcity on that aquatic environment.
Relative levels of water stress will be identified. How the levels will be
categorised, and whether the above indicator ‘layers’ can be combined into a
single index of extraction-related water stress, will be examined as the project
progresses. Where possible, climate induced stress will be distinguished from
extraction induced stress. The inventory is focusing on stress related to water
scarcity, not too much water.
1.4
Ecological Indicators Discussion Paper
This project will investigate whether and how ecological indicators derived
from existing data collections can be used to indicate the extent to which
water systems across Australia have been impacted by surface and
groundwater scarcity. Chapter 2 introduces ecological monitoring, Chapter 3
defines ecological indicators, Chapter 4 summarizes the responses of the
ecological groups to changes in water regimes from a thorough literature
review, Chapter 5 looks at the potential indicators that come through that
literature review and speculates as to what sort of data would be required,
Chapter 6 looks at the available data from existing monitoring programs,
Chapter 7 summarizes the preceding three chapters into feasible indicators for
each ecological group and Chapter 8 looks at the best way forward for all
groups.
3
2
Introduction to Ecological Monitoring
Freshwater organisms have been used widely within Australia and globally for
environmental monitoring (e.g. Barbour et al. 1992; Norris et al. 2007b). These
bioindicators are used to assess responses to environmental stresses (e.g.
organic pollution), particularly physico-chemical characteristics affected by
landuse (e.g. agriculture, urbanisation or mining)(e.g. Barbour et al. 1992;
Chessman 1995; Johnson et al. 2006). Biological monitoring in freshwater
systems has been undertaken using a range of taxa, including invertebrates,
algae, fish, plankton, plants and terrestrial fauna (e.g. birds) – with indices
based on individual groups and/or combinations. Recent examples of studies
that report on assessments of freshwater systems using several groups of
organisms include O'Connor et al. 2000 (invertebrates, diatoms, zooplankton,
fish and birds); Johnson et al. 2006 (fish, macrophytes, benthic diatoms and
macroinvertebrates); and (Angradi et al. 2009)(fish, macroinvertebrates,
phytoplankton, zooplankton, aquatic vegetation).
The term ecological indicators can refer to ecological components (e.g. soils,
biota, physical form, etc), ecological processes (e.g. climate, nutrient
dynamics, species interactions, etc.) or ecosystem services (e.g. maintenance
of hydrological regime, recreation and tourism, educational, etc.) (Department
of the Environment Water Heritage and the Arts 2008). In this discussion
paper I stick to where the bulk of the literature, research and jurisdictional
programs are aimed—at the ecological components of aquatic biota and
associated processes. I concentrate on five main groups of assumed
importance from my experience with existing monitoring programs. The
themes chosen are: vegetation (wetland and riparian), macroinvertebrates,
fish, waterbirds, and algae and plankton. The in-stream components of
macroinvertebrates—fish, algae, and plankton—are reviewed together under
the umbrella of freshwater biota, whilst waterbirds and vegetation stand alone.
Because of the complex nature of ecosystems their function can be quantified
using measures of ecosystem process (Bunn et al. 1999) and I have included
this as well. There is no relevant ecological monitoring of groundwater
dependent ecosystems and these are unfortunately only briefly addressed.
4
3
Ecological Indicators
Sections 3.1 to 3.4 and Section 3.7 are adapted from the United States
Environment Protection Agency’s Environmental Monitoring Assessment
Program, Research Strategy (McDonald et al. 2002).
3.1
What is an Ecological Indicator?
An indicator is one (or more) measure(s) or model(s) that describes the
condition of the system in question (e.g. blood pressure is an indicator of
human health, an ecological indicator is an indication of ecological health).
Effective aquatic ecological indicators are central to determining the condition
of aquatic resources. The most successful ecological indicators have been
multi-metric indices formed by combining biological indicators within a taxon
(e.g. those indices related to fishes—number of species present, number of
pollution-tolerant species, etc.) found in aquatic ecosystems. Separate
indices for different taxa (from plants, birds, vegetation, fishes, etc.) are
important because they may be critical components of aquatic ecosystems,
and because they integrate various natural and anthropogenic stressors into
their responses. Indicators can stand alone or as flags that trigger additional
measurements of the fundamental and associated components of the abiotic
environment, including physical measures of habitat (e.g. substrate type and
quality, depth) and chemical measures of the ambient water quality (e.g.
dissolved oxygen, temperature, salinity, nutrients, and toxics).
3.2
Indicator Development
Indicators can be developed for any level of biological organization (Table
3.1). However, the structural and functional aspects of the biological or
ecological characteristic to be used as an indicator must be appropriate to the
question being asked.
5
Table 3.1. Levels of biological organization to consider during indicator
development with examples of structural and functional aspects of each level
(Adapted from McDonald et al. 2002).
Structure
Level of
Organization
Processes
Heterozygosity
Gene
Polyploidy Rate
Mutation Rate
Recombination Rate
Condition
Anomalies/Deformities
Maximum Size
Tissue Contamination
Individual
Metabolic Rate
Growth Rate
Fecundity
Abundance
Age Class Distribution
Size Class Distribution
Population
Reproduction Rate
Growth Rate (of Population)
Death Rate
Evolution/Speciation
Relative Abundance
Richness -Native
Richness - Total
Evenness
Trophic Composition
Reproductive Composition
Habitat Guilds
Assemblage
(Community)
Competition/Predation
Disease/Parasitism
Mutualism
Recovery Rate
Regional Diversity (gamma)
Homogeneity
Hot Spots
Patches
Patterns
Fragmentation/Recovery
Watershed or
Landscape
(Basin or
Catchment)
Water Delivery
Chemical Delivery (Native and Exotic)
Material Delivery (Sediment, Wood)
Energy Flow
Nutrient Cycles and Spiraling
Population Sources and Sinks
Fragmentation Rate/Recovery Rate
3.3
Indicator Variability
An often overlooked, yet essential component of any monitoring program is
the description of the components of variability, which impacts status and
trends in the indicator. The important consideration is the extent to which
variability in measuring the indicator (noise) masks detection of significant
changes. This may be natural variability such as the real differences within a
body of water or real differences from the period when the sampling site is
visited. It also contains variability created by the samplers and differences
among samplers, the laboratory/data processing and other extraneous
components. Ultimately, there is little point in implementing an indicator on
6
conceptual relevance alone. Sufficient information on indicator variability is
needed to determine the power of the indicator to detect a change or trend. In
snapshot studies, the indicator must be able to determine the status of the
ecosystem to within acceptable levels of tolerance.
3.4
Indicator Demonstration
During the final stages of indicator development, potential users must be given
some sense of how well the indicator performs and how it can be used. This
often implies demonstrating the indicators in a regional scale project, showing
the results and potential conclusions, which may derive from using the
indicator. This is part of a necessary “proof-of-concept” for the indicator to be
accepted into widespread use. Indicator demonstration would be the next
step in this project if potential indicators are found and recommended.
3.5
How could ecological indicators be used to indicate
water stress in catchments and aquifers across Australia?
The concept is that ecological indicators in ecosystems that are subjected to
stress from water scarcity will be detectably different from those in unstressed
systems. In the simplest scenario for this particular project, the ecosystem
would only be subjected to stress from water scarcity and any changes in the
indicator (from some predetermined ‘reference’ or ‘healthy’ value) would be
attributable to water scarcity related stress (Figure 3.1). Even if this type of
ecosystem could be found it would be in the minority as the majority of
Australian aquatic ecosystems are exposed to multiple stressors.
To deal with ecosystems exposed to multiple stressors, including water
scarcity, it is desirable to find indicators that either a) react only to water
scarcity, or b) can partition water scarcity effects from other stressor effects.
An example of these scenarios is shown in Figure 3.2. One of the stressors
that may already be affecting and could affect all ecosystems in the future is
climate change.
7
Changed
Ecological
indicators
Ecological
indicators
Healthy
Ecosystem
functioning
normally
Water scarcity
Stressed
Ecosystem
Figure 3.1: Concept of using ecological indicators to identify stressed
ecosystems in the ideal situation where water scarcity is the only stressor
affecting the indicators.
3.5.1 Dealing with climate change and other stressors
The effects of other stressors in the system, such as Climate Change, are
easily dealt with in a statistical sense by using reference sites. Whether or not
climate change effects in general should affect water allocations is
independent of this paper. Statistically speaking, to partition out the effects of
climates change, reference/comparison sites/units can be used. For example;

Assume or locate several sites that have the same exposure to climate
change (e.g. similar geography and climatic histories)

One or more of the sites are known not to be exposed to water scarcity
related stress during the monitoring period and are treated as reference
sites

