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Gully erosion is a significant source of fine suspended sediment (<63 μm) and associated nutrient pollution to freshwater and marine waterways. Researchers, government agencies, and monitoring groups are currently using monitoring methods designed for streams and rivers (e.g., autosamplers, rising stage samplers, and turbidity loggers) to evaluate suspended sediment in gullies. This is potentially problematic because gullies have several hydrological features and monitoring operational challenges that differ to those of continually flowing streams and rivers (e.g., short and intense flows, high suspended sediment concentrations, and rapid scouring and aggradation). Here we present a laboratory and field‐based assessment of the performance of common suspended sediment monitoring techniques applied to gullies. We also evaluate a recently‐described method; the pumped active suspended sediment (PASS) sampler, which has been modified for monitoring suspended sediment in gully systems. Discrete autosampling provided data at high temporal resolution, however, it had poor collection efficiency (25 ± 10%) of coarser sediment particles (i.e., sand). Rising stage sampling, while robust and cost‐effective, suffered from large amounts of condensation under field conditions (25–35% of sampler volume), due to harsh climatic conditions creating large diurnal temperature differences at the field site, thereby diluting sample concentrations and introducing additional measurement uncertainty. The turbidity logger exhibited a highly variable response when calibrated at each site with physically collected suspended sediment samples (R2 = 0.17–0.83), highlighting that this approach should be used with caution. The modified PASS sampler proved to be a reliable and representative measurement method for gully sediment water quality, however, the time‐integrated nature of the method limits its temporal resolution compared to the other monitoring methods. We recommend monitoring suspended sediment in alluvial gully systems using a combination of complementary techniques (e.g., PASS and RS samplers) to account for the limitations associated with individual methods.

The accurate measurement of suspended sediment (<200 μm) in aquatic environments is essential to understand and effectively manage changes to sediment, nutrient, and contaminant concentrations on both temporal and spatial scales. Commonly used sampling techniques for suspended sediment either lack the ability to accurately measure sediment concentration (e.g., passive sediment samplers) or are too expensive to deploy in sufficient number to provide landscape‐scale information (e.g., automated discrete samplers). Here, we evaluate a time‐integrated suspended sediment sampling technique, the pumped active suspended sediment (PASS) sampler, which collects a sample that can be used for the accurate measurement of time‐weighted average (TWA) suspended sediment concentration and sediment particle size distribution. The sampler was evaluated against an established passive time‐integrated suspended sediment sampling technique (i.e., Phillips sampler) and the standard discrete sampling method (i.e., manual discrete sampling). The PASS sampler collected a sample representative of TWA suspended sediment concentration and particle size distribution of a control sediment under laboratory conditions. Field application of the PASS sampler showed that it collected a representative TWA suspended sediment concentration and particle size distribution during high flow events in an urban stream. The particle size distribution of sediment collected by the PASS and Phillips samplers were comparable and the TWA suspended sediment concentration of the samples collected using the PASS and discrete sampling techniques agreed well, differing by only 4% and 6% for two different high flow events. We should note that the current configuration of the PASS sampler does not provide a flow‐weighted measurement and, therefore, is not suitable for the determination of sediment loads. The PASS sampler is a simple, inexpensive, and robust in situ sampling technique for the accurate measurement of TWA suspended sediment concentration and particle size distribution.

There is considerable interest in applying omics techniques, which have proven extremely valuable for laboratory-based toxicology studies, towards field-scale ecotoxicology and environmental monitoring. Concerns that confounding factors in natural ecosystems may exacerbate variability in omics datasets must be addressed to validate the transition from laboratory to field. This study explores how temporal variability related to seasonal and climatic trends influence qualitative and quantitative metabolomics outcomes, in fish from reference and metal(loid)-polluted wetlands in Australia. Female mosquitofish (Gambusia holbrooki) were sampled on two separate occasions, from a rehabilitated tailings wetland at the site of historic antimony (Sb) processing and a reference wetland with comparable water quality. The first sampling coincided with greater monthly rainfall and colder water temperature, whereas the second sampling was drier and water was warmer. Despite temporal changes and associated differences in metal(loid) concentrations, site differences in metabolite profiles were qualitatively very similar between sampling events. However, quantitative differences were observed, with a greater number of significantly altered metabolites identified during the second sampling event, which coincided with greater metal(loid) concentrations in both water and fish. The majority of identified metabolites were elevated in fish from the contaminated wetland, but with notable decreases in several metabolites that are known to play a role in various aspects of metal(loid) binding, detoxification and excretion. Specifically, decreased aspartate, histidine, myo-inositol, taurine and choline were observed in fish from the contaminated wetland, and may therefore represent a metabolite suite that is broadly indicative of metal toxicity. Quantitative differences between sampling events are suggestive of a dose-response relationship observable at the cellular level which, if harnessed, may be useful for assigning levels of concern based on the degree of change in a multi-parameter set of metabolite biomarkers.