A new approach to determining environmental flow requirements : sustaining the natural values of floodplains of the southern Murray-Darling Basin

Large overbank flood events play an important role in maintaining largescale ecological processes and connectivity along and across the floodplains and between the rivers and their floodplains in the southern Murray-Darling Basin. However, the regulation of rivers means that extensive overbank flooding can only occur in the rare circumstance of extreme flood events. Recent environmental water allocations have focussed on the largest floodplain blocks (‘icon’ sites) and a small set of specific values (e.g. colonial nesting waterbirds), as well as on trialling fine-scale manipulation of infrastructure (e.g. pumping) to water relatively small areas. There has been no comprehensive systematic assessment of the entire floodplain and its wider set of flood-dependent natural assets (such as ecosystems and species; herein referred to as ‘natural values’) to maximise the effectiveness of environmental water use and to catalogue values likely to be lost. This paper describes an assessment of some 220 000 ha found to support flood-dependent natural values in Victoria. We mapped the geographic distribution and estimated components of the flooding requirements (natural flooding frequency, and maximum period without flooding and minimum duration of each flooding event before significant deterioration) for each natural value. Using an example of one stretch of the River Murray, we show how the resultant spatial data can be used with floodplain inundation modelling to compare the outcomes of real or planned environmental watering events; potentially providing tools for management agencies to conserve a wider range of floodplain values than is currently the case. That is, water managers and the public can see what ecosystems and threatened species are intended to be maintained by environmental watering and what values are intended to be abandoned across the whole floodplain, rather than just seeing the small subset of values and ‘icon’ sites that are intended to be maintained. Examples are provided to illustrate how information about the location, water requirements and extent covered by potential floods for specific values can be used to build adaptive watering strategies for areas as large as the whole floodplain.

Linking water-resource models to ecosystem-response models to guide water-resource planning -- an example from the Murray--Darling Basin, Australia

Objectively assessing ecological benefits of competing watering strategies is difficult. We present a framework of coupled models to compare scenarios, using the Coorong, the estuary for the MurrayDarling River system in South Australia, as a case study. The framework links outputs from recent modelling of the effects of climate change on water availability across the MurrayDarling Basin to a hydrodynamic model for the Coorong, and then an ecosystem-response model. The approach has significant advantages, including the following: (1) evaluating management actions is straightforward because of relatively tight coupling between impacts on hydrology and ecology; (2) scenarios of 111 years reveal the impacts of realistic climatic and flow variability on Coorong ecology; and (3) ecological impact is represented in the model by a series of ecosystem states, integrating across many organisms, not just iconic species. We applied the approach to four flow scenarios, comparing conditions without development, current water-use levels, and two predicted future climate scenarios. Simulation produced a range of hydrodynamic conditions and consequent distributions of ecosystem states, allowing managers to compare scenarios. This approach could be used with many climates and/or management actions for optimisation of flow delivery to environmental assets.

Genetic analyses reveal limited dispersal and recovery potential in the large freshwater crayfish Euastacus armatus from the southern Murray-Darling Basin

Understanding dispersal traits and adaptive potential is critically important when assessing the vulnerability of freshwater species in highly modified ecosystems. The present study investigates the population genetic structure of the Murray crayfish Euastacus armatus in the southern Murray–Darling Basin. This species has suffered significant population declines in sections of the Murray River in recent years, prompting the need for information on natural recruitment processes to help guide conservation. We assessed allele frequencies from 10 polymorphic microsatellite loci across 20 sites encompassing the majority of the species’ range. Low levels of gene flow were observed throughout hydrologically connected waterways, but significant spatial autocorrelation and low migration rate estimates reflect local genetic structuring and dispersal limitations, with home ranges limited to distances <50-km. Significant genetic differentiation of headwater populations upstream of barriers imposed by impoundments were also observed; however, population simulations demonstrate that these patterns likely reflect historical limitations to gene flow rather than contemporary anthropogenic impacts. Dispersal limitations, coupled with its biological traits, suggest that local populations are vulnerable to environmental disturbance with limited potential for natural recolonisation following population decline. We discuss the implications of these findings in the context of managing the recovery of the species.