Changes in the chosen indicator(s) in the other sites are compared to
the (non-water stress related) changes in the reference sites and an
evaluation made.
This method works best if the reference and assessment sites are a similar as
possible in as many ways as possible before the assessment period, but it is
8
not essential. Finding more than one reference sites may help considerably.
This method is akin to the example in Figure 3.2a.
a)
Ecological
indicators
Healthy
Ecosystem
functioning
normally
Changed land use,
Climate change,
Chemical pollution,
etc etc.
Including water
scarcity
Multiple stressors
Changed
Ecological
indicators
Stressed
Ecosystem
b)
Changed land use,
Climate change,
Chemical pollution,
etc etc.
Multiple stressors
Ecological
indicators
Already
Stressed
Ecosystem
Changed
Ecological
indicators
Water scarcity
Stressed
Ecosystem
Figure 3.2: Concept of using ecological indicators to identify stressed
ecosystems where multiple stressors affect the ecological indicators.
a) A component of change in the indicator can be attributed to water scarcity,
and b) the ecological indicators are designed or adjusted to react only to water
scarcity.
3.6
Standardising Indicators
Indicators need to be standardised for comparison. The standardising can be
in the sampling protocol or calculation of the indicator, or both. For example,
9
the Sustainable Rivers Audit (SRA) uses a standardised sampling protocol for
all fish sampling in the MDB. This makes it possible to directly compare
across sites or regions in, say, number of fish or number of fish species or
number of herbivorous fish species, etc. On the other hand, the
macroinvertebrate sampling has slight differences between jurisdictions (live
pick Vs lab sort). But the comparisons are made possible because the
number of species is compared against a predicted number of species or
community structure for the relevant sampling method.
The raw data are rarely used for reporting purposes and the indicators are
typically called ‘Indices’ or ‘Metrics’. An index is the score after standardising
for sampling. For example, an AUSRIVAS OE score is the Observed to
Expected Ratio and although more extreme values can occur; for
macroinvertebrates this typically takes a value between 0.3 and 1.5. In the
Sustainable Rivers Audit the term metric refers to an index that has generally
been range standardised to only take values between 0 and 1. When
referring to indicators, this paper talks about the variable measured and when
referring to metrics I infer the SRA definition above; i.e. the indicator called
species richness is the number of species in the taxon of interest, the metric
called species richness is a ratio of how fit the spatial unit (site or region) is,
based on species richness in that group.
3.7
Indicator Responsiveness
Evaluating the degree to which a particular indicator actually responds to
stressor gradients is an important aspect of the indicator development
process. Without some knowledge of the shape of the response curve and the
variability associated with the response, it is difficult to evaluate the utility of
any particular indicator. For example, an indicator such as percent native
vegetation can only take a value between 0 and 1, but this does not make it a
metric. Proportions are non-linear, particularly near the extremes and so a
score of say 0.99 is not the same distance from 0.98 as a score of 0.51 is from
0.50. Understanding the responsiveness is part of the process used to
generate the metrics in monitoring programs like the SRA.
10
3.8
Which Indicators?
One of the requirements of this discussion paper is to review potential
ecological indicators sensitive to water scarcity that could be used to indicate
water stress either across Australia, or in parts of Australia. Preference is to
be given to using existing programs and data where possible.
Several approaches could be taken on this. One approach would be to review
existing programs first, then determine whether there is anything relevant to
water scarcity being collected. The second approach would be to determine
what relevant indicators are needed and then to interrogate existing data and
programs to find compatibilities. The former approach is certainly more time
efficient but risks not finding as many potential indicators. Because no
jurisdiction currently uses ecological indicators of water related stress per se,
the second approach should locate many more relevant potential indicators.
Many of these potential indicators will not be available ‘off the shelf’, but the
approach has a higher chance of finding a way forward. Therefore the
approach I have taken is the latter of the two. I start by reviewing the literature
and experts in detail and then drill into the available data to search for
matching data and indicators.
3.9
Regional indicators
As is noted for river health indicators in the Framework for the Assessment of
River and Wetland Health (FARWH) (Norris et al. 2007a) it is quite
reasonable to have different indicators for different regions. In fact it would be
expected that this were the case because the ecological responses of different
ecosystems must be related to the organisms and processes naturally
occurring there. For example, floodplain vegetation may be an ideal indicator
for floodplain ecosystems but it is totally irrelevant in regions where
floodplains do not occur.
3.10 It’s all a matter of scale
Scale is one of the most important issues for this project. Scale of response
for each indicator and scale of reporting required for the project are very
different matters. For example, it may be found that wilting in individual trees
11
is a very good indicator of water scarcity related stress. How to turn this into
an indicator is one question and how to report tree wilting on a national scale
is another. Each potential indicator will need to address a response scale and
how it may be used in a national reporting framework. Temporal scale also
plays a huge role in this project. How long does the response unit have to be
exposed to scarce water before it responds? Generally speaking the
aggregating of indicators to larger spatial scales has been well studied and
indicators developed in this report can be aggregated using the FARWH
protocol (Norris et al. 2007a)
3.11 Indicators Summary
Indicators of any kind need to be responsive, have known relationships and be
suitable for the question(s) being asked. This report will list currently used
ecological indicators in Australian aquatic resource monitoring programs and
propose more, based on conceptual relationships using the literature review
and expert opinion. However, any proposed indicators and not even all those
currently in use have been subjected to rigorous evaluation of sources of
variability and ultimately, ecological sensitivity. That is beyond the scope of
this discussion paper but recommendations will address a way forward.
12
4
Identifying Potential Ecological Indicators of Water
Scarcity for the Australian Environment.
Considerable literature reviews were performed for this section but only
summaries are presented here. The literature reviews in detail are provided
as appendices.
4.1
Literature demonstrating the use of ecological indicators
of water scarcity
There is very little existing literature looking at water scarcity and ecological
relationships. However, there are a number of studies (mostly Australian)
reporting on closely related topics such as the development of ecological
indicators for use in monitoring aspects of flow alteration. The potential of a
range of organisms to be used as indicators of the effects of environmental
water allocations on wetlands of the Murray–Darling Basin were discussed in
Reid and Brooks (2000). In a similar approach as outlined for this paper, their
assessment was based on current knowledge of responses of particular
taxonomic groups to physical and chemical changes associated with changes
in water levels in wetland systems (Reid and Brooks 2000).
4.2
In-stream biota
This section summarizes the literature relevant to macroinvertebrates, fish,
algae and plankton. Benthic macroinvertebrates are one of the most common
groups used for assessing ecological river quality. Benthic macroinvertebrates
are capable of reflecting different anthropogenic perturbations through
changes in structure or function in the assemblages and thus enable an
overall assessment of streams (Hering et al. 2004). Examples of freshwater
monitoring programs based on benthic macroinvertebrates include
AUSRIVAS, which has been used in all states and territories throughout
Australia (Norris et al. 2001) and AQEM (developed under the EU Water
Framework Directive (Hering et al. 2004)). Sheldon and Thoms (2006) used
an analytical approach to investigate relationships between macroinvertebrate
assemblages and flow variability indices (including indices reflecting stream
13
permanence and connectivity). Similarly, the Lotic-invertebrate Index for Flow
Evaluation (LIFE), for assessing the impact of variable flows on benthic
macroinvertebrate populations (see also (Monk et al. 2006)), reported on a
wide-scale application of LIFE across England and Wales (Extence et al.
1999). The LIFE approach is discussed in more detail in Appendix 3. Other
studies investigated the suitability of using AUSRIVAS monitoring to assess
the impact of dams (Marchant and Hehir 2002) and during periods of drought
(Rose et al. 2008). (Growns 2008) assessed relationships between fish
assemblages and an index of hydrological alteration in regulated rivers. Fish
are also regarded as good bioindicators and are often used for the
assessment of the ecological integrity of rivers, because of their longevity,
mobility and sensitivity to habitat modification (e.g. Lasne et al. 2007;
Oberdorff et al. 2002; Welcomme et al. 2006b). The more widely used
freshwater bioindicators are based on community-level data (e.g. species
richness, and diversity). This is the case for several macroinvertebrate
indices, such as SIGNAL (Chessman 1995), AUSRIVAS (Davies 2000), family
richness, EPT (Ephemeroptera, Plecoptera and Trichoptera) and OCH
(Odonata, Coleoptera and Hemiptera) (Barbour et al. 1992). Fish based
monitoring programs tend to include community, population and individual
based metrics (e.g. Harris and Gehrke 1996).
Algae and plankton have rarely been used as bioindicators in ongoing
monitoring programs.
4.2.1 Relationships between hydrology and ecology of in-stream biota
A conceptual diagram summarising effects of reduced flow on invertebrates is
shown in Figure 4.1.
14
Figure 4.1: Summary of the effects of decreased stream flow on habitat
conditions and invertebrate community abundance, diversity and composition
(from Dewson et al. 2007). The general structure can be applied to other
in-stream biota including fish, algae and plankton.
4.2.2 Responses of in-stream biota to water scarcity (i.e. reduced flow
or drought)
The most frequently reported responses to water scarcity (i.e. reduced
flow/discharge or drought) for macroinvertebrates were decreases in diversity
and abundance (Table 4.1). Changes to community composition were also
reported by a number of studies. In particular, riffle habitat specialists tended
to be replaced by pool-preferring taxa, as flow or discharge decreased.
Several studies reported changes in patterns of drift (increases and
decreases) in response to reduced flows (Table 4.1).
15
Table 4.1: Responses of macroinvertebrates to reduced flow or discharge,
including drought.
Flow characteristics
affected
Reduced flow
(from drought and/or water
diversion and/or
abstraction)
Biological or Ecological Response
References
Of the 22 studies cited in an earlier literature
review, the most reported decreases in density
(12 studies) and taxonomic richness (9 studies);
and altered species composition (20 studies). Of
the 11 studies cited that investigated drift, 10
reported increases.
(Dewson et al. 2007)
(review paper)
Reduced community diversity; Increased number
of pollution-tolerant, lentic taxa present in edge
habitat; increased number of pollution-sensitive
“pool-preferring” taxa in riffle habitat; reduced
abundance of some taxa; altered community
structure.
(Attrill et al. 1996; Cowx et al.
1984; Rose et al. 2008;
Suren and Jowett 2006)
Increased drift for some species during
(experimental) periods of reduced flow; altered
species composition of drift invertebrates.
(James et al. 2009; Tonkin et
al. 2009)
Changes to predation and competition (increases
and decreases reported).
(Malmqvist and Sackmann
1996; Matczak and Mackay
1990; Zhang et al. 1998)
Reduced connectivity
(cessation of flow/river
reduced to fragmented
pools or flow in the
hyporheic zone only)
Reduced diversity and abundance of rheophilous
taxa (e.g. riffle-dwelling mussels, hydropsychic
caddisflies); reduced recolonisation as a result of
reduced drift; altered community structure
(Boulton 2003; Golladay et
al. 2004; Hose et al. 2005)
Drought and/or water
diversion or abstraction
coupled with increased
salinity and poor water
quality
Altered species assemblage (increased
dominance of salinity-tolerant taxa)
(Lind et al. 2006)
Reduced frequency,
duration and area of
inundation of
floodplain/wetlands
Reduced abundance and biomass of
invertebrates
(Boulton and Lloyd 1992)
Research concerning the responses of fish to water scarcity has involved
many studies focused at population-scale monitoring (c.f. macroinvertebrate
studies, which were mostly community-level), and the response most often
reported was population decline (Table 4.2). Other responses detected in
population-level studies included reduced growth rates and recruitment.
Several authors also reported changes at the community scale and these
included reduced diversity and/or increased prevalence of exotic species or
habitat generalists, and decreased prevalence of riffle specialists (Table 4.2).
16
Table 4.2: Responses of fish to reduced flow or discharge, including drought.
Flow characteristics
affected
Reduced flow
(from drought and/or
water diversion and/or
abstraction)
Biological or Ecological Response
References
Of the 50 studies cited in an earlier review, most
reported population declines during drought (38
studies).
Other prevalent findings were death attributed to
poor water quality, crowding, decreased
reproduction, altered community assemblages,
altered movement patterns (increased
movement during early stages of drought;
decreased movement in later stages because of
lost connectivity).
(Matthews and MarshMatthews 2003)
(review paper)
Reduced abundance and biomass (overall);
reduced richness and abundance of rifflespecialist species; some pool-dwelling species
found to be insensitive to moderate flow
reductions (e.g. 75-90% reduction of summer
flow); reduced growth rates; altered community
structure (increased prevalence of exotic species
and/or habitat generalists); reduced Index of
Biotic Integrity scores, increased competition and
predation; reduced recruitment and/or failure to
spawn.
(Bradford and Heinonen
2008; Cowx et al. 1984;
Freeman and Marcinek
2006; Harris 1988;
Magoulick and Kobza
2003; Marchetti and Moyle
2001; Osmundson et al.
2002; Osmunson et al.
2002)
Long-term flow reduction
Population declines and local extinctions;
reduced growth rates and recruitment for some
species.
(Bond et al. 2008;
Matthews and MarshMatthews 2003)
Reduced connectivity
(cessation of flow/river
reduced to fragmented
pools or flow in the
hyporheic zone only)
Reduced diversity and abundance of rifflespecialist species; crowding (i.e. fish trapped in
dry season refuges with deteriorating
physicochemical conditions and reduced food
availability); increased competition and
predation, increased rates of disease, parasitism
and mortality; stranding of fish (particularly
larvae and juveniles); altered community
structure.
(Bradford 1997; Bradford
et al. 1995; Freeman et al.
2001; Kushlan 1976;
Lowe-McConnell 1985;
Magoulick and Kobza
2003; Medeiros and
Maltchik 1999; Pusey et
al. 2004; Woodland and
Ward 1990)
Reduced frequency,
duration and area of
inundation of
floodplain/wetlands
Reduced spawning areas and/or recruitment
success of lowland river fish.
(Cadwallader and
Lawrence 1990; Geddes
and Puckridge 1989; Jubb
1972; Lake 1975;
Welcomme 1979; Whitley
and Campbell 1974)
The responses of fish need to be considered on a site-by-site or case-by-case
basis. For example, a recent study found that a hydrological index that
described hydrological change in six regulated rivers in the Murray–Darling
Basin explained only a small amount of variation in fish assemblage structure
and the abundances of individual fish species (Growns 2008). This may
reflect the general nature of the hydrology index used, a composite measure
of various aspects of hydrological change.
17
In comparison to macroinvertebrates and fish, literature documenting the
responses of algae and plankton to water scarcity was limited (Table 4.3). Of
the few studies identified, most reported increases in algal biomass in
response to reduced flow or drought, but decreases in diversity and altered
community structure were also documented.
Table 4.3: Responses of algae and plankton to reduced flow or discharge,
including drought.
Flow characteristics
affected
Reduced flow
(from drought and/or
water diversion and/or
abstraction)
Drought and/or water
diversion or abstraction
coupled with increased
salinity and poor water
quality
Biological or Ecological Response
References
Of the 7 studies cited in an earlier literature
review, most reported increases in algae (6
studies); some reported mixed responses.
(Dewson et al. 2007)
(review paper)
Reduced production and altered community
assemblage of benthic algae (and substantially
so, if flow reduction results in the loss of
permanent pools)
(Robson and Matthews 2004)
Altered periphyton biomass.
(Tonkin et al. 2009)
Increased production of phytoplankton
associated with flow reduction
(Lloyd et al. 2003)
Changes in species composition of zooplankton
(Nielsen et al. 2005; Zhou et
al. 2008)
Decreased species diversity and richness of
diatoms in streams with increased secondary
salinity (attributable to heavy irrigation and
dryland farming)
(Blinn and Bailey 2001)
Examples of the responses of other freshwater organisms to water scarcity
were also found in the literature (Table 4.4). Several population-level effects
were documented for shrimp, including reduced reproductive success,
reduced migration of larvae and altered size-class distribution. Drought was
found to be associated with decreased richness but increased abundance of
emergent propagules (invertebrates, protista and algae). Lastly, related
research on two turtle species demonstrated that reduced flows were likely to
result in decreased reproductive output (pig-nosed turtle), and drought (pond
drying) resulted in an increase in emigration rates and stress levels in slider
turtles.
18
Table 4.4: Responses of other freshwater organisms to reduced flow or
discharge, including drought.
Organism
Flow characteristics
affected
Biological or Ecological Response
References
Shrimp
Reduced flow
(from drought and/or
water diversion and/or
abstraction)
Reduced migration of shrimp larvae;
Increased densities in shallower and
smaller pools; increased competition
for resources and decreased
reproductive success; altered sizeclass distribution.
(Covich et al. 2003;
Pringle and
Scatena 1999)
Wetland sediment
propagules
(invertebrates,
protista and algae)
Drought and/or water
diversion or abstraction
coupled with increased
salinity and poor water
quality
Decreased richness and increased
abundance of emergent propagules
associated with (experimentally)
increased salinity (i.e. similar to
conditions that may be present as a
result of hydraulic alteration in natural
wetland systems)
(Skinner et al.
2001)
Turtles
Reduced flow
(modelled water
abstraction)
Reproductive output of pig-nosed
turtle predicted to decrease (based on
models of reduced river flows), as a
result of habitat fragmentation,
reduced access to food and nesting
resources.
(Georges et al.
2003)
Pond drying (drought)
Slider turtle (not an Australian
endemic) showed behavioural
(increased emigration) and endocrine
(increased levels of “stress” hormone)
responses to decline in habitat quality
(pond drying).
(Cash and
Holberton 2005)
19
4.3
Waterbirds
4.3.1 Relationships between hydrology and ecology of waterbirds
Waterbirds were approached vigorously because there are several features of
their ecology that appealed to make them potentially suitable candidates to
supply indicators. They are widespread and by definition they are water
dependent birds. An interesting feature of their ecology is that they are at the
top of a chain of events related to water dependency. That is, they are
dependent on water itself, but also reliant on other ecosystem responses to
water or the hydrological regime. For example, they rely on suitable nesting
habitat, which may be floating macrophytes, which in turn are reliant on the
hydrology of the system. Or they may be dependent on eating the fish, which
may be dependent on eating the macroinvertebrates, which may be
dependent on grazing on the algae, which may be dependent on the nutrients,
which may be dependent on the soil, which may be dependent on the
hydrology. There are many, many such complex interactions between
waterbirds and their environment and unfortunately this means that there are
many, many ways that they may become absent from, or less productive in an
area. In other words, there are no immediately perceivable indicators of water
scarcity for waterbirds that aren’t confounded by at least one other variable.
Even persistence or presence at site is a poor indicator, because they can
move quite readily and absence doesn’t mean poor condition (Kushlan 1993).
One unique feature of this group is their capability for migrating across
catchments. This has two consequences: their absence may tell us nothing
because they just happen to be somewhere else; or their presence means
that at least the area they are in can support them. There is a lot of emphasis
in the literature on breeding events in waterbirds, but this is difficult to interpret
as a potential indicator because of the inherently variable nature of breeding
and their migration patterns. For example, breeding only once in 8 years will
sustain the populations of some species in some areas(Lesley 2001). In
years when they aren’t breeding in an area they may be doing so somewhere
else. So in the long run if the species persists at the regional or national
scale, then it will probably migrate to other areas when opportunities arise. So
how can a breeding indicator be used? Perhaps one could say that in region
20
X (say, Hattah Lakes) if species Y has bred and fledged young twice in the
last 10 years, then that is normal. Well, if that become an indicator then at
least 10 years of data would be required for reporting. Besides which the
sensitivity is questionable because statistically speaking it would not be
uncommon for a 1 in 5 year flood to occur only once or not occur at all in a
10-year period. So non-breeding may tell us there is a potential water
shortage in that area, but not whether that is an unnatural shortage. However,
if there were long-term data that showed that species Y has never gone more
than, say, 5 years without breeding before, then there is a way forward.
Hence a problem with many potential indicators in most themes, but
waterbirds in particular, is the need to partition natural variability.
Because they are an icon group of species with reasonably high public
appeal, the waterbirds literature review (Appendix A1) is comprehensive and
many options are explored. Waterbirds have recently been adopted in some
monitoring programs (see Chapter 7) albeit with little research into sensitivity.
21
4.3.2 Responses of waterbirds to water scarcity (i.e. reduced flow or
drought)
There are no papers looking at water scarcity per se. A summary of known
responses to hydrological alterations is given in Table 4.3.1. Most literature is
relevant to wetlands or floodplains and little refers to the river channel.
Table 4.3.1: Responses of waterbirds to hydrological alteration.
Flow characteristics
affected
Reduced Wetlands
Area
Biological or Ecological Response
References
Decreased Waterbird Abundance
(Kingsford and Thomas
2004), (Lesley 2001),
(Kingsford et al. 1999)
Decreased Waterbird Diversity
(Green et al. 2002)
Reduced Breeding events
(Hughes 2003; Kingsford
and Johnson 1998),
(Eglington et al. 2008),
(Kingsford and Norman
2002)
Reduced Breeding Success
(Russell et al. 2002),
(Kushlan 1993)
Increased migration
(Kingsford and Norman
2002), (Kingsford et al.
1999)
Decreased waterbird population
(Kingsford and Johnson
1998)
Change in diet
(Kingsford and Norman
2002)
Increased waterbird abundance
(Kingsford et al. 1999),
(Dorfman et al. 2001)
Increased waterbird breeding
(Lesley 2001)
Increased waterbird abundance
(Bellio et al. 2009)
Decreased Breeding success
(Desgranges et al. 2006)
Fewer breeding events
(Lesley 2001)
Changed community composition
(Kingsford and Thomas
2004)
Decreased Flood
magnitude
Decreased breeding
(Kingsford and Auld 2005)
Changed timing of
flood
Decreased breeding
(Lesley 2001), (Kingsford
et al. 1999), (Kingsford
and Norman 2002)
Permanence of flow
Decreased waterbird diversity
(Kushlan 1993),
(Robledano et al. 2009)
Reduced Flow Volume
Wetland drying phase
Variability in water
depth
Decreased Flood
Frequency
22
4.4
Vegetation
4.4.1 Relationships between hydrology and ecology of vegetation
There is little literature on in-channel vegetation and this section refers to
riparian and floodplain vegetation in the main. Vegetation requires water and
differs from the other themes in that it potentially uses surface water, ground
water and rainfall, hence is a potentially better indicator of overall water stress.
Literature from the theme is really dominated by contemporary studies and
there are significant keystone papers in the last few years. Intuitively there is
a lot of potential in this theme because of a couple of significant biological
traits unique to vegetation: 1) Individuals don’t move, if there is a water
scarcity issue, the tree(s) must weather it out, they can’t move. 2) The known
responses to stressors can apply and be measured at the individual or
population (e.g. stand of trees) scale. This theme threw up considerably more
potential indicators than the others and certainly has fewer issues with
confounding than any of the others. In other words, whilst there are other
potential stressors to vegetation, many effects can be readily differentiated
from water stress effects.
4.4.2 Responses of vegetation to water scarcity (i.e. reduced flow or
drought)
Known and potential responses were well summarised by (Poff and
Zimmerman 2010) but in Table 4.4.1 I have included many others as turned
up in the literature review (Appendix A2). One finding from the literature
review is that there is a tendency to monitor overall vegetation health, as well
as or instead of simply responding to individual stressors, so I have also
included a table listing recommended general indicators of vegetation health
from a couple of key contemporary papers (Table 4.4.2).
23
Table 4.4.1: Responses of vegetation to reduced flow or discharge, including
drought.
Flow characteristics
affected
Lower peak flows
Biological or Ecological Response
References
Change in recruitment, failure of seedlings
(Poff and Zimmerman 2010)
Terrestrialisation of flora
(Poff and Zimmerman 2010)
Increased exotic success
(Poff and Zimmerman 2010)
Lower species richness
(Poff and Zimmerman 2010)
Vegetation encroachment
(Poff and Zimmerman 2010)
Increased Riparian cover
(Poff and Zimmerman 2010)
Change in community composition
(Poff and Zimmerman 2010)
Decreased species richness
(Poff and Zimmerman 2010)
Increased wood production
(Poff and Zimmerman 2010)
Reduced growth rate
(Poff and Zimmerman 2010)
Change in community composition
(Poff and Zimmerman 2010)
Terrestrialisation or desertification
(Poff and Zimmerman 2010)
Reduced area of riparian cover
(Poff and Zimmerman 2010)
Reduced riparian recruitment
(Poff and Zimmerman 2010)
Invasion of exotic riparian species
(Poff and Zimmerman 2010)
Increased mortality/reduced growth rates
(Poff and Zimmerman 2010)
Reduced species richness
Reduced cover
(Poff and Zimmerman 2010)
Increased variability
Decreased germination/survival and growth
(Poff and Zimmerman 2010)
General soil moisture
shortage
Trees: Slower Growth/ Mortality
Dieback
(Jensen et al. 2008),
(Roberts 2004),
(Cunningham et al. 2009)
Less reproduction
(Roberts 2004)
Understorey: depletion of seed banks
(Roberts 2004)
Attrition of perennating organs
(Roberts 2004)
Differentiation in dieback
(Cunningham et al. 2009)
Changes in Xylem water potential
(Merritt et al. 2010)
Wilting, chlorosis, leaf discoloration, leaf death,
canopy reduction
(Merritt et al. 2010)
Terrestrialisation
(Roberts 2004), (Overton et
al. 2006), (Wen et al. 2009),
(Kingsford and Thomas
2004)
Loss of vigour/cover of dominant trees
(Roberts 2004)
Lower species richness
(Roberts 2004)
Reduced number of strata
(Roberts 2004)
Reduced leaf area
(Capon et al. 2009)
Increased species richness
(Roberts and Hale 2007)
Abundance and proportion perennial species
(Roberts and Hale 2007)
Increased exotic species richness/abundance
(Roberts and Hale 2007)
Fewer peak flows
Decreased duration of
floodplain inundation
Loss of seasonal flow
peaks
General Water availability
24
Decreased water dispersed species
(Roberts and Hale 2007)
Decreased forest productivity
(Horner et al. 2009)
Vigour/Decreased Leaf Area
(Horner et al. 2009),
(Cunningham et al. 2007b),
(Wen et al. 2009), (Roberts
2004)
Dieback
(Cunningham et al. 2009)
Increased salinity from
reduced leaching
(flushing)
Reduced riparian vegetation health
Increased Black Box distribution
(Holland et al. 2009),
(Overton et al. 2006)
Increased salinity from
lower water tables
Species loss
(Salter et al. 2008)
Riparian Vegetation condition
(Overton et al. 2006)
Terrestrialisation
(Overton et al. 2006),
(Ringrose et al. 2007)
Changes in tree and shrub height
(Ringrose et al. 2007)
Crown condition
(Wen et al. 2009)
Fewer Floods
Table 4.4.2: General measures of health used for riparian or floodplain
vegetation.
General Vegetation
health Indicator
How measured
References (Lobo et al. 1997)
Ecological Condition
Hectares of dead trees
(Roberts 2004)
Nativeness
% of species that are non-native
(Roberts 2004)
Canopy Condition
% Canopy alive
(Roberts 2004)
Regeneration Density
Number of juveniles/seedlings/ Hectare
(Roberts 2004)
Demography
Number regenerating tress in size
classes
(Roberts 2004)
Plant Area Index
the area of leaves and stems per unit
ground area,
(Cunningham et al. 2007b)
Photosynthetic
capacity/Vigour/Biomass
NDVI
(Cunningham et al. 2007a;
Cunningham et al. 2009; McVicar
et al. 2003; Sims and Thoms
2002)
25
4.5
Biological Processes
Functional integrity is a complement to structural integrity and refers to the
rates, patterns, and relative importance of different ecosystem-level processes
(Gessner and Chauvet 2002). The biological processes of metabolism,
respiration and primary production respond to environmental variables that
are commonly influenced by catchment disturbance (e.g. such as light and
temperature regimes and nutrient loads) (Bunn et al. 1999; Fellows et al.
2006). Community attributes such as macroinvertebrate functional indicators
can be used to track ecosystem processes (e.g., secondary production, leaf
processing rates) in the case of extreme disturbance, but may not be sensitive
at lower levels of disturbance (Bunn and Davies 2000). Therefore, direct
measures of ecosystem processes, such as benthic community metabolism,
are important considerations in aquatic ecosystem health monitoring (Bunn
and Davies 2000; Fellows et al. 2006).
Ecosystem processes that potentially could be used as functional indicators of
river ecosystem health include:

Rates of leaf breakdown

Ecosystem metabolism (the combination of algal productivity and
ecosystem respiration)

