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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.

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.

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.

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