Human impacts on freshwater biota are often assessed by comparisons with regional reference sites judged to be free or nearly free from the influence of stressors of concern. These comparisons may involve predictive models that extrapolate from reference-site data to estimate the biota that would occur at each assessment site in the absence of the stressors. This extrapolation often involves selection or weighting of data from particular reference sites, but it is seldom demonstrated whether this process results in a more accurate, precise and sensitive assessment than would be achieved from comparison with a simple unweighted combination of data from all reference sites, that is a null model. In addition, predictive models often rely on additive combinations of environmental predictor variables, but such combinations may poorly represent the natural control of spatial variation in biological communities by multiple limiting factors. In this paper, we describe a different type of reference-site approach, based on the concept of limiting environmental differences (LEDs) as natural constraints on biological similarity among sites. In this method, an assessment site is compared with a sub-set of environmentally matched reference sites selected by application of LED criteria to individual environmental variables. We illustrate this approach by its application to a potentially subtle impact: the effect of water abstraction on fish assemblages in unregulated streams in northeastern New South Wales, Australia. We compared (1) a LED-based predictive model, (2) a null model and (3) a model based on cluster analysis and multiple discriminant analysis in the style of the widely followed River Invertebrate Prediction and Classification System (RIVPACS). The LED-based model was about as accurate as the RIVPACS-type model and the most precise and sensitive of the three, being best able to distinguish sites where fish assemblages departed from reference status.

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The physical, chemical and biological characteristics of 65 farm ponds in the Northern Tablelands and Central Western Slopes regions of New South Wales, Australia, were similar to those recorded for Australian ponds in other studies. The strongest single relationship between physico-chemical characteristics and biological characteristics was for high abundance of phytoplankton, low abundance of macrophytes, high turbidity, and high nutrient concentrations in ponds on granitic soil. Variation among the ponds was such that no other relationship was significant. Five groups of ponds were discerned on the basis of their biological and physico-chemical characteristics. One group could be classed as reasonably ‘pristine’, with high water clarity and high abundance of macrophytes; another group presented highly eutrophic, phytoplankton-dominated conditions. Ponds in these two groups can be described as being in ‘alternative stable states’. A third group had been modified with the intention of improving the appearance or utility of the ponds. The last two groups identified in this analysis had no specific parallels in the literature. Abundance of macrophytes was related to good water quality, and encouragement of increased abundance of submerged plants in farm ponds could result in improved water quality.

Aquatic and amphibious macrophytes were surveyed during two seasons at 85 sites on unregulated streams in northeastern New South Wales, Australia, during a period of prolonged and recurring drought. Fifty-four of these sites were designated as reference sites with respect to water abstraction because upstream entitlement for abstraction was less than 1% of their mean annual flow (MAF). The remaining sites had an average of 4% of MAF licensed for upstream abstraction (range 1-20%). No statistically significant overall difference in macrophyte assemblage diversity (number of taxa) or composition was detected between reference and non-reference sites. When each non-reference site was compared with those particular reference sites that it most resembled in non-hydrological environmental features relevant to macrophyte assemblages, the similarity between observed and reference data was unrelated to the amount of upstream entitlement for abstraction. The lack of any evident impact on macrophyte assemblages was attributed mainly to the relatively small proportion of flow licensed for abstraction, the fact that the study sites did not dry completely, and the resilience of stream macrophytes to drought. However, the difficulty in distinguishing abstraction impacts from high background spatial variability in macrophyte assemblages may also have been influential.

To reduce endosulfan (C9H6O3Cl6S; 6,7,8,9,10,10-hexachloro-1,5, 5a,6,9,9a-hexahydro-6,9-methano-2,4,3-benzodioxathiepin 3-oxide) contamination in rivers and waterways, it is important to know the relative significances of airborne transport pathways (including spray drift, vapor transport, and dust transport) and waterborne transport pathways (including overland and stream runoff). This work uses an integrated modeling approach to assess the absolute and relative contributions of these pathways to riverine endosulfan concentrations. The modeling framework involves two parts: a set of simple models for each transport pathway, and a model for the physical and chemical processes acting on endosulfan in river water. An averaging process is used to calculate the effects of transport pathways at the regional scale. The results show that spray drift, vapor transport, and runoff are all significant pathways. Dust transport is found to be insignificant. Spray drift and vapor transport both contribute low-level but nearly continuous inputs to the riverine endosulfan load during spraying season in a large cotton (Gossypium hirsutum L.)-growing area, whereas runoff provides occasional but higher inputs. These findings are supported by broad agreement between model predictions and observed typical riverine endosulfan concentrations in two rivers.