Rates of nutrient uptake

Microbial respiration

Nitrification

Fine particulate organic matter export

Coarse particulate organic matter retention

Invertebrate production (Young et al. 2008).
Of the above, rates of leaf breakdown and ecosystem metabolism are more
commonly used because they respond to many physical and chemical
stressors and are relatively inexpensive and easy to measure (Young et al.
2008). There are no studies looking at the relationships specifically between
water scarcity and process measures such as benthic metabolism or leaf litter
decomposition.
26
Process responses like leaf breakdown and ecosystem metabolism are
affected by a wide range of factors, both anthropogenic and natural (Gessner
and Chauvet 2002; Young et al. 2008). In some circumstances (general
monitoring) this can be a bonus, adding a range of detectable impairments to
the detection. On the other hand if can be an impediment to specific impact
monitoring because of the problem of partitioning out the effects of the
impairment of interest (Young et al. 2008). For example, leaf litter breakdown
has limited sensitivity and robustness because it responds to multiple factors
that complicate the partitioning of effects from anthropogenic stress and
natural variability (background noise) (Gessner and Chauvet 2002). Rivers at
different altitudes or in different ecoregions also show systematic variation in
naturally occurring nutrient concentrations, hydrological regimes, river
geomorphology and bed substrate, and the nature of the riparian vegetation
(which influences stream temperature via shading) hence water temperature
and ultimately leaf decomposition rates (Young et al. 2008). Litter breakdown
assays can overcome this limitation by being used in an impact monitoring
situation (e.g. downstream–upstream comparisons) (Gessner and Chauvet
2002), or sensitivity can be generally improved statistically be measuring covarying effects such as water temperature, light, or nutrient concentrations in
the field and partitioning them statistically (Young et al. 2008). Similarly, to
account for as much external variability as possible, these methods demand
highly standardised protocols for sampling and measurement (Gessner and
Chauvet 2002). Either way, the need for removal of other factor effects by
sampling or analysis reflects the suitability of the type of indicators for small
scale rather than regional monitoring.
Water scarcity may contribute to higher levels of, say, primary productivity but
reference sites without the water stress would be needed to partition out the
water scarcity effects (as per Figure 3.2a). Responses to hydrological
changes described in Table 4.5.1 are observed, or predicted, from existing
literature. It should be noted that Young et al. (2008) looked at many more
influencing factors than just flow, and all of the listed responses can occur for
a multitude of non-flow related reasons.
27
Table 4.5.1: Responses of biological processes to reduced flow or discharge,
including drought. GPP = primary productivity, ER = ecosystem respiration,
P/R = ratio of photosynthesis to respiration (P/R). All are from Young et al.
(2008).
Flow characteristics
affected
Biological or Ecological Response
Reference
Water Abstraction
(reduced flows)
Changes in Leaf Breakdown?
Increased GPP, P/R
Increased GPP
Young et al. (2008)
Young et al. (2008)
Gessner and Chauvet (2002)
Flow fluctuations
(Floods)
Decrease in GPP, P/R, minor decrease
in ER
Young et al. (2008)
Increased River
Drying
Increased GPP, P/R
Young et al. (2008)
High flows and
Abrasion
Reduced Algal Biomass
Young et al. (2008)
Fellows et al. 2006
28
5
Potential suitable indicators for ecological indicators
of water scarcity from responses cited in the literature
In this section I merely list all of the potential indicators as found in the
literature review and speculate on the data needed to convert the response
into an indicator and issues that may influence its use.
5.1
Macroinvertebrates
Table 5.1: Data requirements and issues identified for generating indicators
for the ecological responses identified in the literature review to a potential
indicator for water scarcity related stress for macroinvertebrates.
Potential indicator
Data needed
Issues
Decreased density
(and biomass)
Time series of density or
historical density estimates
What is a natural density?
There are natural cycles in
density associated with the
nature of our streams anyway
Decreased Richness
Expected richness without stress
Coarse indicator that changes
with many stressors
Decreased Diversity
Expected diversity without stress
Coarse indicator that changes
with many stressors
Changed composition
(incl. Salinity/pollution
tolerance, functional
guild ratios, etc.)
Expected composition without
stress. Long-term reference data
sets documenting natural
variation. Need comparison sites
that are subjected to the same
stressors excepting hydrological
stress.
Need to understand which
Australian taxa are affected
(further research needed).
Responses likely to be site or
habitat specific
Increased Drift
Invertebrate drift estimates and
a reference – historical data or
reference sites
Drift is only occasionally
measured. Confounded when
scarcity turns into no flow.
29
5.2
Fish
Table 5.2: Data requirements and issues for getting from ecological response
from literature review to a potential indicator for water scarcity related stress
for fish.
Potential indicator
Data needed
Population declines
Spatial and temporal records to
(abundance and
account for natural variability
Issues
Also related to other stressors
biomass)
Fish kills
Event based monitoring
Can be caused by other
agents (blackwater, erosion
after bushfires)
Decreased reproduction
Recruitment/demographic data
Spatially confounded, spawn in
including natural/historical values
different areas in different
years?
Changed communities
Spatial and temporal records to
Further research may be
(incl. increased invasives,
account for natural variability
needed to isolate water
and guild changes, IBI
scarcity type responses
scores)
Altered movement
Tagging/tracking data, need for
Probably dependent on a
patterns
historical information to determine
multitude of other factors, such
natural movements
as flow history, barriers, etc.
Reduced species
Spatial and temporal records to
Also related to other stressors
richness (incl. local
account for natural variability
extinctions)
30
5.3
Algae/Plankton
Table 5.3: Data requirements and issues for getting from ecological response
from literature review to a potential indicator for water scarcity related stress
for Algae/Plankton.
Data needed
Potential indicator
Issues
Increased/altered
Reference biomass values that
Very noisy and skewed
algal/phytoplankton
account for cyclical nature of the
distributions making sensitivity
biomass
response
low. Lack of historical data.
Altered benthic
Reference assemblage data with
Extremely difficult to convert
community or
historical natural changes
community type measures to
zooplankton assemblage
indicators of known and
meaningful response
Reduced production
As per biomass
As per biomass
Decreased diatom
Knowledge of which species are
Can respond to other stressors
richness and diversity
salinity tolerant/sensitive
if present
5.4
Miscellaneous biota
Table 5.4: Data requirements and issues for getting from ecological response
from literature review to a potential indicator for water scarcity related stress
for miscellaneous biota.
Potential indicator
Reduced migration
Data needed
Issues
Need historical information to
Probably dependent on a
determine natural movements
multitude of other factors, such
as flow history, barriers, etc.
Altered size class
Historical/reference size class data
distribution
Reduced reproduction
Difficult to convert to
meaningful indicator
Historical reproduction
Possibly a long-term response,
volumes/frequencies, etc
not currently monitored
anyways
Decreased propagule
Historical/reference data
richness
Decreased reproduction
Natural phenomenon in
ephemeral systems
Historical reproduction
Long-term, variable, tedious to
31
(turtles)
volumes/frequencies, etc
determine sensible indicator,
not available everywhere
Hormonal responses
Long-term records of natural
Time consuming and
responses
expensive to collect. Not
known to be sensitive anyways
Increased emigration
5.5
As per migration
As per migration
Waterbirds
Table 5.5: Data requirements and issues for getting from ecological response
from literature review to a potential indicator for water scarcity related stress
for waterbirds.
Response
Data needed
Issues
Increased/Decreased
Waterbird Abundance
Accurate population estimates,
Long-term data with seasonal
fluctuations
Migration, etc. Controls for other
variables that affect abundance?
Site specific and low abundance
doesn’t necessarily mean poor
condition
Decreased Waterbird
Diversity
Expected diversity without stress
Naturally temporally variable,
difficult to determine what is a
significant change
Changed community
composition
Pre-stressor community
composition, measure of natural
variability in community
Very difficult to turn into an indicator.
Natural variability very high
Increased migration
Background migration levels without
water stress
Confounded by conditions
elsewhere? Can’t migrate if not
present anyway.
Change in diet
Expected diet. Frequent sampling.
Quantifying diet? Or just a switch?
Is it water stress causing switch?
Increased/Decreased
waterbird breeding
Long-term breeding records (bird
numbers, species, locations, etc)
What is normal breeding? Is it the
number of species breeding?
Number of individuals breeding?
Decreased Breeding
success
Historical breeding attempts,
fledgling success, nest
abandonment records,
What is natural? Is water stress the
only limiter? Is persistence already
an indicator?
Reduced Breeding
events
Long-term records of breeding
events for specific sites
Is it number of events through a
period of years?
32
5.6
Vegetation
Table 5.1: Data requirements and issues for getting from ecological response
identified in literature review to a potential indicator for water scarcity related
stress for macroinvertebrates.
Response
Data needed
Issues
Increased/Lower species
richness
Long-term records for each
monitoring site/spatial unit
Probably naturally highly variable
between sites – Very difficult to set
reference condition, let alone
decide what is a significant change
unless there is substantial historical
data available
Vegetation encroachment,
Increased/Reduced
Riparian cover
Records of natural distribution for
every site/spatial unit. Including
documented natural changes
without water scarcity
Lots of external interventions also
affecting this. Responds to other
stressors. Requires loads of
surveys and data.
Change in community
composition
Pre-stressor community
composition, measure of natural
variability in community
Very difficult to turn into an
indicator. Natural variability very
high
Increased wood
production/Decreased
forest productivity
Very long-term data sets
Difficult to imagine how enough
precision could be achieved to give
reasonable sensitivity
Terrestrialisation or
desertification
Long-term species distribution data
for each site/spatial unit
Already varies with distance to
channel/water, so may be difficult
to partition natural variation from
water stress responses
Reduced riparian
recruitment
Natural recruitment records
including density and frequency
Fine scale measurements needed.
Difficult o to imagine sensitivity at
large scales
Increased
mortality/reduced growth
rates
Comparison mortality/growth rates
Tedious to measure growth rates,
but otherwise promising. Can dead
veg be easily monitored? Lidar?
Decreased
germination/survival
Comparison germination/survival
rates
Tedious to measure rates, Longterm needed
Depletion of seed banks
Historical/natural data needed for
reference.
Tedious to measure, long turn
around for results
Attrition of perennating
organs
Non-water stress related attrition
rates
Could be confounded by other
stressors anyways
Dieback/Canopy Condition/
Plant Area Index/
Photosynthetic
capacity/Vigour/Biomass
Non-water stress related values,
historical and spatial references
Known to vary naturally temporally
and spatially
Differentiation in dieback
Stand density and age data
Already shown to not work for
Changes in Xylem water
potential
Reference values. Long-term data
Tedious for little reward at large
scales. Clouded by within stand
variation
Loss of vigour/cover of
dominant trees
Long-term cover and species data.
Species data still needs on ground
monitoring at this stage
Reduced number of strata
Long-term data needed
Hard to determine reference and a
sensitive indicator. Probably very
site specific
Abundance and proportion
Reference conditions required,
Tedious to measure
E. camaldulensis
33
perennial species
probably from long-term data
Increased exotic species
richness/abundance
Long-term data with species
identifications and distributions
Tedious to measure. Small scale
Decreased water dispersed
species
Long-term data with species
identifications and distributions
Tedious to measure. Small scale
5.7
Biological processes
As noted by Fellows et al. (2006), the most important feature of a good
indicator of ecosystem health is that it responds to the disturbance gradient of
interest. The nature of ecosystem process measures mean that they respond
to multiple stressors and are therefore not considered in this section.
6
Current Status of Ecological Indicators
Data sets listed in the “Raising National Water Standards project Ecological
Outcomes of Flow Regimes” project (Overton et al. 2009) were investigated
for each group. Furthermore, jurisdictional data sets provided by project 2a
and in previous reviews by Gippel (2007) and Edgar (2008) were interrogated.
Programs or data sets that do not use appropriate sampling strategies cannot
be considered. For example, research has shown that sites chosen by expert
opinion to be ‘representative’ are usually not representative. So, only data
that are from a true probabilistic sampling strategy can be considered. Data
from targeted monitoring programs, such as to monitor specific impacts, are
also not suitable for this purpose.
6.1
In-stream biota
6.1.1 Macroinvertebrates
Macroinvertebrates are widely monitored throughout Australia and generally
follow sound sampling design and rigid defensible sampling protocols. There
are programs in all states and these are well documented by project 2a.
34
It is rather unfortunate that so much of the potential value of
macroinvertebrate data collected in Australia is untapped. Most programs rely
on indicators that have very coarse responses to very coarse stressors. Even
with the amount of investment in these programs, the indicators used have
rarely been exposed to rigorous testing and validation of sensitivity. Indicators
like SIGNAL2 and OE50 Scores are general responses that could not tease
out water scarcity effects from confounding stressors, even if they were
proven to be responsive. For example, the Ausrivas OE50 score was not
related to hydrological indicators in a study looking at downstream of dam
impacts (Marchant and Hehir 2002). Hence neither SIGNAL2 nor AUSRIVAS
OE50 was identified in the literature as potential indicators, which included:

Decreased density (and biomass)

Decreased Richness/Diversity

Changed composition (incl. salinity/pollution tolerance, functional guild
ratios, etc.)

Increased Drift.
The first three of these indicators could readily be calculated from existing
data sets because of the sound sampling strategies used. However, all of
them would also respond to many other stressors than water scarcity and so
have little value to this project. Increased drift is not monitored as part of any
ongoing program at the moment. The use of specific tolerances and
functional guilds is widespread overseas but sparsely used in Australia. If
there is a way forward for bugs in this project it is via this route.
6.1.2 Fish
Fish are monitored in the Sustainable Rivers Audit (MDBA), the whole of
Victoria and NSW using the SRA sampling protocol, and will be sampled in
QLD as part of the SEAP. There is a historical data set for 10 Queensland
catchments using a suitable sampling strategy as part of the Long-Term
Monitoring Program (LTMP), which is paused since 2007. None of the other
states have existing programs that could produce suitable data for unbiased
35
environmental assessment. There were 81 fish data sets from the MDB
recognised in the Ecological Outcomes of Environmental Flows Project
(Overton et al. 2009). Of these, none are better than the above although
some, such as the fishways assessment program, could be worth further
investigation if needed.
Of the potential indicators from (Table 5.2), the following indicators could not
be calculated using existing agency data:

Fish kills

Decreased reproduction (this may be included in a revised SRA fish
protocol within a couple of years)

Altered movement patterns.
The following could be calculated for fish using the existing programs:

Population declines (abundance and biomass)

Changed communities (incl. increased invasives, and guild changes,
IBI scores)

