Effect-based monitoring of two rivers under urban and agricultural influence reveals a range of biological activities in sediment and water extracts.

Chemical contaminants, such as pesticides, pharmaceuticals and industrial compounds are ubiquitous in surface water and sediment in areas subject to human activity. While targeted chemical analysis is typically used for water and sediment quality monitoring, there is growing interest in applying effect-based methods with in vitro bioassays to capture the effects of all active contaminants in a sample. The current study evaluated the biological effects in surface water and sediment from two contrasting catchments in Aotearoa New Zealand, the highly urbanised Whau River catchment in Tamaki Makaurau (Auckland) and the urban and mixed agricultural Koreti (New River) Estuary catchment. Two complementary passive sampling devices, Chemcatcher for polar chemicals and polyethylene (PED) for non-polar chemicals, were applied to capture a wide range of contaminants in water, while composite sediment samples were collected at each sampling site. Bioassays indicative of induction of xenobiotic metabolism, receptor-mediated effects, genotoxicity, cytotoxicity and apical effects were applied to the water and sediment extracts. Most sediment extracts induced moderate to strong estrogenic and aryl hydrocarbon (AhR) activity, along with moderate toxicity to bacteria. The water extracts showed similar patterns to the sediment extracts, but with lower activity. Generally, the polar Chemcatcher extracts showed greater estrogenic activity, photosynthesis inhibition and algal growth inhibition than the non-polar PED extracts, though the PED extracts showed greater AhR activity. The observed effects in the water extracts were compared to available ecological effect-based trigger values (EBT) to evaluate the potential risk. For the polar extracts, most sites in both catchments exceeded the EBT for estrogenicity, with many sites exceeding the EBTs for AhR activity and photosynthesis inhibition. Of the wide range of endpoints considered, estrogenic activity, AhR activity and herbicidal activity appear to be the primary risk drivers in both the Whau and Koreti Estuary catchments.

Evaluating statistical model performance in water quality prediction.

Exposure to contaminated water while swimming or boating or participating in other recreational activities can cause gastrointestinal and respiratory disease. It is not uncommon for water bodies to experience rapid fluctuations in water quality, and it is therefore vital to be able to predict them accurately and in time so as to minimise population's exposure to pathogenic organisms. E. coli is commonly used as an indicator to measure water quality in freshwater, and higher counts of E. coli are associated with increased risk to illness. In this case study, we compare the performance of a wide range of statistical models in prediction of water quality via E. coli levels for the weekly data collected over the summer months from 2006 to 2014 at the recreational site on the Oreti river in Wallacetown, New Zealand. The models include naive model, multiple linear regression, dynamic regression, regression tree, Markov chain, classification tree, random forests, multinomial logistic regression, discriminant analysis and Bayesian network. The results show that Bayesian network was superior to all the other models. Overall, it had a leave-one-out and k-fold cross validation error rate of 21%, while predicting the majority of instances of E. coli levels classified as unsafe by the Microbiological Water Quality Guidelines for Marine and Freshwater Recreational Areas 2003, New Zealand. Because Bayesian networks are also flexible in handling missing data and outliers and allow for continuous updating in real time, we have found them to be a promising tool, and in the future, plan to extend the analysis beyond the current case study site.

Concentrations of Campylobacter spp., Escherichia coli, Enterococci, and Yersinia spp. in the Feces of Farmed Red Deer in New Zealand.

Intensive deer farming can cause environmental issues, mainly by its impact on soils and water quality. In particular, there is a risk to the microbial quality of water, as high quantities of suspended sediment and fecal bacteria can enter into water systems. The feces of farmed red deer (, = 206) from Canterbury and Southland, New Zealand, were analyzed with regard to the presence of spp., , enterococci, and spp.. Enterococci and were isolated from all samples, with mean concentrations of 4.5 × 10 (95% CI 3.5 × 10, 5.6 10) and 1.3 × 10 (95% CI 1.1 × 10, 1.5 × 10) per gram of dry feces, respectively. spp. were isolated from 27 fecal samples, giving an overall prevalence of 13.1%. isolation rates were variable within and between regions (Canterbury 7.95% [95% CI 2-14%], Southland 16.95% [95% CI 10-24%]). Five out of 42 composite samples were positive for , and one sample for The overall prevalence ranges on a per-animal basis were therefore 2.43 to 11.17% and 0.49 to 2.91%, respectively. This study is the first to quantify the concentration of spp. present in healthy deer farmed in New Zealand. Deer feces are a potential source of human campylobacteriosis, with all genotypes isolated also previously observed among human cases. The fecal outputs from deer should be regarded as potentially pathogenic to humans and therefore be appropriately managed.

Monthly sampling reveals seasonal fine sediment fluctuations and riverine invertebrate community responses.

Managing the impacts of anthropogenically enhanced deposited fine sediment levels in lotic ecosystems requires understanding of how catchment land-use changes have altered the natural sediment regime (erosion, transport, deposition) of rivers. Unfortunately, no existing studies have employed an appropriate sampling frequency over a period encompassing the full range of seasonal flow conditions expected to influence in-stream sediment dynamics. We determined the short-term (monthly) dynamics of deposited fine sediment and invertebrate communities over 12-months in 15 fourth- and fifth-order rivers draining catchments of low, medium and high land-use intensity in Southland, New Zealand to determine when and where fine sediment threatens stream health. We compared the Quorer resuspension method (suspendable inorganic sediment, SIS) and the in-stream visual sediment cover assessment method, and evaluated the effectiveness of four commonly-used invertebrate stream health metrics against their newly developed sediment-specific counterparts. Monthly variability in SIS was substantial across all land-use categories, but became more pronounced as land-use intensity increased. All 15 sites experienced a prolonged period of relatively stable flow which coincided with the largest short-term increase in SIS at 14 of the 15 sites. However, variability in SIS was not mirrored in macroinvertebrate metrics. These findings suggest that controlling inputs of fine sediment to rivers and streams will be most effective when targeted at periods of prolonged stable flow, particularly within high land-use intensity catchments. The resuspension method consistently outperformed visual estimates when considering its relationship with macroinvertebrate metrics, while sediment-specific metrics demonstrated a stronger association with fine sediment than commonly employed metrics e.g. (%EPT). We conclude that restoration/mitigation practices cannot be based solely on short-term, or even long-term, reductions in fine sediment, or on physical measures alone, but should be based on long-term recoveries of sediment-impacted invertebrate communities using concurrent measurements of both biotic and abiotic conditions.