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Chan T.U.,Monash University | Hart B.T.,Monash University | Kennard M.J.,Griffith University | Kennard M.J.,Commonwealth Environmental Research Facility | And 9 more authors.
River Research and Applications | Year: 2012

This paper reports the development and application of two Bayesian Network models to assist decision making on the environmental flows required to maintain the ecological health of the Daly River (Northern Territory, Australia). Currently, the Daly River is unregulated, with only a small volume of water extracted annually for agriculture. However, there is considerable pressure for further agricultural development in the catchment, particularly with demand for extra water extraction during the dry season (May-November). The abundances of two fish species-barramundi (Lates calcarifer) and sooty grunter (Hephaestus fuliginosus)-were chosen as the ecological endpoints for the models, which linked dry season flows to key aspects of the biology of each species. Where available, data were used to define flow-fish habitat relationships, but most of the relationships were defined by expert opinion because of a lack of quantified ecological knowledge. Recent field data on fish abundances were used to validate the models and gave prediction errors of 20-30%. The barramundi model indicated that the adult sub-population was key to overall fish abundance, with this sub-population particularly impacted by the timing of abstraction (early vs. late dry season). The sooty grunter model indicated that the juvenile sub-population dominated the overall abundance and that this was primarily due to the amount of hydraulically suitable riffle habitat. If current extraction entitlements were fully utilized, the models showed there would be significant impacts on the populations of these two fish species, with the probability of unacceptable abundances increasing to 43% from 25% for sooty grunter and from 36% for barramundi under natural conditions. © 2010 John Wiley & Sons, Ltd.


Catford J.A.,Commonwealth Environmental Research Facility | Catford J.A.,University of Melbourne | Vesk P.A.,University of Melbourne | White M.D.,Arthur Rylah Institute for Environmental Research | And 2 more authors.
Diversity and Distributions | Year: 2011

Aim Biological invasions pose a major conservation threat and are occurring at an unprecedented rate. Disproportionate levels of invasion across the landscape indicate that propagule pressure and ecosystem characteristics can mediate invasion success. However, most invasion predictions relate to species' characteristics (invasiveness) and habitat requirements. Given myriad invaders and the inability to generalize from single-species studies, more general predictions about invasion are required. We present a simple new method for characterizing and predicting landscape susceptibility to invasion that is not species-specific. Location Corangamite catchment (13,340km2), south-east Australia. Methods Using spatially referenced data on the locations of non-native plant species, we modelled their expected proportional cover as a function of a site's environmental conditions and geographic location. Models were built as boosted regression trees (BRTs). Results On average, the BRTs explained 38% of variation in occupancy and abundance of all exotic species and exotic forbs. Variables indicating propagule pressure, human impacts, abiotic and community characteristics were rated as the top four most influential variables in each model. Presumably reflecting higher propagule pressure and resource availability, invasion was highest near edges of vegetation fragments and areas of human activity. Sites with high vegetation cover had higher probability of occupancy but lower proportional cover of invaders, the latter trend suggesting a form of biotic resistance. Invasion patterns varied little in time despite the data spanning 34years. Main conclusions To our knowledge, this is the first multispecies model based on occupancy and abundance data used to predict invasion risk at the landscape scale. Our approach is flexible and can be applied in different biomes, at multiple scales and for different taxonomic groups. Quantifying general patterns and processes of plant invasion will increase understanding of invasion and community ecology. Predicting invasion risk enables spatial prioritization of weed surveillance and control. © 2011 Blackwell Publishing Ltd.


Kennard M.J.,Griffith University | Kennard M.J.,Commonwealth Environmental Research Facility | Mackay S.J.,Griffith University | Pusey B.J.,Griffith University | And 3 more authors.
River Research and Applications | Year: 2010

Hydrologic metrics have been used extensively in ecology and hydrology to summarize the characteristics of riverine flow regimes at various temporal scales but there has been limited evaluation of the sources and magnitude of uncertainty involved in their computation. Variation in bias, precision and overall accuracy of these metrics influences the ability to correctly describe flow regimes, detect meaningful differences in hydrologic characteristics through time and space, and define flow-ecological response relationships. Here, we examine the effects of two primary factors-discharge record length and time period of record-on uncertainty in the estimation of 120 separate hydrologic metrics commonly used by researchers to describe ecologically relevant components of the hydrologic regime. Metric bias rapidly decreased and precision and overall accuracy markedly increased with increasing record length, but tended to stabilize >15 years and did not change substantially >30 years. We found a strong positive relationship between the degree of overlap of discharge record and similarity in hydrologic metrics when based on 15- and 30-year discharge periods calculated within a 36-year temporal window (1965-2000), although hydrologic metrics calculated for a given stream gauge tended to vary only within a restricted range through time. Our study provides critical guidance for selecting an appropriate record length and temporal period of record given a degree of metric bias and precision deemed acceptable by a researcher. We conclude that: (1) estimation of hydrologic metrics based on at least 15 years of discharge record is suitable for use in hydrologic analyses that aim to detect important spatial variation in hydrologic characteristics; (2) metric estimation should be based on overlapping discharge records contained within a discrete temporal window (ideally >50% overlap among records); and (3) metric uncertainty varies greatly and should be accounted for in future analyses. © 2009 John Wiley & Sons, Ltd.


Kennard M.J.,Griffith University | Kennard M.J.,Commonwealth Environmental Research Facility | Pusey B.J.,Griffith University | Pusey B.J.,Commonwealth Environmental Research Facility | And 4 more authors.
Freshwater Biology | Year: 2010

The importance of hydrologic variability for shaping the biophysical attributes and functioning of riverine ecosystems is well recognised by ecologists and water resource managers. In addition to the ecological dependences of flow for aquatic organisms, human societies modify natural flow regimes to provide dependable ecological services, including water supply, hydropower generation, flood control, recreation and navigation. Management of scarce water resources needs to be based on sound science that supports the development of environmental flow standards at the regional scale. 2. Hydrological classification has long played an essential role in the ecological sciences for understanding geographic patterns of riverine flow variability and exploring its influence on biological communities, and more recently, has been identified as a critical process in environmental flow assessments. 3. We present the first continental-scale classification of hydrologic regimes for Australia based on 120 metrics describing ecologically relevant characteristics of the natural hydrologic regime derived from discharge data for 830 stream gauges. Metrics were calculated from continuous time series (15-30 years of record constrained within a 36-year period) of mean daily discharge data, and classification was undertaken using a fuzzy partitional method - Bayesian mixture modelling. 4. The analysis resulted in the most likely classification having 12 classes of distinctive flow-regime types differing in the seasonal pattern of discharge, degree of flow permanence (i.e. perennial versus varying degrees of intermittency), variations in flood magnitude and frequency and other aspects of flow predictability and variability. Geographic, climatic and some catchment topographic factors were generally strong discriminators of flow-regime classes. The geographical distribution of flow-regime classes showed varying degrees of spatial cohesion, with stream gauges from certain flow-regime classes often being non-contiguously distributed across the continent. These results support the view that spatial variation in hydrology is determined by interactions among climate, geology, topography and vegetation at multiple spatial and temporal scales. Decision trees were also developed to provide the ability to determine the natural flow-regime class membership of new stream gauges based on their key environmental and/or hydrological characteristics. 5. The need to recognise hydrologic variation at multiple spatial scales is an important first step to setting regional-scale environmental flow management strategies. We expect that the classification produced here can underpin the development of a greater understanding of flow-ecology relationships in Australia, and management efforts aimed at prescribing environmental flows for riverine restoration and conservation. © 2009 Blackwell Publishing Ltd.

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