Reduced species richness (incl. local extinctions).
All of these potential indicators would be expected to be very susceptible to
many other stressors as well as water scarcity.
6.1.3 Algae and plankton
Some state water quality programs include variables like Chlorophyll-a and/or
algae counts and these are at various scales of spatial replication. There are
6 sites measured annually for algae counts in the Murray river by the EPA in
South Australia, and up to 120 sites measured for algal counts twice yearly in
the south East Queensland EHMP (Gippel 2007). It is presumed that there
are also many regional monitoring programs carried out by councils,
particularly where the resource has a high public use component. Only the
36
EHMP program collects data in a way that allows for meaningful scientific
analysis on a monitoring program.
6.1.4 Miscellaneous
As the name of this component suggests, there are only small scale and adhoc monitoring using the miscellaneous taxa.
6.2
Waterbirds
Waterbirds are not included in any of the existing state or federal monitoring
programs (Edgar 2008; Gippel 2007), nor are they listed in the Framework for
Comparative Assessment of the Ecological Condition of Australian Rivers and
Wetlands (Norris et al. 2007a). They are listed as of potential future value
“when appropriate data become available” in the Assessment of River and
Wetland Health: Potential Comparative Indices (Norris et al. 2007b).
There are 89 bird related data sets listed in the Ecological Outcomes of Flow
Regimes metadata spreadsheet. The majority are of limited spatial extent and
are usually specific to a particular wetland or floodplain. Many have temporal
replication, however, and therefore offer a good resource for further
investigation. The only Australia-wide data sets are held by Birds Australia
and are of limited value for monitoring because of inconsistencies in sampling
protocols.
Surveys of waterbirds with a recent temporal component generally do not
include breeding observations. There are many data sets listed that record
breeding observations, yet the majority of these do so only in an opportunistic
way, i.e. only recording when breeding was noticed, and sampling effort is
therefore inconsistent and incomparable. Surveys that record when birds do
breed are recording when a system is not in stress, not when a system is in
stress. This method can only be relevant when all systems are surveyed for
breeding and using a consistent sampling method.
There were five datasets that contain long-term information with a scientifically
robust sampling design that remain contemporarily relevant (Table 6.2.1). Two
37
of these data sets are in the Coorong, two are across NSW or the MDB and
one is the Narran Lakes system within the MDB (Table 6.2.1).
Table 6.2.1: Contemporarily relevant waterbird data sets identified from the
ecological response to flows project metadatabase (Overton et al. 2009) that
could have value to the ecological indicators of water scarcity project.
Data set
Frequency
Area covered
Dates
Notes
Coorong waterbirds
Annual
(January)
Coorong
2000 - present
Adult counts,
Bird food
resources
Eastern Australia
Waterbird Survey
Annual
(October)
NSW
1983-present
Adult counts
Eastern Australia
Aerial Waterbird
Survey
Annual
(October
/November)
MDB = NSW,
QLD, VIC, SA,
ACT
1983-present
Adult counts,
(species or
functional group),
Breeding
Wader Surveys
?Annual
Coorong and
SE coastal
lakes, SA
2000-2008
Shorebird counts
Waterbird surveys
of Narran Lakes
Annual
Narran Lakes,
NSW, Lower
Balonne, QLD
1970’s present
Counts, Breeding,
Habitat modelling
The Narran Lakes data set is freely available, the Wader Surveys in Coastal
SA belong to a jurisdiction (DEH) and the others are held by Academics.
MDBA Icon Site Monitoring Program
The MDB Icon site monitoring program has benchmarks for particular sites,
such as minimum of three breeding events in 10 years (MDBC 2008). Further
enquiry suggests that these ‘rules’ were arbitrarily probably put forward by
local action groups prior to the ministerial approval of the TLM project in 2002
and are subject to review (Swiripek 2010).
38
6.3
Vegetation
For most of Australia there are no ongoing systematic monitoring programs for
riparian or floodplain vegetation condition. There will be vegetation surveys
as part of the SRA and ISC (Victorian Index of Stream Condition) in the near
future. There have been baseline surveys of vegetation in the Murray Darling
Basin Authority TLM Icon sites and most of the Murray channel in South
Australia. The Living Murray program has identified remote sensing as a
valuable tool for monitoring and has implemented a “Mapping Stand
Condition” project in 2008. The first report from this GIS based project should
be available within a couple of months (J Swirepik, pers. Comm.).
Of all the possible indicators given for vegetation responses to water scarcity,
most require small scale on ground measurements, meaning extremely
tedious numbers of measurements. This can’t be avoided by taking only a
few samples at a lot of sites because there is so much within stand variability.
However, it is so simple to take whole of stand assessments of health under
the umbrella indicator of Dieback/Canopy Condition/ Plant Area Index/
Photosynthetic capacity/Vigour/Biomass using remote sensing.
Remotely sensed data for parts of Australia has been acquired continuously
since 1972 and since July 1981 for all of Australia daily (McVicar et al. 2003)
and a brief description of the available data is given in Table 6.4. Access to
some of these data sets would give very good spatial and temporal coverage,
allowing for quite good determinations of regions suffering water scarcity.
39
Table 6.3: Technical specifications for major historical, current and future key
terrestrial satellite systems as of September 18, 2003 (source: McVicar et al.
2003).
The NOAA satellite data are used by the Bureau of Meteorology to report the
NDVI for all of Australia every month using NOAA remote sensed data and 1.1
km pixels (http://www.bom.gov.au/jsp/awap/ndvi/index.jsp). This includes
reporting NDVI anomalies, which indicates whether the vegetation greenness
at a particular location is typical for a certain time of year or whether the
vegetation is more or less green
(http://www.bom.gov.au/climate/austmaps/about-ndvi-maps.shtml). At the
moment anyone can access images, but the proposal is that end users should
be able to access the layers themselves (King 2003).
The MODIS data (LPDAAC 2010) are now freely available for the whole of
Australia in grabs every 16 days since 2000 at 250m resolution. The MODIS
data can be accessed by anyone and requires no pre-processing as EVI and
NDVI are already calculated (Paget and King 2008). MODIS is the
recommended way forward for this project and is further discussed in the next
section.
40
6.4
Biological Processes
Whilst a more complete assessment of river health would include functional
indicators, (Young et al. 2008), direct measurements of ecosystem processes
are often neglected in river health assessment programs (Bunn and Davies
2000; Fellows et al. 2006). The only functional metric that is used routinely in
water-quality assessment is biochemical oxygen (O2) demand (BOD) and is
most suited to sites influenced by wastewater discharges (Young et al. 2008).
7
Identification of indicators feasible to use, based on
criteria including whether adequate data exist to
populate the indicator.
7.1
Introduction
Most of the available data sets have limited spatial extent and therefore
different ecological indicators may be used in different parts of Australia. This
is sensible as different ecosystems have different key components and the
nature of what is being measured already probably reflects what is important
in a region anyway. The issue of scaling the indicator to the scale of reporting
is addressed using examples in section 8.4.
7.2
In-stream Biota
7.2.1 Macroinvertebrates
There are no indicators feasible for macroinvertebrates to indicate water
scarcity (alone) at this stage. All available indicators, or indicators that could
be calculated form existing programs, are general health indicators and
therefore susceptible to confounding. There is some potential for
development of specific water scarcity indicators using existing data but this
will require considerable future research (see Chapter 8).
41
7.2.2 Fish
There are no indicators feasible for fish to indicate water scarcity (alone) at
this stage. All available indicators or indicators that could be calculated from
existing programs are general health indicators and therefore susceptible to
confounding.
7.2.3 Algae and plankton
There are no indicators feasible for algae and plankton to indicate water
scarcity (alone) at this stage. Very few data are available and only the EHMP
data set offers enough rigour in its design to allow further research into
potential indicator development if desired. This region however has a
subtropical climate and the findings may therefore not be totally relevant to the
rest of Australia.
7.2.4 Miscellaneous
There are no indicators feasible for the miscellaneous taxa to indicate water
scarcity (alone) at this stage. All indicators that could be developed would
require considerable investment into further data collection prior to
development.
7.3
Waterbirds
A proposal by Kingsford and Lee (2007) to the then Murray Darling Basin
Commission suggested birds could be included as indicators of floodplain the
health. The report suggested species richness, abundance and breeding as
potential indicators. There was no documentation of indicator calculations,
indicator variability, and indicator responsiveness or indicator demonstration.
Hence the use of waterbirds as indicators of ecosystem health has a very long
way to go, let alone the narrowing down of the responses to water scarcity
when there are multiple stressors present. This taxa faces additional complex
hurdles associated with spatial and temporal variability.
On the other hand, these taxa may be well suited to event based monitoring.
When an inundation event that triggers breeding is recorded, the success of
breeding may be an indication of stress. That is, the number of breeding
pairs, fledgling survival, nest stranding, nest desertion, etc, are all potential
42
indicators. However it is a long way from a potential indicator to an actual
indicator. For every proposed indicator a series of questions need to be
answered. What proportion of fledgling success is natural? What proportion
is indicating water related stress? What is the variability of this indicator?
How large does a difference in proportions need to be before I can statistically
detect the effect? What is the responsiveness of this indicator? How can we
separate water related stress from other stressors like chemical pollution and
predation? Does setting up this indicator require an additional cost to existing
programs? Are there sufficient data to set up a demonstration of this
indicator?
There are no feasible indicators of water related stress using waterbird data
from existing programs.
7.4
Vegetation
On-ground data collection for vegetation is not an option because of the
tediousness of it and the problem of upscaling it to a meaningful indicator.
The Victorian ISC has revised their streamside zone component and may be
implementing statewide monitoring of the riparian vegetation using remote
sensing. This will be worth following up on.
At the moment, remote sensing and NDVI in particular appeals, and should be
followed up.
7.5
Biological Processes
There are major problems from indicators being confounded because of
responses to multiple stressors that rules processes out at this stage.
43
8
Options and recommendations for the way forward
8.1
Introduction
In this section I briefly list what would be required to go forward with the
indicators, with the most potential from each group. I take the one indicator
with the most potential, NDVI, through a detailed example of how the next
step may progress.
8.2
In-stream Biota
8.2.1 Macroinvertebrates
At the moment the analyses for river health type programs uses community
level indicators like OE Score and SIGNAL score that have coarse responses
to multiple stressors. The only way forward for macroinvertebrates as
indicators of water scarcity related stress in Australia using currently available
data sets requires further research investment. This would require extensive
review of current data sets in conjunction with hydrological data, then further
experimentation to determine which individual taxa or functional groups are
suitable indicators. This would be a high-risk investment because it is
probable that these groups, if they exist at all, are already affected or have
limited distributions, and even then they may also be open to confounding
from other stressors. A start would be to interrogate some existing
macroinvertebrate data that has associated hydrological data. The SRA data
at the valley process zone level appeals intuitively but would be expected to
suffer from the coarseness of the macroinvertebrate measures used.
This exploratory analysis was performed for the 2007 SRA data using a
Spearman’s rank correlation coefficient of the 3 macroinvertebrate submetrics, and overall River Health Macroinvertebrate (RHM) metric against the
five hydrology sub-metrics and the total hydrology (SRHI) metric (Table 8.1).
The signal sub-metric was somewhat more related to the hydrology than the
other metrics, but none were statistically significant at the 0.05 level.
44
Table 8.1: Spearman’s correlation coefficients for SRA macroinvertebrate
metrics and hydrological metrics for 23 zones sampled in implementation
period 3 (2007). OE = Ausrivas OE50, S = Species Richness, RHM = SRA
Macroinvertebrate health score, SRHIvar = Hydrological variability submetric,
hf = High Flows, ls= low spells, lz= duration of zero flows, vol= Volume.
SRHIvar
SRHIhf
SRHIs
SRHIlz
SRHIvol
SRHI
OE
0.19
0.09
0.12
0.20
0.01
0.11
S
0.12
0.17
-0.09
-0.13
0.20
-0.01
SignaL2
0.38
0.41
0.30
0.34
0.34
0.38
RHM
0.26
0.30
0.07
0.05
0.26
0.16
In other words, to determine likely indicators will require extensive
hydrological knowledge, and if that is available then why use the bugs? The
macroinvertebrate indicators (this applies to all ecological indicators) would
only be of value in regions where hydrological data wasn’t available. A
simpler alternative option is discussed in Chapter 9.
The response of individual taxa or functional groups may offer better value as
indicators and if this theme were to progress, the next step would be to
interrogate the relationships at that level. This would require considerable
effort (and expense) for a potentially weak response and is therefore
described as a low priority. A related type of analyses at that finer taxonomic
scale has recently been looked at in NSW for the long-term relationships with
temperature (climate change) by Bruce Chessman (Chessman 2009). A
major difference is that water scarcity is probably not a long-term gradual
effect as climate change was treated for that paper.
Recommended way forward:- Drop macroinvertebrates as a potential indicator
of water related stress in Australian ecosystems.
8.2.2 Fish
The best way forward for fish would be to perform research to attempt to
isolate indicators that are water scarcity specific. This is intuitively a waste of
resources. Fish function in ecosystems is very complex and their response to
45
water scarcity in amongst so many other influencing environmental factors
could be best described as unpredictable. Like waterbirds, absence doesn’t
mean a lot and besides there are no sampling programs that detect every fish
every time, so probability of absence needs further work. Fish monitoring is
not performed in a representative way outside of the MDB (plus the remainder
of Victoria and NSW), therefore it hardly seems worth investing more
resources in this group for this project.
I interrogated the SRA data at the Valley process level. This involved testing
for relationships between the hydrology (FSR) data and the individual fish
theme sub-metrics. The SRA themes are set up to report on different aspects
of the ecosystem, so correlations between the fish and hydrological scores for
each catchment are unlikely, however for fish there are 13 sub-metrics
calculated for each zone, which are then combined into nativeness,
diagnostics and expectedness, which are then combined into a fish health
metric. This analysis was not expected to show significant relationships, as a
study had already shown the lack of response of fish indicators to hydrological
variables in one part of the MDB (Growns 2008).
Of the five FSR sub-metrics used in the SRA, the one most likely to surrogate
for water scarcity is SRHIvol, which reflects the total volume of water available
in the system during the past 5 years, and compares this to a natural value. A
high score reflects the region has little modification from natural and a low
score means the total volume is significantly less than natural. The highest
relationship of any of the SRA fish submetrics to SRHIvol was a rank
correlation of -0.34 (Table 8.2). This suggests very weak relationships and
that factors other than hydrology play a major role in the SRA fish submetrics.
Graph of the relationships confirm that the fish scores are quite independent
of the total volume indicator. The example graph I include is the one with the
strongest relationship, the Observed to Expected (OE) proportion of
historically occurring native fish in the region (Figure 8.2). It clearly
demonstrates a weak relationship exists but high or low OE scores can be
associated with high or low hydrology scores (Figure 8.2).
46
Table 8.2: Spearman’s correlation coefficients for SRA fish theme submetrics
and hydrological total volume metric for 23 zones sampled in implementation
period 3 (2007). Negative values mean that when total volume is closer to
natural the fish indicator performs poorer.
Indicator
Correlation with
FSR Volume
indicator
-0.19
-0.34
-0.03
-0.07
0.34
proportion native abundance
-0.24
proportion native species
proportion native biomass
proportion macrocarnivores
proportion mega carnivores
total abundance
fish with abnormalities
-0.25
-0.06
0.13
-0.15
-0.11
0.22
zone weighted caught to
predicted ratio native species
0.02
Fish
total species richness
observed to expected ratio
pelagic species richness
benthic species richness
intolerant species richness
Figure 8.2: Relationship between SRA hydrology total volume metric and
SRA Fish OE score at the valley zone for 2007 (IP3). Arrow and shades
merely represent arbitrary cut off for healthy OE scores.
47
Recommended way forward:- Drop fish as a potential indicator of water
related stress in Australian ecosystems.
8.2.3 Algae and plankton
There is no obvious way forward.
8.2.4 Miscellaneous
There is no obvious way forward.
8.3
Waterbirds
Existing indicators do not exist but there are some data sets available, as well
as the potential to develop event-based indicators. Waterbird data, especially
counts, are highly variable spatially and temporally and therefore are
extremely unlikely to be sensitive to detecting anything but very coarse
changes. Waterbird indicators also have limited relevance in many parts of
Australia and in many years. Because there is a high likelihood of getting
indicators with very low sensitivity, any further research into using waterbirds
for this project are classified as quite risky.
An inexpensive way forward may be to fund some small projects looking at
developing event-based indicators using existing data sets. This is seen as a
low priority. A more expensive way forward would be to fund some projects
looking at developing annual indicators using existing data sets, with a view to
eventually become a partner supporting ongoing annual waterbird surveys.
This is seen as a very low priority.
Recommended way forward:- Drop waterbirds as a potential indicator of
water related stress in Australian ecosystems. Use existing waterbird data to
set hydrological threshold/trigger values rather and monitor hydrology and
hydraulics. See alternative approach (Chapter 9).
8.4
Vegetation
The general health of the vegetation, as measured by NDVI using remote
sensing, appeals as a sensible way forward. Other factors contribute to
changes in NDVI, such as herbivory and seasonal variations, but the use of
48
reference sites and occasional ground-truthing would be simple. The data
have an archived and accessible history and therefore could be used in
conjunction with historical soil moisture/hydrological records for calibration.
MODIS (LPDAAC 2010) derived data is freely available (Paget and King
2008) and a suggested way forward would be to interrogate these data to look
for responsiveness and sensitivity of NDVI to water related stress.
An issue is the sampling unit and reporting unit. Currently all of Australia is
sampled, but it seems sensible to only sample and report on riparian and
floodplain vegetation. This would require using reporting GIS layers to
excludemajor chunks of Australia from the reporting. It would also allow
reporting at any scale desired, such as specific wetlands or rivers or SWMA,
as defined for the FARWH. A sensible approach may be to relate archived
images against archived hydrological data including floods etc. Then calibrate
and test the functioning of the images against known hydrological stresses
and then apply the findings across all SWMAs or chosen reporting units for
the chosen reporting period.
It is important to have spatial reference regions for comparisons. That is,
some regions that are known not to be stressed by water scarcity should be
used to monitor natural fluctuations in NDVI.
8.5
The way forward using NDVI
This section is written in anticipation of the NDVI being trialled as a way
forward, but could apply in general to any chosen indicator.
Source of the data
Whether it’s a biological indicator or NDVI, there are several data sources
available and these should be compared to determine the best individual
source, remembering that multiple sources may be possible. For example,
some suggested criteria for sourcing data for the NDVI indicator are given in
49
Table 8.5.1. For NDVI, MODIS is clearly the preferred supplier of data. All the
information required to use the MODIS NDVI data for Australia is contained in
the paper by Paget and King (2008) and is included at the end of Appendix 2.
Table 8.5.1: Example of criteria to determine best possible sources of data for
population of ecological indicator of water scarcity related stress. *Each
source is rated Low Medium or High for these criteria. ? means further
research such as a pilot study is required.
NOAA
Landsat
MODIS
Yes
Yes
Yes
Yes
No
Yes
At what spatial scale is the measurement made?
1km
?100m
250m
At what temporal scale is the measurement
made?
daily
?
16 days
?
?
?
M
L
H
H
H
H
?
?
H
Availability
Are the data available for the temporal and
spatial components required (say 2000 – 2008)
Future relevance
Are the data going to be
available/relevant/comparable with future
sampling/monitoring?
Resolution
Sensitivity
Are these data able to demonstrate a change in
response to water scarcity at the reporting scales
required?
Ease of use*
Is it relatively simple for the data to be analysed
and interpreted?
Accessability*
Is it relatively easy to access the data?
Cost
What is the cost of obtaining the data?
(H=low cost)
50
Spatial considerations
Spatial scale is probably the most important consideration needed for the
entire project. There are two aspects: scale of measurement and scale of
reporting. NDVI again appeals here because it is measured at 250m pixels
and can be scaled up using averages to any scale, even the entire country or
entire MDB (Figure 8.3).
Figure 8.3: Example NDVI time series for the entire MDB (Schmidt et al.
2005).
Remote sensing of vegetation has specific peculiarities of scale to consider.
These include whether to extract just flood plain data, or just the riparian zone
data? The whole of catchment data (as in Figure 8.3) will return averages that
are heavily influenced by agriculture and whilst these may add some value I
think just riparian/floodplain data would better reflect water scarcity ecological
impacts. I believe there are GIS layers of riparian zones available, possibly
just for the MDB and or Victoria as used in the SRA and ISC programs
respectively. Access to these layers would substantially reduce the cost of
any pilot study.
51
The chosen spatial unit for reporting should probably reflect the scale at which
impairment is expected to be detectable. The reporting scale can be flexible
and may reflect set areas, say 10 km2 grids, catchments, ecological regions,
Surface Water Management Areas (SWMA), or sites of particular interest (e.g.
a RAMSAR wetland). The users of the end product will decide on the scales
of reporting to be used. The response of NDVI should be looked at using
average values but could also include comparisons of shapes of the
distribution within each spatial reporting unit.
Temporal considerations
The dates of the assessment period need to be determined. The data will
probably need to be seasonally adjusted (NDVI definitely does) to make
comparisons meaningful. This has consequences for the comparison to be
made. For example, should one be comparing long-term trend or trajectory or
just be looking for a step or drop in the NDVI anomaly. It would probably be
sensible to look for a gradual decrease in the NDVI anomaly in the
assessment area relative to the reference area(s). Another thought, however,
is how to treat the anomaly temporally. It could be calculated on the 16 day
cycles, monthly, or quarterly. A pilot study looking at a known stressed region
should look at the effects of using different periods to calculate moving
average of the NDVI anomaly, and see at what point the stress could be
picked up.
Reference considerations
Are there data available for suitable non-stressed regions to act as
references? The references could be based on similar hydrological zones, or
similar ecological zones. It is also possible to simply analyse all regions in,
say, NSW at the same time and merely rank or order them in terms of
apparent NDVI anomalies for the reporting period.
52
A suggested method
This is only a suggestion; there are many ways that an indicator may be used.

Choose spatial and temporal reporting scales. e.g. The Lower Bidgee
floodplain between 2005 and 2009

Choose one or more appropriate reference locations for the same
period that are known not to be water stressed. Appropriate may mean
subject to similar non-water scarcity stressors, such as latitude or land
use, or it may refer to starting NDVI. Having similar starting NDVI is not
essential but may simplify interpretation. Say, a coastal catchment that
has not been drought declared during the sampling period.

Calculate say monthly NDVI values for each region for the sampling
period

Seasonally adjust each series of data (using long-term data, not just
the sampling period)1