Bayesian clustering with AutoClass explicitly recognises uncertainties in landscape classification

Clustering of multivariate data is a commonly used technique in ecology, and many approaches to clustering are available. The results from a clustering algorithm are uncertain, but few clustering approaches explicitly acknowledge this uncertainty. One exception is Bayesian mixture modelling, which treats all results probabilistically, and allows comparison of multiple plausible classifications of the same data set. We used this method, implemented in the AutoClass program, to classify catchments (watersheds) in the Murray Darling Basin (MDB), Australia, based on their physiographic characteristics (e.g. slope, rainfall, lithology). The most likely classification found nine classes of catchments. Members of each class were aggregated geographically within the MDB. Rainfall and slope were the two most important variables that defined classes. The second-most likely classification was very similar to the first, but had one fewer class. Increasing the nominal uncertainty of continuous data resulted in a most likely classification with five classes, which were again aggregated geographically. Membership probabilities suggested that a small number of cases could be members of either of two classes. Such cases were located on the edges of groups of catchments that belonged to one class, with a group belonging to the second-most likely class adjacent. A comparison of the Bayesian approach to a distance-based deterministic method showed that the Bayesian mixture model produced solutions that were more spatially cohesive and intuitively appealing. The probabilistic presentation of results from the Bayesian classification allows richer interpretation, including decisions on how to treat cases that are intermediate between two or more classes, and whether to consider more than one classification. The explicit consideration and presentation of uncertainty makes this approach useful for ecological investigations, where both data and expectations are often highly uncertain.

Differential macrohabitat use by birds on an unregulated lowland floodplain of south-eastern Australia

In many lowland floodplains around the world, upriver interferences to flows (weirs, dams, off-takes) have led to much reduced frequency and duration of flooding. As a result, many floodplain wetlands are now inundated relatively rarely if at all. Given regulation of most lowland rivers in southeastern Australia, we assessed use of wetlands by birds in the essentially unregulated Ovens River in northeastern Victoria. Twelve sites (0.4-1.2 ha) were studied after flooding. Four sites were 'permanent billabongs', four were temporary wetlands and the other four were randomly selected woodland sites >60 m from the nearest water body (including the river) acting as 'control' or 'reference' sites. Aquatic birds were not recorded using woodland sites, but many species were differentially associated with either billabongs or temporary wetlands. A surprising number of non-aquatic birds either exclusively or differentially were associated with wetland sites compared with woodland sites. We concluded that heterogeneous macrohabitat will increase local avian biodiversity on lowland floodplains. Moreover, densities and diversity of non-aquatic, woodland species also increased with the presence of wetlands. Temporary wetlands were used differently from permanent billabongs by birds, especially in foraging methods. This suggests that the reinstatement of major flooding on heavily regulated floodplains would be ecologically advantageous for birds by providing foraging and breeding opportunities.

Temporal changes in macroinvertebrate assemblages following experimental flooding in permanent and temporary wetlands in an Australian floodplain forest

The River Murray, Australia, is a highly regulated river from which almost 80% of mean annual flow is removed for human use, primarily irrigated agriculture. Consequent changes to the pattern and volume of river flow are reflected in floodplain hydrology and, therefore, the wetting/drying patterns of floodplain wetlands. To explore the significance of these changes, macroinvertebrate samples were compared between permanent and temporary wetlands following experimental flooding in a forested floodplain of the River Murray. Weekly samples from two permanent wetlands and four associated temporary sites were used to track changes in macroinvertebrate assemblage composition. Non-metric multidimensional scaling was used to ordinate the macroinvertebrate data, indicating consistent differences between the biota of permanent and temporary wetlands and between the initial and later assemblages in the temporary sites. There were marked changes over time, but little sign that the permanent and temporary assemblages were becoming more alike over the 25-week observation period. The apparent heterogeneity of these systems is of particular importance in developing river management plans which are likely to change flooding patterns. Such plans need to maintain a mosaic of wetland habitats if floodplain biodiversity is to be supported.

Bayesian classification of catchments using spatial data: a first step to improved modelling of catchment effects on stream ecological condition

A major challenge facing freshwater ecologists and managers is the development of models that link stream ecological condition to catchment scale effects, such as land use. Previous attempts to make such models have followed two general approaches. The bottom-up approach employs mechanistic models, which can quickly become too complex to be useful. The top-down approach employs empirical models derived from large data sets, and has often suffered from large amounts of unexplained variation in stream condition.

