Abstract. River health monitoring traditionally has made use of structural measurements (water quality or taxonomic composition of aquatic organisms). We argue that a more complete assessment of river health should include functional metrics, such as rates of organic matter decomposition and ecosystem metabolism. Leaf breakdown links the characteristics of riparian vegetation with the activity of both aquatic invertebrates and microbial organisms and is affected by natural and human-induced variation in a wide range of environmental factors. Measurement of leaf breakdown is relatively simple and has modest equipment requirements. River metabolism (gross primary productivity and ecosystem respiration) measures the rates of production and use of organic C in river ecosystems as a whole, providing a direct estimate of the food base that determines life-supporting capacity. Metabolism measurements require more sophisticated equipment than do measurements of leaf breakdown, but improvements in technology have made metabolism measurements relatively easy. We review the factors that influence leaf breakdown and river metabolism and pay particular attention to the effects of human-induced environmental stressors. We also describe how measurements can be standardized and suggest criteria for interpreting functional measures in terms of river ecosystem health. Last, we consider the strengths and weaknesses of both methods as functional measures and provide recommendations for their use as biomonitoring tools.

1. Modification of natural landscapes and land-use intensification are global phenomena that can result in a range of differing pressures on lotic ecosystems. We analysed national-scale databases to quantify the relationship between three land uses (indigenous vegetation, urbanisation and agriculture) and indicators of stream ecological integrity. Boosted regression tree modelling was used to test the response of 14 indicators belonging to four groups -water quality (at 578 sites), benthic invertebrates (at 2666 sites), fish (at 6858 sites) and ecosystem processes (at 156 sites). Our aims were to characterise the ecological response curves of selected functional and structural metrics in relation to three land uses, examine the environmental moderators of these relationships and quantify the relative utility of metrics as indicators of stream ecological integrity. 2. The strongest indicators of land-use effects were nitrate + nitrite, delta-15 nitrogen value (d 15 N) of primary consumers and the Macroinvertebrate Community Index (a biotic index of organic pollution), while the weakest overall indicators were gross primary productivity, benthic invertebrate richness and fish richness. All indicators declined in response to removal of indigenous vegetation and urbanisation, while variable responses to agricultural intensity were observed for some indicators. 3. The response curves for several indicators suggested distinct thresholds in response to urbanisation and agriculture, specifically at 10% impervious cover and at 0.1 g m )3 nitrogen concentration, respectively. 4. Water quality and ecosystem process indicators were influenced by a combination of temperature, slope and flow variables, whereas for macroinvertebrate indicators, catchment rainfall, segment slope and temperature were significant environmental predictor variables. Downstream variables (e.g. distance to the coast) were significant in explaining residual variation in fish indicators, not surprisingly given the preponderance of diadromous fish species in New Zealand waterways. The inclusion of continuous environmental variables used to develop a stream typology improved model performance more than the inclusion of stream type alone. 5. Our results reaffirm the importance of accounting for underlying spatial variation in the environment when quantifying relationships between land use and the ecological integrity of streams. Of distinctive interest, however, were the contrasting and complementary responses of different indicators of stream integrity to land use, suggesting that multiple indicators are required

Summary 1. The value of measuring ecosystem functions in regular monitoring programs is increasingly being recognised as a potent tool for assessing river health. We measured the response of ecosystem metabolism, organic matter decomposition and strength loss, and invertebrate community composition across a gradient of catchment impairment defined by upstream landuse stress in two New Zealand streams. This was performed to determine if there were consistent responses among contrasting functional and structural indicators. 2. Rates of gross primary production (GPP) and ecosystem respiration (ER) ranged from 0.1 to 7.0 gO2 m−2 day−1 and from 0.34 to 16.5 gO2 m−2 day−1 respectively. Rates of GPP were variable across the landuse stress gradient, whereas ER increased linearly with the highest rates at the most impacted sites. Production/respiration (P/R) and net ecosystem metabolism (NEM) indicated that sites at the low and high ends of the stress gradient were heterotrophic with respiration rates presumably relying on organic matter from upstream sources, adjacent land or point sources. Sites with moderate impairment were predominantly autotrophic. 3. Declines in the tensile strength of the cotton strips showed no response across part of the gradient, but a strong response among the most impaired sites. The rate of mass loss of wooden sticks (Betula platyphylla Sukaczev) changed from a linear response to a U‐shaped response across the impairment gradient after water temperature compensation, whereas leaf breakdown at a subset of sites suggested a linear loss in mass per degree‐day. Three macroinvertebrate metrics describing the composition of the invertebrate community and its sensitivity to pollution showed similar linear inverse responses to the landuse stress gradient. 4. The first axis of a redundancy analysis indicated an association between landuse stress and various measures of water quality, and wooden stick mass loss, the invertebrate metric % EPT [percentage of macroinvertebrate taxa belonging to the Ephemeroptera, Plecoptera and Trichoptera (excluding Hydroptilidae] taxa, P/R and NEM, supporting the utility of these structural and functional metrics for assessing degree of landuse stress. The second axis was more strongly associated with catchment size, ER and GPP which suggests that these indicators were responding to differences in stream size. 5. Our results suggest that nonlinear responses to catchment impairment need to be considered when interpreting measurements of ecosystem function. Functional indicators could be useful for detecting relatively subtle changes where the slope of the response curve is maximised and measurements at the low and high ends of the impairment gradient are roughly equivalent. Such responses may be particularly valuable for detecting early signs of degradation at high quality sites, allowing management responses to be initiated before the degradation becomes too advanced, or for detecting initial moves away from degraded states during the early stages of restoration. Close ...