Calculate NDVI anomalies for each series during the sampling period

Perform an intervention analysis type approach to compare the NDVI
anomaly series.
Before using NDVI
It’s all well and good to recommend using NDVI, however before any indicator
is used, its responsiveness and sensitivity must be known. Therefore if it were
This is easily done for NDVI data, e.g: Verbesselt J., Hyndman R., Newnham G. & Culvenor
D. (2010) Detecting trend and seasonal changes in satellite image time series Remote
Sensing of Environment, 114: 106-15.
1
53
desirable to look further into using NDVI as a potential indicator some
validation trials should be run.
These trials would involve collating information about regions that have been
known to and not to be stressed during the 10 years that MODIS data are
available for. The ability of the NDVI anomaly (or the EVI anomaly) to detect
changes in those regions could be trialled in and the results used to inform
future data collection and analysis. The US EPA Research strategy for the
Environmental Monitoring and Assessment Program (McDonald et al. 2002)
should be consulted throughout the trial process.
9
Alternative view
At the end of the day the same question arises for any indicator or theme.
Why use the ecological indicator if the hydrological one(s) are available? In
other words, the only value that an ecological indicator could add is in a
situation where there aren’t appropriate hydrological models, or if it is desired
to determine measures of impact of stress rather than the level of stress. For
example, it may be that a 10% alteration in flow severely degrades one
ecosystem but a 30% alteration barely affects another. However, all the
ecological indicators readily available respond to many other stressors as
well, hence general ecological condition and hydrological stress are not
always directly related.
If it is the alteration to flow that is of primary concern then hydrological models
will suffice; if it is impact then the ecological indicators may be adequate. On
top of all this, it must be remembered that without further calibration, other
stressors may affect ecological indicators.
This project sets out to find ecological indicators by reviewing the literature
and determining trigger points or values for an ecological response to occur.
The condition of the taxon below these trigger values is used to set a
54
reference value against which to compare potentially stressed aquatic
ecosystems. This requires monitoring the ecosystem in depth (pun intended!).
An alternative approach could be to monitor the trigger values. In other words
if the literature review has revealed that water bird species A in X region need
a flood event of Y Megalitres at least once in every Z years to reproduce and
persist in the area: Why monitor the birds? It is a huge cost and the
indicators are not yet shown to be sensitive and their responsiveness is not
known. We can model flood events practically anywhere in the country these
days for comparatively little cost. If water stress alone is our concern then we
could very easily monitor the hydrology/flood events to indicate whether
region X has had enough water for a healthy ecosystem. If the birds don’t
breed then that is probably of interest to someone somewhere, as it could
indicate another stressor in the system, but water scarcity is not the issue.
10
Conclusion
Of the tens of potential indicators identified in this paper, all are susceptible to
confounding. In other words, factors other than water scarcity can influence
the ecological response. Water scarcity can be measured directly using
hydrological data and therefore should be used where available. If there are
any regions where hydrological data are not available then NDVI as calculated
from NOAA or MODIS satellite data appeal as an appropriate ecological
indicator. Further research needs to be done to evaluate its response in
different regions and at different scales but the data are archived and freely
available to do this. Even NDVI, however, cannot be used in every corner of
Australia and alternative measures for each region may need to be identified.
The main recommendation from this paper is to not use ecological indicators
to identify water scarcity related stressed ecosystems. Ecological indicators
may be used to assess which stressed systems are in worse condition than
others if required.
55
Appendix 1 Water birds literature review
A1.1 Literature Review of Waterbird Ecology relevant to water
use and water scarcity
Waterbirds depend on wetlands
Waterbirds depend on wetlands for survival, reproduction and recruitment
(Bellio et al. 2009). When wetlands disappear for whatever reasons, waterbird
numbers decline. For example, waterbird numbers estimated during annual
aerial surveys collapsed by 90% when the Lowbidgee wetland was destroyed
by development of the floodplain for an irrigation area (Kingsford and Thomas
2004). On the other hand the response is not always so obvious. Hydrological
data indicate that river management from the Hume weir began impacting on
waterbird breeding areas in the mid-1950s, but ornithological records reveal
that the natural system resisted change for 20 years but changed after about
1975 (Lesley 2001).
River and floodplain management
River regulation and the disruption of the seasonal flood regime along a river
often spells disaster for waterbirds (Nilsson and Dynesius 1994). A reduction
in water flow in to wetlands results in reduced breeding events for colonial
nesting bird species (Hughes 2003; Kingsford and Johnson 1998) and
reduced breeding success for wading birds in general (Russell et al. 2002).
Water alone is not enough to guarantee success as waterbird breeding can be
directly linked to other factors like variability in flow (Briggs et al. 1997; Lesley
2001). Perhaps the most critical factor likely to affect the long-term stability of
waterbird persistence is the interval between breeding episodes. This factor is
of real concern during extended drought periods and managed forest flood
events (Lesley 2001). For example, in the Barmah-Milewa forest, breeding
numbers of egrets have not exceeded 330 pairs since the mid-1970s yet
these species were recorded nesting in ‘thousands’ or in the ‘largest known
egret rookery in Victoria’ in 1940 and 1961 respectively (Lesley 2001).
56
Whilst birds may occur on almost any water body, water following the natural
flood regime will not support colonial water birds in the long term without
suitable nesting habitat (Kingsford and Johnson 1998) and safe roosting sites
(Paillisson et al. 2002). For example, altricial waterbirds (the young are cared
for by the adults) nest on branches over open water in trees at the edge of
River Red Gum areas or in dead River Red Gums (Briggs et al. 1997). The
associations of breeding Darters, Great Cormorants and Pacific Herons with
wetlands containing large areas of dead River Red Gum reflected this
preference (Briggs et al. 1997).
Wetlands provide a food source for waterbirds
Wetlands provide an important source of food whether the birds eat plant
material, fish or macroinvertebrates and all these food sources can be linked
to flow. Some waterbird species are herbivorous and many of their
distributions are related to wetland plant communities (Desgranges et al.
2006). Other species specialise in fish (piscivores) and their distributions are
less related to fish community types but to abundance of appropriate sized
fish. For some other waterbird species (generally waders), presence can be
determined by aquatic macroinvertebrates abundance (Briggs et al. 1997).
Within wetlands, water depth and fluctuations influence macrophyte and
macroinvertebrate distributions - which ultimately determines waterbird
communities (Bellio et al. 2009). Litter inputs, organic matter decay, the
timing and level of nutrient releases and increases in invertebrate populations
are linked to periods of submergence and desiccation associated with flow
peaks and troughs (Lesley 2001). Fish population numbers follow the
increases in plant and macroinvertebrate populations (Crome 1988) and fisheating bird numbers follow the fish population numbers (Kingsford and Auld
2005).
Water birds use wetlands for breeding
For successful breeding to occur, suitable nest sites, cover, and food must be
available over a specific period of time (Kushlan 1993). Different bird species
have different nest types (ground, floating, attached, or above water)
(Desgranges et al. 2006) but reduced flows to wetlands adversely affects
breeding habitat and subsequent breeding of waterbirds (Briggs et al. 1997).
57
Different species respond differently to different flood types, for example
breeding waders need small scale floods (Eglington et al. 2008). Differences
between species in breeding and recruitment may offer additional possibilities
for measuring floodplain and river health for a catchment (Kingsford and Lee
2007).
When do Water birds use wetlands for breeding
There are many different potential cues for waterbird breeding to occur but
generally when food resources reach sufficient abundance and waterbirds
gain enough weight they will breed (Kingsford et al. 1999). This general rule
applies across different regions and other cues. For example, breeding of
Australian waterbirds coincides with food abundance in the southern spring,
the wet season in the tropics and following floods inland (Kingsford and
Norman 2002). Most breeding in south-Western Australia occurs in spring
and rainfall was the most important proximate cue stimulating gonadal
recrudescence (Halse and Jaensch 1989).
Factors affecting the success of the breeding event
In permanent or semi permanent wetlands, the reproductive success of
waterbirds may depend on water level fluctuations to make food available
during nesting (Kushlan 1993). In more ephemeral wetlands a flood event
that triggers a breeding event does not guarantee the breeding will be
successful. The response of the birds to the flood event are not instantaneous
and low numbers of waterbirds usually occur after flooding, when habitat is
extensive and waterbird numbers have not increased by immigration or
breeding (Kingsford and Norman 2002). Waterbird abundance is usually at its
highest during the drying phases of wetlands (Kingsford et al. 1999), for
example numbers were greatest on Lake Eyre in December 1990 after the
flood had reached the lake in August (Kingsford et al. 1999).The duration (and
by association the rate of fall) of the water determines the reproductive
performance of the colony (Lesley 2001).
Changes in wetland area affects waterbirds
In general the total number of birds in a wetland system is related to the total
area of the wetland available as in general a larger wetland area means a
58
larger potential habitat range. Broadly speaking, water availability is related to
wetland area and decreased wetland area equals decreased wader diversity
(Green et al. 2002). Waterbirds are often distributed around the edge of
wetlands where water is relatively shallow (Kingsford et al. 1999) and larger
areas of shallow water therefore means larger total population size.
Yet species respond differently to the hydrology of the system. For example,
fluctuating water levels suit small to medium shorebirds that forage in < 30 cm
water (Bellio et al. 2009) but any changes in water level can have a negative
impact on breeding success of many wetland bird species (Desgranges et al.
2006).
Reduced flow equals reduced wetland areas
We know that flow is positively related to wetland area. (Kingsford and Auld
2005). The loss of total wetland area and subsequent habitat loss through
draining of wetlands, regulation of rivers, diversion of water for irrigation and
floodplain development are major threats to waterbirds (Kingsford and
Norman 2002). This applies even when the wetland area may be the same or
similar, but the hydrology of the forest has changed considerably. For
example, we know that the Barmah-Millewa forest supported large numbers of
colonially-nesting waterbirds prior to the commissioning of the Hume
Reservoir (Lesley 2001). River management in the Barmah Milewa forest has
reduced the frequency of the natural flooding regime which has resulted in
80% fewer successful breeding episodes (Lesley 2001). Reduced water
however can result in large concentrations of waterbirds either in situ or when
birds are forced to move and concentrate on the remaining, more permanent
wetlands (Kingsford and Norman 2002). Other effects from hydrological
modifications at the large scale is the changes includes the relative
representation of wetland types and wetland habitats (Robledano et al. 2009).
Changes in water management often means reduced flooding and flooddependent vegetation will die through lack of water and increased impacts
from salinisation (Kingsford and Thomas 2004). These types of changes could
conceivably favour piscivorous birds over herbivorous birds.
59
Flows and floods affect colony size
For Australian waterbirds, food abundance usually coincides with flooding
patterns or rainfall, which produce wetland habitats (Chambers 2008;
Kingsford and Norman 2002). Again, the size of the flood event has different
repercussions for different species.
Before they respond by breeding, colonial waterbirds usually require the flood
to reach a certain threshold (Kingsford and Auld 2005). This hydrological
threshold can be related to flood high, timing of flood peaks, and duration of
flooding (Lesley 2001).
Naturally, successful breeding events contribute to overall colony size, hence
it is documented that total colony size (number of nests) and sizes of six
nesting Ciconiidae (Intermediate Egret, Rufous Night Heron, Glossy Ibis,
Straw-necked Ibis, Australian White Ibis and Royal Spoonbill) colonies were
significantly related to annual flows in the Macquarie Marshes in 1978, and
1986 – 1996 (Kingsford and Johnson 1998). Whilst the total volume of flow in
a year was a good indicator of the extent of waterbird breeding in the
Macquarie Marshes (Kingsford and Lee 2007) for most colonial waterbirds
the relationship was also very strong for flow in just the three months before
breeding (Kingsford and Auld 2005). Hence the timing of the flow is important
and pulses rather than annual volumes also play a role. For example, in order
to induce breeding in the Barmah-Millewa Forest, the pulse maximum had to
be a minimum size and needed to occur in September and/or October (rarely
November) (Lesley 2001).
Habitat quality is related to hydrology
The presence of safe roosting or breeding sites are mainly governed by the
hydrological and disturbance conditions in wetlands (Paillisson et al. 2002).
Reduction in water flow to wetlands reduces both semipermanent and
ephemeral wetland vegetation (Hughes 2003). Changes in hydrological
conditions lead to habitat changes in wetlands that can be related to changes
in the ranges of colonial waterbirds (Kushlan 1993) and even modify the
60
surrounding bird community towards a more heterogeneous assemblage
including scrubland and palustrine species (Robledano et al. 2009).
With a reduction in flooded areas, there will be less feeding habitat for
waterbirds and fewer breeding opportunities (Kingsford et al. 1999)
and at the edge of open water, fewer trees that provide their nest sites (Briggs
& Thornton 1995).
Foraging success is the key to breeding
Even on some semi-permanent Australian wetlands that contain cormorants
most of the time, there is great variability in abundance and this presumably
reflects food availability (Kingsford and Norman 2002) and colonies are less
likely to breed successfully without sufficient resources. Prey availability after
breeding has commenced may be the critical factor and it is known to be
closely related to the growth of colonial waterbird chicks (Kushlan 1993). So,
whilst waterbirds obviously need water for persistence, and habitat for nesting,
foraging success may be the key to breeding success (Paillisson et al. 2002;
Russell et al. 2002). The argument for wading waterbirds may be summarized
as follows:

Breeding activities are energetically demanding.

Wading birds mainly consume aquatic vertebrates

The efficiency with which these can be acquired depends in large part
on the water conditions.

Poor foraging efficiency leads to late initiation of nesting, high mortality
of offspring, abandonment of nests, or any combination of the above
(Russell et al. 2002).
The principle applies to herbivores as well, as about 200 Black Swans died
when aquatic macrophytes declined at Lake Altibouka (Kingsford and Norman
2002) whilst in the Netherlands the abundance and duration of stay of water
birds are closely associated with the presence of Chara. (Noordhuis et al.
2002). Nesting of Australian Pelicans on Lake Wyara in south-western
Queensland coincided with high levels of fish populations after a flood event
61
while Black Swans nested later as the water cleared and aquatic macrophytes
became abundant (Kingsford and Norman 2002).
Foraging success for survival (not breeding)
Waterbird communities are ultimately determined by the distribution of the
prey of the birds (Bellio et al. 2009). Similarly, the composition and abundance
of waterbird communities on wetlands can reflect the availability of food in the
region generally. For example herbivorous species can be more common in
rice-growing areas and fish-eating birds can be abundant around fish farms
(Kingsford and Norman 2002). Even temporarily flooded grasslands (1100
ha) can constitute a very important feeding area by supporting large flocks of
waterbird species irrespective of breeding (Paillisson et al. 2002).
Drying of wetlands
Whilst flooding can increase habitat and post-flood drying plays a very
important role in concentrating prey in drying wetlands (Dorfman et al. 2001),
the importance of a preceding dry phase is still not well understood in
Australia and the drying up of water bodies is either ignored or regarded as
detrimental to waterbirds (Crome 1988). The drying and filling of temporary
wetlands contributes to habitat variability, which can be a key component of
the success of some species, such as Black-necked Stork (Dorfman et al.
2001). After extensive inland flooding there are inevitable dry periods that will
eventually force waterbirds to move (Kingsford and Norman 2002). But this
drying phase before the next inundation is an important part of the long-term
ecological processes for the area, for example the need for swamps to dry to
provide duck breeding habitat has been well known overseas (Crome 1988).
In Booligal (NSW), most species bred best after a flood on a previously dried
out basin (Crome 1988) rather than semi permanent water bodies. In the dry
period, grasses and other dry land vegetation can grow in the basins and
when re-flooded these rich organic substrates and the decaying flooded
vegetation provide resources for rapidly developing populations of detritivores
such as chironomids (Crome 1988). This is quickly followed by development
of a complex wetland flora and a diverse invertebrate population that can
eventually becomes dominated by fish (Crome 1988).
62
Before the water completely recedes, the drying period creates new shallow
wading areas that can provide new feeding opportunities for many waterbird
species. (Kingsford et al. 1999). Fish die in phenomenal numbers as wetlands dry back (Kingsford et al. 1999) and concentrated fish populations can
attract large numbers of fish-feeding birds (Whitfield and Taylor 2009). But
waterbird numbers can decline rapidly when the increased predation reduced
the populations of fish faster than is sustainable (Whitfield and Taylor 2009)
After the water has receded waterbird diet may even switch from herbivory to
insectivory or they may move from fresh to saline areas, also changing their
diet (Kingsford and Norman 2002). The types of birds present can change
dramatically during the drying period. In a longitudinal study of a major flood
event in the Cooper Creek system Kingsford et al. (1999) found that ducks
were almost exclusively dominant pre-flood, numbers of all birds dropped
during the flood, herbivores were the most common during the majority of the
drying phase, but their abundance fell at least a year before the lake was dry.
In contrast, piscivore populations were low pre flood and then rose rapidly and
immediately post flood were the most abundant foraging group (Kingsford et
al. 1999). As the number of piscivores and (herbivorous) ducks declined
dramatically during the drying phase, the abundance of waders reached a
maximum (Kingsford et al. 1999). Waterbird population changes for
herbivores can be attributed to the changes in abundance and diversity of
non-emergent macrophytes caused by altered water regimes in the littoral
zone of floodplain lakes (Lesley 2001).
A1.2 There’s lots we need to consider before using
waterbirds as indicators
Little is known of Australian Water birds
Although waterbirds are reasonably well studied compared to many other
animals, there are many unknowns (Kingsford and Lee 2007). Knowledge of
their ecology remains poor for many species, particularly cryptic and rare
species, and is only moderate to good for hunted species (Kingsford and
Norman 2002).
63
Whilst reduced flooding is perceived as detrimental in general, for many
Australian waterbird species, little is known about the impact of reduced
altered hydrological regimes on breeding (Kingsford and Johnson 1998). For
example, the (long-term) difference in impact of a few small breeding events,
compared to an occasional large breeding event is unknown (Kingsford and
Johnson 1998). Australia’s arid environment and river systems are inherently
variable and we have restricted knowledge of waterbird movements and use
of different wetlands in general (Kingsford and Lee 2007) and migration
patterns for Australian water birds is relatively limited or unclear (Chambers
2008).
Wetland Types
Wetlands vary from inundated grasslands to marshes and swamps to
inundated shrublands and or forests and different bird species tend to be
associated with different wetland types (Desgranges et al. 2006). This is
probably mostly because of the different habitat and potential feeding
resources on offer. Nevertheless the long-term fluctuations between drought
and flooding makes applying classifications for an Australian wetlands difficult
(Fjeldsa 1985) and it is simpler to concentrate on the bird communities
themselves. Furthermore, decreases in hydrological condition from river
management results in a change in the distribution and abundance of wetland
types on the regional scale (Desgranges et al. 2006). In other words, different
types of wetlands are differentially subjected to different rates of loss (Green
et al. 2002). This can have serious consequences for water birds but the
changes in waterbird communities may be an indicator of the changes. For
example, species that nest in wet grasslands are more vulnerable than
migrant species to changes in the water regime as extensive spring flooding
during the breeding season can delay or prevent waders from breeding
(Paillisson et al. 2002).
Wetlands show spatial and temporal variation
Ephemeral wetland habitat extent vary as a are a result of Australia’s highly
variable climate and river-flooding patterns (Kingsford and Norman 2002). As
the wetlands and their associated habitat vary enormously, any classification
64
of wetlands must t be flexible enough to reflect the varying conditions (Fjeldsa
1985). This variation is location dependent.
Spatial variation in waterbird numbers
The presence of many birds at a site is often an indicator of good
environmental conditions, however, the presence of only a few birds may not
reflect poor environmental conditions because conditions elsewhere may be
influencing bird numbers at the monitoring site (Kushlan 1993). In other words,
spatial variability must be understood because even looking across Australia
as a whole, there are generally always some refugia available even when
there are extended dry periods. On the other hand, when there are more
frequent flooding events, colonial waterbirds may have many choices of
feeding or nesting sites and birds may not be present in all suitable places at a
particular time (Kushlan 1993). We do know however that waterbird
movements in Australia are dynamic, with habitat, food and breeding
requirements generally determining whether waterbirds move, when they do
and how far (Kingsford and Norman 2002). Equally, monitoring and
bioassessment need to be aware of the timescales over which ecological,
hydrological and geomorphological patterns and processes respond (Vaughan
et al. 2009). Understanding what constitutes natural population changes
because of normal climatic or environmental variation is necessary before
anthropogenic stressors can be implicated (Lesley 2001).
Numbers or waterbirds vary widely from one year to another and during the
breeding season (Reitan and Sandvik 1996). Some of the variability can be
taken out by looking only at presence of the waterbirds or only at their
breeding. There are relatively few natural areas in Australia where colonial
waterbirds breed (Kingsford and Auld 2005) and much of the overall potential
breeding area has declined (REF). Even though natural wetland areas are
declining, artificial wetlands like irrigation channels and ponds can support
many bird species (Rendo´n et al. 2008) and these artificial impoundments
can even provide temporary nest sites (Kingsford and Norman 2002).
65
Migration
Regular movements are not common in most Australian waterbird species
although some, particularly waders, migrate between Northern Hemisphere
breeding grounds and non-breeding habitat in Australia (Kingsford and
Norman 2002). Rainfall (either in the form of total rainfall or number of raindays) appeared to be associated with the timing of arrival, departure and
season length and this relationship is particularly apparent in drier regions
(Chambers 2008). Other factors that may contribute to changes in timing of
migration include changes to vegetation, changes in temperature, land-use
and water-use (particularly in the case of waterbirds) at both the breeding and
non-breeding grounds (Chambers 2008).
A1.3 Literature Review of Waterbirds as indicators
Waterbird indicators – general
The basic biology of colonially nesting waterbirds makes them ideal
bioindicators (Kingsford and Lee 2007; Kushlan 1993; Lesley 2001).
Waterbirds are a major component of the floodplain wetland ecosystems and
integrate information from across the entire ecosystem and indicators can be
designed to standalone or to complement other indicators (e.g. flow, fish,
vegetation) (Kingsford and Lee 2007). Existing long-term data sets have
provided good evidence for the value of waterbird data and its ability to reflect
ecological changes to a particular site as a result of water resource
development (Kingsford and Lee 2007). Kushlan (1993) identified the
following potentially appropriate colonial waterbird bioindicators;
genotoxicity, mixed function oxidases, metallothionein induction, tissue
concentration of contaminants, egg shell quality, other physiological
responses, histopathology and teratology, growth, behaviour, reproductive
performance, mortality, presence/absence, distribution, and population
indices. Many of those potential indicators mentioned above are indicators at
the organism level as such more appropriate to non-migratory birds or from
more permanent water bodies. Kingsford and Lee (2007) suggested
monitoring floodplain health using waterbirds in the Australian context should
include species richness, abundance and breeding indicators. This literature
66
review has also identified potential community structure indicators that may be
considered.
Waterbird Communities
Historically, descriptions of waterbird communities generally correspond to
functional groups relating different food preferences and where the birds
usually forage (Kingsford and Lee 2007). In Australia waterbirds generally
belong to one of five community types and the typical habitats for each
community or association are characterized mainly by factors associated with
the stability or permanency of the wetland (viz feeding conditions?) and with
presence or absence of vegetation cover (Fjeldsa 1985). The kind of
vegetation and the topography of the wetland appear to influence the avian
community only slightly and the habitat associations are probably more
related to hydraulics of the system (Fjeldsa 1985). For example, reduced
periods with spring water levels under 25 cm was adverse to numerous
ground-feeding waterbirds (Ciconiiformes and waders) that require shallow
waters.(Paillisson et al. 2002). On the other hand some species such as
ducks are less sensitive to water level fluctuations (Paillisson et al. 2002).
Similarly, it is not uncommon for natural wetlands have a higher ratio of
migratory to residential species than artificial wetlands (Bellio et al. 2009).
Differences in the number and relative abundance of colonial wading bird
species between Florida and Venezuela appear to reflect differing
hydrological conditions in two otherwise similar ecosystems (Kushlan 1993)
Waterbird Community Bioindicators
Because of the sensitivity of the entire waterbird community to inundation
patterns, a number of different indices can be used to track floodplain health
using waterbirds (Kingsford and Lee 2007). The number of waterbirds and the
composition of waterbird communities can reflect changes in water quality or
changes to flow regime (Kingsford and Lee 2007). These changes can be
monitored at the community level using include total abundance, species
richness, functional groups, community composition, presence/abundance of
particular species (threatened or migratory), abundance of breeding birds
species richness of breeding birds(Kingsford and Lee 2007). Changes in
67
ecosystem functioning should alter patterns of colonial waterbird community
structure over time (Kushlan 1993).
Waterbird Population Bioindicators
The presence (and persistence) of a colonial waterbird species at a site
indicates that the ecosystem is suitable for it at some level and therefore is an
appropriate bioindicators of those conditions that the bird requires (Kushlan
1993). If the species present are of a high nature conservation value then this
can add value to the biological integrity and ecological value of a wetland
(Paillisson et al. 2002). Colonial waterbird abundance or population data have
the potential to provide more information than presence/absence data alone
however (Kushlan 1993).
Reproductive performance can be an early indication of population effects that
appear later (Kushlan 1993) and basic population parameters such as birth
rates are among the most appropriate variables to use as bioindicators
(Lesley 2001). The timeframe for making assessments using population
indicators needs to take into account the reproductive biology of the species
considered. For example, some species have an approximate mean wild
survival of 8–10 years with a potential lifespan of 20–25 years (Lesley 2001).
Treating it as a closed system (i.e. ignoring migration), this would mean a
flood one year in 7 would sustain the population perpetually and even a one
flood year in 20 may suffice albeit at lower numbers. Therefore long-term
monitoring of population numbers may have value as an indicator of wetland
health. These numbers could change between species and the relative
abundance of species could indicate the inundation history for a closed
system. But these differences emerge over long periods and it is likely that
concerns over a decrease of an individual colonial waterbird species would
overshadow concern for changes in community indices (Kushlan 1993).
Bird mortality could be an important indicator and has often been recognized
as a signal of broader environmental problems (Kushlan 1993). Although
death of a single bird provides little information, Kushlan (1993) suggests that
massive or repeated instances of mortality can be considered to be an assay,
68
analogous to typical toxicology bioassay. This is misleading if one wanted to
compare regions or wetlands because one cannot generate an assessment
unless the organisms (waterbirds) are exposed to each region or wetland. In
other words, if birds are absent for whatever reason then they cannot be used
to assess that area.
We do know that hydrological stress factor is probably the most critical factor
affecting long-term stability or persistence of waterbird breeding within the
forest (Lesley 2001). Without breeding or migration, some species can
become locally absent but this may also be a natural event. It is
recommended that the absence of waterbirds could be considered as potential
warning signals of degradation that should lead to more direct measurements
(Mattsson and Cooper 2006), (e.g. hydrological indicators, macrobenthos
monitoring, catchment-scale land use, etc).
Richness type indicators
In some environments the number of species of waterbirds present is related
to the number of waterbirds present (MDBC 2008). On other occasions
however the number of species present may be a representation of the health
of the ecosystem. For example, the number of duck species can show
positive trend with increasing water level (Reitan and Sandvik 1996), and
freshwater wetlands can support more species than saline ones (Chambers
2008). On the other hand, whilst the presence of many birds at a site is often
an indicator of good environmental conditions, however, the presence of only
a few birds may not reflect poor environmental conditions because conditions
elsewhere may be influencing bird numbers at the monitoring site (Kushlan
1993).
Breeding type indicators
Waterbird population indicators will probably require one or two generations to
turnover to detect changes (Lesley 2001) and some species may not breed
successfully for decades (Kingsford and Norman 2002). A simpler measure
may be to monitor breeding events. Some waterbirds have site fidelity for
breeding and so monitoring of specific sites could be an option (Kingsford and
Lee 2007). Of course this again raises the issue of not being able to monitor
69
the whole continent equally, rather only sites where breeding is known to
occur.
The types of indicators would be related to commencement of breeding,
number and types of species nesting, nest abandonment/desertion events,
fledgling success and the sequence of species that breed. There are
documented cases of the sequence of triggers for breeding for different
species. In south western Queensland, pelican breeding probably coincided
with high levels of fish populations while Black Swans nested later as the
water cleared and aquatic macrophytes became abundant (Kingsford and
Norman 2002).
Spatial and Temporal monitoring
Australia experiences great spatial and temporal heterogeneity of wetlands
because of continuing long- and short-term oscillations between flooding and
drought (Fjeldsa 1985). Consequently there is spatial and temporal variability
in the availability of Australian wetland habitat and available food resources,
which are probably the most important factors determining the abundance of
waterbirds (Kingsford and Norman 2002). The considerable spatial and
temporal variation in cormorant abundance on semi-permanent wetlands is
thought to reflect food availability (Kingsford and Norman 2002). It is therefore
not surprising that waterbird abundance in Australia is generally unpredictable
and interpretation of such data can be difficult (Kingsford and Norman 2002).
Nevertheless, if appropriate indices are calculated and maintain trends over
time and space, the underlying population changes should be inferable
(Kushlan 1993). In other words, annual monitoring provides only broad
information and requires long periods of data to ensure that the stochastic
variation can be separated from anthropogenic impacts (Kingsford and Lee
2007). For example, when periods of drought and no egret breeding in the
northern half of the Murray–Darling Basin corresponded with floods in the
southern half, egret breeding numbers continued to decline in the southern
half (Kingsford and Johnson 1998; Lesley 2001). This suggests that
immigration is not a mechanism for colony reformation in the Barmah-Millewa
70
forest. (Lesley 2001) and gives an example of how large spatial and temporal
scale data sets are very important to interpret local scale changes.
Some waterbirds use the same or different wetlands at different times
(Kingsford and Norman 2002). This could make investigations of specific
distributions difficult (Kingsford and Norman 2002) but could also make birds
ideal candidates for assessing wetland condition from a landscape
perspective (Veselka IV et al. 2009). Sometimes the variability is predictable
and this could be put to use when developing indicators. For example, many
tropical waterbirds are driven by the seasonal wet and dry: they spread out
onto inundated floodplains during the wet season and then retreat to remnant
wetlands in the dry season (Kingsford and Norman 2002).
The presence of any particular waterbird community may be as much a
reflection of factors operating outside the catchment or site as factors intrinsic
to the site itself and so relevant to floodplain condition.(Kingsford and Lee
2007). These factors may act at local, regional or continental scales
(Kingsford and Norman 2002). For example, presence of any species may
depend on having a regional waterbird population pool available (Kushlan
1993). Waterbird distribution and abundance in one part of the MDB may be
affected by flows elsewhere in the Basin (Kingsford and Lee 2007). This is
well documented as the boom and bust cycle of Australian dryland river
systems (Kingsford et al. 1999).
Functional indicators
Waterbirds can be allocated to different functional groups according to say
nesting requirements or feeding types (e.g. Hughes et al. 2009; Kingsford and
Thomas 2004). Changes in nesting numbers of birds from a particular feeding
functional group can suggest the effect of a common stressor related to food
abundance or availability (Kushlan 1993). Kingsford and Thomas (2004)
attributed declines across all feeding functional groups: piscivores (82%),
herbivores (87%), ducks and small grebe species (90%), large wading birds
(91%), and small wading birds (95%), to similar levels of decline in the aquatic
biota that formed their food base.
71
Breeding indicators
The breeding of colonial waterbirds is a potentially useful measure for
measuring environmental flows because waterbird breeding is highly
responsive to high flows and flooding (Kingsford and Auld 2005). Yet not all
species respond in the same way, as Kingsford and Auld (2005) found no
significant relationship between breeding of Cattle and Little Egrets and river
flows. In general, poor reproductive performance is due to some aspect of the
environment creating stress and, as a result, can be used as a bioindicator of
general environmental stress (Kushlan 1993). Because waterbirds are top
order consumers, poor reproductive performance can signal long-term
environmental change related to diminished ecosystem productivity at lower
tropic levels (Lesley 2001). When habitat or food availability is low there is a
reduction in the number and quality of chicks produced (Kushlan 1993).
Colonially-nesting waterbirds develop traditional attachments to nest sites that
provide reliable nesting and foraging habitats but local breeding populations
can expire from prolonged dry periods (Lesley 2001). Reinstating a suitable
hydrological regime under these circumstances, may prove an ineffective
recovery strategy (Lesley 2001).
Irrigation developments in the Cooper Creek catchment to divert water from
the river and decrease the frequency and flooding of wetlands of the Lower
Cooper were predicted to result in fewer feeding areas and less breeding
opportunities for waterbirds (Kingsford et al. 1999). Consequently, boom
periods would be shorter and bust periods longer (Kingsford et al. 1999).
Growth
Growth and condition are commonly used bioindicators in various animals
(Kushlan 1993). Using a waterbird example, a link has been inferred between
growth of young herons and water conditions in their feeding habitat (Kushlan
1993).
72
Waterbirds abandon/desert nests/stranding
Inter and intra annual variations in depths changes wetland areas which can
lead to an increased probability of nests being stranded particularly for water
birds that nest near the surface (Desgranges et al. 2006). When a nest
becomes stranded the birds face the inevitable energetic conflict between
moving to another habitat or remaining where decreasing resources may
become abundant (Kingsford and Norman 2002). Australian Pelicans also
sometimes stay and die (Kingsford and Norman 2002) but many species
desert or abandon the nest and their offspring. Ibis abandoned their almost
fledged chicks on Lake Altiboulka, following rapid recession of a natural flood
(Kingsford and Norman 2002). Nest desertion is a result of inadequate flows
(Kingsford and Lee 2007) and has been directly attributable to periods when
water levels dropped rapidly from pumping upstream (Kingsford and Auld
2005). The rate of fall rather than the fall itself was associated with
abandoned breeding at the Algeboia Plain (Lesley 2001). Although proximate
factors for such abandonment are probably associated with falling water
levels, ultimate factors are probably related to food availability (Kingsford and
Norman 2002).
Positives for using waterbirds
There are a large number of waterbird species found in Australia (81 in the
Murray–Darling Basin alone) leading to a wide range of potential responses
(Kingsford and Lee 2007). Among the positives for using waterbirds are;