We believe that the lack of success of both modelling approaches may be at least partly explained by scientists considering too wide a breadth of catchment type. Thus, we believe that by stratifying large sets of catchments into groups of similar types prior to modelling, both types of models may be improved. This paper describes preliminary work using a Bayesian classification software package, ‘Autoclass’ (Cheeseman and Stutz 1996) to create classes of catchments within the Murray Darling Basin based on physiographic data.

Autoclass uses a model-based classification method that employs finite mixture modelling and trades off model fit versus complexity, leading to a parsimonious solution. The software provides information on the posterior probability that the classification is ‘correct’ and also probabilities for alternative classifications. The importance of each attribute in defining the individual classes is calculated and presented, assisting description of the classes. Each case is ‘assigned’ to a class based on membership probability, but the probability of membership of other classes is also provided. This feature deals very well with cases that do not fit neatly into a larger class. Lastly, Autoclass requires the user to specify the measurement error of continuous variables.

Catchments were derived from the Australian digital elevation model. Physiographic data werederived from national spatial data sets. There was very little information on measurement errors for the spatial data, and so a conservative error of 5% of data range was adopted for all continuous attributes. The incorporation of uncertainty into spatial data sets remains a research challenge.

The results of the classification were very encouraging. The software found nine classes of catchments in the Murray Darling Basin. The classes grouped together geographically, and followed altitude and latitude gradients, despite the fact that these variables were not included in the classification. Descriptions of the classes reveal very different physiographic environments, ranging from dry and flat catchments (i.e. lowlands), through to wet and hilly catchments (i.e. mountainous areas). Rainfall and slope were two important discriminators between classes. These two attributes, in particular, will affect the ways in which the stream interacts with the catchment, and can thus be expected to modify the effects of land use change on ecological condition. Thus, realistic models of the effects of land use change on streams would differ between the different types of catchments, and sound management practices will differ.

A small number of catchments were assigned to their primary class with relatively low probability. These catchments lie on the boundaries of groups of catchments, with the second most likely class being an adjacent group. The locations of these ‘uncertain’ catchments show that the Bayesian classification dealt well with cases that do not fit neatly into larger classes.

Although the results are intuitive, we cannot yet assess whether the classifications described in this paper would assist the modelling of catchment scale effects on stream ecological condition. It is most likely that catchment classification and modelling will be an iterative process, where the needs of the model are used to guide classification, and the results of classifications used to suggest further refinements to models.

Bearing the risk : learning to be drier mid-river

This paper investigates learning related to the phenomena of drying over the past decade in the southern Murray-Darling Basin in Australia, as perceived in a mid-river site within the western Riverina of New South Wales, Australia. The insights from audio-recorded interviews, with a wide range of adults across the water-dependent community, mostly relate to the catchment of the  Murrumbidgee River in the Shire of Hay. Our overarching theme is about how  people are learning about, understanding and bearing the risks, of what is widely regarded as a prolonged drought. For some, the learning is about how to cope with less water in the Basin, and particularly from the river, as predicted in the climate change literature. Our narrative-based, empirical research registers the felt experience of those located, in situ, as a severe ‘irrigation drought’ extends into 2009. The paper dramatises the many obstacles to learning how to think and act differently, in difficult and rapidly changing ecosocial circumstances.

Wetland conservation in the Murray–Darling Basin – is it going down the drain?

This Editorial aims to highlight one of the most serious threats to Australian avifauna in recent times.

Droughts, floods and freshwater ecosystems : evaluating climate change impacts and developing adaptation strategies

Climate change is expected to have significant impacts on hydrologic regimes and freshwater ecosystems, and yet few basins have adequate numerical models to guide the development of freshwater climate adaptation strategies. Such strategies can build on existing freshwater conservation activities, and incorporate predicted climate change impacts. We illustrate this concept with three case studies. In the Upper Klamath Basin of the western USA, a shift in land management practices would buffer this landscape from a declining snowpack. In the Murray–Darling Basin of south-eastern Australia, identifying the requirements of flood-dependent natural values would better inform the delivery of environmental water in response to reduced runoff and less water. In the Savannah Basin of the south-eastern USA, dam managers are considering technological and engineering upgrades in response to more severe floods and droughts, which would also improve the implementation of recommended environmental flows. Even though the three case studies are in different landscapes, they all contain significant freshwater biodiversity values. These values are threatened by water allocation problems that will be exacerbated by climate change, and yet all provide opportunities for the development of effective climate adaptation strategies.