We tested the assumptions and predictions of a foraging model for drift-feeding fish. We used three-dimensional videography to describe the foraging behavior of brown trout, Salmo trutta, mapped water depth and velocity in their foraging area, sampled invertebrate drift to determine length class specific drift densities, and captured trout to determine the size composition of their diet. The model overestimated the fish's prey capture rate and gross energy intake rate by a factor of two. Most of this error resulted from the fact that prey detection probabilities within the fish's foraging area averaged only half the expected value. This was the result of a rapid decrease in capture probability with increasing lateral distance from the fish's focal point. Some of the model's assumptions were accurate: equations for predicting reaction distance and minimum prey size supported reliable predictions of the shape and size of the fish's foraging area and the size composition of the diet. Other assumptions were incorrect: fish detected prey within the predicted reaction volume, not on its upstream surface as expected, fish intercepted prey more slowly than the expected maximum sustainable swimming speed, and fish captured about two-thirds of their prey downstream of their focal point, rather than upstream.

Benthic Phormidium mats can contain high concentrations of the neurotoxins anatoxin-a and homoanatoxin-a. However, little is known about the co-occurrence of anatoxin-producing and non-anatoxin-producing strains within mats. There is also no data on variation in anatoxin content among toxic genotypes isolated from the same mat. In this study, 30 Phormidium strains were isolated from 1 cm2 sections of Phormidium-dominated mats collected from three different sites. Strains were grown to stationary phase and their anatoxin-a, homoanatoxin-a, dihydroanatoxin-a and dihydrohomoanatoxin-a concentrations determined using liquid chromatography-mass spectrometry. Each strain was characterized using morphological and molecular (16S rRNA gene sequences) techniques. Eighteen strains produced anatoxin-a, dihydroanatoxin-a or homoanatoxin-a. Strains isolated from each mat either all produced toxins, or were a mixture of anatoxin and non-anatoxin-producing genotypes. Based on morphology these genotypes could not be separated. The 16S rRNA gene sequence comparisons showed a difference of at least 17 nucleotides among anatoxin and non-anatoxin-producing strains and these formed two separate sub-clades during phylogenetic analysis. The total anatoxin concentration among toxic strains varied from 2.21 to 211.88 mg kg−1 (freeze dried weight), representing a 100 fold variation in toxin content. These data indicate that both the relative abundance of anatoxin and non-anatoxin-producing genotypes, and variations in anatoxin producing capability, can influence the overall toxin concentration of benthic Phormidium mat samples.

1.We compare the rates and mechanisms of processing of tussock {Chionochloa spp.) leaf litter in six New Zealand streams draining grassland catchments that contrast in the extent to which they have been developed for pasture. 2. Rates of processing, measured as rate of weight loss of leaf packs and rate of leaf softening, were at the slow end of the spectrum for vascular plant processing. Processing was faster at developed sites, mediated mainly through the influence of oxidized nitrogen concentration on microbial activity. 3. Few invertebrate shredders colonized leaf packs and it is unlikely that invertebrates had an appreciable effect on leaf processing in our study streams, which do not effectively retain leaf litter. Very small headwater tributaries appear to retain leaf litter and possess a more abundant shredder community. 4. Measures of leaf processing in our six streams were significantly correlated with Petersen's (1992) RCE score of stream condition. We discuss the potential for using rate of leaf litter processing as a method of bioassessment. 5. Even the most degraded stream in our study is classed as 'good' using the RCE inventory system. Human impact in the Taieri River is relatively small compared with the degradation observed in some parts of the world.

1. Broad-scale assessment of stream health is often based on correlative relationships between catchment land-use categories and measurements of stream biota or water chemistry. Few studies have attempted to characterise the response curves that describe how measures of ecosystem function change along gradients of catchment land use, or explored how these responses vary at broad spatial scales. 2. In autumn 2008, we conducted a survey of 84 streams in three bioregions of New Zealand to assess the sensitivity of functional indicators to three land-use gradients: percentage of native vegetation cover, percentage of impervious cover (IC) and predicted nitrogen (N) concentration. We examined these relationships using general linear models and boosted regression trees to explore monotonic, non-monotonic and potential threshold components of the response curves. 3. When viewing the responses to individual land-use gradients, four of five functional indicators were positively correlated with the removal of native vegetation cover and N. In general, weaker and less responsive models were observed for the IC gradient. An analysis of the response to multiple stressors showed d 15 N of primary consumers and gross primary productivity (GPP) to be the most responsive functional indicators to land-use gradients. The multivariate models identified thresholds for change in the relationship between the functional indicators and all three land-use gradients. Apparent thresholds were <10% IC, between 40 and 80% loss of native vegetation cover and at 0.5 and 3.2 mg L )1 N. 4. The strength of regression models and the nature of the response curves suggest that measures of ecosystem function exhibit predictable relationships with land use. Furthermore, the responses of functional indicators varied little among three bioregions. This information provides a strong argument for the inclusion of functional indicators in a holistic assessment of stream health.

Scientific monitoring of river health is well established and has a significant role to play in environmental assessment by communities, managers and policy makers. Cultural indicators help to articulate cultural values, assess the state of the environment from a cultural perspective and assist with establishing a role for Māori in environmental monitoring. We reviewed the philosophies behind cultural and scientific monitoring of river health and compared the results from the two approaches at 25 sites in the Motueka and Riwaka catchments. Both scientific and cultural indicators suggested a decrease in river health in relation to increased land-use pressure. There were also correlations between the results from the two approaches suggesting cultural indicators could be used in a similar manner as scientific indicators to set environmental benchmarks. Using scientific approaches alongside culturally based monitoring provides a wealth of knowledge to understand better what we mean by river health. The two approaches can be regarded as complementary and reflect two different knowledge systems and perspectives.