Waterbirds can track ecosystem health at the landscape scale,
including key wetlands and entire catchments (Kingsford and Lee
2007)

The structure of waterbird communities and functional distribution
patterns is strongly associated with habitat quality, changes in landuse
and physical disturbance to the bank profile (Hughes et al. 2009)

Waterbirds are predominantly at the top of the food chain and so they
can track changes in other indicators (e.g. invertebrates, vegetation,
fish) providing an additional indirect measure of these indicators
(Kingsford and Lee 2007)
73

Trained amateurs can identify bird species through passive observation
or playback recordings of focal species (Mattsson and Cooper 2006),
this is considerably less sampling effort than for fish or
macroinvertebrates

Using stream-dependent birds as an early warning signal for
degradation of stream biotic integrity could improve the efficacy of
catchment monitoring programmes in detecting and identifying
perturbations within the catchment. (Mattsson and Cooper 2006)

Population indices for colonial wading birds in the Everglades have
been shown to change in relation to changes in wetland hydrology
(Kushlan 1993)

The limited number of sites used by colonial waterbirds and their
geographic restriction make them particularly vulnerable to
anthropogenic impacts (Kingsford and Auld 2005)

There is good evidence that waterbird communities have already
responded to changing flooding regimes in the Murray–Darling Basin
(Kingsford and Lee 2007)
Negatives for using waterbirds
There are, however, major difficulties in using colonial waterbird population
indices as bioindicators of ecosystem change (Kushlan 1993). These include;

Presence does not mean that all aspects of a bird's needs are met; a
bird may be present but not reproducing. (Kushlan 1993)

Mobility of the species (Kushlan 1993)

Lakes may temporarily have a much wider selection of species than
normal because of drought somewhere else (Fjeldsa 1985)

Breeding populations of colonial waterbirds are known to rebound after
natural and human induced reductions (Lesley 2001)

Colonial waterbirds are large in size, need wide ranging habits, are
difficulty to approach and capture, and migrate (Kushlan 1993)

Waterbirds can concentrate in artificial wetlands when natural wetlands
are dry (Rendo´n et al. 2008)

Inherent variation in Australia’s climate may make any long-term,
systematic impact difficult to discern above shorter-term, background
74
variation (Kingsford and Norman 2002). Can boom and bust cycles be
quantified and converted to an indicator water related stress?

Waterbird communities are effective indicators of the ecological
integrity of wider river landscape (Hughes et al. 2009) – it may be
difficult to partition out the effects of water related stress from other
effects such a habitat fragmentation, pollution, etc

High natural variability means that distribution changes may prove hard
to distinguish from short-term fluctuations (Kushlan 1993)

Factors other than flow patterns may be implicated in the decline of
waterbirds The proliferation of Cyprinus carpio and grazing by domestic
stock are examples of confounding environmental stressors (Lesley
2001)

When a downward trend of a population index is detected, it may not
be possible to know what is causing the trend without doing a causality
study (Kushlan 1993)

Other factors such as weather and contaminants also can affect
nesting success. (Kushlan 1993)

Populations trends can be caused by environmental changes (Kushlan
1993).

The many factors affecting population density at a particular site
suggest that it may be difficult to relate population data to overall
habitat value (Kushlan 1993)

The absence of a species at the time of sampling does not prove that
ecosystem conditions are unsuitable for it (Kushlan 1993)

Wetland loss and development of water resources are formidable
issues, closely tied to future economic development in Australia
(Kingsford and Norman 2002)
Caveat. Waterbirds numbers are declining anyway
Waterbirds are declining around the world (Bellio et al. 2009; Rendo´n et al.
2008). Unless policies protecting rivers are implemented, habitats for
waterbirds will continue to disappear (Kingsford and Norman 2002) and
waterbird numbers and local diversity will continue to decline. The declines
are well documented for some regions. For example, The number of
75
waterbird species in the Lower Murrumbidgee has declined significantly by
21% since development (Kingsford and Thomas 2004). The large colony sizes
in the Macquarie marshes (of more than 100,000 nests estimated during the
floods of the 1950s) are unlikely to occur again (Kingsford and Johnson 1998).
Leslie (2001) identified evidence of declining abundance and diversity of
colonially-nesting waterbirds within all four waterbird functional guilds in the
Barmah-Milewa Forest.
76
Appendix 2 Literature Review of Vegetation Ecology
relevant to water scarcity
Physical habitat in streams is a major determinant of in-stream biotic
composition (Bunn and Arthington 2002) and a major component of habitat is
in channel vegetation. The aquatic life and process in the channel are
adapted to this flow regime (Bunn and Arthington 2002). Outside the main
channel, floods, dry periods, and seasonal flows are all part of the flow regime
and are the equivalent on the floodplains and for floodplain vegetation as the
river flow regime is for in channel processes (Roberts and Marston 2000).
Vegetation needs water for survival and regeneration phases and the water
regime for each phase may be different (Roberts and Marston 2000). Hence
different types of floodplain and or wetland vegetation are adapted to and
require differences in components of flow regime including;
o
Magnitude of flood
o
Duration of flooding
o
Rate of flood ascension/recession
o
Frequency of floods
o
Seasonality (Roberts 2004; Roberts and Marston 2000)
Hence disruption to natural flow regimes should be observable in changes to
channel or floodplain vegetation characteristics. However, vegetation on the
margins of inundation zones can also use rainfall stored in the soil is an
additional possible source (Thorburn et al. 1994). The spatially and temporally
complicated nature of these environments means the adaptive strategies used
by plants can be complex (Thorburn et al. 1994). For this theme the challenge
will be to isolate water scarcity effects from other effects.
What happens to vegetation when it is water stressed?
Plants can use rainfall, surface water or groundwater. All these may be
available in flooded conditions in wetlands or on floodplains, whereas in
77
drought periods groundwater is their only source of water when surface water
bodies have dried up and soil water reserves have been depleted (Thorburn et
al. 1994). In marshy areas, rainfall and groundwater are the two primary
sources of water for plants (Thorburn et al. 1994). Overall, the effects of
changes in the inundation regime on plants depends on whether a plant has a
narrow or wide range of environmental tolerances and whether the species is
resistant (i.e. has capacity to withstand stress) or resilient (has the capacity to
recover) (Bunn and Arthington 2002).
The frequency and intensity of exposure to hydrological stress by floodplain
vegetation are increased by river flow regulation(Jensen et al. 2008). River
regulation is associated with many changes in flow apart from less water
availability (Poff et al. 2009; Poff and Zimmerman 2010). A thorough literature
review of riparian ecological responses to change in flow regimes was
conducted by Poff and Zimmerman (2010, Table A2.1).
Table A2.1: Responses of riparian zones vegetation to altered flow regimes
from river regulation (source: Poff and Zimmerman 2010)
Flow component
Primary flow alteration
Riparian Ecological Response
Magnitude
loss of peak flows
Altered recruitment, failure of seedling
establishment
Terrestrialisation of flora
Increased success of non-native
Lower species richness
Vegetation encroachment into channels
Increased riparian cover
Frequency
Decreased frequency
of peak flows
Shift in community composition
Reductions in species richness
Increase in wood production
Duration
Decreased duration of
floodplain inundation
Reduced growth rate or mortality
Altered assemblages
Terrestrialisation or desertification of species
composition
Reduced area of riparian plant or forest cover
Timing
Loss of seasonal flow
peaks
Reduced riparian plant recruitment
Invasion of exotic riparian plant species
Reduced plant growth and increased mortality
Reduction in species richness and plant cover
Rate of change
Increased variability
Decreased germination survival and growth of
plants
78
Dry climate floodplain vegetation communities are adapted to but prone to
moisture stress (Roberts 2004) and show varying responses including include
slower growth, dieback or mortality when there is a shortage of available
moisture (Jensen et al. 2008). The variation in responses can be because of
differences in species and individual site circumstances but the general effect
of moisture stress response in trees is;

Vigour for existing mature trees
o fewer and shorter periods of growth conversely more and longer
periods of little no growth or water or heat stress

Regeneration
o fewer opportunities to flower, set seed, germinate or for seedling
establishment (Roberts 2004)
And the typical responses of understorey and wetland plants;

flood events not long enough to complete life cycle and set seeds

flood events not long enough to re-establish carbohydrate reserves
in perennating organs

depletion of seed banks through decay, ageing and predation due to
infrequent flooding

attrition of perennating organs (rhizomes, rubbers) due to fewer and
shorter opportunities for growth (Roberts 2004)
Scale of changes in vegetation associated with hydrological stress
Scale of hours (Merritt et al. 2010)
Somatal conductance, transpiration, net carbon assimilation, leaf internal CO2
concentration, carbon isotope discrimination (an index of time –integrated
carbon concentration and water use efficiency) and xylem water potential can
change as plants increase their water use efficiency or become stressed in
response to anoxia, water availability or changes in atmospheric conditions.
Such measurements have led to the development of thresholds of
groundwater depletion for some riparian species through measuring the onset
and consequences of chronic water stress
79
Scale of hours-weeks (Merritt et al. 2010)
Wilting, chlorosis and discoloration of leaves, abscission, leaf death and
reduction in canopy volume can collectively express negative, short to long
term (hours-weeks) response to reduced water availability. Extreme water
stress may result in xylem cavitation and branch dieback in trees and shrubs
(‘drought pruning’), which can relieve overall water stress in the individual by
reducing leaf area. Severe moisture stress sometimes results in complete
branch or tree dieback allowing reduced stress in surviving branches and
individuals within a riparian forest stand.
Long-term responses (Jensen et al. 2008)
Slower growth and dieback or mortality will become more common. Plants
may continue to produce seed under stress, and germination may occur
opportunistically in response to local rainfall, but the seedlings are insecure
until they have developed ‘sinker’ roots to free them of dependence on nearsurface soil moisture.
Salinity and the interaction between groundwater and surface water
Salt accumulates in floodplain soils as a result of capillary rise of water
transporting the natural salts to the surface (Overton et al. 2006). Shallow
groundwater is drawn up and either evaporated at the surface, or used by the
trees (Overton et al. 2006) and river regulation can cause water tables to rise
closer to the surface, increasing salt accumulation rates in floodplain soils
(Holland et al. 2009). The salt is left behind in the upper soil layers where it
slowly accumulates where historically it would have been flushed by flooding
every few years (Holland et al. 2009; Jolly et al. 2008; Overton et al. 2006).
Reductions in the frequency, duration and extent of flooding mean that the
leaching of salt from the plant root zone is reduced, causing a reduction in soil
water availability and riparian vegetation health (Holland et al. 2009).
Alternatively, in areas where rivers lose water to the groundwater, reductions
in the frequency, duration and extent of flooding can result in lowering of water
tables beneath floodplains (Holland et al. 2009). If the groundwater is
80
relatively fresh, then lowering of water tables results in a reduction of water
availability (Holland et al. 2009).
This water scarcity related stress can potentially be detected by changes in
the vegetation. For example, persistence of submergent species
likeVallisneria australis and the woody shrub Melaleuca ericifolia was
compromised by increased salinity (Salter et al. 2008). Increased salinity was
associated with areas of non-tree vegetation in poor condition on the Chowilla
floodplain, and an increasing occurrence of saltbush species (Overton et al.
2006). Wetlands can slowly change from ephemeral wetland environments to
floodplain halophytic communities in such conditions (Overton et al. 2006).
The two main species of Eucalypts associated with floodplains in the Murray–
Darling Basin are River Red Gum (Eucalyptus camaldulensis) and Black Box
(E. largiflorens). River red gum has lower tolerance to salinity than black box
and generally most black box exists on the higher parts of the floodplain
where depth to groundwater is rarely less than 2m (Overton et al. 2006). The
differences in salinity tolerance means that large scale changes to flood
regimes and subsequent lack of salt flushing means that Black box can
become more favoured in some riparian zones.
Potential Indicators
Plant community attributes such as richness, diversity, cover, growth,
productivity, community composition and biomass can be linked to the
hydrologic attributes of rivers and may respond in predictable ways to specific
hydrologic alterations (Merritt et al. 2010). Plant associations or dominant
cover types show strong affinities for specific hydrologic attributes such as
inundation duration and depth to ground water (Merritt et al. 2010). A recent
study from Africa showed that indicators can be derived for woody plant
variables response to desiccation-driven change (water-table lowering and
increased salinisation) (Ringrose et al. 2007). Distinct changes in tree and
shrub height, plant density and species richness as well as changes to
abundance of brackish ground-water-tolerant and dryland species were
81
related to water scarcity (Ringrose et al. 2007). The next section looks through
some potential indicators in an Australian context.
Terrestrialisation
Differences in tolerances to stressors means that the make up of communities
can change through time. The process of changing to drier conditions is
sometimes referred to in floodplain vegetation ecology as Terrestrialisation,
meaning that overall the floodplain is beginning to support species more
typical of terrestrial environments and habitats (Roberts 2004). Plant
communities undergoing Terrestrialisation can be expected to progress
through stages such as;

loss of vigour, (initially in sensitive perennial species)

loss of species

shift in structural characteristics such as cover and number of strata

gradual establishment of species better adapted to drier conditions
(Roberts 2004)
Detectable changes in vegetation characteristics therefore include species
richness, number of strata, cover of dominant trees and groundstorey species
(Roberts 2004).
Terrestrialisation is not officially defined and at this stage is only applied in an
anecdotal sense (Roberts 2004). However this type of response is the move
towards saltbush species on the Chowilla floodplain described by Overton et.
al (2006). The response of large long-lived species like River red gum may be
much slower than other species. Whilst the total area of River Red Gum
forests and woodlands in Yanga National Park remained over a sampling
period of 40 years there were significant changes in the areas of River Red
Gum understorey communities (Wen et al. 2009). Spike-rush ground cover
was associated with high soil moisture after a decade of above normal
flooding but drying saw a change to dominance by chenopod shrubs or bare
ground understorey (Wen et al. 2009). Similarly, invasions by more droughttolerant species such as chenopod (e.g. Nitre Goosefoot (Chenopodium
82
nitrariaceum) and shrubby species such as Lignum (Muehlenbeckia florulenta)
occurred in the Murrumbidgee catchment after water resource development
(Kingsford and Thomas 2004; Wen et al. 2009). Lignum is a common and
widely distributed shrub of Australia's desert floodplains and is very tolerant to
flooding and drying (Capon et al. 2009). Lignum tolerates drying by reducing
leaf area ratios and recruitment is a likely response to surface water hydrology
(Capon et al. 2009).
Vegetation responses to water scarcity include not just less water but changes
in inundation history like less frequent flooding or reduced area of flooding.
The drawdown of Lake Mokoan allowed for documented responses of
vegetation to a controlled change in inundation from wetter and younger to
older and drier (Roberts and Hale 2007). There was an
increase in species richness, in the number and the proportion of terrestrial
species, the number and relative proportion of perennial species, a decrease
in nativeness (% of species native), and in the proportion of species that were
mainly water dispersed (Roberts and Hale 2007).
Terrestrialisation at Lake Mokoan was a gradual process, with no abrupt
ecological changes, -The oldest and driest quadrats, were not significantly
different from each other in terms of floristic composition (Roberts and Hale
2007). Floristic composition was virtually defined after four years without
inundation and that timeframe is therefore an ideal point to review vegetation
status (Roberts and Hale 2007).
Species richness
The response of species richness to drying is certainly time dependant. For
example, species richness of seeds in dry-stored wetland sediments
decreased by approximately 50%, to approximately 25 species over just 9
years (Roberts 2004). Therefore this type of indicator (seed bank species
richness) would need to be consider species resilience times. It is suggested
that River red gums require inundation once in every 4 years whilst Black box
only 1 in 12 years for persistence (Roberts 2004). Therefore any richness
83
indicator can be value added in a water scarcity context by taking into account
the composition of the species present (Mathews 2009).
Vegetation form
Hydrological stress may be evidenced by changes in the 3 dimensional
structure or missing layers from the strata of the riparian vegetation. Roberts
(2004) cites a paper suggesting that upper stratus should have at least 50%
old mature or mature but not emergent stratum. But there is little quantified
research available in this topic. Similarly, native and alien cover needs further
research, but an index using non-native cover of lower strata <1.5 m tall has
been used and there may be an apparent inverse relationship between
flooding frequency and number of introduced species in the Barmah Forest
(Roberts 2004). These types of anecdotal relationships are often open to
confounding and natural variation so further investigative research would be
required for them to become viable indicators.
Whilst increased dominance by natives may indicate the return to conditions
for which the natives are adapted, intermittency is not unusual in desert
riparian systems and therefore dry conditions are not necessarily expected to
favour non-native herbaceous species over natives (Katz et al. 2009). Thus,
dominance by native herbs per se may not be a measure of hydrologic
restoration in this system as non-native dominance may also reflect general
levels of disturbance such as the degree of present or recent agricultural
activity (i.e. livestock grazing, irrigated crops (Katz et al. 2009). Perennial-flow
reference sites had higher herbaceous cover, higher species richness, lower
weighted wetland indicator scores, and higher relative cover of hydric
perennials and hydric annuals than non-perennial sites (Katz et al. 2009). In
contrast, non-perennial sites had higher relative cover of mesic perennials and
xeric annuals (Katz et al. 2009). All of these are useful metrics for assessing
riparian condition (Katz et al. 2009)
Condition of floodplain vegetation
The condition of floodplain vegetation can be considered by vigour, population
sustainability, and ecological integrity. Specific attributes relative to these
84
attributes can be measured or estimated, and applied to dominant trees or to
the whole community, as required (Roberts 2004).
Vigour
Water availability along an environmental gradient leads to a decrease in
forest productivity and leaf area index over that gradient (Horner et al. 2009).
Thus changes in vigour can be a result of a natural spatial gradient when
distance from the river channel relates to decreasing water availability in some
forest stands (Cunningham et al. 2007b; Wen et al. 2009). Visual assessment
of canopy condition on the Chowilla floodplain after reports of increased
dieback found the few live trees of both River Red Gum and Black Box were
trees mainly in patches beside the River Murray (Roberts 2004). A study of
tree health from Renmark to Walker Flat where over 80% of trees showed
some stress, found stressed trees were typically associated with dry creeks
and lagoons, or where saline ground water flowed into the creeks (Roberts
2004).
Similarly, temporal changes in site productivity due to decreasing water
availability led to reductions in leaf area and stand density for long-lived
organisms such as trees (Horner et al. 2009). Vigour is often surrogated by
measuring canopy cover or crown condition. Crown condition is known to
improve in River Red Gums with frequent flooding and is apparently closely
linked with the hydrological regime within the floodplain (Wen et al. 2009).
Dieback
Overall levels of dieback remain as a potential general indicator of water
scarcity related stress, but there are other causes of dieback and within
stands there can be considerable variation in the level of dieback. Drought –
related dieback could cause higher mortality in smaller trees as larger trees
have access to groundwater, or higher mortality in larger tress because of
reduced vigour, making vigour and stand dynamics in combination a potential
indicator. However, a recent study of E. camaldulensis (in a stand showing
considerable dieback) found different-sized trees had similar probabilities of
being alive (Cunningham et al. 2009). It is possible that the cause of water
stress may differ among different-sized trees, with small trees responding to
85
low surface soil moisture while large trees are affected by lower availability of
groundwater (Cunningham et al. 2009). Either way. A lot more research
needs to be done before stand dieback differentiation could be used as an
indicator. Dieback in the Murray river is related to longitude, and this may be
a reflection of decreased water availability downstream which may in turn be
affected by decreasing rainfall or increased rive regulation (Cunningham et al.
2009). Nevertheless the high levels of River red gum dieback in the lower
MDB is likely to be associated with recent droughts and increased reliability on
groundwater (Cunningham et al. 2009). Dieback patchiness may be because
of differences in water availability on small scales such as minor differences in
topography (affecting the distribution of flood waters), different water holding
capacities of soil types and differences in the depth and salinity of
groundwater (Cunningham et al. 2009).
Community structure
Plant communities can be linked to hydrologic attributes of rivers and may
respond in predictable ways to specific hydrologic alterations such as
inundation, duration and depth to ground water (Merritt et al. 2010).
Vegetation characteristics (by indicator)
Attributes used to characterize vegetation include biomass, vegetation
volume, growth rates and stand physical structure. Yet the response of these
attributes to river flow or hydrological alteration are often very river and sitespecific, limiting transferability of relationships to other rivers even in the same
hydroclimatic regions (Merritt et al. 2010)
Suggested Indicators
The following indicators have been used in Australian studies looking at the
health of riparian or floodplain vegetation (from Roberts 2004);

ecological condition (expressed as hectares of dead trees)

non-native species (% of all species)

canopy condition (arbitrary % alive indicates healthy)
86

regeneration density (recorded as the number of juveniles and
seedlings per hectare)

number of regenerating trees in size classes (classes chosen to
indicate more recent or not so recent)
All the above are measured from in situ surveys, but it is interesting to note
that the amount of severely degraded vegetation can be detected from aerial
photography and this allows analysis of longitudinal patterns back to the
1980’s (Roberts 2004). A more recent study tried to relate overall stand
condition in E. camaldulensis to water related stress and investigated which
indicators that could be used in a quantitative assessment of E. camaldulensis
stand condition (Cunningham et al. 2007b). Interestingly there was little
evidence of differences in physiological performance in trees among goodand poor-condition (Cunningham et al. 2007b). This suggests that the death
of many trees and a resultant reduction in tree density of the stand results in a
level where soil moisture is adequate for the few living trees (Cunningham et
al. 2007b). Hence measures on indivual tress may mask the overall stand
condition and remotely sensed data can be used to estimate stand condition
across large areas (Cunningham et al. 2007b).
Seed production
Seed volumes released from unhealthy River Red Gums or Black box can be
significantly less than volumes released from healthy trees, but the differences
may be related to seasonality more than stress (Jensen et al. 2008). As such
seed production makes a poor potential indicator until more is known of
natural variation.
Remote Sensing
Remote sensing offers the capability to monitor a wide range of landscape
biophysical properties relevant to management and policy, including plant
(crop, forest, natural ecosystem) growth, yield and biomass; soil moisture;
water loss by evaporation; flood areas; fire hotspots and fire scars; sunlight
amount; and some soil properties (McVicar et al. 2003). Information on these
variables can be obtained for the past, the present and the future. Remote
87
sensing complements, rather than competes with, in-situ monitoring systems
and modelling (Cunningham et al. 2007a; McVicar et al. 2003).
Maps of green, actively growing vegetation, and its departure from normal
conditions for the time of year can be readily generated using remote sensed
data (McVicar et al. 2003) and Plant Area Index (PAI) and vigour for River red
gum stands were successfully predicted using just GIS layers of
environmental variables (Cunningham et al. 2007a). The best predictive
model for PAI used 6 and Vigour used 4 variables all derived from remote
sensed data (Cunningham et al. 2007a). The models were able to choose
from long-term (9 years) variance or mean values or the most recent years
value and from SPOT or LandSat TM data (Cunningham et al. 2007a).
The commonly used Normalised Difference Vegetation Index (NDVI)
calculates the photosynthetic capacity of vegetation based on the difference in
reflectance of the surface to visible (red) and near-infrared light (McVicar et al.
2003). This quantity has been shown to be a useful (albeit not perfect)
index of the proportion of the surface covered by green vegetation, and hence
of the vigour of the vegetation (McVicar et al. 2003). NDVI was the single
most important variable for predicting PAI in the Murray River floodplains,
although its performance as a lone predictor is not given (Cunningham et al.
2007a). In a similar study Cunningham et al. (2007b) found very strong
relationships between NDVI and several condition variables including PAI and
crown vigour (Table A2.3).
The strong relationship between vegetation vigour of mixed E. camaldulensis,
E. coolibah (coolabah) and M. forentula and inundation history were modelled
in the Condamine-Balonne region using NDVI by Sims and Thoms (2000).
They used five classifications of vegetation growth vigour (incorporated
variation from the long-term mean) and the top four categories reflected
inundation history well. Interestingly however, very low growth vigour was
common only where flooding occurred more frequently than once per year
(Sims and Thoms 2002). This result shows that site specific information is
always needed because of possible interactions with other factors like soil
88
anoxia, disturbance frequency or pixel mixing at the vegetation/water
boundary (Sims and Thoms 2002).
Table A2.3: Pearson’s correlations (n=12 sites) among the condition variables
measured in the field and with the remotely sensed vegetation index NDVI
Significant correlations are indicated: *P<0.05. Strong correlations (r>0.75)
are indicated by superscript A. (source: Cunningham et al. 2007b).
The leaf area index available through MODIS gives reasonable estimates
most cover types and land use types in Australia (Hill et al. 2006). Whilst
overestimation occurs in some eastern Australian open forests and
woodlands, (Hill et al. 2006) a monitoring program that uses historical
references would still detect changes through time. Temporal NDVI series
have been shown to be an accurate signal of vegetative phenology, which in
turn is a fundamental vegetation property and analysis of temporal series of
NDVI yields are suitable for regional scale applications (Lobo et al. 1997).
Issue of temporal and spatial scales
Measures of the physiological characteristics of individual plants may be the
most sensitive to short term changes in flow regime, but reveal little about the
important ecological consequences of changes in stream flow (Merritt et al.
2010). The choice of measurement at the level of the individual, population or
community level or some combination will largely depend upon the vegetation
attributes that are deemed important, along with established goals for
maintenance and restoration of riparian vegetation (Merritt et al. 2010).
NDVI is known to cycle through different seasons naturally, and this may give
a summer peak or a spring peak in NDVI. S (Lobo et al. 1997). Hence
89
anomalies are considered to be more valuable than unadjusted raw NDVI
scores.
Other factors affect vegetation health
Riparian taxa are influenced by channel incision, channelisation, increased in
floodplain soil salinity and other physical factors so vegetation communities
may be responding to flow indirectly through a wide range of physical and
biotic factors (Merritt et al. 2010). A number of factors other than groundwater
depth and flooding frequency affect the extent of soil salinisation, including the
salinity of the groundwater, and soil texture (Overton et al. 2006). Stressors
other than flow regime include rising saline groundwater and land clearance
and grazing can affect Eucalyptus spp. on the Murray, especially where
regeneration is sparse or patchy (Jensen et al. 2006). Because of factors such
as climate, soil properties, groundwater, species biogeography, assessments
will be floodplain-specific and unlikely to be linear (Roberts 2004). At Lake
Mokoan, the quality of the vegetation was linked to time since last
disturbance. For example, older and (therefore) less disturbed quadrats had
more terrestrial functional types, more non-native species, more species
dispersed by animal vectors, and greater species richness (Roberts and Hale
2007).
Indicators such as species richness can be non-comparable between different
sites or even areas within a site. For example, communities with the highest
percentages of non-native species were ‘on higher ground’, or were ‘highly
disturbed’ or had an understorey replaced by weak species (Roberts 2004).
Conversely, the lowest % of non-native species was for Red gum + spike rush
+ spiny mud grass open forest community which is wide spread and occurs on
low-lying or more frequently-flooded sites (Roberts 2004).
Several factors can be responsible for disguising potential patterns using
NDVI such as the spatial accuracy of the data, non-vegetation influences on
the NDVI, the scale of variation, and the measures for productivity and
persistence of productivity (Bader 2000).
90
Exotic veg
Lippia Phyla canescens is one of the few significant environmental weeds on
lowland floodplains in the Murray–Darling Basin and is a species that persist
under dry conditions so should be disadvantaged by flow rehabilitation
(Roberts 2004).
Issues with using vegetation as an ecological indicator
Advantages/strengths
1.
There are lots of types/forms of vegetation with different lifehistories/relationships with flow.
2.
NDVI and ground truthing may indicate changes a range of temporal
scales (i.e. seasonal, internannual)
Negatives/weaknesses
1.
Temporal and spatial complexity – separating out climate from water
extraction stress.
2.
The nature of the response of vegetation to hydrological stress. For
example: with red gum, the response might be asymptotic, In such a
situation, the response is very delayed to the extent of the stress
previously occurring, and that pass this point, may have reached a
point of no return. So while you can use vegetation as an indicator of
stress, you also run the risk of loss of ecological integrity, especially if
the relationship between stress and indicator responses, is not known,
or is delayed.
91
Appendix 2.1 README FILE FOR MODIS-DERIVED Land
Products (Paget and King 2008)
CONTENTS
-------1) DATA CUSTODIAN
2) ACCESS AND CONDITIONS OF USE
3) CITATION
4) DISCLAIMER, COPYRIGHT AND LICENCE
5) DATA SOURCE
6) DATA INFORMATION
7) DIRECTORY, FILENAME AND DATA FORMATS
8) GEOGRAPHICAL COVERAGE
9) DATA QUALITY
10) VERSION INFORMATION
11) UPDATES
12) REFERENCES
13) CONTACTS
1) DATA CUSTODIAN
-------------------------------------------------------CSIRO Marine and Atmospheric Research is the custodian of this
dataset.
This dataset has been developed by the Time Series Remote
Sensing Team, CSIRO Marine and Atmospheric Research. The
original data were supplied by the Land Processes Distributed
Active Archive Center (LPDAAC), located at the U.S.Geological
Survey (USGS) Earth Resources Observation and Science Center
(EROS) http://LPDAAC.usgs.gov.
2) ACCESS AND CONDITIONS OF USE
-------------------------------------------------------These data are available from:
http://www-data.wron.csiro.au/rs/MODIS/LPDAAC
Please note the citation and legal information in Sections 3
and 4 below.
In order to help us keep track of who is using the data,
please do not pass the data on to a third party. Instead,
refer them to the web site. In return for free access to
these data, we ask that you send us citations and copies of
publications arising from work that use these data
(Matt.Paget@csiro.au).
92
3) CITATION
-------------------------------------------------------When referring to this dataset in publications, please cite
both:
Paget MJ and King EA (2008) MODIS Land data sets for the
Australian region. CSIRO Marine and Atmpospheric Research
Internal Report No. 004.
http://lpdaac.usgs.gov/citation.asp
4) DISCLAIMER, COPYRIGHT AND LICENCE
-------------------------------------------------------Use of these data is subject to the Legal Notice and
Disclaimer at
http://www.csiro.au/org/LegalNoticeAndDisclaimer.html
These data are Copyright, CSIRO, 2008.
These data are made available under the conditions of the
Creative Commons Attribution-Share Alike 3.0 License:
http://creativecommons.org/licenses/by-sa/3.0/
5) DATA SOURCE
-------------------------------------------------------Data are derived from the MODIS Land Products that are
distributed by the LPDAAC as tiles from a global sinusoidal
projection. The primary reference for the MODIS land products
is http://lpdaac.usgs.gov/modis/dataproducts.asp.
Tiles for selected products for Australia have been downloaded
and then mosaiced and remapped using the Modis Reprojection
Tool (MRT).The products have been split into individual bands
to reduce file size and have been reformatted to ensure
consistency in SDS and attribute nomenclature.
Data from the MODIS instruments on both Terra and Aqua have
been used, with spatial resolutions of 250m, 500m and 1km,
depending on product.Temporal frequency of the data is daily,
8 days or 16 days, once again, depending on the product,
A full explanation of the processing is provided in the report
referred to in section 3 (above).
6) DATA INFORMATION
-------------------------------------------------------Data are available for a variety of terrestial applications.
Products include:
93
Surface reflectance
(MOD09Q1, MOD09A1)
Land surface temperature and emissivity
(MOD11A1, MYD11A1,
MOD11A2)
Vegetation indicies
(MOD13Q1)
Thermal anomalies / Fire
(MOD14A2)
Leaf area index and Fraction of photosynthetically active
radiation
(MOD15A2)
Gross Primary productivity
(MOD17A2)
Bidirectional reflectance distribution function and albedo
(MOD43B1, MOD43B3, MOD43B4, MCD43A1-A4, MCD43B1-B4)
The data are identified by the EOS product code. A generic
product code is
MxDnnyy
where,
x = 'O' (Terra), 'Y' (Aqua), 'C' (Combined Terra and Aqua).
nn = Product number, which defines the type of product.
yy = Sub-product code, which may distinguish the spatial
and/or temporal resolution.
Full detail on these and other products, including the
Algorithm Theoretical Basis Document (ATBD), are available
from the LPDAAC website.
The term "collections" refers to the MODIS land product
versioning system. Data products within a collection have been
processed with specific algorithm, instrument characterisation
and calibration refinements. For many products there are
significant changes between collections that reflect a new
understanding of physical processes or new ancillary data
sets. Therefore caution should be exercised if mixing data
from two or more collections.
The collection number of a product is identified by a threedigit number (001-005) following the product code. Collection
5 is the current version and was implemented for all data
produced from 01 January 2007. The LPDAAC is currently
reprocessing the entire data set from launch to 31 December
2006 to collection 5. The majority of the data available here
is collection 5, however for some products collection 4 data
is retained until the corresponding collection 5 data become
available. If collection 6 is released at some future time,
that data will most likely be included here.
7) DIRECTORY, FILENAME AND DATA FORMATS
------------------------------------------------------The ftp site has two levels of subdirectories. The first
level denotes the product and collection (version) and the
second level denotes the epoch.
A daily product:
94
MOD11A1.005/
2007.02.01/
2007.02.02/
2007.02.03/
...
An 8-day product:
MOD43A1.005/
2007.01.01/
2007.01.09/
2007.01.17
...
A 16-day product:
MOD13Q1.005/
2007.02.18/
2007.03.05/
2007.03.21/
...
Filenames have the following format:
MXDxxxx.yyyy.ddd.aust.ccc.bNN.label.hdf.gz
where,
X =
xxxx =
yyyy =
ddd =
aust =
ccc =
bNN =
original
label =
hdf.gz =
Spacecraft, 'O'=Terra, 'Y'=Aqua, 'C'=combined (both)
Product code
Year
GMT day number that the time-step begins (Jan,1=001)
Designates an Australian regional mosaic
Collection number
Band number (retains the order of the SDSs from the
product)
Short descriptive name for the SDS
HDF file, gzipped
Data are supplied as gzipped (standard) HDF files with one
file per band, where the band relates to the order of the
SDS's in the LPDAAC product. All of the HDF-EOS metadata are
retained as global attributes. In the cases where the band is
a byte or bitmap index (e.g, quality flags) an index is
supplied as an attribute. The Report (Sec. 3) contains full
details on the mosaicing, remapping and reformatting
processes.
Since May 2008 (processing date rather than epoch), log files
relating to the processing have been included with the mosaic
data files. Individually the log files are text files. They
are provided as gzip-ed tar files. The tar filenames have the
following format:
logs_yyyymmddThhmmss
95
where,
yyyymmdd = Year, month and day of the processing.
T = A separator.
hhmmss = Hour, minute and second of the processing.
The log files consist of:
hdf.list = List of input LPDAAC files.
remap.par = Parameters for the resample program (MRT).
bXX_mosaic.log = Output from the mosaic program (MRT).
bXX_remap.log = Output from the resample program (MRT).
bXX_reformat.log = Output from the reformatting program.
where XX is the band number.
Products in the mosaic archive may be regenerated with
progressively more complete data over several days as the
LPDAAC data pool is populated. The mosiac files will be
overwritten with the latest data. The log files, however,
will not be overwritten as they are time-stamped with the time
of processing. Therefore, the log files act as a record of
the processing for each band and for the epoch.
8) GEOGRAPHICAL COVERAGE
------------------------------------------------------Data are unprojected, in geographic decimal degrees,
referenced to WGS84.
The data are all remapped to the region 10.0 - 45.0 S and
110.0 - 155.0 E.
The number of pixels, pixel size and exact spatial extent
differ between the products depending on the spatial
resolution of the data (e.g. 250, 500 or 1000 m).
Precise geolocation information for each of the spatial
resolutions is provided in Appendix B of the report (Paget &
King, 2008 - see Sec. 3 above).
9) DATA QUALITY
------------------------------------------------------LPDAAC are responsible for the actual data quality and provide
quality channels as part of most products. These channels are
processed the same as the data channels. The mosiacing,
remapping and reformatting processes do not alter either the
data or the quality fields.
Users should be aware that not all tiles for a particular
mosiac necessarily become available from the LPDAAC on the
same day. It is therefore possible that the most recent
mosaic for any given product will be updated over several
days, each time containing progressively more and more actual
data within the same (standard) geographic extent.
96
We have had some minor issues with file corruption that have
been detected by users unable to un-gzip the mosaic files. If
you discover any such files, please report them to us (see
contacts below).
10) VERSION INFORMATION
-------------------------------------------------------------Please see section 6 with reference to 'collections'.
11) UPDATES
-------------------------------------------------------------The mosiac collection is automatically updated daily. In
practice this means that the archive is updated within 24
hours of new data being released on the LPDAAC data pool. The
documentation (papers and reports, and possibly this README
file) will mostly reflect the state of the data set at the
time of its initial release and may not be updated in
synchrony with the data themselves. As such, the files
present on the ftp server should be regarded as the definitive
inventory of the data set.
12) REFERENCES
-------------------------------------------------------------Paget MJ and King EA (2008). MODIS Land data sets for the
Australian region. CSIRO Marine and Atmospheric Research
Internal Report 004.
Land Processes Distributed Active Archive Center (LPDAAC).
http://lpdaac.usgs.gov
13) CONTACTS
-------------------------------------------------------------June 2008
Mr Matt Paget, CSIRO Marine and Atmospheric Research
matt.paget@csiro.au
Dr Edward King, CSIRO Marine and Atmospheric Research
edward.king@csiro.au
97
Appendix 3
Summary of literature review of in-stream
biota ecology relevant to water scarcity
Notes on methods and scope
This section reports on information from the scientific literature. The literature
search was limited to post-1999 papers published in English only, using
multiple databases accessed via “CrossSearcher” (Expanded Academic
ASAP (Gale); InfoTrac Onefile (Gale), Science Direct (Elsevier), Wiley
Interscience (inc. Blackwell), Web of Science, Ecology Abstracts (CSA).
Various combinations of the following terms were used: water stress,
ecological indicator, water scarcity, drought, ecological impacts,
macroinvertebrates, fish, flow, review, freshwater ecology, stream biota, river
biota.
This review focuses on research reporting relationships between
hydrology/flow variables (from mostly for flowing waters (i.e. rivers), but
relevant research on wetlands or lakes also included), particularly with respect
to reduced or altered flows; and for the most commonly monitored freshwater
biota, namely macroinvertebrates and fish. However, selected research
publications on other biota found incidentally during the literature search that
was deemed to be relevant has also been included (e.g. zooplankton,
diatoms, other vertebrates, other algae). The initial search resulted in a shortlist of approximately 250 papers. Abstracts were read in order to refine the list
further; the remaining 94 papers were used to prepare this review.
Very few published papers were found to report on the use of a particular
faunal group specifically as indicators of water scarcity, but a substantial body
of literature exists on the topic of using freshwater biota for more general
environmental monitoring (and especially detection of pollution).
Biology and ecology of aquatic biota relevant to water scarcity
The flow regime is widely regarded to be the key driver of river and floodplain
wetland ecosystems (Bunn and Arthington 2002). Variable flows are a natural
feature of many Australian river systems and aquatic biota have evolved
98
under these conditions. Furthermore, drought forms an integral part of the
Australian climate, and has played an important role in promoting diversity
within its unique aquatic ecosystems (Rose et al. 2008; Sheldon and Thoms
2006). However, there is considerable evidence that human activities across
catchments and in water bodies (i.e. land clearing, grazing, urbanisation, river
regulation, water extraction) have served to exacerbate the impacts of, and
delay the ecological recovery from drought (Bond et al. 2008).
Australian stream biota have adapted to become resistant (able to survive dry
periods) or resilient (have efficient recovery mechanisms) to periods of water
scarcity (Boulton 2003). For example, some macroinvertebrates have drought
resistant traits, such as resistant forms (e.g. cocoons, desiccation resistant
egg masses), spiracular respiration, very large size, aerial dispersal and short
life cycles (Bonada et al. 2007). Once surface flow disappears (as a result of
on-going drought or anthropogenic activity e.g. water abstraction), streams are
often reduced to a series of isolated pools and refugia become critical for the
survival of aquatic organisms (Boulton 2003). Important refugia include the
hyporheic zone and spring-fed pools (for macroinvertebrates and fish), seeps,
leaf litter, dry sediment and exposed riffle zones (dry biofilm) (for algae and
plankton) (Boulton 2003; Magoulick and Kobza 2003; Robson and Matthews
2004).
Mechanisms underlying the impact of water scarcity on in-stream biota
Reduced flow or discharge can lead to changes in physical, chemical and
biological characteristics of stream environments. These changes often
equate to reduced habitat quality or availability for in-stream biota. A
conceptual model for the Cotter River, ACT (Cottingham et al. 2005) illustrates
the mechanisms by which reduced flows may impact on macroinvertebrates
and fish (Figure A3.1).
99
Figure A3.1. Ecological responses expected when flow is reduced in the
Cotter River, ACT (from Cottingham et al. 2005).
Reduced flows result in riparian vegetation encroaching into the channel,
thereby reducing channel capacity (1). Low flows and a reduced frequency of
flushing are considered to have increased the retention of nutrients and fine
sediment, resulting in conditions favourable for the growth of filamentous
algae and biofilms that are unpalatable for macroinvertebrates (2). Reduced
flow also results in armouring, reduced flushing of detritus, nutrients, fine
sediment (3). These changes, along with areas of the streambed becoming
exposed, lead to a reduction in habitat availability and quality for
macroinvertebrates and fish in the substratum (4). Habitat quality may also be
reduced (through changes to water quality) because sediment and organic
matter entering the channel directly from adjacent valley slopes may not be
flushed by low flows in the main channel (Cottingham et al. 2005).
100
In the case of algae and plankton, a conceptual model presented by Burns
and Ryder (2001), which illustrated how changes to flow characteristics (as a
form of physical disturbance) affect biofilms, is also useful for understanding
the mechanism of impact for water scarcity on group of organisms (Figure
A3.2). Flow and water level act as resource modulators for biofilms through
their influence on nutrient and light availability, and by clearing substrata
through scouring and abrasion. Hence, flow regulates accrual of biofilm
biomass in river systems. Currents directly affect biofilms through scour and
substratum loss (which indirectly break boundary layers that impede nutrient
uptake) and by altering light attenuation through differences in loads of
suspended solids.
Based on this conceptual model, it can be inferred that the main mechanisms
by which water scarcity can affect biofilm production is through an increase in
light levels and reduced exposure to substrates. Based on this conceptual
model, it can be inferred that one of the main mechanisms by which water
scarcity can affect biofilm production is through an increase in light levels.
101
Figure A3.2. Components of community structure and function important in
determining biomass, composition and physiology of riverine biofilms. Matter
and energy flow are connected by solid arrows that indicate ‘processes’. The
‘modulators’ of community function are indicated by arrows originating from
small circles (---). Physical disturbances are derived from the community
modulators such as flow (top) and grazers (below). Essential resources for
biofilm growth are shown in the second layer of the diagram (Burns and Ryder
2001).
102
Relationships between hydrology and ecology
A number of studies have investigated relationships between hydrology and
ecology, for in-stream biota. The studies most relevant to the issue of water
scarcity are those that assessed impacts of (a) reduced flows, discharge or
drought, or (b) flow alteration, on in-stream biota. Recent reviews on the
ecological impacts of reduced flows or drought include (Lake 2003),
(Matthews and Marsh-Matthews 2003), (Dewson et al. 2007), (Bond et al.
2008), (Rose et al. 2008). Reviews on the more general issue of flow
alteration include (Petts 1984), (Walker 1985), (Kingsford 2000), (Bunn and
Arthington 2002), (Lloyd et al. 2003), (Biggs et al. 2005), (Welcomme et al.
2006a), and (Poff et al. 2009).
Several examples of quantitative research linking hydrological and ecological
data were also identified:

Macroinvertebrates – (DeGasperi et al. 2009; Gibbins et al. 2001;
Jowett and Duncan 1990; Konrad et al. 2008; Lorenz et al. 2004; Monk
et al. 2006; Rempel et al. 2000; Shivoga 2001)

Fish – (Growns 2008; Kennard et al. 2007; King et al. 2009; Knight et al.
2008; Mannes et al. 2008; Roy et al. 2005)

Algae/Plankton – (Dickerson et al. 2009; Maltchik and Medeiros 2006;
Matveev and Matveeva 2005; Thorp and Mantovani 2005)
The LIFE approach (Lotic-invertebrate Index for Flow Evaluation; (Extence et
al. 1999), for assessing the impact of variable flows on benthic
macroinvertebrate populations, is highly relevant and warrants a more
detailed discussion. The LIFE method was developed using data from a
number of English rivers and is primarily based on the known flow preferences
of selected British benthic macroinvertebrates. Commonly identified British
freshwater species were allocated into one of six flow groups (see Table
A3.1).
103
Table A3.1. Benthic freshwater macroinvertebrate flow groups, ecological
associations and defined current velocities (Extence et al. 1999).
Group
Ecological flow association
Mean current velocity
I
Taxa primarily associated with rapid flows
Typically > 100 cm s-1
II
Taxa primarily associated with moderate to fast
flows
Typically 20–100 cm s-1
III
Taxa primarily associated with slow or sluggish
flows
Typically < 20 cm s-1
IV
Taxa primarily associated with flowing (usually
slow) and standing waters
—
V
Taxa primarily associated with standing waters
—
VI
frequently associated with drying or drought
impacted sites
—
Statistical modelling was used to explore relationships between several
hundred flow variables and LIFE scores. This process identified a subset of
flow variables that were of critical importance in influencing community
structure in different rivers. Combinations of the following flow measures were
examined for comparison with long-term LIFE values:
1. Flow statistics (e.g. percentile flow, mean flow, maximum flow,
minimum flow, etc. Over various time scales);
2. Flow duration (e.g. 90, 120, 150 days, etc);
3. Flow period (e.g. full year, April–September, March–October, etc)
(Extence et al. 1999).
The architects of the LIFE approach advocate that their technique is suitable
for assessing the effects of low flows, as well as abstraction and augmentation
outputs. In addition, they suggest the LIFE method could provide a basis for
setting benchmark flows suitable for protecting and maintaining ecological
integrity (Extence et al. 1999). The LIFE approach has not been adopted by
monitoring agencies in the UK, however, some further research investigating
the application of this technique has been published (e.g. (Clarke et al. 2003;
Greenwood et al. 2006; Monk et al. 2006).
104
Responses of in-stream biota to water scarcity
The effects of reduced flow or drought on in-stream biota are presented in
detail earlier in the report (Table 4.1- 4.4). To recap, the most frequently
reported responses of animals (i.e. macroinvertebrates, fish, other vertebrates
or invertebrates) to water scarcity were (i) decreases in diversity and
abundance, (ii) changes to community composition, (iii) reduced reproductive
success. In particular, riffle habitat specialists tended to be replaced by poolpreferring taxa, as flow or discharge decreased. For algae or plankton,
reduced flow or drought was associated with increases in algal biomass,
decreases in diversity and altered community structure.
Groundwater dependence
Some species of algae and macroinvertebrates may be useful indicators of
groundwater dependency for base flows in rivers (Boulton and Hancock
2006). The river–groundwater connectivity can also create an important habitat
mosaic that sustains biodiversity in floodplains (Brunke et al. 2003).
Riparian bird diversity
Regardless of the habitat type, we know that in Australia, all bird richness is
related to water availability (Hawkins et al. 2005) and there are fewer species
in drier areas (Hawkins et al. 2005). The potential of using all birds as
indicators is highlighted by (Jansen and Robertson 2001) who found that
riparian zones support higher abundance and diversities of birds than nonriparian habitats. There is a clear link between riparian bird communities and
in stream degradation (Hughes et al. 2009) and riparian birds were added to
the list of routine indicators for stream ecosystem bioassessment in Oregon,
USA (Bryce et al. 2002). Yet these links and indicators are always more
generally than just water related stress. The indicator developed by Bryce et
al. (2002) is for generic assessment not just hydrological condition; the link
made by Hughes et al. (2009) results from global and local processes, and the
results from Jansen ad Robertson (2001) are somewhat muddied by grazing
and habitat clearance making them less sensitive to water balance alone.
105
Acknowledgements
Substantial contributions by literature collation and summaries were made by
Kerry Beggs and Nicole McCasker. Expert advice was given by many, but
particular guidance was given by Edward King, Jane Roberts and Neil Sims.
106
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